Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (4): 877-886.doi: 10.23919/JSEE.2022.000085

• ELECTRONICS TECHNOLOGY • Previous Articles     Next Articles

Energy-efficient resource management for CCFD massive MIMO systems in 6G networks

Yumeng SU(), Hongyuan GAO*(), Shibo ZHANG()   

  1. 1 College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
  • Received:2020-10-19 Accepted:2022-03-01 Online:2022-08-30 Published:2022-08-30
  • Contact: Hongyuan GAO E-mail:suyumeng1994@126.com;gaohongyuan@hrbeu.edu.cn;liangziyanhua@126.com
  • About author:|SU Yumeng was born in 1994. She received her B.S. degree in electronic information engineering from Harbin Engineering University, Harbin, Heilongjiang, China, in 2016. She is currently working toward her Ph.D. degree with Harbin Engineering University. Her current research interests include intelligent computing, resource management, secure communications, massive MIMO, co-frequency co-time full-duplex systems, network slicing, and beyond 5G technologies.E-mail: suyumeng1994@126.com||GAO Hongyuan was born in 1977. He received his Ph.D. degree from the Department of Communication and Information Systems, College of Information and Communication Engineering, Harbin Engineering University, China, in 2010. He was a visiting research professor with the Department of Computer and Information Science, Korea University, Sejong, South Korea, from 2015 to 2016. He is currently an associate professor with the College of Information and Communication Engineering, Harbin Engineering University. His research interests include wireless energy harvesting communications, intelligent computing, software radio, signal recognition and classification, cognitive radio, array signal processing, long term evolution (LTE)-unlicensed, artificial intelligence, HetNets in 5G, communication theory and image processing, and massive MIMO. E-mail: gaohongyuan@hrbeu.edu.cn||ZHANG Shibo was born in 1994. He received his B.S. degree in electronic information engineering from Harbin Engineering University, Harbin, Heilongjiang, China, in 2016. He is currently working toward his Ph.D. degree with Harbin Engineering University. His research interests include fog/edge computing, cognitive relays, energy harvesting, heterogeneous networks, the Internet-of-Things, and future 6G networks. E-mail: liangziyanhua@126.com
  • Supported by:
    This work was supported by the Ph.D. Student Research and Innovation Fund of the Fundamental Research Funds for the Central Universities (3072020GIP0803), Heilongjiang Province Key Laboratory Fund of High Accuracy Satellite Navigation and Marine Application Laboratory (HKL-2020-Y01), the National Natural Science Foundation of China (61571149), the Initiation Fund for Postdoctoral Research in Heilongjiang Province (LBH-Q19098), and the Key Laboratory of Advanced Marine Communication and Information Technology, Ministry of Industry and Information Technology

Abstract:

This paper presents a co-time co-frequency full-duplex (CCFD) massive multiple-input multiple-output (MIMO) system to meet high spectrum efficiency requirements for beyond the fifth-generation (5G) and the forthcoming the sixth-generation (6G) networks. To achieve equilibrium of energy consumption, system resource utilization, and overall transmission capacity, an energy-efficient resource management strategy concerning power allocation and antenna selection is designed. A continuous quantum-inspired termite colony optimization (CQTCO) algorithm is proposed as a solution to the resource management considering the communication reliability while promoting energy conservation for the CCFD massive MIMO system. The effectiveness of CQTCO compared with other algorithms is evaluated through simulations. The results reveal that the proposed resource management scheme under CQTCO can obtain a superior performance in different communication scenarios, which can be considered as an eco-friendly solution for promoting reliable and efficient communication in future wireless networks.

Key words: the sixth-generation (6G), massive multiple-input multiple-output (MIMO), co-time co-frequency full-duplex, energy-efficient, resource management