Machine Learning-Based AP Selection in User-Centric Cell-free Multiple-Antenna Networks

arXiv (Cornell University)

Abstract

User-centric cell-free (UCCF) massive multiple-input multiple-output (MIMO) systems are considered a viable solution to realize the advantages offered by cell-free (CF) networks, including reduced interference and consistent quality of service while maintaining manageable complexity. In this paper, we propose novel learning-based access point (AP) selection schemes tailored for UCCF massive MIMO systems. The learning model exploits the dataset generated from two distinct AP selection schemes, based on large-scale fading (LSF) coefficients and the sum-rate coefficients, respectively. The proposed learning-based AP selection schemes could be implemented centralized or distributed, with the aim of performing AP selection efficiently. We evaluate our model's performance against CF and two heuristic clustering schemes for UCCF networks. The results demonstrate that the learning-based approach achieves a comparable sum-rate performance to that of competing techniques for UCCF networks, while significantly reducing computational complexity.

Authors 7

1. Shirin Salehi Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics (INDA) , RWTH Aachen University , Aachen , Germany

2. S. Mashdour

   Pontifícia Universidade Católica do Rio de Janeiro

   Affiliation as printed

   Centre for Telecommunications Studies , Pontifical Catholic University of Rio de Janeiro , Rio de Janeiro 22541-041 , Brazil

3. Orhun Tamyigit Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics (INDA) , RWTH Aachen University , Aachen , Germany

4. Sadra Seyedmasoumian Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics (INDA) , RWTH Aachen University , Aachen , Germany

5. Majid Moradikia

   Worcester Polytechnic Institute

   Affiliation as printed

   Department of Data Science , Worcester Polytechnic Institute (WPI) , 100 Institute Road , Worcester , MA , 01609-2280 , USA

6. Rodrigo C. de Lamare

   Pontifícia Universidade Católica do Rio de Janeiro · University of York

   Affiliation as printed

   Centre for Telecommunications Studies , Pontifical Catholic University of Rio de Janeiro , Rio de Janeiro 22541-041 , Brazil

   School of Physics, Engineering and Technology , University of York , United Kingdom

7. Anke Schmeink Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics (INDA) , RWTH Aachen University , Aachen , Germany