lte_rrm.pdf

Communication Networks

University of Bremen

Prof. Dr. rer. nat. habil. C. Grg

Master Thesis

LTE-Advanced: Radio Access Network

Resource Management

of

Yangyang Dong

Matriculation Number: 2462710

Bremen, June 1, 2013

Supervised by:

Prof. Dr. rer. nat. habil. Carmelita Grg

Dr. -Ing. Xi Li

Dr. -Ing. Yasir Zaki

Safdar Nawaz Khan Marwat, M. Sc.

This publication is meant for internal use only. All rights reserved. No liabilities with

respect to its content are accepted. No part of it may be reproduced, stored in a retrieval

system, or transmitted, in any form or by any means, electronic, mechanical, photocopying,

recording, or otherwise, without the prior written permission of the publisher.

I assure, that this work has been done solely by me without any further help from others

except for the ocal support by the Chair of Communication Networks. The literature

used is listed completely in the bibliography.

Bremen, June 1, 2013

(Yangyang Dong)

Acknowledgements

This thesis has been carried out in the department of Communication Networks (ComNets)

at University of Bremen, Germany, under the supervision of Prof. Dr. rer. nat. habil.

Carmelita Grg. This work is the last assignment during my pursuit of a Master of Science

(M.Sc.) degree in Communication and Information Technology.

Upon the completion of my master thesis, I would like to thank Prof. Dr. Carmelita Grg

for her opportune advice on the research direction and support during every stage of my

work. I am sincerely grateful to my supervisor Safdar Nawaz Khan Marwat, who motivated

and helped me throughout my thesis. I would also give my thanks to Dr. Yasir Zaki and

Dr. Xi Li, who gave me valuable advice on the thesis direction and helped me whenever

I asked. I also appreciate the help from the other researchers of the Communication

Networks department. In addition, I would also express my gratitude to my friends for

giving me a happy and wonderful life in Bremen. Finally, special thanks to my parents

and my brother, who give me unconditional love, patience and support.

Yangyang Dong

Bremen, 05. 2013

MASTER THESIS

2 Yangyang Dong

Abstract

The ongoing development of mobile devices and their applications increases the require-

ments for high data rates and large capacity of the wireless communication networks

rapidly. The LTE (Long Term Evolution) system provides the mobile users with a good

throughput and a low latency. In order to meet the requirements of the future mobile data

trac, the 3GPP (3rd Generation Partnership Project) has introduced advanced features

to the LTE system, such as the Carrier Aggregation (CA), extension of the uplink multiple

access, enhanced MIMO (Multiple Input Multiple Output), and the Relay Nodes (RN).

The enhanced system is known as the LTE-Advanced (LTE-A) system.

This thesis intends to investigate the uplink Radio Access Network (RAN) resource man-

agement in LTE-Advanced. It covers three main areas: the Component Carrier Selection

(CCS), the Power Control (PC) for the uplink, and the radio resource scheduling. The

CCS aims at selecting a proper number of carriers for the mobile terminals; the PC adjusts

the uplink transmit Power Spectral Density (PSD); and the scheduling algorithm allocates

radio resources to the mobile terminals according to their channel conditions and Quality

of Service (QoS) requirements.

Literature survey reveals that the CCS is a relatively newer topic with little work done on

it. However, the PC for macrocell scenarios has been covered in several research articles

and papers. Similarly, several scheduling algorithms have been proposed for LTE and LTE-

A downlink, whereas the scheduling methods for LTE-A uplink along with the advanced

recent features are very rare.

In this thesis, a CCS algorithm depending on the path loss and the slow fading during

propagation of the radio signals has been developed; based on the channel conditions and

the QoS requirements of the users, a Channel and QoS Aware (CQA) uplink scheduler has

been designed, which works in a decoupled time and frequency domain. The implementa-

tion and simulation of the proposed schemes are performed using the OPNET Modeler

1

.

In order to allocate radio resources in compliance with the uplink PC, the scheduling al-

gorithms consider the PSD of the terminals determined by the PC schemes. Two PC

algorithms have been implemented and compared in terms of throughput performance in

this work.

The results illustrate that the proposed CCS algorithm provides a good QoS performance

and overall throughput. One of the implemented PC algorithms provides better application

experiences. The designed CQA scheduler supports a relatively high overall throughput

while guaranteeing the QoS requirements of dierent applications. In addition, it grants

some level of fairness among the users.

1http://www.opnet.com/

Kurzfassung

Die stndige Entwicklung von mobilen Endgerten und deren Anwendungen steigert auch

die Nachfrage nach hohen Datenraten und groer Kapazitt mobiler Netzwerke. Das LTE

(Long Term Evolution) System bietet Nutzern einen hohen Datendurchsatz und geringen

Latenzzeiten. Um jedoch auch in Zukunft den steigenden Anforderungen des Datenver-

kehrs gerecht zu werden, hat das 3GPP (3rd Generation Partnership Project) dem LTE

System fortschrittliche Funktionen hinzugefgt. Dies umfasst unter anderem die Carrier

Aggregation (CA), die Erweiterung des Uplink Multiple Access, die verbesserte Nutzung

von MIMO (Multiple Input Multiple Output) und die Untersttzung von Relay Nodes

(RN). Das verbesserte System ist als LTE-Advanced (LTE-A) bekannt.

Diese Arbeit hat das Ziel, das Uplink Ressourcen Management des Radio Access Network

(RAN) in LTE-Advanced zu untersuchen. Sie beinhaltet drei Abschnitte: die Component

Carrier Selection (CCS), die Uplink Power Control (PC) und die Allokierung von Kanal-

kapazitten. Die CCS sucht eine angemessene Anzahl von Komponententrger fr mobile

Endgerte aus; die PC passt die spektrale Leistungsdichte der Uplink bertragung (Power

Spectrum Density - PSD) an; und der Scheduling-Algorithmus weist den Endgerten -

entsprechend ihren Kanalbedingungen und den Anforderungen der Dienstgte (Quality of

Service - QoS) - Kanalkapazitten zu.

Ein Studium der Fachliteratur zeigt, dass CCS ein junges und noch relativ unerforschtes

Thema ist. PC fr Makrozellen Szenarios wurde dagegen bereits in einigen Verentli-

chungen behandelt. Weiterhin wurden schon mehrere Scheduling-Algorithmen fr LTE

und LTE-A Downlink entworfen. Scheduling-Algorithmen fr LTE-A Uplink, die die fort-

schrittlichen neuen Funktionen bercksichtigen, sind dagegen ausgesprochen selten.

In dieser Arbeit wird ein CCS Algorithmus entwickelt, der von Pfadverlusten und dem

Slow-Fading zwischen dem Endgert und der Basisstation abhngt. Basierend auf den

Kanalbedingungen und den QoS Anforderungen der Nutzer wurde ein Kanal- und QoS-

bewusster (CQA) Uplink Scheduler entwickelt welcher in einem entkoppelten Zeit- und

Frequenzbereich arbeitet. Die Umsetzung und Simulation der vorgeschlagenen Schemata

wurde mit dem OPNET Modeler

2

durchgefhrt. Um die Kanalkapazitten in berein-

stimmung mit dem Uplink PC zuzuweisen, bercksichtigen die Scheduling-Algorithmen

die PSD der Endgerte, die von den PC Schemata bestimmt werden. In dieser Arbeit wur-

den zwei PC Algorithmen eingesetzt und hinsichtlich ihres Datensatzverhaltens verglichen.

Die Ergebnisse zeigen, dass der vorgeschlagene CCS Algorithmus insgesamt gesehen eine

gute Leistung zeigt, was QoS und Datensatz betrit. Einer der beiden eingesetzten Al-

gorithmen weist bessere Eigenschaften beim Einsatz auf. Der entworfene CQA Scheduler

untersttzt einen relativ hohen Datendurchlauf bei gleichzeitiger Erfllung der QoS Anfor-

derungen verschiedener Anwendungen. Zustzlich sichert er ein gewisses Ma an Fairness

zwischen den Nutzern.

2http://www.opnet.com/

Contents

Acknowledgements 1

Abstract 3

Kurzfassung 4

1 Introduction 9

1.1 LTE to LTE-Advanced: Problem Statement . . . . . . . . . . . . . . . . . . 9

1.2 State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

1.3 Thesis Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

1.4 Thesis Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2 New Functionalities of LTE-Advanced 13

2.1 Network Architecture: Evolved Packet System (EPS) . . . . . . . . . . . . . 13

2.1.1 Evolved Universal Terrestrial Radio Access Network (E-UTRAN) . . 13

2.1.2 Protocol Stack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.1.3 Evolved Packet Core (EPC) . . . . . . . . . . . . . . . . . . . . . . . 15

2.2 Carrier Aggregation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2.2.1 Component Carrier Aggregation . . . . . . . . . . . . . . . . . . . . 16

2.2.2 Serving Cell and Component Carrier . . . . . . . . . . . . . . . . . . 18

2.3 Extension of Uplink Multiple Access . . . . . . . . . . . . . . . . . . . . . . 19

2.4 Coordinated Multi-Point Transmission/Reception (CoMP) . . . . . . . . . . 20

2.4.1 Downlink Coordinated Multi-Point Transmission . . . . . . . . . . . 21

2.4.2 Uplink Coordinated Multi-Point Reception . . . . . . . . . . . . . . 22

2.5 Enhanced Use of MIMO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

2.6 Relay Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

3 Radio Channel 25

MASTER THESIS Contents

3.1 Channel Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

3.1.1 Path Loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

3.1.1.1 Free Space Path Loss Model . . . . . . . . . . . . . . . . . 26

3.1.1.2 Okumura Model . . . . . . . . . . . . . . . . . . . . . . . . 26

3.1.1.3 Hata Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3.1.1.4 ETSI Model for LTE Systems . . . . . . . . . . . . . . . . . 27

3.1.2 Slow Fading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3.1.3 Fast Fading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.1.3.1 Jakes-like Method of Complex Gain Generation . . . . . . . 31

3.1.4 Link Budget . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

3.2 Link-to-System Level Mapping . . . . . . . . . . . . . . . . . . . . . . . . . 33

4 RRM in a Multi-CC LTE-A System 35

4.1 Admission Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

4.1.1 Common Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

4.2 Component Carrier Selection . . . . . . . . . . . . . . . . . . . . . . . . . . 37

4.3 Uplink Signalling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.3.1 Channel State Information (CSI) . . . . . . . . . . . . . . . . . . . . 38

4.3.2 Buer Status Report (BSR) . . . . . . . . . . . . . . . . . . . . . . . 38

4.3.3 Power Headroom Report (PHR) . . . . . . . . . . . . . . . . . . . . 39

4.4 Resource Allocation and Scheduling . . . . . . . . . . . . . . . . . . . . . . . 40

4.4.1 Bearer Classication . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

4.4.2 Time Domain Scheduling . . . . . . . . . . . . . . . . . . . . . . . . 42

4.4.2.1 Blind Equal Throughput Scheduler . . . . . . . . . . . . . . 42

4.4.2.2 Maximum Throughput Scheduler . . . . . . . . . . . . . . . 43

4.4.2.3 Proportionally Fair Scheduler . . . . . . . . . . . . . . . . . 43

4.4.2.4 Bandwidth and QoS Aware Scheduler . . . . . . . . . . . . 43

4.4.3 Frequency Domain Scheduling . . . . . . . . . . . . . . . . . . . . . . 44

6 Yangyang Dong


4.4.3.1 Maximum Throughput . . . . . . . . . . . . . . . . . . . . 44

4.4.3.2 Proportionally Fair . . . . . . . . . . . . . . . . . . . . . . . 45

4.5 Uplink Power Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

5 Simulation Results and Analysis 51

5.1 The OPNET Modeler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

5.2 Scenario Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

5.3 Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

5.4 Component Carrier Selection Analysis . . . . . . . . . . . . . . . . . . . . . 58

5.5 Power Control Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

5.6 Channel and QoS Aware MAC Scheduler Analysis . . . . . . . . . . . . . . 62

5.6.1 Channel Awareness Analysis . . . . . . . . . . . . . . . . . . . . . . . 62

5.6.2 QoS Awareness Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 62

5.6.2.1 CQA vs. BET vs. MaxT vs. PF . . . . . . . . . . . . . . . 63

5.6.2.2 QoS Weight vs. no-QoS Weight . . . . . . . . . . . . . . . . 64

5.6.2.3 Mixed Trac . . . . . . . . . . . . . . . . . . . . . . . . . . 65

5.6.3 Fairness Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

6 Conclusions and Outlook 69

6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

6.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Appendix A E-UTRAN Operating Bands 73

Appendix B E-UTRAN Channel Bandwidths 75

Appendix C Intra-band Contiguous CA Operating Bands 77

Appendix D Inter Band CA Operating Bands 79

Appendix E Transport Block Size (TBS) Table 81

Yangyang Dong 7


List of Figures 83

List of Tables 85

List of Abbreviations 87

Bibliography 89

Index 93

8 Yangyang Dong

1 Introduction

With the development of the highly advanced mobile devices, the demands for higher data

rates and better QoS increased rapidly. Therefore, the 3GPP has specied new standards

for the mobile communications based on the GSM (Global System for Mobile Communi-

cations)/EDGE (Enhanced Data rates for GSM Evolution) and UMTS (Universal Mobile

Telecommunications System)/HSPA (High Speed Packet Access) network technologies in

2004: LTE and the System Architecture Evolution (SAE), which dene the radio access

network and the core network (CN) of the system, respectively. The SAE is called the

Evolved Packet Core (EPC), and LTE, together with the SAE, are known as the Evolved

Packet System (EPS). The EPS is discussed in detail in the subsequent chapters. LTE sup-

ports high data rates of up to 300 Mbit/s in the downlink (DL) and 75 Mbit/s in the uplink

(UL). However, this does not meet the IMT-Advanced (International Mobile Telecommuni-

cations - Advanced) or the 4G requirements such as a data rate up to 1 Gbit/s, which was

set by the ITU-R (International Telecommunication Union Radiocommunication Sector)

organization. As a result, the 3GPP Release 10 documents feature new technologies aiming

at improving the performance in LTE-Advanced. A brief illustration of the evolution of

the mobile networks can be found in the following gure.

!"#!$"%

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Figure 1.1: Evolution of Mobile Networks

1.1 LTE to LTE-Advanced: Problem Statement

The standards for LTE are specied in the 3GPP Release 8 document series, with some

enhancements in Release 9. The world's rst LTE network was deployed in the two Scandi-

navian cities Stockholm and Oslo in 2009. As an enhancement to LTE, LTE-Advanced was

presented as a candidate 4G system to the ITU-T (International Telecommunication Union

Telecommunication Standardization Sector) in 2009, and was nalized by the 3GPP in Re-

lease 10 in March, 2011. It is expected to keep backward compatibility with LTE, which

means that a LTE-A network can be deployed in the frequency bands occupied by the LTE

system and would thus be able to utilize most of the LTE technologies. Meanwhile, the

LTE terminals can also work in the LTE-A system.

In order to achieve a better performance such as a higher data rate and a better throughput,

LTE-A has some new features in comparison to LTE. The main features include the Carrier

Aggregation, the extension of the uplink multiple access, the enhanced MIMO, and the

MASTER THESIS 1. Introduction

Relay Nodes. This thesis focuses on the Carrier Aggregation and the extension of the uplink

multiple access. The former one aggregates several bands to get a wider bandwidth for data

transmission; the latter one enables non-contiguous radio resource allocation. However, a

wider bandwidth does not always ensure better performance - terminals lacking sucient

power, for example, would not benet from it. Therefore, it is essential to determine

whether the frequency bands should be aggregated or not, which is why a component

carrier selection algorithm is needed. Besides, how to schedule one or multiple bands

to various mobile terminals is also a problem to be solved, thus an ecient scheduler is

required to allocate bandwidth to dierent users to fulll their requirements for dierent

applications. Furthermore, since this thesis focuses on the uplink, power constraint is a big

issue for the mobile terminals. A power control scheme can be used to adjust the users'

transmit power.

1.2 State of the Art

Despite the relative novelty of the topic, a substantial amount of literature is already in

existence. The 3GPP specications [1], [2], and [3] are used as the foundation of this

thesis. A considerable amount of scientic material has to be reviewed to understand the

new features in LTE-A. For example, [4], [5], [6], [7], and [8] give details about the evolution

from LTE to LTE-A. [9] and [10] introduce various features of carrier aggregation, and [11]

gives an overview of the Coordinated Multi-Point transmission/reception (CoMP) used in

LTE-A.

Since LTE-A is a new standard, the Radio Resource Management (RRM) for the uplink

has not been studied widely. Regarding the component carrier selection, [12] proposes

two ways of deploying the carriers: the Round Robin Balancing and the Mobile Hashing

Balancing. The former tries to distribute loads equally to all the carriers while the latter

maps the uniformly distributed output hash values directly on the Component Carrier

(CC) indices [13] to provide a balanced load across all the CCs in the long term. However,

this method does not give a solution for the LTE-A system where the users are able to use

more than one carrier. [14] proposes a CC selection method based on the path loss of the

users, assigning multiple carriers on the users with a lower path loss. This method fullls

the need to select carriers for the LTE-A users. However, it assumes that all the users are

stationary, and the slow fading has not been taken into account.

Admission Control (AC) has also been studied in several research articles and papers. [15]

proposes a reference AC algorithm, which admits a user if its required capacity can be

fullled while the capacity of the already existing calls is not inuenced. [16] suggests an

admission algorithm based on the Fractional Power Control (FPC), which can be used for

the uplink.

The power control for the uplink has been investigated during this thesis. [1] denes the

power control for the uplink, and suggests that FPC can be utilized for compensating

the path loss during propagation. The FPC is based on the path loss to the serving cell.

[17] investigates the performance of the uplink FPC in LTE. [18] and [19] propose a new

algorithm based on the interference to the neighboring cells as well as the path loss to

the serving cell. [20] compares two dierent approaches for the PC: the Open Loop Power

Control (OLPC) and the Closed Loop Power Control (CLPC). [21] also investigates the

CLPC in the LTE system. [22] aims at improving the cell edge throughput in the LTE

10 Yangyang Dong

MASTER THESIS 1.3. Thesis Contribution

system using a combined power control scheme.

Recent research on the scheduling of the radio resources mainly focuses on LTE. For LTE

downlink, [23] proposes an optimized service aware scheduler, which dierentiates users

with various QoS classes. [24] also brings forward a scheduling method that fullls dierent

QoS requirements. For LTE uplink, [25] suggests a bandwidth and QoS aware scheduler,

which takes both the frequency bandwidth and the QoS into consideration during schedul-

ing. In addition, it utilizes resource chunks since there is a contiguous resource allocation

constraint. For LTE-A uplink, [16] uses two ways of scheduling: one is the Proportional

Fair (PF) method, and the other is the GBR (Guaranteed Bit Rate) aware method. [26]

presents a cross-carrier scheduling method in addition to the per-carrier scheduling method,

enabling scheduling on several carriers. [27] proposes a subcarrier allocation method which

assumes equal power allocation among all the subcarriers. [28] proposes a more complete

resource management method for the LTE-A system, which includes carrier selection and

radio resource scheduling.

1.3 Thesis Contribution

For this thesis, a LTE-A uplink radio resource scheduler has been designed, implemented,

and analyzed in regard to its performance. The scheduler is based on the advanced features

such as the CCS and the PC. The implementation and the performance analysis has been

achieved using the OPNET Modeler [29].

Firstly, a CCS algorithm based on [14] is implemented, which takes both the path loss

and the slow fading into consideration to decide the number of carriers to be assigned

to a user. Furthermore, a mobility model has been adopted, which facilitates the CCS

decisions for the users moving with various velocities. A Channel and QoS Aware (CQA)

scheduling method has been designed, which aims at guaranteeing the QoS requirements

and providing a reasonably good throughput, as well as providing a certain level of fairness.

The scheduler uses a decoupled time and frequency domain structure. All the radio bearers

1

are classied into bearer lists in the Bearer Classication phase, and their Time Domain

Packet Scheduling (TDPS) metrics are calculated. Afterwards, bearers are sorted within

the lists according to their TDPS metrics by the TDPS scheduler. Finally, the bearers at

the top of the TDPS bearer sorted list get into the Frequency Domain Packet Scheduling

(FDPS) phase, where radio resources are allocated to the bearers. PC is also implemented

to estimate the maximum of user transmit power that is allowed, thus determining the

maximum radio resources a user can get in this phase. Both the FPC and the IBPC have

been implemented, in order to compare which algorithm performs better.

1.4 Thesis Overview

The rest of the thesis is organized as follows: Chapter 2 gives an overview of the EPS in the

LTE-A system. Furthermore, new functionalities of LTE-A such as Carrier Aggregation,

CoMP, and Relay Nodes are also introduced. Chapter 3 gives a description of the radio

channel model utilized in this thesis, including the path loss, the slow fading and the

1radio bearers belong to EPS bearers, which are a data structure that uniquely identies a trac ow

between the user and the transport network

Yangyang Dong 11

MASTER THESIS 1. Introduction

fast fading models. Afterwards, the link-to-system mapping is presented. In the next

chapter, the radio access network resource management in the LTE-A system with multiple

carriers is discussed in detail, including fundamental concepts and realization methods.

This part includes the AC, the CCS, the scheduling, and the PC schemes. Chapter 5

shows some simulation results, and a detailed analysis of these results. The nal chapter

draws conclusions and provides an outlook for possible further research.

12 Yangyang Dong

2 New Functionalities of LTE-Advanced

The rst part of this chapter provides an overview of the network architecture that supports

both the LTE and the LTE-A systems. Then the main dierences between LTE and LTE-A

are highlighted, which include Carrier Aggregation, Extension of Uplink Multiple Access,

CoMP, enhanced use of MIMO, and support for Relay Nodes. This thesis focuses mainly

on the rst two aspects.

2.1 Network Architecture: Evolved Packet System (EPS)

The EPS architecture is the basis for both the LTE and the LTE-A networks. It has

two parts: the Evolved Universal Terrestrial Radio Access Network (E-UTRAN) and the

Evolved Packet Core (EPC), which correspond to the radio access network and the core

network, respectively. For LTE-A, both the air interface and the E-UTRAN are enhanced,

while the EPC remains unchanged from the LTE version. Figure 2.1 shows the EPS for the

LTE-Advanced system. Further details about the nodes and functionalities are provided

in the following subsections.

Figure 2.1: Evolved Packet System (EPS) of LTE-A

2.1.1 Evolved Universal Terrestrial Radio Access Network (E-UTRAN)

The eNodeB (E-UTRAN Node B) is the most important node in the E-UTRAN, fullling

tasks similar to those performed by the NodeB and RNC (Radio Network Controller)

MASTER THESIS 2. New Functionalities of LTE-Advanced

together in the UMTS radio access network. According to [30], the eNodeB manages

all the radio interface related functions - such as admission control and radio resource

scheduling - and provides the air interface with user plane and control plane protocols

towards the UE (User Equipment). One eNodeB serves one or several cells, and two

eNodeBs are connected via the X2 interface. The eNodeB and the UEs are connected via

the Uu interface. In LTE-Advanced, according to [2], Relay Nodes are utilized for network

performance enhancement, for example, to obtain wider coverage, higher data rates, and

better QoS performance and fairness among users. The RN is connected to the Donor

eNodeB via the radio air interface Un, which is modied from the air interface Uu. Donor

eNodeB not only serves its own UEs in its serving cell, but also shares the radio resources

with the RNs.

2.1.2 Protocol Stack

This section describes the user and control plane protocols towards the UEs provided by

the eNodeB. Figure 2.2 gives the protocol stack of EPS. The Access Stratum (AS) shows

the protocol stack of the radio access network, i.e., the E-UTRAN. In the user plane,

the protocols include the Packet Data Convergence Protocol (PDCP) layer, the Radio

Link Control (RLC) layer, the Medium Access Control (MAC) layer, and the Physical

layer (PHY) protocols. The control plane also consists of these protocols, as well as the

Radio Resource Control (RRC) protocol, which handles control plane signalling between

the E-UTRAN and the UEs.

Figure 2.2: Protocol Stack of LTE-Advanced

According to [7], the functionalities of dierent layers are given as follows:

14 Yangyang Dong

MASTER THESIS 2.1. Network Architecture: Evolved Packet System (EPS)

RRC (Radio Resource Control): The RRC only exists in the control plane, whichmanages the control plane signalling between the eNodeB and UEs. It establishes,

maintains and releases the RRC connections and signalling/data radio bearers. It

also manages security and mobility functions.

PDCP (Packet Data Convergence Protocol): The PDCP layer deals with in-sequence delivery and retransmission, ciphering and duplicate detection. It also man-

ages header compression in the user plane, and integrity protection in the control

plane.

RLC (Radio Link Control): The RLC layer supports transmission of the upperlayer data with three dierent modes: AM (Acknowledged Mode), UM (Unacknowl-

edged Mode), and TM (Transparent Mode). It also segments data according to the

size of the transport block and re-segments it in case of retransmission. Furthermore,

it can correct errors through Automatic Repeat reQuest (ARQ).

MAC (Medium Access Control): The MAC layer mainly handles scheduling,and error correction through HARQ (Hybrid Automatic Repeat reQuest), etc.

PHY (Physical Layer): The PHY layer is mainly for coding/decoding, transmis-sion/reception, modulation and so on.

2.1.3 Evolved Packet Core (EPC)

LTE-Advanced uses the core network architecture of LTE - the System Architecture Evo-

lution (SAE). The SAE is a at, all-IP network which can be accessed by both, the 3GPP

legacy systems (e.g. GSM, UMTS, HSPA) and non-3GPP systems (e.g. WiMAX, WLAN).

As is shown in Figure 2.3, the SAE allows handovers within and among dierent system

types, which is a feature highly attractive for network operators.

!

mgmt: media gateway mobile terminal IMS: IP Multimedia Subsystem

"#

Figure 2.3: System Architecture Evolution (SAE)

In Figure 2.2, the Non-Access Stratum (NAS) represents the protocol stack of the core

network. The functionalities of dierent layers dened by 3GPP can be described as

follows:

Yangyang Dong 15


MME (Mobility Management Entity): The MME is the main control node,which is responsible for mobility and session management, bearer activation/deactivation,

etc.

S-GW (Serving Gateway): The S-GW is used to route and forward data packets.In addition, it is also responsible for the user plane handovers and mobility between

LTE/LTE-A and the other 3GPP technologies.

2.2 Carrier Aggregation

In order to get higher data rate, a wider bandwidth is required for data transmission.

According to the 3GPP specications [1], the LTE-Advanced system is able to aggregate

two or more CCs to obtain a wider transmission bandwidth. This is dened as Carrier

Aggregation (CA). The current 3GPP standards allow for up to ve carriers.

2.2.1 Component Carrier Aggregation

LTE terminals can only receive/transmit on a single component carrier. While LTE-A

terminals, according to the specications, are able to receive or transmit data on one or

multiple component carriers simultaneously, due to the reason that the LTE-A terminals

have the capabilities to receive and/or transmit with carrier aggregation. Each component

carrier has a limit number of 110 Physical Resource Blocks (PRBs) in the frequency domain,

which is supposed to be compatible with the LTE Rel. 8 technologies. The allowed channel

bandwidths for each component carrier are 1.4 MHz, 3.0 MHz, 5 MHz, 10 MHz, 15 MHz and

20 MHz, which are the bandwidths utilized in LTE. The number of PRBs in E-UTRAN for

dierent bandwidths can be found in Table 2.1 [31]. The same specication states that it is

possible to congure a UE to aggregate a dierent number of CCs or dierent bandwidths

in the uplink and the downlink.

LTE Spectrum(MHz) 1.4 3 5 10 15 20

Number of PRBs 6 15 25 50 75 100

Table 2.1: Number of PRBs in E-UTRA Channel Bandwidth

Figure 2.4 shows an illustration of the uplink carrier aggregation. The R8/R9 users, i.e.,

the LTE users, can only be allocated with one carrier; while the R10 users, i.e., LTE-A

users, can use multiple component carriers.

The 3GPP has specied the operating bands for E-UTRAN, which can be found in Ap-

pendix A. For each band, the allowed transmission bandwidths are also dened by the

3GPP, which are given in Appendix B. In addition to the spectrum bands already speci-

ed for the LTE users, the LTE-A users are able to utilize more bands [3]:

450 - 470 MHz band (identied in WRC-07 to be used globally for IMT systems); 698 - 862 MHz band (identied in WRC-07 to be used in Region 2 and nine countriesof Region 3

1

);

1

Region 1: Europe, Africa, the Middle East west of the Persian Gulf including Iraq, the former Soviet

16 Yangyang Dong

MASTER THESIS 2.2. Carrier Aggregation

!"

Figure 2.4: Carrier Aggregation

790 - 862 MHz band (identied in WRC-07 to be used in Regions 1 and 3); 2.3 - 2.4 GHz band (identied in WRC-07 to be used globally for IMT systems); 3.4 - 4.2 GHz band (3.4- 3.6 GHz identied in WRC-07 to be used in a large numberof countries);

4.4 - 4.99 GHz band.

Both contiguous and non-contiguous component carrier aggregation are supported for the

uplink and the downlink. According to the 3GPP specications, the carrier aggregation in

the LTE-A system can be classied into three types: the intra-band contiguous aggregation,

the intra-band non-contiguous aggregation and the inter-band non-contiguous aggregation.

The operating bands of intra-band contiguous CA and inter-band CA are dened by the

3GPP, which can be found in Appendix C and D, respectively. Intra-band contiguous

carrier aggregation is the simplest form, where multiple contiguous component carriers

within the same operating frequency band are aggregated. Once aggregated, the channel

can be considered to be an enlarged channel by the mobile terminals. However, this might

not always be possible, since not all bands are available to the LTE-Advanced users; even

if contiguous frequency bands are available, they might do not have enough bandwidth to

support the LTE-A users. This leads to the non-contiguous carrier aggregation. Within

the same frequency band, the aggregation can also be non-contiguous, when the bands that

are to be aggregated are separated by a frequency gap. Another non-contiguous carrier

allocation method is the inter-band aggregation, meaning that the component carriers

belong to dierent operating frequency bands. Figure 2.5 shows the three dierent CA

types.

Union and Mongolia;

Region 2: Americas, Greenland, and some of the eastern Pacic Islands;

Region 3: most of non-former-Soviet-Union Asia, east of and including Iran, and most of Oceania.

Yangyang Dong 17


Figure 2.5: Carrier Aggregation Types

2.2.2 Serving Cell and Component Carrier

In the LTE system, the UE has only one RRC connection with the eNodeB, which handles

the control signalling between the eNodeB and the UEs. While for the LTE-Advanced,

according to [9], there are several serving cells due to carrier aggregation, with one cor-

responding to each component carrier. Initially, a RRC connection is established with a

single CC, using the same RRC establishment procedure that was specied for LTE. The

component carrier is called the Primary Component Carrier (DL and UL PCCs). The

UE receives PDCCH (Physical Downlink Control Channel) and PDSCH (Physical Down-

link Shared Channel) and transmits PUCCH (Physical Uplink Control Channel), PUSCH

(Physical Uplink Shared Channel), and Physical Random Access Channel (PRACH) on

the Primary CC. Further CCs can then be congured from the eNodeB, which are called

Secondary Component Carriers (SCC), on which no PUCCH or PRACH transmissions are

made. The SCCs are added and removed as required, while the PCC is only changed at

handover. For UEs using the same set of CCs, dierent PCCs are possible. As depicted in

Figure 2.6, the PCC serves the Primary Serving Cell (PSC), while the SCC serves the Sec-

ondary Serving Cell (SSC). The coverage of the serving cells are not necessarily the same,

resulting from dierent component carrier frequencies and power planning. Furthermore,

in case of inter-band carrier aggregation, the component carriers will probably experience

dierent path loss, which increases with increasing frequency.

It is also pointed out in [9] that the introduction of carrier aggregation mainly has an

impact on the MAC and the physical layer. For example, the MAC layer should be able to

handle scheduling on multiple CCs and HARQ ACK/NACK (Acknowledgement/Negative

Acknowledgement) per CC. In addition, some new RRC controlling signals are introduced,

for example new RRC messages to handle the SCCs. In order to uphold backward compat-

ibility with the LTE system, there should be as few changes in the protocols as possible.

18 Yangyang Dong

MASTER THESIS 2.3. Extension of Uplink Multiple Access

Figure 2.6: Serving Cell: Primary Serving Cell and Secondary Serving Cell

2.3 Extension of Uplink Multiple Access

In line with [32], Orthogonal Frequency Division Multiplexing Access (OFDMA) is used

in the LTE downlink, providing wide transmission bandwidth while still staying robust to

frequency selectivity of radio channels. The uplink is based on Single Carrier - Frequency

Division Multiplexing Access (SC-FDMA) as the transmission scheme. According to [33],

OFDMA is also utilized in LTE-Advanced downlink for the multi-carrier transmission.

However, the OFDMA modulation has a drawback: variation in the instantaneous power

of the transmitted signal is very large. In other words, the Peak-to-Average-Power-Ratio

(PAPR) of OFDMA is very high. This is a critical issue for the uplink, since the mobile

terminals should ideally have low consumption. On the other hand, the SC-FDMA used in

LTE has a constraint that only allows adjacent radio resource allocation in frequency do-

main. For LTE-A, contiguous or non-contiguous bands are aggregated to provide a wider

bandwidth. Therefore, the LTE-Advanced uplink utilizes a single-carrier transmission

scheme using DFT-Spread OFDM (DFTS-OFDM)

2

, which allows non-contiguous resource

allocation as well as adjacent allocation. DFTS-OFDM overcomes the disadvantages of

the OFDMA and the SC-FDMA: it has a relatively small variation in the instantaneous

transmit power, leading to a lower PAPR compared to OFDMA; it also breaks the con-

straint of contiguous resource allocation, resulting in a higher scheduling exibility than

the SC-FDMA. The basic principle of DFTS-OFDM transmission is illustrated in Figure

2.7.

In DFTS-OFDM, at the transmitter side, M modulation symbols are generated from aSeries-to-Parallel transformation. Afterwards, these M symbols are applied to a size-M

2Discrete Fourier Transform Spread OFDM: a method for achieving single carrier transmission in OFDM

by incorporating DFT in the pre-stage of the Inverse Fast Fourier Transform (IFFT)

Yangyang Dong 19


!

"#

$

!

%

!

$

&

'!

'!

('

('

)

Figure 2.7: DFTS-OFDM in LTE-Advanced Uplink

DFT. The output of DFT is put to a size-N (N > M) Inverse DFT (IDFT), where theother (NM) inputs of the IDFT are set to zero. This method is also called the distributedDFTS-OFDM [34]. Afterwards, a Parallel-to-Series transformation is conducted; and the

outputs are inserted with a cyclic prex. After converting digital signals to analog, the

signals are transmitted via the radio channel. At the receiver side, the inverse procedures

are performed to get the transmitted data.

In the light of [33], within one component carrier DFTS-OFDM is able to support both

contiguous and non-contiguous data transmission, as is depicted in Figure 2.8 (a). Ev-

ery component carrier has PUCCH, carrying the controlling signals such as the HARQ

ACK/NACK signals, Scheduling Request signals and Channel Quality Indicator (CQI)

signals, which ensures backwards compatibility with LTE. PUSCH is used to transmit

data of mobile terminals. Among several dierent component carriers, N-times clustered

DFTS-OFDM is used (Figure 2.8 (b)). LTE-Advanced users can use multiple (N as showedin the gure) component carriers for data transmission. Within these component carriers,

contiguous or non-contiguous bands are supported alike. In addition, every component

carrier can be used by a LTE user, conducting parallel LTE transmission.

2.4 Coordinated Multi-Point Transmission/Reception (CoMP)

This section gives an introduction to the Coordinated Multi-point (CoMP) transmis-

sion/reception, which is specied in the 3GPP release 9 [1]. Future mobile networks should

be able to serve a large amount of mobile terminals simultaneously. Traditionally, each

mobile terminal is assigned to one base station, i.e., the eNodeB, according to the criteria

such as signal strength and terminal distance to the base stations. Ideally, there should be

no interference within the same cell, thanks to the OFDM scheme which makes sure the

signals are orthogonal to one another. However, signals from the other base stations can

interfere with the mobile terminals in the serving eNodeB. In addition, the user in the serv-

ing eNodeB also causes interference with the users in the other eNodeBs. One approach to

20 Yangyang Dong

MASTER THESIS 2.4. Coordinated Multi-Point Transmission/Reception (CoMP)

(a) Clustered DFTS-OFDM

(b) N-times Clusteres DFTS-OFDM

Figure 2.8: Clustered DFTS-OFDM in LTE-Advanced Uplink

achieve better performance is to reduce interference using CoMP transmission/reception.

In mobile systems with CoMP, multiple geographically distributed antennas cooperate

with each other to improve the user performance. In LTE-Advanced, CoMP is expected

to improve the coverage of high data rates and the cell-edge throughput.

The specications dene CoMP techniques for both the downlink and the uplink. In

downlink, two CoMP categories are considered: Joint Processing (JP) and Coordinated

Scheduling/Beamforming (CS/CB). Their main dierence is that in the former scheme,

data is available at each point in CoMP cooperating set and many eNodeBs simultaneously

transmit data to the same UE, while in the latter scheme data is only available at the

serving eNodeB, and it is the only eNodeB that transmits data to the UE. In uplink, only

one coordinated approach is considered: Joint Reception (JR).

2.4.1 Downlink Coordinated Multi-Point Transmission

As has been pointed out, two downlink CoMP transmission techniques are considered:

Joint Processing and Coordinated Scheduling/Beamforming. As stated in the 3GPP stan-

dards, in Joint Processing data for a particular UE is available at multiple eNodeBs. Two

Yangyang Dong 21


dierent methods are being studied for the JP scheme: Joint Transmission (JT) and Dy-

namic Cell Selection (DCS). In joint transmission, multiple points who have the UE data

simultaneously transmit to the UE. In Dynamic Cell Selection, a fast cell selection approach

is performed and only one of the coordinated points transmits data at a time. Figures 2.9

(a) and 2.9 (b) show JT and DCS, respectively.

(a) Joint Transmission

(b) Dynamic Cell Selection

Figure 2.9: Downlink CoMP: Joint Processing

In Coordinated Scheduling/Beamforming, data is only available at the serving cell, which

transmits data to the UE. However, the UE scheduling/beamforming decisions are made

with coordination among cells. The terminals are provided with knowledge about the exact

coordinated transmission, for instance, from which point the data will be transmitted.

Figure 2.10 illustrates the CS/CB.

Figure 2.10: Coordinated Scheduling/Beamforming (CS/CB)

2.4.2 Uplink Coordinated Multi-Point Reception

Figure 2.11: Joint Reception and Coordinated Scheduling

22 Yangyang Dong

MASTER THESIS 2.5. Enhanced Use of MIMO

In uplink coordinated multi-point reception, signals are received at multiple, geographically

separated points. Coordination is performed among those points. The 3GPP Release 9

species Joint Reception (JR) and/or Coordinated Scheduling (CS), which is shown in

Figure 2.11. 3GPP also emphasizes that the need for extended CP operation in certain

uplink subframes should be further investigated.

2.5 Enhanced Use of MIMO

MIMO is one of the key techniques in current mobile systems, which uses multiple antennas

at both, the transmitter and the receiver sides. It aims at improving the performance, for

example increasing the overall throughput. As dened in 3GPP Release 11 [2], LTE-

Advanced extends the Rel. 8 LTE spatial multiplexing to up to 8 layers in DL and 4 layers

in UL, respectively. Figure 2.12 shows the evolution of MIMO from LTE to LTE-Advanced.

Figure 2.12: Extension of MIMO from LTE to LTE-Advanced

The 3GPP Release 11 species that instead of using up to four layers MIMO in LTE,

LTE-A supports up to eight layers of spatial multiplexing in the downlink. Similarly in

the uplink, LTE-A also extends to four layers of spatial multiplexing, other than only one

layer in LTE. In case of single user spatial multiplexing, up to two transport blocks can be

transmitted from a scheduled UE per uplink component carrier. Each transport block has

its own MCS (Modulation and Coding Scheme).

2.6 Relay Nodes

Relay Nodes are also introduced in 3GPP release 11 [2] to improve the system performance

in LTE-A, for example to improve the coverage and cell-edge throughput. The relay node is

connected to a Donor eNodeB via the Un air interface in the E-UTRAN, which is a modied

version of E-UTRAN Uu interface. The Donor eNodeB not only serves its own UEs, but

also shares radio resources with the relay nodes. Figure 2.13 depicts the functionality of

the relay nodes.

Yangyang Dong 23


Figure 2.13: Relay Node and Donor Cell

With respect to the usage of spectrum, two categories of RN operations are specied in

[2]:

Inband: the eNodeB-RN link shares the carrier frequency with the RN-UE links. Outband: the eNodeB-RN link uses dierent carrier frequency than the relay-UElinks.

For both cases, the LTE users should be able to connect to the Donor Cell. In addition, the

eNodeB-RN link should also be able to operate on the same carrier frequency as DoeNB-UE

links.

24 Yangyang Dong

3 Radio Channel

A radio channel is the medium that carries information from a transmitter to a receiver

in the form of electromagnetic waves. This chapter gives an overview of wireless radio

channels and the channel models which are used in this thesis. In addition, the link budget

of the radio channel and the link to system mapping are introduced.

3.1 Channel Modeling

A channel model is a mathematical representation of the radio channel. A channel can be

modeled by calculating the physical processes which modify the transmitted signals. In

wireless communications the channel has a huge randomness. Therefore, statistical channel

models are required to model the eects of the channel on the transmitted signals. The

following gure illustrates the channel modeling:

Figure 3.1: Channel Model Block Diagram

The wireless transmitted signals are mainly aected by the radio channel in three aspects:

path loss, slow fading and fast fading. Path loss depends on the distance between the

transmitter and the receiver. Slow fading is mainly caused by shadowing eect, when a

large object such as a hill or a large construction is in the propagation path; while fast

fading occurs mainly due to multi-path propagation. Details about the models for these

three aspects are described in the following sections.

3.1.1 Path Loss

Path loss is the power attenuation of the transmitted signal when it propagates from

the transmitter to the receiver. Path loss may be caused by free-space loss, reection,

refraction, diraction, absorption and so on. Assume PTx is the power of the transmittedsignal and PRx is the received power. The path loss can be illustrated as:

PL =PTxPRx(3.1)

Furthermore, it can be expressed in dB as shown in the following formula:

L = 10 logPTxPRx(3.2)

Since each individual wireless path may come across dierent aecting factors, it may not

be able to describe the actual path loss in a single mathematical equation. As a result,

MASTER THESIS 3. Radio Channel

models for dierent types of radio links under various conditions have been developed.

A combination of these models are expected to give accurate path loss estimations. The

Free Space Model, the Okumura Model and the Hata Model are among the most popular

statistical models for path loss calculations.

3.1.1.1 Free Space Path Loss Model

Free space path loss refers to the signal power loss when it propagates through free space.

It is proportional to the square of the distance between the transmitter and receiver, and

the square of the carrier frequency of the radio channel [35].

PL =PTxPRx

=1

GTxGRx(4pifd

c)2

(3.3)

where GTx and GRx are the gain factors of the transmit and receive antennas, respectively;f is the carrier frequency and c is the speed of light in vacuum.

The free space path loss in logarithmic scale is given in the following formula:

L = 10 logPTxPRx

= 20 log4pifd

c 10 logGTxGRx (3.4)

3.1.1.2 Okumura Model

The Okumura Model is also described in [35]. It is an empirical radio propagation model,

which was built using the data collected in Tokyo, Japan in 1960. The data refers to the

path loss measurement at dierent distances from the eNodeB. Therefore, the model is

suitable for cities with densely urban structures but not many tall buildings. Okumura

model is used as the base for many other path loss models. The model is applicable for a

distance between 1 km and 100 km, and a frequency range from 150 MHz to 1920 MHz.

The mobile station antenna height should be between 1 m and 10 m, and base station

antenna height is in the range of 30 m to 1000 m. The empirical Okumura Model in

logarithmic scale can be expressed in the following formula:

L = LF +AMU HMG HBG Gcorrection (3.5)

where LF is the free space path loss and AMU is the median of the path loss additional toLF in urban area. HMG and HBG are the mobile station and base station antenna heightgain factors, respectively. Gcorrection is a correction gain factor due to the environment. Inaddition, Okumura also proposed formulas to calculate the HMG and HBG:

HMG =

{10 log(hM/3), for hM 3 m20 log(hM/3), for 3 m < hM < 10 m(3.6)

HBG = 20 log(hB/200), for 30 m < hB < 1000 m (3.7)

26 Yangyang Dong

MASTER THESIS 3.1. Channel Modeling

where the hM and hB correspond to the mobile station and base station heights, respec-tively.

3.1.1.3 Hata Model

The Hata Model is also given in [35], which is also known as the Okumura-Hata Model

for being a developed version of the Okumura Model. Besides making use of the empirical

information from the Okumura Model, it models the eects of diraction, reection and

scattering eects caused by city structures. Although it is extended from the Okumura

Model, the Hata Model only supports a frequency range of 150 MHz to 1500 MHz. The

mobile station antenna height should be between 1 m and 10 m, and the base station

antenna height is between 30 m and 200 m. The mobile and base station distance should

be in the range of 1 km to 20 km. The Hata Model covers three varieties for transmission

in urban areas, suburban areas and open areas, which can be formulated as follows:

Hata Model for Urban Areas:

Lurban = 69.55 + 26.16 log fc 13.82 log hB CH + (44.9 6.55 log hB) log d (3.8)where fc is the carrier frequency in MHz, d is the distance between the base andmobile stations, CH is a correction factor due to mobile station antenna height, whichdepends on the coverage:

For small or medium sized cities:

CH = 0.8 + (1.1 log fc 0.7)hM 1.56 log fc (3.9) For large cities:

CH =

{8.29 log(1.54hM )

2 1.1, if 150 fc 2003.2 log(11.75hM )

2 4.97, if 200 < fc 1500 (3.10)

Hata Model for Suburban Areas:

Lsuburban = Lurban 2(log fc28

)2 5.4 (3.11) Hata Model for Open Areas:

Lsuburban = Lurban 4.78(log fc)2 + 18.33 log fc 40.94 (3.12)

3.1.1.4 ETSI Model for LTE Systems

Nowadays, the mobile systems operate on a high frequency with the coverage for both small

and large cell sizes. Therefore, neither the Okumura nor the Hata Model is suitable for

the modern mobile networks. Based on the fundamental models such as the Okumura and

the Hata Model, the European Telecommunications Standards Institute (ETSI) proposed

several simplied path loss models for various environments of the UMTS system [36],

which can also be utilized in the LTE and LTE-A systems. The mean of the log-normally

distributed path loss is given as a function of the distance from the mobile station to the

base station:

Yangyang Dong 27


Path Loss Model for Indoor Oce Test Environment:

L = 37 + 30 logR+ 18.3n(n+2)/(n+1)0.46 (3.13)

where R is the distance from the UE to the eNodeB in meters, and n is the numberof oors in the path.

Path Loss Model for Outdoor to Indoor and Pedestrian Test Environment:

L = 40 logR+ 30 log f + 49 (3.14)

where R is the distance from the UE to the eNodeB in kilometers, and f is thecarrier frequency in MHz.

Path Loss Model for Vehicular Test Environment:

L = 40(1 4 103hB) logR 18 log hB + 21 log f + 80 (3.15)where R is the distance from the UE to the eNodeB in kilometers, f is the carrierfrequency in MHz, and hB is the base station antenna height in meters.Suppose a carrier frequency of 2000 MHZ is used and the base station antenna isxed at a height of 15 meters, the formula becomes:

L = 128.1 + 37.6 logR (3.16)

This simplied path loss model is utilized in this thesis.

3.1.2 Slow Fading

In wireless transmissions, attenuation of the transmit power is often caused by large objects

such as trees and buildings along the propagation path of the radio signals. This atten-

uation is called slow fading. It is also known as shadow fading, since it is mainly caused

by shadowing. Usually, these objects along the path have dierent sizes, locations and

dielectric properties. Therefore, statistical models are required to represent the shadowing

eects. The most widely used model is the log-normal model, which models the variation

of received power in both outdoor and indoor propagation environments.

Assume that the ratio of the power transmitted and the power received is Ps in linear scaleand S in logarithmic scale, which means:

S = 10 logPs (3.17)

According to [37], the probability distribution function (PDF) of the log-normally dis-

tributed Ps in linear scale can be expressed as:

p(Ps) =10/ ln 102pidBPs

e (10 logPsdB)

2

2dB2(3.18)

where dB and dB are the mean and the standard deviation of S, respectively. They areboth expressed in dB scale.

28 Yangyang Dong


The PDF of the normally distributed S (Gaussian distributed) is given in the followingformula:

p(S) =1

2pidBe (SdB)

2

2dB2(3.19)

The slow fading model used in this thesis is log-normally distributed with zero mean and

variance, which was proposed in [24]. It considers the time correlation between the slow

fading values. Assume that a user starts moving from a point P, where the slow fading is

randomly generated by a log-normal distribution and equals to S(0). According to [25],with the user moving, the slow fading at distance , 2, 3, ..., n from the start point Pcan be illustrated as:

S(n) = e/dcS((n 1)) + Vi (3.20)

dc is the decorrelation distance, where the covariance (Cov() = 2dBe/dc) between the

two point is 2dBe1. Vi is an independent identically distributed (i.i.d) normal randomvariable. The mean and variance (in dB) of Vi are given below:

2,dB = 0 (3.21)

22,dB = 2dB(1 e2/dc) (3.22)

With the mobile user moving, a short decorrelation distance corresponds to a quick shadow

fading change, whereas a long decorrelation distance implies a slow shadow fading variation.

3.1.3 Fast Fading

Unlike the signals propagating along a xed path in the wired communication, the radio

signals in wireless transmission usually experience multi-path channels, thus leading to an

amplitude change and a phase shift at the receiver side. These eects are termed as fast

fading. The scale of fast fading eect is smaller compared to the eects of the path loss

and the slow fading. Fast fading causes both frequency and time selectivity.

Suppose a single, ideal Dirac impulse of power (t) is transmitted at time 0, i.e.:

x(t) = (t) (3.23)

Due to the multi-path propagation, more than one pulse might be received at the receiver,

with each one of them arriving at dierent time and with dierent amplitudes and phases

(Figure 3.2). The received signal h(t) is a superposition of the impulse response functions,which can be expressed by:

Yangyang Dong 29


Figure 3.2: Channel Impulse Response

y(t) = h(t) =N1n=0

nejn(t n) (3.24)

where N is the number of received impulse responses, which also stands for the number ofpaths. n represents the time delay of the n

thimpulse. ne

jnis the complex amplitude of

the received impulses, which includes both the magnitude and the phase. n can be givenby n = 2pifcn with a central frequency of fc. Since several responses reach the receiverat the same time, certain frequencies are attenuated more than the others. This is known

as the frequency-selective fading.

In practice, channels are time-variant, leading to the time dependent n and n, thusthe impulse responses would also be time-dependent. Therefore, the channel is not only

frequency selective, but also time selective. The time-variant impulse response can be

illustrated as:

y(t,t) = h(t,t) =N1n=0

n(t)ejn(t

)(t n(t)) (3.25)

Figure 3.3 shows a time-variant channel where the impulse response of the channel varies

with time. The time-axis is denoted by t and delay-axis is denoted by t.

The time selectivity of the channel is caused not only due to the time varying channels,

but also due to the movements of the transmitter or receiver, which is widely known as the

Doppler Shift. Assume that the signal has a frequency of f , and it arrives at the receivermoving at a speed of v with an angle of to the direction of movement. c is the speed oflight in free space. The Doppler Shift can be expressed by:

n = 2pifvcos()/c (3.26)

30 Yangyang Dong


Figure 3.3: Time Variant Channel Impulse Response

The frequency selectivity of the channel is caused by multi-path propagation, thus it is

not avoidable. Whereas the time selectivity can be negligible if the transmitter and the

receiver are stationary.

Several models have been proposed to depict fast fading for system level simulation pur-

poses. The one used in this thesis is the Jakes-like Method of Complex Gain Generation.

3.1.3.1 Jakes-like Method of Complex Gain Generation

This model takes both the delay spread for frequency selectivity and the Doppler Shift

for time selectivity into consideration. The time selectivity is modeled according to the

Clarke's model [25] and the frequency selectivity is modeled in [38]. The time and frequency

dependent channel can be illustrated in Figure 3.4.

Assume that the receiver is moving at a speed of v, and N rays with the same amplitudeare received with an arrival angle of n. L PBRs are used in the network. For each rayn, suppose fl is the center frequency at PRB l, n is the delay of ray n, then the phasechange n at PRB l can be expressed as:

n = fln (3.27)

The Doppler Shift can also be illustrated as:

n = mtcosn (3.28)

Yangyang Dong 31


Figure 3.4: Time and Frequency Selective Channel [23]

where mt is the maximum Doppler Shift, which is determined by m = 2piflv/c. Thetime-variant complex gain at PRB l can be acquired by accumulating the amplitudes ofthe phases of all the N rays:

gl(t) =1N

N1n=0

ej(n+n) (3.29)

3.1.4 Link Budget

The link budget is a power budget, which considers all the power gains and losses of a signal

during the propagation from the transmitter to the receiver. It is used for determining the

Signal to Interference and Noise Ratio (SINR) of each PRB.

SINR = PTx Ptotallosses NF N0 (3.30)

where PTx stands for the transmit power. Ptotallosses represents the total losses during thepropagation, which include the path loss, the slow fading and the fast fading. NF is theNoise Figure caused by the electronic equipment, and N0 is the thermal noise.

32 Yangyang Dong

MASTER THESIS 3.2. Link-to-System Level Mapping

3.2 Link-to-System Level Mapping

Wireless network simulations are often divided into link-level and system-level ones. The

former ones consider air interface and physical layer related issues of one single link such

as modulation schemes, channel coding, and equalization; while the latter ones do not

simulate every individual link but consider many transmitters and receivers. This thesis

works on the system-level simulations. Therefore, a link-to-system level mapping method

is required to get the link level statistics for the system level simulations.

!

"

!

"

Figure 3.5: Actual Value Interface

As is shown in Figure 3.5, the SINR values of all the PRBs are mapped to a single value

SINRavg, which stands for the overall channel conditions of the UE. In uplink, the ActualValue Interface (AVI) [8] mapping method is used, which averages the link level SINR

values of all the PRBs:

SINRavg =1

N(SINR1 + SINR2 + ...+ SINRN ) (3.31)

The obtained SINRavg is compared to the target SINR of the highest MCS, which is theSINR value of the 10% Block Error Probability (BLEP) of the corresponding Additive

White Gaussian Noise (AWGN) curve (Figure 3.6). If SINRavg is greater than the targetSINR, the highest MCS is chosen. Otherwise, compare the SINRavg with the target SINRof the next highest MCS, until a MCS with a target SINR lower than the SINRavg isfound. If the target SINR of the lowest MCS is still larger than the SINRavg, the user isconsidered not able to be served with its current channel conditions.

Once the MCS is determined, the Transport Block Size (TBS) can be decided according

to the TBS table (see Appendix E).

Yangyang Dong 33


Figure 3.6: AWGN Channel BLER vs. SINR Curve [23]

34 Yangyang Dong

4 RRM in a Multi-CC LTE-A System

The Radio Resource Management in the LTE-Advanced system is dierent from the one

in the LTE system, since the LTE-A system is able to aggregate multiple carriers for data

transmission. Figure 4.1 illustrates the RRM framework of a general uplink LTE-A system

with multiple carriers. The highlighted parts are covered in this thesis.

!"#$ !"#% !"#

Figure 4.1: RRM Framework of LTE-Advanced Uplink

The Admission Control is in the Radio Resource Control layer of the control plane in the

eNodeB, which decides whether to accept or deny a new incoming connection. Once the

new connection is admitted, the CC Selection module allocates one or multiple CCs to

it based on the UE QoS requirements, terminal capability and so on. Afterwards, the

Time/Frequency Domain MAC Packet Scheduler (TDPS/FDPS) allocates radio resources

to the UEs according to their buer sizes and channel conditions, etc. Since a UE may use

multiple CCs for data transmission, the scheduler is capable of supporting joint scheduling

across multiple assigned CCs. In the uplink, the UEs are limited by the transmission

power, therefore, Power Control is also an important issue. In order to keep backward

compatibility with the Release 8 LTE system, the 3GPP working group agrees that several

separate RRM blocks operate independently on each CC, meaning that independent Link

Adaptation (LA) and HARQ are performed per CC basis. This ensures that the LTE

terminals are also able to work in the LTE-Advanced system. The 3GPP does not specify

algorithms for these functions, so vendors are free to design their own methods.

MASTER THESIS 4. RRM in a Multi-CC LTE-A System

4.1 Admission Control

The AC is typically used for real-time trac, such as VoIP (Voice over IP), audio/video

streaming and gaming, and other time critical applications. It grants or denies the access

to a new radio bearer, depending on whether the required QoS of the new radio bearer will

be fullled while the required QoS of the already existing sessions is guaranteed. The 3GPP

denes four service level QoS parameters in [39]: QoS Class Identier (QCI), Allocation

and Retention Priority (ARP), Guaranteed Bit Rate (GBR), and Aggregate Maximum Bit

Rate (AMBR):

QCI: Corresponds to a service type based on its bearer priority, packet delay budgetand packet loss rate.

ARP: Provides the basis for admission control in bearer setup, and it is also impor-tant in a congestion situation when bearers need to be discarded. Once the connection

has been established, the ARP does not inuence the bearer level treatment such as

the packet scheduling. The range of the ARP values is from 1 to 15, with 1 being the

highest level of priority.

GBR: Indicates the bit rate that can be expected to be provided by a GBR bearer. AMBR: Shared by all the non-GBR bearers of one UE. It denotes the total maximumbit rate that a UE may have for all the non-GBR bearers. With AMBR, network

operators are able to dierentiate subscribers with dierent priorities.

4.1.1 Common Algorithms

3GPP does not specify an algorithm for Admission Control. Therefore, several algorithms

have been proposed to admit or deny new connections in the system. Here are some

common algorithms for the AC in the LTE-A system.

The reference admission control algorithm is proposed in [15]:

c(t) + creq margin C (4.1)

This algorithm can be used for both downlink and uplink, in which c(t) represents therequired capacity of all the already existing connections, creq is the required capacity ofthe new connection, and C is the cell capacity. margin is a ratio, standing for the capacitythat can be occupied by real-time trac over the total capacity.

The reference AC algorithm is relatively simple and does not require lots of calculations.

However, this algorithm treats all the users equally and does not dierentiate them based

on their channel conditions. Besides, margin does not represent the actual ratio of real-time trac throughout over the overall cell throughput, which is time-variant in practice.

Another algorithm for AC which considers the channel quality is the FPC (See Chapter

4.5) based AC Algorithm [16]. Since the power control is only necessary for the uplink,

this method can only be used for the admission control in the uplink. It calculates the

required number of PRBs per TTI (Transmission Time Interval) of the new incoming user,

provided that its GBR requirement and transmit power constraint are fullled.

36 Yangyang Dong

MASTER THESIS 4.2. Component Carrier Selection

ki=1

Ni +Nnew Ntotal (4.2)

where Ni is the required number of PRBs per TTI of the already existing users, Nnewis the number of PRBs required by the new incoming connection, and Ntotal is the totalnumber of PRBs provided by the frequency bands in the system. The Ni of the existingusers can be calculated at the eNodeB by dividing the total throughput by the average

scheduled throughput per PRB information; while the Nnew needs to be estimated usingthe path loss and required GBR information. The FPC based AC algorithm tries to block

the users with high path loss to satisfy the requirements of the previously admitted users.

4.2 Component Carrier Selection

For the LTE users, only one component carrier can be used for data transmission. It is

proved in [26] that the Round Robin (RR) balancing is an ecient way to allocate CCs to

the LTE users in a system with more than one CC. When a new user arrives, it is assigned

on the carrier that has the least number of users at present.

Unlike the LTE system, the LTE-A system allows a user to transmit data on up to ve

component carriers. The CC Selection module allocates one or multiple CCs to the incom-

ing users based on their QoS requirements and channel conditions, etc. For the downlink,

being allocated on multiple CCs generally results in a higher throughput, thanks to the

the larger transmission bandwidth and higher transmission power. However, this might

not always work for the uplink, especially for the users who are power limited at the cell

edge. According to [14], even if the users are assigned on multiple CCs, they do not have

sucient power to exploit the increased transmission bandwidth. It is shown in [28] that

with a proper CC allocation, the average and cell center user throughput can be highly

improved. Therefore, a sucient way to select the component carriers for the users is

needed.

In this work, the intra-band contiguous carrier aggregation is assumed, i.e., two contiguous

carriers from the same band are utilized in the network. A simple algorithm is implemented

in this work such that the users whose distance to the eNodeB is farther than a distance

limit are assigned on one, otherwise both CCs. This algorithm is easy to implement

and requires relatively simple calculations; however, dierent distance limits give dierent

performances. If the best performance is to be achieved, the determination of the distance

limit requires a great amount of testing. Moreover, the network environment changes over

the time, while the distance limit would not adapt accordingly once it is set.

An eective path loss threshold based CC selection algorithm was proposed in [14] to

distinguish between power-limited and non-power-limited LTE-A users:

Pthreshold = L95% 10 logK + Pbackoff

(4.3)

where L95% is the estimated 95 percentile user path loss, K is the total number of CCsand is the path loss compensation factor used in the power control scheme. Pbackoff

Yangyang Dong 37


is the estimated power back-o to model the eects of increased PAPR and CM (Cubic

Metric) when a user transmits over multiple CCs simultaneously. If a user is scheduled for

transmission only on one CC, there is no power back-o; otherwise, it is set with a xed

value, for example, 4 dB or 6 dB. With a higher power back-o, less LTE-A users will

be assigned on multiple CCs due to the limitation of user transmission power. When the

path loss of the LTE-A users is higher than the threshold Pthreshold, they are considered tobe power-limited and assigned on one single CC; otherwise they are considered to be non-

power-limited and can use multiple CCs for data transmission. By doing this, the cell-edge

users will not experience performance loss from being scheduled over multiple CCs, while

the non-power-limited users can benet from the advantages of a wider bandwidth.

This algorithm is implemented in this work, however, improvement has also been made

to get better performance. Instead of assuming that the users are stationary, a time-

variant radio channel model is used to get the real-time channel conditions of the users.

Furthermore, not only the path loss is considered when determining the threshold and the

number of CCs, another important component of the radio channel - the slow fading, is

also taken into consideration. The proposed algorithm can be illustrated as follows:

Pthreshold = (L+ SF )95% 10 logK + Pbackoff

(4.4)

where SF stands for the slow fading of the user. When the sum of the user's path loss andslow fading is higher than the threshold, one CC is assigned; otherwise, the user can use

both CCs for data transmission.

4.3 Uplink Signalling

The uplink signalling provides the eNodeB with the required scheduling information of

the users. The channel aware scheduling methods in the uplink strongly demand the

information of the respective channels. Since the uplink transmission buers are located

in the users, the information on the buer status needs to be transmitted to the eNodeB

as well. In addition, the user needs to report the power headroom measurements to the

eNodeB in order to not exceed its maximum power during the uplink packet forwarding.

4.3.1 Channel State Information (CSI)

The CSI informs the eNodeB of the channel conditions of the users. The Sounding Refer-

ence Signals (SRS) are transmitted from the users. The SINR of the SRS is measured to

estimate the CSI. SRS can be transmitted over the whole bandwidth, or just a portion of

the bandwidth.

4.3.2 Buer Status Report (BSR)

In the downlink, the data buers are located in the eNodeB, so the scheduler in the eNodeB

has the knowledge of the user data. In the uplink, the buers are located in the users while

38 Yangyang Dong

MASTER THESIS 4.3. Uplink Signalling

the scheduling decisions are made at the eNodeB. Therefore, the BSR provides the serving

eNodeB with the information on the amount of data in the users' buers.

According to the 3GPP specication [40], a BSR shall be triggered if any of the following

events occurs:

New data arrives in the user buer, and its priority is higher than that of the alreadyexisting user data;

Uplink resources are allocated and number of padding bits is larger than the size ofthe Short/Long BSR;

The serving cell changes.

Buffer SizeLCG ID Oct 1

(a) Short BSR

Buffer Size #1 Buffer Size #2Buffer Size #2 Buffer Size #3

Buffer Size #3 Buffer Size #4

Oct 1

Oct 2

Oct 3

(b) Long BSR

Figure 4.2: Buer Status Report

In line with the 3GPP specications, the buer status is reported on a Logical Channel

Group (LCG) basis. A LCG is a group of radio bearers with similar QoS requirements.

The maximum number of LCGs is xed to be four. Two formats of BSRs are dened: the

Short BSR and the Long BSR. The former one (see Figure 4.2 (a)) contains one LCG ID

eld and one corresponding Buer Size eld, and only one LCG is reported in the Short

BSR; the latter one (see Figure 4.2 (b)) consists of four Buer Size elds, corresponding

to LCG IDs No. 1 to No. 4, and all four LCGs are reported. The LCG ID identies the

group of the logical channels of which the buer status is being reported, and the length

of the LCG ID is 2 bits; Buer Size indicates the total amount of data available in all the

logical channels of a LCG in Bytes, and the length of this eld is 6 bits. If there is data

from only one LCG in the user buer, a short BSR is transmitted; otherwise, a long BSR

is delivered.

4.3.3 Power Headroom Report (PHR)

The PHR is dened in [41] for the uplink, which indicates the dierence between the UE

maximum transmit power and the estimated uplink scheduling transmit power. In a power

headroom report, the user sends the information on the Power Spectral Density (PSD) to

Yangyang Dong 39


the eNodeB. Then the eNodeB uses this information to perform RRM decisions such as

determining the transmission bandwidth and MCS.

4.4 Resource Allocation and Scheduling

Resource allocation and scheduling is conducted by the MAC packet scheduler. It dynam-

ically distributes the radio resources among the active users with an appropriate MCS. It

aims to maximally utilize the scarce radio resources, while meeting the QoS requirements

of the EPS bearers. The scheduling is performed in every TTI. 1 TTI equals 1 ms.

As explained in Chapter 2.3, N-times clustered DFTS-OFDM is agreed as the uplink

access scheme of the uplink LTE-A system, due to its lower signal PAPR compared to the

OFDMA scheme and backward compatibility with the LTE system. Furthermore, it has a

higher scheduling exibility compared to the SC-FDMA scheme, permitting non-contiguous

PRB assignments to achieve a higher spectral eciency. The scheduling information is

broadcasted to all the users through the PDCCH. Users have to monitor the PDCCH to

know when to transmit and receive. The scheduling decisions are made per bearer basis.

By using the DiServ (Dierentiated Services) architecture, the scheduler is able to dier-

entiate between various trac types and assign the radio resources according to their QoS

requirements. The main characteristic of the proposed scheduler is that it guarantees the

QoS of dierent trac types and considers their channel conditions, while keeping a rea-

sonable fairness and user throughput. The scheduler has a decoupled time and frequency

domain structure, including Bearer Classication, TDPS and FDPS. Figure 4.3 illustrates

the scheduler structure implemented in this thesis.

Figure 4.3: Decoupled Time and Frequency Domain Scheduling

The radio bearers can be classied into GBR bearers and non-GBR bearers:

GBR: The QoS of the GBR bearers is guaranteed by dedicating a xed number ofresources to the UE when a connection is established. VoIP trac could be dened

as GBR.

Non-GBR: For the bearers with no xed resources reserved, no certain bit rate canbe guaranteed. Best Eort (BE) trac such as HTTP (Hypertext Transfer Protocol)

40 Yangyang Dong

MASTER THESIS 4.4. Resource Allocation and Scheduling

and FTP (File Transfer Protocol) can be categorized to be non-GBR bearers.

In the following subsections, each part of the scheduler will be given in details.

4.4.1 Bearer Classication

In the Bearer Classication phase, the bearers are classied according to their TDPS

metric, which depends on their QoS requirements, channel conditions and buer status.

The TDPS metric is calculated in this phase for the time domain scheduler.

The QoS parameter used for the bearer classication is the QCI, which is an index associ-

ated with predened values for the priority, delay budget and packet loss rate. Nine QCI

classes are predened by the 3GPP - four for the GBR bearers and ve for the non-GBR

bearers. In addition, network operators are allowed to dene additional new classes based

on their specic needs. Since each trac type has dierent QoS requirements, each bearer

is assigned with a single QCI class. In the MAC scheduler, the bearers are distributed into

ve MAC QoS classes according to [24]: two classes - MAC QoS Class 1 and Class 2 for

the GBR bearers and three classes - MAC QoS Class 3, 4 and 5 for the non-GBR bearers.

Table 4.1 shows how MAC QoS classes are mapped onto QCI classes.

Bearer Type QCI class MAC QoS Class Trac Type

GBR QCI-1 MAC-QoS-1 VoIP

Non-GBR QCI-7 MAC-QoS-3 Video Conferencing

Non-GBR QCI-8 MAC-QoS-4 HTTP

Non-GBR QCI-9 MAC-QoS-5 FTP

Table 4.1: QCI and MAC QoS Mapping

For each MAC QoS class, the TDPS weight Wi,k(t) of a bearer k of the user i is calcu-lated based on the following formula, which takes the QoS of dierent trac types into

consideration:

Wi,k(t) =Rmin,kRi,k(t)

i,k(t)max,k

%k(t) (4.5)

where Rmin,k stands for the bit rate budget, i.e., the minimum throughput of the bearerk at a certain QoS class; and max,k is the end-to-end delay budget, i.e., the maximumtolerant delay of the bearer k. Ri,k(t) is the average throughput, and i,k(t) is the averagedelay of bearer k of user i. %k(t) is a variable: if i,k(t) is higher than the delay thresholdof bearer k at time t , it is set to 10; otherwise it is set to 1. This variable is to avoid largedelays of some delay-sensitive trac, for example the video applications. In case that the

bearer delay is larger than the delay threshold, its QoS weight is increased by 10 times to

increase the possibility to be scheduled.

The bit rate budget, the packet delay budget and the delay threshold values for various QoS

classes are given in Table 4.2. For example, a VoIP bearer has an average throughput of 110

kbps and an average delay of 0.01 s (below the delay threshold), the weight is calculated

as 55kbps/110kbps 0.01s/0.1s 1 = 0.05. If the average delay increases to 0.05 s (exceeds

Yangyang Dong 41


Bearer Type Bit Rate Budget Delay Budget Delay Threshold

(kbps) (ms) (ms)

VoIP 55 100 20

Video Conferencing 132 150 50

Buered Video 132 300 100

HTTP 120 300

FTP 10 300

Table 4.2: Bit Rate Budget, Delay Budget and Delay Threshold [39]

the delay threshold), the weight will be set to 55kbps/110kbps 0.05s/0.1s 10 = 2.5. Inthis way, the priority of the VoIP bearer will increase to get more resources, thus resulting

in a decreased delay.

After acquiring the TDPS weight of each bearer, the TDPS metric of each bearer can be

calculated according to dierent TDPS algorithms, which are given in the next subsection.

The bearers are put into a bearer list for scheduling by the time domain scheduler.

4.4.2 Time Domain Scheduling

During the Time Domain Scheduling session, the bearers are sorted in each TTI according

to the TDPS priority metric calculated in the Bearer Classication phase. The bearers

with higher TDPS metric values are chosen for the FDPS. The scheduling is performed

per bearer basis in the uplink LTE-A system, because there is no contiguous-resource-

allocation constraint as in LTE, thanks to the exploitation of the DFTS-OFDM access

scheme. Moreover, uplink signalling, such as the CSI, the BSR and the PHR, provides the

eNodeB with the information required for the uplink scheduling.

Some of the basic and widely used scheduling algorithms include: Blind Equal Throughput

(BET), Maximum Throughput (MaxT) and Proportional Fair (PF). A brief introduction

to these algorithms is given below.

4.4.2.1 Blind Equal Throughput Scheduler

The BET scheduling algorithm is a simple algorithm which does not require a-priori knowl-

edge of the channel conditions. It gives equal amount of radio resources to all the bearers to

keep an equal throughput among them, regardless of whether they are close to the eNodeB

or at the cell edge [42]. One of the advantages of the BET scheduler is that it provides

fairness among all the bearers, however, it leads to low cell throughput.

The BET priority metric could be calculated by:

Pk(t) = argmax1

Tk(t)(4.6)

where Tk(t) stands for the average throughput of the bearer k over a time window:

42 Yangyang Dong

MASTER THESIS 4.4. Resource Allocation and Scheduling

Tk(t) =

{(1 1 )Tk(t 1) + 1 Rk(t) if bearer k is served in time slot t;(1 1 )Tk(t 1) otherwise.

where

Rk(t) is the actual achieved throughput of bearer k over a time window. is thetime window which is measured by TTIs, and usually it is a number between 500 TTIs to

1000 TTIs.

4.4.2.2 Maximum Throughput Scheduler

The MaxT scheduler is also discussed in [42], which aims at maximizing the cell throughput

by giving priority to the bearers closer to the eNodeB, who have better instantaneous

channel conditions. The priority metric calculation can be expressed as follows:

Pk(t) = argmax rk(t) (4.7)

where

rk(t) is the instantaneously supported throughput of the bearer k over a time win-dow. This algorithm maximizes the cell throughput and the spectral eciency, however,

it does not serve all the bearers equally. As a result, the bearers at the cell edge might

starve due to their bad channel conditions.

4.4.2.3 Proportionally Fair Scheduler

The BET scheduler ensures fairness among all the bearers but gives a low cell throughput;

while the MaxT scheduler provides high cell throughput, however, it does not consider fair-

ness among all the bearers. Therefore, [42] also proposed the Proportionally Fair scheduler,

which is a compromise between the BET and the MaxT algorithms: it tries to provide a

relatively high cell throughput of the network, while keeping some level of fairness.

Pk(t) = argmaxrk(t)

Tk(t)(4.8)

where

rk(t) is the instantaneously supported throughput of the bearer k over a time win-dow. Tk(t) is the average throughput of the bearer k over a time window, which is calculatedwith the same formula for the BET scheduler.

4.4.2.4 Bandwidth and QoS Aware Scheduler

The BQA Scheduler was proposed in [25] for LTE uplink to provide ecient and fair al-

location of the radio resources to the users according to their various QoS requirements

and instantaneous channel conditions. Since there is a contiguous-resource-allocation con-

straint for LTE uplink, the TDPS metric is calculated per user basis. The TDPS weight

calculated in the Bearer Classication phase is taken into consideration when deciding the

priority metric.

Yangyang Dong 43


Pi(t) = argmaxri(t)

Ti(t)

Mk=1

Wi,k(t) (4.9)

where

ri(t) is the instantaneously supported throughput of the user i over a time window.Ti(t) is the average throughput of the user i over a time window. M is the total numberof the bearers of the user i.

For LTE-A uplink, since DFTS-OFDM is used, the contiguous-resource-allocation con-

straint does not exist anymore. A per bearer basis Channel and QoS Aware (CQA)

sched

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