Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
Performance Analysis for LoS and NLoS
for a Multiple-Relay Buffer-Aided NOMA Network
A. Ramı́rez1
G. Corral Briones2
H. Mendoza3
1−2
Institute for Advanced Studies
in Engineering and Technology,
IDIT UNC-CONICET
Córdoba, Argentina
3 Digital Communication Lab
National University of Córdoba (UNC)
Córdoba, Argentina
1 adrian.ramirez@conicet.gov.ar, 2 graciela.corral@unc.edu.ar,
3 horacio.mendoza@unc.edu.ar
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
Contents
1
Introduction
2
System Model and Preliminaries
System model
Transmission in the Source-Relay link
Transmission in the Relay-Destination link
3
Choosing α for NOMA
4
The proposed algorithm
5
Simulation Results
6
Conclusions
2 / 16
Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
Introduction
Paper contributions
—Analysis of outage probability,
sum-rate capacity and buffer
states distribution over an A2G
cooperative network.
—Configurations considering
either Line-of-Sight and
Non-Line-of-Sight components.
—Comparison of results with
different orders of spatial
diversity and stochastic channel
models.
—A proposed algorithm for
evaluation of the system
performance.
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
System model
Transmission in the Source-Relay link
Transmission in the Relay-Destination link
System model
Relay-assisted network
—One source S, two destinations D1 and D2 and a Cluster C of K
Half Duplex Decode and Forward relays Rk .
—Comm only by relays.
—Rk equipped with buffer of size L (maximum number elements).
—Buffers store Qk number of packets.
—Same amount of elements for D1 and D2 at the relays.
—Time divided into slots of one packet duration.
—Degradation by AWGN and Rayleigh/Rician block fading.
—Complex channel coefficient hij and channel gain gij = |hij |2 .
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
System model
Transmission in the Source-Relay link
Transmission in the Relay-Destination link
System model
—Source node assumed saturated and information rate ri at Di is
fixed and may differ.
—Succesful comm if the receiver SNR Γij is greater/equal than
threshold γj (or capture ratio).
—Relays with AWGN thermal noise variance σk2 .
—Packet sent at each time slot from S or Rk with fixed power Pi .
—Retransmission bassed on ACK/NACK.
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
System model
Transmission in the Source-Relay link
Transmission in the Relay-Destination link
System model
Figure 1: System model for the two-hop buffer-aided network.
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
System model
Transmission in the Source-Relay link
Transmission in the Relay-Destination link
System model
Figure 2: Scenario with only NLoS
components.
Figure 3: Scenario with LoS and
NLoS components.
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
System model
Transmission in the Source-Relay link
Transmission in the Relay-Destination link
Transmission in the S-R link
—Source transmits with rate r1 + r2 .
Source-Relay Transmission SNR:
ΓSRk (PS ) =
gSRk PS
≥ 2r1 +r2 − 1 > γRk
σk2
Probability of transmission outage:
"
#
(2 r1 +r2 − 1 )σk2
pout = P gSRk <
PS
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
System model
Transmission in the Source-Relay link
Transmission in the Relay-Destination link
Transmission in the R-D link
—NOMA information symbols x1 and x2 superimposed.
Information symbol x:
x=
√
α x1 +
√
1 − α x2
Information symbol y1 received at D1 :
q
p
y1 = hrk D1 αPRk x1 + hrk D1 (1 − α)PRk x2 + η1
Information symbol y2 received at D2 :
q
p
y2 = hrk D2 αPRk x1 + hrk D2 (1 − α)PRk x2 + η2
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
Choosing α for NOMA
To ensure succesive interference cancellation (SIC):
—Each relay (with full CSIT) chooses α in each time slot.
—The SINR for at least one of the symbols is greater/equal to a
threshold γj at both D1 and D2 .
Considering x2 decoded at both D1 and D2 , and after x1 decoded
interference-free just at D1 :
ΓRk Dj (PRk ) =
(1 − α)PRk gRk Dj
≥ γj
2
αPRk gRk Dj + σD
j
ΓRk D1 (PRk ) =
j ∈ {1, 2}
αPRk gRk D1
≥ γ1
2
σD
1
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
Choosing α for NOMA
α can take values on the range:
αmin ≤ α ≤ max{0, min{1, αmax }}
The reception outage probability is:
pout = P[αmin > min{1, αmax }]
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
Scenario Performance Analysis.
1: for n = 1 → N do
. N samples loop
2:
for k = 1 → K do
. K relays loop
3:
Setting of αmin ;
4:
Setting of αmax ;
5:
Ct(S,Rk∗ ) = gS,Rk∗ < γS,Rk∗ σR2 ∗ /PRk∗ ;
k
6:
Ct(Rk∗ ,D) = αmin > min{1, αmax };
7:
Ln(S,R) = (q(Rk ) < L) ∧ (¬ CtS,R (Rk ) > γS,R );
8:
Ln(R,D) = (q(Rk ) > 0) ∧ (¬ CtR,D (Rk ) > γR,D );
9:
end for
10:
Relay’s buffers actualization;
11:
Cm = (Ln(S,R) > 0) ∨ (Ln(R,D) > 0);
12: end for
13: Pout = ¬ E{Cm};
14: Psumrate = (rS,R ∗ /2) E{Cm};
k
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
System model
10 0
3
2.5
Sum-rate capacity
Outage probability
10 -1
10 -2
10 -3
10 -4
K = 4. SR Rayleigh link
K = 4. SR Rician link
K = 2. SR Rician link
K = 2. SR Rayleigh link
0
5
10
2
1.5
1
k = 4. SR Rayleigh link
k = 4. SR Rician link
k = 2. SR Rician link
k = 2. SR Rayleigh link
0.5
15
20
25
Transmission SNR
Figure 4: Outage probability for
rates rRk∗ ,D1 = 3 and rRk∗ ,D2 = 3.
30
0
0
5
10
15
20
25
30
Transmission SNR
Figure 5: Outage probability for
rates rRk∗ ,D1 = 4 and rRk∗ ,D2 = 1.
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
System model
10 0
2.5
2
Sum-rate capacity
Outage probability
10 -1
10 -2
K = 4. SR Rayleigh link
K = 4. SR Rician link
K = 2. SR Rayleigh link
K = 2. SR Rician link
10 -3
10 -4
1.5
1
K = 4. SR Rayleigh link
K = 4. SR Rician link
K = 2. SR Rayleigh link
K = 2. SR Rician link
0.5
0
0
5
10
15
20
25
30
Transmission SNR
Figure 6: Sum-rate capacity for rates
rRk∗ ,D1 = 3 and rRk∗ ,D2 = 3.
0
5
10
15
20
25
30
Transmission SNR
Figure 7: Sum-rate capacity for rates
rRk∗ ,D1 = 4 and rRk∗ ,D2 = 1.
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
System model
Buffer states by relay
Buffer states by relay
60 %
Scenario 1
Scenario 1
60 %
40 %
20 %
40 %
20 %
0%
0%
0
1
2
3
4
0
1
2
0
1
2
60 %
Scenario 2
Scenario 2
60 %
40 %
20 %
40 %
20 %
0%
0%
0
1
2
3
4
Figure 8: Buffer states for L = 4
Figure 9: Buffer states for L = 2
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Introduction
System Model and Preliminaries
Choosing α for NOMA
The proposed algorithm
Simulation Results
Conclusions
Questions?
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