Abstract
In this paper, the problem of single-channel blind source separation (SCBSS) of a mixture of two co-frequency phase-shift keying (PSK) signals with unknown carrier frequency offsets (CFOs) is investigated. Two SCBSS algorithms which are robust to CFOs are proposed to perform separation of the mixture signals. In the first algorithm, the phase changes of the received signals caused by CFOs are tracked when performing separation of the signals. In the second algorithm, the CFOs are estimated directly before separation by using the cyclostationary feature of the signal, and they are used as known values during the separation of the signals. Simulation results show that both of the two proposed algorithms lead to significant performance improvement as compared with that achieved by using the conventional SCBSS algorithm. When CFOs are small, the phase tracking based algorithm is preferred as it can achieve same performance as that achieved by using the cyclic-feature based algorithm, but with much lower complexity. When CFOs are big, the cyclic-feature based algorithm is a better choice because it can achieve much better performance than that achieved by using the phase tracking based algorithm.
Original language | English |
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Title of host publication | MILCOM 2017 - 2017 IEEE Military Communications Conference |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 641-646 |
Number of pages | 6 |
ISBN (Electronic) | 9781538605950 |
DOIs | |
Publication status | Published - Dec 7 2017 |
Externally published | Yes |
Event | 2017 IEEE Military Communications Conference, MILCOM 2017 - Baltimore, United States Duration: Oct 23 2017 → Oct 25 2017 |
Publication series
Name | Proceedings - IEEE Military Communications Conference MILCOM |
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Volume | 2017-October |
Conference
Conference | 2017 IEEE Military Communications Conference, MILCOM 2017 |
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Country/Territory | United States |
City | Baltimore |
Period | 10/23/17 → 10/25/17 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.
ASJC Scopus Subject Areas
- Electrical and Electronic Engineering