Semi-blind joint maximum likelihood channel estimation and data detection for MIMO systems
Abuthinien, M., Chen, S. and Hanzo, L. (2008) Semi-blind joint maximum likelihood channel estimation and data detection for MIMO systems. IEEE Signal Processing Letters, 15, 202-205.
Available under License Creative Commons Public Domain Dedication.
Semi-blind joint maximum likelihood (ML) channel estimation and data detection is proposed for multiple-input multiple-output (MIMO) systems. The joint ML optimization over channel and data is decomposed into an iterative two-level optimization loop. An efficient optimization search algorithm referred to as the repeated weighted boosting search (RWBS) is employed at the upper level to identify the unknown MIMO channel while an enhanced ML sphere detector termed as the optimized hierarchy reduced search algorithm is used at the lower level to perform ML detection of the transmitted data. Only a minimum pilot overhead is required to aid the RWBS channel estimator’s initial operation, which not only speeds up convergence but also avoids ambiguities inherent in blind joint estimation of both the channel and data. Index Terms—Channel estimation, data detection, joint maximum likelihood estimation, multiple-input multiple-output.
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||23 Jan 2008 09:42|
|Last Modified:||27 Mar 2014 20:09|
|Further Information:||Google Scholar|
|ISI Citation Count:||15|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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