Power allocation algorithms for massive MIMO systems with multi-antenna users
Authors: 
Evgeny Bobrov, Boris Chinyaev, Viktor Kuznetsov, Dmitrii Minenkov, Daniil YudakovAuthors Info & Claims
Abstract
Modern 5G wireless cellular networks use massive multiple-input multiple-output (MIMO) technology. This concept entails using an antenna array at a base station to concurrently service many mobile devices that have several antennas on their side. In this field, a significant role is played by the precoding (beamforming) problem. During downlink, an important part of precoding is the power allocation problem that distributes power between transmitted symbols. In this paper, we consider the power allocation problem for a class of precodings that asymptotically work as regularized zero-forcing. Under some realistic assumptions, we simplify the spectral efficiency functional and obtain tractable expressions for it. We prove that equal power allocation provides optimum for the simplified functional with total power constraint (TPC). We propose low-complexity Intersection methods (IM) that improve equal power allocation in the case of per-antenna power constraints (PAPC). On simulations using Quadriga, the proposed IM method in combination with widely-studied water filling (WF) shows a significant gain in spectral efficiency while using a similar computing time as the reference equal power (EP) solution.
References
[1]
Andrews Jeffrey G, Buzzi Stefano, Choi Wan, Hanly Stephen V, Lozano Angel, Soong Anthony CK, and Zhang Jianzhong Charlie What will 5G be? IEEE Journal on Selected Areas in Communications 2014 32 6 1065-1082
[2]
Marzetta Thomas L Noncooperative cellular wireless with unlimited numbers of base station antennas IEEE Transactions on Wireless Communications 2010 9 11 3590-3600
[3]
Ge Xiaohu, Zi Ran, Wang Haichao, Zhang Jing, and Jo Minho Multi-user massive MIMO communication systems based on irregular antenna arrays IEEE Transactions on Wireless Communications 2016 15 8 5287-5301
[4]
Le Long and Hossain Ekram Multihop cellular networks: Potential gains, research challenges, and a resource allocation framework IEEE Communications Magazine 2007 45 9 66-73
[5]
Phan Khoa T, Le-Ngoc Tho, Vorobyov Sergiy A, and Tellambura Chintha Power allocation in wireless multi-user relay networks IEEE Transactions on Wireless Communications 2009 8 5 2535-2545
[6]
Ngo Hien Quoc, Larsson Erik G, and Marzetta Thomas L Energy and spectral efficiency of very large multiuser MIMO systems IEEE Transactions on Communications 2013 61 4 1436-1449
[7]
Parfait, Tebe., Kuang, Yujun., & Jerry, Kponyo. (2014). Performance analysis and comparison of ZF and MRT based downlink massive MIMO systems. In 2014 sixth international conference on ubiquitous and future networks (ICUFN), pages 383–388. IEEE.
[8]
Zhang Jiankang, Chen Sheng, Maunder Robert G, Zhang Rong, and Hanzo Lajos Regularized zero-forcing precoding-aided adaptive coding and modulation for large-scale antenna array-based air-to-air communications IEEE Journal on Selected Areas in Communications 2018 36 9 2087-210
[9]
Fatema Nusrat, Hua Guang, Xiang Yong, Peng Dezhong, and Natgunanathan Iynkaran Massive MIMO linear precoding: A survey IEEE Systems journal 2017 12 4 3920-3931
[10]
Zheng Kan, Zhao Long, Mei Jie, Shao Bin, Xiang Wei, and Hanzo Lajos Survey of large-scale MIMO systems IEEE Communications Surveys & Tutorials 2015 17 3 1738-1760
[11]
Dhakal, Sunil. (2019). High rate signal processing schemes for correlated channels in 5G networks.
[12]
Björnson Emil, Hoydis Jakob, and Sanguinetti Luca Massive MIMO networks: Spectral, energy, and hardware efficiency Foundations and Trends in Signal Processing 2017 11 3–4 154-655
[13]
Tse, David., & Viswanath, Pramod. (2005).Fundamentals of wireless communication. Cambridge university press.
[14]
Wei Yu Uplink-downlink duality via minimax duality IEEE Transactions on Information Theory 2006 52 2 361-374
[15]
Björnson, Emil., & Jorswieck, Eduard. (2013). Optimal resource allocation in coordinated multi-cell systems. Now Publishers Inc.
[16]
Boccardi, Federico., Huang, Howard. (2006). Optimum power allocation for the MIMO-BC zero-forcing precoder with per-antenna power constraints. In 2006 40th Annual Conference on Information Sciences and Systems, pages 504–504. IEEE.
[17]
Deng Xitirnin and Haimovich Alexander M Power allocation for cooperative relaying in wireless networks IEEE Communications Letters 2005 9 11 994-996
[18]
Host-Madsen Anders and Zhang Junshan Capacity bounds and power allocation for wireless relay channels IEEE Transactions on Information Theory 2005 51 6 2020-2040
[19]
Liang Yingbin and Veeravalli Venugopal V Gaussian orthogonal relay channels: Optimal resource allocation and capacity IEEE Transactions on Information Theory 2005 51 9 3284-3289
[20]
Zhao, Yi., Adve, Raviraj., & Lim, Teng Joon. (2006). Improving amplify-and-forward relay networks: optimal power allocation versus selection. In 2006 ieee international symposium on information theory, pages 1234–1238. IEEE.
[21]
Nguyen Duy HN and Nguyen Ha H Power allocation in wireless multiuser multi-relay networks with distributed beamforming IET Communications 2011 5 14 2040-2051
[22]
Sanguinetti, Luca., Zappone, Alessio., & Debbah, Merouane. (2018). Deep learning power allocation in massive MIMO. In 2018 52nd Asilomar conference on signals, systems, and computers, pages 1257–1261. IEEE.
[23]
Van Chien Trinh, Björnson Emil, and Larsson Erik G Joint power allocation and load balancing optimization for energy-efficient cell-free massive MIMO networks IEEE Transactions on Wireless Communications 2020 19 10 6798-6812
[24]
Björnson Emil, Jorswieck Eduard, and Ottersten Bjorn Impact of spatial correlation and precoding design in OSTBC MIMO systems IEEE Transactions on Wireless Communications 2010 9 11 3578-3589
[25]
Sun Liang and McKay Matthew R Eigen-based transceivers for the MIMO broadcast channel with semi-orthogonal user selection IEEE Transactions on Signal Processing 2010 58 10 5246-5261
[26]
Hanzaz, Zakaria., Schotten, Hans Dieter. (2013). Analysis of effective SINR mapping models for MIMO OFDM in LTE system. pages 1509–1515.
[27]
Mohajer, Amin. (2022). Mahya Sam Daliri, A Mirzaei, A Ziaeddini, M Nabipour, and Maryam Bavaghar. Heterogeneous computational resource allocation for noma: Toward green mobile edge-computing systems. IEEE Transactions on Services Computing.
[28]
Nikjoo Faramarz, Mirzaei Abbas, and Mohajer Amin A novel approach to efficient resource allocation in noma heterogeneous networks: Multi-criteria green resource management Applied Artificial Intelligence 2018 32 7–8 583-612
[29]
Amin Mohajer F, Sorouri A Mirzaei, Ziaeddini A, Jalali Rad K, and Bavaghar Maryam Energy-aware hierarchical resource management and backhaul traffic optimization in heterogeneous cellular networks IEEE Systems Journal 2022 16 4 5188-5199
[30]
Jaeckel Stephan, Raschkowski Leszek, Börner Kai, and Thiele Lars QuaDRiGa: A 3-D multi-cell channel model with time evolution for enabling virtual field trials IEEE Transactions on Antennas and Propagation 2014 62 6 3242-3256
[31]
Aitken Alexander C IV.-On least squares and linear combination of observations Proceedings of the Royal Society of Edinburgh 1936 55 42-48
[32]
Zaidi, Ali., Athley, Fredrik., Medbo, Jonas., Gustavsson, Ulf., Durisi, Giuseppe., & Chen, Xiaoming. (2018). 5G Physical Layer: principles, models and technology components. Academic Press.
[33]
Bobrov, Evgeny., Chinyaev, Boris., Kuznetsov, Viktor., Lu, Hao., Minenkov, Dmitrii., Troshin, Sergey., Yudakov, Daniil., & Zaev, Danila. (2021). Adaptive regularized zero-forcing beamforming in Massive MIMO with multi-antenna users. arXiv preprint arXiv:2107.00853.
[34]
Mahmood, Nurul H., Berardinelli, Gilberto., Tavares, Fernando ML., Lauridsen, Mads., Mogensen, Preben., & Pajukoski, Kari. (2014). An efficient rank adaptation algorithm for cellular MIMO systems with IRC receivers. In 2014 IEEE 79th Vehicular Technology Conference (VTC Spring), pages 1–5. IEEE.
[35]
Bobrov, Evgeny., Markov, Alexander., & Vetrov, Dmitry. (2021). Variational autoencoders for studying the manifold of precoding matrices with high spectral efficiency. arXiv preprint arXiv:2111.15626.
[36]
Joham Michael, Utschick Wolfgang, and Nossek Josef A Linear transmit processing in MIMO communications systems IEEE Transactions on Signal Processing 2005 53 8 2700-2712
[37]
Nguyen Duy HN and Le-Ngoc Tho Mmse precoding for multiuser miso downlink transmission with non-homogeneous user snr conditions EURASIP Journal on Advances in Signal Processing 2014 1–12 2014
[38]
Shi Shuying, Schubert Martin, and Boche Holger Downlink MMSE transceiver optimization for multiuser MIMO systems: Duality and sum-MSE minimization IEEE Transactions on Signal Processing 2007 55 11 5436-5446
[39]
Hesham Mehana A and Nosratinia A Diversity of MMSE MIMO receivers IEEE Transactions on Information Theory 2012 58 11 6788-6805
[40]
Wubben, Dirk., Bohnke, Ronald., Kuhn, Volker., & Kammeyer, K-D. (2004). Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice-reduction. In 2004 IEEE International Conference on Communications (IEEE Cat. No. 04CH37577), volume 2, pages 798–802. IEEE.
[41]
Ren Bin, Wang Yingmin, Sun Shaohui, Zhang Yawen, Dai Xiaoming, and Niu Kai Low-complexity MMSE-IRC algorithm for uplink massive MIMO systems Electronics Letters 2017 53 14 972-974
[42]
Wang Bin, Chang Yongyu, and Yang Dacheng On the SINR in massive MIMO networks with MMSE receivers IEEE Communications Letters 2014 18 11 1979-1982
[43]
Verdú Sergio Spectral efficiency in the wideband regime IEEE Transactions on Information Theory 2002 48 6 1319-1343
[44]
Björnson Emil, Bengtsson Mats, and Ottersten Björn Optimal multiuser transmit beamforming: A difficult problem with a simple solution structure [lecture notes] IEEE Signal Processing Magazine 2014 31 4 142-148
[45]
Lagen, Sandra., Wanuga, Kevin., Elkotby, Hussain., Goyal, Sanjay., Patriciello, Natale., & Giupponi, Lorenza. (2020). New radio physical layer abstraction for system-level simulations of 5G networks. In ICC 2020-2020 IEEE International Conference on Communications (ICC), pages 1–7. IEEE.
[46]
Brueninghaus, Karsten., Astely, David., Salzer, Thomas., Visuri, Samuli., Alexiou, Angeliki., Karger, Stephan., Seraji, G-A. (2005). Link performance models for system level simulations of broadband radio access systems. In 2005 IEEE 16th international symposium on personal, indoor and mobile radio communications, volume 4, pages 2306–2311. IEEE.
[47]
Francis Jobin and Mehta Neelesh B Eesm-based link adaptation in point-to-point and multi-cell ofdm systems: Modeling and analysis IEEE Transactions on Wireless Communications 2014 13 1 407-417
[48]
Bobrov, Evgeny., Kropotov, Dmitry., Troshin, Sergey., & Zaev, Danila. (2021). L-BFGS precoding optimization algorithm for massive MIMO systems with multi-antenna users.
[49]
Bohagen, Frode., Orten, Pål., & Oien, GE. (2005). Construction and capacity analysis of high-rank line-of-sight MIMO channels. In IEEE Wireless Communications and Networking Conference, 2005, volume 1, pages 432–437. IEEE.
[50]
Wei Yu, Rhee Wonjong, Boyd Stephen, and Cioffi John M Iterative water-filling for gaussian vector multiple-access channels IEEE Transactions on Information Theory 2004 50 1 145-152
[51]
Hoydis, Jakob., Cammerer, Sebastian., Aoudia, Fayçal Ait., Vem, Avinash., Binder, Nikolaus., Marcus, Guillermo., & Keller, Alexander. (2022). Sionna: An open-source library for next-generation physical layer research. arXiv preprint arXiv:2203.11854.
[52]
Bobrov, Evgeny., Kropotov, Dmitry., & Lu, Hao. (2021). Massive MIMO adaptive modulation and coding using online deep learning algorithm. IEEE Communications Letters.
[53]
TSG RAN; NR;. Physical layer procedures for data (release 16) v16.0.0. 3GPP TS 38.214, 2019.
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Publication History
Published: 05 July 2023
Accepted: 16 June 2023
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