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Sparse Code Multiple Access Assisted Resource Allocation for 5G V2X Communications

delete2022-10-01
delete9
PRE
AI
Z
Zhenjiang Shi
刘佳佳 cover
刘佳佳 (Jiajia Liu) *
DOI:10.1109/TCOMM.2022.3197605delete
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Abstract

Abstract

En 中文
In 5G vehicle-to-everything (V2X) systems, the scarcity of spectrum resources and the inefficiency of resource allocation make vehicle-to-vehicle (V2V) communications that require stringent latency and high reliability still a challenge. Existing relevant literatures either focus on vehicle-to-infrastructure (V2I) communications, or consider scenarios where the vehicle roles (transmitter or receiver) are fixed in V2V communications, or study the resource allocation within a single cell. What's more, considering the high-speed movement of vehicles across the coverage regions of multiple cells, the above resource allocation problem becomes even more challenging. Toward this end, we consider in this paper a multi-cell 5G V2X system where V2V links and V2I links coexist and the vehicle roles are not fixed, and propose a sparse code multiple access-based centralized resource allocation scheme, so as to address the above challenges. In view of the fact that our formulated maximizing packet reception ratio problem is a combinatorial optimization problem and is NP-hard, we design a three-stage heuristic yet joint alternating optimization approach to obtain a suboptimal solution. Extensive numerical results demonstrate the superior performances of the proposed scheme in multiple perspectives.
Keywords:
Resource management
Vehicular ad hoc networks
Vehicle-to-infrastructure
Optimization
Entertainment industry
NOMA
Safety
5G vehicle-to-everything communications
sparse code multiple access
centralized resource allocation

Journal

IEEE Transactions on Communications cover
IEEE Transactions on Communications
IF:
8.3
Papers:
1.2W
Citations:
3.6W

Organization

N
Northwestern Polytechnical University
Scholars:
4.6W
Papers: 3.7W
Citations: 5.3W
X
Xidian University
Scholars:
2.4W
Papers: 1.9W
Citations: 9.7K