Blind and semi-blind ML detection for space-time block-coded OFDM wireless systems

Handle URI:
http://hdl.handle.net/10754/346760
Title:
Blind and semi-blind ML detection for space-time block-coded OFDM wireless systems
Authors:
Zaib, Alam; Al-Naffouri, Tareq Y
Abstract:
This paper investigates the joint maximum likelihood (ML) data detection and channel estimation problem for Alamouti space-time block-coded (STBC) orthogonal frequency-division multiplexing (OFDM) wireless systems. The joint ML estimation and data detection is generally considered a hard combinatorial optimization problem. We propose an efficient low-complexity algorithm based on branch-estimate-bound strategy that renders exact joint ML solution. However, the computational complexity of blind algorithm becomes critical at low signal-to-noise ratio (SNR) as the number of OFDM carriers and constellation size are increased especially in multiple-antenna systems. To overcome this problem, a semi-blind algorithm based on a new framework for reducing the complexity is proposed by relying on subcarrier reordering and decoding the carriers with different levels of confidence using a suitable reliability criterion. In addition, it is shown that by utilizing the inherent structure of Alamouti coding, the estimation performance improvement or the complexity reduction can be achieved. The proposed algorithms can reliably track the wireless Rayleigh fading channel without requiring any channel statistics. Simulation results presented against the perfect coherent detection demonstrate the effectiveness of blind and semi-blind algorithms over frequency-selective channels with different fading characteristics.
KAUST Department:
Electrical Engineering Program
Citation:
Blind and semi-blind ML detection for space-time block-coded OFDM wireless systems 2014, 2014 (1):131 EURASIP Journal on Advances in Signal Processing
Publisher:
Springer Nature
Journal:
EURASIP Journal on Advances in Signal Processing
Issue Date:
2014
DOI:
10.1186/1687-6180-2014-131
Type:
Article
ISSN:
1687-6180
Additional Links:
http://asp.eurasipjournals.com/content/2014/1/131
Appears in Collections:
Articles; Electrical Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorZaib, Alamen
dc.contributor.authorAl-Naffouri, Tareq Yen
dc.date.accessioned2015-03-17T13:14:27Zen
dc.date.available2015-03-17T13:14:27Zen
dc.date.issued2014en
dc.identifier.citationBlind and semi-blind ML detection for space-time block-coded OFDM wireless systems 2014, 2014 (1):131 EURASIP Journal on Advances in Signal Processingen
dc.identifier.issn1687-6180en
dc.identifier.doi10.1186/1687-6180-2014-131en
dc.identifier.urihttp://hdl.handle.net/10754/346760en
dc.description.abstractThis paper investigates the joint maximum likelihood (ML) data detection and channel estimation problem for Alamouti space-time block-coded (STBC) orthogonal frequency-division multiplexing (OFDM) wireless systems. The joint ML estimation and data detection is generally considered a hard combinatorial optimization problem. We propose an efficient low-complexity algorithm based on branch-estimate-bound strategy that renders exact joint ML solution. However, the computational complexity of blind algorithm becomes critical at low signal-to-noise ratio (SNR) as the number of OFDM carriers and constellation size are increased especially in multiple-antenna systems. To overcome this problem, a semi-blind algorithm based on a new framework for reducing the complexity is proposed by relying on subcarrier reordering and decoding the carriers with different levels of confidence using a suitable reliability criterion. In addition, it is shown that by utilizing the inherent structure of Alamouti coding, the estimation performance improvement or the complexity reduction can be achieved. The proposed algorithms can reliably track the wireless Rayleigh fading channel without requiring any channel statistics. Simulation results presented against the perfect coherent detection demonstrate the effectiveness of blind and semi-blind algorithms over frequency-selective channels with different fading characteristics.en
dc.publisherSpringer Natureen
dc.relation.urlhttp://asp.eurasipjournals.com/content/2014/1/131en
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.en
dc.titleBlind and semi-blind ML detection for space-time block-coded OFDM wireless systemsen
dc.typeArticleen
dc.contributor.departmentElectrical Engineering Programen
dc.identifier.journalEURASIP Journal on Advances in Signal Processingen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionDepartment of Electrical Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabiaen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorAl-Naffouri, Tareq Y.en
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