Abstract
In this paper, we investigate the selection problem of access points (APs) in cell-free massive multiple-input multiple-output (MIMO) systems, where APs equipped with a large number of antennas are geographically distributed over a wide area with no cell border. These APs simultaneously serve many users, which are randomly distributed all over the area. We first derive formulas to calculate two proposed metrics used to measure the effective channel gain from all users to all APs and the channel quality of each user. Moreover, these metrics are only based on large-scale fading coefficients, which change very slowly in time. Next, we propose an algorithm to effectively sort and connect users to each AP in a sequential manner using these proposed metrics. Simulation results show that cell-free massive MIMO systems using proposed scheme have better performance compared to existing schemes.
Highlights
Massive multiple-input multiple-output (MIMO) systems where a large number of antennas are equipped on the base stations (BSs) or access points (APs) to simultaneously serve many users in the same frequency resource, is an emerging technology for 5G wireless communication systems and future wireless networks [1], [2]
We focus on AP-user selection problem in a cell-free massive MIMO system
In cell-free massive MIMO research, full connection is commonly assumed between users and APs
Summary
Massive multiple-input multiple-output (MIMO) systems where a large number of antennas are equipped on the base stations (BSs) or access points (APs) to simultaneously serve many users in the same frequency resource, is an emerging technology for 5G wireless communication systems and future wireless networks [1], [2]. The authors of [8] compared cell-free massive MIMO with small cell systems They focused on maxmin power control to provide uniformly good service for every user and pilot assignment with the assumption that all users are served by all APs at the same time. In [10], the authors proposed an energy efficiency maximization scheme using power allocation and user-AP selection They showed that a fully connected user-AP is not optimal. In [12], the authors investigated the energy efficiency in downlink transmission by optimizing power allocation, user-AP association, and antenna activation on each AP in a combinational manner This algorithm had very high computational complexity since they combined three challenging problems in cell-free massive MIMO into a mixed integer nonlinear problem.
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