Communications and Network, 2013, 5, 380-385
http://dx.doi.org/10.4236/cn.2013.53B2069 Published Online September 2013 (http://www.scirp.org/journal/cn)
Relay Selection and Power Allocation in
Amplify-and-Forward Cognitive Radio Systems Based on
Spectrum Sharing
Daqian Zhao, Zhizhong Zhang, Fang Cheng
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China
Email: 359411295@qq.com, zhangzz@cqupt.edu.cn, chengfang@cqupt.edu.cn
Received July, 2013
ABSTRACT
In this paper, we consider a spectrum sharing scheme that is a joint optimization of relay selection and power allocation
at the secondary transmitter, which aims to achieve the maximum possible through put for the secondary user. This pa-
per considers the scenario where the primary user is incapable of supporting its target signal-to-noise ratio (SNR). More
especially, the secondary transmitter tries to assist the primary user with achieving its target SNR by cooperative am-
plify-and-forward (AF) relaying with two-phase. By exhaustive search for all candidate secondary transmitters, an op-
timal secondary transmitter can be selected, which not only can satisfy the primary user’s target SNR, but also maxi-
mize the secondary us er’s throughpu t. The optimal secondary transmitter acts as a relay for the primary user by allocat-
ing a part of its power to amplify-and-forward the primary signal over the primary user’s licensed spectrum bands. At
the same time, as a reward, the optimal secondary transmitter uses the remaining power to transmit its own signal over
the remaining licensed spectrum bands. Thus, the secondary user obtains the spectrum access opportunities. Besides,
there is no interference between the pr imary user and th e second ary us er. We study the join t optimizati o n of relay selec-
tion and power allocation such that the secondary user’s throughput is maximized on the condition that it satisfies the
primary user’s target SNR. From the simulation, it is shown that the joint op timization of relay selection and power al-
location provides a significant throughput gain compared with random relay selection with optimal power allocation
(OPA) and random relay selection with water-filling power allocation (WPA). Moreover, the simulation results also
shown that our spectrum sharing scheme obtains the win-win solution for the primary system and the secondary system.
Keywords: Spectrum Sharing; Cooperative Communication; Relay Selection; Power Allocatio n; Throughput;
Maximum Ratio Combining; Cognitiv e Radio Systems
1. Introduction
Currently, the fixed spectrum access (FSA) policy has
traditionally been adopted by spectrum regulators, which
assigns each piece of spectrum with certain bandwidth to
one or more dedicated users. By doing so, only the as-
signed (licensed) users have the right to exploit the allo-
cated spectrum, and other users are not allowed to use it,
regardless of whether the licensed users are using it or
not. Recent studies on the actual spectrum utilization
measurements have revealed that a large portion of the
licensed spectrum experiences low utilization [1-3].
However, cognitive radio (CR) is an agile spectrum ac-
cess/sharing technology that allows unlicensed (secon-
dary) systems to operate in licensed frequency bands
without causing harmful interference to licensed (pri-
mary) systems, and thus spectrum utilization can be sig-
nificantly improved [4-6]. Thus, CR is widely regarded
as one of the most promising technologies for future
wireless communications.
Cooperative relay communication can improve power
efficiency in the wireless networks by increasing the spa-
tial diversity. By the use of relays, the transmitted power
from the source terminal can be significantly reduced
[7-9].
The literature [10] prop osed an opportunistic sp ectrum
sharing protocol that exploited the scenario where the
primary system was incapable of supporting its target
transmission rate. Specifically, the secondary system
tried to assist the primary system with achieving its target
rate via two-phase cooperative OFDM relaying. However,
the literature [10] didn’t study the problem of relay se-
lection in a multi-relay secondary system, so the outage
was more likely occur at the primary system. If the out-
age was occurred at the primary system, it wasn’t the
win-win solution for the primary system and the secon-
dary system. The literature [10] used the dual decompo-
C
opyright © 2013 SciRes. CN
D. Q. ZHAO ET AL. 381
sition method and the authors was derived the
closed-form solutions for the set of subcarriers, subcar-
rier pairing and power allocation, so the algorithm was
complex. In our paper, we study the problem of relay
selection in a multi-relay secondary system so that the
outage can’t easily occur at the primary system. Fur-
thermore, the algorithm complexity in our paper is
straightforward compared with the literature [10] an d the
simulation results also shown that our spectrum sharing
scheme is better than [10].
In [11], the authors studied the problem of joint relay
selection and power allocation at the source and relay the
nodes in a CR system in which nodes were allowed to
amplify-and-forward cooperate with each other. How-
ever, the literature [11] used the opportunistic spectrum
access (OSA) model: the CR user carried out spectrum
sensing to detect spectrum holes [12], so it presented a
very high demand for the spectrum sensing accuracy
when the primary system exist, and it was not easily to
realize. In addition, the literature [11] had set up the in-
terference threshold to protect the primary user, so the
throughput was limited. In our paper, we don’t need set
up the interference threshold to protect the primary user.
On the contrary, we assist the primary user with achiev-
ing its target SNR, as a reward, the secondary user can
access the primary user’s licensed spectrum bands.
In this paper, we study the joint optimization of relay
selection and power allocation such that the secondary
user’s throughput is maximized on the condition that it
satisfies the primary user’s target SNR. By exhaustive
search for all candidate secondary transmitters, an opti-
mal secondary transmitter can be selected, which not
only can satisfy the primary user’s target SNR, but also
maximize the secondary user’s throughput. Since the
optimal secondary transmitter uses different licensed
spectrum bands to amplify-and-forward primary signal
and to transmit its own signal, so there is no interference
between the primary user and the secondary user. From
the simulation, it is shown that the joint optimization of
relay selection and power allocation provides a signifi-
cant throughput gain compared with OPA and WPA.
Moreover, the simulation results also shown that our
spectrum sharing scheme obtains the win-win solution
for the primary system and the secondary system.
The rest of this paper is organized as follows. In Sec-
tion 2, we introduce the system model. System perform-
ance is analyzed in Section 3. The joint optimization of
resource allocation is presented in Section 4. Simulation
results are shown in Section 5. Finally, this paper is con-
cluded in Section 6.
2. System Description
We consider cooperative cognitive radio systems as
shown in Figure 1. The primary system, comprising of a
primary user base station (PUBS) and a primary user
receiver (PUR), supports the relaying functionality and
has the license to operate in some spectrum bands. We
assume that the primary system has multiple licensed
spectrum bands as shown in Figure 2, and PUR can keep
track of the SNR of the PUBSPUR link. The secon-
dary system, comprising of n secondary user transmitters
(,1...
i
SUT in
) and a secondary user receiver (SUR),
can only operate in licensed spectrum bands by using the
scenario where the PUR is incapable of supporting its
target SNR (e.g., the SNR of the PUBSPUR link is
below a threshold due to path loss, shadowing, moving,
or interference). Specifically, the secondary transmitter
tries to assist the primary user with achieving its target
SNR by cooperative AF relaying with two-phase. The
scenario provides an opportunity for the secondary user
to access the licensed spectrum bands of the primary
system. Since the optimal secondary transmitter uses dif-
ferent licensed spectrum bands to amplify-and-forward
primary signal and to transmit its own signal, so there is
no interference between the primary user and the secon-
dary user. We assume that the secondary system is able
to emulate system parameters of the primary system. For
the sake of simplicity, we assume that the relay
(i) has been selected as the optimal relay. The prob-
lem of relay selection will be addressed in Section 4.
th
i
SUT
P
UBS
1
SUT
i
SUT
n
SUT
PUR
SUR
,pp
h
,pi
h
,ip
h
,is
h
Figure 1. System model.
Figure 2. PU’s licensed spectrum bands.
Copyright © 2013 SciRes. CN
D. Q. ZHAO ET AL.
382
Both the primary system and the secondary system ex-
perience independent and frequency-selective Rayleigh
fading. The channel gains of the ,
, , i links are
denoted as ,
PUBS PUR
SUR
i
PUBS SUTi
SUT PURSUT
p
p, ,
h
p
i, ,ip, ,is, respectively. We as-
sume that these channel state information (CSI) are
available at prior to transmission. We consider slow fad-
ing where the channel gains remain constant over the
one-phase. We assume that ,
hhh
p
p, ,
n
p
i, ,ip, ,is are
independent additive white Gaussian noises with zero
mean and variance 0. Let
nnn
N
p
X
and
X
denote the
signal to be transmitted to PUR and SUR, respectively,
which have unit power. The PUBS and ,1..
i
SUT in.
each have a sum transmit power constraint, denoted as
max
P
UBS
P and .
max , 1...
i
SUT
Pi n
3. Analysis of Performance
In the first phase, as shown by the black solid arrows in
Figure 1, PUBS transmits the signal
p
X
while PUR
and i listen. The signal received at PUR in the first
phase is give n by
SUT
,,,
p
pppppp
yPhXnp
(1)
where
p
P is the power transmitted from PUBS to PUR
and PUBS to . P UBS us es the maxi mum tr ansmis -
sion power i
SUT
max
P
UBS
P to transmit the primary signal,
namely as max
P
UB
p
PPS. From equation (1), the instanta-
neous SNR of PUR in the first phase can be written as
2
,
10
||
ppp
Ph
N
(2)
Similarly, the signal received at is given by
i
SUT
,,,
p
ippip
yPhXnpi
,
(3)
In the second phase, as shown by the red solid arrows
in Figure 1, PUBS remains silent while i amplify-
and-forward primary signal over the primary user’s li-
censed spectrum bands as shown in Figure 2. The signal
received at PUR in the second phase can be written as
SUT
,,,ipi ippiip
yhyn

(4)
where i
is the amplification factor and is defined as
,
2
,0
||
sp
i
ppi
P
Ph N
(5)
where ,
s
p is the power transmitted from i to
PUR. By replacing equation (3) and equation (5) into
equation (4), we have
PSUT
,, ,'
,,
2
,0
||
pspippi
ipp ip
ppi
PPh h
yX
Ph N

where ,,
',,
2
,0
||
sp ip
ippi ip
ppi
Ph
nnn
Ph N

,
,
. Since
p
i
n and
,ip
n',
ip
n are independent additive white Gaussian noises,
is also Gaussian with zero mean and variance
2
,,
'
00
2
,0
1
sp ip
ppi
Ph
NN
Ph N


(7)
From equation (6) and equation (7), the instantaneous
SNR at PUR in the second phase can be written as
22
,, ,
222
,,, 0
||||
psp ippi
ppi spip
PP hh
0
P
hPhNN

(8)
It has been shown that applying the maximum ratio
combining at PUR in an AF relay system maximized the
SNR [13]. Therefore, we use the maximum ratio com-
bining (MRC) at PUR to combine the two received sig-
nals from the first phase and the second phase. We as-
sume that PUR has all the CSIs. As the instantaneous
SNR at the output of combiner equals the sum of the
SNRs of the incoming signals [13], we can write the in-
stantaneous SNR
p
after applying the MRC as
12p

 (9)
where 1
and 2
are obtained from equation (2) and
equation (8), respectively. Since i must be assist
PUR with achieving its target SNR by acting as an AF
relay, the PUR’s target SNR constraint as follows
SUT
p
T

(10)
where T
is the PUR’s target SNR.
In the second phase, i also uses its remaining
power to transmit its own signal over the remaining li-
censed spectrum bands on the condition that it satisfies
the PUR’s target SNR as shown in Figure 2. The signal
received at SUR is given by
SUT
,,,isssissis
yPhXn,
(11)
where ,
s
s is the power transmitted from i to
SUR. From equation (11), the instantan eous SNR at SUR
in the second phase can be written as
PSUT
2
,,
0
ss is
s
Ph
N
(12)
Therefore, assuming that the relay has been se-
lected, we can write the instantaneous throughput of SUR
as
th
i
,2
() (1
iss s
TP log)

(13)
n
(6) Since ,
s
p and ,
P
s
s are the transmit power from
, this two transmit power must be satisfy the fol-
P
i
SUT
Copyright © 2013 SciRes. CN
D. Q. ZHAO ET AL. 383
lowing constraint
,, i
SUT
s
pss max
PPP (14)
In the next section, we solve the joint optimization of
resource allocation problem to maximize the instantane-
ous throughput of SUR in equation (13).
4. Resource Allocation
In this section, we solve the joint optimization of relay
selection and pow er allocation at the secondary transmit-
ter to achieve the maximum possible throughput for the
SUR while guaranteeing the PUR to achieve its target
SNR. The optimal power allocation at the secondary
transmitter to maximize the throughput for the SUR is
calculated. Then, through an exhaustive search for all
candidate secondary transmitters, an optimal secondary
transmitter can be selected, which not only can satisfy
the primary user’s target SNR, but also maximize the
secondary user’s throughput as defined in equation (13).
Therefore, in the following, we set up the optimization
problem to find the optimum set of transmit powers ,
s
p
and ,
P
s
s for the secondary transmitter. The power allo-
cation problem for all candidate secondary transmitters
can be formulated as the following optimization
P

,
*
,, ,
argmax ()
ss
s
sii ss
P
PTP (15)
subject to
,,
,,
0, 0
i
pT
SUT
s
pssmax
sp ss
PPP
PP



where *
,,
s
si
P is the optimal values of ,
s
s for the
secondary transmitter. The optimal relay selection can be
formulated as an exhaustive search for all candidate sec-
ondary transmitters
Pth
i
*
,,
argmax )
ˆ(
issi
i
iTP (16)
where i ranges from 1 to n and i represents the optimal
secondary transmitter. From equation (10) we can obtain
22
1,00
,22 2
,, 1,
()( )
()
Tppi
sp
pip piTip
PhN N
PPhhh N



 0
(17)
According to our spectrum sharing scheme, as long as
the optimal secondary transmitter can satisfy the PUR’s
target SNR, it can access the remaining licensed spec-
trum bands instead of exceeding the PUR’s target SNR.
Therefore, the equation (17) can be rewritten as
22
1,00
,22 2
,, 1,
()( )
()
Tppi
sp
pip piTip
PhN N
PPhhh N




From equation (14), we know that the power allocation
is optimal when ,, i
SUT
s
pssmax
PPP
SUT
, name ly as
0
(18)
,
i,
s
smax s
PP P
p
(19)
By replacing equation (18) into equation (19), the op-
timal power allocation *
,,
s
si
P can be written as
22
1,00
*
,, 22 2
,, 1,
()( )
()
iTppi
SUT
ssi max
pip piTip
PhN N
PP Phhh N



  0
Hz
(20)
The optimal secondary transmitter is then found by an
exhaustive search for all candidate secondary transmit-
ters and finding the optimal secondary transmitter that
maximizes the throughput us ing equation (16).
5. Simulation Results
In this section, the simulation results are presented to
demonstrate the performance of our spectrum sharing
scheme in terms of SUR throughout.
We consider cooperative cognitive radio systems with
n secondary transmitters oper ating in AF mode as shown
in Figure 1. All the channels are assumed to be Rayleigh
fading with unity bandwidth. We assume that
10W
PUBS
max
P, 00.1 /NW
.
First, we simulate that SUR throughput versus PUR
target SNR, assuming that . The
number of the candidate secondary transmitters are fixed
at
10 ,1
i
SUT
max
PWin
10n
, which have already satisfied the PUR’s target
SNR. We apply our spectrum sharing scheme and simu-
late that SUR throughput versus PUR target SNR in
Figure 3. We have also simulated the cases of random
relay selection with optimal power allocation (OPA) and
random relay selection with water-filling power alloca-
tion (WPA). Similarly, both of two algorithms have al-
ready satisfied the PUR’s target SNR. Note in the WPA
that the power allocation at PUBS and i are prede-
termined by the water-filling algorithm based on the
chann el and the channel,
SUT
i
SUTSUR
PUBS PUR
10 11 12 13 14 15 16 1718
0
1
2
3
4
5
6
7
PUR target SNR (dB)
SUR throughput (bps/Hz)
Opt i mal approach
Random relay with OPA
Random relay with WPA
Figure 3. SUR throughput versus PUR target SNR.
Copyright © 2013 SciRes. CN
D. Q. ZHAO ET AL.
384
respectively. From Figure 3, we see that the SUR
throughput increases significantly when our spectrum
sharing scheme for relay selection and power allocation
is applied compared with the OPA and the WPA. When
the PUR’s target , it means that the PUR
no need to cooperate and the SUR throughput is the
maximum equal 6.3626 bps/Hz. However, the optimal
secondary transmitter can’t access the PU’s licensed
spectrum bands, so it’s a peak for the SUR throughput.
When the PUR’s target , the PUR seeks
to cooperate and the optimal secondary tran smitter assists
the PUR with achieving its target SNR by acting as an
AF relaying with two-phase. Then, as a reward, the op-
timal secondary transmitter can access the remaining
licensed spectrum bands. With the PUR target SNR in-
creases, the optimal secondary transmitter needs allocate
more power to assist the PUR with achieving its target
SNR and thus leading to a lower SUR throughput. Ap-
plying our optimal approach the SUR throughput gains
of 2.6351 bps/Hz and 3.1046 bps/Hz compared with the
OPA and the WPA are obtained, respectively, at the
PUR’s target . When in the
optimal approach; in the OPA and the
WPA, the SUR throughput rapid decline. This is because
the optimal secondary transmitter allocates more power
to amplify-and-forward the primary signal, so the SUR
throughput decreases rapidly.
9.95SNR dB
9.SNR
12SNR dB15SNR dB
95dB
SNR 17 dB
Figure 4 shows that SUR throughput versus
compared with the OPA and the WPA while the PUR’s
target SNR is fixed at 12dB and the number of the can-
didate secondary transmitters are fixed at . When
, the optimal approach provides 2.6338
bps/Hz and 3.0904 bps/Hz throughput gains compared
with the OPA and the WPA, respectively. Because a part
of the transmit power is allocated to amplify-and-forward
the primary signal, so the curve didn’t start from zero.
From the Figure 4, we also can see that the OPA and the
WPA need allocate more power to amplify-and-forward
the primary signal compared with optimal approach.
i
SUT
max
P
10n
5
i
SUT
max
PW
01 2 34 5 67 8 910
0
1
2
3
4
5
6
7
SUT
i
Pmax (W)
SUR throughput (bp s/ Hz)
Opt i m al approach
Random relay wi t h OP A
Random relay wi t h W PA
Figure 4. SUR throughput ve r sus .
i
SUT
max
P
23 4 5 6 7 8910
3
3.5
4
4.5
5
5.5
6
6.5
Number of candi dat e SUT
i
SUR t hroughput (bps /Hz )
Opt im al approach
Random relay wi th OPA
Random relay wi th WPA
Figure 5. SUR throughput versus the number of candidate
SUTi.
Figure 5 shows that SUR throughput versus the num-
ber of candidate i compared with the OPA and the
WPA while the PUR’s target and
SUT
1i12SNR dB
10 ,
i
SUT
max
PWn
. As seen, the optimal approach
provides an appealing throughput increase by increasing
the number of candidate i while the OPA and the
WPA do not provide any throughput increase. This is
because the optimal secondary transmitter is selected
randomly in the OPA and the WPA.
SUT
6. Conclusions
In this paper, we consider a spectrum sharing scheme
that is a joint optimization of relay selection and power
allocation at the secondary transmitter, which aims to
achieve the maximum possible throughput for the sec-
ondary user. This paper considers the scenario where the
primary user is incapable of supporting its target SNR.
Specifically, the secondary transmitter tries to assist the
primary user with achieving its target SNR by allocating
a part of its power to amplify-and-forward the primary
signal over the primary user’s licensed spectrum bands.
At the same time, as a reward, the secondary transmitter
uses the remaining power to transmit its own signal over
the remaining licensed spectrum bands. By exhaustive
search for all candidate secondary transmitters, an opti-
mal secondary transmitter can be selected, which not
only can satisfy the primary user’s target SNR, but also
maximize the secondary user’s throughput. We study the
joint optimization of relay selection and power allocation
such that the secondary user’s throughput is maximized
on the condition that it satisfies the primary user’s target
SNR. Simulation results confirmed the efficiency of this
spectrum sharing scheme and it benefits to both the pri-
mary system and the secondary system.
7. Acknowledgements
This work is partially supported by National Major Sci-
Copyright © 2013 SciRes. CN
D. Q. ZHAO ET AL.
Copyright © 2013 SciRes. CN
385
ence and Technology Special Project of China
(2012ZX03005008, 2012ZX03005002-005), Chongqing
Municipal Education Commission Science and Technol-
ogy Research Project (KJ130513), Chongqing Basic and
Cutting edge Project (cstc2013jcyjA40020), 2011
Chongqing Universities outstanding achievement trans-
formation funded project, 2010 Chongqing Municipal
Intellectual Property special funds.
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