@article{komninakis_adaptive_2000,
 abstract = {This paper addresses the problem of adaptive channel tracking and equalization for multi-input multi-output (MIMO) time-variant frequency-selective channels. A finite-length minimum-mean-squared-error decision-feedback equalizer (MMSE-DFE) performs the equalization task, while a Kalman filter tracks the MIMO channel, which models the corrupting effects of inter-symbol interference (ISI), inter-user interference (IUI), and noise. The Kalman tracking is aided by previous hard decisions produced by the DFE, with a decision delay \>0, which causes the Kalman filter to track the channel with a delay. A channel prediction module bridges the time gap between the channel estimates produced by the Kalman filter and those needed for the DFE adaptation. The proposed algorithm offers good tracking behavior for multi-user fading ISI channels at the expense of higher complexity.},
 type={4},
 author = {Komninakis, C. and Fragouli, C. and Sayed, A. H. and Wesel, R. D.},
 journal = {ICC 2000, New Orleans, Louisiana, June 18-22},
 pages = {pages 1655--1659},
 tags = {wireless},
 title = {Adaptive {Multi}-{Input} {Multi}-{Output} {Fading} {Channel} {Equalization} using {Kalman} {Estimation}},
 volume = {vol. 3},
 year = {2000}
}

{"_id":"xQPaAJAhTmdn5cdNn","bibbaseid":"komninakis-fragouli-sayed-wesel-adaptivemultiinputmultioutputfadingchannelequalizationusingkalmanestimation-2000","authorIDs":["BovhRrwbYouQ7xD9S"],"author_short":["Komninakis, C.","Fragouli, C.","Sayed, A. H.","Wesel, R. D."],"bibdata":{"bibtype":"article","type":"4","abstract":"This paper addresses the problem of adaptive channel tracking and equalization for multi-input multi-output (MIMO) time-variant frequency-selective channels. A finite-length minimum-mean-squared-error decision-feedback equalizer (MMSE-DFE) performs the equalization task, while a Kalman filter tracks the MIMO channel, which models the corrupting effects of inter-symbol interference (ISI), inter-user interference (IUI), and noise. The Kalman tracking is aided by previous hard decisions produced by the DFE, with a decision delay >0, which causes the Kalman filter to track the channel with a delay. A channel prediction module bridges the time gap between the channel estimates produced by the Kalman filter and those needed for the DFE adaptation. The proposed algorithm offers good tracking behavior for multi-user fading ISI channels at the expense of higher complexity.","author":[{"propositions":[],"lastnames":["Komninakis"],"firstnames":["C."],"suffixes":[]},{"propositions":[],"lastnames":["Fragouli"],"firstnames":["C."],"suffixes":[]},{"propositions":[],"lastnames":["Sayed"],"firstnames":["A.","H."],"suffixes":[]},{"propositions":[],"lastnames":["Wesel"],"firstnames":["R.","D."],"suffixes":[]}],"journal":"ICC 2000, New Orleans, Louisiana, June 18-22","pages":"pages 1655–1659","tags":"wireless","title":"Adaptive Multi-Input Multi-Output Fading Channel Equalization using Kalman Estimation","volume":"vol. 3","year":"2000","bibtex":"@article{komninakis_adaptive_2000,\n abstract = {This paper addresses the problem of adaptive channel tracking and equalization for multi-input multi-output (MIMO) time-variant frequency-selective channels. A finite-length minimum-mean-squared-error decision-feedback equalizer (MMSE-DFE) performs the equalization task, while a Kalman filter tracks the MIMO channel, which models the corrupting effects of inter-symbol interference (ISI), inter-user interference (IUI), and noise. The Kalman tracking is aided by previous hard decisions produced by the DFE, with a decision delay \\>0, which causes the Kalman filter to track the channel with a delay. A channel prediction module bridges the time gap between the channel estimates produced by the Kalman filter and those needed for the DFE adaptation. The proposed algorithm offers good tracking behavior for multi-user fading ISI channels at the expense of higher complexity.},\n type={4},\n author = {Komninakis, C. and Fragouli, C. and Sayed, A. H. and Wesel, R. D.},\n journal = {ICC 2000, New Orleans, Louisiana, June 18-22},\n pages = {pages 1655--1659},\n tags = {wireless},\n title = {Adaptive {Multi}-{Input} {Multi}-{Output} {Fading} {Channel} {Equalization} using {Kalman} {Estimation}},\n volume = {vol. 3},\n year = {2000}\n}\n\n","author_short":["Komninakis, C.","Fragouli, C.","Sayed, A. H.","Wesel, R. D."],"key":"komninakis_adaptive_2000","id":"komninakis_adaptive_2000","bibbaseid":"komninakis-fragouli-sayed-wesel-adaptivemultiinputmultioutputfadingchannelequalizationusingkalmanestimation-2000","role":"author","urls":{},"metadata":{"authorlinks":{"fragouli, c":"https://bibbase.org/show?bib=https%3A%2F%2Fbibbase.org%2Fnetwork%2Ffiles%2F52xaJNXvSgauGDmZR&noBootstrap=1&authorFirst=1&nocache=1&fullnames=1&theme=bullets&group0=year&group1=type&owner="}},"downloads":0},"bibtype":"article","biburl":"https://bibbase.org/network/files/52xaJNXvSgauGDmZR","creationDate":"2020-11-13T02:21:59.648Z","downloads":0,"keywords":[],"search_terms":["adaptive","multi","input","multi","output","fading","channel","equalization","using","kalman","estimation","komninakis","fragouli","sayed","wesel"],"title":"Adaptive Multi-Input Multi-Output Fading Channel Equalization using Kalman Estimation","year":2000,"dataSources":["ZyBHKCcCyS7Qk9n3w","2BHqTGHtDg7BjRAJQ","XpqzCLvCgsYBqbTpK","QNNZyNQzfeETJyTbL","Z6bBhKezwKd3pPWRc"]}