TY - GEN
T1 - Resource Allocation Based on Three-Sided Matching Theory in Cognitive Vehicular Networks
AU - Wen, Shuhui
AU - Liang, Wei
AU - Cui, Jingjing
AU - Wang, Dawei
AU - Li, Lixin
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In this paper, we investigate the resource allocation and vehicle to everything (V2X) offloading in the cognitive vehicular networks. The cognitive radio (CR), mobile edge computing (MEC), and non-orthogonal multiple access (NOMA) schemes are applied aim to solve the combinational problem of resource allocation and V2X offloading. The problem for jointly optimizing power and time allocation in the MEC based CR (CR-MEC) networks is conceived. We decompose the joint optimization problem into two subproblems, which are power allocation and time allocation problems. In order to solve this joint optimization problem, an advanced comprehensive resource allocation (ACRA) algorithm based on three-sided matching theory is employed. More specifically, the proposed algorithm is to realize the most reasonable matching among primary users (PUs), cognitive users (CUs) as well as a cognitive base station (BS), and put forward a V2X offloading strategy, by appropriately allocating power and time aim to minimize the system energy consumption. The simulation results show that, our proposed algorithm converges to stable. Furthermore, the proposed NOMA based CR-MEC networks can achieve lower energy consumption compared to the orthogonal multiple access (OMA) based CR-MEC networks.
AB - In this paper, we investigate the resource allocation and vehicle to everything (V2X) offloading in the cognitive vehicular networks. The cognitive radio (CR), mobile edge computing (MEC), and non-orthogonal multiple access (NOMA) schemes are applied aim to solve the combinational problem of resource allocation and V2X offloading. The problem for jointly optimizing power and time allocation in the MEC based CR (CR-MEC) networks is conceived. We decompose the joint optimization problem into two subproblems, which are power allocation and time allocation problems. In order to solve this joint optimization problem, an advanced comprehensive resource allocation (ACRA) algorithm based on three-sided matching theory is employed. More specifically, the proposed algorithm is to realize the most reasonable matching among primary users (PUs), cognitive users (CUs) as well as a cognitive base station (BS), and put forward a V2X offloading strategy, by appropriately allocating power and time aim to minimize the system energy consumption. The simulation results show that, our proposed algorithm converges to stable. Furthermore, the proposed NOMA based CR-MEC networks can achieve lower energy consumption compared to the orthogonal multiple access (OMA) based CR-MEC networks.
KW - cognitive radio
KW - mobile edge computing
KW - non-orthogonal multiple access
KW - vehicle to everything
KW - vehicular network
UR - http://www.scopus.com/inward/record.url?scp=85122994721&partnerID=8YFLogxK
U2 - 10.1109/VTC2021-Fall52928.2021.9625230
DO - 10.1109/VTC2021-Fall52928.2021.9625230
M3 - 会议稿件
AN - SCOPUS:85122994721
T3 - IEEE Vehicular Technology Conference
BT - 2021 IEEE 94th Vehicular Technology Conference, VTC 2021-Fall - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 94th IEEE Vehicular Technology Conference, VTC 2021-Fall
Y2 - 27 September 2021 through 30 September 2021
ER -
