Improving spectrum access using a beam-forming relay scheme for cognitive radio transmissions

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Published in IET CommunicationsReceived on 22nd July 2013Revised on 6th December 2013Accepted on 12th January 2014doi: 10.1049/iet-com.2013.0646

094The Institution of Engineering and Technology 2014

ISSN 1751-8628

Improving spectrum access using a beam-formingrelay scheme for cognitive radio transmissionsWael Jaafar1, Wessam Ajib2, David Haccoun1

1Department of Electrical Engineering, École Polytechnique de Montréal, Montreal, Quebec, H3T 1J4, Canada2Department of Computer Sciences, Université du Québec á Montréal, Montreal, Quebec, H2X 3YZ, Canada

E-mail: [email protected]

Abstract: Cognitive radio (CR) systems allow unlicensed secondary users to transmit on the licensed frequency bands withoutdegrading the transmissions of licensed primary users. Combining CR with other emerging techniques such as multi-antennarelaying may bring many benefits for the secondary transmissions. In this study, the authors propose and investigate a newrelay-based cooperation scheme for a CR network to improve the secondary access to the licensed spectrum band withoutcausing additional interference to the simultaneous primary transmission. The proposed scheme considers one multi-antennarelay node that can assist either the primary or the secondary transmission using beam-forming (BF). In the proposed newscheme, the BF weights are designed in the presence of imperfect channel state information (CSI). Simulation results showthat the secondary’s channel capacity is significantly improved and outperforms conventional transmission schemes. Theresults also reveal the impact of imperfect CSI on the primary outage performance and the efficiency of the proposed solutionfor minimising the interference due to imperfect CSI.

1 Introduction

Cognitive radio (CR) technology has emerged as a promisingsolution to the spectrum congestion and spectrumunder-utilisation issues [1, 2]. It allows unlicensed users touse parts of the licensed spectrum without disturbing (ortolerably disturbing) the transmissions of licensed users. InCR networks (CRNs), secondary users (SUs) share thelicensed spectrum band with the primary users (PUs) byeither sensing the PUs’ activity and transmitting at emptyspectrum bands (interweave CRN) or by keeping theirtransmit power below a certain threshold to avoidundesirable interference at the primary receiver (PR)(underlay CRN). This power limitation mechanism makesSUs suffer from degraded performances [1].In order to improve the SUs performance, primary and

secondary users may transmit simultaneously on the samelicensed spectrum bands in such a way that SUs assist PUsusing cooperative techniques such as relaying or errorcontrol coding (overlay CRN) [2]. This model relaxes thesecondary power limitation in the underlay model, henceproviding a better secondary access to the licensed spectrumbands. Consequently, user cooperation allows to obtainspatial diversity gains and/or reduce interference because ofsimultaneous transmissions. These advantages are providedby the several paths created by the relay nodes between thesource and the destination [3, 4].When relay nodes are equipped with multiple antennas,

advanced transmission techniques could be used such asspace–time-coding [4] or beam-forming (BF) [5]. Using BF,each data stream is multiplied by a weight vector for

transmission using multiple antennas. It has been shownthat this low complexity strategy provides substantialperformance gains [6, 7].Recently, integrating user cooperation in CRNs has

attracted attention for improving both the spectrumutilisation and the transmissions’ performances. In [8], theauthors assumed that a SU acts as a relay for the primarytransmissions. Results show that cognitive relaying enhancesthe secondary throughput under certain network topologyconditions. In [9], an adaptive cooperation diversity schemewith best-relay selection is proposed for multi-relay CRNs inorder to improve the secondary outage performance whilesatisfying the primary quality-of-service (QoS). By lettingthe ‘best’ CR node assist the secondary transmission, thesecondary outage probability can be significantly improved.In [10], we propose a scheme where one relay node assistssimultaneously the primary and secondary transmissionseach time it is able to decode correctly the signals. We showthat the secondary outage performance is improved at theexpense of a substantial increase on the transmit power ofthe relay node. This scheme has been extended to the case ofa multi-antenna relay with antenna selection in [11]. We alsoproposed an adaptive cooperative scheme in [12] where onerelay node can assist primary transmissions, secondarytransmissions or both transmissions simultaneously. Wehave shown that the secondary outage performance issignificantly improved while the primary QoS criterion isrespected. Liu et al. [13] proposed an incremental relayingscheme that exploits distributed BF at the relay nodes inorder to assist the secondary transmission. Using thistechnique improves the secondary average throughput

IET Commun., 2014, Vol. 8, Iss. 7, pp. 1094–1103doi: 10.1049/iet-com.2013.0646

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without causing unacceptable interference to the ongoingprimary transmission. In [14, 15], the authors proposed anoptimal relay selection and BF scheme for theamplify-and-forward (AF) multi-relay multi-antenna CRN,in order to maximise the secondary capacity with respect torelay power and primary interference constraints. Theyshowed that this scheme outperforms conventional relayselection and BF schemes. In [16], the authors proposed acooperative scheme where a multi-antenna ST sends, alongwith its own signal, the primary signal in exchange for alicensed spectrum access. The proposed scheme is restrictedto the case of two antennas at the ST and full-duplexrelaying. In [17], the authors used a similar cooperationscheme where the ST assists the PUs’ transmissions alongwith its own transmissions using zero-forcing BF. Thistechnique improves both primary and secondaryperformances in terms of error rate, and outperforms thetechnique presented in [16].Even though some work has focused on exploiting user
cooperation for CRNs, to the best of our knowledge notmuch work has been reported in investigating multi-antennarelaying for both primary and secondary transmissions [10–17]. Moreover, most work considering pre-coding at themulti-antenna CR nodes assume that the secondary nodeshave perfect knowledge of the interference channel (ST-PR)and perfect knowledge of the primary channel (PT-PR) [17,18], which oversimplifies the system.In this paper, we propose to investigate a novel cooperative

scheme where a CR relay node is able to assist the primarytransmission or the secondary one using BF adaptively inthe presence of imperfect channel state information (CSI)(on the interference and primary channels). In addition, theprimary transmission is incremental as it may require theretransmission of the same (primary or secondary) signal.The retransmission is exploited to improve the secondaryaccess to the licensed spectrum band. That improvement isobtained without causing any additional interference to theprimary transmission. Moreover, it is adapted to thesituation of imperfect CSI, which matches better the true

Fig. 1 CRN: transmissions of the primary and secondary systems


scenarios where information about channels linked to thePR are partially known at the secondary nodes by usinglimited-feedback mechanisms.The remainder of the paper is organised as follows. The

next section presents the system model. In Section 3, theproposed scheme is described. Section 4 investigates the BFweights problem at the relay node and power allocation atthe secondary transmitter (ST) assuming imperfect CSI.Section 5 presents and discusses the simulation results, anda conclusion closes the paper in Section 6.

2 System model

2.1 Notations

Throughout the paper, E{.} denotes the expected value, XH

and xH denote the conjugate transpose of matrix X andvector x, respectively. x‖ ‖F and |x| denote the Frobeniusnorm of a vector x and the magnitude of a complex numberx, respectively.As illustrated in Fig. 1, we consider a primary network and

a CRN composed respectively of a primary transmitter (PT), aPR, a ST and a secondary receiver (SR), all equipped with asingle antenna, and of a relay node (RE), that belongs to thesecondary system, equipped with N antennas (N≥ 2).We assume that PT and ST transmit their respective signals

xp and xs, with powers Pp and Ps such that Ps ≤ Pmaxs , where

Pmaxs is the maximal transmit power of ST. We assume also

that RE uses the transmit power Pr limited by a maximalvalue Pmax

r . For convenience, we assume thatE{|xp|2} = E{|xs|2} = 1.Transmissions are processed over equal lengths time-slots

(each time-slot is sub-divided into two equal sub-slots),during which the Rayleigh fading channels are assumedstationary, but vary independently from a time-slot toanother. The proposed system is designed for the casewhere primary and secondary systems perform time-slottedtransmissions in the same frequency band, where we

1095& The Institution of Engineering and Technology 2014

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assume that the secondary system is able to synchronise itselfto the time-slotted primary transmissions. Synchronisationmethods were investigated in [19–23].We denote by hij, hir and hrj are the fading coefficients
and vectors of fading coefficients of the channels i− j, i− rand r− j, respectively, where i designates the transmitterand j the receiver (i = p or s, j = p or s and r designates RE).The variances of hij, hir and hrj are given by lij = d−h

ij ,lir = d−h

ir and lrj = d−hrj , respectively, with dij, dir and drj

are the distances between nodes i− j, i− r and r− j and ηis the path-loss exponent.In our system model, the assumptions about the

information exchange between the primary and secondarysystems are similar to the assumptions used in overlay CRNsystems as given in [17, 24–26]. Hence, we assumethroughout the paper that receivers (PR, SR and RE) haveperfect knowledge of their respective incoming channels.Furthermore, we assume that RE has a perfect knowledgeof the channels hrp and hrs. However, only estimates of thechannels hpp and hsp, denoted by h pp and hsp are known atST and RE. Without loss of generality, the relation betweenthe true channel hij and its estimate hij can be given byChen et al. [27] as

hij = rhij +��1− r2√

d (1)

where ρ∈ [0, 1] is the correlation coefficient between hij andhij and where δ is a circular symmetric complex Gaussianrandom variable with zero mean and variance λij. Inpractice, the CSI of the channel PT-PR (resp. ST-SR) canbe obtained at PR (resp. at SR) by classic channel trainingand estimation mechanisms as in [28]. Similarly, the CSI ofthe interference channel (ST-PR) (resp. PT-SR) is obtainedat PR (resp. at SR), where that information may be readilyobtained at ST, if PR is aware of the latter and wouldfeedback the CSI to it. Otherwise, dedicated means must bedeployed by ST to obtain the CSI of ST-PR and PT-PRchannels. For instance, ST can use the feedback informationfrom a cooperative sensor (e.g. the relay node) that islocated in the vicinity of PR and thus be able to eavesdropthe CSI feedback from PR to PT [29].Owing to the required exchange of information about the

channels’ states, we assume that transmissions occur over aslow-fading environment where the channels’ states areconstant within a given time-slot, hence allowing CSIexchange and transmissions on the same time-slot.

3 Proposed scheme

The transmissions in the proposed scheme are performed overtwo sub-slots as follows.

3.1 First sub-slot transmissions

At the first sub-slot, PT and ST send their signals xp and xsusing transmit powers Pp and Ps, respectively. The receivedsignals at PR, SR and RE are then expressed by

yp(1) =��Pp

√hppxp +

��Ps

√hspxs + np (2)

ys(1) =��Ps

√hssxs +

��Pp

√hpsxp + ns (3)


and

yr(1) =��Pp

√h prxp +

��Ps

√hsrxs + nr (4)

where np and ns are the additive white Gaussian noise(AWGN) coefficients with zero mean and finite variance N0

received at PR and SR, respectively, while nr is the AWGNvector of coefficients with zero mean and variance N0INreceived at RE. It is to be noted that Pp has a fixedarbitrarily value, while 0 , Ps , Pmax

s is controlled suchthat the primary transmission is not in outage over the firstsub-slot. That means the signal-to-interference-plus-noise-ratio (SINR) at PR has to satisfy

SINRp (1) =Pp hpp

∣∣∣ ∣∣∣2Ps hsp

∣∣∣ ∣∣∣2 +N0

=gp h pp

∣∣∣ ∣∣∣2gs hsp

∣∣∣ ∣∣∣2 +1≥ Qp (5)

where γp = (Pp/N0), γs = (Ps/N0) and Θp is the primary SINRthreshold, above which the primary transmission isconsidered successful [3]. According to (5), γs satisfies

gs = min gmaxs , max(0, bs)( )

(6)

where gmaxs = (Pmax

s /N0) and

bs =1

hsp

∣∣∣ ∣∣∣2gp h pp

∣∣∣ ∣∣∣2Qp

− 1

⎛⎜⎝

⎞⎟⎠ (7)

In the case of primary channel deep fading, setting Ps = 0 maynot prevent the primary transmission’s failure. However, weprefer to keep ST silent and let the primary transmission tryits best as it works in an incremental way. Since ST knowsonly hsp and h pp, then βs becomes

bs =1

hsp

∣∣∣ ∣∣∣2gp h pp

∣∣∣ ∣∣∣2Qp

− 1

⎛⎜⎝

⎞⎟⎠ (8)

The primary transmission is incremental, which means PRbroadcasts a control message about the success or thefailure of the first sub-slot transmission. Hence, two casesmay occur depending on the control message:

(1) If a positive message is broadcast [i.e. condition in (5) issatisfied], then RE forwards xs using decode-and-forward-BF(DF-BF) if it succeeds to decode it or ST repeats xs if it fails.We call this case ‘good primary channel’.(2) If a negative message is broadcast, then RE forwards xpusing DF-BF if it succeeds to decode it or PT repeats xp ifit fails. This case is called ‘bad primary channel’.

Without loss of generality, only DF has been considered atRE. AF could be used at RE, providing as expected a smallersecondary’s channel capacity gain.For the second sub-slot, we treat separately the cases ‘good

primary channel’ and ‘bad primary channel’.


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3.2 Second sub-slot transmissions
We consider the following possibilities:

(1) Good primary channel (RE assists the secondarytransmission): At the end of the first sub-slot, RE attemptsto decode xs using the optimum combining-successiveinterference cancellation (OC-SIC) proposed technique[30, 31]. Although joint maximum likelihood (JML) [32, 33]is expected to provide a better decoding performance, werather propose to use OC-SIC for its quasi-optimaldecoding capability [in particular, at low signal-to-interference-ratio (SIR)] and its reduced implementationcomplexity [32] compared with JML. Decoding isproceeding as follows:

(i) Attempt to decode xs while considering xp as interference.Hence, the secondary SINR at RE, denoted by SINR(r)

s , isgiven by

SINR(r)s = gsh

HsrR

−1s hsr (9)

where Rs = gph prhHpr + IN . The condition for success or

failure of decoding xs at RE is similar to the one in (5)where SINR(r)

s is compared to Θs, the SINR threshold overwhich xs is considered successfully decoded.(ii) If SINR(r)

s , Qs, first, attempt to decode xp whileconsidering xs as interference. Consequently, the primarySINR at RE, denoted by SINR(r)

p , is expressed by

SINR(r)p = gph

HprR

−1p h pr (10)

where Rp = gshsrhHsr + IN . If SINR

(r)p ≥ Qp (xp is decoded

correctly), omit xp from (4) and attempt to decode xs.Hence, the secondary SNR is given by

SNR(r)s = gs hsr

∥∥ ∥∥2F (11)

Finally, xs is considered correctly decoded at RE ifSINR(r)

s ≥ Qs, otherwise (SINR(r)s , Qs) if SINR(r)

p ≥ Qpand SNR(r)

s ≥ Qs. It is to be noted that even if RE decodesxp, in some cases, there is no use for this signal at RE sinceit is already decoded at PR.

† RE successfully decodes xs: In this case, RE applies a N × 1weight vector w(DF)

s to xs and forwards the product to SR whilePT sends a new signal x′p(x′p≠ xp) to PR using transmitpower Pp at the second sub-slot. The overall received signalat SR (of both sub-slots) is given by

ys =��Ps

√hss

hrsw(DF)s

[ ]︸��︷︷��︸

Wh(DF)s

xs +��Pp

√hps

0

[ ]︸��︷︷��︸

Wh1

xp +0��Pp

√hps

[ ]︸��︷︷��︸

Wh2

x′p + n(DF)s

= h(DF)s xs + h1xp + h2x′p + n(DF)s (12)

where n(DF)s is the 2 × 1 AWGN received at SR. By applyingOC, SINR at SR is expressed by

SINR(DF)s = h(DF)

H

s R(DF)−1

s h(DF)s

= gs hss∣∣ ∣∣2 + hrsw

(DF)s

∣∣ ∣∣2gp h ps

∣∣∣ ∣∣∣2+1

(13)


where R(DF)s =∑2

i=1 hihHi + N0I2.

The received signal at PR at the second sub-slot is denotedby yp(2), and is given by

yp(2) =��Pp

√hppx

′p + hrpw

(DF)s xs + np (14)

Hence, SINR at PR is written as

SINRp (2) =gp|hpp|2

hrpw(DF)s

∣∣∣ ∣∣∣2 +1(15)

† RE fails to decode xs: In this case, ST repeats the samesignal using transmit power Ps given by (6) and PTtransmits a new signal x′p using power Pp. Hence SINR atSR is expressed by

SINR(rep)s = 2gs hss

∣∣ ∣∣2gp h ps

∣∣∣ ∣∣∣2 +1(16)

and the received SINR at PR at the second sub-slot is givenby (5).

(2) Bad primary channel (RE assists the primarytransmission): In this case, PR fails to decode xp at the firstsub-slot and requires a retransmission at the secondsub-slot. In our scheme, RE assists the primary transmissionwhile ST sends xs using a controlled transmit power at thesecond sub-slot. xp is decoded by following a similarapproach as in (9)–(11).

† RE successfully decodes xp: In this case, RE applies a N × 1weight vector w(DF)

p to xp and forwards the product to PR atthe second sub-slot. Meanwhile, ST sends xs using transmitpower P(DF)

s (the value of P(DF)s is determined in the next

section). Hence, the received signal at PR is written as

yp =��Pp

√hpp

hrpw(DF)p

[ ]︸��︷︷��︸

Wh(DF)p

xp +��Ps

√hsp��

P(DF)s

√hsp

[ ]︸��︷︷��︸

Wh5

xs + n(DF)p

= h(DF)p xp + h5xs + n(DF)p (17)

where n(DF)p is the AWGN received at PR. By applying OC,SINR at PR is given by

SINR(DF)p = h(DF)

H

p R(DF)−1

p h(DF)p (18)

where R(DF)p = h5h

H5 + IN . Similarly to (17) and (18), the

received signal and SINR at SR are, respectively, given by

ys =��Ps

√hss��

P(DF)s

√hss

[ ]︸��︷︷��︸

Wh′ DF( )s

xs +��Pp

√hps

hrsw(DF)p

[ ]︸��︷︷��︸

Wh6

xp + n(DF)s

= h′ DF( )s xs + h6xp + n(DF)s (19)


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and
SINR′ DF( )s = h′ DF( )H

s R′ DF( )−1

s h′ DF( )s (20)

where R′ DF( )s = h6h

H6 + IN .† RE fails to decode xp: In this case, PT repeats xp using

transmit power Pp while ST transmits xs using transmitpower Ps given by (6). It is to be noted that the value of Ps

is sub-optimal for this case. However, it has been chosen toavoid extra information exchange for power allocation.

The overall received signal at node a (a = p or s) isexpressed by

ya = 11

[ ] ��Pp

√hpa︸��︷︷��︸

Wh(a)3

xp + 11

[ ] ��Ps

√hsa︸��︷︷��︸

Wh(a)4

xs + n(rep)a (21)

Using OC, SINR at PR is given by

SINR(rep)p = h(p)

H

3 R(rep)−1

p h(p)3 (22)

where R(rep)p = h(p)4 h(p)

H

4 + N0I2. Likewise, the received SINRat SR is written as

SINR(rep)s = h(s)

H

4 R(rep)−1

s h(s)4 (23)

where R(rep)s = h(s)3 h(s)

H

3 + N0I2.Fig. 2 provides a detailed flowchart for the transmission

steps of our proposed scheme.

Fig. 2 Flowchart of the proposed cognitive scheme


4 BF weights design and power allocation

In this section, we determine the antenna weights used inbeam-forming at RE and the transmit power of ST at thesecond sub-slot in the presence of imperfect CSI. We focushere on the cases ‘good primary channel’ (RE successfullydecodes xs) and ‘bad primary channel’ (RE successfullydecodes xp) only, since the other cases require a simplerpower allocation that has been detailed in the previoussection.Then, we propose a simple solution to neutralise the

imperfect CSI effect. It is to be noted that because ofthe complexity of the investigated problem, some of theproposed solutions are sub-optimal but somewhat offer alow-complexity implementation.

4.1 Good primary channel (RE successfullydecodes xs)

In this case, the role of BF is to maximise the secondary’schannel capacity while controlling the interference towardsthe primary transmission at the second sub-slot. The weightdesign problem can be formulated as follows [34]

argmaxw(DF)s

log2 1+ SINR(DF)s

( )

s.t.SINRp (2) ≥ Qp

w(DF)s

∥∥ ∥∥2F ≤ gmax

r

{ (24)

where SINR(DF)s and SINRp(2) are given by (13) and (15),

respectively. Since maximising the received SINR isequivalent to maximising the channel capacity and


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assuming imperfect CSI at RE, (24) can be reformulated as
argmaxw(DF)s

hrsw(DF)s

∣∣ ∣∣2

s.t.hrpw

(DF)s

∣∣∣ ∣∣∣2 ≤ m1( h pp )

||w(DF)s ||2F ≤ gmax

r

⎧⎨⎩

(25)

where m1( h pp ) = (gp h pp

∣∣∣ ∣∣∣2/Qp)− 1. Based on the method

presented in [34], the optimal solution of (25) is obtained asfollows. w(DF)

s is in the form of awg + bw h⊥, where

g = hHrp/‖hrp‖F( )

, h⊥ = h⊥/‖h⊥‖F( )

, h⊥ = hHrs − gHhHrs( )

g

and αw and βw are complex values. w(DF)s should lie in the

space spanned jointly by hHrp and the projection of hHrs onto

the null space of hHrp (Lemma 2, [34]). Let hHrs = ahg+bh h⊥ . Then, using Theorem 2 in [34], the optimal BFweight vector is w(DF)

s = awg + bw h⊥ where αw and βw aregiven by

† If m1(h pp) ≥ gmaxr ( hrp

∥∥∥ ∥∥∥2F

ah

∥∥ ∥∥2F/ ah

∥∥ ∥∥2F+ bh

∥∥ ∥∥2F)

aw =��

gmaxr

ah

∥∥ ∥∥2F + bh

∥∥ ∥∥2F

√ah (26)

and

bw =��

gmaxr

ah

∥∥ ∥∥2F + bh

∥∥ ∥∥2F

√bh (27)

† Otherwise

aw =��m1( h pp )√

hrp

∥∥∥ ∥∥∥F

ah

ah

∥∥ ∥∥F

(28)

and

bw =��gmaxr − m1( h pp )

hrp

∥∥∥ ∥∥∥2F

√√√√√ bh

bh

∥∥ ∥∥F

(29)

The obtained solution would work perfectly if the estimatedchannels are equal to the true channels. However, becauseof estimation errors, the first constraint in (25) could beviolated. Consequently, we propose to substitute (25) by anew problem written as

argmaxw(DF)s

hrsw(DF)s

∣∣ ∣∣2

s.t.hrpw

(DF)s

∣∣∣ ∣∣∣2 ≤ a1m1( h pp )

||w(DF)s ||2F ≤ gmax

r

⎧⎨⎩

(30)

where α1∈ [0, 1] is an arbitrarily selected protective margin.Solving (30) is processed exactly as for (25).


4.2 Bad primary channel (RE successfullydecodes xp)

The objective of relaying the primary signal is not to improveits transmission performance but to provide the same primaryperformance as if the secondary transmission were absent.Hence, we aim at maximising the secondary’s channelcapacity without causing any additional interference to theprimary transmission compared to conventional schemes.The joint weight design at RE and power allocation at STproblem can be formulated as [34]

argmaxw(DF)p ;g(DF)s

log2 1+ SINR′(DF)s

( )

s.t.SINR(DF)

p ≥ Qp

w(DF)p

∥∥∥ ∥∥∥2F≤ gmax

r

⎧⎨⎩

(31)

where SINR′(DF)s and SINR(DF)

p are expressed by (20) and(18), respectively. Owing to their complex expressions, wesimplify (31) by assuming that ST has perfect knowledge ofthe channels hpp and hsp. Hence, the expressions ofSINR

′(DF)s and SINR(DF)

p become

SINR′(DF)s = g(DF)s hss

∣∣ ∣∣2hrsw

(DF)p

∣∣∣ ∣∣∣2 +1(32)

and

SINR(DF)p = gp h pp

∣∣∣ ∣∣∣2 + hrpw(DF)p

∣∣∣ ∣∣∣2g(DF)s hsp

∣∣∣ ∣∣∣2 +1(33)

Using (32) and (33) and assuming imperfect CSI at RE, a newproblem is formulated

argminw(DF)p ;g(DF)s

hrsw(DF)p

∣∣∣ ∣∣∣2

s.t.hrpw

(DF)p

∣∣∣ ∣∣∣2 ≥ m2 h pp , hsp , g(DF)s

( )w(DF)p

∥∥∥ ∥∥∥2F≤ gmax

r

⎧⎪⎨⎪⎩

(34)

where m2 h pp , hsp , g(DF)s

( )= xr(Qp, h pp )− gp h pp

∣∣∣ ∣∣∣2( )1+ g(DF)s hsp

∣∣∣ ∣∣∣2( )is issued from the following constraint

SINRp(DF) = gp h pp

∣∣∣ ∣∣∣2 + hrpw(DF)p

∣∣∣ ∣∣∣2g(DF)s hsp

∣∣∣ ∣∣∣2 +1≥ xr(Qp, hpp) (35)

with

xr(Qp, hpp) =Qp if r , 1

2gp h pp

∣∣∣ ∣∣∣2 if r = 1

⎧⎨⎩ (36)

χρ defines the required SINR at PR if a retransmission isrequested. When ρ = 1, we choose to respect the same SINR


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as for the case of a non-assisted primary transmission.However, when ρ < 1, high interference on the primarytransmission is expected. Consequently, we intent to satisfyΘp in order to minimise the impact of imperfect CSI.Without any constraint, the objective function in (34) canbe minimised to be equal to zero. Based on these twoobservations: (i) the objective function is reduced to zeroand (ii) the left term of the first constraint is maximised to
be above m2 h pp , hsp , g(DF)s

( ), a new problem formulation

is proposed as follows

argmaxw(DF)p ;g(DF)s

hrpw(DF)p

∣∣∣ ∣∣∣2 ≥ m2 h pp , hsp , g(DF)s

( )( )

s.t.hrsw

(DF)p

∣∣∣ ∣∣∣2 = 0

w(DF)p

∥∥∥ ∥∥∥2F= g(DF)r ≤ gmax

r

⎧⎪⎨⎪⎩

(37)

where the term between brackets in the objective functionrepresents the lowest tolerable value. Assuming that thisvalue is ignored in (37), the solution is obtained by themethod of orthogonal projection [13]

w(DF)p =

��g(DF)r

√PhHrp

PhHrp

∥∥∥ ∥∥∥F

, where P = IN − hHrshrs

hrs∥∥ ∥∥2

F

(38)

To solve (37), we propose to use Algorithm (A1) presentedbelow (Fig. 3) as follows.The Algorithm (A1) combined with (38) provides a

sub-optimal solution to the original problem in (31). Sinceimperfect knowledge of the channel states is considered, wepropose to modify steps 7 and 11 of Algorithm (A1) such

that hrpw(DF)p

∣∣∣ ∣∣∣2 is compared to (1+ a2)m2 h pp , hsp , g(DF)s

( ),

where α2∈ [0, +∞) is an arbitrarily protective margin.Consequently, the imperfect CSI effect could besignificantly reversed (see Section 5 for results comparison).

Fig. 3 Algorithm (A1)


5 Simulation results

We consider the system model shown in Fig. 1 where dpp =dss = 1 distance unit and where d0 = 2. The path-lossexponent is set to η = 4 and the primary and secondarySINR thresholds are equal to Θp =Θs = 0 dB, unlessotherwise stated. We first assume perfect CSI at ST and RE(Figs. 4 and 5), then imperfect CSI at both nodes (Fig. 6).In our results of Fig. 6, the impact of imperfect CSI (ofchannels ST-PR and PT-PR) is reversed only at RE.Anyhow, reversing the imperfect CSI effect at ST has beeninvestigated in [27].

Fig. 4 Comparison of the schemes’ performances (n = 2, Θp =Θs = 0 dB, γs

max = γrmax = γp)

a Primary outage probabilityb Secondary’s channel capacityc Consumed power


Fig. 5 Performances of ‘Prop.’ scheme versus gmaxr (N = 2 andN = 3, Qp = Qs = 0 dB, gmaxs = gp = 12 dB)

a Primary outage probabilityb Secondary’s channel capacity

Fig. 6 Impact of imperfect CSI on ‘Prop.’ scheme performances(N = 2, Qp = Qs = 0 dB, gmaxs = gmaxr = gp)

a Primary outage probabilityb Secondary’s channel capacityc Consumed power

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To show the advantages for using the proposed scheme, wechoose to evaluate the primary outage probability (denotedPout,p) since the primary system has an interferenceconstraint to satisfy. Meanwhile, the channel capacity(denoted Cs) is evaluated for the secondary system.Furthermore, we evaluate the average power consumed bythe nodes of the networks for the transmissions over onetime-slot. We distinguish them as consumed power by PTand consumed power by ST + RE.The performances are determined using Monte Carlo

simulations by averaging the outage performances overseveral randomly selected relay node’s positions locatedwithin the area delimited by PT–PR–SR–ST.Our proposed scheme (denoted ‘Prop.’) is compared to a

non-cooperative scheme (denoted ‘non-coop.’), to aconventional relaying scheme (denoted ‘Conv.’) and to amodified scheme of the proposed one (denoted ‘Mod. AF/DF’) that are described as follows. In the ‘non-coop.’scheme, the primary transmission is incremental, that is, PTretransmits the same signal over the two sub-slots whenever

gp h pp

∣∣∣ ∣∣∣2 , Qp. Meanwhile, the secondary transmission is

processed using repetition, where ST transmits using γsgiven by (6). In the ‘Conv.’ scheme, the primarytransmission is also incremental. However, the secondarytransmission is always assisted by RE using DF-BF or byST as in the ‘good primary channel’ case of ‘Prop.’scheme. The ‘Mod. AF/DF’ scheme is similar to the ‘Prop.’


scheme when RE decodes correctly the signals to beforwarded. However, when RE fails to decode the signals,AF and BF are jointly used (AF–BF) to forward the signals[Details of weights design and power allocation are omittedbecause of similarity to the case of DF–BF.]. Theseschemes are used as a benchmark for comparison with theproposed scheme.Fig. 4 illustrates the primary outage probability, the

secondary’s channel capacity and the consumed power bythe nodes in the CRN against γp for the ‘non-coop.’,‘Conv.’, ‘Mod. AF/DF’ and ‘Prop.’ schemes. In Fig. 4a, all


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schemes achieve the same Pout,p performance. This resultvalidates that the ‘Prop.’ scheme maintains the same Pout,p
as the conventional schemes. However, from Fig. 4b, wesee that ‘Prop.’ and ‘Mod. AF/DF’ schemes provide aslightly superior secondary’s channel capacity. Indeed,besides the performance gain obtained by assisting thesecondary transmission as in the ‘Conv.’ scheme, both‘Prop.’ and ‘Mod. AF/DF’ schemes provide an additionalgain when the primary transmission is assisted, allowing STto transmit with a limited interference towards PR. Eventhough ‘Prop.’ and ‘Mod. AF/DF’ schemes have similarperformances, ‘Prop.’ scheme is preferred, since itconsumes slightly less power at the transmitting nodes(particularly at low γp) as can be seen in Fig. 4c.In Fig. 5, we investigate the impact of the maximal relay

transmit power and number of antennas at RE on Pout,p andCs of ‘Prop.’ scheme. In Fig. 5a, as gmax

r increases for afixed N, Pout,p improves, then saturates at a constant value.This constant value represents the best Pout,p performancewhen no interference is present. As N increases, Pout,p

improves to reach faster its best value since the system usesDF–BF more efficiently. Moreover, an additional antenna atRE improves significantly Cs as it can be shown in Fig. 5b.It is to be noted that ‘consumed power figure’ has not beenillustrated since the same powers are used for both cases.Fig. 6 shows the impact of imperfect CSI at RE and

the proposed solution to compensate its effect. In Fig. 6a,for ρ = 0.5 and no power adjustment, that is, α1 = α2 = 0,Pout,p degrades dramatically because of the inaccuracy ofthe BF processed at RE, causing high interference at theprimary transmission. By adjusting adequately α1 and α2 forthe weights design at RE, Pout,p improves significantly butremains worse than for the case of ρ = 1 (perfect CSI at STand RE). If a power adjustment were processed at ST, thenPout,p of the perfect CSI case can be further approached.Fig. 6b shows that the power adjustment reduces thesecondary’s channel capacity, Cs. However, when noadjustment is performed, Cs is higher and slightlyoutperforms the case ρ = 1 at very high γp. This canbe explained by the fact that ST transmits more often whenρ = 0.5 than when ρ = 1, and hence causes more interferenceto PR. From Fig. 6c, the power consumed by PT is thesame for all cases since it is fixed. Meanwhile, theconsumed power by the secondary nodes (ST + RE) slightlydecreases with ρ because of imperfect CSI. Moreover, thepower adjustment reduces significantly the consumedpower by ST + RE, aiming at limiting the interferencetowards PR.

6 Conclusion

In this paper, we have proposed and analysed a newrelay-based scheme for CR communications where amulti-antenna relay node is able to assist either the primaryor the secondary transmission using BF. By accuratelydesigning the BF weights at the relay node and taking intoaccount the impact of imperfect CSI, we show that theproposed scheme outperforms the conventional schemes interms of secondary’s channel capacity and also circumventsthe effect of imperfect CSI on the primary outage probability.

7 References

1 Haykin, S.: ‘Cognitive radio: brain-empowered wirelesscommunications’, IEEE J. Sel. Areas Commun., 2005, 23, (2),pp. 201–220


2 Goldsmith, A., Jafar, S., Maric, I., Srinivasa, S.: ‘Breaking spectrumgridlock with cognitive radios: an information theoretic perspective’,Proc. IEEE, 2009, 97, (5), pp. 894–914

3 Laneman, J., Tse, D., Wornell, G.: ‘Cooperative diversity in wirelessnetworks: Efficient protocols and outage behavior’, IEEE Trans. Inf.Theory, 2004, 50, (12), pp. 3062–3080

4 Jaafar, W., Ajib, W., Haccoun, D.: ‘On the performance of multi-hopwireless relay networks’, Wirel. Commun. Mob. Comput., 2014, 14,(1), pp. 145–160

5 Havary-Nassab, V., Shahbazpanahi, S., Grami, A.: ‘Jointreceive-transmit beamforming for multi-antenna relaying schemes’,IEEE Trans. Signal Process., 2010, 58, (9), pp. 4966–4972

6 Caire, G., Shamai, S.: ‘On the achievable throughput of a multiantennaGaussian broadcast channel’, IEEE Trans. Inf. Theory, 2003, 49, (7),pp. 1691–1706

7 Viswanathan, H., Venkatesan, S., Huang, H.: ‘Downlink capacityevaluation of cellular networks with known-interference cancellation’,IEEE J. Sel. Areas Commun., 2003, 21, (5), pp. 802–811

8 Simeone, O., Bar-Ness, Y., Spagnolini, U.: ‘Stable throughput ofcognitive radios with and without relaying capability’, IEEE Trans.Commun., 2007, 55, (12), pp. 2351–2360

9 Zou, Y., Zhu, J., Zheng, B., Yao, Y.-D.: ‘An adaptive cooperationdiversity scheme with best-relay selection in cognitive radionetworks’, IEEE Trans. Signal Process., 2010, 58, (10), pp. 5438–5445

10 Jaafar, W., Ajib, W., Haccoun, D.: ‘A novel relay-aided transmissionscheme in cognitive radio networks’. Proc. IEEE GlobalTelecommunications Conf., GLOBECOM, December 2011, pp. 1–6

11 Jaafar, W., Ajib, W., Haccoun, D.: ‘Adaptive relaying scheme forcognitive radio networks’, IET Commun., 2013, 7, (11), pp. 1151–1162

12 Jaafar, W., Ajib, W., Haccoun, D.: ‘Opportunistic adaptive relaying incognitive radio networks’. Proc. IEEE Int. Conf. on Commun., ICC,June 2012, pp. 1–5

13 Liu, J., Chen, W., Cao, Z., Zhang, Y.: ‘Cooperative beamforming aidedincremental relaying in cognitive radios’. IEEE Int. Conf. onCommunications, ICC, June 2011, pp. 1–5

14 Li, Q., Zhang, Q., Feng, R., Luo, L., Qin, J.: ‘Optimal relay selection andbeamforming in MIMO cognitive multi-relay networks’, IEEECommun. Lett., 2013, 17, (6), pp. 1188–1191

15 Feng, R., Li, Q., Zhang, Q., Qin, J.: ‘Optimal beamforming in spectrumsharing cognitive non-regenerative multi-relay networks’, Electron.Lett., 2013, 49, (17), pp. 1102–1104

16 Bohara, V., See, H.T., Yang, H., Pandharipande, A.: ‘Interference-freeoverlay cognitive radio network based on cooperative space timecoding’. Proc. of the Fifth Int. Conf. on Cogn. Radio OrientedWireless Net. Commun. (CROWNCOM), June 2010, pp. 1–5

17 Manna, R., Louie, R., Yonghui, L., Vucetic, B.: ‘Cooperative spectrumsharing in cognitive radio networks with multiple antennas’, IEEETrans. Signal Process., 2011, 59, (11), pp. 5509–5522

18 Tourki, K., Qaraqe, K., Alouini, M.-S.: ‘Outage analysis for underlaycognitive networks using incremental regenerative relaying’, IEEETrans. Veh. Technol., 2012, 62, (99), p. 1

19 Zhao, Q., Tong, L., Swami, A., Chen, Y.: ‘Decentralized cognitive MACfor opportunistic spectrum access in ad hoc networks: a POMDPframework’, IEEE J. Sel. Areas Commun., 2007, 25, (3), pp. 589–600

20 Zhao, Q., Swami, A.: ‘A survey of dynamic spectrum access: signalprocessing and networking perspectives’. IEEE Int. Conf. onAcoustics, Speech and Signal Process. ICASSP’07, 2007, vol. 4,pp. IV-1349–IV-1352

21 He, S., Jiang, L., He, C.: ‘A novel secondary user assisted relaymechanism in cognitive radio networks with multiple primary users’.IEEE Global Commun. Conf. GLOBECOM’12, 2012, pp. 1254–1259

22 Giupponi, L., Ibars, C.: ‘Distributed cooperation among cognitive radioswith complete and incomplete information’, EURASIP J. Adv. SignalProcess., 2009, 2009, (1), pp. 1–13

23 Hassen, T.W.: ‘Synchronization in Cognitive Overlay Systems’. Thesis,Aalto University, School of Electrical Engineering, 2012

24 Krikidis, I., Sun, Z., Laneman, J., Thompson, J.: ‘Cognitive legacynetworks via cooperative diversity’, IEEE Commun. Lett., 2009, 13,(2), pp. 106–108

25 Jovicic, A., Viswanath, P.: ‘Cognitive radio: an information-theoretic perspective’, IEEE Trans. Inf. Theory, 2009, 55, (9),pp. 3945–3958

26 Sahai, A., Cabric, D.: ‘Spectrum sensing: fundamental limits andpractical challeneges: Part I and part II’. IEEE Int. Symp. on NewFrontiers in Dynamic Spectrum Access, DySpan’05, November 2005

27 Chen, J., Si, J., Li, Z., Huang, H.: ‘On the performance of spectrumsharing cognitive relay networks with imperfect CSI’, IEEE Commun.Lett., 2012, 16, (7), pp. 1002–1005


www.ietdl.org
28 Tong, L., Sadler, B., Dong, M.: ‘Pilot-assisted wireless transmissions:
general model, design criteria, and signal processing’, IEEE SignalProcess. Mag., 2004, 21, (6), pp. 12–25

29 Kang, X., Garg, H., Liang, Y.-C., Zhang, R.: ‘Optimal power allocation forOFDM-based cognitive radio with new primary transmission protectioncriteria’, IEEE Trans. Wirel. Commun., 2010, 9, (6), pp. 2066–2075

30 Winters, J.: ‘Optimum combining in digital mobile radio with cochannelinterference’, IEEE J. Sel. Areas Commun., 1984, 2, (4), pp. 528–539

31 Tse, D., Viswanath, P.: ‘Fundamentals of wireless communication’(Cambridge University Press, 2005)


32 Blomer, J., Jindal, N.: ‘Transmission capacity of wireless ad hocnetworks: Successive interference cancellation against Joint detection’.IEEE Int. Conf. on Commun., ICC’09, 2009, pp. 1–5

33 Letaief, K., Choi, E., Ahn, J.-Y., Chen, R.: ‘Joint maximumlikelihood detection and interference cancellation for MIMO/OFDMsystems’. IEEE Vehicular Tech. Conf., VTC-Fall’03, 2003, vol. 1,pp. 612–616

34 Zhang, R., Liang, Y.-C.: ‘Exploiting multi-antennas for opportunisticspectrum sharing in cognitive radio networks’, IEEE J. Sel. Top.Signal Process., 2008, 2, (1), pp. 88–102


Improving spectrum access using a beam-forming relay scheme for cognitive radio transmissions

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