Optimal sequential channel estimation for multi-channel cognitive radio
In this paper, we consider how to quickly obtain accurate channel gain estimates for multi-channel cognitive radio systems. A sequential setup, in which the cognitive users estimate available channels one by one, is considered. In addition, the channel estimation for each channel is also sequential....
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description | In this paper, we consider how to quickly obtain accurate channel gain estimates for multi-channel cognitive radio systems. A sequential setup, in which the cognitive users estimate available channels one by one, is considered. In addition, the channel estimation for each channel is also sequential. In particular, cognitive users will determine whether to finish the estimation process of the current channel and switch to next channel for estimation based on the training symbols received so far. To balance the tradeoff between the estimation error and time spent on the channel estimation, we aim to design a switch function and an estimator that minimize a linear combination of these two factors. We obtain the optimal solution for the general case. Numerical results are provided to show the substantial gain of our solution over that of uniformly allocating training time to each channel. |
doi_str_mv | 10.1109/CISS.2012.6310850 |
format | Conference Proceeding |
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A sequential setup, in which the cognitive users estimate available channels one by one, is considered. In addition, the channel estimation for each channel is also sequential. In particular, cognitive users will determine whether to finish the estimation process of the current channel and switch to next channel for estimation based on the training symbols received so far. To balance the tradeoff between the estimation error and time spent on the channel estimation, we aim to design a switch function and an estimator that minimize a linear combination of these two factors. We obtain the optimal solution for the general case. 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A sequential setup, in which the cognitive users estimate available channels one by one, is considered. In addition, the channel estimation for each channel is also sequential. In particular, cognitive users will determine whether to finish the estimation process of the current channel and switch to next channel for estimation based on the training symbols received so far. To balance the tradeoff between the estimation error and time spent on the channel estimation, we aim to design a switch function and an estimator that minimize a linear combination of these two factors. We obtain the optimal solution for the general case. Numerical results are provided to show the substantial gain of our solution over that of uniformly allocating training time to each channel.</description><subject>Bayesian estimation</subject><subject>Channel estimation</subject><subject>cognitive radio</subject><subject>Integrated circuits</subject><subject>sequential analysis</subject><subject>Signal to noise ratio</subject><subject>spectrum sharing</subject><isbn>9781467331395</isbn><isbn>1467331392</isbn><isbn>1467331384</isbn><isbn>9781467331401</isbn><isbn>1467331406</isbn><isbn>9781467331388</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1j8FOwzAQRI0QElDyAYhLfiDBm41j-4giKJUq9dDeK8det0ZpUhIXib8nqO1edkZvNZpl7Bl4DsD1a71Yr_OCQ5FXCFwJfsMeoawkIqAqb1mipbp6Le5ZMo5ffBoFquT6gc1XxxgOpk1H-j5RF8Mk7d50HbUpjf8ohr5LfT-kh1MbQ3aFtt91IYYfSgfjQv_E7rxpR0oue8Y2H--b-jNbruaL-m2ZBc1jZomEtM41HiqBGtEa66RtiMA4Bw0qclNhz9EqqJx1ChpopCg8yenU44y9nGMDEW2Pw9Rv-N1eXsc_7-1Pfg</recordid><startdate>201203</startdate><enddate>201203</enddate><creator>Caromi, R.</creator><creator>Lifeng Lai</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201203</creationdate><title>Optimal sequential channel estimation for multi-channel cognitive radio</title><author>Caromi, R. ; Lifeng Lai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-cee57cddbf1653933cacd7cbee1add1b38ed978f03c816dcd81b1b752fe7cacf3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Bayesian estimation</topic><topic>Channel estimation</topic><topic>cognitive radio</topic><topic>Integrated circuits</topic><topic>sequential analysis</topic><topic>Signal to noise ratio</topic><topic>spectrum sharing</topic><toplevel>online_resources</toplevel><creatorcontrib>Caromi, R.</creatorcontrib><creatorcontrib>Lifeng Lai</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Caromi, R.</au><au>Lifeng Lai</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Optimal sequential channel estimation for multi-channel cognitive radio</atitle><btitle>2012 46th Annual Conference on Information Sciences and Systems (CISS)</btitle><stitle>CISS</stitle><date>2012-03</date><risdate>2012</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><isbn>9781467331395</isbn><isbn>1467331392</isbn><eisbn>1467331384</eisbn><eisbn>9781467331401</eisbn><eisbn>1467331406</eisbn><eisbn>9781467331388</eisbn><abstract>In this paper, we consider how to quickly obtain accurate channel gain estimates for multi-channel cognitive radio systems. A sequential setup, in which the cognitive users estimate available channels one by one, is considered. In addition, the channel estimation for each channel is also sequential. In particular, cognitive users will determine whether to finish the estimation process of the current channel and switch to next channel for estimation based on the training symbols received so far. To balance the tradeoff between the estimation error and time spent on the channel estimation, we aim to design a switch function and an estimator that minimize a linear combination of these two factors. We obtain the optimal solution for the general case. Numerical results are provided to show the substantial gain of our solution over that of uniformly allocating training time to each channel.</abstract><pub>IEEE</pub><doi>10.1109/CISS.2012.6310850</doi><tpages>6</tpages></addata></record> |
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subjects | Bayesian estimation Channel estimation cognitive radio Integrated circuits sequential analysis Signal to noise ratio spectrum sharing |
title | Optimal sequential channel estimation for multi-channel cognitive radio |
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