Interference Mitigation by MIMO Cooperation and Coordination - Theory and Implementation Challenges

Vincent Lau Dept of ECE,

Hong Kong University of Science and Technology

Background

2

Traditional Interference Management in Cellular Systems

n  Frequency Reuse: ¬  Static spectrum sharing; TDM within

each cell (GSM) ¬  Adjacent cells use different frequency ¬  Widely used for voice communication ¬  Coverage radius reduced and low

spectral efficiency

n  CDMA/OFDMA & Scheduling: ¬  Universal frequency reuse is possible ¬  Interference Averaging:

n  Spread spectrum in time-domain (CDMA) or frequency domain (OFDMA)

¬  Statistical multiplexing of time-frequency

¬  More signal processing and complicated resource allocation

¬  The system is highly interference-limited

3

F1

F3

F2

F2

F3

F2

F3

F1

F3

F1

F2

F1

F2

F1

F3

F1

F1

F3

F2

Frequency Reuse(reuse 3)

CDMA

OFDM

Spatial Interference Mitigation using MIMO Technology

n  Multiple antennas provides spatial degrees of freedom for interference mitigation

n  Beamforming has been widely used for spatial interference mitigation ¬  SINR is a function of T, R and q

¬  t: trade-off between controlling interference to others and maximizing signal power

¬  r: trade-off between suppressing interference and maximizing signal power

4

Transmi(ers   Receivers  

1,1H

1,2H

2,3H3,3H

1 1,p t

2 2,p t

3 3,p t

1r

2r

3r

1

1

1

,

[ ,..., ] (power vector) { ,..., } (Tx beamforming vectors) { ,..., } (Rx beamforming vectors) (channel matrix from Tx to Rx )

TL

L

L

l k

p p

k l

===

pT t tR r rH

Successive Interference Cancellation (SIC) and Dirty Paper Coding (DPC)

n  SIC for uplink receiving

n  DPC for downlink transmitting [M. Costa, TIT83]

5

Decoder User 1

Encoder User 1

Decoder User 2

Encoder User 2

-+

-+

Decoder User L

…

…

y

1b̂ 2b̂ b̂L

DPC Encoder 1

DPC Encoder 2

DPC Encoder L

Concatenation

Pre-coder

It is convenient to simply view DPC as successive interference pre-cancellation at the Tx.

Achievements and Limitations of Existing Interference Mitigation Technologies

n  Achievements ¬  Beamforming + DPC achieves the capacity of single cell MIMO

downlink ¬  Beamforming + SIC achieves the capacity of single cell MIMO

uplink ¬  Simple beamforming scheme (e.g., zero-forcing) + user selection

achieves a large portion of the capacity

n  Limitations ¬  The inter-cell interference is not handled and is treated as noise ¬  The performance of the system is limited by inter-cell interference ¬  The cell edge users suffers from bad performance

n  This motivates the idea of inter-cell interference (ICI) mitigation by cooperation and coordination between BSs

6

Theory of Co-MIMO

7

Joint processing

I

I

I

I

I

I

Ø  Multiple BSs collaborate to mitigate ICI or align interference for cancellation. Ø  Improves cell-edge performance and overall throughput.

Multi-cell environment with frequency reuse factor 1

Optical fiber

Optical fiber Optical fiber

interference

Basic Concepts of Cooperative and Coordinative MIMO

8

(1) Cooperative Zero-Forcing Beamforming (ZFBF)

2h1h

1e

2e

1 1g t The direction of the projection gives transmitter vector, while the norm square of the projection gives the equivalent channel

The mutual interfering multi-user channel is decomposed into multiple parallel independent SISO channels:

T1  

R2  T2  

R1  

21 1 1g = h t

22 2 2g = h t

The optimal power allocation is easy, e.g., Water-filling is optimal for sum rate maximization with sum power constraint

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ZFBF on a Larger dimension Signal Space à achieve full DoF

(2) Coordinated Zero-Forcing (IA) n  Consider a MIMO cellular network consisting of three BSs and three MSs,

where each node has 2 antennas and each BS delivers 1 data stream.

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(2) Coordinated Zero-Forcing (IA) n  Breakthrough performance

¬  Interference alignment (IA) achieves the optimal throughput scaling law w.r.t. SNR in MIMO interference networks and MIMO-X networks [V. R. Cadambe, S. A. Jafar, and S. Shamai, TIT 08], [V. R. Cadambe and S. A. Jafar, TIT08].

¬  Famous for the saying “No matter how many people come to share the cake, everyone can get a half.”

n  Limitations ¬  The feasibility issue arises without infinite dimension symbol

extension [C. M. Yetis, S. A. Jafar, and A. H. Kayran, TSP 10]. ¬  Requires perfect CSI: “Small channel estimation errors can be

tolerated, while larger errors reduce the diversity gain significantly.” [A. Sezgin, S. A. Jafar, and H. Jafarkhani, GlobalCOM 09’]

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(K/2)log SNR

n  Co-MIMO with full cooperation ¬  All CSI and data symbols are collected at a central processor (CP) à heavy backhaul

consumption ¬  A virtual MIMO BC/MAC is created for the transmission of all users ¬  A user is served by all BSs – a big MIMO!

n  Coordinated MIMO without Cooperation ¬  The CP only collects CSI à limited backhaul consumption ¬  The CP jointly optimize the user scheduling, power allocation and beamforming

vectors of all BSs ¬  A user is only severed by one BS, the signals from other BSs are treated as interference

n  Co-MIMO with limited cooperation ¬  In practice, the capacity of backhaul is limited ¬  Co-MIMO is “more expensive” compared with Coordinated MIMO ¬  We have to quantize the data symbols and/or only exchange part of the data symbols

Different Levels of Cooperation

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Standardization in LTE

13

Related Standard Activities in LTE Advanced n  Coordinated multipoint transmission/reception (CoMP)

¬  Improve coverage, cell-edge throughput, and/or system throughput n  CoMP schemes (especially DL) identified in LTE-A (3GPP TR 36.814)

¬  Joint processing/transmission (multipoint transmission to single UE) (a) Coherent transmission (joint precoding)

(b) Non-coherent transmission (independent precoding)

¬  Coordinated scheduling/beamforming (data is transmitted only from one cell site, and scheduling/beamforming is coordinated among cells)

(a) Coordinated scheduling (ICIC with fast cell selection (FCS)) (b) Coordinated beamforming (space-domain fast ICIC)

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Practical Challenges and Issues

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n  Backhaul constraint ¬  Backhaul latency ¬  Capacity constraints

n  CSI Acquisition n  Synchronization

¬  Timing Sync ¬  Frequency offsets Sync

Practical Challenges and Issues

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n  Backhaul capacity requirements ¬  Co-MIMO requires the exchange of a large amount of information ¬  Depending on the backhaul technology, the backhaul capacity may or may not support

Co-MIMO operation ¬  Methods to reduce the Backhaul burden for Co-MIMO:

n  Quantizing baseband signals n  Cell Clustering (Q: What’s the optimal number of cooperative cells) n  Optimized data sharing via a rate splitting

n  Backhaul Latency requirements ¬  Backhaul Latency must be small compared to channel coherent time

Backhaul Constraint

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Typical Backhaul Latency in LTE system

n  Objective: ¬  Accurate channel estimation (CE) with moderate overhead is basis of any

advanced Co-MIMO scheme. n  Challenges:

¬  High # of channel components per cooperation area ¬  Multi cell environment with strong inter cell interference ¬  Strong variation of path loss over different cells ¬  Fast outdating of CSI ¬  Larger CSI delay due to cooperation ¬  Pilot Pollution between Cells

n  Possible Research Activities: ¬  Exploiting channel reciprocity ¬  Overhead reduction schemes (compression techniques) ¬  Accurate CSI estimation under strong inter cell interference ¬  Codebook design under strong variation of path loss ¬  Robust CSI prediction schemes

CSI Estimation Quality

1/1/2009 18

n  Feedback of channel information ¬  Allows transmitter adaptation and enables interference avoidance ¬  Consumes reverse link capacity: tradeoff performance gain vs. reverse link penalty

n  Some approaches: ¬  Hierarchical feedback: provide more information on stronger (more relevant)

transmitters ¬  Feedback compression: Lossless vs. lossy ¬  Channel tracking: only provide feedback info for channel evolution ¬  Feedback combined with channel prediction ¬  Two-step scheduling: Coarse CSI (e.g., SINR) feedback for scheduling and refined CSI

feedback for power allocation and pre-coder calculation

CSI Feedback design for Co-MIMO

1/1/2009 19

n  For Co-MIMO, the transmission from multiple BSs must be synchronized. ¬  OFDM with CP allows some margins in timing sync. ¬  However, large distances between the base stations result in large timing

offsets which may exceed CP length and lead to inter-symbol interference n  Sync using primary clock reference

¬  Primary clock boards of cooperative BSs is synchronized to a common external reference clock

¬  Commercial Rubidium- and crystal-based reference clocks can be phase-locked to the GPS.

n  Network synchronization ¬  Suitable for indoor BSs where GPS signal may be blocked ¬  Precise timing protocol (PTP) specified in IEEE 1588 standard is a good

candidate ¬  Packet delay spread must be kept small to achieve high accuracy of timing

sync: give higher priority for PTP packets

Timing Synchronization

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n  CFO causes inter-carrier interference in OFDM systems n  Challenges of CFO Sync for Co-MIMO:

¬  Each receiver need to estimate multiple CFOs of multiple BSs ¬  CFO compensation at the Rx side requires high complexity equalizer ¬  CFO compensation at the Tx side needs CFO feedback from the receiver

Carrier Frequency offsets (CFO) Synchronization

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Performance under Practical Constraints

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Flexible Partial Cooperative MIMO n  Consider a MIMO downlink cellular network with B Basestations (BSs)

and N mobile users (MSs) [H. Huang and V. Lau].

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Flexible Partial Cooperative MIMO n  Performance and insight:

¬  Suppose the BSs are symmetrically distributed along a line and the pathloss grows exponentially w.r.t. distance.

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(1) Simulation Results: CDF of downlink user rates for different backhaul capacities per BS.

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No Coop

Full Coop

Tradeoff between user rates and backhaul capacity

USRP Platform Overview n  The universal software radio platform (USRP) demonstrates a wireless

radio system using a general purpose PC n  Key components of the USRP platform are:

¬  General purpose PC ¬  Universal software radio platform (USRP) board ¬  Transceiver board ¬  Indoor antennas ¬  GNU Radio (software development toolkit) ¬  Hydra (wireless testbed which supports most features specified in the IEEE 802.11n

standard)

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Host PC

TransceiverBoard

TransceiverBoard

USB

Tx

Rx

Tx

Rx

USRP Board

Connection Diagram of the USRP Board

E100 Embedded platform

Hardware Configuration of Co-MIMO Uplink

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h12

XCVR2450Board

XCVR2450Board

LANcable

Tx/Rx

Tx/RxUS

RP

Boa

rdHost PCUSB

MS #1

US

RP

Boa

rd

Host PCXCVR2450Board

USBTx/Rx

MS #2

US

RP

Boa

rd

XCVR2450Board

XCVR2450Board

Tx/Rx

Tx/RxUS

RP

Boa

rd

USB

BS #1

BS #2

XCVR2450Board

Tx/RxHost PC

Host PC

USBh11

h22

y1

y2

x1

x2

h21

BS Setup MS Setup

Upper-level Protocol and Physical Layer scheme

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TS from MS1

TS from MS2

Data from MS1

Data from MS2

MS1:

MS2:

BS1

BS2

Send CSI to BS1 via Socket communication

BS1

BS2

BS1 calculates ZF receive vectors r1,r2 and Send r2 to BS2

BS1

BS2

BS2 send r2^T*y2 to BS1, BS1 decode x1 using r1^T*y1+ r2^T*y2

Time diagram of Data transmission from MSs

Cooperative receiving at the BSs (only for decoding of x1)

Physical layer scheme: OFDM with 56 data subcarriers Cooperative receiving based on Zero-Forcing (ZF) detection at BSs Constant transmit power and uniform power allocation over subcarriers at MSs

(1) System Parameters for the Co-MIMO Experiment

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Specification Value MCS index 3 Modulation 16QAM Coding Rate R 1/2 Spatial stream 1 Data rate 26.0 Mb/s Distance 2m No. of packet 1000 packets Data bits in a packet 1000 bits / packet Signal transmit gain 5000 to 9000 Interference transmit gain 6000, 9000 Maximum transmit power 50 mW Carrier frequency 2.4 GHz Transmit antenna type 5 dBi omni-directional Receive antenna type 5 dBi omni-directional

(1) Co-MIMO Experiment Results

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Verify the cooperative gain under some practical constraints: Ø  CSI estimation error Ø  Timing/CFO sync error Ø  Practical modulation and coding scheme

(1) Implementation Issues n  Large CSI feedback delay

¬  Each CSI training costs about 10ms ¬  CSI Feedback costs about 10ms ¬  If exhaustive search is used to find the best BF vector in the codebook, it takes about

1ms for each subcarrier even when the codebook size is reduced to 256 ¬  According to channel correlation tested over time, the feedback delay must be kept

within 70ms to achieve 20db suppression gain.

31 0 5 10 15 20 25 30 35 40 45 500.982

0.984

0.986

0.988

0.99

0.992

0.994

0.996

0.998

1

1.002

X: 7Y: 0.9953

average time correlation over 56 subcarriers

per 10ms

Solutions: 1. Use structured codebook to reduce the searching time 2. Only feedback CSI for two subcarriers by exploiting the channel correlation over subcarriers

Conclusion: CSI feedback delay is a serious problem in practical implementation!

(2) System Parameters for the Coordinated MIMO Experiment

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Specification Value MCS index 1 Modulation QPSK

Coding Rate R 1/2 Spatial stream 1 Data rate 13.0 Mb/s Distance 2m

No. of packet 5000 packets Data bits in a packet 1000 bits / packet Signal transmit gain 6000 to 9000 Interference transmit gain 6000 to 9000 Maximum transmit power 50 mW

Carrier frequency 2.4 GHz Transmit antenna type 5 dBi omni-directional Receive antenna type 5 dBi omni-directional

(2) Coordinated MIMO Experiment Results

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6000 6500 7000 7500 8000 8500 900010-2

10-1

100

Tx2 Interference

Rx1

Pack

et E

rror R

ate

(PER

)

Rx1 PER - Tx2 Interference Curve (MCS1) (Tx1 Gain = 9000)

Coordinated MIMORandom Beamforming

Verify the coordination gain under some practical constraints: Ø  CSI estimation error and feedback delay Ø Timing/CFO sync error, Ø Practical modulation and coding scheme

(3) Energy Saving Performance [Cui’04]

n  Not always “the more Tx antennas, the better”! n  Not always “the more cooperative BSs, the better”! n  Effect of Pcct is significant when Pcct is non-negligible from the total power consumption

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Tx 1

Tx 2 Tx 1 Rx 1

Rx 1

Tx 1 to Rx 1 without any help (SISO link) Cooperative MIMO without CSIT (MISO)

Transmission energy per bit (exclude Pcct ) Total energy per bit (include Pcct )

Using Alamouti scheme with BPSK modulation in both typology

Due to Pcct effect

Due to NO Pcct

Conclusion

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(1) Summary of Co-MIMO and Coordinated MIMO

36

Coordinated MIMO: • Moderate performance gain • Light backhaul burden • Insensitive to Sync error • Easier for distributed Implementation • Optimal transmission scheme is unknown

Co-MIMO: • Largest performance gain • Heavy backhaul burden • Sensitive to Sync error • Centralized Implementation • Optimal transmission scheme is known

What’s the best tradeoff between coordination and cooperation?

(2) Summary of Major Implementation Challenges

n  Advanced backhaul technologies to meet the requirement of Co-MIMO n  CSI Estimation and Feedback

¬  Overhead of training ¬  Feedback delay makes CSI outdated

n  Scalable Implementation ¬  How to adapt the cooperative level according to the network state and users’

requirement? n  Adapting the number of cooperative cells for each user n  Adapting the amount of information exchanged : From full cooperative to

coordinated MIMO n  How to make users operating at different cooperative levels co-exit?

¬  How to balance between centralized and distributed control? n  Co-MIMO and Coordinated MIMO in fast fading channel

¬  A thorough study on the performance gain of open loop Co-MIMO is still lacking

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n  Energy per bit metric n  Circuit power consumption Pcct is constant as long as

transmission rate ≠ 0 ¬  Further complicates the Co-MIMO and Coordinated MIMO

design n  The choice of # of Tx antennas is a combinatorial problem

¬  Not always use all the Tx antennas ¬  Not always involve in more cooperative BSs ¬  Effect of Pcct is significant when Pcct is non-negligible from the

total power consumption

(3) Summary of the Green Aspects of Co-MIMO and Coordinated MIMO

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(4) Techniques Beyond Physical Layer: Interference-Aware Networking

n  Physical Layer Technologies ¬  Coordinated MIMO

n  Spatial interference mitigation via signal processing techniques n  Infrastructure based MIMO/OFDM Networks, Multi-channel Mesh, Multi-hop

Cooperative Systems

¬  Cooperative MIMO n  resolve interference issues in Cellular Systems via data cooperation

n  • System Level Technologies ¬  Interference-Aware Networking

n  Exploit knowledge of interference profile in MAC and networking protocol designs

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