Massive MIMO Pilot Assignment Optimization based on Total Capacity
Jose Carlos Marinello, Cristiano Magalhaes Panazio, Taufik Abrao

TL;DR
This paper addresses pilot assignment in massive MIMO systems, proposing a total capacity metric and a low complexity algorithm to optimize uplink and downlink performance simultaneously, especially with many users.
Contribution
It introduces a novel total capacity metric for pilot assignment and a low complexity suboptimal algorithm to improve massive MIMO performance.
Findings
Proposed method achieves 4.2 Mbps rate with 64 antennas and 10 users.
Method maintains symmetric rates for uplink and downlink.
Performance improves significantly with increased users when combined with power control.
Abstract
We investigate the effects of pilot assignment in multi-cell massive multiple-input multiple-output systems. When deploying a large number of antennas at base station (BS), and linear detection/precoding algorithms, the system performance in both uplink (UL) and downlink (DL) is mainly limited by pilot contamination. This interference is proper of each pilot, and thus system performance can be improved by suitably assigning the pilot sequences to the users within the cell, according to the desired metric. We show in this paper that UL and DL performances constitute conflicting metrics, in such a way that one cannot achieve the best performance in UL and DL with a single pilot assignment configuration. Thus, we propose an alternative metric, namely total capacity, aiming to simultaneously achieve a suitable performance in both links. Since the PA problem is combinatorial, and the search…
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