china mobile cran white paper v26 2014

C-RAN

The Road Towards Green RAN

White Paper

Version 2.6 (Sep., 2013)

China Mobile Research Institute

China Mobile Research Institute

i

Table of Contents

Executive Summary ....................................................................................................................... 1

1 Introduction ............................................................................................................................ 3

1.1 Background ......................................................................................................................... 3

1.2 Vision of C-RAN .................................................................................................................. 3

1.3 Objectives of This White Paper ....................................................................................... 4

1.4 Status of This White Paper .............................................................................................. 4

2 Challenges of Todays RAN ............................................................................................... 5

2.1 Large Number of BS and Associated High Power Consumption .............................. 5

2.2 Rapid Increasing CAPEX/OPEX of RAN.......................................................................... 6

2.3 Explosive Network Capacity Need with Falling ARPUs............................................... 8

2.4 Dynamic Mobile Network Load and Low BS Utilization Rate .................................... 9

2.5 Growing Internet Service Pressure on Operators Core Network............................ 9

3 Architecture of C-RAN ....................................................................................................... 11

3.1 Advantages of C-RAN ..................................................................................................... 13

3.2 Technical Challenges of C-RAN ..................................................................................... 14

4 Technology Trends and Feasibility Analysis ...................................................................... 15

4.1 Wireless Signal Transmission on Optical Network.................................................... 15

4.2 Dynamic Radio Resource Allocation and Cooperative Transmission/Reception . 22

4.3 Large Scale Baseband Pool and Its Interconnection ........................................................... 26

4.4 Open Platform Based Base Station Virtualization ................................................................ 27

4.5 Distributed Service Network ................................................................................................. 31

5 Evolution Path ...................................................................................................................... 33

5.1 C-RAN Centralized Base Station Deployment ........................................................... 33

5.2 Multi-standard SDR and Joint Signal Processing ...................................................... 33

5.3 Virtual BS on Real-time Cloud Infrastructure ............................................................ 34

6 Recent Progress .................................................................................................................. 35

6.1 TD-SCDMA and GSM Field Trial .................................................................................... 35

6.2 TD-LTE C-RAN Field Trial ............................................................................................... 41

6.3 Large Scale Baseband Pool Equipment Development ............................................. 43

6.4 C-RAN Prototype Based on General Purpose Processor .................................................. 45

6.5 Progress on C-RAN Virtualization ................................................................................. 47

7 Conclusions ........................................................................................................................... 52

8 Acknowledgement .............................................................................................................. 53

9 Terms and Definitions ....................................................................................................... 54

Cover is for

position only

China Mobile Research Institute ii

10 Reference ............................................................................................................................ 56

China Mobile Research Institute 1

Executive Summary

Data explosion in the big data era is in fact putting operators in a dilemma situation. On the one hand, operators have to spend huge investment on network infrastructure upgrade to accommodate the explosively increasing traffic, resulting in a significant increase of the total cost of ownership. On the other hand, operators are not seeing proportional revenue growth with the data traffic. Under the circumstance, traditional RAN architecture where a dedicated

equipment room with supporting facilities is needed for each base station is facing more and more challenges and issues for network deployment and operation, especially for LTE.

First, LTE site density is higher and thus requires more such equipment rooms, which is increasingly difficult to obtain since available real estate is becoming scarcer. Moreover, LTE suffers much more severe interference issue than 2G, 3G networks due to its universal frequency reuse OFDM nature and its higher cell density. Existing collaborative technologies

such as joint transmission or joint reception can not perform effectively under traditional architecture with X2 interface which is of low bandwidth and high latency. Last but not the least traditional base stations are deployed for their peak scale to accommodate the peak traffic. This practice, however, due to the time-varying nature of the traffic, not only lowers the equipment utilization efficiency, but also greatly increases the power consumption unnecessarily.

Featuring centralized, collaborative, cloud and clean system, the cloud RAN (C-RAN) is proposed by CMCC to help operators to address the above-mentioned challenges. A C-RAN network centralizes the BBU processing resource together into a pool so that the resource could

be managed and allocated dynamically on demand. C-RAN offers many benefits to operators, including but not limited to: Energy saving, mainly because of facility sharing in the centralization office, especially

air-conditioning sharing and due to improved resource efficiency by virtualization. TCO reduction since lots of site rooms could be saved and power consumption is

significantly decreased. Also, site construction can be sped up since there is no need to find the separate equipment room for every base station. Instead, one centralized site office can accommodate several dozens of base stations.

Improved spectral efficiency due to facilitation of advanced technology implementation, especially Coordinated Multi-point technique by providing high-speed low-latency switching networks in the centralized site office to enable timely information exchange among BBU within the pool.

Improved resource efficiency thanks to resource virtualization.

To enable service on edge and boost service innovation when open general-purposed platform is adopted for C-RAN implementation.

To leverage such benefits, however, three major challenges must be addressed. A cost-effective fronthaul solution which minimizes fiber consumption while

maximizing the number of transported TD-LTE carriers (especially 8-antenna TD-LTE carriers).

A scalable BBU pool architecture which efficiently supports various key technologies

including CoMP and live migration.

Virtualization technology meeting the strict real-time constraints of wireless signal

processing. This includes the optimization on hypervisor, operating systems, management functions, I/O virtualization, and so on.

China Mobile has been developing and deploying C-RAN systems since 2009. In particular, CMCC has conducted extensive field trials in more than 10 cities across China. Our field trials in GSM and TD-SCDMA have vigorously demonstrated the benefits that C-RAN centralization can


bring to operators. For example, compared to distributed TD-SCDMA networks, up to 15% CAPEX and 50% OPEX could be saved using C-RAN centralization. Moreover, system roll out time is saved by 1/3 and in view of green deployment, the saving on power consumption can be as high as 70%. In the meantime, the TD-LTE C-RAN trials in the cities of Fuzhou, Chengdu and Guangzhou

have verified the maturity and effectiveness of CPRI compression and single fiber bi-direction (SFBD) technologies in fronthaul implementation. Using SFBD and CPRI compression with 2:1 compression ratio, we can save the fiber consumption by 4 folds while maintaining a lossless system performance. Moreover, WDM-based fronthaul solutions are being tested currently, which promises even greater potential to further save on fiber resource and make it much easier for large-scale C-RAN deployment.

Simulation results also demonstrated C-RANs advantages in achieving higher CoMP gain than using traditional architecture. Average cell spectrum efficiency and cell-edge spectrum efficiency by C-RAN CoMP are 20% and 45% higher than SU-MIMO respectively. On the road toward virtualization to realize resource cloudization in C-RAN BBU pool, we have developed an x86-based 3-mode base station prototype in which GSM, TS-SCDMA and TD-LTE

are realized in a pure software manner. We demo-ed an end-to-end call using commercial UE and CN. However, currently the real-time wireless signal processing in pure software implementation is not achieved cost effectively; the power-performance ratio is very low. We therefore concluded that a dedicated hardware accelerator is needed for processing some L1 functions that are computation-intensive, e.g. iFFT/FFT. There is also some discussion and viewpoints regarding how to implement virtualization from data center in C-RAN in this White Paper.

C-RAN is a multi-stage RAN evolution which requires joint efforts from every partner in the ecosystem including both IT and telecom industry. We would also like to take this WP as an opportunity to call for more action, contribution and commitment on C-RAN research and development, which we believe is the sure trend to the future.

--- End of Executive Summary


1 Introduction

1.1 Background

Todays mobile operators are facing a strong competition environment. The cost to build,

operate and upgrade the Radio Access Network (RAN) is becoming more and more expensive

while the revenue is not growing at the same rate. The mobile internet traffic is surging, while

the ARPU is flat or even decreasing slowly, which impacts the ability to build out the networks

and offer services in a timely fashion. To maintain profitability and growth, mobile operators

must find solutions to reduce cost as well as to provide better services to the customers.

On the other hand, the proliferation of mobile broadband internet also presents a unique

opportunity for developing an evolved network architecture that will enable new applications

and services, and become more energy efficient.

The RAN is the most important asset for mobile operators to provide high data rate, high

quality, and 24x7 services to mobile users. Traditional RAN architecture has the following

characteristics: first, each Base Station (BS) only connects to a fixed number of sector

antennas that cover a small area and only handle transmission/reception signals in its coverage

area; second, the system capacity is limited by interference, making it difficult to improve

spectrum capacity; and last but not least, BSs are built on proprietary platforms as a vertical

solution. These characteristics have resulted in many challenges. For example, the large

number of BSs requires corresponding initial investment, site support, site rental and

management support. Building more BS sites means increasing CAPEX and OPEX. Usually, BSs

utilization rate is low because the average network load is usually far lower than that in peak

load; while the BS processing power cant be shared with other BSs. Isolated BSs prove costly

and difficult to improve spectrum capacity. Lastly, a proprietary platform means mobile

operators must manage multiple none-compatible platforms if service providers want to

purchase systems from multiple vendors. Causing operators to have more complex and costly

plan for network expansion and upgrading. To meet the fast increasing data services, mobile

operators need to upgrade their network frequently and operate multiple-standard network,

including GSM, WCDMA/TD-SCDMA and LTE. However, the proprietary platform means mobile

operators lack the flexibility in network upgrade, or the ability to add services beyond simple

upgrades.

In summary, traditional RAN will become far too expensive for mobile operators to keep

competitive in the future mobile internet world. It lacks the efficiency to support sophisticated

centralized interference management required by future heterogeneous networks, the flexibility

to migrate services to network edge for innovative applications and the ability to generate new

revenue from revenue from new services. Mobile operators are faced with the challenge of

architecting radio network that enable flexibility. In the following sections, we will explore ways

to address these challenges.

1.2 Vision of C-RAN

The future RAN should provide mobile broadband Internet access to wireless customers with

low bit-cost, high spectral and energy efficiency. The RAN should meet the following

requirements:

Reduced cost (CAPEX and OPEX)

Lower energy consumption


High spectral efficiency

Based on open platform, support multiple standards, and smooth evolution

Provide a platform for additional revenue generating services.

Centralized base-band pool processing, Co-operative radio with distributed antenna equipped

by Remote Ratio Head (RRH) and real-time Cloud infrastructures RAN (C-RAN) can address the

challenges the operators are faced with and meet the requirements. Centralized signal

processing greatly reduces the number of sites equipment room needed to cover the same

areas; Co-operative radio with distributed antenna equipped by Remote Radio Head (RRH)

provides higher spectrum efficiency; real-time Cloud infrastructure based on open platform and

BS virtualization enables processing aggregation and dynamic allocation, reducing the power

consumption and increasing the infrastructure utilization rate. These novel technologies provide

an innovative approach to enabling the operators to not only meet the requirements but

advance the network to provide coverage, new services, and lower support costs.

C-RAN is not a replacement for 3G/B3G standards, only an alternative approach to current

delivery. From a long term perspective, C-RAN provides low cost and high performance green

network architecture to operators. In turn operators are able to deliver rich wireless services in

a cost-effective manner for all concerned.

C-RAN is not the only RAN deployment solution that will replace all todays macro cell station,

micro cell station, pico cell station, indoor coverage system, and repeaters. Different

deployment solutions have their respective advantages and disadvantages and are suitable for

particular deployment scenarios. C-RAN is targeting to be applicable to most typical RAN

deployment scenarios, like macro cell, micro cell, pico cell and indoor coverage. In addition,

other RAN deployment solution can serve as complementary deployment of C-RAN for certain

case.

1.3 Objectives of This White Paper

The objective of this white paper is to present China Mobiles vision of C-RAN and provide a

research framework by identifying the technical challenges of C-RAN architecture. We would

like to invite both industry and academic research institutes to join the research to guide the

vision into reality in the near future.

1.4 Status of This White Paper

This document version 2.5 is a revised version of version 2.0 released in December 2010. It is

not yet fully complete and there may still be some inconsistencies. However, it is considered to

be useful for distribution at this stage. It is expected that new research challenges might be

added in future versions. Comments and contributions to improve the quality of this white

paper are welcome.


2 Challenges of Todays RAN

2.1 Large Number of BS and Associated High Power Consumption

As operators constantly introduce new air interface and increase the number of base stations to

offer broadband wireless services, the power consumption gets a dramatic rise. For example: in

the past 5 years, China Mobile has almost doubled its number of BS, to provide better network

coverage and capacity. As a result, the total power consumption has also doubled. The higher

power consumption is translated directly to the higher OPEX and a significant environmental

impact, both of which are now increasingly unacceptable.

The following figure 1 shows the components of the power consumption of China Mobile. It

shows the majority of power consumption is from BS in the radio access network. Inside the BS,

only half of the power is used by the RAN equipment; while the other half is consumed by air

condition and other facilitate equipments.

Obviously, the best way to save energy and decrease carbon-dioxide emissions is to decrease

the number of BS. However, for traditional RAN, this will result in worse network coverage and

lower capacity. Therefore, operators are seeking new technologies to reduce energy

consumption without reducing the network coverage and capacity. Today, there are quite a

number of amendment technologies that helps reduce BS power consumption, such as the

software solutions which save power through turning off selected carriers on idle hours like

midnight, the green energy solutions which offer solar, wind and other renewable energy for

base stations power supply according to local natural conditions, and the energy-saving air

conditioning technology which combined with the local climate and environment characteristics,

reduce the energy consumption of the air conditioning equipment, etc. However, these

technologies are supplementary methods and cannot address the fundamental problems of

power consumption with the number of increasing BS.

In the long run, mobile operators must plan for energy efficiency from the radio access network

architecture planning. A change in infrastructure is the key to resolve the power consumption

challenge of radio access network. Centralized BS would reduce the number of BS equipment

rooms, reduce the A/C need, and use resource sharing mechanisms to improve the BS

utilization rate efficiency under dynamic network load.

Channel, 6%

Transmission,

15%

Management

office, 7%

Cell site, 72%

Major

Equipment,

51%Air

Conditioners,

46%

Other Support

Equipment,

3%

Fig.1 Power Consumption of Base Station


2.2 Rapid Increasing CAPEX/OPEX of RAN

Over recent years, mobile data consumption has experienced a record growth among the

worlds operators as subscribers use more smart phones and mobile devices, like tablets. To

satisfy this consumer usage growth, mobile operators must significantly increase their network

capacity to provide mobile broadband to the masses. However, in an intensifying competitive

marketplace, high saturation levels, rapid technological changes and declining voice revenue,

operators are challenged with deployment of traditional BS as the cost is high, the return is not

high enough. Average Revenue Per User (ARPU) are all affecting mobile operators profitability.

They become more and more cautious about the Total Cost of Ownership (TCO) of their

network in order to remain profitable and competitive.

Fig. 2: Increasing CAPEX of 3G Network Construction and Evolution

Analysis of the TCO

The TCO including the CAPEX and the OPEX results from the network construction and

operation. The CAPEX is mainly associated with network infrastructure build, while OPEX is

mainly associated with network operation and management.

In general, up to 80% CAPEX of a mobile operator is spent on the RAN. This means that most

of the CAPEX is related to building up cell sites for the RAN. The historical CAPEX expenditure of

2007-2012 forest are shown in Fig.2. Because 3G/B3G signals deployed frequency 2GHz have

higher path loss and penetration loss than 2G signals (deployed frequency 900MHz), multiple

cell sites are needed for the similar level of 2G coverage. Thus, the dramatic increase was

found in the CAPEX when building a 3G network.

The CAPEX is mainly spent at the stage of cell site constructions and consists of purchase and

construction expenditures. Purchase expenditures include the purchases of BS and

supplementary equipments, such as power and air conditioning equipments etc. Construction

expenditures include network planning, site acquisition, civil works and so on. As shown is Fig.3,

it is noticeable that the cost of major wireless equipments makes up only 35% of CAPEX, while

the cost of the site acquisition, civil works, and equipment installation is more than 50% of the

total cost. Essentially, this means that more than half of CAPEX is not spent on productive

wireless functionality. Therefore, ways to reduce the cost of the supplementary equipment and

the expenditure on site installation and deployment is important to lower the CAPEX of mobile

operators.


Fig. 3: CAPEX and OPEX Analysis of Cell Site

OPEX in network operation and the maintenance stage play a significant part in the TCO.

Operational expenditure includes the expense of site rental, transmission network rental,

operation /maintenance and bills from the power supplier. Given a 7-year depreciation period of

BS equipment, as shown in Fig.4, an analysis of the TCO shows that OPEX accounts for over 60%

of the TCO, while the CAPEX only accounts for about 40% of the TCO. The OPEX is a key factor

that must be considered by operators in building the future RAN.

The most effective way to reduce TCO is to decrease the number of sites. This will bring down

the cost for the construction of the major equipment; and will minimize the expenditure on the

installation and rental of the equipment incurred by their occupied space. Fewer sites means

the corresponding cost of supplementary equipment will also be saved. This can significantly

decrease the operators CAPEX and OPEX, but results in poorer network coverage and user

experience in the traditional RAN. Therefore, a more cost-effective way must be found to

minimize the non-productive part of the TCO while simultaneously maintaining good network

coverage.

Fig. 4 TCO Analysis of Cell Site

Multi-standard environment

It is understood that the large number of legacy terminals, 2G, 3G, and B3G infrastructure will

coexist for a very long time to meet consumers demand. Most of the major mobile operators

worldwide will thus have to use two or three networks (Table 1) [1]. In the new economic

climate, operators must find ways to control CAPEX and OPEX while growing their businesses.

The base station occupies the largest part of infrastructure investment in a mobile network.

Multi-mode base station is expected as a cost efficient way for operators to alleviate the cost of

network construction and O&M. In addition, sharing of hardware resources in a multi-mode

base station is the key approach to lower cost.


Table 1. Multi-Network Operation of Major Mobile Service Providers

Cellular Technologies Vodafone China Mobile

France Telecom

T-Mobile

Verizon SK Telecom

Telstra China Unicom

TD-SCDMA

WCDMA

CDMA One & 2000 &

EVDO

GSM GPRS EDGE

LTE

2.3 Explosive Network Capacity Need with Falling ARPUs

Data rate of mobile broadband network grows significantly with the introduction of air-interface

standards such as 3G and B3G; this in turn speeds up end users mobile data consumption.

Some forecasts indicated the number of people who access mobile broadband will triple in next

several years, after LTE and LTE-A are deployed. These findings reflect the fact that the

increasing bandwidth of wireless broadband triggers the increase in mobile traffic, because the

mobile users can use a variety of high-bandwidth services, such as video-based applications.

This new trend will become a serious challenge to future RAN.

Based on the forecast data [2], global mobile traffic increases 66-fold with a compound annual

growth rate (CAGR) of 131% between 2008 and 2013. The similar trend is observed in current

CMCC network. On the contrary, the peak data rate from UMTS to LTE-A only increases with a

CAGR of 55%. Clearly, as shown in Fig.5, there is a large gap between the CAGR of new air

interface and the CAGR of customers need. In order to fill this gap, new infrastructure

technologies need to be developed to further improve the performance of LTE/LTE-A.

Fig. 5 Mobile Broadband Data-rates/Traffic Growth

On the other hand, the revenue of mobile operators is not increasing at the same pace as the

network capacity they provide. Mobile operators voice volumes are steadily increasing and the

data volume grows quickly, but revenues are not and ARPUs are even falling in some case. In

order to face the slow growth in revenue, operators are forced to constantly hold down costs

notably operating costs. That means mobile operators must find a low cost, high-capacity

access network with novel techniques to meet the growth of mobile data traffic while keeping a

healthy, profitable growth.


2.4 Dynamic Mobile Network Load and Low BS Utilization Rate

One characteristic of the mobile network is that subscribers are frequently moving from one

place to another. From data based on real operation network, we noticed that the movement of

subscribers shows a very strong time-geometry pattern. Around the beginning of working time,

a large number of subscribers move from residential areas to central office areas for work;

when the work hour ends, subscribers move back to their homes. Consequently, the network

load moves in the mobile network with a similar patternso called "tidal effect". As shown in

Fig.6, during working hours, the core office areas Base Stations are the busiest; in the non-

work hours, the residential or entertainment areas Base Stations are the busiest.

Fig. 6 Mobile Network Load in Daytime

Each Base Stations processing capability today can only be used by the active users in its cell

range, causing idle BS in some areas/times and oversubscribed BS in other areas. When

subscribers are moving to other areas, the Base Station just stays in idle with a large of its

processing power wasted. Because operators must provide 7x24 coverage, these idle Base

Stations consume almost the same level of energy as they do in busy hours. Even worse, the

Base Stations are often dimensioned to be able to handle a maximum number of active

subscribers in busy hours, thus they are designed to have much more capacity than the

average needed, which means that most of the processing capacity is wasted in non-busy time.

Sharing the processing and thus the power between different cell areas is a way to utilize these

BS more effectively.

2.5 Growing Internet Service Pressure on Operators Core Network

With the hyper-growth of smart phones as well as emerging 3G embedded Internet Notebook,

the mobile internet traffic has been grown exponentially in the last few years and will continue

to grow more than 66x in the next 5-6 years. However because of increasingly competition

between mobile operators, the projected revenue growth will be much lower than the traffic

growth. There will be a huge gap between the cost associated with this mobile internet traffic

and the revenue generated, let alone the mobile operators needing to spend billions of dollars

to upgrade their back-haul and core network to keep up with the growing pace. This is a huge

common challenge to all the mobile operators in the wireless industry.

The exponential growth of mobile broadband data puts pressure on operators existing packet

core elements such as SGSNs and GGSNs, increasing mobile Internet delivery cost and

challenging the flat-rate data service models. The majority of this traffic is either Internet

bound or sourced from the Internet. Catering to this exponential growth in mobile Internet

traffic by using traditional 3G deployment models, the older 3G platform is resulting in huge


CAPEX and OPEX cost while adding little benefit to the ARPU. Additional issues are the

continuous CAPEX spending on older SGSNs & GGSNs, the higher Internet distribution cost, the

congestion on backhaul and the congestion on limited shared capacity of base stations.

Therefore, offloading the Internet traffic, as close to the base stations as possible, can be an

effective way to reduce the mobile Internet delivery cost.

Fig. 7 Wireless traffic on a commercial 3G

Meanwhile it is interesting to understand how people are using todays mobile internet. A recent

research paper [3] published by one major TEM may give us a glimpse of the most popular

mobile applications. It is surprising to see that people are gradually using mobile internet just

like they use the fixed broadband network. Content services which include content delivered

through web and P2P are actually dominating the network traffic. Fig.7 is an example of

wireless traffic on a commercial 3G operator. Considering this usage pattern, do we have better

choice than just blindly spending billions of dollars to upgrade back-haul and the core network?


3 Architecture of C-RAN

We believe Centralized processing, Cooperative radio, Cloud, and Clean (Green) infrastructure

Radio Access Network (C-RAN) is the answer to solve the challenges mentioned above. Its a

natural evolution of the distributed BTS, which is composed of the baseband Unit (BBU) and

remote radio head (RRH). According to the different function splitting between BBU and RRH,

there are two kinds of C-RAN solutions: one is called full centralization, where baseband (i.e.

layer 1) and the layer 2, layer 3 BTS functions are located in BBU; the other is called partial

centralization, where the RRH integrates not only the radio function but also the baseband

function, while all other higher layer functions are still located in BBU. For the solution 2,

although the BBU doesnt include the baseband function, it is still called BBU for the simplicity.

The different function partition method is shown in Fig.8.

Fig. 8 Different Separation Method of BTS Functions

Based on these two different function splitting methods, there are two C-RAN architectures.

Both of them are composed of three main parts: first, the distributed radio units which can be

referred to as Remote Radio Heads (RRHs) plus antennas which are located at the remote site;

second, the high bandwidth low-latency optical transport network which connect the RRHs and

BBU pool; and third, the BBU composed of high-performance programmable processors and

real-time virtualization technology.

RRH

RRH

RRH

RRH

RRH

RRH

RRH

Virtual BS Pool

L1/L2/L3/O&M L1/L2/L3/O&M L1/L2/L3/O&M

Fiber

Fig. 9 C-RAN Architecture 1: Fully Centralized Solution

GPS

Main Control & Clock

Core net-work

Base-band

process-ing

Transmitter/Receiver

PA&

LNA

Antenna

DigitalIF

Solution 1Solution 2

BBU RRU


RRH/L1

RRH/L1

RRH/L1

RRH/L1

RRH/L1

RRH/L1

RRH/L1

Virtual BS Pool

L2/L3/O&M L2/L3/O&M L2/L3/O&M

Fiber or

Microwave

Fig. 10 C-RAN Architecture 2: Partial Centralized Solution

The fully centralized C-RAN architecture, as shown in figure 9, has the advantages of easy

upgrading and network capacity expansion; it also has better capability for supporting multi-

standard operation, maximum resource sharing, and its more convenient towards support of

multi-cell collaborative signal processing. Its major disadvantage is the high bandwidth

requirement between the BBU and to carry the baseband I/Q signal. In the extreme case, a TD-

LTE 8 antenna with 20MHz bandwidth will need a 10Gpbs transmission rate.

The partial centralized C-RAN architecture, as shown in figure 10, has the advantage of

requiring much lower transmission bandwidth between BBU and RRH, by separating the

baseband processing from BBU and integrating it into RRH. Compared with the full centralized

one, the BBU-RRH connection only need to carry demodulated data, which is only 1/20~1/50 of

the original baseband I/Q sample data. However, it also has its own shortcomings. Because the

baseband processing is integrated into RRH, it has less flexibility in upgrading, and less

convenience for multi-cell collaborative signal processing.

With either one of these C-RAN architectures, mobile operators can quickly deploy and make

upgrades to their network. The operator only needs to install new RRHs and connect them to

the BBU pool to expand the network coverage or split the cell to improve capacity. If the

network load grows, the operator only needs to upgrade the BBU pools HW to accommodate

the increased processing capacity. Moreover, the fully centralized solution, in combination with

open platform and general purpose processors, will provide an easy way to develop and deploy

software defined radio (SDR) which enables upgrading of air interface standards by software

only, and makes it easier to upgrade RAN and support multi-standard operation.

Different from traditional distributed BS architecture, C-RAN breaks up the static relationship

between RRHs and BBUs. Each RRH does not belong to any specific physical BBU. The radio

signals from /to a particular RRH can be processed by a virtual BS, which is part of the

processing capacity allocated from the physical BBU pool by the real-time virtualization

technology. The adoption of virtualization technology will maximize the flexibility in the C-RAN

system.


Both solutions described above are under development and evaluation. They could be properly

deployed in different networks depending on the situation of the network. The following

discussion will focus on the Fully Centralized Solution.

3.1 Advantages of C-RAN

The benefits of the C-RAN architecture are listed as follows:

Energy Efficient/Green Infrastructure

C-RAN is an eco-friendly infrastructure. Firstly, with centralized processing of the C-RAN

architecture, the number of BS sites can be reduced several folds. Thus the air conditioning

and other site support equipments power consumption can be largely reduced. Secondly,

the distance from the RRHs to the UEs can be decreased since the cooperative radio

technology can reduce the interference among RRHs and allow a higher density of RRHs.

Smaller cells with lower transmission power can be deployed while the network coverage

quality is not affected. The energy used for signal transmission will be reduced, which is

especially helpful for the reduction of power consumption in the RAN and extend the UE

battery stand-by time. Lastly, because the BBU pool is a shared resource among a large

number of virtual BS, it means a much higher utilization rate of processing resources and

lower power consumption can be achieved. When a virtual BS is idle at night and most of

the processing power is not needed, they can be selectively turned off (or be taken to a

lower power state) without affecting the 7x24 service commitment.

Cost-saving on CAPEX &OPEX

Because the BBUs and site support equipment are aggregated in a few big rooms, it is much

easier for centralized management and operation, saving a lot of the O&M cost associated

with the large number of BS sites in a traditional RAN network. Secondly, although the

number of RRHs may not be reduced in a C-RAN architecture its functionality is simpler, size

and power consumption are both reduced and they can sit on poles with minimum site

support and management. The RRH only requires the installation of the auxiliary antenna

feeder systems, enabling operators to speed up the network construction to gain a first-

mover advantage. Thus, operators can get large cost saving on site rental and O&M.

Capacity Improvement

In C-RAN, virtual BSs can work together in a large physical BBU pool and they can easily

share the signaling, traffic data and channel state information (CSI) of active UEs in the

system. It is much easier to implement joint processing & scheduling to mitigate inter-cell

interference (ICI) and improve spectral efficiency. For example, cooperative multi-point

processing technology (CoMP in LTE-Advanced), can easily be implemented under the C-

RAN infrastructure.

Adaptability to Non-uniform Traffic

C-RAN is also suitable for non-uniformly distributed traffic due to the load-balancing

capability in the distributed BBU pool. Though the serving RRH changes dynamically

according to the movement of UEs, the serving BBU is still in the same BBU pool. As the

coverage of a BBU pool is larger than the traditional BS, non-uniformly distributed traffic

generated from UEs can be distributed in a virtual BS which sits in the same BBU pool.

Smart Internet Traffic Offload

Through enabling the smart breakout technology in C-RAN, the growing internet traffic from

smart phones and other portable devices, can be offloaded from the core network of

operators. The benefits are as follows: reduced back-haul traffic and cost; reduced core

network traffic and gateway upgrade cost; reduced latency to the users; differentiating


service delivery quality for various applications. The service overlapping the core network

also supplies a better experience to users.

3.2 Technical Challenges of C-RAN

The centralized C-RAN brings lots of benefits in cost, capacity and flexibility over traditional

RAN, however, it also has some technical challenges that must be solved before deployment by

mobile operators.

Radio over Low Cost Optical Network

In C-RAN architecture 1, the optical fiber between BBU pool and RRHs has to carry a large

amount of baseband sampling data in real time. Due to the wideband requirement of LTE/LTE-A

system and multi-antenna technology, the bandwidth of optical transport link to transmit

multiple RRHs baseband sampling data is 10 gigabit level with strict requirements of

transportation latency and latency jitter.

Advanced Cooperative Transmission/Reception

Joint processing is the key to achieve higher system spectrum efficiency. To mitigate

interference of the cellular system, multi-point processing algorithms that can make use of

special channel information and harness the cooperation among multiple antennas at different

physical sites should be developed. Joint scheduling of radio resources is also necessary to

reduce interference and increase capacity.

To support the above Cooperative Multi-Point Joint processing algorithms, both end-user data

and UL/DL channel information needs to be shared among virtual BSs. The interface between

virtual BSs to carry this information should support high bandwidth and low latency to ensure

real time cooperative processing. The information exchanged in this interface includes one or

more of the following types: end-user data package, UE channel feedback information, and

virtual BSs scheduling information. Therefore, the design of this interface must meet the real-

time joint processing requirement with low backhaul transportation delay and overhead.

Baseband Pool Interconnection

The C-RAN architecture centralizes a large number of BBUs within one physical location, thus

its security is crucial to the whole network. To achieve high reliability in case of unit failure, in

order to recover from error, and to allow flexible resource allocation of BBU, there must be a

high bandwidth, low latency, low cost switch network with flexible, extensible topology that

interconnects the BBUs in the pool. Through this switch network, the digital baseband signal

from any RRH can be routed to any BBU in the pool for processing. Thus, any individual BBU

failure wont affect the functionality of the system.

Base Station Virtualization Technology

After the baseband processing units have been put in a centralized pool, it is essential to design

virtualization technologies to distribute/group the processing units into virtual BS entities. The

major challenges of virtualization are: real-time processing algorithm implementation,

virtualization of the baseband processing pool, and dynamic processing capacity allocation to

deal with the dynamic cell load in system.

Service on Edge

Unlike service in a data center, distributing services on the edge of the RAN has its unique

challenges. In the following research framework part, we try to summarize these challenges

into the following three categories: services on the edges integration with the RAN, intelligence

of DSN, and the deployment and management of distributed service.


4 Technology Trends and Feasibility Analysis

In order to solve the technical challenges of C-RAN architecture, based on current technical

conditions and future development trends, we suggest to do further research in the following

areas. The purpose is to solve the low cost high bandwidth wireless signal transmission problem

based on an optical network, dynamic resource allocation and collaborative radio technology. It

also comprehends the large scale BBU pool and associated interconnection problem, virtualized

BS based on open platforms and distributed service network solutions. The following is a

detailed analysis and discussion of these challenges.

4.1 Wireless Signal Transmission on Optical Network

The C-RAN architecture, which consists of the distributed RRH and BBU, means that need to

transport untreated wireless signals between BBU and RRH. The BBU-RRH connectivity

requirements pose challenges to the optical transmission speed and capacity. Usually, optical

fiber transmission must be used to carry the BBU-RRH signal to meet the strict bandwidth and

delay requirements.

BBU-RRH Bandwidth Requirement

Air interface is upgrading rapidly, new technologies like multiple antenna technology (2 ~ 8

antenna in every sector), wide bandwidth (10 MHz ~ 20 MHz every carrier) has been widely

adopted in LTE/LTE-A, thus the bandwidth of CPRI/Ir/OBRI (Open BBU-RRH Interface) link

bandwidth is much higher than the 2G and 3G era. In general, the system bandwidth, the

MIMO antenna configuration and the RRH concatenation levels are the main factors which have

an impact on the OBRI bandwidth requirement. For example, the bandwidth for 200 kHz GSM

systems with 2Tx/2Rx antennas and 4xsampling rate is up to 25.6Mbps. The bandwidth for

1.6MHz TD-SCDMA systems with 8Tx/8Rx antennas and 4 times sampling rate is up to

330Mbps. The transmission of this level of bandwidth on fiber link is matured and economic.

However, with the introducing of multi-hop RRH and high orders MIMO supporting 8Tx/8Rx

antenna configuration, the wireless baseband signal bandwidth between BBU-RRH would rise to

dozens of Gbps. Therefore, exploring different transport schemes for the BBU-RRH wireless

baseband signal is very important for C-RAN.

Transportation Latency, Jitter and Measurement Requirements

There are also strict requirements in terms of latency, jitter and measurement. In CPRI/Ir/OBRI

transmission latency, due to the strict requirements of LTE/LTE-A physical layer delay

processing also improve the baseband wireless signal transmission delay jitter and

requirements indirectly. Not including the transmission medium between the round-trip time

(i.e., regardless of delays caused by the cable length), for the user plane data (IQ data) on the

CPRI/Ir/OBRI links, the overall link round-trip delay may not exceed 5s. The OBRI interface

requires periodic measurement of each link or multi-hop cable length. In terms of calibration,

the accuracy of round trip latency of each link or hop should satisfy 16.276ns [4].

System Reliability

For the reliability of the system, because the traditional optical transmission networks

(SDH/PTN) in the access network links provide reliable loop protection, automatic replace and

fiber optic link management function, C-RAN architecture in the access network must also

provide comparative reliability and manageability. In traditional RAN architecture, each BBU on

the access ring usually has access to the corresponding transmission equipment of the center

transmission machine room through SDH/PTN. Through the SDH/PTN ring routing and


protection function, the system can quickly switch to the safe routing mode when any point on

this loop experiences optical fiber failure, ensuring that business is not interrupted. Under the

C-RAN architecture, it also should offer a similar optical fiber ring network protection function.

Centralized BBU should support more than 10~1000 base station sites, and then the optical

fiber connected OBRI link between distributed RRH and centralized BBU is long. If only point-2-

point optical fiber transmission occurred between each distributed RRH and centralized BBU,

then any fault on the optical fiber link will lead to the corresponding RRH loosing service. In

order to ensure the normal operation of the whole system under the condition of any single

point of failure in the optical fiber, the CPRI/Ir/OBRI link connecting the BBU-RRH should use

fiber ring network protection technology, using the main/minor optical fiber of different

channels to realize CPRI/Ir/OBRI link real-time backup.

Operation and Management

At the same time, under the traditional RAN architecture, the transmission network which

consists of SDH/PTN also provides the unified optical fiber network management ability for the

access ring. This includes unified management of the access ring fiber optic link of the entire

network, supervisory control of the access ring optical fiber breakdown, etc. BBU-RRH wireless

signal transport directly on the access ring, whose CPRI/Ir/OBRI interface should also, provides

similar management ability and fit into unified optical fiber network management.

Cost Requirements

Finally, in terms of cost, the high speed optical module necessary for the CPRI/Ir/OBRI optical

interface will be amongst the important factors affecting the C-RAN economic structure.

Compared to traditional architecture, the wireless signal transmission data rate on C-RAN is

more than 100-200 times higher than the bearer service data rate after demodulation. Building

the fiber transportation network in developed city is very hard. This is less of an issue for

operators that already deploy optical fiber and particularly for operators own their own optical

network.

Although the cost of the optical fiber employing CPRI/Ir/OBRI for high speed wireless signal

transmission doesn't need to increase, the high speed optic module or optical transmission

equipment costs must compare to traditional SDH/PTN transmission equipment in order to

make C-RAN architecture more attractive on the CAPEX and OPEX fronts .Therefore, how to

achieve a low cost, high bandwidth and low latency wireless signal optical fiber transmission will

become a key challenge for realization of the future LTE and LTE network deployment by C-RAN.

For the above problems and corresponding technical progress trend, we will analyze and put

forward ideas for solving these problems.

4.1.1 Data Compression Techniques of CPRI/Ir/OBR Link

In view of the above LTE/LTE-A BBU-RRH wireless signal transmission bandwidth problems,

several data compression techniques that can reduce the burden on the OBRI interface are

being investigated to deal with the inevitable bandwidth issue, including time domain

schemes (e.g. reducing signal sampling, non-linear quantization, and IQ data compression)

as well as frequency domain schemes (e.g. sub-carrier compression).

For LTE system with 20MHz bandwidth, the BBU uses 2048 FFT / IFFT but the effective

number of subcarriers is only 1,200, so if the FFT / IFFT is implemented in the RRH, then

the Ir interface between BBU and the RRH only has to transmit effective data subcarriers,

such that the Ir interface load can be reduced about 40%, However, frequency domain

compression leads to an increase in IQ mapping complexity, which would increase the

interface logic design and processing complexity. Meanwhile, the RRH needs to process


parts of the RACH, Therefore, RRH cannot treat different RACH configurations transparently,

instead RRH needs to process RACH based on configuration. Since there are hundreds of

different configurations, each has to be controlled by different timing algorithms in the RRH,

which could greatly increase the complexity of system design. Therefore, considering the

implementation complexity and cost, such frequency domain compression is not feasible at

the moment.

DAGC time-domain based compression technology is a method used for IQ compression.

The basic principle of DAGC is to select the average power reference based on the best

baseband demodulation range, normalize the power of each symbol, and reduce the signal

dynamic range. DAGC compression will adversely affect system performance. The receiver

dynamic range of the uplink will be reduced, which leads to deterioration of the signal to

noise ratio. At the same time, the EVM indicators will worsen on the downlink. With

increased compression ratio, the system performance will deteriorate even more. Currently,

we still need to investigate the impacts caused by different compression schemes.

Table 2 lists the advantages and disadvantages of various compression schemes. As

indicated, there is no ideal OBRI link data compression scheme. More studies in this area

are required.

Table 2. Comparison of Pros and Cons for Various Data Compression Techniques

Bandwidth

Compression

Schemes

Pros Cons

Reducing signal

sampling

Low complexity;

Efficient compression to 66.7%;

Less impacts on protocols.

Severe performance loss.

Non-linear

quantization

Improve the QSNR;

Mature algorithms available, e.g. A law

and U law;

High compression efficiency to 53%.

Some impacts on the OBRI interface

complexity.

IQ data

Compression

Potential high compression efficiency;

Only need extra decompression and

compression modules.

High complexity;

Difficult to set up a relativity model;

Real-time and compression distortion

issues;

No mature algorithm available.

Sub-carrier

Compression

High compression efficiency to 40%

~58%;

Easy to be performed in downlink.

Increase the system complexity;

Extra processing ability on optical chips

and the thermal design;

High device cost;

Difficulty for maintenance;

RACH processing is a big challenge; More

storage, larger FPGA processing

capacity.

4.1.2 Transmission delay and jitter of CPRI/Ir/OBRI link

As mentioned previously, CPRI/Ir/OBRI link have strict demands on transmission delay,

jitter and measurement. However, because the link round trip delay requirements (5 us) of

the user plane data (IQ data) in CPRI/Ir/OBRI link do not include the transmission medium

round-trip time (i.e. delay in optical transmission), this requirement can be satisfied by the

existing technical conditions. At the same time, because CPRI/Ir/OBRI optical fiber routing

generally does not change with time and delay jitter caused by transmission is relatively

small, it is easy to meet the corresponding requirements.


On the other hand, because LTE/LTE-A has strict requirements about physical layer

treatment delay, CPRI/Ir/OBRI total transmission delay on the link should not exceed a

certain level. The physical layer HARQ process places the highest demand on processing

delay. HARQ is an important technology to improve the performance of the physical layer,

its essence is testing the physical layer on the receiving end of a sub-frame for correct or

incorrect transmission, and rapid feedback ACK/NACK to the launching end physical layer,

then let launching physical layer to make the decision whether or not to send again. If sent

again, the receiver does combined processing for multi-launching signal in the physical

layer, and then provides feedback to the upper protocol after demodulation success.

According to the LTE/LTE-A standard, the ACK/NACK HARQ on uplink and downlink process

should be finished in 3 ms after receiving the signals in the shortest case, which requires

that sub-frame processing delay in the physical layer should be generally less than 1 ms.

Because the physical layer processing itself takes 800-900 us, then CPRI/Ir/OBRI optical

transmission delay may be 100-200 us at the most. According to the light speed(200,000

kilometers per hour) estimated in the fiber, CPRI/Ir/OBRI interface maximum transmission

distance under the C-RAN framework is limited from 20 km to 40 km. Specific value is

related to delay margin the physical layer treatment itself.

4.1.3 Optical Transmission Technology Progress and Cost Reduction

As mentioned above, BBU-RRH wireless signal connection supporting LTE and LTE-Advance

creates new challenges to optical transmission network rates and cost. The rapid

development of the optical transmission technology provides more economic solutions to

solve the problem. A single fiber capacity of current commercial WDM system can be up to

3.2 T.10 Gpbs optical transmission technology applies generally and become fundamental

40 G system is mature and gradually being commercialized, 100 G technology is still not

mature and costs too much, there is still 2-3 years until the telecommunication

commercial level, but along with coherent technical breakthroughs, promoting of

standardization has already become a now advantage. 10GE standardization and

industrialization will greatly improve the relevant market capacity of the optical

transmission module, which will help to reduce the cost of 10 Gbps optical modules. 40GE

technology is still in the research process. On the other hand, at the access network level,

1.25 G,2.5 G EPON is already widely used in solving FTTX access, 10G PON technology can

be commercial in one or two years, the future PON technological development have several

directions like WDM-PON, Hybrid PON and 40G PON.

Similar to what the Moore's Law is doing in the transformation of the semiconductor

industry, the field of optical communication has a similar trend: Every year, the speed of

optical transmission increases while the cost of the said module declines. Transceiver

modules that are capable of supporting multi-wavelength WDM have emerged in the

market place. Since commercial LTE deployment has just begun, we can safely predict that

it will take about 5 years before the commercial LTE-A multi-carrier system deployment is

needed. By then, if the optical module advancement and cost reduction has reached an

acceptable level, then the RRH-BBU bottleneck will be effectively removed.

Figure 11 shows the 2.5G SFP and 10G SFP / XFP / XENPAK optical modules pricing trends.

We can deduce that optical modules pricing has dropped by 66% to 77% in nearly 3 years,

and the trend will continue in the coming years, further reducing the cost of optical

transmission network. If this price trend continues, it would greatly help to reduce CAPEX

of a C-RAN network.


0

500

1000

1500

2000

2500

3000

Aug-07 Feb-08 Aug-08 Feb-09 Aug-09

Pri

ce h

isto

ry o

f 2

.5G

mo

dule

s (

RM

B).

10Km 40Km 80Km

66.7%

54.2%

62.2%

60%

61.5%

35.2%

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Aug-07 Feb-08 Aug-08 Feb-09 Aug-09Pri

ce h

isto

ry o

f 1

0G

mo

dule

s (

RM

B).

550m 10Km 40Km

Fig. 11 Price history of Commercial 2.5G/10G Optical Modules

4.1.4 BBU-RRH Optical Fiber Network Protection

Although BBU-RRH direct transmission under C-RAN framework does not provide a ring

network protection function like traditional SDH/PTN, the CPRI/Ir/OBRI interface rate

standards provide a similar ring network protection function, and are supported by

manufacturers. At the same time, in order to avoid having every RRH fully occupy two

optical fibers on a physically routed pair the RRHs can be connected to each in a cascaded

manner according to the CPRI/Ir/OBRI interface specification. This permits two different

routing trunk cables to form a ring and be connected to the same BBU, as shown in Figure

10. As long as the CPRI/Ir/OBRI interface rate is high enough, the BBU-RRH ring network

protection technology can save the use of many optical fibers and ensure a short round trip

delay. Taking a TD-SCDMA system for example, a 6.144 Gpbs CPRI/Ir/OBRI link can

support 15 TD-SCDMA carriers of 8-antenna RRH and a typical TD-SCDMA macro station

with 3 sectors, 5/5/5 configuration at most. The IQ data of a RRH with three sectors

connected to the same BBU machine through two different physical routing backbone

optical cables. When a trunk cable fails, three RRHs will connect to the BBU through

another trunk cable under less than 40ms protection rotated time to guarantee that all

business does not interrupt. For lower-rate GSM system, it is even simpler to connect six or

more RRHs through such a CPRI/Ir/OBRI annular link and achieve the same functions.

However, according to LTE/LTE-A system with higher wireless signal transmission rate, it is

necessary to introduce WDM technology to realize a similar loop protection function.

Transmission ring

Trunk cable 2

Trunk cable 1

Optical

switching box

Central apparatus

room

Radio remote

head

Fig. 12 RRH Ring Protection Loop


4.1.5 Current Deployment Solutions

In order to meet the high bandwidth transmission between RRH and BBU, operators can

use different solutions based on their current transmission network resources. In China

Mobile, the current backhaul is mainly an optical transport network with three layers of

transmission network: the core transmission layer, the convergence transmission layer and

the access transmission layer. All the layers are using ring topology to provide fail safe

protection. The optical resources of different layers are similar to the following: at the core

transmission layer, each optical route has 144 to 576 fibers; at the convergence

transmission layer, each route has 96-144 fibers; while at the access transmission layer,

each route has 24-48 fibers. If the Baseband pool is located in the transmission

convergence equipment room, the optical fiber resource to and from the equipment room

determines the coverage of the baseband pool.

According to the resourcing of the optical transmission network, especially the fiber

resource in the access transmission network, there are four different solutions to carry

CPRI/Ir/OBRI over it: 1. Dark fiber; 2. WDM/OTN; 3. Unified Fixed and Mobile access like

UniPON; 4. Passive WDM. These solutions have different advantages and disadvantages,

and they are each suitable for different deployment scenarios. From the trials conducted,

for a BBU pool with less than 10 macro BSs, it is preferred to use a dark fiber solution while

other solutions still need more field tests and verification, because they may introduce new

transmission devices and associated O&M issues.

The first solution is Dark fiber. It is suitable when there is plenty of fiber resource. It is easy

to deploy if there are a lot spare fiber resources. The benefits of this solution are: fast

deployment and low cost because no additional optical transport network equipment is

needed. The concerns of this solution are: it consumes significant fiber resource, thus the

network extensibility will be a challenge; new protection mechanisms are required in case

of fiber failure; and it is hard to implement O&M, therefore it will introduce some difficulties

for optical network O&M. However, there are feasible solutions to address such challenges.

For fiber resources, if there is already a channel route available, it is fairly inexpensive to

add new fiber cables or upgrade existing fibers. To address fiber failure protection, there

are CPRI/Ir/OBRI compliant products available now that have the 1+1 backup or ring

topology protection features. If deployed with physical ring topology that provides

alternative fiber route, it will be able to provide similar recoverability capability as SDH/PTN.

For the O&M of the fiber in the access ring, we are considering introducing new O&M

capabilities in the CPRI/Ir/OBRI standard to satisfy the fiber transport network

management requirement.

The second solution is WDM/OTN solution. It is suitable for Macro cellular base station

systems when there is limited fiber resource, especially where the fiber resource in the

access ring is very limited, or adding new fiber in existing route is too difficult or cost is too

high. By upgrading the optical access transmission network to WDM/OTN, the bandwidth of

transporting CPRI/Ir/OBRI interface on BBU-RRH link is largely improved. Through

transmitting as many as 40 or even 80 wavelength with 10Gpbs in one fiber, it can support

a large number of cascading RRH on one pair of optical fiber. This technology can reduce

the demand of dark fiber, however, upgrading existing access ring into WDM/OTN

transmission network means higher costs. On the other hand, because the access transport

network is usually within a few tens of kilometers, the WDM/OTN equipment can be much

cheaper than those used in long distant backbone networks.

The third solution is based on CWDM technology. It combines the fixed broadband and

mobile access network transmission at the same time for indoor coverage with passive


optical technology, thus named as Unified PON. It can provide both PON services and

CPRI/Ir/OBRI transmission on the same fiber [5]. In this solution, an optical fiber can

support as many as 14 different wavelengths. In the UniPON standard, the uplink and

downlink channel are transmitted on two difference wavelengths, thus other free

wavelengths can be used for CPRI/Ir/OBRI data transmission between the BBU and RRH.

Because of sharing the optical fiber resources, it can reduce the overall cost. It is suitable

for C-RAN centralized baseband pool deployment of indoor coverage.

4.1.6 Summarize

Based on the above analysis, fully centralized C-RAN architecture requires a high

bandwidth, low latency, high reliability and low cost optical solution to transmit high speed

baseband signal between BBU and RRH. Its promising to find feasible solutions emerging in

the near future. However, there are still many challenges in the current solutions. For

example, current data compression schemes fail to satisfy OBRI transmission in the LTE-A

phase. The rapid development of high-speed optical modules and the associated cost

reduction is heading in the right direction but we still need a breakthrough in optical devices.

Failure protection schemes for BBU-RRH connection are able to provide similar functions to

SDH/PTN in case of fiber cut, but we still need to find solutions for unified O&M with

traditional transmission networks. UniPON based on passive WDM technology is a promising

solution for certain deployment scenarios but it must be designed to be competitive in cost.

In conclusion, we have various directions to solve the high-speed baseband signal

transmission requirement of C-RAN but we still need to explore new technology or a

combination of existing technology to find a more economical and effective solution.

Considering the technical challenges as well as the limitation in current optical network

resources, it is clear that C-RAN can be widely applied in a short time frame. Instead, a

stepped plan should be used to gradually construct the centralized network: first,

centralized deployment can be applied in some green field or replacement of old network in

a small scale. Dark fiber can be used as the BBU-RRH transmission solution. One access

ring that connects 8~12 macro sites can be centralized together, with a maximum ring

range of 40km. In the future, a larger number of macro BS in various deployment scenarios

can be further tested.


4.2 Dynamic Radio Resource Allocation and Cooperative

Transmission/Reception

One key target for C-RAN system is to significantly increase average spectrum efficiency and

the cell edge user throughput efficiency. However, users at the cell boundary are known to

experience large inter-cell interference (ICI) in a fully-loaded OFDM cellular environment, which

will cause severe degradation of system performance and cannot be mitigated by increasing the

transmit power of desired signals. At the same time, in view of the analysis, single cell wireless

resources usage efficiency is low. To improve system spectrum efficiency, advanced multi-cell

joint RRM and cooperative multi-point transmission schemes should be adopted in the C-RAN

system.

Cooperative Radio Resource Management for multi-cells

The multi-cell RRM problem has been addressed in various academic studies. Many uses

various optimization techniques in trying to determine the optimal resource scheduling and the

power control solutions to maximize the total throughput of all cells with some specific

constraints. To reduce the complexity incurred in the C-RAN network architecture and the

scheduling process, the joint processing/scheduling should be limited to a number of cells

within a cluster. The complexity of scheduling among the eNBs clusters is determined by the

velocity of mobile users and the number of UEs and RRHs in the cluster. Thus, choosing an

optimal clustering approach will require balancing among the performance gain, the

requirement of backhaul capacity and the complexity of scheduling.

As shown in Fig.13, UEs will be served by one of the available clusters which are formed in a

static or semi-static way based on the feedback or measurements reports of UEs. In this

scenario, a subset of cells within a cluster will cooperate in transmission to the UEs associated

with the cluster. To further reduce the complexity, it is possible to limit the number of cells

cooperating in joint transmission to a UE at each scheduling instant. The cells in actual

transmission to a UE are called active cells for the UE. The active cells can be defined from the

UE perspective based on the signal strength (normally cells with strong signal strength are

chosen among cells within the supercell). The activation/de-activation of a cell can be done by

a super eNB, which is the control entity in cell clustering and can adjust the sets scope based

on the UE feedback.


Cell cluster 1Cell cluster 2

Cell cluster 3

Fig. 13 The UE assisted network controlled cell clustering


Cooperative Transmission / Reception

Cooperative transmission / reception (CT/CR) is well accepted as a promising technique to

increase cell average spectrum efficiency and cell-edge user throughput. Although CT/CR

naturally increases system complexity, it has potentially significant performance benefits,

making it worth a more detailed consideration. To be specific, the cooperative transmission /

reception is characterized into two classes, as shown in Fig.14:

Joint processing/transmission (JP)

The JP scheme incurs a large system overhead: UE data distribution and joint

processing across multiple transmission points (TPs); and channel state information

(CSI) is required for all the TP-UE pairs.

Coordinated scheduling and/or Coordinated Beam-Forming (CBF)

With a minimum cooperation overhead, to improve the cell edge-user throughput via

coordinated beam-forming: No need for UE data sharing across multiple TPs; Each TP

only needs CSI between itself and the involved UEs (no need for CSI between other

TPs and UEs).

Fig. 14 JP scheme and CBF scheme

In this section, the performance of the JP scheme with intra-cell collaboration, and performance

with inter-cell collaboration in C-RAN architecture are evaluated in a TDD system. We assume

that full DL channel state information (CSI) can be obtained ideally at the eNB side. The

downlink throughput and spectrum efficiency results with different schemes in both 2 antenna

and 8 antenna configuration are shown in Fig.15. Detailed simulation parameters can be found

in [6-9].

3GPP Case 1 (TDD)


1.9 2.542.47

5.46

2.81

6.15

3.01

6.58

0

2

4

6

8

2Tx (X)/2Rx 8Tx(XXXX)/2Rx

Ave. cell spectrum efficiency (bps/Hz)

SU-MIMO

MU-MIMO

0.0560.098

0.047

0.1830.0780.227

0.101

0.266

0

0.1

0.2

0.3


Cell-edge spectrum efficiency (bps/Hz)

SU-MIMO

MU-MIMO

ITU UMi (TDD)

1.44 1.971.8

3.78

1.93

4.54

1.97

5.35

0

2

4

6


Ave. cell spectrum efficiency (bps/Hz)

SU-MIMO MU-MIMO

Intra-site CoMP C-RAN CoMP

0.0410.0520.039

0.0920.07 0.161

0.075

0.202

0

0.1

0.2

0.3


Cell-edge spectrum efficiency (bps/Hz)

SU-MIMO

MU-MIMO

Fig. 15 Compare of Downlink Throughput and SE

From the simulation results we can see, compared to the non-cooperative transmission

mechanism (MU-BF in LTE-A), the spectrum efficiency of intra-cell collaboration and inter-cell

collaboration under C-RAN architecture could achieve a 13% and 20% gain, respectively, while

the cell edge users spectrum efficiency, from the above two mechanisms can get 75% and 119%

gain respectively.

Technical Challenges

Cooperative transmission / reception (CT/CR) has great potentials in reducing interference and

improving spectrum efficiency of system. However, this technology has many problems that

need to be further studied before it can be applied to the practical networks. There are many

challenges listed as follows:

Advanced joint processing schemes

DL channel state information (CSI) feedback mechanism

User pairing and joint scheduling algorithms for multi-cells

Coordinated Radio resource allocation and power allocation schemes for multi-cells.


4.3 Large Scale Baseband Pool and Its Interconnection

Centralized Baseband Pool

There are many distributed BS products using RRH+BBU architecture in market. Some TEMs

products have realized dynamic allocation of carrier processing within one BBU to adapt to

dynamic workloads among different RRH connected to it. This architecture can be viewed as the

first step of centralized baseband pool concept, but in general a single BBU has limited

processing capability, typically only supporting about 10 macro BSs carriers. Its not yet

capable of supporting dynamic resource allocation across different BBU, thus hard to resolve

the dynamic network load in a larger area. In the current RRH+BBU architecture, the RRH is

usually connected to a particular BBU by a fixed link, and it can only transmits its baseband

signal and O&M signaling to the BBU its connected to. This makes it difficult for another BBU to

obtain any uplink baseband data from that RRH. Similarly, any other BBU has difficulty sending

downlink baseband data to this RRH. Because of this limitation, the processing resources of

different BBUs can hardly be shared: the idle BBUs processing resources are wasted and it

cannot be used to help the BBU with a heavy workload.

The centralized baseband pool should provide a high bandwidth, low latency switch matrix with

an appropriate protocol to support the high speed, low latency and low cost interconnection

among multiple BBUs. In a medium sized dense urban network coverage (approximately 25 sq.

km in area), with an average distance between BS of 500m, a centralized baseband pool that

can cover the whole area needs to support about 100 BS. For a typical TD-SCDMA system with

3 sectors per macro BS and 3 carriers/sectors, it means that the centralized baseband pool

needs to support 900 TD-SCDMA carriers. Imagine if the centralized Baseband pool coverage

is even larger, such as 15 km X 15 km, then the baseband pool would need to support up to

1000 macro BSs carriers. Because of the limitation in the high-speed differential signal

transmission, the traditional BBU architecture cannot scale up to support such capacity by

simply expanding the backplane dimensions.

Infinite Band technology can provide significant switching bandwidth (20Gbps-40Gpbs/port)

and very low switching latency. It is widely used in supercomputers. However, the cost per port

is very high (20,000RMB) and as such does not meet the C-RAN cost requirement. Inspired by

the data center networks distributed inter-connect architecture, the centralized BBU pool in C-

RAN can also use a distributed optic interconnection to combine multiple BBU into a scalable

baseband pool. Based on that, the RRHs signal can be routed to any one of BBUs in the pool.

Thus load balance according to dynamic network load among BBUs can be achieved, and

system power consumption can be reduced. It also makes the deployment of multi-point MIMO

technology and interference mitigation algorithms easier, which can improve radio system

capacity.

Dynamic carrier scheduling


The dynamic carrier scheduling of resources within baseband pools enhances redundancy of the

BBU and increases overall operational reliability of the baseband pool. When a baseband card or

a carrier processing unit fails, the work load can be promptly redistributed to other available

resources within the pool, and restore the normal operation. In addition, for areas that have

strong dynamic network load, the operator can deploy fewer baseband resources to meet the

demands of different sites that have opposite peak loads at different times. For example,

operator can use the same BBU pool with multiple RRHs to cover both residential areas and

office areas. Then dynamically allocates baseband resources to ensure basic coverage for both

areas. Remaining baseband resources can be dynamically allocated to cover the business area

during working hours and the residential area during after working hours. This will increase the

overall carrier resource utilization.

Large-scale BBU Inter-connection

A large scale baseband inter-connect solution should be able to support 10-1000 macro BS,

with the following requirements:

Inter-connection between BBUs must satisfy the wireless signals requirements of low

latency, high speed, and high reliability. The requirements are similar to the CPRI/Ir/OBRI

interface, and should support real-time transmission of 2.5/6.144/10Gbps rate.

Dynamic carrier scheduling among BBUs to achieve efficient load balance within the

system and failure protection without service interruption.

Support multipoint collaboration (CoMP). It needs to consider the data flow between

different BBUs to support collaboration radio.

Fault-tolerance. Fiber inter connection should support 1+1 failure protection, BBU frame

and baseband processing board N +1 protection to achieve high system robustness.

High scalability: it can extend the system capability smoothly without services interruption.

4.4 Open Platform Based Base Station Virtualization

Current Multi-Standard BS Solutions

Nowadays, most major mobile operators in the world have to operate multiple standards

simultaneously. It is a natural choice to use multi-mode base stations for low cost operation.

Therefore, SDR based on a common platform to support multi-standards has become the

mainstream in TEMs products. The following are the two types of multi-mode base stations.

Unified BBU system platform supporting multi-mode by plugging in different processing

boards. The processing board which supports multi-standard (such as GSM, TD-SCDMA,

TD-LTE) has a unified interface and can be plugged in the same BBU system platform.

Operators can use one set of a BBU system platform to support multi-standard operation.

In this case, some modules of BBU system such as control module, timing module and RRH


I/O modules can be shared between BBU processing boards which support different

standards. However, this structure can't share processing resources between different

processing boards and usually need to replace or add new processing board hardware for

upgrades.

Unified BBU system platform and unified processing board hardware platform to support

multi-mode through the software re-configuration. Through software upgrades or

configuration, the same processing board can support different standards (e.g. LTE or TD-

SCDMA). In some of the latest products, the RRH can also be SDR-enabled to support

different standards in the same spectrum band. This solution allows the base station to be

upgraded to a new standard without changing the hardware. However, current products

usually require the BBU to restart in order to download new DSP / FPGA software for

standards upgrade. This limits the sharing of hardware between different standards. In

fact, this prevents the dynamic resources allocation according to real-time traffic load

without interrupt of services.

Current SDR base station products partially meets the requirements of multistandards

support, however, it does not satisfy the operator flexible operation requirement of dynamically

shared resources among multiple standards, load-balancing, etc.

Evolution of Software Defined Radio

Driven by Moore's law in semiconductor industry, Digital Signal Processor (DSP) and General

Purpose Processors (GPP) have made a lot of progresses in the architecture, performance and

power consumption in recent years. This provides more choices for SDR base stations. Multi-

core technology is widely used in DSP and 3 ~ 6 cores processors have been commercially

available. At the same time, DSP floating-point processing capacity is also improving at a fast

pace. The emergence of the DSP system based on SoC architecture combines traditional DSP

core and communication accelerator together has improved the BBU processing density and

improved the power efficiency. Moreover, real-time OS running on DSP pave the path to

virtualization of DSP processing resources. On the other hand, DSP from different

manufacturers and even a same manufacturer cannot guarantee backwards compatibility. The

real-time operating systems are different from each other, and there is no de fact standard yet.

Generally BBUs based on DSP platform are proprietary platforms. And it is still difficult to

achieve smooth upgrading and resource virtualization.

Meanwhile, General Purpose Processors have progressed rapidly, and they are now capable of

efficiently processing wireless signals. Therefore, the telecom industry now has more choices

for software defined radio. Technology evolution in areas such as multi-core, SIMD (single-

instruction multiple data), large on-chip caches, low latency off-chip system memory are

facilitating the use of GPP in traditional signal processing applications such as baseband

processing in base stations. Traditional general processors usually have lower performance than

DSP in power efficiency; however, in recent years the general processor has made a lot of

improvements in this respect. Fig.14 shows the general processor technical progress in


processing performance and power consumption in nearly 6-7 years. It is can be seen that the

floating point computing capacity per watt improves very fast. These data points prove that the

evolution in GPP has made it an attractive solution for various data processing tasks in the base

station.

The advantage of GPP is that they have a long history of backward compatibility, ensuring that

software can run on each new generation of processor without any change, and this is

beneficial for smooth upgrade of the BBU. On the operating system side, there are multiple

OSs available on GPP that have real-time capability, and also allow the virtualization of BS

baseband signal processing.

Fig. 14: Compute performance evolution of GPP *

(CPUs in 50-65 watt power envelopes used as basis for comparison in graph)

Technical progress in DSP and GPP has provided more powerful signal processing with less

power consumption. This progress has made the SDR based BS solutions more attractive.

Traditional DSP has become matured solution for product, and will continue to evolve. The

advanced research on wireless signal processing on GPP has provided more choices for the base

station, and has the potential to become part of the future open, unified multi-mode BS

platform.

Base Station Virtualization

Once the large scale BBU pool with high-speed, low-latency interconnection, plus the common

platform of DSP/GPP and open SDR solution could be realized, it has set the base for a a virtual

BS.

Virtualization is a term that refers to the abstraction of computer resources. It hides the

physical characteristics of a computing platform from users, instead showing another abstract

computing platform. If such a concept can be utilized in a base station system, the operator

can dynamically allocate processing resources within a centralized baseband pool to different


virtualized base stations and different air interface standards. This allows the operator to

efficiently support the variety of air interfaces,

china mobile cran white paper v26 2014

Documents

vision of c

architecture of c

advantages of c

green ran white paper

optical network

technical challenges

dynamic mobile network

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