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Optimized training and basis expansion model parameters for doubly-selective channel estimation
We address the problem of estimating doubly-selective channels using pilot clusters that are time-division multiplexed with the data. The pilot clusters consist of zero-padded pilot symbols in order to decouple channel estimation from data detection. Channel estimation is carried out using the basis...
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Published in: | IEEE transactions on wireless communications 2009-03, Vol.8 (3), p.1490-1498 |
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description | We address the problem of estimating doubly-selective channels using pilot clusters that are time-division multiplexed with the data. The pilot clusters consist of zero-padded pilot symbols in order to decouple channel estimation from data detection. Channel estimation is carried out using the basis expansion model (BEM-)based method, where different BEMs are investigated, and the exact MMSE method which requires full knowledge of the channel statistics. For a fixed number of pilot symbols, we attempt to optimize the power and placement of the pilot symbols at the transmitter side used in transmission, and the number of BEM coefficients used in channel estimation, in the sense of minimizing the total mean-square estimation error (MSE) that includes modelling error. Simulation results confirm that for a wide range of SNR and Doppler spread values, this optimization greatly reduces the MSE and the bit-error rate, and that modelling error, which was ignored in existing work on training design, should be taken into account. The effects of uncertainty in the channel statistics are also studied. |
doi_str_mv | 10.1109/TWC.2009.080364 |
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The pilot clusters consist of zero-padded pilot symbols in order to decouple channel estimation from data detection. Channel estimation is carried out using the basis expansion model (BEM-)based method, where different BEMs are investigated, and the exact MMSE method which requires full knowledge of the channel statistics. For a fixed number of pilot symbols, we attempt to optimize the power and placement of the pilot symbols at the transmitter side used in transmission, and the number of BEM coefficients used in channel estimation, in the sense of minimizing the total mean-square estimation error (MSE) that includes modelling error. Simulation results confirm that for a wide range of SNR and Doppler spread values, this optimization greatly reduces the MSE and the bit-error rate, and that modelling error, which was ignored in existing work on training design, should be taken into account. 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Receivers ; Uncertainty</subject><ispartof>IEEE transactions on wireless communications, 2009-03, Vol.8 (3), p.1490-1498</ispartof><rights>2009 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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The pilot clusters consist of zero-padded pilot symbols in order to decouple channel estimation from data detection. Channel estimation is carried out using the basis expansion model (BEM-)based method, where different BEMs are investigated, and the exact MMSE method which requires full knowledge of the channel statistics. For a fixed number of pilot symbols, we attempt to optimize the power and placement of the pilot symbols at the transmitter side used in transmission, and the number of BEM coefficients used in channel estimation, in the sense of minimizing the total mean-square estimation error (MSE) that includes modelling error. Simulation results confirm that for a wide range of SNR and Doppler spread values, this optimization greatly reduces the MSE and the bit-error rate, and that modelling error, which was ignored in existing work on training design, should be taken into account. The effects of uncertainty in the channel statistics are also studied.</description><subject>Applied sciences</subject><subject>basis-expansion model</subject><subject>Bit error rate</subject><subject>Boundary element method</subject><subject>Channel estimation</subject><subject>Channels</subject><subject>Clusters</subject><subject>Design optimization</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>doubly selective</subject><subject>Error detection</subject><subject>Estimation error</subject><subject>Exact sciences and technology</subject><subject>Finite impulse response filter</subject><subject>Frequency</subject><subject>Information, signal and communications theory</subject><subject>Mathematical models</subject><subject>Multiplexing</subject><subject>Pilots</subject><subject>Radiocommunications</subject><subject>Signal and communications theory</subject><subject>Signal, noise</subject><subject>Statistics</subject><subject>Studies</subject><subject>Symbols</subject><subject>Systems, networks and services of telecommunications</subject><subject>Telecommunications</subject><subject>Telecommunications and information theory</subject><subject>time-varying</subject><subject>Time-varying channels</subject><subject>Transmission and modulation (techniques and equipments)</subject><subject>Transmitters</subject><subject>Transmitters. 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Receivers</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Whitworth, T.</creatorcontrib><creatorcontrib>Ghogho, M.</creatorcontrib><creatorcontrib>McLernon, D.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on wireless communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Whitworth, T.</au><au>Ghogho, M.</au><au>McLernon, D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimized training and basis expansion model parameters for doubly-selective channel estimation</atitle><jtitle>IEEE transactions on wireless communications</jtitle><stitle>TWC</stitle><date>2009-03-01</date><risdate>2009</risdate><volume>8</volume><issue>3</issue><spage>1490</spage><epage>1498</epage><pages>1490-1498</pages><issn>1536-1276</issn><eissn>1558-2248</eissn><coden>ITWCAX</coden><abstract>We address the problem of estimating doubly-selective channels using pilot clusters that are time-division multiplexed with the data. The pilot clusters consist of zero-padded pilot symbols in order to decouple channel estimation from data detection. Channel estimation is carried out using the basis expansion model (BEM-)based method, where different BEMs are investigated, and the exact MMSE method which requires full knowledge of the channel statistics. For a fixed number of pilot symbols, we attempt to optimize the power and placement of the pilot symbols at the transmitter side used in transmission, and the number of BEM coefficients used in channel estimation, in the sense of minimizing the total mean-square estimation error (MSE) that includes modelling error. Simulation results confirm that for a wide range of SNR and Doppler spread values, this optimization greatly reduces the MSE and the bit-error rate, and that modelling error, which was ignored in existing work on training design, should be taken into account. The effects of uncertainty in the channel statistics are also studied.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TWC.2009.080364</doi><tpages>9</tpages></addata></record> |
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subjects | Applied sciences basis-expansion model Bit error rate Boundary element method Channel estimation Channels Clusters Design optimization Detection, estimation, filtering, equalization, prediction doubly selective Error detection Estimation error Exact sciences and technology Finite impulse response filter Frequency Information, signal and communications theory Mathematical models Multiplexing Pilots Radiocommunications Signal and communications theory Signal, noise Statistics Studies Symbols Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory time-varying Time-varying channels Transmission and modulation (techniques and equipments) Transmitters Transmitters. Receivers Uncertainty |
title | Optimized training and basis expansion model parameters for doubly-selective channel estimation |
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