@inproceedings{14191bb9c88f44999babdfab7e1de54f,
title = "CS-PSO algorithm for off-grid narrow-band interference mitigation in OFDM systems",
abstract = "In this paper, we propose a novel approach to recover off-grid narrow-band-interference (NBI) in orthogonal-frequency-division-multiplexing (OFDM) systems using a compressive-sensing (CS) framework. NBI degrades the performance of OFDM systems which motivates the need for mitigation techniques to reduce its effect. NBI is a sparse signal in the frequency-domain (FD). However, frequency-grid mismatch destroys the sparsity of NBI in the FD. Therefore, the received off-grid NBI is characterized by a nonlinear model which is parametrized by two vectors; the first vector represents the frequency-grid-mismatch and the second vector represents the FD sparse NBI. A CS-based particle-swarm-optimization (CS-PSO) evolutionary algorithm is proposed based on a weighted sum of ℓ0 and ℓ2 norms fitness function to jointly recover the support of the FD sparse vector and the frequenc ygrid- mismatch vector. Simulation results demonstrate the merits of the proposed approach.",
keywords = "Compressive sensing, OFDM, Off-grid NBI, PSO, ℓ norm",
author = "Hanan Al-Tous and Imad Barhumi and Abdulrahman Kalbat and Naofal Al-Dhahir",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Wireless Communications and Networking Conference, WCNC 2017 ; Conference date: 19-03-2017 Through 22-03-2017",
year = "2017",
month = may,
day = "10",
doi = "10.1109/WCNC.2017.7925684",
language = "English",
series = "IEEE Wireless Communications and Networking Conference, WCNC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2017 IEEE Wireless Communications and Networking Conference, WCNC 2017 - Proceedings",
}