Performance Analysis of Downlink Linear Precoding for Multi-Cell Massive MIMO under Correlated Rayleigh Fading Channels
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Date
2022-09
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Addis Ababa University
Abstract
The Fifth Generation (5G) networks have performance targets of high Spectral Efficiency
(SE), decreased latency, energy savings, cost reduction, high system capacity, and huge
device connections. To increase the SE of networks, researchers deal with increasing the
transmit power, obtaining the array gain, using Space Division Multiple Access (SDMA),
and deploying massive numbers of antennas at the Base Station (BS). A Multi User-
Multiple Input Multiple Output (MU-MIMO) technology that combines SDMA with
Time Division Duplex (TDD) to limit the Channel State Information (CSI) acquisition
overhead and a massive number of antennas at the BS is known as Massive-Multiple Input
Multiple Output (M-MIMO). For efficient use of massive antennas at the BS, the channel
characteristics between User Equipments (UEs) and the BS must be known. Practical
channels are known to be spatially correlated due to sampling at the BS, environmental
orientations, and polarization effects. Estimation of spatially correlated channels in a
multi-cell M-MIMO system degrades due to reuse of pilot signals among UEs, which
cannot be addressed by increasing the number of BS antennas.
Alleviating the impact of pilot contamination in multi-cell cellular systems is conducted in
various research. However, describing pilot contamination effects based on UEs position
on the channel estimation is not addressed in most of the researches.
In this research, the effect of UEs position on channel estimation and the ability to get
favourable channels is investigated under correlated Rayleigh fading channels. Using blind
estimation of precoded channels, the performance of different linear precoding schemes is
examined using MATLAB simulation platform.
The pilot contamination effect is negligible under more correlated channels if the angle of
arrival (position of UEs) is slightly different. The Minimum Mean Square Error (MMSE)
precoding schemes have better performance than Regularized Zero Forcing (RZF), Zero
Forcing (ZF), and Maximum Ratio Transmission (MRT). RZF has better performance
than ZF when the effective Signal to Noise Ratio (SNR) is low or the number of antennas
at the BS is small, unless they have the same level of performance.
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Keywords
Spectral Efficiency, Massive MIMO, Pilot Contamination, Linear Precoding, MMSE, RZF, ZF, MRT