Hybrid Atomic Norm Sparse/Diffuse Channel Estimation

Lyu, Lei; Mitra, Urbashi

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https://hdl.handle.net/2142/130306 Copy

Description

Title

Hybrid Atomic Norm Sparse/Diffuse Channel Estimation

Author(s)

• Lyu, Lei
• Mitra, Urbashi

Issue Date

2025-09-17

Keyword(s)

• Channel estimation
• Convex optimization
• Atomic norm
• Source signal separation
• Constrained Cramér-Rao bound

Abstract

In this paper, the hybrid sparse/diffuse (HSD) channel model in frequency domain is proposed. Based on the structural analysis on the resolvable paths and diffuse scattering statistics in the channel, the Hybrid Atomic-Least-Squares (HALS) algorithm is designed to estimate sparse/diffuse components with a combined atomic and l2 regularization. A theoretical analysis is conducted on the Lagrangian dual problem and the conditions needed to be satisfied by primal and dual solutions are provided. This analysis, in turn, suggests an algorithm for optimal frequency support estimation. Debiased methods for improved channel estimation are provided. Given differing amounts of side information, performance bounds are derived in terms of a genie-aided estimator and constrained Cramér-Rao lower bounds (CRLB). Numerical results via simulations on synthetic data as well as real experimental data validate the efficacy of the proposed method. There are clear tradeoffs with respect to the properties of the channel with respect to performance: sparsity of specular paths and relative energy of diffuse components.

Publisher

Allerton Conference on Communication, Control, and Computing

Series/Report Name or Number

2025 61st Allerton Conference on Communication, Control, and Computing Proceedings

ISSN

2836-4503

Type of Resource

Text

Genre of Resource

Conference Paper/Presentation

Language

eng

Handle URL

https://hdl.handle.net/2142/130306&&

Copyright and License Information

Copyright 2025 is held by Lei Lyu and Urbashi Mitra.

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