A New Joint TSPA/WGC Pilot Contamination Reduction Strategy Based on Exact Graph Coloring Grouping Algorithm

11Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Massive multiple-input multiple-output (MIMO) system uses a large number of antennas in the base station (BS) serving a set of users in order to increase the spectral efficiency. The pilot-contamination is considered the most remarkable impairment that limits the performance of massive MIMO system. In this paper, two different pilot assignment approaches are jointly proposed to reduce pilot contamination effect. A time-shifted pilot assignment (TSPA) approach is used, where a cellular network is divided into exclusive groups, wherein users in the same group send their uplink-pilots simultaneously, while other users receive their downlink-data. Through the uplink-pilot phase, a heuristic weighted graph coloring-based pilot assignment (WGC-PA) approach is used to reduce intra-group interference caused by pilot contamination. Different uplink-pilots are allocated to the users in the same group having the largest pilot contamination severity (PCS), whereas other users with the smallest PCS share the same uplink-pilots. To divide the cellular network into exclusive groups, we propose a cells grouping technique based on the adjacent distance between cells. This proposed technique uses a backtracking based graph coloring algorithm. It ensures that no two adjacent cells are in the same group in the time-shifted approach. The simulation results show that the proposed joint WGC/TS-PA strategy not only reduces the pilot contamination effect but also reduces computational complexity than the weighted graph coloring approach.

Cite

CITATION STYLE

APA

Shaalan, I. E., Khattaby, A. A., & Dessouki, A. S. (2019). A New Joint TSPA/WGC Pilot Contamination Reduction Strategy Based on Exact Graph Coloring Grouping Algorithm. IEEE Access, 7, 150552–150564. https://doi.org/10.1109/ACCESS.2019.2947665

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free