Outage Probability and Throughput Analysis of SWIPT Enabled Cognitive Relay Network With Ambient Backscatter
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3198 IEEE INTERNET OF THINGS JOURNAL, VOL. 5, NO. 4, AUGUST 2018
Outage Probability and Throughput Analysis of
SWIPT Enabled Cognitive Relay Network
With Ambient Backscatter
Syed Tariq Shah, Kae Won Choi , Senior Member, IEEE, Tae-Jin Lee , Member, IEEE,
and Min Young Chung , Member, IEEE
Abstract—In this paper, we propose an ambient backscatter and more flexible solution for the powering-up of energy-
(AB)-enabled decode-and-forward (DF) cognitive relay network constrained network nodes. Besides reliability and flexibility,
with wireless energy-harvesting capabilities. In our proposed another major advantage of the RF-EH technology is the abil-
scheme, a source node communicates with its destination node via
a radio frequency-powered DF relay. It is assumed that the relay ity of the RF signals to simultaneously carry both information
node is equipped with two different interfaces and can concur- and energy [5], [6]. This technology is known as simultaneous
rently harvest/decode and backscatter the received source signals. wireless information and power transfer (SWIPT) [7].
A power-splitting-based approach is adopted for the information For SWIPT operation, Varshney [5] has considered an ideal
processing and the energy harvesting at the relay. The analytical receiver design which has the ability to simultaneously har-
expressions for the outage probability at all of the receiving nodes
are derived. It has been shown that the analytical results match vest energy and process information from received RF signals.
the simulation results. It has also been shown that using the AB However, this ideal receiver design is not practical because the
for secondary communications can significantly improve the over- existing RF EH circuits cannot directly decode the informa-
all network performance in terms of the achievable throughput tion present in the received RF signals. To enable SWIPT,
and the energy efficiency. Zhou et al. [8] have proposed two practical EH receivers, i.e.,
Index Terms—Ambient backscatter (AB), cooperative relay time switching (TS) and power-splitting (PS). In TS approach
networks, simultaneous wireless information and power transfer the receiver circuit switches between EH and information pro-
(SWIPT), wireless energy harvesting (WEH). cessing in the time domain. On the other hand, in PS approach
the receiver circuits split the power of the received signal
into two portions: one for EH and the other for information
I. I NTRODUCTION
processing. Based on the TS and PS receiving architectures,
IRELESS energy harvesting (WEH)-based communi-
W cation networks have emerged as a new networking
paradigm. In WEH networks, the energy constrained nodes
Nasir et al. [9] proposed two relaying protocols namely, TS
relaying (TSR) protocol and PS relaying (PSR) protocol.
They further studied the performances of both protocols in
in the network can be remotely replenished via wireless an amplify-and-forward (AF) relay-based SWIPT network and
power transfer technology. Unlike legacy battery powered they concluded that at high transmission rates and low signal-
networks, the WEH networks do not require any manual to-noise ratio (SNR) the TSR protocol outperforms the PSR
recharging/replacement of batteries, leading to an enhanced protocol. For a decode-and-forward (DF) relay network, the
network lifetime with a significantly reduced operational TSR and PSR performances were analyzed in [10], reveal-
cost [1], [2], [4]. Furthermore, unlike other conventional ing that the PSR protocol achieved a performance that is
energy harvesting (EH) techniques such as thermoelectric, superior to that of the TSR. A relay-selection scheme for large-
wind, and solar energy, which are not very reliable and are scale EH-based Internet-of-Things (IoT) networks is proposed
highly dependent on the surrounding environments, ambient in [11]. The proposed scheme selects the relay based on
radio frequency (RF) EH has newly emerged as a reliable its residual-energy level and the channel quality. Here, the
proposed scheme significantly improved the outage-probability
Manuscript received January 9, 2018; revised April 20, 2018; accepted
May 8, 2018. Date of publication May 16, 2018; date of current performance of the EH relays.
version August 9, 2018. This work was supported by the National The performance of SWIPT in cognitive relay networks
Research Foundation of Korea through the Korean Government under Grant has been evaluated in various research works [12]–[15].
2014R1A5A1011478. (Corresponding author: Min Young Chung.)
S. T. Shah is with the College of Information and Communication Wang et al. [12] proposed an SWIPT-enabled AF relay-based
Engineering, Sungkyunkwan University, Suwon 16419, South Korea, and also cognitive network. In their proposed scheme, the relay node
with the Department of Telecommunication Engineering, FICT, Balochistan first harvests the energy from the primary-communication sig-
University of Information Technology, Engineering and Management
Sciences, Quetta, Pakistan (e-mail: syed.tariq@skku.edu). nals using a PSR protocol, and it then utilizes the harvested
K. W. Choi, T.-J. Lee, and M. Y. Chung are with the College of energy to send its own secondary information along with
Information and Communication Engineering, Sungkyunkwan University, the amplified primary signal. The secondary communication
Suwon 16419, South Korea (e-mail: kaewonchoi@skku.edu; tjlee@skku.edu;
mychung@skku.edu). in [12] not only acts as an interference to the primary commu-
Digital Object Identifier 10.1109/JIOT.2018.2837120 nication but it also consumes a portion of the scarce harvested
2327-4662 c 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
Authorized licensed use limited to: Sungkyunkwan University. Downloaded on August 25,2020 at 07:27:11 UTC from IEEE Xplore. Restrictions apply.SHAH et al.: OUTAGE PROBABILITY AND THROUGHPUT ANALYSIS OF SWIPT ENABLED COGNITIVE RELAY NETWORK WITH AB 3199
energy. A similar approach for a TSR-protocol-based DF relay metrics are outage probability, throughput, and energy effi-
was studied in [14]. Unlike [12], the network model of [14] ciency. For the remainder of this paper, the communications
consists of multiple relays, and an optimal relay-selection between the source-to-destination (S-to-D) nodes and the relay
scheme was proposed accordingly. Similar to [12], however, a (R)-to-neighboring nodes are labeled as primary communi-
two-way AF relay-based cognitive SWIPT network is studied cation and secondary communication, respectively. The main
in [15], wherein a portion of the harvested power is used to contributions of the present paper are summarized as follows.
transmit the secondary information of the network. 1) An AB-enabled SWIPT-based DF relay network is
The use of an ambient RF signal for WEH has been thor- proposed, where the relay node is enabled to concur-
oughly studied in [1] and [3]. Beside EH, another interesting rently perform both SWIPT and AB operations.
aspect of ambient RF signals is their use in the infor- 2) Since the proposed network model adopts the PSR pro-
mation transmission that is via the backscattering technol- tocol for EH and information processing at the relay, an
ogy [16], [17]. Ambient backscatter (AB) communication is adaptive PS mechanism has been used. For each com-
a new and promising communication method for low data munication block time, the considered PS mechanism
rate networks. The AB nodes do not require any specific dynamically adjusts the PS ratio based on the received
power storage/supply infrastructure. When data transmission SNR at the relay.
is required, the AB transmitter (AB-Tx) backscatters the RF 3) For both the primary and secondary communications,
signals that are received from an ambient source [16]. For the closed-form expressions for both the throughput and
the backscattering operation, the AB-Tx switches its mode the outage probability are derived. We show that our
between the nonreflect and reflect modes that correspond simulation results match our analytical results, which
to the bits “0” and “1,” respectively. On the other hand, not only verify our simulation and analytical models but
the AB receiver (AB-Rx) uses the envelope detection and also provide thorough practical insights into the effect
averaging techniques to decode the information from the of different system parameters on the overall network
received backscattered signals [17]. Since AB can be imple- performance.
mented without complex circuitry and encoding/decoding
mechanisms, it can be easily integrated into any wireless B. Organization
communication node [18], [19]. A prototype example of a The rest of this paper is organized as follows. Section II
full duplex AB has been reported in [18], where a WiFi AP presents the proposed system model and a detailed discus-
transmits data to normal WiFi clients and at the same time sion on EH, information decoding (ID), and AB operations.
decodes the backscatter signals reflected by different IoT sen- Section III derives analytical expressions for the outage
sors. However, due to the ambient nature of this technology, probability and the achievable throughput. The performance
the performance of the backscatter communication is highly analysis and the conclusion of this paper are presented in
dependent upon the availability of the ambient RF signals. Sections IV and V, respectively.
A. Paper Objectives and Contribution II. S YSTEM M ODEL AND P ROPOSED S CHEME
The idea of relays for coverage extension in wireless sensor A. System Model
networks has been well established and widely accepted [20]. We consider a network consisting of a primary source node
In cooperative wireless sensor networks, the battery power of S, a destination node D, a DF relay node R, and a secondary
the cooperating nodes (such as relay nodes) is usually lim- backscatter (BS) node C. The node S communicates with the
ited, and to actively perform their role in the network, these node D via node R, where R is considered as an energy-
nodes may need to rely on an additional charging mecha- constrained node with EH and AB capabilities. In addition to
nism [21], [22]. Moreover, besides the sole action of relaying, relying S-to-D primary communication, node R also communi-
these energy-constrained sensor nodes also comprise their own cates with node C using AB technology. We consider that node
sensed information that they must transmit to another neigh- R has two different interfaces for both SWIPT and backscat-
boring node. Therefore, an efficient relaying mechanism that tering operations. In summary, node R utilizes the SWIPT and
not only recharges the relay nodes but also aids them to backscatter interfaces for S → D primary communication and
transmit their own information is required. the R ↔ C secondary communication, respectively.
In this paper, we introduce an AB-enabled SWIPT DF Our considered network model is depicted in Fig. 1(a),
relay network where a source node transmits its informa- where g(i,j) and d(i,j) (i, j ∈ {S, R, C, D}) denote the chan-
tion to a destination node via an energy constrained relay. nel coefficients and the distance between nodes, respectively.
The relay node harvests a portion of the received source- The channel gains between nodes are modeled as Rayleigh
signal power using the PS approach, and it then utilizes this block-fading channels and for each time block the chan-
harvested energy to forward the received information to its nels are independent and identically distributed. A path
destination. In addition to the relaying operation, the relay loss between communicating nodes has been modeled as a
node also simultaneously communicates with a neighboring distance-dependent path loss model with rate d−ε , where d is
node using AB communication. Such a network model can the distance between nodes and ε is the path-loss exponent.
widely be used in emerging energy-constrained IoT-based The use of such channel and path-loss models is motivated by
relay networks [11]. In the proposed scheme, the performance previous research work done in this area [9], [10], [12]–[15].
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using the harvested energy, node R forwards the decoded
source signal to node D. Meanwhile, C also backscatters its
information to node R.
More specifically, node S transmits its information signals
to node R during m1 (phase I). The received source signal
(Y(S,R) ) and SNR at node R during m1 can, respectively, be
expressed as
PS
(a) Y(S,R) = ε g(S,R) xS + n0 (1)
d(S,R)
PS |g(S,R) |2
γR = ε (2)
d(S,R) σ2
where xS , PS , n0 , and σ 2 are the normalized information signal
from node S, source Tx power, additive white Gaussian noise
(AWGN), and the variance of the AWGN, respectively. The
relay node splits the signal √ Y(S,R) that is received
√ via EH/ID
(b) interface
√ into two portions, αY (S,R) and 1 − αY
√ (S,R) . The
αY(S,R) portion of signal is used for EH and 1 − αY(S,R)
Fig. 1. System model. (a) System model AB enabled SWIPT relay network. portion is used for ID. After a successful EH the received SNR
(b) Time-block structure for proposed network model.
at node R can be expressed as
TABLE I
(1 − α)PS |g(S,R) |2
TABLE OF N OTATIONS γ̃R = ε . (3)
d(S,R) σ2
In the proposed DF relay network, the received source signal
at the node R can only be successfully decoded if its SNR is
greater than or equal to the minimum required decoding-SNR
γ0 , where γ0 = 22U − 1 and U is the source transmission rate.
Therefore, based on (3) and γ0 the value of the PS factor can
be calculated as
ε
γ0 σ 2 d(S,R)
α = 1− . (4)
PS |g(S,R) |2
In our proposed DF relay network, the PS strategy that is
provided by (4) is ideal. More specifically, if the value of PS
factor α is greater than (4), a small portion of the signal power
is used for EH, and an unnecessarily-high power is allocated
for the signal decoding, resulting in a waste of the valuable
power resource. Alternatively, if the value of the PS factor α
is less than (4), the relay node utilizes more power for the EH,
thereby resulting in the decoding failure of the source signal.
As shown in Fig. 1(b), the transmission block time T is divided Based on PS factor α derived in (4), the harvested power (PR )
into two equal slots m1 and m2 and a PS-based relaying proto- at node R from the received source signal is defined as PR =
col (PSR) is used for EH and information processing at node ε
(η/d(S,R) ε
)(PS |g(S,R) |2 − γ0 d(S,R) σ 2 ), where η is the energy
R [10]. The α in Fig. 1(b) is the PS factor and its value is conversion efficiency and its value is within the range of (0, 1].
real in (0, 1]. For the sake of readers’ convenience, all the Meanwhile, node R also transfers its own secondary infor-
notations used in this paper are summarized in Table I. mation to node C by backscattering the received signal Y(S,R)
using its AB interface. As a result of this backscattering oper-
B. Energy Harvesting, Information Decoding, and Ambient ation at node R, the received SNR at node C (BS receiver)
Backscatter Operations can be expressed as [23]
As shown in Fig. 1, the whole communication procedure is ζ PS |g(S,R) |2 |g(R,C) |2
divided into two phases. In phase I, node S transmits its infor- γCBS = ε ε (5)
d(S,R) d(R,C) σ2
mation to node R during time slot m1 . Node R harvests energy
and decodes the received signal while concurrently backscat- where ζ is the fraction of power scattered back by node R and
ter it to transmit its own information to node C. The relay its value is within the range of (0, 1].
node performs both of these operations using two separate In the phase II of the proposed scheme, the node R forwards
interfaces, i.e., AB interface and EH/ID interface. In phase II, the decoded primary signal using the PR . The signal broadcast
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by node R during m2 time slot can be written as SR = PR x̃S , Proposition 1: According to (9) the outage probability of
where x̃S is the decoded version of source-information signal primary communication can be expressed as
xS . Note that during m2 , node C acts as an AB transmit-
ter and communicates with the node R by backscattering the out = J1 + J2
PD (10)
received ambient signal (i.e., SR ). It can be observed that, dur- where
ing both time-slots m1 and m2 the relay node operates in a
l
full-duplex mode and simultaneously performs both primary J1 = 1 − exp − (11)
communication and backscatter operations. The backscatter (S,R)
signal transmitted (received) from (at) relay node in both time and
slots is a modulated version of the transmitted (received) pri-
a n exp(n)E1 (n) 4β
mary radio signal. Therefore, it can effectively be canceled out J2 = exp − 1− K1 ( 4βτ ) .
using recent self-interference cancellation techniques proposed PS (S,R) PS (S,R) τ
in [24]–[28]. (12)
In case of primary communication, the secondary AB com-
The K1 (.) in (12) is the first-order modified Bessel function
munication, however, might act as an interference. Therefore,
of the second kind [29]. Other variables are
the signal that is received at the destination node D (Y(R,D) )
during m2 can be expressed as (R,D)
n=
w (R,C) (C,D)
PR ε
Y(R,D) = ε g(R,D) x̃S + IBS + n0 (6) ζ γ0 d(R,D)
d(R,D) w= ε ε
d(R,C) d(C,D)
√ ε ε
where IBS [( PR ζ |g(R,C) |2 |g(C,D) |2 )/( d(R,C) d(C,D) )] is ε
a = γ0 d(S,R) σ2
the interference that is
caused by the BS signal reflected by ε
γ0 d(S,R) ε
d(R,D) σ2
node C and d(C,D) = d(R,C) 2 + d(R,D)
2 − 2d(R,C) d(R,D) cos(θ ), β=
η (R,D)
where θ is the angle between nodes C, R, and D (∠CRD).
1
Based on the received Y(R,D) signal in (6), the signal- τ =
to-interference-plus-noise ratio (SINR) at node D can be PS (S,R)
expressed as and
PR |g(R,D) |2 ε
γ0 d(S,R) σ2
γD = ε
l= .
d(R,D) σ 2 + IBS PS
ε
ηq|g(R,D) |2 d(R,C) ε
d(C,D)
=
Proof: Proof of Proposition 1 is provided in
ε
ζ ηq|g(R,C) |2 |g(C,D) |2 d(R,D) ε
+ d(S,R) ε
d(R,C) ε
d(R,D) ε
d(C,D) σ2 Appendix A.
(7) Based on PD out derived in Proposition 1 the achievable
ε throughput of the primary communication is given by
where q = PS |g(S,R) |2 − γ0 d(S,R) σ 2 . Similarly, as a result of
backscattering operation at node C (i.e., secondary communi- CD = 1 − PD out U(T/2)/T (13)
cation during m2 ), the received SNR at node R can be written
where T/2 is the effective S-to-D communication time.
as
Similar to the primary communication, the outage in the
ε
ζ η|g(R,C) |2 |g(C,R) |2 PS |g(S,R) |2 − γ0 d(S,R) σ2 secondary communication occurs when the received SNR
γRBS = ε ε ε . (8) of a backscattered signal at receiving node is less than a
d(S,R) d(R,C) d(C,R) σ2
predefined threshold. Thus, the outage probability of the
III. O UTAGE P ROBABILITY AND R-to-C secondary communication link can be defined as
T HROUGHPUT A NALYSIS
out = Pr γC ≤ γ1
PRC BS
(14)
The outage of a communication link occurs when the
received SNR/SINR at receiving node is less than a predefined where γ1 = 22U − 1 is the threshold SNR for the AB com-
threshold SNR/SINR. The outage probability of primary com- munication and U is the BS transmission rate. The analytical
munication (i.e., S-to-D link) can be calculated as expression for the outage probability of node C (PBC out ) can be
obtained using Proposition 2.
out = Pr(γ
PD
R
< γ0 ) + Pr(γR > γ0 , γD < γ0 ) .
(9)
Proposition 2: For secondary communication during m1 ,
J1 J2 the outage probability at node C can be obtained as
The terms J1 and J2 in (9) show that the outage of primary
communication link occurs when the received SNR/SINR at ζ PS |g(S,R) |2 |g(R,C) |2
Pout = Pr
RC
ε ε ≤ γ1
any receiving node (i.e., node R and node D) is less than d(S,R) d(R,C) σ2
a decoding threshold SNR (γ0 ). The analytical expression = 1 − νK1 (ν) (15)
for outage probability of the primary-communication link is
provided in the following proposition. where v ([4hγ1 ]/[ (S,R) (R,C) ]).
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Leg
Proof: Proof of Proposition 2 is provided in In legacy scheme, the SNR at relay node is γR = γR and
Leg
Appendix B. SNR at destination node γD can be defined as
Unlike that of the R-to-C, the C-to-R secondary communi-
ε
|g(R,D) |2 η PS |g(S,R) |2 − γ0 d(S,R) σ2
cation during the m2 slot is highly dependent on the received Leg
SNR (γR ) of the primary source signal (Y(S,R) ) at node R. γD = ε ε . (22)
d(S,R) d(R,D) σ2
It is because if the received SNR is below than a predefined
threshold value (i.e., γ0 ), the relay will not be able to decode Note that, unlike (7) the SNR expression in (22) does not
it. As a result of this decoding failure, there will be no primary include any interference term. The analytical expression for
communication during m2 which also means that there will be outage probability of S-to-D communication link in legacy
no ambient signal available for node C to perform backscat- scheme is derived in Proposition 4.
ter communication. Hence, the outage probability of C-to-R Proposition 4: Based on (21) the outage probability expres-
secondary communication link can be expressed as sion for legacy scheme can be expressed as
Leg Leg
PLout = 1 − Pr γR ≥ γ0 , γD ≥ γ0 (23)
out = Pr(γ
PCR R < γ0 ) + Pr γR > γ0 , γR < γ1 .
BS
(16)
L1 exp − PS a(S,R)
L2
= 1− (24)
PS (S,R)
The outage probability expression for C-to-R AB communi-
∞ ε ε
cation during m2 is derived in Proposition 3. q γ0 d(S,R) d(R,D) σ2
× exp − exp −
Proposition 3: Based on (16) the outage probability expres- PS (S,R) η (R,D) q
sion for secondary communication between node C-to-R can 0
be expressed as (25)
a
= 1 − exp − (26)
out = L1 + L2
PCR
(17) PS (S,R)
⎛ ⎞
exp − PS a(S,R)
∞ ε ε ε ε
q 4γ0 d(S,R) d(R,D) σ2 4γ0 d(S,R) d(R,D) σ2
= 1− exp − oK1 (o)dq × K1 ⎝ ⎠.
PS (S,R) PS (S,R) PS η (R,D) (S,R) PS η (R,D) (S,R)
0
(27)
where o = (4j/[q (C,R) (R,C) ]) and j =
ε
[(γ1 d(S,R) ε
d(R,C) ε
d(C,R) σ 2 )/ηζ ]. Proof: The proof of Proposition 4 follows the similar
Proof: Proof of Proposition 3 is provided in steps as provided in Appendix C and therefore it is omitted
Appendix C. here.
Similar to the primary communication, the achievable The energy efficiency in both our proposed and legacy
throughput of the secondary communication can also be schemes can be defined as the achievable sum-throughput
calculated using the outage probabilities that are derived under the unit-energy consumption [30]. Thus, energy efficien-
using (15) and (17). More specifically, the achievable cies of the proposed and the legacy networks can, respectively,
throughput of the AB communications at node C (CCBS ) be calculated as
during m1 and at node R (CRBS ) during m2 can be CT
P = (28)
calculated as PS
CLeg
RC(or CR) L = . (29)
R) = 1 − Pout
BS
CC(or U(T/2)/T. (18) PS
Finally, the sum-throughput of the overall network can be
obtained as
IV. P ERFORMANCE E VALUATION
CT = CD + CCBS + CRBS . (19) In this section, the analytical results that are derived in
Section III are used to provide a detailed insight into the effect
In order to investigate the efficiency of our proposed of the different systemic parameters on the overall network
scheme, we compare our proposed scheme with a legacy performance. Unless otherwise stated, for the performance
DF SWIPT relay scheme without backscatters [10]. In legacy analysis, the values of the different systemic parameters are
scheme, the throughput of primary S-to-D communication link set to PS = 1 W, η = 1, ζ = 0.35, and σ 2 = 10−3 W.
can be calculated as The distance between source-to-destination is set to 3 m
(i.e., dS,R = dR,D = 1.5 m) and the relay-to-secondary
CL = 1 − PLout U(T/2)/T (20) node distance is set to 2 m (i.e., dR,C = dC,R = 2 m).
The values of transmission rates for both secondary and pri-
where PLout is the outage probability of S-to-D communication mary communications are set to U = 2 bits/s/Hz and
link in legacy scheme and it can be calculated as U = 1 bits/s/Hz, respectively; this is because the trans-
mission rate of radio communication is generally higher than
Leg Leg
PLout = Pr min γR , γD < γ0 . (21) that of AB communication.
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Fig. 2. Outage probability with varying values of transmission rates (U and Fig. 4. Outage probability with varying values of transmission power (PS )
U) for PS = 1, ζ = 0.35, and η = 1. for ζ = 0.35, U = 2 bits/s/Hz, U = 1 bits/s/Hz, and η = 1.
Fig. 3. Throughput with varying values of transmission rates (U and U) for
PS = 1, ζ = 0.35, and η = 1. Fig. 5. Throughput with varying values of transmission power (PS ) for
ζ = 0.35, U = 2 bits/s/Hz, U = 1 bits/s/Hz, and η = 1.
The outage probability and the achievable throughput with at transmission rate less than a certain value, the through-
varying source-transmission rates are shown in Figs. 2 and 3, put decreases. Nonetheless, for transmission rate larger than a
respectively. It is evident that the analytical results of this paper certain value, the throughput again decreases, it is because the
match the corresponding simulation results, thereby verify- receiving node is unable to successfully decode a large amount
ing the accuracy of the our analysis. It is shown in Fig. 2 of received data in limited time. It can also be observed from
that as the value of transmission rate increases the outage Fig. 3 that the overall network sum-rate of proposed scheme
probabilities at destination nodes also increase. It is because is significantly higher than legacy scheme. However, in legacy
the decoding threshold values (i.e., γ0 and γ1 ) in (9), (14), scheme the achievable throughput at primary destination node
and (16) are increasing functions of U and U. Therefore, D is slightly higher than the proposed scheme. It is because,
higher transmission rates result in larger values of decoding in the proposed scheme, the secondary backscatter commu-
thresholds, which further leads to higher outage probabilities nications during time slot m2 [see (7)] causes interference to
at destinations. On the other hand, the achievable through- the primary communication. This tradeoff between improved
put of both primary and secondary communications in our network sum-rate and decreased primary throughput is part
proposed scheme increases as the transmission rate increases, of the underlay cognitive networks and cannot be completely
but then after a certain point (i.e., U 2 bits/s/Hz, and U avoided. Similar trends between proposed and legacy schemes
1 bits/s/Hz during m1 and 2 bits/s/Hz during m2 ) it starts can be observed in rest of this paper.
declining. This is because the achievable throughput depends Figs. 4 and 5 depict the outage probability and achiev-
on the transmission rate [see (13) and (18)] and therefore, able throughput with varying source transmission power (PS )
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Fig. 6. Outage probability with varying values of BS reflection coefficient Fig. 8. Outage probability with varying values of energy conversion efficiency
(ζ ) for Ps = 1, U = 2 bits/s/Hz, U = 1 bits/s/Hz, and η = 1. (η) for Ps = 1, U = 2 bits/s/Hz, U = 1 bits/s/Hz, and ζ = 0.35.
Fig. 7. Throughput with varying values of BS reflection coefficient (ζ ) for Fig. 9. Throughput with varying values of energy conversion efficiency (η)
Ps = 1, U = 2 bits/s/Hz, U = 1 bits/s/Hz, and η = 1. for Ps = 1, U = 2 bits/s/Hz, U = 1 bits/s/Hz, and ζ = 0.35.
values, respectively. The outage probability plot in Fig. 4 the primary and secondary communications are provided in
shows that as the value of transmission power increases the Figs. 6 and 7, respectively. It has been shown that as the
outage probabilities of both primary and secondary commu- value of ζ increases, the outage probability of secondary nodes
nication decreases. It is because the higher values of the PS decreases and their throughput increases. It is due to the fact
result in improved SNR/SINR at receiving nodes which ulti- that at higher values of ζ , a larger portion of received signal
mately decreases their outage probability. Furthermore, it can power is reflected back by the AB-Tx, which leads to improved
also be observed from Fig. 4 that the outage probability of SNR and consequently results in reduced outage probability
secondary communication during m1 (i.e., PRC out ) is lower than and improved throughput at AB-Rx. On the other hand, unlike
others. It is because, unlike SWIPT operation where a por- secondary communication, the increasing values of ζ severely
tion of the received signal is used for ID, the AB operation affects the outage probability and throughput of primary com-
at the relay is directly performed by backscattering the whole munication. It is because, during m2 , the larger values of ζ
received signal to node C using relays backscatter interface. results in more severe interference to primary communication
Similar to the outage probability, the throughput results that [see (7)].
are plotted in Fig. 5 also show the same trend, where, as the The analysis of the outage probability and the throughput
value of the transmission power is increased, the achievable of the system with varying values of the energy conversion
throughputs at the destination nodes also increase. efficiency, η, are shown in Figs. 8 and 9. It can be observed
The effects of the backscattering reflection coefficient ζ on that the throughputs of the primary (i.e., S-R-D) and sec-
the outage probability and the achievable throughput of both ondary communications during the m2 (i.e., C-to-R) increase
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Fig. 10. Outage probability with varying values of source-to-relay distance Fig. 12. Energy efficiency with varying values of transmission power (PS )
(dSR ) for Ps = 1, U = 2 bits/s/Hz, U = 1 bits/s/Hz, ζ = 0.35, and η = 1. for ζ = 0.35, U = 2 bits/s/Hz, U = 1 bits/s/Hz, and η = 1.
further leads to weak transmit power at relay PR which eventu-
ally results in poor SINR/SNR for both primary and secondary
communications [see (7) and (8)]. The energy efficiency of the
proposed network with varying values of transmission power
PS is plotted in Fig. 12. It can be observed that compare to
legacy scheme the proposed scheme significantly increases the
network energy efficiency. It is also shown that there exists a
point where the systems energy efficiency is maximum i.e.,
PS 0.1.
V. C ONCLUSION
In this paper, we have studied the performance of an AB
enabled SWIPT-based DF relay network. Analytical expres-
sions for outage probability and achievable throughput at all
destination nodes are derived. With the help of analytical and
numerical results, the impact of different system parameters
Fig. 11. Throughput with varying values of source-to-relay distance (dSR )
on overall network performance has been studied. We show
for Ps = 1, U = 2 bits/s/Hz, U = 1 bits/s/Hz, ζ = 0.35, and η = 1. that the proposed AB enabled SWIPT DF relay network can
significantly improve both the network sum-throughput and
energy efficiency. It is also shown that the performance of the
proposed scheme is highly affected by the source transmission
whereas their outage-probability values decrease as the value power and transmission rates.
of η increases. However, the throughput and outage probability
of secondary communication between nodes R and C during
A PPENDIX A
m1 are not affected by the varying values of η. The reason is
that the AB-Tx at node R backscatters the source signal Y(S,R) This Appendix derives the outage probability of primary
during m1 , whose power is independent of η. Whereas, during communication link provided in (10). By substituting the
m2 , the node C reflects back the signal SR transmitted by node values of γR from (2) in J1 , the first term of (9) becomes
R, whose power PR is an increasing function of η.
J1 = Pr |g(S,R) |2 < l
The impact of the S-to-R distance, dSR , on the outage
probability and throughput of primary and secondary commu- = F|g(S,R) |2 (l)
nications are depicted in Figs. 10 and 11. The results show that l
the performance of both the outage probability and throughput = 1 − exp − (30)
(S,R)
decreases as the value of dSR increases. This is because the
ε
larger values of dSR result in increased path loss d(S,R) which ε
where l = [(γ0 d(S,R) σ 2 )/Ps ], F|g(S,R) |2 (l), and (S,R) are the
eventually causes lower SNR and harvested power at relay cumulative distribution function and mean of the exponen-
[see (4) and (7)]. Moreover, this decline in harvested power tial random variable |g(S,R) |2 , respectively. Similarly, after
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inserting γD from (7) into (9), the second term of (9) becomes where
∞ n = [( (R,D) )/(w (R,C) (C,D) )] and E1 (x) =
x [exp(−t)/t]dt is the expectational integral. By substituting
J2 the value of I1 derived in (34) into J2 , the integral in (32)
PS |g(S,R) |2 can be solved as
= Pr ε > γ0
d(S,R) σ2 ∞
b
ε
ηq|g(R,D) |2 d(R,C) ε
d(C,D) J2 = 1 − exp − n exp(n)E1 (n) fq (Q)dq
q (R,D)
ε
ζ ηq|g(R,C) |2 |g(C,D) |2 d(R,D) ε
+ d(S,R) ε ε ε σ2 0
d(R,C) d(R,D) d(C,D)
exp − PS a(S,R)
∞
q
< γ0 = exp − dq
PS (S,R) PS (S,R)
0
ε ∞
= Pr Ps |g(S,R) |2 − γ0 d(S,R) σ2 > 0
− n exp(n)E1 (n)
b
|g(R,D) | < + w|g(R,C) |2 |g(C,D) |2
2
(31) 0
q
q b
× exp − − dq
where b = ε
([γ0 d(S,R) ε
d(R,D) σ 2 )/η] and w = PS (S,R) q (R,D)
n exp(n)E1 (n) 4β
ε ε ε
[(ζ γ0 d(R,D) )/(d(R,C) d(C,D) )]. Conditioning J2 on q the (31) a
can be expressed as = exp − 1− K1 4βτ
PS (S,R) PS (S,R) τ
∞ (35)
b
J2 = 1 − Pr |g(R,D) | > + w|g(R,C) |2 |g(C,D) |2
2
where β = (b/ (R,D) ) and τ = (1/[PS (S,R) ]). The sec-
q
ond
∞ integral part in√above equation is solved according to
−(β/4z)−τ z dz = (β/τ )K (√βτ ) [29] [where K (.) is the
0
I1 e
0 1 1
× fq (Q)dq (32) first order modified Bessel function of second kind]. Thus, the
outage probability of primary communication can be obtained
where fq (Q) = (1/[PS (S,R) ]) exp(−([q + a]/[PS (S,R) ])) by substituting the J1 [from (30)] and J2 [from (35)] in (10).
is the probability density function (PDF) of q and a = This completes the proof of Proposition 1.
ε
γ0 d(S,R) σ 2 . After conditioning on |g(R,C) |2 |g(C,D) |2 , the term
I1 of (32) can be expressed as A PPENDIX B
∞ ∞ The proof provided in this Appendix is for Proposition 2
b
I1 = Pr |g(R,D) |2 > + wz1 z2 where the analytical expression for outage probability of R-
q to-C secondary communication link is derived. Based on (15),
0 0
× f|g(R,C) |2 (z1 )f|g(C,D) |2 (z2 )dz1 dz2 the PRC
out can also be expressed as
∞ ∞ hγ1
b wz1 z2 PRC
out = Pr |g(S,R) | 2
≤ (36)
= exp − + f|g(R,C) |2 (z1 ) |g(R,C) |2
q (R,D) (R,D) ε ε
0 0 where h = [(d(S,R) d(R,C) σ 2 )/ζ PS ]. Conditioning the (36) on
× f|g(C,D) |2 (z2 )dz1 dz2 (33) |g(R,C) | , the Pout can be expressed as
2 RC
∞
where f|g(R,C) |2 (z1 ) = [1/ (R,C) ] exp(−[z1 / (R,C) ]) and hγ1
f|g(C,D) |2 (z2 ) = [1/ (C,D) ] exp(−[z2 / (C,D) ]) are the PDF PRC
out = 1 − exp − f|g(S,R) |2 (z)dz
z (R,C)
of |g(R,C) |2 and |g(C,D) |2 , respectively. Similarly, (R,C) and 0
⎡
∞
(C,D) are their mean values. After inserting the PDF values 1 z
in I1 , the integrals in (33) can be solved as = ⎣ exp − dz
(S,R) (S,R)
0
⎤
exp − q (R,D)
b ∞ ∞
z2 z hγ1
I1 = exp − − exp − − dz⎦
(R,C) (C,D) (C,D) (S,R) z (R,C)
0 0
∞ = 1 − vK1 (v) (37)
−z1 wz1 z2
× exp − dz1 dz2
(R,D) (R,C) where ν (4hγ1 /[ (S,R) (R,C) ]), and f|g(S,R) |2 (z) =
0
[1/ (S,R) ] exp(−[z/ (S,R) ]) is the PDF of exponential random
∞ exp − z2
variable |g(S,R) |2 . This completes the proof of Proposition 2.
b (C,D)
= n exp − dz2
q (R,D) z2 + n (C,D)
0 A PPENDIX C
b The outage probability expression for secondary commu-
= exp − n exp(n)E1 (n) (34)
q (R,D) nication during m2 (PCR
out ) is derived in this Appendix. Note
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Syed Tariq Shah received the M.S. and Ph.D. Tae-Jin Lee (M’99) received the B.S. and M.S.
degrees in electronic and electrical engineering from degrees in electronics engineering from Yonsei
Sungkyunkwan University, Seoul, South Korea, in University, Seoul, South Korea, in 1989 and 1991,
2015 and 2018, respectively. respectively, the M.S.E. degree in electrical engi-
He is currently an Assistant Professor with the neering and computer science from the University
Department of Telecommunications Engineering, of Michigan, Ann Arbor, MI, USA, in 1995, and the
Balochistan University of Information Technology, Ph.D. degree in electrical and computer engineering
Engineering and Management Sciences, Quetta, from the University of Texas at Austin, Austin, TX,
Pakistan. His current research interests include 5G USA, in 1999.
networks, LTE-Advanced networks, wireless energy In 1999, he joined the Corporate Research and
harvesting, and device-to-device communications. Development Center, Samsung Electronics, Suwon,
South Korea, as a Senior Engineer. Since 2001, he has been a Professor with
the College of Information and Communication Engineering, Sungkyunkwan
University, Suwon. From 2007 to 2008, he was a Visiting Professor with
Pennsylvania State University, University Park, PA, USA. His current research
interests include performance evaluation, resource allocation, medium access
control, and design of communication networks and systems, wireless
LANs/PANs, vehicular networks, energy-harvesting networks, Internet of
Things, ad hoc/sensor/RFID networks, and next-generation wireless commu-
nication systems.
Kae Won Choi (M’08–SM’15) received the B.S. Dr. Lee has been a voting member of the IEEE 802.11 WLAN Working
degree in civil, urban, and geosystem engineering Group and a member of the IEICE.
and M.S. and Ph.D. degrees in electrical engi-
neering and computer science from Seoul National
University, Seoul, South Korea, in 2001, 2003, and
2007, respectively.
From 2008 to 2009, he was with the Min Young Chung (M’04) received the B.S.,
Telecommunication Business of Samsung M.S., and Ph.D. degrees in electrical engineering
Electronics Company Ltd., Suwon, South Korea. from the Korea Advanced Institute of Science and
From 2009 to 2010, he was a Post-Doctoral Technology, Daejeon, South Korea, in 1990, 1993,
Researcher with the Department of Electrical and and 1999, respectively.
Computer Engineering, University of Manitoba, Winnipeg, MB, Canada. From 1999 to 2002, he was a Senior Member
From 2010 to 2016, he was an Assistant Professor with the Department of of Technical Staff with the Electronics and
Computer Science and Engineering, Seoul National University of Science Telecommunications Research Institute, Daejeon,
and Technology, Seoul. In 2016, he joined the faculty of Sungkyunkwan where he was engaged in research on the devel-
University, Seoul, where he is currently an Associate Professor with the opment of multiprotocol label switching systems.
College of Information and Communication Engineering. His current research In 2002, he joined the faculty of Sungkyunkwan
interests include RF energy transfer, visible light communication, device-to- University, Suwon, South Korea, where he is currently a Professor with
device communication, cognitive radio, and radio resource management. the College of Information and Communication Engineering. His current
Dr. Choi has been serving as an Editor of IEEE C OMMUNICATIONS research interests include D2D communications, software-defined networking,
S URVEYS AND T UTORIALS since 2014, IEEE W IRELESS 5G wireless communication networks, and wireless energy harvesting.
C OMMUNICATIONS L ETTERS since 2015, and the IEEE T RANSACTIONS Dr. Chung was an Editor of the Journal of Communications and Networks
ON W IRELESS C OMMUNICATIONS since 2017. from 2005 to 2011. He is a member of the IEICE, KICS, KIPS, and KISS.
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