Exploiting Spatial and Temporal Correlations in Massive MIMO Systems Operating Over Non-Stationary Aging Channels
Sajad Daei, Gabor Fodor, Mikael Skoglund

TL;DR
This paper presents a real-time beamforming framework for massive MIMO systems that mitigates spatial correlation and channel aging effects, improving spectral efficiency in non-stationary environments.
Contribution
It introduces a novel channel estimation scheme considering mobility and antenna spacing, and derives an expression for optimizing spectral efficiency in massive MIMO systems.
Findings
Optimal pilot spacing is unaffected by large-scale channel parameters.
Increasing transmit antennas reduces interference impact.
Proposed method outperforms prior approaches in simulations.
Abstract
This work investigates a multi-user, multi-antenna uplink wireless system, in which multiple users transmit signals to a base station. Prior research has explored the potential for linear growth in spectral efficiency by employing multiple transmit and receive antennas. This gain depends heavily on the quality of channel state information and the number of uncorrelated antennas. However, spatial correlations, arising from closely-spaced antennas and channel aging effects -- stemming from the difference between the channel state at pilot and data time instances -- can substantially counteract these benefits, and degrade the transmission rate, especially in non-stationary environments. To address these challenges, this work introduces a real-time beamforming framework to compensate for the spatial correlation and channel aging effects. First, a channel estimation scheme leveraging…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Millimeter-Wave Propagation and Modeling · Molecular Communication and Nanonetworks
MethodsBalanced Selection
