By

Mohamed Aref

Teaching AssistantElectrical Engineering Dept., Suez Canal University Email: mattia@eng.suez.edu.eg

Challenges in

Wireless

Communication

2

Multipath and

Fading

MIMO and

DiversityReceive Diversity

/Maximum ratio

combining (MRC)

Alamouti Space

Time Block

Coding Scheme

MIMO EvolutionCoordinated Multi

point (CoMP)Level of

Cooperation and

Architecture

CoMP System

Model

High data rate demand

Lightweight and simple remote terminals

Mobility and portability

Interference and noise

Quality of service QoS

Security and Privacy

3

Line of sight LOS

Reflection

Scattering

Diffraction Rx anntena

Tx anntena 4

5

Bc :Coherence bandwidths(t)

t

s(t)

t

s(t)

t

s(t)

t

Destructive interference Constructive Interference

5

6

Tc :Coherence Time

7

8

8

Frequency selective Time variance

9

•Frequency diversity

•Time Diversity

•Polarization Diversity

•Space Diversity

Diversity Types

•Multiplexing

•Beamforming

MIMOFunctions

10

Tx1

Rx1

Rx2

)(1 tr

)(2 tr

11

Select the highest power gain branch.

11

12

threshold

Ant. Sw.Switch to the max power gain antenna when the current one falls below a given threshold.

12

13

2211 rhrhZ

21 ararZ

Each signal branch weighted with the same factor, irrespective of the signal amplitude.

Each signal branch is multiplied by a weight factor that is proportional to the signal amplitude.

13

14

Maximum likelihood detector

1h 2h

1s

Channelestimator

Channelestimator

1r

2Rx

2n1n

1Tx

1s

2r

1Rx

**

1111 nshr Received signals

ReceiverCombining

scheme

Transmitsymbols 1s

2122 nshr

1~s

22111

2

2

2

1

22111

)(

~

nhnhshh

rhrhs

)(

~ˆ

2

2

2

1

11

hh

ss

Detector

1h

2h

1

11

jehh

2

22

jehh

Interference and noise

14

122111 nshshr 212212 nshshr

22111~ rhrhs

21122~ rhrhs

t Tt

1s

2s

*

2s

*

1s

1Tx

2Tx

time

antennas

AlamoutiEncoding

Received signals

AlamoutiDecoding

Transmitsymbols

21, ss

Combiner

Detector

Channelestimator

1Tx 2Tx

2r

1s 2s*

2s*

1s

1h 2h

1r

1n

2n

2h1h

1h

2h

1~s 2

~s

xR

1s 2s

15

Detector

2h1h 1~s 2

~s

1s 2s

22111

2

2

2

1

22111

)(

~

nhnhshh

rhrhs

12212

2

2

2

1

21122

)(

~

nhnhshh

rhrhs

)(

~ˆ

2

2

2

1

11

hh

ss

)(

~ˆ

2

2

2

1

22

hh

ss

Detector

1616

0 2 4 6 8 10 12 14 16 18 2010

-4

10-3

10-2

10-1

100

Eb/No (dB)

BE

R

Transmit vs. Receive Diversity

No Diversity (1Tx, 1Rx)

Alamouti (2Tx, 1Rx)

Maximal-Ratio Combining (1Tx, 2Rx)

3 dB

• The performance of Alamoutischeme with two transmitters anda single receiver is 3 dB worsethan two-branch MRRC.

• Each transmit antenna radiateshalf the energy in order to ensurethe same total radiated power aswith one transmit antenna.

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1122111111 nshshr 1212121112 nshshr

22222112122111111~ rhrhrhrhs

22122122121111212~ rhrhrhrhs

t Tt

1s

2s

*

2s

*

1s

1Tx

2Tx

time

antennas

AlamoutiEncoding

Received signals

AlamoutiDecoding

Transmitsymbols

21, ss

1Rx

2Rx 2122211221 nshshr 2212221222 nshshr

Combiner

Detector

Channelestimator

1Tx 2Tx

1s 2s

*

2s*

1s

11r

21n

12h11h

11h

12h

1~s 2

~s

2Rx

Channelestimator

22h21h

22n11n

12n

11h12h

21h

21h

22h

22h

2s1s

12r21r

22r

1818

22222112122111111

2

22

2

21

2

12

2

11

22222112122111111

)(

~

nhnhnhnhshhhh

rhrhrhrhs

21222212112112112

2

22

2

21

2

12

2

11

22122122121111212

)(

~

nhnhnhnhshhhh

rhrhrhrhs

)(

~ˆ

2

22

2

21

2

12

2

11

11

hhhh

ss

Detector

)(

~ˆ

2

22

2

21

2

12

2

11

22

hhhh

ss

19

• The Alamouti scheme provides similarperformance to MRC regardless of theemployed coding and modulation schemes.

• The scheme does not require any feedbackfrom the receiver to the transmitter and itscomputation complexity is similar to MRC.

•No bandwidth expansion needed, as theredundancy added in space.

• The scheme can easily be generalized to 2transmit antennas and M receive antennasto provide diversity order of 2M.

• Alamouti schemes is the basic for what iscalled STBC.

• An extension for the STBC is the OSTBCwhich is widely used (e.g. LTE).

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21

Single-UserMIMO

Multi-UserMIMO

21

NetworkMIMO

MassiveMIMO

•In conventional wireless cellular systems, signal processing is performed in each cellindependently; out-of-cell interference is treated as background noise.

•Base stations from different cells communicate with their respective remote terminals only.

BS1BS2

UE1

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•That inter-cell interference can be seen as another resource if base stations cooperativelyprocess signals. Thus interference may be exploited, or coordinated, instead of removing it.

BS1BS2

UE1

•Such techniques are often referred to as virtual MIMO, network MIMO, Cooperative MIMO, Multi-Cell MIMO, or more recently, Coordinated Multi-Point (CoMP).

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•The main idea of CoMP is as follows: when a UE is in the cell-edge region, it may be able to receive signalsfrom multiple cell sites and the UE’s transmission may be received at multiple cell sites regardless of thesystem load.

•Base stations no longer tune separately their physical and link/MAC layer parameters (power level, time slot,subcarrier usage, beamforming coefficients etc.) or decode independently of one another, but insteadcoordinate their coding or decoding operations on the basis of global channel state and user data informationexchanged over backhaul links among several cells.

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•The transmission to a single scheduled UE is performed by a unique BS (each UE receives the datafrom its serving BS).

•However; the scheduling, including any transmission weights, is dynamically coordinated betweenthe BSs in order to control and/or reduce the unnecessary interference between differenttransmissions.

•In principle, the best serving set of UEs will be selected so that the transmitter beams areconstructed to reduce the interference on other UEs, while increasing the served UE’s signal strength.

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•The data is simultaneously transmitted from multiple BS to each UE.

•So, the multi-point transmissions will be coordinated as a single transmitter with antennas that are geographically separated.

•JP requires the exchange of UE data among BSs as well as UE channel information and consequently, requires significant backhaul resources.

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•UE sends back its estimated and quantized channel state information (CSI) toall the cooperative BSs through individual feedback links.

•Each BS unilaterally optimizes the linear precoding matrix, based on itsgathered global CSI.

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•UE estimates the channel state information (CSI) of all cooperating BSs, quantizes it and sends to its anchor BS.

• The quantized CSI received at each individual BS is reported to the Central Unit (CU).

•The CU jointly performs linear precoding and sends back the precodingmatrices to each BS.

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•One fundamental challenge facing CoMP is the large network infrastructure required between cooperatingbase stations, typically referred to as backhaul.

•Introducing cooperation between base stations can easily lead to yet another n-fold increase of backhaulinfrastructure unless smart and backhaul-efficient cooperation techniques are employed.

•CoMP was introduced mainly for the cell-edge users, therefore it is expected that these users should takemore in the backhaul than the cell center users.

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•For CoMP model, the CS and JP schemes are based on the use of the SINR as the performance metric that needsto be maximized in order to increase the overall cell throughput.

•Let 𝑁 cells and 𝐾 users per cell with 𝑁𝑡 antennas at each base-station. antenna at each remote user.

•Let Si be a complex scalar denoting the information signal for the i th user, Wi be its associated beamformingvector, and Hi the channel vector from the cell to i th user.

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•The signal-to interference- plus-noise ratio (SINR) at the input of the receiver(i th user) is given by:

0

/

2

i

2

i

i||||

||||SINR

NHw

Hw

ik

k

i

Interference from other base stations

Noise

Desired power from the serving BS

31

32

• Leakage refers to the interference caused by the signal intended for a desired UE on the remaining UEs. That is, leakage is a measure of how much signal power leaks into the other UEs.

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•The performance criterion for choosing the precoding/beamforming weighting vectors will be based on maximizing SLNR for all UEs.

•The leakage-based precoding/beamforming leads to a decoupled optimization problem and admits an analytical closed form solution.

•The SLNR at the i th UE over can be expressed as:

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•S. M. Alamouti, “A simple transmitter diversity scheme for wireless communications,” IEEE J. Select. Areas Commun., Oct. 1998, vol. 16, pp.1451–1458.

•Jerry R. Hampton, “Introduction to MIMO Communications”, Cambridge University Press, 2014.

•R. Irmer, H. Droste, P. Marsch, M. Grieger, G. Fettweis, S. Brueck, H.-P. Mayer, L. Thiele, and V. Jungnickel, “Coordinated multipoint: Concepts, performance, and field trial results,” IEEE Communications Magazine, vol. 49, no. 2, pp. 102 –111, feb 2011.

•N. Seifi, M. Viberg, J. Robert W. Heath, J. Zhang, and M. Coldrey,“Coordinated single-cell vs multi-cell transmission with limited-capacity backhaul,” in Proc. IEEE Asilomar Conf. on Signals, Syst. and Comput.,Nov. 2010.

•Musa Ali Abu-Rgheff, “Introduction to CDMA Wireless Communications”, Academic Press, 2007.

•Hamid Jafakhani, “Space-Time Coding Theory and Practice”, Cambridge University Press, 2005.

•Vigay K. Garg, “Wireless Communications and Networking”, Elsevier Inc., 2007.

•Yong Soo Cho, Jaekwon Kim, “MIMO-OFDM wireless communications with MATLAB”, John Wiley & Sons (Asia) Pte Ltd, 2010.

•Other internet resources.

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