LEADER 04403nam 2200649Ia 450 001 9910437889803321 005 20200520144314.0 010 $a1-283-63148-2 010 $a9786613943934 010 $a3-642-31692-1 024 7 $a10.1007/978-3-642-31692-0 035 $a(CKB)2670000000250609 035 $a(EBL)1030548 035 $a(OCoLC)809543580 035 $a(SSID)ssj0000736318 035 $a(PQKBManifestationID)11434226 035 $a(PQKBTitleCode)TC0000736318 035 $a(PQKBWorkID)10768080 035 $a(PQKB)10994993 035 $a(DE-He213)978-3-642-31692-0 035 $a(MiAaPQ)EBC1030548 035 $z(PPN)258856297 035 $a(PPN)168320061 035 $a(EXLCZ)992670000000250609 100 $a20120622d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAnalysis and transceiver design for the MIMO broadcast channel /$fRaphael Hunger 205 $a1st ed. 2013. 210 $aHeidelberg $cSpringer$d2012 215 $a1 online resource (322 p.) 225 0$aFoundations in signal processing, communications and networking,$x1863-8538 ;$vv. 8 300 $aDescription based upon print version of record. 311 $a3-642-43634-X 311 $a3-642-31691-3 320 $aIncludes bibliographical references and index. 327 $aSystem Models -- Dualities for the MIMO BC and the MIMO MAC with Linear Transceivers -- Rate Duality with Nonlinear Interference Cancelation -- Matrix-Based Gradient-Projection Algorithm -- MIMO BC Transceiver Design with Interference Cancelation -- Asymptotic High Power Analysis of the MIMO BC -- Description of the Quality of Service Feasibility Region. 330 $aThis book deals with the optimization-based joint design of the transmit and receive filters in   MIMO broadcast channel in which the user terminals may be equipped with several antenna elements. Furthermore, the maximum performance of the system in the high power regime as well as the set of all feasible quality-of-service requirements is analyzed. First, a fundamental duality is derived that holds between the MIMO broadcast channel and virtual MIMO multiple access channel. This duality construct allows for the efficient solution of problems originally posed in the broadcast channel in the dual domain where a possibly hidden convexity can often be revealed. On the basis of the established duality result, the gradient-projection algorithm is introduced as a tool to solve constrained optimization problems to global optimality under certain conditions. The gradient-projection tool is then applied to solving the weighted sum rate maximization problem which is a central optimization that arises in any network utility maximization. In the high power regime, a simple characterization of the obtained performance becomes possible due to the fact that the weighted sum rate utility converges to an affine asymptote in the logarithmic power domain. We find closed form expressions for these asymptotes which allows for a quantification of the asymptotic rate loss that linear transceivers have to face with respect to dirty paper coding. In the last part, we answer the fundamental question of feasibility in quality-of-service based optimizations with inelastic traffic that features strict delay constraints. Under the assumption of linear transceivers, not every set of quality-of-service requirements might be feasible making the power minimization problem with given lower bound constraints on the rate for example infeasible  in these cases. We derive a complete description of the quality-of-service feasibility region for  arbitrary channel matrices. 410 0$aFoundations in Signal Processing, Communications and Networking,$x1863-8538 ;$v8 606 $aRadio$xTransmitter-receivers$xDesign and construction 606 $aMIMO systems 606 $aWireless communication systems 615 0$aRadio$xTransmitter-receivers$xDesign and construction. 615 0$aMIMO systems. 615 0$aWireless communication systems. 676 $a621.3822 700 $aHunger$b Raphael$01058907 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437889803321 996 $aAnalysis and Transceiver Design for the MIMO Broadcast Channel$92503121 997 $aUNINA