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Efficient RRH Activation Management for 5G V2X

Authors :
Ke, Jing-Wen
Hwang, Ren-Hung
Wang, Chih-Yu
Kuo, Jian-Jhih
Chen, Wei-Yu
Source :
IEEE Transactions on Mobile Computing; February 2024, Vol. 23 Issue: 2 p1215-1229, 15p
Publication Year :
2024

Abstract

Vehicle-to-everything (V2X) communication is one of the key technologies of 5G New Radio to support emerging applications such as autonomous driving. Due to the high density of vehicles, Remote Radio Heads (RRHs) will be deployed as Road Side Units to support V2X. Nevertheless, activation of all RRHs during low-traffic off-peak hours may cause energy wasting. The proper activation of RRH and association between vehicles and RRHs while maintaining the required service quality are the keys to reducing energy consumption. In this work, we first formulate the problem as an Integer Linear Programming optimization problem and prove that the problem is NP-hard. Then, we propose two novel algorithms, referred to as “Least Delete (LD)” and ”Largest-First Rounding with Capacity Constraints (LFRCC).” The simulation results show that the proposed algorithms can achieve significantly better performance compared with existing solutions and are competitive with the optimal solution. Specifically, the LD and LFRCC algorithms can reduce the number of activated RRHs by 86<inline-formula><tex-math notation="LaTeX">$\%$</tex-math><alternatives><mml:math><mml:mo>%</mml:mo></mml:math><inline-graphic xlink:href="hwang-ieq1-3232547.gif"/></alternatives></inline-formula> and 89<inline-formula><tex-math notation="LaTeX">$\%$</tex-math><alternatives><mml:math><mml:mo>%</mml:mo></mml:math><inline-graphic xlink:href="hwang-ieq2-3232547.gif"/></alternatives></inline-formula> in low-density scenarios. In high-density scenarios, the LD algorithm can reduce the number of activated RRHs by 90<inline-formula><tex-math notation="LaTeX">$\%$</tex-math><alternatives><mml:math><mml:mo>%</mml:mo></mml:math><inline-graphic xlink:href="hwang-ieq3-3232547.gif"/></alternatives></inline-formula>. In addition, the solution of LFRCC is larger than that of the optimal solution within 7<inline-formula><tex-math notation="LaTeX">$\%$</tex-math><alternatives><mml:math><mml:mo>%</mml:mo></mml:math><inline-graphic xlink:href="hwang-ieq4-3232547.gif"/></alternatives></inline-formula> on average.

Details

Language :
English
ISSN :
15361233
Volume :
23
Issue :
2
Database :
Supplemental Index
Journal :
IEEE Transactions on Mobile Computing
Publication Type :
Periodical
Accession number :
ejs65157379
Full Text :
https://doi.org/10.1109/TMC.2022.3232547