Mitigation pilot contamination based on matching technique for uplink cell-free massive MIMO systems

Al Ayidh, A., Sambo, Y. and Imran, M. A. (2022) Mitigation pilot contamination based on matching technique for uplink cell-free massive MIMO systems. Scientific Reports, 12, 16893. (doi: 10.1038/s41598-022-21241-0) (PMID:36207432) (PMCID:PMC9546999)

Abstract

In this paper, the cell-free massive multiple input multiple output (MIMO) network is affected by the pilot contamination phenomenon when a large number of users and a small number of available pilots exists, the quality of service (QoS) will deteriorate due to the low accuracy of the channel estimation because some of users will use the same pilot. Therefore, we address this problem by presenting two novel schemes of pilot assignment and pilot power control design based on the matching technique for the uplink of cell-free massive MIMO systems to maximize spectral efficiency. We first formulate an assignment optimization problem in order to find the best possible pilot sequence to be used by utilizing genetic algorithm (GA) and then propose a Hungarian matching algorithm to solve this formulated problem. Regarding the power control design, we formulate a minimum-weighted assignment problem to assign pilot power control coefficients to the estimated channel’s minimum mean-squared error by considering the access point (AP) selection. Then, we also propose the Hungarian algorithm to solve this problem. Simulation results show that our proposed schemes outperform the state-of-the-art techniques concerning both the pilot assignment and the pilot power control design by achieving a 15% improvement in the spectral efficiency. Finally, the computational complexity analysis is provided for the proposed schemes compared with the state-of-the-art techniques.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Sambo, Dr Yusuf and Al Ayidh, Abdulrahman and Imran, Professor Muhammad
• Authors: Al Ayidh, A., Sambo, Y., and Imran, M. A.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: Scientific Reports
• Publisher: Nature Research
• ISSN: 2045-2322
• ISSN (Online): 2045-2322
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Scientific Reports 12: 16893
• Publisher Policy: Reproduced under a Creative Commons License

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
300725		Distributed Autonomous Resilient Emergency Management System (DARE)	Muhammad Imran	Engineering and Physical Sciences Research Council (EPSRC)	EP/P028764/1	ENG - Systems Power & Energy