A Learning-Inspired Resource Allocation for Energy Harvesting-Powered Cognitive M2M Communications

XU Yi-han; TIAN Yong-bo; ZHANG Yang-gang; HUA Min; ZHOU Wen

doi:10.12263/DZXB.20211258

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A Learning-Inspired Resource Allocation for Energy Harvesting-Powered Cognitive M2M Communications

PAPERS | 更新时间：2025-12-08

- A Learning-Inspired Resource Allocation for Energy Harvesting-Powered Cognitive M2M Communications
- ACTA ELECTRONICA SINICA Vol. 51, Issue 2, Pages: 467-476(2023)
- 作者机构：
  
  1.南京林业大学信息科学技术学院，江苏南京 210037
  2.复旦大学信息科学与工程学院，上海 200433
- 作者简介：
- 基金信息：
  
  Foundation Item(s):　National Natural Science Foundation of China(61801225;61601275);Scientific Research Fund for Introducing High-Level Talents and High-Level Returnees of Nanjing Forestry University(GXL015)
- DOI：10.12263/DZXB.20211258
  CLC： TN914;
- Received：13 September 2021，
  
  Revised：2022-08-28，
  
  Published：25 February 2023
- 稿件说明：
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许艺瀚,田永波,张扬刚等.基于学习的能量采集认知M2M通信资源分配算法[J].电子学报,2023,51(02):467-476.

XU Yi-han,TIAN Yong-bo,ZHANG Yang-gang,et al.A Learning-Inspired Resource Allocation for Energy Harvesting-Powered Cognitive M2M Communications[J].ACTA ELECTRONICA SINICA,2023,51(02):467-476.
许艺瀚,田永波,张扬刚等.基于学习的能量采集认知M2M通信资源分配算法[J].电子学报,2023,51(02):467-476. DOI： 10.12263/DZXB.20211258.

XU Yi-han,TIAN Yong-bo,ZHANG Yang-gang,et al.A Learning-Inspired Resource Allocation for Energy Harvesting-Powered Cognitive M2M Communications[J].ACTA ELECTRONICA SINICA,2023,51(02):467-476. DOI： 10.12263/DZXB.20211258.

摘要

本文针对能量采集认知机器到机器（Machine-to-Machine，M2M）通信的能量效率问题，在保证服务质量（Quality of Service，QoS）的条件下，提出了一种能效优化算法.以最大化网络中用户能效为目标，综合考虑传输功率控制、时隙分配、传输模式选择、中继选择以及每个设备的能量状态为约束，将优化问题建模为一个混合整数非线性规划问题.将该能效优化问题转化为离散时间有限状态马尔科夫决策过程（Discrete-time and Finite-state Markov Decision Process，DFMDP）进行求解.提出一种基于深度强化学习的算法寻找最优策略.仿真结果表明，所提算法在平均能效方面优于其他方案，且收敛速度在可接受范围内.

Abstract

In order to optimize the energy efficiency for energy harvesting-powered cognitive M2M communications underlaying cellular network

an energy efficient algorithm is proposed while guaranteeing the quality of service of users. Firstly

the problem is formulated as a mixed integer nonlinear programming problem with the goal of maximizing energy efficiency by jointly considering transmission power control

time slot allocation

transmission mode and relay selection with the constraints of the energy status of each device. After that

the optimization problem is modeled as a discrete-time and finite-state Markov decision process. Afterward

a deep reinforcement learning-based algorithm is proposed to find the optimal strategy. Numerical results validate that the proposed scheme outperforms other schemes in terms of average energy efficiency with an acceptable convergence speed.

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references

ZHOU Z Y , GONG J , HE Y J , et al . Software defined machine-to-machine communication for smart energy management [J]. IEEE Communications Magazine , 2017 , 55 ( 10 ): 52 - 60 .

ZHANG C T , ZHOU Z Y , LIU P J , et al . Resource allocation for energy harvesting based cognitive machine-to-machine communications [C]// ICC 2019 - 2019 IEEE International Conference on Communications (ICC) . Shanghai : IEEE , 2019 : 1 - 6 .

ALHUSSIEN N , GULLIVER T A . Optimal resource allocation in cellular networks with H2H/M2M coexistence [J]. IEEE Transactions on Vehicular Technology , 2020 , 69 ( 11 ): 12951 - 12962 .

蒋继胜 , 朱晓荣 . H2H与M2M共存场景下的上行资源分配算法 [J]. 电子学报 , 2018 , 46 ( 5 ): 1259 - 1264 .

JIANG J S , ZHU X R . An uplink resource allocation algorithm under the scenario of coexistence of H2H & M2M based on knapsack model [J]. Acta Electronica Sinica , 2018 , 46 ( 5 ): 1259 - 1264 . (in Chinese)

AHMAD T , CHAI R , ADNAN M , et al . Low-complexity heuristic algorithm for power allocation and access mode selection in M2M networks [J]. IEEE Internet of Things Journal , 2022 , 9 ( 2 ): 1095 - 1108 .

ZHOU Z Y , GUO Y F , HE Y H , et al . Access control and resource allocation for M2M communications in industrial automation [J]. IEEE Transactions on Industrial Informatics , 2019 , 15 ( 5 ): 3093 - 3103 .

JANG H S , PARK H S , SUNG D K . A non-orthogonal resource allocation scheme in spatial group based random access for cellular M2M communications [J]. IEEE Transactions on Vehicular Technology , 2017 , 66 ( 5 ): 4496 - 4500 .

NOBAR S K , AHMED M H , MORGAN Y , et al . Uplink resource allocation in energy harvesting cellular network with H2H/M2M coexistence [J]. IEEE Transactions on Wireless Communications , 2020 , 19 ( 8 ): 5101 - 5116 .

田辉 , 王聪 , 马文峰 , 等 . 一种人与人和机器到机器共存下能效最大化的上行用户分配算法 [J]. 电子与信息学报 , 2021 , 43 ( 10 ): 2902 - 2910 .

TIAN H , WANG C , MA W F , et al . A user association algorithm for maximizing energy efficiency with human-to-human and machine-to-machine coexistence [J]. Journal of Electronics & Information Technology , 2021 , 43 ( 10 ): 2902 - 2910 . (in Chinese)

徐少毅 , 高帅 . 机器对机器通信中一种基于能量效率与系统容量的多目标无线资源管理算法 [J]. 电子与信息学报 , 2019 , 41 ( 12 ): 2817 - 2825 .

XU S Y , GAO S . Energy efficiency and system capacity based multi-objective radio resource management in M2M communications [J]. Journal of Electronics & Information Technology , 2019 , 41 ( 12 ): 2817 - 2825 . (in Chinese)

MITRAN P . On optimal online policies in energy harvesting systems for compound Poisson energy arrivals [C]// 2012 IEEE International Symposium on Information Theory Proceedings . Cambridge : IEEE , 2012 : 960 - 964 .

BAXTER L A . Markov decision processes: Discrete stochastic dynamic programming [J]. Technometrics , 1995 , 37 ( 3 ): 353 .

CAI X J , ZHENG J , ZHANG Y . A Graph-coloring based resource allocation algorithm for D2D communication in cellular networks [C]// 2015 IEEE International Conference on Communications (ICC) . London : IEEE , 2015 : 5429 - 5434 .

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