联合干扰控制与PSO的D2D网络资源分配

doi:10.3969/j.issn.0255-8297.2021.02.016

摘要/Abstract

摘要： 针对D2D（device-to-device）通信用户在复用传统蜂窝通信信道资源的过程中会产生干扰问题，提出了一种基于粒子群算法（particle swarm optimization，PSO）的D2D通信功率匹配联合干扰控制资源分配算法，在控制干扰的同时实现整个系统吞吐量最大化。首先，通过不同用户功率的阈值划分不同安全通信范围，只有处于安全通信范围的用户才能进行后续的功率分配，从而有效降低系统干扰；其次，采用一种基于粒子群算法的功率匹配方法，将D2D用户发送端作为粒子群，通过迭代寻找最优功率，使整个系统吞吐量最大化。仿真结果表明：本文所提出的算法可以明显提高系统的整体吞吐量并降低干扰至最低，从而使整个系统的通信质量达到最优。

关键词: D2D, 资源分配, 粒子群算法, 吞吐量, 干扰

Abstract: Address to interference problems faced by D2D (device-to-device) communication users in the process of multiplexing traditional cellular communication channel resources, a resource allocation algorithm based on particle swarm optimization (PSO) algorithm for D2D communication power matching joint interference control is proposed in this paper, which maximizes the throughput of the whole system while controlling interference. Firstly, security communication are divided into different ranges according to threshold values of user-powers, and only the users in the security communication range have opportunity to join in subsequent power distribution, thus effectively reducing system interference. Secondly, a power matching method based on PSO is adopted to take D2D senders as particle swarm. It maximizes the throughput of the whole system by searching for the optimal power through iteration. Simulation results show that the proposed algorithm can significantly improve the overall throughput of the system and minimize the interference, so as to achieve the optimal communication quality of the whole system.

Key words: D2D (device-to-device), resource allocation, particle swarm optimization (PSO), throughput, interference

中图分类号:

TN929.5

刘煜恒, 彭艺, 付晓霞, 安浩杰. 联合干扰控制与PSO的D2D网络资源分配[J]. 应用科学学报, 2021, 39(2): 338-346.

LIU Yuheng, PENG Yi, FU Xiaoxia, AN Haojie. D2D Network Resource Allocation Based on Joint Interference Control and PSO[J]. Journal of Applied Sciences, 2021, 39(2): 338-346.

参考文献

[1] Zhang Z, Hu R Q, Qian Y. D2D communication underlay in uplink cellular networks with distance based power control[C]//2016 IEEE International Conference on Communications (ICC). Kuala Lumpur, 2016:1-6.
[2] Elsherief M, Elwekeil M, Elnaby M A. Resource and power allocation for achieving rate fairness in D2D communications overlaying cellular networks[J]. Wireless Networks, 2019, 25(7):4049-4058.
[3] Dhilipkumar S, Arunachalaperumal C, Thanigaivelu K. A comparative study of resource allocation schemes for D2D networks underlay cellular networks[J]. Wireless Personal Communications, 2019, 106(3):1075-1087.
[4] Elgarhy O, Reggiani L. Increasing efficiency of resource allocation for D2D communication in NB-IoT context[J]. Procedia Computer Science, 2018, 130:1084-1089.
[5] Sun Z, Yang D. A D2D wireless resource allocation scheme based on overall fairness[J]. 3D Research, 2019, 10(2):1-10.
[6] Jang S, Han C, Lee K, et al. Reinforcement learning-based dynamic band and channel selection in cognitive radio ad-hoc networks[J]. EURASIP Journal on Wireless Communications and Networking, 2019, 2019(1):1-25.
[7] Yu S, Ejaz W, Guan L, et al. Resource allocation in RF energy harvesting-assisted underlay D2D communication[J]. Transactions on Emerging Telecommunications Technologies, 2019, 30(7):435-420.
[8] Dhilipkumar S, Arunachalaperumal C, Thanigaivelu K. A Comparative study of resource allocation schemes for D2D networks underlay cellular networks[J]. Wireless Personal Communications, 2019, 106(3):1075-1087.
[9] 翟旭平, 龚磊, 张男. 基于补偿因子的D2D通信自适应联合功率控制算法[J]. 应用科学学报, 2019, 37(1):1-11. Zhai X P, Gong L, Zhang N. Adaptive joint power control algorithm based on compensation factor for device-to-device communication[J]. Journal of Applied Sciences, 209, 37(1):1-11. (in Chinese)
[10] 袁泉, 孙彦超, 李校林, 等. 一种基于用户划分的LTE上行闭环功率控制算法[J]. 重庆邮电大学学报(自然科学版), 2013, 25(3):305-309 Yuan Q, Sun Y C, Li J L, et al. A LTE up link closed loop power control algorithm based on division of UEs[J]. Journal of Chongqing University of Posts and Tele Communications (Natural Science), 2013, 25(3):305-309. (in Chinese)
[11] Sun S, Shin Y. Resource allocation for D2D communication using particle swarm optimization in LTE networks[C]//International Conference on Information and Communication Technology Convergence. IEEE, 2014:371-376.
[12] Huang S, Li J, Huang J. DTMR:delay-aware traffic admission, mode selection, and resource allocation for D2D communication[J]. Wireless Networks, 2019, 25(1):439-453.
[13] Hamdi M, Zaied M. Resource allocation based on hybrid genetic algorithm and particle swarm optimization for D2D multicast communications[J]. Applied Soft Computing Journal, 2019, 83(2):152-164.
[14] Xu Y F, Yin R, Han T, et al. Dynamic resource allocation for device-to-device communication underlaying cellular net-works[J]. International Journal of Communication Systems, 2014, 27(10):2408-2425.

[1]	金彦亮, 罗雪涛, 王雪, 聂宏. 基于窄带干扰缓和技术的到达时间估计[J]. 应用科学学报, 2020, 38(3): 455-465.
[2]	翟旭平, 龚磊, 张男. 基于补偿因子的D2D通信自适应联合功率控制算法[J]. 应用科学学报, 2019, 37(1): 1-11.
[3]	苏云霞, 吴雅婷, 张雪凡. LED可见光通信的抗干扰及其工程实现[J]. 应用科学学报, 2018, 36(3): 451-460.
[4]	董莉, 宋晓勤, 韩杰. 基于遗传粒子群优化的认知OFDM网络资源分配算法[J]. 应用科学学报, 2017, 35(3): 288-298.
[5]	陈佳敏, 朱琦. 基于启发式蚁群算法的家庭基站信道分配方法[J]. 应用科学学报, 2017, 35(3): 299-308.
[6]	杨琼, 张怡, 唐成凯, 何伟. GPS空时自适应滤波矩阵重构抗干扰算法[J]. 应用科学学报, 2016, 34(4): 380-386.
[7]	杨柳, 郭道省, 叶展, 谢斯林, 王雅慧, 张邦宁. 卫星通信系统中编码调制模式分配算法[J]. 应用科学学报, 2016, 34(4): 371-379.
[8]	向伟, 张剑峰, 谢威, 马文峰. 异构蜂窝网络中功率有效的家庭基站分簇频谱分配策略[J]. 应用科学学报, 2016, 34(3): 275-285.
[9]	许坤, 陈谋. 基于干扰观测器的移动机器人轨迹跟踪控制[J]. 应用科学学报, 2016, 34(2): 177-189.
[10]	徐凤阳, 王东, 肖扬, 寇金锋. 大规模MIMO系统中基于子空间跟踪的半盲信道估计[J]. 应用科学学报, 2015, 33(5): 459-469.
[11]	刘文钊, 戴幻尧, 黄振宇, 崔建岭. 基于空域调制效应的干扰极化参数估计[J]. 应用科学学报, 2015, 33(5): 518-526.
[12]	林启中，张冬梅，许魁，谢威. 蜂窝网络中M2M通信上行接入资源分配[J]. 应用科学学报, 2015, 33(2): 129-141.
[13]	倪艺洋，邵世祥，朱洪波. 单向放大转发中继D2D 通信系统可达速率分析与联合功率优化[J]. 应用科学学报, 2014, 32(6): 559-565.
[14]	许悦，朱琦. 基于干扰管理的宏基站与家庭基站联合资源分配[J]. 应用科学学报, 2014, 32(5): 493-498.
[15]	杨鼎成1，何浩2. 多小区MU-MIMO系统中基于信道投射的块对角化预编码设计[J]. 应用科学学报, 2014, 32(4): 385-393.