Hypergraph-Based Joint Channel and Power Resource Allocation for Cross-Cell M2M Communication in IIoT

被引：6

作者：

Zhuansun, Chenlu ^{[1
]}

Yan, Kedong ^{[1
]}

Zhang, Gongxuan ^{[1
]}

Huang, Chanying ^{[1
]}

Xiao, Shan ^{[2
]}

机构：

[1] Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, Nanjing 210094, Peoples R China

[2] Fiberhome Telecommun Technol Co Ltd, Nanjing 210026, Peoples R China

来源：

IEEE INTERNET OF THINGS JOURNAL | 2023年 / 10卷 / 17期

关键词：

Machine-to-machine communications; Interference; Resource management; Industrial Internet of Things; NOMA; Complexity theory; Receivers; Cross-cell machine-to-machine (M2M); hypergraph theory; Industrial Internet of Things (IIoT); nonorthogonal multiple access (NOMA); resource allocation; TO-MACHINE COMMUNICATIONS; RANDOM-ACCESS; NETWORKS; MANAGEMENT; SCHEME; ENERGY;

D O I：

10.1109/JIOT.2023.3263567

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Industrial Internet of Things (IIoT) is the leading application scenario of the fifth generation wireless communication systems (5G) and beyond. Nonorthogonal multiple access (NOMA) has become a key technology for 5G due to its high spectrum efficiency. In this article, a joint channel and power resource allocation problem is investigated for cross-cell IIoT networks with aim of maximizing sum rate of NOMA-based machine-to-machine pairs and cellular Machine Devices (cMDs). Since joint channel and power resource allocation problem is an NP-hard problem, the original problem is transformed into a hypergraph model to optimize channel and power resource allocation. Then, a channel allocation algorithm based on hypergraph coloring theory is proposed, and an alternative power allocation algorithm is presented. Next, some properties of hypergraph coloring and complexities are analyzed. Finally, simulation results demonstrate that the proposed algorithm outperforms the graph-based algorithm in terms of sum rate, and also improves the spectrum efficiency significantly.

引用

页码：15350 / 15361

页数：12

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