Distributed Receivers for Extra-Large Scale MIMO Arrays: A Message Passing Approach

We study the design of receivers in extra-large scale MIMO (XL-MIMO) systems, i.e. systems in which the base station is equipped with an antenna array of extremely large dimensions. While XL-MIMO can significantly increase the system's spectral efficiency, they present two important challenges. One is the increased computational cost of the multi-antenna processing. The second is the variations of user energy distribution over the antenna elements and therefore spatial non-stationarities in these energy distributions. Such non-stationarities limit the performance of the system. In this paper, we propose a distributed receiver for such an XL-MIMO system that can address both challenges. Based on variational message passing (VMP), We propose a set of receiver options providing a range of complexity-performance characteristics to adapt to different requirements. Furthermore, we distribute the processing into local processing units (LPU), that can perform most of the complex processing in parallel, before sharing their outcome with a central processing unit (CPU). Our designs are specifically tailored to exploit the spatial non-stationarities and require lower computations than linear receivers such as zero-forcing. Our simulation study, performed with a channel model accounting for the special characteristics of XL-MIMO channels, confirms the superior performance of our proposals compared to the state of the art methods.

[1]  Fredrik Rusek,et al.  Fully Decentralized Approximate Zero-Forcing Precoding for Massive MIMO Systems , 2019, IEEE Wireless Communications Letters.

[2]  Caijun Zhong,et al.  One-Bit Quantized Massive MIMO Detection Based on Variational Approximate Message Passing , 2018, IEEE Transactions on Signal Processing.

[3]  Tim Brown,et al.  Practical guide to the MIMO radio channel with MATLAB examples , 2012 .

[4]  B. Sundar Rajan,et al.  Low-Complexity Detection in Large-Dimension MIMO-ISI Channels Using Graphical Models , 2011, IEEE Journal of Selected Topics in Signal Processing.

[5]  Elisabeth de Carvalho,et al.  Deep Learning Based Spatial User Mapping on Extra Large MIMO Arrays , 2020 .

[6]  Fredrik Rusek,et al.  Beyond Massive MIMO: The Potential of Data Transmission With Large Intelligent Surfaces , 2017, IEEE Transactions on Signal Processing.

[7]  Robert W. Heath,et al.  Non-Stationarities in Extra-Large-Scale Massive MIMO , 2019, IEEE Wireless Communications.

[8]  Cyril Leung,et al.  Matched filter bound for OFDM on Rayleigh fading channels , 1995 .

[9]  Robert W. Heath,et al.  Linear Receivers in Non-Stationary Massive MIMO Channels With Visibility Regions , 2018, IEEE Wireless Communications Letters.

[10]  Elisabeth de Carvalho,et al.  A Message Passing Based Receiver for Extra-Large Scale MIMO , 2019, 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

[11]  Liang Liu,et al.  Decentralized Massive MIMO Processing Exploring Daisy-Chain Architecture and Recursive Algorithms , 2019, IEEE Transactions on Signal Processing.

[12]  Michail Matthaiou,et al.  On the Uplink Transmission of Multi-user Extra-large Scale Massive MIMO Systems , 2019, ArXiv.

[13]  Emil Björnson,et al.  Capacity Analysis for Spatially Non-Wide Sense Stationary Uplink Massive MIMO Systems , 2015, IEEE Transactions on Wireless Communications.

[14]  Harald Haas,et al.  Asilomar Conference on Signals, Systems, and Computers , 2006 .

[15]  Zhongfeng Wang,et al.  Low Complexity Message Passing Detection Algorithm for Large-Scale MIMO Systems , 2018, IEEE Wireless Communications Letters.

[16]  Helmut Bölcskei,et al.  Outdoor MIMO wireless channels: models and performance prediction , 2002, IEEE Trans. Commun..

[17]  Shi Jin,et al.  Expectation Propagation Detector for Extra-Large Scale Massive MIMO , 2019, IEEE Transactions on Wireless Communications.

[18]  Christopher M. Bishop,et al.  Pattern Recognition and Machine Learning (Information Science and Statistics) , 2006 .

[19]  Emil Björnson,et al.  Ubiquitous cell-free Massive MIMO communications , 2018, EURASIP Journal on Wireless Communications and Networking.

[20]  Emil Björnson,et al.  Making Cell-Free Massive MIMO Competitive With MMSE Processing and Centralized Implementation , 2019, IEEE Transactions on Wireless Communications.

[21]  Hien Quoc Ngo,et al.  Energy Efficiency in Cell-Free Massive MIMO with Zero-Forcing Precoding Design , 2017, IEEE Communications Letters.

[22]  Emil Björnson,et al.  Massive MIMO is a Reality - What is Next? Five Promising Research Directions for Antenna Arrays , 2019, ArXiv.

[23]  Taufik Abrão,et al.  Low-Complexity Distributed XL-MIMO for Multiuser Detection , 2020, 2020 IEEE International Conference on Communications Workshops (ICC Workshops).

[24]  Hien Quoc Ngo,et al.  Cell-Free Massive MIMO for Wireless Federated Learning , 2019, IEEE Transactions on Wireless Communications.

[25]  Emil Björnson,et al.  Optimal Design of Energy-Efficient Multi-User MIMO Systems: Is Massive MIMO the Answer? , 2014, IEEE Transactions on Wireless Communications.

[26]  Robert W. Heath,et al.  Extremely Large Aperture Massive MIMO: Low Complexity Receiver Architectures , 2018, 2018 IEEE Globecom Workshops (GC Wkshps).