LEADER 04185nam 22007215 450 001 9910299486803321 005 20200703231524.0 010 $a3-319-04984-4 024 7 $a10.1007/978-3-319-04984-7 035 $a(CKB)3710000000093978 035 $a(EBL)1698176 035 $a(OCoLC)880449479 035 $a(SSID)ssj0001186906 035 $a(PQKBManifestationID)11787422 035 $a(PQKBTitleCode)TC0001186906 035 $a(PQKBWorkID)11243747 035 $a(PQKB)11511727 035 $a(MiAaPQ)EBC1698176 035 $a(DE-He213)978-3-319-04984-7 035 $a(PPN)177822236 035 $a(EXLCZ)993710000000093978 100 $a20140313d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aLow Complexity MIMO Receivers /$fby Lin Bai, Jinho Choi, Quan Yu 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (313 p.) 300 $aDescription based upon print version of record. 311 $a3-319-04983-6 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- Signal Processing at Receivers: Detection Theory -- MIMO Detection: Vector Space Signal Detection -- Successive Interference Cancellation Based MIMO Detection -- Lattice Reduction Based MIMO Detection -- MIMO Iterative Receivers.- Bit-Wise MIMO-BICM-ID using Lattice Reduction -- Randomized Sampling-based MIMO Iterative Receivers -- Iterative Channel Estimation and Detection -- Multiuser and Multicell MIMO Systems: The Use of Lattice Reduction. 330 $aMultiple-input multiple-output (MIMO) systems can increase the spectral efficiency in wireless communications. However, the interference becomes the major drawback that leads to high computational complexity at both transmitter and receiver. In particular, the complexity of MIMO receivers can be prohibitively high. As an efficient mathematical tool to devise low complexity approaches that mitigate the interference in MIMO systems, lattice reduction (LR) has been widely studied and employed over the last decade. The co-authors of this book are world's leading experts on MIMO receivers, and here they share the key findings of their research over years. They detail a range of key techniques for receiver design as multiple transmitted and received signals are available. The authors first introduce the principle of signal detection and the LR in mathematical aspects. They then move on to discuss the use of LR in low complexity MIMO receiver design with respect to different aspects, including uncoded MIMO detection, MIMO iterative receivers, receivers in multiuser scenarios, and multicell MIMO systems. 606 $aElectrical engineering 606 $aComputer organization 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aCommunications Engineering, Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/T24035 606 $aComputer Systems Organization and Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13006 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 615 0$aElectrical engineering. 615 0$aComputer organization. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 14$aCommunications Engineering, Networks. 615 24$aComputer Systems Organization and Communication Networks. 615 24$aSignal, Image and Speech Processing. 676 $a004.6 676 $a620 676 $a621.382 676 $a621.384 700 $aBai$b Lin$4aut$4http://id.loc.gov/vocabulary/relators/aut$0945765 702 $aChoi$b Jinho$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aYu$b Quan$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910299486803321 996 $aLow Complexity MIMO Receivers$92135901 997 $aUNINA