Work

Sparse Channel Estimation in Wideband Systems With Geometric Sequence Decomposition

Year: 2021

Type: article

Abstract: The sparsity of multipaths in the wideband channel has motivated the use of compressed sensing for channel estimation. In this letter, we propose a different approach to sparse channel estimation. We exploit the fact that${L}$taps of channel impulse response in time domain constitute a non-orthogonal superposition of${L}$geometric sequences in frequency domain. This converts the channel estimation problem into the extraction of the parameters of geometric sequences. Numerical results show that the proposed scheme is superior to existing algorithms in high signal-to-noise ratio (SNR) and large bandwidth conditions.

Source: IEEE Wireless Communications Letters

DOI: 10.1109/lwc.2021.3123314

Authors: Woong-Hee Lee, Ki Won Sung

Institutions: Korea University, KTH Royal Institute of Technology

Language: English

Topic: Sparse and Compressive Sensing Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: European Commission, National Research Foundation of Korea

Awards: G1117567001, Virtual Presence in Moving Objects through 5G