Mitigating Pilot Contamination and Enabling IoT Scalability in Massive MIMO Systems

TL;DR

This work tackles pilot contamination and IoT scalability in massive MIMO for 5G by proposing a cluster-based pilot allocation scheme. It clusters IoT devices using a modified KFaster Medoid algorithm based on spatial covariance, assigns orthogonal pilots to clusters, and mitigates inter-cell contamination via a max-$K$-cut graph partitioning approach. The combined clustering-graph framework yields improved spectral efficiency and scalability, demonstrated by simulations showing stable SE with large device counts and manageable omission rates. The approach promises practical pilot-resource savings and enhanced performance for dense IoT deployments in multi-cell Massive MIMO systems.

Abstract

Massive MIMO is expected to play an important role in the development of 5G networks. This paper addresses the issue of pilot contamination and scalability in massive MIMO systems. The current practice of reusing orthogonal pilot sequences in adjacent cells leads to difficulty in differentiating incoming inter- and intra-cell pilot sequences. One possible solution is to increase the number of orthogonal pilot sequences, which results in dedicating more space of coherence block to pilot transmission than data transmission. This, in turn, also hinders the scalability of massive MIMO systems, particularly in accommodating a large number of IoT devices within a cell. To overcome these challenges, this paper devises an innovative pilot allocation scheme based on the data transfer patterns of IoT devices. The scheme assigns orthogonal pilot sequences to clusters of devices instead of individual devices, allowing multiple devices to utilize the same pilot for periodically transmitting data. Moreover, we formulate the pilot assignment problem as a graph coloring problem and use the max k-cut graph partitioning approach to overcome the pilot contamination in a multicell massive MIMO system. The proposed scheme significantly improves the spectral efficiency and enables the scalability of massive MIMO systems; for instance, by using ten orthogonal pilot sequences, we are able to accommodate 200 devices with only a 12.5% omission rate.

Figures (4)

• Figure 1: Required and interference signals of $i_{th}$ and $j_{th}$ cells
• Figure 2: Comparison of clustered devices with and without uniform distribution
• Figure 3: Impact of increasing devices in a cell over omitted devices
• Figure 4: Impact of average SE by increasing users with fixed coherence block