Journal of Telecommunication, Switching Systems and Networks

Interference Effect Analysis of Pilot Contaminated Massive MIMO Downlink with Different Pre-coders and Channel Estimation

  1. Sabikun Nahar Jeferine
  2. Md. Abu Bakar Siddiqui

Abstract

A new idea in cellular MU-MIMO is the use of large numbers of BS antennas to serve several single-antenna terminals simultaneously. In multi-cell environments, adjacent cells using the same spectrum cause a pilot contamination problem and degrade signal quality. This pilot overhead can be reduced by reusing pilot sequences in nearby cells; however, this potentially introduces interference in the channel estimation phase, the so-called "pilot contamination" effect. The achievable rate equations for both uplink (UL) and downlink (DL) systems of pilot contaminated massive MIMO system using different pre-coders are available in different studies. But the rate of interference using those pre-coders is nowhere analyzed.  Not even the comparison study has been studied till now showing the best suitable pre-coder with least interference. In this paper, we studied the interference detection of a practical massive MIMO system under the effect of pilot contamination and derived equations for the approximate achievable rate of the interference caused by pilot contamination, considering maximum ratio combining (MRC), zero forcing (ZF) and minimum mean square error (MMSE) pre-coding techniques. The numerical and simulation results at the end of the paper verifies the rate expressions and also makes a comparison among their rates of interference caused by pilot contamination of the massive MIMO system using the MRC, ZF and MMSE pre-coders. Keywords: Massive MIMO, Downlink achievable rate, Pilot contamination, Co-channel Interference, Channel estimation, Imperfect CSICite this Article Sabikun Nahar Jeferine, Md. Abu Bakar Siddiqui. Interference Effect Analysis of Pilot Contaminated Massive MIMO Downlink with Different Pre-coders and Channel Estimation. Journal of Telecommunication, Switching Systems and Networks. 2017; 4(2): 1–9p.

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