Adaptive antenna subarray formation for MIMO systems

Karamalis, PD; Skentos, ND; Kanatas, AG

dc.contributor.author	Karamalis, PD	en
dc.contributor.author	Skentos, ND	en
dc.contributor.author	Kanatas, AG	en
dc.date.accessioned	2014-03-01T01:23:32Z
dc.date.available	2014-03-01T01:23:32Z
dc.date.issued	2006	en
dc.identifier.issn	1536-1276	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17008
dc.subject	Antenna arrays	en
dc.subject	Antenna subset selection	en
dc.subject	Diversity	en
dc.subject	Genetic algorithms	en
dc.subject	MIMO systems	en
dc.subject	Radio propagation	en
dc.subject	Spatial multiplexing	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.classification	Telecommunications	en
dc.subject.other	Antenna elements	en
dc.subject.other	Antenna subset selection	en
dc.subject.other	Antenna wireless systems	en
dc.subject.other	Spatial multiplexing	en
dc.subject.other	Computational complexity	en
dc.subject.other	Computer hardware	en
dc.subject.other	Cost effectiveness	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Optimization	en
dc.subject.other	Radio transmission	en
dc.subject.other	Wireless telecommunication systems	en
dc.subject.other	Antenna arrays	en
dc.title	Adaptive antenna subarray formation for MIMO systems	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TWC.2006.04532	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TWC.2006.04532	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	MIMO systems with reduced hardware complexity have attracted researchers' attention due to their high efficiency and low cost. Sub-optimum algorithms for antenna subset selection have been intensively studied in the literature. In this paper we present a new technique to maximize the capacity of multiple antenna wireless systems with reduced available RF chains. The technique is based on the adaptive formation of subarrays, i.e. the grouping of antenna elements and the application of appropriate element weights. The elements of each subarray and their weights are dynamically selected by an evolutionary optimization technique using the link capacity as a cost function. © 2006 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Wireless Communications	en
dc.identifier.doi	10.1109/TWC.2006.04532	en
dc.identifier.isi	ISI:000242256600001	en
dc.identifier.volume	5	en
dc.identifier.issue	11	en
dc.identifier.spage	2977	en
dc.identifier.epage	2982	en