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Efficient joint maximum-likelihood channel estimation and signal detection
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2006 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 5, no 7, 1838-1845 p.Article in journal (Refereed) Published
Abstract [en]

In wireless communication systems, channel state information is often assumed to be available at the receiver. Traditionally, a training sequence is used to obtain the estimate of the channel. Alternatively, the channel can be identified using known properties of the transmitted signal. However, the computational effort required to find the joint ML solution to the symbol detection and channel estimation problem increases exponentially with the dimension of the problem. To significantly reduce this computational effort, we formulate the joint ML estimation and detection as an integer least-squares problem, and show that for a wide range of signal-to-noise ratios (SNR) and problem dimensions it can be solved via sphere decoding with expected complexity comparable to the complexity of heuristic techniques.

Place, publisher, year, edition, pages
2006. Vol. 5, no 7, 1838-1845 p.
Keyword [en]
integer least-squares problem, sphere decoding, wireless communications, multiple-antenna systems, expected complexity, joint detection and estimation
National Category
Engineering and Technology
URN: urn:nbn:se:uu:diva-155855DOI: 10.1109/TWC.2006.1673095ISI: 000239132300034OAI: oai:DiVA.org:uu-155855DiVA: diva2:430339
Available from: 2011-07-08 Created: 2011-07-01 Last updated: 2011-07-08Bibliographically approved

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