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Age of Information in an URLLC-enabled Decode-and-Forward Wireless
Communication System
Presentation · April 2021
CITATIONS
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Some of the authors of this publication are also working on these related projects:
Wireless Energy Transmission for Access Limited Underground Sensors View project
Dynamic Wireless Power Transfer System Using Coupled Magnetic Resonance View project
Chathuranga M. Wijerathna Basnayaka
Sri Lanka Technological Campus
15 PUBLICATIONS   15 CITATIONS   
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Age of Information in an URLLC-enabled
Decode-and-Forward Wireless Communication
System
Chathuranga M. Wijerathna Basnayaka †§, Dushantha Nalin K. Jayakody †§, Tharindu D.
Ponnimbaduge Perera † and Moises Vidal Ribeiro *
†National Research Tomsk Polytechnic University / §Center for Telecommunications
Research,SLTC,Sri Lanka/ * Federal University of Juiz de Fora Campus Universitario
The 2021 IEEE 93rd Vehicular Technology Conference: VTC2021-Spring,Helsinki,Finland
1 / 21
Outline
Outline
1 URLLC-enabled communication networks
2 Age of Information
3 System Model
4 Numerical Results
5 Conclusion
2 / 21
URLLC-enabled communication networks
URLLC-enabled communication networks
Ultra reliable low latency communications (URLLC)
So how do we optimally design URLLC systems ?
Morocho-Cayamcela, Manuel Eugenio, Haeyoung Lee, and Wansu Lim. ”Machine learning for 5G/B5G mobile and wireless
communications: Potential, limitations, and future directions.” IEEE Access 7 (2019)
3 / 21
URLLC-enabled communication networks
Fnite-blocklength information Theory
Large blocklengths mean large latency
Classic performance metric not suitable for the URLLC performances
Replace asymptotic information theory with nonasymptotic finite
blocklength ones!
The information theory community has developed many such
nonasymptotic results Ex : Polyanskiy Poor Verdú Converse Bound
4 / 21
Age of Information
Age of Information
Another approach to latency
Age of Information ( AoI ) measures the freshness of the received
data in mission critical applications.
Outdated information loses its value and can lead to system failures
and safety risks.
5 / 21
System Model
System Model
Figure: System model for URLLC-enabled relay system
6 / 21
System Model
System Model
The received signal at each node
Y1 =
p
PS HSRX1 + WSR (1)
Y2 =
p
PRHRDX2 + WRD (2)
PDF of the small scale channel gain (gij )
fgij (z) = e−z
(3)
Large scale channel gain αij
−10log(αij) = 20log(dij) + 20log

4πfc
C

(4)
7 / 21
System Model
System Model
Channel coefficient
Hij =
√
αij gij . (5)
Signal-to-Noise Ratio (SNR) γj at the receiving node j
γj =
αijgijPi
σ2
ij
(6)
8 / 21
System Model
Decoding Error Probability
The overall decoding error probability
ε = εR + εD(1 − εR) (7)
Following Polyanskiy’s results on short packet communication 1
εj = E

Q
nij C(γj ) − k
p
nij V (γj )
!#
(8)
1
Y. Polyanskiy, H. V. Poor, and S. Verdu, Channel coding rate in the Fnite blocklength regime,” IEEE Trans. Inf. Theory,
vol. 56, no. 5, pp. 230.
9 / 21
System Model
Decoding Error Probability
Under the Rayleigh fading channel conditions,
εj =
Z ∞
0
fγj (z)Q
nij C(γj ) − k
p
nj V (γj )
!
dz (9)
This can be approximated as
εj ≈
Z ∞
0
fγj (z)Θj(z) (10)
10 / 21
System Model
Θj (z) =



1, γj ≤ φj ,
1
2 − βj
√
nij (γj − ψj ), φj  γj  δj ,
0, γj ≥ δj ,
(11)
where βj = 1
2π
r
2
2k
nij −1
, ψj = 2
k
nij − 1, φj = ψj − 1
2βj
√
nij
and
δj = ψj + 1
2.βj
√
nij
.
The closed-form expression for the decoding error probability at the node
εij ≈ 1 −

βj
√
nij Pi αij
σ2

e
−
φi σ2
αij Pi − e
−
δj σ2
αij Pi
!
(12)
11 / 21
System Model
Decoding Error Probability
The closed-form expression for the overall error probability
ε ≈1 −
 
βRβD
√
nηSRηRD × ϕS ϕR(P)2αSRαRD
σ4


e
−
φR σ2
αSR ϕS P
− e
−
δR σ2
αSR ϕS P

e
−
φD σ2
αRD ϕR P
− e
−
δD σ2
αRD ϕR P
 (13)
12 / 21
System Model
Average Age of Information
∆(t) = t − g(t) (14)
Figure: Evolution of Age of Information (∆(t)) with the time
13 / 21
System Model
Average Age of Information
The time average age
∆Tn =
1
Tn
Z Tn
0
∆(t)d(t) =
Pn−1
i=0 Qi
Tn
(15)
where
Qi =
Z Di +Xi
Di
∆(t)d(t) = Yi Xi +
1
2
X2
i
the AAoI can be written as
AAoI = ∆a =
E[X2]
2 + E[XY ]
E[X]
(16)
14 / 21
System Model
Average Age of Information
∆a =
1
2E

X2

E [X]
+ E [s] +
E [wX]
E [X]
(17)
Using Pollaczek–Khinchine formula 2,
E[wX] =
E[X](E[X] − E[s])
E[e−λs]
+
E[s2]E[X]
2(E[X] − E[s])
−
E[X2]
2
(18)
2
R. Talak, S. Karaman, and E. Modiano, “Can determinacy minimize ageof information?” arXiv preprint arXiv:1810.04371,
2018
15 / 21
System Model
Average Age of Information
Total number of transmission R
PR(m) = (1 − ε)εm−1
; m = 1, 2.... (19)
The transmission delay for an update
s = (nT + υ)R (20)
The AAoI of the proposed system
∆a =
(nT + υ)
1 − ε
+
(nT+υ)2(1+ε)
(1−ε)2
2(1
λ − (nT+υ)
1−ε )
+
(1
λ − (nT+υ)
1−ε )
(1−ε)e−(nT+υ)λ
1−εe−(nT+υ)λ
(21)
16 / 21
Numerical Results
Numerical Results
AAoI as a function of update generate
18 / 21
Numerical Results
AAoI as a function block length allocation factor
0.2 0.3 0.4 0.5 0.6 0.7 0.8
10-2
100
102
104
106
Power allocation factor - 0.5
Power allocation factor - 0.3
Power allocation factor- 0.7
19 / 21
Conclusion
Conclusion
Maintaining a small update size (short packet communication)
minimizes the AAoI in wireless relay networks
High packet generation rate may overload the network and lead to a
high average AoI
Low packet generation rate may result in infrequent information
updates at the destination, which may also lead to a high average AoI
20 / 21
Thank you
Contact:
• Email: chathurangab@sltc.ac.lk
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Age of Information in an URLLC-enabled Decode-and-Forward Wireless Communication System

  • 1. See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/350808756 Age of Information in an URLLC-enabled Decode-and-Forward Wireless Communication System Presentation · April 2021 CITATIONS 0 READS 3 1 author: Some of the authors of this publication are also working on these related projects: Wireless Energy Transmission for Access Limited Underground Sensors View project Dynamic Wireless Power Transfer System Using Coupled Magnetic Resonance View project Chathuranga M. Wijerathna Basnayaka Sri Lanka Technological Campus 15 PUBLICATIONS   15 CITATIONS    SEE PROFILE All content following this page was uploaded by Chathuranga M. Wijerathna Basnayaka on 12 April 2021. The user has requested enhancement of the downloaded file.
  • 2. Age of Information in an URLLC-enabled Decode-and-Forward Wireless Communication System Chathuranga M. Wijerathna Basnayaka †§, Dushantha Nalin K. Jayakody †§, Tharindu D. Ponnimbaduge Perera † and Moises Vidal Ribeiro * †National Research Tomsk Polytechnic University / §Center for Telecommunications Research,SLTC,Sri Lanka/ * Federal University of Juiz de Fora Campus Universitario The 2021 IEEE 93rd Vehicular Technology Conference: VTC2021-Spring,Helsinki,Finland 1 / 21
  • 3. Outline Outline 1 URLLC-enabled communication networks 2 Age of Information 3 System Model 4 Numerical Results 5 Conclusion 2 / 21
  • 4. URLLC-enabled communication networks URLLC-enabled communication networks Ultra reliable low latency communications (URLLC) So how do we optimally design URLLC systems ? Morocho-Cayamcela, Manuel Eugenio, Haeyoung Lee, and Wansu Lim. ”Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions.” IEEE Access 7 (2019) 3 / 21
  • 5. URLLC-enabled communication networks Fnite-blocklength information Theory Large blocklengths mean large latency Classic performance metric not suitable for the URLLC performances Replace asymptotic information theory with nonasymptotic finite blocklength ones! The information theory community has developed many such nonasymptotic results Ex : Polyanskiy Poor Verdú Converse Bound 4 / 21
  • 6. Age of Information Age of Information Another approach to latency Age of Information ( AoI ) measures the freshness of the received data in mission critical applications. Outdated information loses its value and can lead to system failures and safety risks. 5 / 21
  • 7. System Model System Model Figure: System model for URLLC-enabled relay system 6 / 21
  • 8. System Model System Model The received signal at each node Y1 = p PS HSRX1 + WSR (1) Y2 = p PRHRDX2 + WRD (2) PDF of the small scale channel gain (gij ) fgij (z) = e−z (3) Large scale channel gain αij −10log(αij) = 20log(dij) + 20log 4πfc C (4) 7 / 21
  • 9. System Model System Model Channel coefficient Hij = √ αij gij . (5) Signal-to-Noise Ratio (SNR) γj at the receiving node j γj = αijgijPi σ2 ij (6) 8 / 21
  • 10. System Model Decoding Error Probability The overall decoding error probability ε = εR + εD(1 − εR) (7) Following Polyanskiy’s results on short packet communication 1 εj = E Q nij C(γj ) − k p nij V (γj ) !# (8) 1 Y. Polyanskiy, H. V. Poor, and S. Verdu, Channel coding rate in the Fnite blocklength regime,” IEEE Trans. Inf. Theory, vol. 56, no. 5, pp. 230. 9 / 21
  • 11. System Model Decoding Error Probability Under the Rayleigh fading channel conditions, εj = Z ∞ 0 fγj (z)Q nij C(γj ) − k p nj V (γj ) ! dz (9) This can be approximated as εj ≈ Z ∞ 0 fγj (z)Θj(z) (10) 10 / 21
  • 12. System Model Θj (z) =    1, γj ≤ φj , 1 2 − βj √ nij (γj − ψj ), φj γj δj , 0, γj ≥ δj , (11) where βj = 1 2π r 2 2k nij −1 , ψj = 2 k nij − 1, φj = ψj − 1 2βj √ nij and δj = ψj + 1 2.βj √ nij . The closed-form expression for the decoding error probability at the node εij ≈ 1 − βj √ nij Pi αij σ2 e − φi σ2 αij Pi − e − δj σ2 αij Pi ! (12) 11 / 21
  • 13. System Model Decoding Error Probability The closed-form expression for the overall error probability ε ≈1 − βRβD √ nηSRηRD × ϕS ϕR(P)2αSRαRD σ4 e − φR σ2 αSR ϕS P − e − δR σ2 αSR ϕS P e − φD σ2 αRD ϕR P − e − δD σ2 αRD ϕR P (13) 12 / 21
  • 14. System Model Average Age of Information ∆(t) = t − g(t) (14) Figure: Evolution of Age of Information (∆(t)) with the time 13 / 21
  • 15. System Model Average Age of Information The time average age ∆Tn = 1 Tn Z Tn 0 ∆(t)d(t) = Pn−1 i=0 Qi Tn (15) where Qi = Z Di +Xi Di ∆(t)d(t) = Yi Xi + 1 2 X2 i the AAoI can be written as AAoI = ∆a = E[X2] 2 + E[XY ] E[X] (16) 14 / 21
  • 16. System Model Average Age of Information ∆a = 1 2E X2 E [X] + E [s] + E [wX] E [X] (17) Using Pollaczek–Khinchine formula 2, E[wX] = E[X](E[X] − E[s]) E[e−λs] + E[s2]E[X] 2(E[X] − E[s]) − E[X2] 2 (18) 2 R. Talak, S. Karaman, and E. Modiano, “Can determinacy minimize ageof information?” arXiv preprint arXiv:1810.04371, 2018 15 / 21
  • 17. System Model Average Age of Information Total number of transmission R PR(m) = (1 − ε)εm−1 ; m = 1, 2.... (19) The transmission delay for an update s = (nT + υ)R (20) The AAoI of the proposed system ∆a = (nT + υ) 1 − ε + (nT+υ)2(1+ε) (1−ε)2 2(1 λ − (nT+υ) 1−ε ) + (1 λ − (nT+υ) 1−ε ) (1−ε)e−(nT+υ)λ 1−εe−(nT+υ)λ (21) 16 / 21
  • 19. Numerical Results AAoI as a function of update generate 18 / 21
  • 20. Numerical Results AAoI as a function block length allocation factor 0.2 0.3 0.4 0.5 0.6 0.7 0.8 10-2 100 102 104 106 Power allocation factor - 0.5 Power allocation factor - 0.3 Power allocation factor- 0.7 19 / 21
  • 21. Conclusion Conclusion Maintaining a small update size (short packet communication) minimizes the AAoI in wireless relay networks High packet generation rate may overload the network and lead to a high average AoI Low packet generation rate may result in infrequent information updates at the destination, which may also lead to a high average AoI 20 / 21
  • 22. Thank you Contact: • Email: chathurangab@sltc.ac.lk View publication stats View publication stats