Age of Information (AoI) measures the freshness of data in mission critical Internet-of-Things (IoT) applications i.e., industrial internet, intelligent transportation systems etc. In this paper, a new system model is proposed to estimate the average AoI (AAoI) in an ultra-reliable low latency communication (URLLC) enabled wireless communication system with decode-and-forward relay scheme over the quasi-static Rayleigh block fading channels. Short packet communication scheme is used to meet both reliability and latency requirements of the proposed wireless network. By resorting finite block length information theory, queuing theory and stochastic processes, a closed-form expression for AAoI is obtained. Finally, the impact of the system parameters, such as update generation rate, block length and block length allocation factor on the AAoI are investigated. All results are validated by the numerical results. Index Terms-Age-of-Information, finite block length regime, latency, reliability, ultra-reliable low latency communications (URLLC) and 5GB.

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Physical Layer Redesign for Unmanned Aerial Vehicle (UAV) Communication
in 5G
Presentation · March 2021
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Chathuranga M. Wijerathna Basnayaka
Sri Lanka Technological Campus
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2. Physical Layer Redesign for Unmanned Aerial
Vehicle (UAV) Communication in 5G
Chathuranga Madhushan Basnayaka
Supervisors: (Prof.) Dushantha Nalin Kumara and (Dr.) Udesh Oruthota
National Research Tomsk Polytechnic University / Center for
Telecommunications Research,SLTC,Sri Lanka
March 10, 2021

3. Outline 2
Latency in UAV Communication Networks
Age of Information
Age of Information in an URLLC-enabled Decode-and-Forward
Wireless Communication System
Numerical Simulation Results

4. Latency in UAV communication networks 3
I 5G will be key enabler of future UAV communication
system
I Ultra reliable low latency communications (URLLC)
concerns the transmission of data at a very small error
probability without violating a given latency constraint
I So how do we optimally design URLLCs? This is a tricky
question, even if we just limited to the physical layer.
I The physical layer design of current systems relies largely
on guidelines provided by information theory analyses. For
example, the well known formula for the capacity of the
AWGN channel
C = W log
1 +
P
N0W
(1)

5. Fnite-blocklength information Theory 4
I But to approach capacity, we need to use codes with large
blocklength ; large blocklengths often mean large latency.
I So we cannot use classic performance metric such as
ergodic capacity or outage capacity to benchmark the
performance of URLLC.
I So what can we do instead? We must replace asymptotic
information theory results with nonasymptotic finite
blocklength ones!
I Over the last 10 years, the information theory community
has developed many such nonasymptotic results Ex :
Polyanskiy Poor Verdú Converse Bound for Finite Block
Length; new theoretical tools

6. Age of Information 5
I Another approach to latency
I Age of Information ( AoI ) measures the freshness of the
received data in mission critical applications Ex:
autonomous vehicles , smart factories, smart homes,
immersive gaming, command and control etc.
I Command and control systems exchange mission critical
information in order to maintain situational awareness
I In such applications, it is essential to keep the information
fresh as outdated information loses its value and can lead
to system failures and safety risks.
I The concept of Age of Information ( AoI ) was introduced
in to quantify the freshness of the knowledge we have
about the status of a remote system.

7. Age of Information in an URLLC-enabled
Decode-and-Forward Wireless Communication
System

8. System Model 7
I A new system model is proposed to estimate the average
AoI AAoI ) in an Relay communication system
Figure: System model for URLLC-enabled relay system

9. System Model 8
The received signal at each communication node
Y1 =
p
PSHSRX1 + WSR, (2)
Y2 =
p
PRHRDX2 + WRD, (3)
The probability density function (PDF) of the small scale
channel gain (gij)
fgij (z) = e−z
(4)
The large scale channel gain αij
−10log(αij) = 20log(dij) + 20log
4πfc
C
(5)

10. System Model 9
channel coefficient between the communication nodes
Hij =
√
αijgij. (6)
The normalized received signal-to-noise ratio (SNR) γj at the
receiving node j
γj =
αijgijPi
σ2
ij
. (7)

11. Block Error Probability 10
Considering DF relay protocol, the overall decoding error
probability
ε = εR + εD(1 − εR) (8)
The expectation of the block error probability
Following Polyanskiy’s results on short packet communication [1]
εj = E
Q
nijC(γj) − k
p
nijV (γj)
!#
(9)
V (γj) (the channel dispersion) = log2
2
e
2
(1 − 1
(1+γj )2 ),
C(γj)(capacity of a complex AWGN channel) = log2(1 + γj) , number of
bits per block k

12. Block Error Probability 11
Under the Rayleigh fading channel conditions, εj can be
formulated as
εj =
Z ∞
0
fγj (z)Q
nijC(γj) − k
p
njV (γj)
!
dz, (10)
Using the approximation technique given in [2] and [3], (10) can
be approximated as
εj ≈
Z ∞
0
fγj (z)Θj(z), (11)
where Θj(z) denotes the linear approximation of Q
nij .C(γj )−k
√
nij .V (γj )

13. Θj(z) =



1, γj ≤ φj,
1
2 − βj
√
nij(γj − ψj), φj γj δj,
0, γj ≥ δj,
(12)
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
.
Using (11) and (12), a closed-form expression for the block error
probability can be derived as
εij ≈ 1 −
βj
√
nijPiαij
σ2
e
−
φiσ2
αijPi − e
−
δjσ2
αijPi
!
. (13)

14. Block Error Probability 13
Finally, substituting (13) in (8), a closed-form expression for
the overall error probability can be obtained as
ε ≈1 −
βRβD
√
nηSRηRD × ϕSϕR(P)2αSRαRD
σ4
e
−
φRσ2
αSRϕSP
− e
−
δRσ2
αSRϕSP
e
−
φDσ2
αRDϕRP
− e
−
δDσ2
αRDϕRP
.
(14)

15. Average Age of Information 14
If the generation time of the freshest update received at time
stamp t is g(t), then AoI can be defined as a random process as
∆(t) = t − g(t). (15)
Figure: Evolution of Age of Information (∆(t)) with the time

16. Average Age of Information 15
Time average AoI can be computed using the area under ∆(t)
(sequence of trapezoids Qi ) . The time average age
∆Tn =
1
Tn
Z Tn
0
∆(t)d(t) =
Pn−1
i=0 Qi
Tn
, (16)
where
Qi =
Z Di+Xi
Di
∆(t)d(t) = YiXi +
1
2
X2
i .
the AAoI can be written as
AAoI = ∆a =
E[X2]
2 + E[XY ]
E[X]
. (17)
In (17), E[XY ] is difficult to estimate without proper approximation.

17. Average Age of Information 16
The system delay (Y ) can be calculated as a summation of the
service time (s) and waiting time (w) of the queue,
∆a =
1
2E
X2
E [X]
+ E [s] +
E [wX]
E [X]
. (18)
Pollaczek–Khinchine [4] formula is used to further simplify (18).
The correlation term E[wX] can be evaluated as
E[wX] =
E[X](E[X] − E[s])
E[e−λs]
+
E[s2]E[X]
2(E[X] − E[s])
−
E[X2]
2
,
(19)

18. Average Age of Information 17
Total number of transmission R needed for the reliable
transmission of an update is geometrically distributed with
transmission error rate and its probability mass function
PR(m) = (1 − ε)εm−1
; m = 1, 2.... (20)
The service time for an update, which is transmitted using one
transmission block is given by
s = (nT + υ)R, (21)
Finally, the AAoI of the proposed system can be derived as
∆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
. (22)

19. Numerical Simulation Results

20. AAoI as a function of update generate 19
10
0
10
1
10
-1
10
0
10
1 Simulated
Theoretical
Number of updates generated per second
I High packet generation rate may overload the network and lead to a
high average AoI
I Low packet generation rate may result in infrequent information
updates at the destination, which may also lead to a high average AoI

21. AAoI as a function block length allocation factor 20
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
I Maintaining a small update size (short packet communication)
minimize the AAoI in the relay network.

22. Publications 21
I Basnayaka C. M. W. ,Perera, T.D.P., Jayakody, D.N.K.,
2021 May .Age of Information in an URLLC-enabled
Decode-and-Forward Wireless communication. IEEE 93rd
Vehicular Technology Conference (VTC-Spring), IEEE.
[Accepted]
I A. Sharma, P. Vanjan, N. Paliwal, C. M. W. Basnayaka,
D. N. K.Jayakody, H.C.Wang and
P.Muthuchidambaranathan “Communication and
Networking Technologies for UAVs: A Survey ” Journal of
Network and Computer Applications (Accepted)
I C. M. W. Basnayaka, K.O. Lakamal and D. N. K.Jayakody,
2019. “The Era of the 5G Drone is Ahead, Are We
Ready?” Vidurava, 36(4), pp.19-21.

23. Work Plan for Next 6 Months 22
I Extend the aforementioned system model for a UAV
communication network.
I Simultaneous Wireless Information and Power Transfer
(SWIPT) and WPT assisted technologies for the UAV
communication system.
I Compare approximated numerical result with the practical
simulated model that uses the polar code as an error
correction code.

24. References 23
Y. Polyanskiy, H. V. Poor, and S. Verdu, “Channel coding
rate in the finite blocklength regime,” IEEE Trans. Inf.
Theory, vol. 56, no. 5, pp. 2307–2359, 2010.
B. Makki, T. Svensson, and M. Zorzi, “Finite block-length
analysis of the incremental redundancy harq,” IEEE Wirel.
Commun. Le., vol. 3, no. 5, pp. 529–532, 2014.
Y. Gu, H. Chen, Y. Li, and B. Vucetic, “Ultra-reliable
short-packet communications: Half-duplex or full-duplex
relaying?” IEEE Wirel. Commun., vol. 7, no. 3, pp.
348–351, 2017.
R. Talak, S. Karaman, and E. Modiano, “Can determinacy
minimize age of information?” arXiv preprint
arXiv:1810.04371, 2018.

25. Questions?
Thank you
Contact:
• Email: chathurangab@sltc.ac.lk
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