LMS adaptive filter with optimum step-size for tracking time-varying channels
In this paper, an adaptive step-size LMS algorithm for tracking time-varying channels is presented. It is well known that in the case of such channels, the output steady-state mean square error (MSB) is a nonlinear function of the algorithm step-size and so, an optimum step-size that minimize the MS...
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| creator | Bilcu, R.C. Kuosmanen, P. Egiazarian, K. |
| description | In this paper, an adaptive step-size LMS algorithm for tracking time-varying channels is presented. It is well known that in the case of such channels, the output steady-state mean square error (MSB) is a nonlinear function of the algorithm step-size and so, an optimum step-size that minimize the MSE exist. Here we propose an algorithm which adaptively adjust the step-size of the LMS toward its optimum value, such that the steady-state MSE is minimized. The nonlinear relation between the steady-state MSE and the step-size is parametrized such that, during the adaptation, estimates of the optimum step-size are easily obtained. These estimates are obtained independent from the channel statistical parameters, therefore, no prior information about the channel parameters is needed. |
| doi_str_mv | 10.1109/ISPA.2003.1296403 |
| format | Conference Proceeding |
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It is well known that in the case of such channels, the output steady-state mean square error (MSB) is a nonlinear function of the algorithm step-size and so, an optimum step-size that minimize the MSE exist. Here we propose an algorithm which adaptively adjust the step-size of the LMS toward its optimum value, such that the steady-state MSE is minimized. The nonlinear relation between the steady-state MSE and the step-size is parametrized such that, during the adaptation, estimates of the optimum step-size are easily obtained. These estimates are obtained independent from the channel statistical parameters, therefore, no prior information about the channel parameters is needed.</description><identifier>ISBN: 953184061X</identifier><identifier>ISBN: 9789531840613</identifier><identifier>DOI: 10.1109/ISPA.2003.1296403</identifier><language>eng</language><publisher>IEEE</publisher><subject>Adaptive algorithm ; Adaptive filters ; Adaptive signal processing ; Convergence ; Filtering algorithms ; Iterative algorithms ; Least squares approximation ; Signal processing algorithms ; Steady-state ; Time-varying channels</subject><ispartof>3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. 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These estimates are obtained independent from the channel statistical parameters, therefore, no prior information about the channel parameters is needed.</description><subject>Adaptive algorithm</subject><subject>Adaptive filters</subject><subject>Adaptive signal processing</subject><subject>Convergence</subject><subject>Filtering algorithms</subject><subject>Iterative algorithms</subject><subject>Least squares approximation</subject><subject>Signal processing algorithms</subject><subject>Steady-state</subject><subject>Time-varying channels</subject><isbn>953184061X</isbn><isbn>9789531840613</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2003</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotT9tKw0AUXBBBrf0A8WV_IPHsLdl9LMVLIUWhCr6V3eTEriZpyK4V_XpX7LwMZ2YYzhByxSBnDMzNavO0yDmAyBk3hQRxQi6MEkxLKNjrGZmH8A4JwkgDcE7W1XpDbWPH6A9IW99FnOiXjzu6T1L_2dMQccyC_0nufqJxsvWHH95oMjE72On776h3dhiwC5fktLVdwPmRZ-Tl7vZ5-ZBVj_er5aLKPAMVMwd1oYQwrWu5K5V0yKzUumhrNLZgjeJao5altrqEFGk4oHLcWV1b1mgQM3L93-sRcTtOvk-PbI-LxS-YG00b</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Bilcu, R.C.</creator><creator>Kuosmanen, P.</creator><creator>Egiazarian, K.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2003</creationdate><title>LMS adaptive filter with optimum step-size for tracking time-varying channels</title><author>Bilcu, R.C. ; Kuosmanen, P. ; Egiazarian, K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i105t-b0c65339fbf2b754be1a4886fce9a61d5288e8478a870f2bd20e5b2ba8ca1d803</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Adaptive algorithm</topic><topic>Adaptive filters</topic><topic>Adaptive signal processing</topic><topic>Convergence</topic><topic>Filtering algorithms</topic><topic>Iterative algorithms</topic><topic>Least squares approximation</topic><topic>Signal processing algorithms</topic><topic>Steady-state</topic><topic>Time-varying channels</topic><toplevel>online_resources</toplevel><creatorcontrib>Bilcu, R.C.</creatorcontrib><creatorcontrib>Kuosmanen, P.</creatorcontrib><creatorcontrib>Egiazarian, K.</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>Bilcu, R.C.</au><au>Kuosmanen, P.</au><au>Egiazarian, K.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>LMS adaptive filter with optimum step-size for tracking time-varying channels</atitle><btitle>3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the</btitle><stitle>ISPA</stitle><date>2003</date><risdate>2003</risdate><volume>2</volume><spage>883</spage><epage>887 Vol.2</epage><pages>883-887 Vol.2</pages><isbn>953184061X</isbn><isbn>9789531840613</isbn><abstract>In this paper, an adaptive step-size LMS algorithm for tracking time-varying channels is presented. It is well known that in the case of such channels, the output steady-state mean square error (MSB) is a nonlinear function of the algorithm step-size and so, an optimum step-size that minimize the MSE exist. Here we propose an algorithm which adaptively adjust the step-size of the LMS toward its optimum value, such that the steady-state MSE is minimized. The nonlinear relation between the steady-state MSE and the step-size is parametrized such that, during the adaptation, estimates of the optimum step-size are easily obtained. These estimates are obtained independent from the channel statistical parameters, therefore, no prior information about the channel parameters is needed.</abstract><pub>IEEE</pub><doi>10.1109/ISPA.2003.1296403</doi></addata></record> |
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| subjects | Adaptive algorithm Adaptive filters Adaptive signal processing Convergence Filtering algorithms Iterative algorithms Least squares approximation Signal processing algorithms Steady-state Time-varying channels |
| title | LMS adaptive filter with optimum step-size for tracking time-varying channels |
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