Page 56 - ITU Journal Future and evolving technologies Volume 3 (2022), Issue 2 – Towards vehicular networks in the 6G era

ITU Journal on Future and Evolving Technologies, Volume 3 (2022), Issue 2

Fig. 9 and Fig. 10 show the converged PRR and 7. CONCLUSION
utility gain obtained by UE0 for 144 realizations, i.e.,
144 initial deployment of UEs in the network. For all In this paper, we obtained a two-distance link
realizations, we use step size = 1 and 10,000 reception rate model for C-V2X based linear
iterations. After executing our algorithm, the regression with results from C-V2X network-level
average PRR increases over all realizations is 5%. It simulation and formulate an optimization problem
could be seen from Fig. 9 that for 134 cases, our for per-node PRR maximization with fairness for
GBMU algorithm enhances UE0’s utility and only in the broadcasting scenarios. An updating algorithm
10 realizations, the GBMU algorithm leads the UE0 (GBMU) was devised to solve the optimization
to a worse position. The effectiveness rate of our problem iteratively, by controlling the mobility of
algorithm is 93% in terms of utility improvement. the transmitter. Simulation results show that our
The overall utility enhancement, averaged across all two-distance model has high accuracy in scenarios
realizations, is by 15%. where the C-V2X network has high vehicle density
and more concurrent transmissions using the same
In terms of the PRR of UE0 before and after the resource. The proposed GBMU is demonstrated to
position updates provided by GBMU, the average converge and provide an improvement in per-node
gain across all realizations is 5%. There are 40 utility by 45%.
realizations where the updated UE0’s position
causes a PRR drop compared to that obtained from ACKNOWLEDGEMENT
UE0’s original place. It is because we use the
fairness-oriented utility to drive the node moving This work was supported in part by Research
direction and amplitude, that the PRR will be Grants Council (RGC) Faculty Development Scheme
sacrificed in some cases, but the obtained utility project (Ref. No.: UGC/FDS25/E04/20) established
gain increases indeed. under the University Grant Committee (UGC) of the
Hong Kong Special Administrative Region (HKSAR),
2 China, and partially sponsored by the Policy
Research Institute of Global Supply Chain (PRISC) of
1.5
The Hang Seng University of Hong Kong (HSUHK).
Normalized gain in Utility 0.5 REFERENCES
1

Kurugollu, F.; Ahmed, S.H.; Hussain, R.;
[1]
0
Ahmad, F.; Kerrache, C.A. Vehicular Sensor
-0.5
Networks: Applications, Advances and
Challenges. Sensors 2020, 20, 3686.
-1
0 50 100 150
https://doi.org/10.3390/s20133686.
Realization index
Fig. 9 – Normalized gain in utility at convergence across [2] K. A. Hafeez, L. Zhao, B. Ma and J. W. Mark,
144 realizations "Performance Analysis and Enhancement of
the DSRC for VANET's Safety Applications," in
0.5
IEEE Transactions on Vehicular Technology,
vol. 62, no. 7, pp. 3069-3083, Sept. 2013, doi:
0.4
10.1109/TVT.2013.2251374.
0.3
Normalized Gain in PRR 0.1 0 [3] A. Rayamajhi, A. Yoseph, A. Balse, Z. Huang, E.
0.2
M. Leslie and V. Fessmann, "Preliminary
Performance Baseline Testing for Dedicated
Short-Range Communication (DSRC) and
-0.1
Cellular Vehicle-to-Everything (C-V2X),"
-0.2
2020 IEEE 92nd Vehicular Technology
-0.3
Conference (VTC2020-Fall), 2020, pp. 1-5, doi:
-0.4
0 50 100 150
Realization index 10.1109/VTC2020-Fall49728.2020.9348708.
Fig. 10 – Normalized gain in PRR at convergence across
144 realizations

44 © International Telecommunication Union, 2022