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Robust DOA Estimation and Communication Enhancement for RIS-Assisted Systems With Phase Mismatch
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DOI：10.1109/lcomm.2026.3715018.png)
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Abstract
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In RIS-assisted wireless systems, Gaussian-mixture noise and RIS phase mismatch can severely degrade both sensing accuracy and data transmission performance. To address these coupled impairments, this letter proposes a robust sequential sensing-aided communication enhancement framework. In the sensing stage, a multi-stage residual sparse regression (MSRSR) algorithm based on alternating minimization is developed. By incorporating atomic and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-norm regularizations into a Lawson norm fidelity criterion, the resulting subproblems are solved using alternating direction method of multipliers (ADMM) and iterative shrinkage-thresholding algorithm (ISTA), enabling robust suppression of impulsive outliers and accurate recovery of the direction of arrival (DOA) and sparse mismatch matrix. In the subsequent communication stage, a low-complexity greedy coordinate descent (GCD) scheme exploits the estimated environmental priors to optimize 2-bit discrete RIS phase shifts for average achievable sum-rate maximization. Simulations verify that under severe hardware and electromagnetic constraints, the proposed scheme significantly outperforms benchmarks, approaches the reference bound under the considered simulation settings, and substantially enhances multi-node throughput.
Keywords:
Direction of arrival (DOA)
greedy coordinate descent (GCD)
Gaussian-mixture noise
phase mismatch
reconfigurable intelligent surface (RIS)
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