Energy Efficiency Optimization for Multi-cell Massive MIMO : Centralized and Distributed Power Allocation Algorithms
You, L., Huang, Y., Zhang, D., Chang, Z., Wang, W., & Gao, X. (2021). Energy Efficiency Optimization for Multi-cell Massive MIMO : Centralized and Distributed Power Allocation Algorithms. IEEE Transactions on Communications, 69(8), 5228-5242. https://doi.org/10.1109/TCOMM.2021.3081451
Published in
IEEE Transactions on CommunicationsDate
2021Copyright
© 2021, IEEE
This paper investigates the energy efficiency (EE) optimization in downlink multi-cell massive multiple-input multiple-output (MIMO). In our research, the statistical channel state information (CSI) is exploited to reduce the signaling overhead. To maximize the minimum EE among the neighbouring cells, we design the transmit covariance matrices for each base station (BS). Specifically, optimization schemes for this max-min EE problem are developed, in the centralized and distributed ways, respectively. To obtain the transmit covariance matrices, we first find out the closed-form optimal transmit eigenmatrices for the BS in each cell, and convert the original transmit covariance matrices designing problem into a power allocation one. Then, to lower the computational complexity, we utilize an asymptotic approximation expression for the problem objective. Moreover, for the power allocation design, we adopt the minorization maximization method to address the non-convexity of the ergodic rate, and use Dinkelbach’s transform to convert the max-min fractional problem into a series of convex optimization subproblems. To tackle the transformed subproblems, we propose a centralized iterative water-filling scheme. For reducing the backhaul burden, we further develop a distributed algorithm for the power allocation problem, which requires limited inter-cell information sharing. Finally, the performance of the proposed algorithms are demonstrated by extensive numerical results.
...
Publisher
Institute of Electrical and Electronics Engineers (IEEE)ISSN Search the Publication Forum
0090-6778Keywords
Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/89734633
Metadata
Show full item recordCollections
Additional information about funding
This work was supported in part by the National Key R&D Program of China under Grant 2018YFB1801103; in part by the National Natural Science Foundation of China under Grants 61801114, 61631018, and 61761136016; in part by the Jiangsu Province Basic Research Project under Grant BK20192002; and in part by the Fundamental Research Funds for the Central Universities. The work of D. Zhang is supported by the National Science Foundation of China (NSFC) under grant 62001423; Henan Provincial Key Research, Development and Promotion Project under grant 212102210175; Henan Provincial Key Scientific Research Project for Colleges and Universities under grant 21A510011. The work of Z. Chang is partly supported by NSFC No. 62071105. ...License
Related items
Showing items with similar title or keywords.
-
The Max-Product Algorithm Viewed as Linear Data-Fusion : A Distributed Detection Scenario
Abdi, Younes; Ristaniemi, Tapani (Institute of Electrical and Electronics Engineers (IEEE), 2020)In this paper, we disclose the statistical behavior of the max-product algorithm configured to solve a maximum a posteriori (MAP) estimation problem in a network of distributed agents. Specifically, we first build a ... -
Optimization of Linearized Belief Propagation for Distributed Detection
Abdi, Younes; Ristaniemi, Tapani (IEEE, 2020)In this paper, we investigate distributed inference schemes, over binary-valued Markov random fields, which are realized by the belief propagation (BP) algorithm. We first show that a decision variable obtained by the BP ... -
Energy efficient optimisation for large-scale multiple-antenna system with WPT
Chang, Zheng; Zhang, Shan; Wang, Zhongyu; Guo, Xijuan; Han, Zhu; Ristaniemi, Tapani (IET, 2018)In this study, an energy-efficient optimisation scheme for a large-scale multiple-antenna system with wireless power transfer (WPT) is presented. In the considered system, the user is charged by a base station with a large ... -
Energy Efficient Optimization for Wireless Virtualized Small Cell Networks With Large-Scale Multiple Antenna
Chang, Zheng; Han, Zhu; Ristaniemi, Tapani (IEEE, 2017)Wireless network virtualization is envisioned as a promising framework to provide efficient and customized services for next-generation wireless networks. In wireless virtualized networks (WVNs), limited radio resources ... -
Joint Spectral and Energy Efficiency Optimization for Downlink NOMA Networks
Khan, Wali Ullah; Jameel, Furqan; Ristaniemi, Tapani; Khan, Shafiullah; Sidhu, Guftaar Ahmad Sardar; Liu, Ju (Institute of Electrical and Electronics Engineers, 2020)Non-orthogonal multiple access (NOMA) holds the promise to be a key enabler of 5G communication. However, the existing design of NOMA systems must be optimized to achieve maximum rate while using minimum transmit power. ...