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TELKOMNIKA Telecommunication, Computing, Electronics and Control
Vol. 18, No. 5, October 2020, pp. 2335~2340
ISSN: 1693-6930, accredited First Grade by Kemenristekdikti, Decree No: 21/E/KPT/2018
DOI: 10.12928/TELKOMNIKA.v18i5.13861  2335
Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA
Intercept probability analysis in DF time switching full-duplex
relaying network with impact of Co-channel interference
at the eavesdropper
Pham Minh Nam1
, Phu Tran Tin2
, Minh Tran3
1
Faculty of Electronics Technology, Industrial University of Ho Chi Minh City, Vietnam
2
Wireless Communications Research Group, Faculty of Electrical and Electronics Engineering,
Ton Duc Thang University, Vietnam
3
Optoelectronics Research Group, Faculty of Electrical and Electronics Engineering,
Ton Duc Thang University, Vietnam
Article Info ABSTRACT
Article history:
Received Aug 10, 2019
Revised Feb 25, 2020
Accepted Mar 18, 2020
In this research, we propose and investigate intercept probability analysis
in DF time switching relaying full-duplex with impact of Co-channel
interference at the eavesdropper. In the beginning stage, we present the DF
time switching relaying full-duplex with the Impact of Co-channel interference
at the eavesdropper. Furthermore, the closed-form expression of the intercept
probability (IP) is analyzed and derived in connection with the primary system
parameters. Finally, the Monte Carlo simulation is performed for verifying
the correctness of the analytical section. From the research results, a novel
solution and some recommendations can be proposed for the communication
network in the near future.
Keywords:
Co-channel
Energy harvesting
Full-duplex
Interference
Outage probability This is an open access article under the CC BY-SA license.
Corresponding Author:
Phu Tran Tin,
Wireless Communications Research Group,
Faculty of Electrical and Electronics Engineering,
Ton Duc Thang University, Ho Chi Minh City, Vietnam.
Email: phutrantin@tdtu.edu.vn
1. INTRODUCTION
Recently, wireless‐powered communication has gained considerable interest because of its capability
to deal with the energy scarcity in energy‐constrained wireless networks. An attractive solution that overcomes
the above limitation is to harvest energy from human-made radio frequency (RF) electromagnetic radiation
(also known as wireless power transfer) [1-6]. Based on that fact, the WPCN and its efficiency are considered
as the main research direction in the communication network. In [7], the authors investigated the fundamental
tradeoff between the rate of transporting a commodity between one point and another. Furthermore, practical
receiver designs for simultaneous wireless information and power transfer is detail studied in [8]. Moreover,
the energy harvesting (EH) communication network with the partial network-level cooperation was proposed
and investigated in [9]. Authors in [10] presented the cognitive relay networks with the EH and information
transmission (IT) at the same time. Moreover, the TSP and PSP protocols in the EH communication network
and the performance comparison between them are investigated in [11-15].
 ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 5, October 2020: 2335 - 2340
2336
In this research, we propose and investigate Intercept Probability (IP) Analysis in DF time switching
Relaying full-duplex with Impact of Co-channel Interference at the eavesdropper. The main contribution of
this paper can be drawn as the follows;
− The DF time switching Relaying full-duplex (FD) with the Impact of Co-channel Interference
at the eavesdropper is proposed and investigated.
− The exact and asymptotic analysis of the system IP is derived and investigated in connection with
the primary system parameters.
− The Monte Carlo simulation is conducted for verifying the correctness of the analytical analysis.
In this paper, the system model of the communication network has considered in second section.
The IP analysis is presented in the third section in detail. Numerical results and some conclusions is drawn
in the fourth sections. In the final section, some conclusions are proposed.
2. SYSTEM MODEL
In this section, Figure 1 proposed the DF time switching relaying full-duplex (FD) with the Impact of
Co-channel interference at the eavesdropper. The energy harvesting (EH) and information transferring (IT)
phases are drawn in Figure 2 [16-20].
IT PhaseEH Phase
S E
R
1... MI I
Interference Links
D
Wiretap
T
EHat R
T (1 )T−
IT
S R D⎯⎯→ ⎯⎯→
Figure 1. System model Figure 2. The EH and IT phases
2.1. Energy harvesting (EH) phase
During the first phase, the received signal at the relay can be given by:
r sr s ry h x n= + (1)
The average transmitted power at the relay can be obtained as:
2
2
(1 ) (1 )
s srh
r s sr
TP hE
P P h
T T


 
= = =
− −
(2)
2.2. Information transmission (IT) phase
In the second phase, the received signal at the relay can be given by
r sr s rr r ry h x h x n= + + (3)
where hrr is the loopback interference channel and  2
r rx P = . The received signal at the eavesdropper can
be expressed as:
1
n n
M
E RE r I I E E
n
y h x x h n
=
= + + (4)
TELKOMNIKA Telecommun Comput El Control 
Intercept probability analysis in DF time switching full-duplex relaying network… (Pham Minh Nam)
2337
where REh is the relay to the eavesdropper channel gain, En is AWGN with variance N0 and nI Eh is the channel
gain between nth
interference source and eavesdropper. We assume that all the interferences source have
the same transmit power IP , it mean that  2
0...
nI I
n M
x P
=
 = From (4), the signal to noise ratio (SNR) at the
eavesdropper can be given as;
2
2
0
1
n
RE r
E M
I I E
n
h P
P h N

=
=
+
(5)
Substituting (2) into (5), (5) can be rewritten as;
2 2 2 2
2 2
0
1 1
1
1n n
s sr RE sr RE
E M M
I I E I E
n n
P h h h h X
Y
P h N h
  

= =
 
= = =
 +
+  + 
(6)
where
0
sP
N
 = ,
0
IP
N
 = ,
2 2
sr REX h h= and
2
1
n
M
I E
n
Y h
=
= 
2.3. Remark 1
The probability density function (PDF) of random variable (RV) Z can be obtained as
13
3
( )
( ) exp( )
( 1)!
M
M
Yf t t t
M

−
= −
−
(7)
where 3 is the mean of RV Y.
3. INTERCEPT PROBABILITY (IP) ANALYSIS
3.1. Exact analysis
The IP can be defined by;
( )Pr E thIP  =  (8)
substituting (6) into (8), the IP can be reformulated as (9).
0
Pr 1 Pr
1 1
( 1)
1 ( )
th th
th
X Y
X X
IP
Y Y
y
F f y dy
 
 



    
=  = −    
 +  +   
 + 
= −   

(9)
Next, the cumulative distribution function (CDF) of X can be computed as (10).
( )
2 2
2 2 2
2
2
0
2
1 1
0
( ) Pr( ) Pr
| ( )
1 exp exp
REsr
X sr RE sr
rd
RE hh
x
F x h h x h
h
x
F h a f a da
a
x
a da
a

 


 
 =  = 
 
 
 
= =  
 
 
= − −  − 
 


(10)
 ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 5, October 2020: 2335 - 2340
2338
Here the (10) can be rewritten as the following;
( )1 2 1 1 2( ) 1 2 2XF x x K x   = −  (11)
applying (7) and (11), (9) can be obtained by;
13 1 2 1 2
3 1
0
2( ) ( 1)
exp( ) ( 1) 2
( 1)!
M
Mth th y
IP y y y K dy
M
      

 

−
  +
=  −   +    −   
 (12)
3.2. Asymptotic analysis
At the high SNR regime (  →  ), (6) can be calculated by (13).
E
X
Y

  


(13)
The IPcan be computed as (14).
0
1 Pr 1 ( )th
th X Y
yX
IP F f y dy
Y




    
= −  = −        
 (14)
Using the results from (7) and (11), the IP can be rewritten by (15).
( )
( )
13 1 2 1 2
3 1
0
1/23 1 2 1 2
3 1
0
2( )
exp 2
( 1)!
2( )
exp 2
( 1)!
M
Mth th
M
Mth th
y
IP y y y K dy
M
y
y y K dy
M
      

 
      

 

 −

−
  
=   −    −   
  
=  −    −   


(15)
By letting t y= , (15) can be reformulated as;
( )2 23 1 2 1 2
3 1
0
4( )
exp 2
( 1)!
M
Mth th
IP t t K t dt
M
      

 


  
=  −    −   
 (16)
applying eq (6.631,3) of table of integral [21], finally the IP can be claimed by;
( ) ( )
1 2
3 1 2
1
,
32
exp
2
1
( 1)!
th
th
M
IP M M W
M
  
    
 

−
 
 
   =   +   
−  
(17)
4. NUMERICAL RESULTS AND DISCUSSION
In this section, we investigate the influence of the primary system parameters on the IP of the system
model [22-27]. As shown in Figure 3, the system IP increases with a rising of ψ from 0 to 25 dB. From
Figure 3, the system IP increases while ψ varies from 0 to 25 dB. Here we set system parameters as γth=0.5,
η=0.8, α=0.5, Ω=10 dB, and M = 1.3. Besides, the asymptotic curve is near the exact curve. The effect of Ω on
the system IP is drawn in Figure 4 with M = 2, η=0.8, α=0.5, Ω=10 dB, and ψ=5 dB. As shown in Figure 4,
the system IP has a huge decrease with the rising of Ω. In Figures 3 and 4, we can state that the simulation and
analytical values are the same to convince the analytical section.
Furthermore, the effect of α and M on the system IP are investigated in Figures 5 and 6. In Figure 5,
we set M = 2, γth=0.5, η=0.5, 0.8,ψ=Ω=5,10 dB and in Figure 6, we set γth=0.5, η=0.8, α=0.5, Ω=5,10 dB.
From these Figures, the system IP has a huge increase with the rising of α and has a huge decrease while M
TELKOMNIKA Telecommun Comput El Control 
Intercept probability analysis in DF time switching full-duplex relaying network… (Pham Minh Nam)
2339
varies from 1 to 10. These results show that the analytical curve is the same as the simulation curve to verify
the correctness of the analytical analysis.
Figure 3. IP versus ψ Figure 4. IP versus Ω
Figure 5. IP versus α Figure 6. IP versus M
5. CONCLUSION
In this research, we propose and investigate IP Analysis in DF time switching Relaying FD with
Impact of Co-channel Interference at the eavesdropper. In the beginning stage, we present the DF time
switching Relaying FD with the Impact of Co-channel Interference at the eavesdropper. Furthermore,
the closed-form expression of the IP is analyzed and derived in connection with the primary system parameters.
Finally, the Monte Carlo simulation is performed for verifying the correctness of the analytical section.
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Intercept probability analysis in DF time switching full-duplex relaying network with impact of Co-channel interference at the eavesdropper

  • 1. TELKOMNIKA Telecommunication, Computing, Electronics and Control Vol. 18, No. 5, October 2020, pp. 2335~2340 ISSN: 1693-6930, accredited First Grade by Kemenristekdikti, Decree No: 21/E/KPT/2018 DOI: 10.12928/TELKOMNIKA.v18i5.13861  2335 Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA Intercept probability analysis in DF time switching full-duplex relaying network with impact of Co-channel interference at the eavesdropper Pham Minh Nam1 , Phu Tran Tin2 , Minh Tran3 1 Faculty of Electronics Technology, Industrial University of Ho Chi Minh City, Vietnam 2 Wireless Communications Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Vietnam 3 Optoelectronics Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Vietnam Article Info ABSTRACT Article history: Received Aug 10, 2019 Revised Feb 25, 2020 Accepted Mar 18, 2020 In this research, we propose and investigate intercept probability analysis in DF time switching relaying full-duplex with impact of Co-channel interference at the eavesdropper. In the beginning stage, we present the DF time switching relaying full-duplex with the Impact of Co-channel interference at the eavesdropper. Furthermore, the closed-form expression of the intercept probability (IP) is analyzed and derived in connection with the primary system parameters. Finally, the Monte Carlo simulation is performed for verifying the correctness of the analytical section. From the research results, a novel solution and some recommendations can be proposed for the communication network in the near future. Keywords: Co-channel Energy harvesting Full-duplex Interference Outage probability This is an open access article under the CC BY-SA license. Corresponding Author: Phu Tran Tin, Wireless Communications Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam. Email: phutrantin@tdtu.edu.vn 1. INTRODUCTION Recently, wireless‐powered communication has gained considerable interest because of its capability to deal with the energy scarcity in energy‐constrained wireless networks. An attractive solution that overcomes the above limitation is to harvest energy from human-made radio frequency (RF) electromagnetic radiation (also known as wireless power transfer) [1-6]. Based on that fact, the WPCN and its efficiency are considered as the main research direction in the communication network. In [7], the authors investigated the fundamental tradeoff between the rate of transporting a commodity between one point and another. Furthermore, practical receiver designs for simultaneous wireless information and power transfer is detail studied in [8]. Moreover, the energy harvesting (EH) communication network with the partial network-level cooperation was proposed and investigated in [9]. Authors in [10] presented the cognitive relay networks with the EH and information transmission (IT) at the same time. Moreover, the TSP and PSP protocols in the EH communication network and the performance comparison between them are investigated in [11-15].
  • 2.  ISSN: 1693-6930 TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 5, October 2020: 2335 - 2340 2336 In this research, we propose and investigate Intercept Probability (IP) Analysis in DF time switching Relaying full-duplex with Impact of Co-channel Interference at the eavesdropper. The main contribution of this paper can be drawn as the follows; − The DF time switching Relaying full-duplex (FD) with the Impact of Co-channel Interference at the eavesdropper is proposed and investigated. − The exact and asymptotic analysis of the system IP is derived and investigated in connection with the primary system parameters. − The Monte Carlo simulation is conducted for verifying the correctness of the analytical analysis. In this paper, the system model of the communication network has considered in second section. The IP analysis is presented in the third section in detail. Numerical results and some conclusions is drawn in the fourth sections. In the final section, some conclusions are proposed. 2. SYSTEM MODEL In this section, Figure 1 proposed the DF time switching relaying full-duplex (FD) with the Impact of Co-channel interference at the eavesdropper. The energy harvesting (EH) and information transferring (IT) phases are drawn in Figure 2 [16-20]. IT PhaseEH Phase S E R 1... MI I Interference Links D Wiretap T EHat R T (1 )T− IT S R D⎯⎯→ ⎯⎯→ Figure 1. System model Figure 2. The EH and IT phases 2.1. Energy harvesting (EH) phase During the first phase, the received signal at the relay can be given by: r sr s ry h x n= + (1) The average transmitted power at the relay can be obtained as: 2 2 (1 ) (1 ) s srh r s sr TP hE P P h T T     = = = − − (2) 2.2. Information transmission (IT) phase In the second phase, the received signal at the relay can be given by r sr s rr r ry h x h x n= + + (3) where hrr is the loopback interference channel and  2 r rx P = . The received signal at the eavesdropper can be expressed as: 1 n n M E RE r I I E E n y h x x h n = = + + (4)
  • 3. TELKOMNIKA Telecommun Comput El Control  Intercept probability analysis in DF time switching full-duplex relaying network… (Pham Minh Nam) 2337 where REh is the relay to the eavesdropper channel gain, En is AWGN with variance N0 and nI Eh is the channel gain between nth interference source and eavesdropper. We assume that all the interferences source have the same transmit power IP , it mean that  2 0... nI I n M x P =  = From (4), the signal to noise ratio (SNR) at the eavesdropper can be given as; 2 2 0 1 n RE r E M I I E n h P P h N  = = + (5) Substituting (2) into (5), (5) can be rewritten as; 2 2 2 2 2 2 0 1 1 1 1n n s sr RE sr RE E M M I I E I E n n P h h h h X Y P h N h     = =   = = =  + +  +  (6) where 0 sP N  = , 0 IP N  = , 2 2 sr REX h h= and 2 1 n M I E n Y h = =  2.3. Remark 1 The probability density function (PDF) of random variable (RV) Z can be obtained as 13 3 ( ) ( ) exp( ) ( 1)! M M Yf t t t M  − = − − (7) where 3 is the mean of RV Y. 3. INTERCEPT PROBABILITY (IP) ANALYSIS 3.1. Exact analysis The IP can be defined by; ( )Pr E thIP  =  (8) substituting (6) into (8), the IP can be reformulated as (9). 0 Pr 1 Pr 1 1 ( 1) 1 ( ) th th th X Y X X IP Y Y y F f y dy             =  = −      +  +     +  = −     (9) Next, the cumulative distribution function (CDF) of X can be computed as (10). ( ) 2 2 2 2 2 2 2 0 2 1 1 0 ( ) Pr( ) Pr | ( ) 1 exp exp REsr X sr RE sr rd RE hh x F x h h x h h x F h a f a da a x a da a         =  =        = =       = − −  −      (10)
  • 4.  ISSN: 1693-6930 TELKOMNIKA Telecommun Comput El Control, Vol. 18, No. 5, October 2020: 2335 - 2340 2338 Here the (10) can be rewritten as the following; ( )1 2 1 1 2( ) 1 2 2XF x x K x   = −  (11) applying (7) and (11), (9) can be obtained by; 13 1 2 1 2 3 1 0 2( ) ( 1) exp( ) ( 1) 2 ( 1)! M Mth th y IP y y y K dy M            −   + =  −   +    −     (12) 3.2. Asymptotic analysis At the high SNR regime (  →  ), (6) can be calculated by (13). E X Y       (13) The IPcan be computed as (14). 0 1 Pr 1 ( )th th X Y yX IP F f y dy Y          = −  = −          (14) Using the results from (7) and (11), the IP can be rewritten by (15). ( ) ( ) 13 1 2 1 2 3 1 0 1/23 1 2 1 2 3 1 0 2( ) exp 2 ( 1)! 2( ) exp 2 ( 1)! M Mth th M Mth th y IP y y y K dy M y y y K dy M                       −  −    =   −    −       =  −    −      (15) By letting t y= , (15) can be reformulated as; ( )2 23 1 2 1 2 3 1 0 4( ) exp 2 ( 1)! M Mth th IP t t K t dt M                =  −    −     (16) applying eq (6.631,3) of table of integral [21], finally the IP can be claimed by; ( ) ( ) 1 2 3 1 2 1 , 32 exp 2 1 ( 1)! th th M IP M M W M            −        =   +    −   (17) 4. NUMERICAL RESULTS AND DISCUSSION In this section, we investigate the influence of the primary system parameters on the IP of the system model [22-27]. As shown in Figure 3, the system IP increases with a rising of ψ from 0 to 25 dB. From Figure 3, the system IP increases while ψ varies from 0 to 25 dB. Here we set system parameters as γth=0.5, η=0.8, α=0.5, Ω=10 dB, and M = 1.3. Besides, the asymptotic curve is near the exact curve. The effect of Ω on the system IP is drawn in Figure 4 with M = 2, η=0.8, α=0.5, Ω=10 dB, and ψ=5 dB. As shown in Figure 4, the system IP has a huge decrease with the rising of Ω. In Figures 3 and 4, we can state that the simulation and analytical values are the same to convince the analytical section. Furthermore, the effect of α and M on the system IP are investigated in Figures 5 and 6. In Figure 5, we set M = 2, γth=0.5, η=0.5, 0.8,ψ=Ω=5,10 dB and in Figure 6, we set γth=0.5, η=0.8, α=0.5, Ω=5,10 dB. From these Figures, the system IP has a huge increase with the rising of α and has a huge decrease while M
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