Problem
Research questions and friction points this paper is trying to address.
massive MIMO
phase noise
information aging
pilot-based estimation
receiver performance
Information aging in massive MIMO systems affected by phase noise
🤖 AI Summary
In 5G massive MIMO uplink systems, phase noise information obtained via pilot-aided estimation deteriorates over time due to aging effects, significantly degrading the performance of conventional receivers. This work systematically quantifies this aging phenomenon for the first time and proposes an iterative receiver based on the expectation–maximization (EM) algorithm that jointly estimates the channel and phase noise. By iteratively refining these estimates, the proposed method effectively mitigates the adverse impact of information aging. Extensive simulations under realistic scenarios demonstrate that the receiver exhibits strong robustness and achieves substantially superior performance compared to existing schemes.
📝 Abstract
In massive MIMO systems, phase noise can spoil the performance of the usual receiver techniques. The problem arises because of the aging of phase-noise information based on pilots. In this paper, in a realistic 5G uplink scenario, we quantify the impact of information aging and we propose an iterative receiver based on expectation-maximization (EM). Simulation results show that the iterative receiver is robust to information aging related to phase noise.
Innovation
Methods, ideas, or system contributions that make the work stand out.
massive MIMO
phase noise
information aging
expectation-maximization (EM)
iterative receiver
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