Sequential Multiuser Scheduling and Power Allocation for Clustered Cell-Free Massive MIMO Networks

European Signal Processing Conference (EUSIPCO), pp. 1484–1488

Abstract

Resource allocation is a fundamental task in cell- free (CF) massive multi-input multi-output (MIMO) systems, which can effectively improve the network performance. In this paper, we study the downlink of CF MIMO networks with network clustering and linear precoding, and develop a sequential multiuser scheduling and power allocation scheme. In particular, we present a multiuser scheduling algorithm based on greedy techniques and a gradient ascent (GA) power allocation algorithm for sum-rate maximization when imperfect channel state information (CSI) is considered. Numerical results show the superiority of the proposed sequential scheduling and power allocation scheme and algorithms to existing approaches while reducing the computational complexity and the signaling load.

Authors 4

1. Saeed Mashdour

   Pontifícia Universidade Católica do Rio de Janeiro

   Affiliation as printed

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

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

2. 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,Brazil

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

   Department of Electronic Engineering, University of York, United Kingdom

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

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Information Theory and Data Analytics,Aachen,Germany,52062

4. João P. S. H. Lima

   Centre for Research and Development in Telecommunications (Brazil)

   Affiliation as printed

   CPQD,Campinas,Brazil

   CPQD, Campinas, Brazil