Location-Aware Channel Estimation Enhanced TDD Based Massive MIMO

Abstract

Pilot contamination (PC) is a stumbling block in theway of realizing massive multi-input multi-output (MIMO) systems. This contribution proposes a location-aware channel estimation-enhanced massive MIMO system employing time-division duplexing protocol, which is capable of significantly reducing the inter-cell interference caused by PC and, therefore, improving the achievable system performance. Specifically, we present a novel location-aware channel estimation algorithm, which utilizes the property of the steering vector to carry out a fast Fourier transform-based post-processing after the conventional pilot-aided channel estimation for mitigating PC. Our asymptotic analysis proves that this post-processing is capable of removing PC from the interfering users with different angle-of-arrivals (AOAs). Since in practice the AOAs of some users may be similar, we further present a location-aware pilot assignment method to ensure that users utilizing the same pilot have distinguishable AOAs, in order to fully benefit from the location-aware channel estimation. Simulation results demonstrate that the proposed scheme can dramatically reduce the inter-cell interference caused by the re-use of the pilot sequence and improve the overall system performance significantly, while only imposing a modest extra computational cost, in comparison with the conventional pilot-aided channel estimation.

Keywords

• Massive multi-input multi-output
• time-division duplexing
• pilot contamination
• inter-cell interference
• location-aware channel estimation
• pilot assignment