面向电力物联网的5G通信认知无线电NOMA系统研究

doi:10.11930/j.issn.1004-9649.202010099

中国电力 ›› 2021, Vol. 54 ›› Issue (5): 35-45.DOI: 10.11930/j.issn.1004-9649.202010099

• 国家“十三五”智能电网重大专项专栏：（七）电力信息通信新技术在能源互联网中的研究与应用专栏 • 上一篇下一篇

面向电力物联网的5G通信认知无线电NOMA系统研究

佘蕊, 张宁池, 王艳茹, 郭丹丹, 马文洁, 刘卉, 张洁

国网信产集团北京中电飞华通信有限公司通信技术中心，北京 100071

收稿日期:2020-10-20 修回日期:2021-03-10 发布日期:2021-05-05
作者简介:佘蕊(1994-),女,通信作者,硕士,助理工程师,从事电力无线通信,电力物联网,信息数据安全传输研究,E-mail:m13730178637@163.com;张宁池(1983-),男,高级工程师,从事电力经济、电力供需研究,E-mail:zhangningchi@sgitg.sgcc.com.cn;王艳茹(1985-),女,硕士,高级工程师,从事电力通信技术研究,E-mail:wangyanru@sgitg.sgcc.com.cn
基金资助:
国家电网公司科技项目(5700-201941235A-0-0-00)

Research on Cognitive Radio Non-orthogonal Multiple Access System in 5G Communications Oriented to Ubiquitous Power Internet of Things

SHE Rui, ZHANG Ningchi, WANG Yanru, GUO Dandan, MA Wenjie, LIU Hui, ZHANG Jie

Communication Technology Center, State Grid Information & Telecommunication Group Beijing Zhongdian Feihua Communications Co., Ltd., Beijing 100071, China

Received:2020-10-20 Revised:2021-03-10 Published:2021-05-05
Supported by:
This work is supported by the Science and Technology Projects of State Grid Corporation of China (No.5700-201941235A-0-0-00)

摘要/Abstract

摘要： 随着电力物联网建设的不断推进，配电网中产生的数据量呈指数增长，传统基于认知无线电的智能电力通信网络已无法满足大量用电信息采集设备对频谱资源高度需求。构建了面向电力物联网的5G网络模型，旨在利用非正交多址接入（non-orthogonal multiple access, NOMA）技术的非正交传输特性进一步提高有限电力专网的频谱资源利用率，为保证频谱检测的准确性，采用多用户协作感知方式。推导了频谱接入概率和吞吐量的闭合表达式；为进一步提高分类结果的准确性，提出了一种改进K-means算法。利用交替迭代算法对检测时间、节点功率和用户簇数进行联合优化，以最大化系统吞吐量。仿真结果表明，与传统正交多址接入系统相比，在改善频谱利用率的同时，感知结果的准确性也得到明显提高。

关键词: 电力物联网, 5G通信, 认知无线电, 非正交多址, 智能电网

Abstract: With the continuous advancement of the construction of the power Internet of Things, the power distribution network has seen exponential growth of data volume. As a result, the traditional smart power communication network based on cognitive radio is no longer capable of meeting the high demand for spectrum resources by a large number of devices that are installed to collect power consumption data. This paper constructs a 5G network model for the power Internet of Things, which aims to use the non-orthogonal transmission characteristics of non-orthogonal multiple access (NOMA) technology to further improve the spectrum resource utilization of the limited power private network. To ensure the accuracy of spectrum detection, a multi-user cooperative sensing method is adopted. The closed expressions of spectrum access probability and throughput are derived; in order to further increase the accuracy of the classification results, an improved K-means algorithm is proposed. The alternate iterative algorithm is implemented to jointly optimize the detection time, node power and the number of user clusters such that the system throughput can be maximized eventually. The simulation results show that compared with the traditional orthogonal multiple access system, not only the spectrum utilization but also the accuracy of the sensing results are significantly improved.

Key words: power internet of things, 5G communication, cognitive radio, non-orthogonal multiple access, smart grid

佘蕊, 张宁池, 王艳茹, 郭丹丹, 马文洁, 刘卉, 张洁. 面向电力物联网的5G通信认知无线电NOMA系统研究[J]. 中国电力, 2021, 54(5): 35-45.

SHE Rui, ZHANG Ningchi, WANG Yanru, GUO Dandan, MA Wenjie, LIU Hui, ZHANG Jie. Research on Cognitive Radio Non-orthogonal Multiple Access System in 5G Communications Oriented to Ubiquitous Power Internet of Things[J]. Electric Power, 2021, 54(5): 35-45.

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参考文献

[1] LIN W, ZIOLKOWSKI R W, HUANG J Q. Electrically small, low-profile, highly efficient, Huygens dipole rectennas for wirelessly powering Internet-of-things devices[J]. IEEE Transactions on Antennas and Propagation, 2019, 67(6): 3670-3679.
[2] SONG F, ZHU M Q, ZHOU Y T, et al. Smart collaborative tracking for ubiquitous power IoT in edge-cloud interplay domain[J]. IEEE Internet of Things Journal, 2020, 7(7): 6046-6055.
[3] 张宁, 杨经纬, 王毅, 等. 面向泛在电力物联网的5G通信: 技术原理与典型应用[J]. 中国电机工程学报, 2019, 39(14): 4015-4025
ZHANG Ning, YANG Jingwei, WANG Yi, et al. 5G communication for the ubiquitous Internet of Things in electricity: technical principles and typical applications[J]. Proceedings of the CSEE, 2019, 39(14): 4015-4025
[4] KAKKAVAS G, TSITSEKLIS K, KARYOTIS V, et al. A software defined radio cross-layer resource allocation approach for cognitive radio networks: from theory to practice[J]. IEEE Transactions on Cognitive Communications and Networking, 2020, 6(2): 740-755.
[5] LIN T H, YANG G C, KWONG W C. A homogeneous multi-radio rendezvous algorithm for cognitive radio networks[J]. IEEE Communications Letters, 2019, 23(4): 736-739.
[6] 徐思雅, 张国翊, 郭少勇, 等. 一种认知无线电的智能电网通信业务数据分组调度机制[J]. 北京邮电大学学报, 2015, 38(增刊1): 15-19
XU Siya, ZHANG Guoyi, GUO Shaoyong, et al. A packet scheduling mechanism on cognitive radio networks for smart grid[J]. Journal of Beijing University of Posts and Telecommunications, 2015, 38(S1): 15-19
[7] 翟少磊, 李博, 张林山, 等. 电力物联网信息化控制中一种高效的认知通信方法[J]. 中国电力, 2016, 49(8): 130-134
ZHAI Shaolei, LI Bo, ZHANG Linshan, et al. An efficient cognitive radio communication algorithm for electric power IOT information control[J]. Electric Power, 2016, 49(8): 130-134
[8] 王毅, 陈启鑫, 张宁, 等. 5G通信与泛在电力物联网的融合: 应用分析与研究展望[J]. 电网技术, 2019, 43(5): 1575-1585
WANG Yi, CHEN Qixin, ZHANG Ning, et al. Fusion of the 5G communication and the ubiquitous electric Internet of Things: application analysis and research prospects[J]. Power System Technology, 2019, 43(5): 1575-1585
[9] 王宏延, 顾舒娴, 完颜绍澎, 等. 5G技术在电力系统中的研究与应用[J]. 广东电力, 2019, 32(11): 78-85
WANG Hongyan, GU Shuxian, WANYAN Shaopeng, et al. Research and application of 5G technology in power systems[J]. Guangdong Electric Power, 2019, 32(11): 78-85
[10] 宣以所. 5G移动通信发展趋势与若干关键技术应用研究[J]. 信息与电脑(理论版), 2017, 377(07): 172-174
XUAN Yisuo. Research on the Development Trend of 5G Mobile Communication and Several Key Technologies[J]. China Computer & Communication, 2017, 377(07): 172-174
[11] 毕奇, 梁林, 杨姗, 等. 面向5G的非正交多址接入技术[J]. 电信科学, 2015, 31(5): 20-27
BI Qi, LIANG Lin, YANG Shan, et al. Non-orthogonal multiple access technology for 5G systems[J]. Telecommunications Science, 2015, 31(5): 20-27
[12] 刘志航, 田宇昊, 袁伟娜. 5G非正交多址技术关键问题研究[J]. 自动化仪表, 2019, 40(8): 83-88
LIU Zhihang, TIAN Yuhao, YUAN Weina. Research on key issues of 5G non-orthogonal multiple access technology[J]. Process Automation Instrumentation, 2019, 40(8): 83-88
[13] ANDREWS J G, BUZZI S, WAN C, et al. What Will 5G Be?[J]. IEEE Journal on Selected Areas in Communications, 2014, 32(6): 1065-1082.
[14] DING Z, LEI X, KARAG G K, et al. A Survey on Non-Orthogonal Multiple Access for 5G Networks: Research Challenges and Future Trends[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(10): 2181-2195.
[15] WANG B, DAI L, WANG Z, et al. Spectrum and Energy Efficient Beamspace MIMONOMA for Millimeter-Wave Communications Using Lens Antenna Array[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(10): 2370-2382.
[16] SALEHI M, TABASSUM H, HOSSAIN E. Meta Distribution of SIR in Large-Scale Uplink and Downlink NOMA Networks[J]. IEEE Transactions on Communications, 2018, 67(4): 3009-3025.
[17] ZHANG Z, SUN H, HU R Q. Downlink and Uplink Non-Orthogonal Multiple Access in a Dense Wireless Network[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(12): 2771-2784.
[18] LIU Y W, DING Z G, ELKASHLAN M, et al. Nonorthogonal multiple access in large-scale underlay cognitive radio networks[J]. IEEE Transactions on Vehicular Technology, 2016, 65(12): 10152-10157.
[19] LV L, NI Q, DING Z G, et al. Application of non-orthogonal multiple access in cooperative spectrum-sharing networks over nakagami- $m$ fading channels[J]. IEEE Transactions on Vehicular Technology, 2017, 66(6): 5506-5511.
[20] LV L, CHEN J, NI Q, et al. Design of cooperative non-orthogonal multicast cognitive multiple access for 5G systems: user scheduling and performance analysis[J]. IEEE Transactions on Communications, 2017, 65(6): 2641-2656.
[21] KADER F, SHIN S Y. Cooperative spectrum sharing with space time block coding and non-orthogonal multiple access[C]//2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN). Vienna, Austria. IEEE, 2016: 490-494.
[22] 杨纲, 寇健, 严思唯, 等. 基于改进kmeans++算法的用户分类与电价政策影响分析[J]. 电力需求侧管理, 2020, 22(3): 57-62
YANG Gang, KOU Jian, YAN Siwei, et al. Classification of users and analysis of influence of electricity price policy based on improved kmeans++ algorithm[J]. Power Demand Side Management, 2020, 22(3): 57-62
[23] 罗鸿轩, 肖勇, 杨劲锋, 等. 基于边缘计算与MapReduce的智能量测终端数据处理方法[J]. 智慧电力, 2020, 48(3): 22-29
LUO Hongxuan, XIAO Yong, YANG Jinfeng, et al. Data processing method for smart metering terminal based on edge computing and map reduce[J]. Smart Power, 2020, 48(3): 22-29
[24] LU P, LV H, LIU N, et al. Optimal flexibility dispatch of demand side resources with high penetration of renewables: a Stackelberg game method[J]. Global Energy Interconnection, 2021, 4(1): 28-38.
[25] LU X J, WANG J, LIU G, et al. Station-and-network-coordinated planning of integrated energy system considering integrated demand response[J]. Global Energy Interconnection, 2021, 4(1): 39-47.

面向电力物联网的5G通信认知无线电NOMA系统研究

Research on Cognitive Radio Non-orthogonal Multiple Access System in 5G Communications Oriented to Ubiquitous Power Internet of Things

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面向电力物联网的5G通信认知无线电NOMA系统研究

Research on Cognitive Radio Non-orthogonal Multiple Access System in 5G Communications Oriented to Ubiquitous Power Internet of Things

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