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Selective DF Relaying in Multi-Relay Networks With Different Modulation Levels Hamza Umit Sokun Salama Ikki Akram Bin Sediq Halim Yanikomeroglu Lakehead University Carleton University Canada Canada sikki@lakeheadu.ca {husokun,

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SLIDE 1

Selective DF Relaying in Multi-Relay Networks With Different Modulation Levels

Hamza Umit Sokun Akram Bin Sediq Halim Yanikomeroglu

Carleton University Canada {husokun, akram,halim}@sce.carleton.ca

Salama Ikki

Lakehead University Canada sikki@lakeheadu.ca

IEEE ICC, June 2014, Sydney, Australia 1

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SLIDE 2

Outline

  • Motivation, Background, and Context
  • Contributions
  • Error Rate Performance Analysis
  • Asymptotic Performance Analysis
  • Simulation Results
  • Summary and Future Work

IEEE ICC, June 2014, Sydney, Australia 2

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SLIDE 3

Motivation

  • Common assumption in cooperative relaying literature:

Same modulation levels by the source and relays – Poor spectrally efficiency

  • Allow different modulation levels at the relays opportunistically

– Better spectrally efficiency

  • Performance analysis  Protocol design
  • Interest in terminal relaying in 3GPP

IEEE ICC, June 2014, Sydney, Australia 3

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SLIDE 4

Background

BER-based selection is better than SNR-based selection, when the signals at branches have different modulation levels.

IEEE ICC, June 2014, Sydney, Australia

  • A. Bin Sediq and H. Yanikomeroglu, “Performance analysis of selection combining of signals

with different modulation levels in cooperative communications,” IEEE Trans. Veh. Technol.,

  • vol. 60, no. 4, pp. 1880–1887, May 2011.
  • A. Bin Sediq and H. Yanikomeroglu, “Selection combining of signals with different

modulation levels in Nakagami-m fading”, IEEE Commun. Letters, vol. 16, no. 5, pp. 752- 755, May 2012.

4

1 relay

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SLIDE 5

Context

Multiple relays

IEEE ICC, June 2014, Sydney, Australia 5

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SLIDE 6

D S R2 RK R1

  • Find biased SNRs

Contribution 1/4

IEEE ICC, June 2014, Sydney, Australia 6

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SLIDE 7

D S R2 RK R1

  • Find BER for selection

combining

  • Not straightforward
  • Relevance to

CoMP HARQ Relay

Contribution 2/4

IEEE ICC, June 2014, Sydney, Australia 7

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SLIDE 8

Contribution 3/4

  • Find E2E BER in a network with selection combining

IEEE ICC, June 2014, Sydney, Australia 8

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SLIDE 9

Contribution 4/4

  • Find asymptotic E2E BER in a network with selection combining

IEEE ICC, June 2014, Sydney, Australia 9

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SLIDE 10

Preliminaries

IEEE ICC, June 2014, Sydney, Australia

( )

( )

2

2 ,

i i i

M ij j M i M

c d BER Q γ γ ≈

( )

( ) ( )

2

1,1 , where 2 2 / 3 , , 2 1 lo 2, , 4 g ,

i i

i M M i i i i

M c d M M M M     = −     − ≥    =

2 2

1 1 2 1

i i i

M ij ij M M ij

d BER c d γ γ     ≈ −   +  

Point-to-Point Rayleigh BER

( )

2 log2

log 2 2 2

1 (1 ) 1 1 1 log 1 2 1

s i i N Ms s i s s i

N M SR SR M SR M s M SR

PER SER d c M d γ γ = − −         ≈ − − −     +    

Average Packet Error Rate

2

where log for Gray-coded constellations

s

SER BER M ≈

Point-to-Point AWGN BER

10

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SLIDE 11

Error Rate Performance (1/3)

For example, for a two-relay scenario, it is given as

IEEE ICC, June 2014, Sydney, Australia

End-to-End Average BER

( )

( ) , , ,

( ) 1 1 1 ( ) ( )

1

r all k e e P S i

  • r m

all i r m all

  • r m

all

P S K K SR SD SR SR comp r m k e P S e P S

BER PER BER PER PER BER

= = = ∈ ∉

     = + −             

∑ ∑ ∏ ∏ ∏

{ } { } { }

1 2 1 2 2 1 1 2 2 1 1,2

(1 ) (1 ) (1 )(1 )

SR SR SD SR SR comp SR SR comp SR SR comp

BER PER PER BER PER PER BER PER PER BER PER PER BER = + − + − + − −

  • represents the cardinality of ,
  • is r-th element power set of , i.e., ,
  • is m-th element of ,
  • is the set of all relays’ indexes, i.e., ,
  • is the average packet error ratio in link ,
  • is average BER in link ,
  • is average BER conditioned on the decoding set at destination terminal after

selection combining.

all

S

( )

r all

P S

all

S ( )

r all

P S

all

S

, (

)

r m all

P S

( )

r all

P S { }

1, ..., K

all

S =

i

SR

PER

i

S R −

SD

BER S D −

DS

comp

BER

11

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SLIDE 12

Error Rate Performance (2/3)

IEEE ICC, June 2014, Sydney, Australia

2 , 2 2 2 2 2

( 2 ) if , i 1,2,..., ( 2 ) if and , 1,2,..., , for i 1,2,..., where and are biasing factors.

S S i R R i j i i i R R i i S Rj

M M SD SD i R D comp inst M M RD SD i R D R D ij R D M M i ij M M

c Q d K BER c Q d j i j K K d d d d γ γ ρ γ γ γ ρ γ γ β γ ρ β  ≥ =  ≈  < < ≠ = =   = =

( )

1 1 1 1 1

2 1

1 1 ... 2 ...

R D i SD SD K SD R D SD i SD i R D s s SD R D R D i K i SD R D R D K

K M M SD i SD R D

BER c Q d e e d d d

γ γ ρ γ ρ γ γ γ γ ρ γ γ γ γ γ γ γ

γ γ γ

− −

∞ − − ≥ = = = =

      =          

∏ ∫ ∫ ∫

( )

1 1 1 1

and , , 1,2,..., 1 2 1

1 1 1 ... 2 ...

SD i R D R D ij R D i j i RjD R D i iK R D i R D SD i R D R D j i SD R R i R D SD R D R D i i i K i j R D R D K

j i j K K M M R D j R D SD R D

BER c Q d e e e d d d d

γ ρ γ γ β γ γ γ β γ β γ γ γ γ γ γ γ γ γ γ γ

γ γ γ γ

< < ≠ = − − − − = = =

          =              

∏ ∫ ∫

i R D i R D SD i

ρ γ γ γ ∞ = =

∫ ∫

{ }

1 decoding set 1 ,...,

and , , 1,2,..., 1

SD R D K R D SD i R D R D ij R D K i j i

K comp j i j K i

BER BER BER

γ ρ γ ρ γ γ ρ γ γ β γ ≥ < < ≠ = =

= +∑

End-to-End Average BER Conditioned on the Decoding Set

An approximate and simpler implementation of the instantaneous BER.

1 2 1 2

12

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SLIDE 13

Error Rate Performance (3/3)

IEEE ICC, June 2014, Sydney, Australia

End-to-End Average BER

( ) ( )

log2 log2

2 2 2 2 2 1 2 2 2

1 1 1 1 log 1 1 2 1 2 1 1 1 log 1 2 1

N Ms s k S s S s k S N Ms s ei s s ei

K M SR M SD M s M k M SR M SD M SR M s M SR

d d BER c M c d d d c M d γ γ γ γ γ γ

=

                            = − − − −             + +                             + − −     +       

∏

( )

( )

( )

log2 , , , ,

2 ( ) 2 2 1 1 ( ) ( ) ( ) ( ) 2 1 1

1 1 1 log 1 2 1 , , , 1 ,

N Ms r all s eo s i r m all

  • r m

all s eo r m all r m all s s s

P S K M SR M s r m e P S e P S M SR P S P S k k M M M SD k y S

d c M d c I c d I γ γ γ γ

= = ∈ ∉         = =

                   × − − −         +                 × ∞ + − ∞ 

∑ ∑ ∏ ∏ ∑ ∑

{ }

{ }

{ }

{ }

( )

( ) { }

{ }

{ }

{ }

, , ,

2 , , ( ) ( ) ( ) 2 2 1 1 1 , ,

1 1 , , , , 1 1 I , , , 1 , , , , ,

s r m all r m all r m all Ri R R i R i i i i i i

M D SD k y SD k y P S P S P S k M k M M R D M i k y R D R D k y x R D k y x

k k d HM P S HM P S c k k c d I d HM P S HM P S γ γ γ γ γ γ

        = = =

   + +               + +     + ∞ + − ∞         

∑ ∑ ∑

         

13

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SLIDE 14

Asymptotic Performance (1/2)

IEEE ICC, June 2014, Sydney, Australia

2 2

4 ,

S i S i

M M SR SNR SR

Nc d PER SNR σ

→∞

≈

2 2

4

S S

M M S SNR SD D

c d BER SNR σ

→∞

≈

2 2

1 1, 4 1

S S i i

S M NR S R S NR R S M

Nc d PER SNR σ

→∞ →∞

≈ − ≈ −

( )

( )

1 1 1 1 1 2

2 , 1,2,..., 1 1 2 1

1 1 ... 2 ... ( 1.5) = 2 (1 )

SD K SD SD i R D s s SD R D R D i K i SD R D R D s i s

K SNR i K M M SD i SD R D K M i K i R D SD M

BER c Q d d d d c K K d

ρ γ ρ γ γ ρ γ γ γ γ γ γ γ

γ γ γ ρ γ πγ

− −

∞ →∞ ≥ = = = = = − + =

  =         Γ +     +  

∏ ∫ ∫ ∫ ∏

1

( )

and , , 1,2,..., 1 2 1 1

( 1.5) 2 (1 )

i SD i R D R D ij R D i j i j i i

K K SNR i M ij j i j K K i j R D SD R D M j i

c K BER K d

γ ρ γ γ β γ

ρ β γ πγ γ

→∞ < < ≠ = + = = ≠

  Γ +   =   +    

∑ ∏

{ }

1 decoding set 1 ,...,

and , , 1,2,..., 1

SD R D K R D SD i R D R D ij R D K i j i

K comp j i j K i

BER BER BER

γ ρ γ ρ γ γ ρ γ γ β γ ≥ < < ≠ = =

= +∑

( )

( ) , , ,

( ) 1 1 1 ( ) ( )

1

r all k e e P S i

  • r m

all i r m all

  • r m

all

P S K K SR SD SR SR comp r m k e P S e P S

BER PER BER PER PER BER

= = = ∈ ∉

     = + −             

∑ ∑ ∏ ∏ ∏

1 1 2 2 3 3 4 4

14

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SLIDE 15

Asymptotic Performance (2/2)

IEEE ICC, June 2014, Sydney, Australia

Asymptotic BER

( )

, , ,

2 2 1 1 ( ) 1 1 ( ) ( ) 1 , 2 2 2 2 2 ( ) 2 2 1 ,

4 1 ( ( ) 1.5) 2 (1 ( 4 ) 4 )

r all

  • r m

all eo r m a S S S k ll s r m al S l s S S i

K SNR K k P S K r m e P S P S M r m all i P S i R D SD r m M M M SR M SD M M S l M R al

BER SNR SNR c P S P Nc c d d Nc d S d ρ σ π σ σ σ σ

→∞ + = = = ∉ − + =

  =           +       Γ + ×     +  

∏ ∑ ∑ ∏ ∏

( )

, , , , ,

1 ( ) 1 ( ) ( ) , 2 ( ) 1 ( ) 1 2 2 2 1 1 ,

1 ( ( ) 1.5) 1 2 (1 ( ) )

r m all r m all r m all i r m all r m all j i i

P S P S P S i M r m all ij P S P S i j R D SD R D r m all M j i

SNR c P S SNR P S d ρ β σ πσ σ

+ + + = = ≠

        Γ +    +    +      

∑ ∏

15

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SLIDE 16

Simulation Results

  • Fig. 2. Asymptotic BER performance of BER-based selection

scheme for two-relay and three-relay scenarios, assuming bits. Although both BER- based selection scheme and SNR-based selection scheme achieve the same diversity order, BER-based selection scheme achieves higher SNR gain for all cases. IEEE ICC, June 2014, Sydney, Australia

  • Fig. 1. BER performance of BER-based selection scheme for two-relay

scenario, assuming bits. It is clear from the figures that the derived BER expressions and the simulation results are in excellent agreement.

1 2 1 2

10, 10, 10, , ,

SR SR SD R D R D

γ γ γ γ γ γ γ γ γ γ = + = + = − = = 264 N =

1 2 3 1 2 3

10, 10, 10, 10, , , ,

SR SR SR SD R D R D R D

γ γ γ γ γ γ γ γ γ γ γ γ γ γ = + = + = + = − = = = 264 N = 16

γ−10 γ γ γ+10 γ+10

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SLIDE 17

Summary

Selection combining of signals with different modulation levels in a relay network

  • Biased SNRs for selection decision
  • BER for selection combining
  • E2E BER in a network
  • Asymptotic E2E BER in a network

IEEE ICC, June 2014, Sydney, Australia 17

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SLIDE 18

Future Work 1

  • ICC 2014 + channel estimation errors + power control.
  • H. U. Sokun, A. Bin Sediq, H. Yanikomeroglu, and S. Ikki, “Impact of

Channel Estimation Errors in Selective Decode-and-Forward Relaying with Different Modulation Levels in a Multi-Relay Network”, under review in IEEE Trans. Commun.

IEEE ICC, June 2014, Sydney, Australia 18

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SLIDE 19

Future Work 2

  • Modulation level and transmission mode joint selection.
  • H. U. Sokun, H. Yanikomeroglu, and A. Bin Sediq, “Modulation level and

transmission mode joint selection in two-hop decode-and-forward cooperative relaying”, under preparation.

  • H. U. Sokun, H. Yanikomeroglu, and A. Bin Sediq, “Spectrally efficient

selective decode-and-forward relaying in multi-relay adaptive cooperative systems”, under preparation.

  • S. Hares, H. Yanikomeroglu, and B. Hashem, “Diversity and AMC (adaptive modulation and

coding)-aware routing in TDMA multihop networks”, IEEE Globecom 2003.

IEEE ICC, June 2014, Sydney, Australia 19

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SLIDE 20

Future Work 3

  • Modulation level and transmission mode (route) joint selection with

maximum-likelihood receiver.

  • A. Bin Sediq and H. Yanikomeroglu, “Performance analysis of soft-bit maximal ratio

combining in cooperative relay networks”, IEEE Trans. Wireless Commun., vol. 8, no. 10, pp. 4934-4939, Oct. 2009.

IEEE ICC, June 2014, Sydney, Australia 20

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SLIDE 21

Future Work 4

  • Joint space-time coding and routing decisions

IEEE ICC, June 2014, Sydney, Australia 21

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SLIDE 22

Thank you!

IEEE ICC, June 2014, Sydney, Australia 22

This work is supported in part by Huawei Canada Co., Ltd., and in part by the Ontario Ministry of Economic Development and Innovation’s ORF-RE (Ontario Research Fund - Research Excellence) program.