Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/84899
Title: Low-complexity single-channel blind separation of co-frequency coded signals
Authors: Liu, Xiaobei
Guan, Yong Liang
Koh, Soo Ngee
Liu, Zilong
Wang, Peng
Keywords: Per-survivor Processing
Single-channel Blind Source Separation
Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Liu, X., Guan, Y. L., Koh, S. N., Liu, Z., & Wang, P. (2018). Low-Complexity Single-Channel Blind Separation of Co-Frequency Coded Signals. IEEE Communications Letters, 22(5), 990-993. doi:10.1109/LCOMM.2018.2805332
Series/Report no.: IEEE Communications Letters
Abstract: Single-channel blind source separation (SCBSS) of uncoordinated, non-spread, co-frequency interfering signals with non-zero carrier frequency offset and timing offset, and without training sequence for channel estimation, is a challenging task. Iterative SCBSS of coded signals leads to good performance but is computationally expensive as it involves the turbo processing of multi-user per-survivor processing and soft-input soft-output channel decoding. In this letter, we propose a low-complexity SCBSS (LC-SCBSS) scheme, which reduces the computational complexity of the conventional iterative SCBSS by using interference-cancellation from the second iteration onward, and adaptive channel truncation for certain users. Simulation results show that the proposed LC-SCBSS reduces the computational complexity by more than 99%, with only a marginal degradation in performance.
URI: https://hdl.handle.net/10356/84899
http://hdl.handle.net/10220/49169
ISSN: 1089-7798
DOI: 10.1109/LCOMM.2018.2805332
Schools: School of Electrical and Electronic Engineering 
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/LCOMM.2018.2805332.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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