{"product_id":"algorithms-for-communications-systems-and-their-applications-hardback-9781119567967","title":"Algorithms for Communications Systems and their Applications (Hardback) 9781119567967","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eAlgorithms for Communications Systems and their Applications\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eNevio Benvenuto (Author), Giovanni Cherubini (Author), Stefano Tomasin (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781119567967, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 4 February 2021\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e960 pages\u003cbr\u003e25.4 x 17.8 x 5.5 cm, 1.928 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eThe definitive guide to problem-solving in the design of communications systems\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eIn \u003ci\u003eAlgorithms for Communications Systems and their Applications, 2nd Edition\u003c\/i\u003e, authors Benvenuto, Cherubini, and Tomasin have delivered the ultimate and practical guide to applying algorithms in communications systems. Written for researchers and professionals in the areas of digital communications, signal processing, and computer engineering, \u003ci\u003eAlgorithms for Communications Systems\u003c\/i\u003e presents algorithmic and computational procedures within communications systems that overcome a wide range of problems facing system designers. \u003c\/p\u003e\n\u003cp\u003eNew material in this fully updated edition includes: \u003c\/p\u003e\n\u003cul\u003e \u003cli\u003eMIMO systems (Space-time block coding\/Spatial multiplexing \/Beamforming and interference management\/Channel Estimation)\u003c\/li\u003e \u003cli\u003eOFDM and SC-FDMA (Synchronization\/Resource allocation (bit and power loading)\/Filtered OFDM)\u003c\/li\u003e \u003cli\u003eImproved radio channel model (Doppler and shadowing\/mmWave)\u003c\/li\u003e \u003cli\u003ePolar codes (including practical decoding methods)\u003c\/li\u003e \u003cli\u003e5G systems (New Radio architecture\/initial access for mmWave\/physical channels)\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThe book retains the essential coding and signal processing theoretical and operative elements expected from a classic text, further adopting the \u003ci\u003enew radio\u003c\/i\u003e of 5G systems as a case study to create the definitive guide to modern communications systems.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface 3\u003c\/p\u003e \u003cp\u003eAcknowledgments 3\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Elements of signal theory 7\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Continuous-time linear systems 7\u003c\/p\u003e \u003cp\u003e1.2 Discrete-time linear systems 10\u003c\/p\u003e \u003cp\u003eDiscrete Fourier transform 13\u003c\/p\u003e \u003cp\u003eThe DFT operator 14\u003c\/p\u003e \u003cp\u003eCircular and linear convolution via DFT 15\u003c\/p\u003e \u003cp\u003eConvolution by the overlap-save method 17\u003c\/p\u003e \u003cp\u003eIIR and FIR filters 19\u003c\/p\u003e \u003cp\u003e1.3 Signal bandwidth 22\u003c\/p\u003e \u003cp\u003eThe sampling theorem 24\u003c\/p\u003e \u003cp\u003eHeaviside conditions for the absence of signal distortion 26\u003c\/p\u003e \u003cp\u003e1.4 Passband signals and systems 26\u003c\/p\u003e \u003cp\u003eComplex representation 26\u003c\/p\u003e \u003cp\u003eRelation between a signal and its complex representation 28\u003c\/p\u003e \u003cp\u003eBaseband equivalent of a transformation 36\u003c\/p\u003e \u003cp\u003eEnvelope and instantaneous phase and frequency 37\u003c\/p\u003e \u003cp\u003e1.5 Second-order analysis of random processes 38\u003c\/p\u003e \u003cp\u003e1.5.1 Correlation 39\u003c\/p\u003e \u003cp\u003eProperties of the autocorrelation function 40\u003c\/p\u003e \u003cp\u003e1.5.2 Power spectral density 40\u003c\/p\u003e \u003cp\u003eSpectral lines in the PSD 40\u003c\/p\u003e \u003cp\u003eCross power spectral density 42\u003c\/p\u003e \u003cp\u003eProperties of the PSD 42\u003c\/p\u003e \u003cp\u003ePSD through filtering 43\u003c\/p\u003e \u003cp\u003e1.5.3 PSD of discrete-time random processes 43\u003c\/p\u003e \u003cp\u003eSpectral lines in the PSD 44\u003c\/p\u003e \u003cp\u003ePSD through filtering 45\u003c\/p\u003e \u003cp\u003eMinimum-phase spectral factorization 46\u003c\/p\u003e \u003cp\u003e1.5.4 PSD of passband processes 47\u003c\/p\u003e \u003cp\u003ePSD of in-phase and quadrature components 47\u003c\/p\u003e \u003cp\u003eCyclostationary processes 50\u003c\/p\u003e \u003cp\u003e1.6 The autocorrelation matrix 56\u003c\/p\u003e \u003cp\u003eProperties 56\u003c\/p\u003e \u003cp\u003eEigenvalues 56\u003c\/p\u003e \u003cp\u003eOther properties 57\u003c\/p\u003e \u003cp\u003eEigenvalue analysis for Hermitian matrices 58\u003c\/p\u003e \u003cp\u003e1.7 Examples of random processes 60\u003c\/p\u003e \u003cp\u003e1.8 Matched filter 66\u003c\/p\u003e \u003cp\u003eWhite noise case 68\u003c\/p\u003e \u003cp\u003e1.9 Ergodic random processes 69\u003c\/p\u003e \u003cp\u003e1.9.1 Mean value estimators 71\u003c\/p\u003e \u003cp\u003eRectangular window 74\u003c\/p\u003e \u003cp\u003eExponential filter 74\u003c\/p\u003e \u003cp\u003eGeneral window 75\u003c\/p\u003e \u003cp\u003e1.9.2 Correlation estimators 75\u003c\/p\u003e \u003cp\u003eUnbiased estimate 76\u003c\/p\u003e \u003cp\u003eBiased estimate 76\u003c\/p\u003e \u003cp\u003e1.9.3 Power spectral density estimators 77\u003c\/p\u003e \u003cp\u003ePeriodogram or instantaneous spectrum 77\u003c\/p\u003e \u003cp\u003eWelch periodogram 78\u003c\/p\u003e \u003cp\u003eBlackman and Tukey correlogram 79\u003c\/p\u003e \u003cp\u003eWindowing and window closing 79\u003c\/p\u003e \u003cp\u003e1.10 Parametric models of random processes 82\u003c\/p\u003e \u003cp\u003eARMA 82\u003c\/p\u003e \u003cp\u003eMA 84\u003c\/p\u003e \u003cp\u003eAR 84\u003c\/p\u003e \u003cp\u003eSpectral factorization of AR models 87\u003c\/p\u003e \u003cp\u003eWhitening filter 87\u003c\/p\u003e \u003cp\u003eRelation between ARMA, MA, and AR models 87\u003c\/p\u003e \u003cp\u003e1.10.1 Autocorrelation of AR processes 89\u003c\/p\u003e \u003cp\u003e1.10.2 Spectral estimation of an AR process 91\u003c\/p\u003e \u003cp\u003eSome useful relations 92\u003c\/p\u003e \u003cp\u003eAR model of sinusoidal processes 94\u003c\/p\u003e \u003cp\u003e1.11 Guide to the bibliography 95\u003c\/p\u003e \u003cp\u003eBibliography 95\u003c\/p\u003e \u003cp\u003eAppendixes 97\u003c\/p\u003e \u003cp\u003e1.A Multirate systems 98\u003c\/p\u003e \u003cp\u003e1.A.1 Fundamentals 98\u003c\/p\u003e \u003cp\u003e1.A.2 Decimation 100\u003c\/p\u003e \u003cp\u003e1.A.3 Interpolation 102\u003c\/p\u003e \u003cp\u003e1.A.4 Decimator filter 104\u003c\/p\u003e \u003cp\u003e1.A.5 Interpolator filter 105\u003c\/p\u003e \u003cp\u003e1.A.6 Rate conversion 108\u003c\/p\u003e \u003cp\u003e1.A.7 Time interpolation 109\u003c\/p\u003e \u003cp\u003eLinear interpolation 110\u003c\/p\u003e \u003cp\u003eQuadratic interpolation 112\u003c\/p\u003e \u003cp\u003e1.A.8 The noble identities 112\u003c\/p\u003e \u003cp\u003e1.A.9 The polyphase representation 113\u003c\/p\u003e \u003cp\u003eEfficient implementations 114\u003c\/p\u003e \u003cp\u003e1.B Generation of a complex Gaussian noise 121\u003c\/p\u003e \u003cp\u003e1.C Pseudo-noise sequences 122\u003c\/p\u003e \u003cp\u003eMaximal-length 122\u003c\/p\u003e \u003cp\u003eCAZAC 124\u003c\/p\u003e \u003cp\u003eGold 125\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 The Wiener filter 129\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 The Wiener filter 129\u003c\/p\u003e \u003cp\u003eMatrix formulation 130\u003c\/p\u003e \u003cp\u003eOptimum filter design 132\u003c\/p\u003e \u003cp\u003eThe principle of orthogonality 134\u003c\/p\u003e \u003cp\u003eExpression of the minimum mean-square error 135\u003c\/p\u003e \u003cp\u003eCharacterization of the cost function surface 136\u003c\/p\u003e \u003cp\u003eThe Wiener filter in the z-domain 137\u003c\/p\u003e \u003cp\u003e2.2 Linear prediction 140\u003c\/p\u003e \u003cp\u003eForward linear predictor 141\u003c\/p\u003e \u003cp\u003eOptimum predictor coefficients 141\u003c\/p\u003e \u003cp\u003eForward prediction error filter 142\u003c\/p\u003e \u003cp\u003eRelation between linear prediction and AR models 143\u003c\/p\u003e \u003cp\u003eFirst and second order solutions 144\u003c\/p\u003e \u003cp\u003e2.3 The least squares method 145\u003c\/p\u003e \u003cp\u003eData windowing 146\u003c\/p\u003e \u003cp\u003eMatrix formulation 146\u003c\/p\u003e \u003cp\u003eCorrelation matrix 147\u003c\/p\u003e \u003cp\u003eDetermination of the optimum filter coefficients 147\u003c\/p\u003e \u003cp\u003e2.3.1 The principle of orthogonality 148\u003c\/p\u003e \u003cp\u003eMinimum cost function 149\u003c\/p\u003e \u003cp\u003eThe normal equation using the data matrix 149\u003c\/p\u003e \u003cp\u003eGeometric interpretation: the projection operator 150\u003c\/p\u003e \u003cp\u003e2.3.2 Solutions to the LS problem 151\u003c\/p\u003e \u003cp\u003eSingular value decomposition 152\u003c\/p\u003e \u003cp\u003eMinimum norm solution 154\u003c\/p\u003e \u003cp\u003e2.4 The estimation problem 155\u003c\/p\u003e \u003cp\u003eEstimation of a random variable 155\u003c\/p\u003e \u003cp\u003eMMSE estimation 155\u003c\/p\u003e \u003cp\u003eExtension to multiple observations 157\u003c\/p\u003e \u003cp\u003eLinear MMSE estimation of a random variable 158\u003c\/p\u003e \u003cp\u003eLinear MMSE estimation of a random vector 158\u003c\/p\u003e \u003cp\u003e2.4.1 The Cramér-Rao lower bound 160\u003c\/p\u003e \u003cp\u003eExtension to vector parameter 162\u003c\/p\u003e \u003cp\u003e2.5 Examples of application 164\u003c\/p\u003e \u003cp\u003e2.5.1 Identification of a linear discrete-time system 164\u003c\/p\u003e \u003cp\u003e2.5.2 Identification of a continuous-time system 166\u003c\/p\u003e \u003cp\u003e2.5.3 Cancellation of an interfering signal 169\u003c\/p\u003e \u003cp\u003e2.5.4 Cancellation of a sinusoidal interferer with known frequency 170\u003c\/p\u003e \u003cp\u003e2.5.5 Echo cancellation in digital subscriber loops 171\u003c\/p\u003e \u003cp\u003e2.5.6 Cancellation of a periodic interferer 172\u003c\/p\u003e \u003cp\u003eBibliography 173\u003c\/p\u003e \u003cp\u003eAppendixes 174\u003c\/p\u003e \u003cp\u003e2.A The Levinson-Durbin algorithm 175\u003c\/p\u003e \u003cp\u003eLattice filters 176\u003c\/p\u003e \u003cp\u003eThe Delsarte-Genin algorithm 177\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Adaptive transversal filters 179\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 The MSE design criterion 180\u003c\/p\u003e \u003cp\u003e3.1.1 The steepest descent or gradient algorithm 181\u003c\/p\u003e \u003cp\u003eStability 181\u003c\/p\u003e \u003cp\u003eConditions for convergence 183\u003c\/p\u003e \u003cp\u003eAdaptation gain 184\u003c\/p\u003e \u003cp\u003eTransient behaviour of the MSE 185\u003c\/p\u003e \u003cp\u003e3.1.2 The least mean square algorithm 186\u003c\/p\u003e \u003cp\u003eImplementation 187\u003c\/p\u003e \u003cp\u003eComputational complexity 188\u003c\/p\u003e \u003cp\u003eConditions for convergence 188\u003c\/p\u003e \u003cp\u003e3.1.3 Convergence analysis of the LMS algorithm 190\u003c\/p\u003e \u003cp\u003eConvergence of the mean 191\u003c\/p\u003e \u003cp\u003eConvergence in the mean-square sense: real scalar case 192\u003c\/p\u003e \u003cp\u003eConvergence in the mean-square sense: general case 193\u003c\/p\u003e \u003cp\u003eFundamental results 196\u003c\/p\u003e \u003cp\u003eObservations 197\u003c\/p\u003e \u003cp\u003eFinal remarks 199\u003c\/p\u003e \u003cp\u003e3.1.4 Other versions of the LMS algorithm 199\u003c\/p\u003e \u003cp\u003eLeaky LMS 199\u003c\/p\u003e \u003cp\u003eSign algorithm 200\u003c\/p\u003e \u003cp\u003eNormalized LMS 200\u003c\/p\u003e \u003cp\u003eVariable adaptation gain 201\u003c\/p\u003e \u003cp\u003e3.1.5 Example of application: the predictor 202\u003c\/p\u003e \u003cp\u003e3.2 The recursive least squares algorithm 208\u003c\/p\u003e \u003cp\u003eNormal equation 209\u003c\/p\u003e \u003cp\u003eDerivation 210\u003c\/p\u003e \u003cp\u003eInitialization 212\u003c\/p\u003e \u003cp\u003eRecursive form of the minimum cost function 212\u003c\/p\u003e \u003cp\u003eConvergence 214\u003c\/p\u003e \u003cp\u003eComputational complexity 214\u003c\/p\u003e \u003cp\u003eExample of application: the predictor 215\u003c\/p\u003e \u003cp\u003e3.3 Fast recursive algorithms 215\u003c\/p\u003e \u003cp\u003e3.3.1 Comparison of the various algorithms 216\u003c\/p\u003e \u003cp\u003e3.4 Examples of application 216\u003c\/p\u003e \u003cp\u003e3.4.1 Identification of a linear discrete-time system 217\u003c\/p\u003e \u003cp\u003eFinite alphabet case 219\u003c\/p\u003e \u003cp\u003e3.4.2 Cancellation of a sinusoidal interferer with known frequency 220\u003c\/p\u003e \u003cp\u003eBibliography 221\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Transmission channels 223\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Radio channel 223\u003c\/p\u003e \u003cp\u003e4.1.1 Propagation and used frequencies in radio transmission 224\u003c\/p\u003e \u003cp\u003eBasic propagation mechanisms 224\u003c\/p\u003e \u003cp\u003eFrequency ranges 224\u003c\/p\u003e \u003cp\u003e4.1.2 Analog front-end architectures 226\u003c\/p\u003e \u003cp\u003eRadiation masks 226\u003c\/p\u003e \u003cp\u003eConventional superheterodyne receiver 227\u003c\/p\u003e \u003cp\u003eAlternative architectures 227\u003c\/p\u003e \u003cp\u003eDirect conversion receiver 228\u003c\/p\u003e \u003cp\u003eSingle conversion to low-IF 229\u003c\/p\u003e \u003cp\u003eDouble conversion and wideband IF 229\u003c\/p\u003e \u003cp\u003e4.1.3 General channel model 230\u003c\/p\u003e \u003cp\u003eHigh power amplifier 230\u003c\/p\u003e \u003cp\u003eTransmission medium 233\u003c\/p\u003e \u003cp\u003eAdditive noise 234\u003c\/p\u003e \u003cp\u003ePhase noise 234\u003c\/p\u003e \u003cp\u003e4.1.4 Narrowband radio channel model 235\u003c\/p\u003e \u003cp\u003eEquivalent circuit at the receiver 237\u003c\/p\u003e \u003cp\u003eMultipath 238\u003c\/p\u003e \u003cp\u003ePath loss as a function of distance 240\u003c\/p\u003e \u003cp\u003e4.1.5 Fading effects in propagation models 243\u003c\/p\u003e \u003cp\u003eMacroscopic fading or shadowing 243\u003c\/p\u003e \u003cp\u003eMicroscopic fading 245\u003c\/p\u003e \u003cp\u003e4.1.6 Doppler shift 245\u003c\/p\u003e \u003cp\u003e4.1.7 Wideband channel model 247\u003c\/p\u003e \u003cp\u003eMultipath channel parameters 249\u003c\/p\u003e \u003cp\u003eStatistical description of fading channels 250\u003c\/p\u003e \u003cp\u003e4.1.8 Channel statistics 252\u003c\/p\u003e \u003cp\u003ePower delay profile 252\u003c\/p\u003e \u003cp\u003eCoherence bandwidth 253\u003c\/p\u003e \u003cp\u003eDoppler spectrum 254\u003c\/p\u003e \u003cp\u003eCoherence time 255\u003c\/p\u003e \u003cp\u003eDoppler spectrum models 256\u003c\/p\u003e \u003cp\u003ePower angular spectrum 256\u003c\/p\u003e \u003cp\u003eCoherence distance 256\u003c\/p\u003e \u003cp\u003eOn fading 257\u003c\/p\u003e \u003cp\u003e4.1.9 Discrete-time model for fading channels 258\u003c\/p\u003e \u003cp\u003eGeneration of a process with a preassigned spectrum 259\u003c\/p\u003e \u003cp\u003e4.1.10 Discrete-space model of shadowing 261\u003c\/p\u003e \u003cp\u003e4.1.11 Multiantenna systems 264\u003c\/p\u003e \u003cp\u003eDiscrete-time model 266\u003c\/p\u003e \u003cp\u003e4.2 Telephone channel 268\u003c\/p\u003e \u003cp\u003eDistortion 270\u003c\/p\u003e \u003cp\u003eNoise sources 270\u003c\/p\u003e \u003cp\u003eEcho 270\u003c\/p\u003e \u003cp\u003eAppendixes 272\u003c\/p\u003e \u003cp\u003e4.A Discrete-time NB model for mmWave channels 273\u003c\/p\u003e \u003cp\u003eAngular domain representation 273\u003c\/p\u003e \u003cp\u003eBibliography 274\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Vector quantization 277\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Basic concept 277\u003c\/p\u003e \u003cp\u003e5.2 Characterization of VQ 278\u003c\/p\u003e \u003cp\u003eParameters determining VQ performance 278\u003c\/p\u003e \u003cp\u003eComparison between VQ and scalar quantization 280\u003c\/p\u003e \u003cp\u003e5.3 Optimum quantization 281\u003c\/p\u003e \u003cp\u003eGeneralized Lloyd algorithm 282\u003c\/p\u003e \u003cp\u003e5.4 The Linde, Buzo, and Gray algorithm 284\u003c\/p\u003e \u003cp\u003eChoice of the initial codebook 285\u003c\/p\u003e \u003cp\u003eSplitting procedure 286\u003c\/p\u003e \u003cp\u003eSelection of the training sequence 287\u003c\/p\u003e \u003cp\u003e5.4.1 k-means clustering 288\u003c\/p\u003e \u003cp\u003e5.5 Variants of VQ 288\u003c\/p\u003e \u003cp\u003eTree search VQ 288\u003c\/p\u003e \u003cp\u003eMultistage VQ 289\u003c\/p\u003e \u003cp\u003eProduct code VQ 291\u003c\/p\u003e \u003cp\u003e5.6 VQ of channel state information 292\u003c\/p\u003e \u003cp\u003eMISO channel quantization 292\u003c\/p\u003e \u003cp\u003eChannel feedback with feedforward information 294\u003c\/p\u003e \u003cp\u003e5.7 Principal component analysis 295\u003c\/p\u003e \u003cp\u003e5.7.1 PCA and k-means clustering 297\u003c\/p\u003e \u003cp\u003eBibliography 299\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Digital transmission model and channel capacity 301\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Digital transmission model 301\u003c\/p\u003e \u003cp\u003e6.2 Detection 305\u003c\/p\u003e \u003cp\u003e6.2.1 Optimum detection 306\u003c\/p\u003e \u003cp\u003eML 307\u003c\/p\u003e \u003cp\u003eMAP 307\u003c\/p\u003e \u003cp\u003e6.2.2 Soft detection 309\u003c\/p\u003e \u003cp\u003eLLRs associated to bits of BMAP 309\u003c\/p\u003e \u003cp\u003eSimplified expressions 312\u003c\/p\u003e \u003cp\u003e6.2.3 Receiver strategies 314\u003c\/p\u003e \u003cp\u003e6.3 Relevant parameters of the digital transmission model 314\u003c\/p\u003e \u003cp\u003eRelations among parameters 315\u003c\/p\u003e \u003cp\u003e6.4 Error probability 317\u003c\/p\u003e \u003cp\u003e6.5 Capacity 320\u003c\/p\u003e \u003cp\u003e6.5.1 Discrete-time AWGN channel 321\u003c\/p\u003e \u003cp\u003e6.5.2 SISO narrowband AWGN channel 322\u003c\/p\u003e \u003cp\u003e6.5.3 SISO dispersive AGN channel 322\u003c\/p\u003e \u003cp\u003e6.5.4 MIMO discrete-time NB AWGN channel 325\u003c\/p\u003e \u003cp\u003e6.6 Achievable rates of modulations in AWGN channels 326\u003c\/p\u003e \u003cp\u003e6.6.1 Rate as a function of the SNR per dimension 327\u003c\/p\u003e \u003cp\u003e6.6.2 Coding strategies depending on the signal-to-noise ratio 329\u003c\/p\u003e \u003cp\u003eCoding gain 330\u003c\/p\u003e \u003cp\u003e6.6.3 Achievable rate of an AWGN channel using PAM 331\u003c\/p\u003e \u003cp\u003eBibliography 333\u003c\/p\u003e \u003cp\u003eAppendixes 334\u003c\/p\u003e \u003cp\u003e6.A Gray labelling 335\u003c\/p\u003e \u003cp\u003e6.B The Gaussian distribution and Marcum functions 336\u003c\/p\u003e \u003cp\u003e6.B.1 The Q function 336\u003c\/p\u003e \u003cp\u003e6.B.2 Marcum function 338\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Single-carrier modulation 341\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Signals and systems 341\u003c\/p\u003e \u003cp\u003e7.1.1 Baseband digital transmission (PAM) 341\u003c\/p\u003e \u003cp\u003eModulator 342\u003c\/p\u003e \u003cp\u003eTransmission channel 343\u003c\/p\u003e \u003cp\u003eReceiver 343\u003c\/p\u003e \u003cp\u003ePower spectral density 344\u003c\/p\u003e \u003cp\u003e7.1.2 Passband digital transmission (QAM) 346\u003c\/p\u003e \u003cp\u003eModulator 346\u003c\/p\u003e \u003cp\u003ePower spectral density 347\u003c\/p\u003e \u003cp\u003eThree equivalent representations of the modulator 348\u003c\/p\u003e \u003cp\u003eCoherent receiver 349\u003c\/p\u003e \u003cp\u003e7.1.3 Baseband equivalent model of a QAM system 349\u003c\/p\u003e \u003cp\u003eSignal analysis 349\u003c\/p\u003e \u003cp\u003e7.1.4 Characterization of system elements 353\u003c\/p\u003e \u003cp\u003eTransmitter 353\u003c\/p\u003e \u003cp\u003eTransmission channel 354\u003c\/p\u003e \u003cp\u003eReceiver 355\u003c\/p\u003e \u003cp\u003e7.2 Intersymbol interference 356\u003c\/p\u003e \u003cp\u003eDiscrete-time equivalent system 356\u003c\/p\u003e \u003cp\u003eNyquist pulses 357\u003c\/p\u003e \u003cp\u003eEye diagram 361\u003c\/p\u003e \u003cp\u003e7.3 Performance analysis 365\u003c\/p\u003e \u003cp\u003eSignal-to-noise ratio 365\u003c\/p\u003e \u003cp\u003eSymbol error probability in the absence of ISI 366\u003c\/p\u003e \u003cp\u003eMatched filter receiver 367\u003c\/p\u003e \u003cp\u003e7.4 Channel equalization 367\u003c\/p\u003e \u003cp\u003e7.4.1 Zero-forcing equalizer 367\u003c\/p\u003e \u003cp\u003e7.4.2 Linear equalizer 368\u003c\/p\u003e \u003cp\u003eOptimum receiver in the presence of noise and ISI 369\u003c\/p\u003e \u003cp\u003eAlternative derivation of the IIR equalizer 370\u003c\/p\u003e \u003cp\u003eSignal-to-noise ratio at detector 374\u003c\/p\u003e \u003cp\u003e7.4.3 LE with a finite number of coefficients 375\u003c\/p\u003e \u003cp\u003eAdaptive LE 376\u003c\/p\u003e \u003cp\u003eFractionally spaced equalizer 378\u003c\/p\u003e \u003cp\u003e7.4.4 Decision feedback equalizer 381\u003c\/p\u003e \u003cp\u003eDesign of a DFE with a finite number of coefficients 384\u003c\/p\u003e \u003cp\u003eDesign of a fractionally spaced DFE 387\u003c\/p\u003e \u003cp\u003eSignal-to-noise ratio at the decision point 389\u003c\/p\u003e \u003cp\u003eRemarks 390\u003c\/p\u003e \u003cp\u003e7.4.5 Frequency domain equalization 390\u003c\/p\u003e \u003cp\u003eDFE with data frame using a unique word 390\u003c\/p\u003e \u003cp\u003e7.4.6 LE-ZF 394\u003c\/p\u003e \u003cp\u003e7.4.7 DFE-ZF with IIR filters 394\u003c\/p\u003e \u003cp\u003eDFE-ZF as noise predictor 400\u003c\/p\u003e \u003cp\u003eDFE as ISI and noise predictor 400\u003c\/p\u003e \u003cp\u003e7.4.8 Benchmark performance of LE-ZF and DFE-ZF 402\u003c\/p\u003e \u003cp\u003eComparison 402\u003c\/p\u003e \u003cp\u003ePerformance for two channel models 403\u003c\/p\u003e \u003cp\u003e7.4.9 Passband equalizers 404\u003c\/p\u003e \u003cp\u003ePassband receiver structure 405\u003c\/p\u003e \u003cp\u003eOptimization of equalizer coefficients and carrier phase offset 407\u003c\/p\u003e \u003cp\u003eAdaptive method 408\u003c\/p\u003e \u003cp\u003e7.5 Optimum methods for data detection 410\u003c\/p\u003e \u003cp\u003e7.5.1 Maximum-likelihood sequence detection 412\u003c\/p\u003e \u003cp\u003eLower bound to error probability using MLSD 413\u003c\/p\u003e \u003cp\u003eThe Viterbi algorithm 414\u003c\/p\u003e \u003cp\u003eComputational complexity of the VA 419\u003c\/p\u003e \u003cp\u003e7.5.2 Maximum a posteriori probability detector 419\u003c\/p\u003e \u003cp\u003eStatistical description of a sequential machine 420\u003c\/p\u003e \u003cp\u003eThe forward-backward algorithm 421\u003c\/p\u003e \u003cp\u003eScaling 425\u003c\/p\u003e \u003cp\u003eThe log likelihood function and the Max-Log-MAP criterion 426\u003c\/p\u003e \u003cp\u003eLLRs associated to bits of BMAP 427\u003c\/p\u003e \u003cp\u003eRelation between Max-Log-MAP and Log-MAP 428\u003c\/p\u003e \u003cp\u003e7.5.3 Optimum receivers 428\u003c\/p\u003e \u003cp\u003e7.5.4 The Ungerboeck’s formulation of MLSD 430\u003c\/p\u003e \u003cp\u003e7.5.5 Error probability achieved by MLSD 433\u003c\/p\u003e \u003cp\u003eComputation of the minimum distance 437\u003c\/p\u003e \u003cp\u003e7.5.6 The reduced-state sequence detection 441\u003c\/p\u003e \u003cp\u003eTrellis diagram 442\u003c\/p\u003e \u003cp\u003eThe RSSE algorithm 444\u003c\/p\u003e \u003cp\u003eFurther simplification: DFSE 446\u003c\/p\u003e \u003cp\u003e7.6 Numerical results obtained by simulations 447\u003c\/p\u003e \u003cp\u003eQPSK over a minimum-phase channel 447\u003c\/p\u003e \u003cp\u003eQPSK over a non minimum phase channel 448\u003c\/p\u003e \u003cp\u003e8-PSK over a minimum phase channel 449\u003c\/p\u003e \u003cp\u003e8-PSK over a non minimum phase channel 449\u003c\/p\u003e \u003cp\u003e7.7 Precoding for dispersive channels 451\u003c\/p\u003e \u003cp\u003e7.7.1 Tomlinson-Harashima precoding 452\u003c\/p\u003e \u003cp\u003e7.7.2 Flexible precoding 454\u003c\/p\u003e \u003cp\u003e7.8 Channel estimation 456\u003c\/p\u003e \u003cp\u003e7.8.1 The correlation method 456\u003c\/p\u003e \u003cp\u003e7.8.2 The LS method 458\u003c\/p\u003e \u003cp\u003eFormulation using the data matrix 459\u003c\/p\u003e \u003cp\u003e7.8.3 Signal-to-estimation error ratio 460\u003c\/p\u003e \u003cp\u003e7.8.4 Channel estimation for multirate systems 464\u003c\/p\u003e \u003cp\u003e7.8.5 The LMMSE method 465\u003c\/p\u003e \u003cp\u003e7.9 Faster-than-Nyquist Signalling 467\u003c\/p\u003e \u003cp\u003eBibliography 467\u003c\/p\u003e \u003cp\u003eAppendixes 470\u003c\/p\u003e \u003cp\u003e7.A Simulation of a QAM system 471\u003c\/p\u003e \u003cp\u003e7.B Description of a finite-state machine 477\u003c\/p\u003e \u003cp\u003e7.C Line codes for PAM systems 478\u003c\/p\u003e \u003cp\u003e7.C.1 Line codes 478\u003c\/p\u003e \u003cp\u003eNon-return-to-zero format 478\u003c\/p\u003e \u003cp\u003eReturn-to-zero format 479\u003c\/p\u003e \u003cp\u003eBiphase format 480\u003c\/p\u003e \u003cp\u003eDelay modulation or Miller code 481\u003c\/p\u003e \u003cp\u003eBlock line codes 481\u003c\/p\u003e \u003cp\u003eAlternate mark inversion 481\u003c\/p\u003e \u003cp\u003e7.C.2 Partial response systems 482\u003c\/p\u003e \u003cp\u003eThe choice of the PR polynomial 485\u003c\/p\u003e \u003cp\u003eSymbol detection and error probability 489\u003c\/p\u003e \u003cp\u003ePrecoding 491\u003c\/p\u003e \u003cp\u003eError probability with precoding 492\u003c\/p\u003e \u003cp\u003eAlternative interpretation of PR systems 493\u003c\/p\u003e \u003cp\u003e7.D Implementation of a QAM transmitter 497\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Multicarrier modulation 499\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 MC systems 499\u003c\/p\u003e \u003cp\u003e8.2 Orthogonality conditions 500\u003c\/p\u003e \u003cp\u003eTime domain 501\u003c\/p\u003e \u003cp\u003eFrequency domain 501\u003c\/p\u003e \u003cp\u003ez-transform domain 501\u003c\/p\u003e \u003cp\u003e8.3 Efficient implementation of MC systems 502\u003c\/p\u003e \u003cp\u003eMC implementation employing matched filters 502\u003c\/p\u003e \u003cp\u003eOrthogonality conditions in terms of the polyphase components 505\u003c\/p\u003e \u003cp\u003eMC implementation employing a prototype filter 505\u003c\/p\u003e \u003cp\u003e8.4 Non-critically sampled filter banks 510\u003c\/p\u003e \u003cp\u003e8.5 Examples of MC systems 515\u003c\/p\u003e \u003cp\u003eOFDM or DMT 515\u003c\/p\u003e \u003cp\u003eFiltered multitone 516\u003c\/p\u003e \u003cp\u003e8.6 Analog signal processing requirements in MC systems 517\u003c\/p\u003e \u003cp\u003e8.6.1 Analog filter requirements 517\u003c\/p\u003e \u003cp\u003eInterpolator filter and virtual subchannels 517\u003c\/p\u003e \u003cp\u003eModulator filter 519\u003c\/p\u003e \u003cp\u003e8.6.2 Power amplifier requirements 520\u003c\/p\u003e \u003cp\u003e8.7 Equalization 521\u003c\/p\u003e \u003cp\u003e8.7.1 OFDM equalization 521\u003c\/p\u003e \u003cp\u003e8.7.2 FMT equalization 524\u003c\/p\u003e \u003cp\u003ePer-subchannel fractionally-spaced equalization 524\u003c\/p\u003e \u003cp\u003ePer-subchannel T -spaced equalization 524\u003c\/p\u003e \u003cp\u003eAlternative per-subchannel T -spaced equalization 525\u003c\/p\u003e \u003cp\u003e8.8 Orthogonal time frequency space modulation 526\u003c\/p\u003e \u003cp\u003eOTFS equalization 527\u003c\/p\u003e \u003cp\u003e8.9 Channel estimation in OFDM 527\u003c\/p\u003e \u003cp\u003eInstantaneous estimate or LS method 528\u003c\/p\u003e \u003cp\u003eLMMSE 530\u003c\/p\u003e \u003cp\u003eThe LS estimate with truncated impulse response 531\u003c\/p\u003e \u003cp\u003e8.9.1 Channel estimate and pilot symbols 532\u003c\/p\u003e \u003cp\u003e8.10 Multiuser access schemes 532\u003c\/p\u003e \u003cp\u003e8.10.1 OFDMA 533\u003c\/p\u003e \u003cp\u003e8.10.2 SC-FDMA or DFT-spread OFDM 534\u003c\/p\u003e \u003cp\u003e8.11 Comparison between MC and SC systems 535\u003c\/p\u003e \u003cp\u003e8.12 Other MC waveforms 536\u003c\/p\u003e \u003cp\u003eBibliography 537\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Transmission over multiple input multiple output channels 539\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 The MIMO NB channel 539\u003c\/p\u003e \u003cp\u003eSpatial multiplexing and spatial diversity 544\u003c\/p\u003e \u003cp\u003eInterference in MIMO channels 544\u003c\/p\u003e \u003cp\u003e9.2 CSI only at the receiver 545\u003c\/p\u003e \u003cp\u003e9.2.1 SIMO combiner 545\u003c\/p\u003e \u003cp\u003eEqualization and diversity 548\u003c\/p\u003e \u003cp\u003e9.2.2 MIMO combiner 548\u003c\/p\u003e \u003cp\u003eZero-forcing 549\u003c\/p\u003e \u003cp\u003eMMSE 550\u003c\/p\u003e \u003cp\u003e9.2.3 MIMO nonlinear detection and decoding 550\u003c\/p\u003e \u003cp\u003eV-BLAST system 550\u003c\/p\u003e \u003cp\u003eSpatial modulation 552\u003c\/p\u003e \u003cp\u003e9.2.4 Space-time coding 553\u003c\/p\u003e \u003cp\u003eThe Alamouti code 553\u003c\/p\u003e \u003cp\u003eThe Golden code 555\u003c\/p\u003e \u003cp\u003e9.2.5 MIMO channel estimation 556\u003c\/p\u003e \u003cp\u003eThe least squares method 556\u003c\/p\u003e \u003cp\u003eThe LMMSE method 557\u003c\/p\u003e \u003cp\u003e9.3 CSI only at the transmitter 558\u003c\/p\u003e \u003cp\u003e9.3.1 MISO linear precoding 558\u003c\/p\u003e \u003cp\u003eMISO antenna selection 559\u003c\/p\u003e \u003cp\u003e9.3.2 MIMO linear precoding 560\u003c\/p\u003e \u003cp\u003eZF precoding 561\u003c\/p\u003e \u003cp\u003e9.3.3 MIMO nonlinear precoding 562\u003c\/p\u003e \u003cp\u003eDirty paper coding 562\u003c\/p\u003e \u003cp\u003eTH precoding 564\u003c\/p\u003e \u003cp\u003e9.3.4 Channel estimation for CSIT 564\u003c\/p\u003e \u003cp\u003e9.4 CSI at both the transmitter and the receiver 565\u003c\/p\u003e \u003cp\u003e9.5 Hybrid beamforming 566\u003c\/p\u003e \u003cp\u003eHybrid beamforming and angular domain representation 567\u003c\/p\u003e \u003cp\u003e9.6 Multiuser MIMO: broadcast channel 568\u003c\/p\u003e \u003cp\u003e9.6.1 CSI at both the transmitter and the receivers 569\u003c\/p\u003e \u003cp\u003eBlock diagonalization 570\u003c\/p\u003e \u003cp\u003eUser selection 571\u003c\/p\u003e \u003cp\u003eJoint spatial division and multiplexing 572\u003c\/p\u003e \u003cp\u003e9.6.2 Broadcast channel estimation 573\u003c\/p\u003e \u003cp\u003e9.7 Multiuser MIMO: multiple-access channel 573\u003c\/p\u003e \u003cp\u003e9.7.1 CSI at both the transmitters and the receiver 574\u003c\/p\u003e \u003cp\u003eBlock diagonalization 575\u003c\/p\u003e \u003cp\u003e9.7.2 Multiple-access channel estimation 575\u003c\/p\u003e \u003cp\u003e9.8 Massive MIMO 575\u003c\/p\u003e \u003cp\u003e9.8.1 Channel hardening 576\u003c\/p\u003e \u003cp\u003e9.8.2 Multiuser channel orthogonality 576\u003c\/p\u003e \u003cp\u003eBibliography 576\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Spread-spectrum systems 581\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Spread-spectrum techniques 581\u003c\/p\u003e \u003cp\u003e10.1.1 Direct sequence systems 581\u003c\/p\u003e \u003cp\u003eClassification of CDMA systems 589\u003c\/p\u003e \u003cp\u003eSynchronization 590\u003c\/p\u003e \u003cp\u003e10.1.2 Frequency hopping systems 590\u003c\/p\u003e \u003cp\u003eClassification of FH systems 592\u003c\/p\u003e \u003cp\u003e10.2 Applications of spread-spectrum systems 593\u003c\/p\u003e \u003cp\u003e10.2.1 Anti-jamming 594\u003c\/p\u003e \u003cp\u003e10.2.2 Multiple access 596\u003c\/p\u003e \u003cp\u003e10.2.3 Interference rejection 597\u003c\/p\u003e \u003cp\u003e10.3 Chip matched filter and rake receiver 597\u003c\/p\u003e \u003cp\u003eNumber of resolvable rays in a multipath channel 597\u003c\/p\u003e \u003cp\u003eChip matched filter 598\u003c\/p\u003e \u003cp\u003e10.4 Interference 601\u003c\/p\u003e \u003cp\u003eDetection strategies for multiple-access systems 603\u003c\/p\u003e \u003cp\u003e10.5 Single-user detection 603\u003c\/p\u003e \u003cp\u003eChip equalizer 603\u003c\/p\u003e \u003cp\u003eSymbol equalizer 605\u003c\/p\u003e \u003cp\u003e10.6 Multiuser detection 606\u003c\/p\u003e \u003cp\u003e10.6.1 Block equalizer 606\u003c\/p\u003e \u003cp\u003e10.6.2 Interference cancellation detector 608\u003c\/p\u003e \u003cp\u003eSuccessive interference cancellation 608\u003c\/p\u003e \u003cp\u003eParallel interference cancellation 610\u003c\/p\u003e \u003cp\u003e10.6.3 ML multiuser detector 610\u003c\/p\u003e \u003cp\u003eCorrelation matrix 611\u003c\/p\u003e \u003cp\u003eWhitening filter 611\u003c\/p\u003e \u003cp\u003e10.7 Multicarrier CDMA systems 612\u003c\/p\u003e \u003cp\u003eBibliography 613\u003c\/p\u003e \u003cp\u003eAppendixes 615\u003c\/p\u003e \u003cp\u003e10.A Walsh codes 616\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Channel codes 619\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 System model 620\u003c\/p\u003e \u003cp\u003e11.2 Block codes 622\u003c\/p\u003e \u003cp\u003e11.2.1 Theory of binary codes with group structure 622\u003c\/p\u003e \u003cp\u003eProperties 622\u003c\/p\u003e \u003cp\u003eParity check matrix 625\u003c\/p\u003e \u003cp\u003eCode generator matrix 628\u003c\/p\u003e \u003cp\u003eDecoding of binary parity check codes 628\u003c\/p\u003e \u003cp\u003eCosets 629\u003c\/p\u003e \u003cp\u003eTwo conceptually simple decoding methods 630\u003c\/p\u003e \u003cp\u003eSyndrome decoding 631\u003c\/p\u003e \u003cp\u003e11.2.2 Fundamentals of algebra 633\u003c\/p\u003e \u003cp\u003emodulo-q arithmetic 634\u003c\/p\u003e \u003cp\u003ePolynomials with coefficients from a field 637\u003c\/p\u003e \u003cp\u003eModular arithmetic for polynomials 638\u003c\/p\u003e \u003cp\u003eDevices to sum and multiply elements in a finite field 640\u003c\/p\u003e \u003cp\u003eRemarks on finite fields 642\u003c\/p\u003e \u003cp\u003eRoots of a polynomial 646\u003c\/p\u003e \u003cp\u003eMinimum function 648\u003c\/p\u003e \u003cp\u003eMethods to determine the minimum function 650\u003c\/p\u003e \u003cp\u003eProperties of the minimum function 652\u003c\/p\u003e \u003cp\u003e11.2.3 Cyclic codes 653\u003c\/p\u003e \u003cp\u003eThe algebra of cyclic codes 653\u003c\/p\u003e \u003cp\u003eProperties of cyclic codes 654\u003c\/p\u003e \u003cp\u003eEncoding by a shift register of length r 658\u003c\/p\u003e \u003cp\u003eEncoding by a shift register of length k 661\u003c\/p\u003e \u003cp\u003eHard decoding of cyclic codes 662\u003c\/p\u003e \u003cp\u003eHamming codes 663\u003c\/p\u003e \u003cp\u003eBurst error detection 666\u003c\/p\u003e \u003cp\u003e11.2.4 Simplex cyclic codes 666\u003c\/p\u003e \u003cp\u003eRelation to PN sequences 668\u003c\/p\u003e \u003cp\u003e11.2.5 BCH codes 669\u003c\/p\u003e \u003cp\u003eAn alternative method to specify the code polynomials 669\u003c\/p\u003e \u003cp\u003eBose-Chaudhuri-Hocquenhemcodes 671\u003c\/p\u003e \u003cp\u003eBinary BCH codes 674\u003c\/p\u003e \u003cp\u003eReed-Solomon codes 675\u003c\/p\u003e \u003cp\u003eDecoding of BCH codes 676\u003c\/p\u003e \u003cp\u003eEfficient decoding of BCH codes 681\u003c\/p\u003e \u003cp\u003e11.2.6 Performance of block codes 689\u003c\/p\u003e \u003cp\u003e11.3 Convolutional codes 690\u003c\/p\u003e \u003cp\u003e11.3.1 General description of convolutional codes 693\u003c\/p\u003e \u003cp\u003eParity check matrix 695\u003c\/p\u003e \u003cp\u003eGenerator matrix 696\u003c\/p\u003e \u003cp\u003eTransfer function 696\u003c\/p\u003e \u003cp\u003eCatastrophic error propagation 700\u003c\/p\u003e \u003cp\u003e11.3.2 Decoding of convolutional codes 702\u003c\/p\u003e \u003cp\u003eInterleaving 702\u003c\/p\u003e \u003cp\u003eTwo decoding models 703\u003c\/p\u003e \u003cp\u003eDecoding by the Viterbi algorithm 704\u003c\/p\u003e \u003cp\u003eDecoding by the forward-backward algorithm 705\u003c\/p\u003e \u003cp\u003eSequential decoding 706\u003c\/p\u003e \u003cp\u003e11.3.3 Performance of convolutional codes 710\u003c\/p\u003e \u003cp\u003e11.4 Puncturing 711\u003c\/p\u003e \u003cp\u003e11.5 Concatenated codes 711\u003c\/p\u003e \u003cp\u003eThe soft-output Viterbi algorithm 711\u003c\/p\u003e \u003cp\u003e11.6 Turbo codes 713\u003c\/p\u003e \u003cp\u003eEncoding 713\u003c\/p\u003e \u003cp\u003eThe basic principle of iterative decoding 718\u003c\/p\u003e \u003cp\u003eFBA revisited 719\u003c\/p\u003e \u003cp\u003eIterative decoding 728\u003c\/p\u003e \u003cp\u003ePerformance evaluation 730\u003c\/p\u003e \u003cp\u003e11.7 Iterative detection and decoding 730\u003c\/p\u003e \u003cp\u003e11.8 Low-density parity check codes 734\u003c\/p\u003e \u003cp\u003e11.8.1 Representation of LDPC codes 735\u003c\/p\u003e \u003cp\u003eMatrix representation 735\u003c\/p\u003e \u003cp\u003eGraphical representation 736\u003c\/p\u003e \u003cp\u003e11.8.2 Encoding 737\u003c\/p\u003e \u003cp\u003eEncoding procedure 737\u003c\/p\u003e \u003cp\u003e11.8.3 Decoding 738\u003c\/p\u003e \u003cp\u003eHard decision decoder 738\u003c\/p\u003e \u003cp\u003eThe sum-product algorithm decoder 741\u003c\/p\u003e \u003cp\u003eThe LR-SPA decoder 744\u003c\/p\u003e \u003cp\u003eThe LLR-SPA or log-domain SPA decoder 745\u003c\/p\u003e \u003cp\u003eThe min-sum decoder 747\u003c\/p\u003e \u003cp\u003eOther decoding algorithms 748\u003c\/p\u003e \u003cp\u003e11.8.4 Example of application 748\u003c\/p\u003e \u003cp\u003ePerformance and coding gain 748\u003c\/p\u003e \u003cp\u003e11.8.5 Comparison with turbo codes 749\u003c\/p\u003e \u003cp\u003e11.9 Polar codes 751\u003c\/p\u003e \u003cp\u003e11.9.1 Encoding 752\u003c\/p\u003e \u003cp\u003eInternal CRC 753\u003c\/p\u003e \u003cp\u003eLLRs associated to code bits 754\u003c\/p\u003e \u003cp\u003e11.9.2 Tanner graph 755\u003c\/p\u003e \u003cp\u003e11.9.3 Decoding algorithms 757\u003c\/p\u003e \u003cp\u003eSuccessive cancellation decoding - the principle 758\u003c\/p\u003e \u003cp\u003eSuccessive cancellation decoding - the algorithm 760\u003c\/p\u003e \u003cp\u003eSuccessive cancellation list decoding 763\u003c\/p\u003e \u003cp\u003eOther decoding algorithms 765\u003c\/p\u003e \u003cp\u003e11.9.4 Frozen set design 765\u003c\/p\u003e \u003cp\u003eGenie-aided SC decoding 766\u003c\/p\u003e \u003cp\u003eDesign based on density evolution 767\u003c\/p\u003e \u003cp\u003eChannel polarisation 770\u003c\/p\u003e \u003cp\u003e11.9.5 Puncturing and shortening 770\u003c\/p\u003e \u003cp\u003ePuncturing 771\u003c\/p\u003e \u003cp\u003eShortening 772\u003c\/p\u003e \u003cp\u003eFrozen set design 774\u003c\/p\u003e \u003cp\u003e11.9.6 Performance 774\u003c\/p\u003e \u003cp\u003e11.10Milestones in channel coding 775\u003c\/p\u003e \u003cp\u003eBibliography 775\u003c\/p\u003e \u003cp\u003eAppendixes 781\u003c\/p\u003e \u003cp\u003e11.A Nonbinary parity check codes 782\u003c\/p\u003e \u003cp\u003eLinear codes 783\u003c\/p\u003e \u003cp\u003eParity check matrix 784\u003c\/p\u003e \u003cp\u003eCode generator matrix 785\u003c\/p\u003e \u003cp\u003eDecoding of nonbinary parity check codes 786\u003c\/p\u003e \u003cp\u003eCoset 786\u003c\/p\u003e \u003cp\u003eTwo conceptually simple decoding methods 787\u003c\/p\u003e \u003cp\u003eSyndrome decoding 787\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Trellis coded modulation 789\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Linear TCM for one and two-dimensional signal sets 790\u003c\/p\u003e \u003cp\u003e12.1.1 Fundamental elements 790\u003c\/p\u003e \u003cp\u003eBasic TCM scheme 792\u003c\/p\u003e \u003cp\u003eExample 792\u003c\/p\u003e \u003cp\u003e12.1.2 Set partitioning 795\u003c\/p\u003e \u003cp\u003e12.1.3 Lattices 797\u003c\/p\u003e \u003cp\u003e12.1.4 Assignment of symbols to the transitions in the trellis 802\u003c\/p\u003e \u003cp\u003e12.1.5 General structure of the encoder\/bit-mapper 807\u003c\/p\u003e \u003cp\u003eComputation of dfree 809\u003c\/p\u003e \u003cp\u003e12.2 Multidimensional TCM 811\u003c\/p\u003e \u003cp\u003eEncoding 812\u003c\/p\u003e \u003cp\u003eDecoding 815\u003c\/p\u003e \u003cp\u003e12.3 Rotationally invariant TCM schemes 817\u003c\/p\u003e \u003cp\u003eBibliography 817\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Techniques to achieve capacity 819\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Capacity achieving solutions for multicarrier systems 819\u003c\/p\u003e \u003cp\u003e13.1.1 Achievable bit rate of OFDM 819\u003c\/p\u003e \u003cp\u003e13.1.2 Waterfilling solution 820\u003c\/p\u003e \u003cp\u003eIterative solution 821\u003c\/p\u003e \u003cp\u003e13.1.3 Achievable rate under practical constraints 821\u003c\/p\u003e \u003cp\u003eEffective SNR and system margin in MC systems 822\u003c\/p\u003e \u003cp\u003eUniform power allocation and minimum rate per subchannel 823\u003c\/p\u003e \u003cp\u003e13.1.4 The bit and power loading problem revisited 824\u003c\/p\u003e \u003cp\u003eTransmission modes 824\u003c\/p\u003e \u003cp\u003eProblem formulation 825\u003c\/p\u003e \u003cp\u003eSome simplifying assumptions 826\u003c\/p\u003e \u003cp\u003eOn loading algorithms 826\u003c\/p\u003e \u003cp\u003eThe Hughes-Hartogs algorithm 827\u003c\/p\u003e \u003cp\u003eThe Krongold-Ramchandran Jones algorithm 827\u003c\/p\u003e \u003cp\u003eThe Chow-Cioffi Bingham algorithm 830\u003c\/p\u003e \u003cp\u003eComparison 832\u003c\/p\u003e \u003cp\u003e13.2 Capacity achieving solutions for single carrier systems 833\u003c\/p\u003e \u003cp\u003eAchieving capacity 837\u003c\/p\u003e \u003cp\u003eBibliography 838\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Synchronization 839\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 The problem of synchronization for QAM systems 839\u003c\/p\u003e \u003cp\u003e14.2 The phase-locked loop 841\u003c\/p\u003e \u003cp\u003e14.2.1 PLL baseband model 843\u003c\/p\u003e \u003cp\u003eLinear approximation 844\u003c\/p\u003e \u003cp\u003e14.2.2 Analysis of the PLL in the presence of additive noise 846\u003c\/p\u003e \u003cp\u003eNoise analysis using the linearity assumption 847\u003c\/p\u003e \u003cp\u003e14.2.3 Analysis of a second order PLL 848\u003c\/p\u003e \u003cp\u003e14.3 Costas loop 852\u003c\/p\u003e \u003cp\u003e14.3.1 PAM signals 852\u003c\/p\u003e \u003cp\u003e14.3.2 QAM signals 854\u003c\/p\u003e \u003cp\u003e14.4 The optimum receiver 856\u003c\/p\u003e \u003cp\u003eTiming recovery 858\u003c\/p\u003e \u003cp\u003eCarrier phase recovery 862\u003c\/p\u003e \u003cp\u003e14.5 Algorithms for timing and carrier phase recovery 863\u003c\/p\u003e \u003cp\u003e14.5.1 ML criterion 863\u003c\/p\u003e \u003cp\u003eAssumption of slow time varying channel 863\u003c\/p\u003e \u003cp\u003e14.5.2 Taxonomy of algorithms using the ML criterion 863\u003c\/p\u003e \u003cp\u003eFeedback estimators 865\u003c\/p\u003e \u003cp\u003eEarly-late estimators 866\u003c\/p\u003e \u003cp\u003e14.5.3 Timing estimators 867\u003c\/p\u003e \u003cp\u003eNon data aided 867\u003c\/p\u003e \u003cp\u003eNDA synchronization via spectral estimation 869\u003c\/p\u003e \u003cp\u003eData aided and data directed 871\u003c\/p\u003e \u003cp\u003eData and phase directed with feedback: differentiator scheme 874\u003c\/p\u003e \u003cp\u003eData and phase directed with feedback: Mueller \u0026amp; Muller scheme 874\u003c\/p\u003e \u003cp\u003eNon data aided with feedback 877\u003c\/p\u003e \u003cp\u003e14.5.4 Phasor estimators 878\u003c\/p\u003e \u003cp\u003eData and timing directed 878\u003c\/p\u003e \u003cp\u003eNon data aided forM-PSK signals 878\u003c\/p\u003e \u003cp\u003eData and timing directed with feedback 879\u003c\/p\u003e \u003cp\u003e14.6 Algorithms for carrier frequency recovery 880\u003c\/p\u003e \u003cp\u003e14.6.1 Frequency offset estimators 881\u003c\/p\u003e \u003cp\u003eNon data aided 881\u003c\/p\u003e \u003cp\u003eNon data aided and timing independent with feedback 882\u003c\/p\u003e \u003cp\u003eNon data aided and timing directed with feedback 883\u003c\/p\u003e \u003cp\u003e14.6.2 Estimators operating at the modulation rate 883\u003c\/p\u003e \u003cp\u003eData aided and data directed 884\u003c\/p\u003e \u003cp\u003eNon data aided forM-PSK 885\u003c\/p\u003e \u003cp\u003e14.7 Second-order digital PLL 885\u003c\/p\u003e \u003cp\u003e14.8 Synchronization in spread-spectrum systems 885\u003c\/p\u003e \u003cp\u003e14.8.1 The transmission system 885\u003c\/p\u003e \u003cp\u003eTransmitter 885\u003c\/p\u003e \u003cp\u003eOptimum receiver 886\u003c\/p\u003e \u003cp\u003e14.8.2 Timing estimators with feedback 887\u003c\/p\u003e \u003cp\u003eNon data aided: non coherent DLL 888\u003c\/p\u003e \u003cp\u003eNon data aided modified code tracking loop 888\u003c\/p\u003e \u003cp\u003eData and phase directed: coherent DLL 891\u003c\/p\u003e \u003cp\u003e14.9 Synchronization in OFDM 891\u003c\/p\u003e \u003cp\u003e14.9.1 Frame synchronization 891\u003c\/p\u003e \u003cp\u003eEffects of STO 891\u003c\/p\u003e \u003cp\u003eSchmidl and Cox algorithm 893\u003c\/p\u003e \u003cp\u003e14.9.2 Carrier frequency synchronization 894\u003c\/p\u003e \u003cp\u003eEstimator performance 895\u003c\/p\u003e \u003cp\u003eOther synchronization solutions 895\u003c\/p\u003e \u003cp\u003e14.10Synchronization in SC-FDMA 896\u003c\/p\u003e \u003cp\u003eBibliography 899\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Self-training equalization 901\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Problem definition and fundamentals 901\u003c\/p\u003e \u003cp\u003eMinimization of a special function 904\u003c\/p\u003e \u003cp\u003e15.2 Three algorithms for PAM systems 908\u003c\/p\u003e \u003cp\u003eThe Sato algorithm 908\u003c\/p\u003e \u003cp\u003eBenveniste-Goursat algorithm 909\u003c\/p\u003e \u003cp\u003eStop-and-go algorithm 909\u003c\/p\u003e \u003cp\u003eRemarks 910\u003c\/p\u003e \u003cp\u003e15.3 The contour algorithm for PAM systems 910\u003c\/p\u003e \u003cp\u003eSimplified realization of the contour algorithm 912\u003c\/p\u003e \u003cp\u003e15.4 Self-training equalization for partial response systems 913\u003c\/p\u003e \u003cp\u003eThe Sato algorithm 914\u003c\/p\u003e \u003cp\u003eThe contour algorithm 915\u003c\/p\u003e \u003cp\u003e15.5 Self-training equalization for QAM systems 917\u003c\/p\u003e \u003cp\u003eThe Sato algorithm 918\u003c\/p\u003e \u003cp\u003e15.5.1 Constant-modulus algorithm 919\u003c\/p\u003e \u003cp\u003eThe contour algorithm 921\u003c\/p\u003e \u003cp\u003eJoint contour algorithm and carrier phase tracking 922\u003c\/p\u003e \u003cp\u003e15.6 Examples of applications 924\u003c\/p\u003e \u003cp\u003eBibliography 928\u003c\/p\u003e \u003cp\u003eAppendixes 930\u003c\/p\u003e \u003cp\u003e15.A On the convergence of the contour algorithm 931\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Low-complexity demodulators 933\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Phase-shift keying 933\u003c\/p\u003e \u003cp\u003e16.1.1 Differential PSK 935\u003c\/p\u003e \u003cp\u003eError probability ofM-DPSK 936\u003c\/p\u003e \u003cp\u003e16.1.2 Differential encoding and coherent demodulation 937\u003c\/p\u003e \u003cp\u003eDifferentially encoded BPSK 937\u003c\/p\u003e \u003cp\u003eMultilevel case 938\u003c\/p\u003e \u003cp\u003e16.2 (D)PSK non-coherent receivers 940\u003c\/p\u003e \u003cp\u003e16.2.1 Baseband differential detector 940\u003c\/p\u003e \u003cp\u003e16.2.2 IF-band (1 Bit) differential detector 942\u003c\/p\u003e \u003cp\u003eSignal at detection point 944\u003c\/p\u003e \u003cp\u003e16.2.3 FM discriminator with integrate and dump filter 945\u003c\/p\u003e \u003cp\u003e16.3 Optimum receivers for signals with random phase 946\u003c\/p\u003e \u003cp\u003eML criterion 948\u003c\/p\u003e \u003cp\u003eImplementation of a non coherentML receiver 951\u003c\/p\u003e \u003cp\u003eError probability for a non coherent binary FSK system 953\u003c\/p\u003e \u003cp\u003ePerformance comparison of binary systems 956\u003c\/p\u003e \u003cp\u003e16.4 Frequency-based modulations 957\u003c\/p\u003e \u003cp\u003e16.4.1 Frequency shift keying 957\u003c\/p\u003e \u003cp\u003eCoherent demodulator 959\u003c\/p\u003e \u003cp\u003eNon coherent demodulator 959\u003c\/p\u003e \u003cp\u003eLimiter-discriminator FM demodulator 961\u003c\/p\u003e \u003cp\u003e16.4.2 Minimum-shift keying 961\u003c\/p\u003e \u003cp\u003ePower spectral density of CPFSK 963\u003c\/p\u003e \u003cp\u003ePerformance 963\u003c\/p\u003e \u003cp\u003eMSK with differential precoding 967\u003c\/p\u003e \u003cp\u003e16.4.3 Remarks on spectral containment 968\u003c\/p\u003e \u003cp\u003e16.5 Gaussian MSK 968\u003c\/p\u003e \u003cp\u003ePSD of GMSK 972\u003c\/p\u003e \u003cp\u003e16.5.1 Implementation of a GMSK scheme 973\u003c\/p\u003e \u003cp\u003eConfiguration I 973\u003c\/p\u003e \u003cp\u003eConfiguration II 974\u003c\/p\u003e \u003cp\u003eConfiguration III 975\u003c\/p\u003e \u003cp\u003e16.5.2 Linear approximation of a GMSK signal 977\u003c\/p\u003e \u003cp\u003ePerformance of GMSK 978\u003c\/p\u003e \u003cp\u003ePerformance in the presence of multipath 983\u003c\/p\u003e \u003cp\u003eBibliography 985\u003c\/p\u003e \u003cp\u003eAppendixes 985\u003c\/p\u003e \u003cp\u003e16.A Continuous phase modulation 986\u003c\/p\u003e \u003cp\u003eAlternative definition of CPM 986\u003c\/p\u003e \u003cp\u003eAdvantages of CPM 988\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Applications of interference cancellation 989\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 Echo and near–end crosstalk cancellation for PAM systems 990\u003c\/p\u003e \u003cp\u003eCrosstalk cancellation and full duplex transmission 991\u003c\/p\u003e \u003cp\u003ePolyphase structure of the canceller 992\u003c\/p\u003e \u003cp\u003eCanceller at symbol rate 993\u003c\/p\u003e \u003cp\u003eAdaptive canceller 994\u003c\/p\u003e \u003cp\u003eCanceller structure with distributed arithmetic 995\u003c\/p\u003e \u003cp\u003e17.2 Echo cancellation for QAM systems 998\u003c\/p\u003e \u003cp\u003e17.3 Echo cancellation for OFDM systems 1001\u003c\/p\u003e \u003cp\u003e17.4 Multiuser detection for VDSL 1004\u003c\/p\u003e \u003cp\u003e17.4.1 Upstream power back-off 1009\u003c\/p\u003e \u003cp\u003e17.4.2 Comparison of PBO methods 1011\u003c\/p\u003e \u003cp\u003eBibliography 1014\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Examples of communication systems 1019\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 The 5G cellular system 1019\u003c\/p\u003e \u003cp\u003e18.1.1 Cells in a wireless system 1019\u003c\/p\u003e \u003cp\u003e18.1.2 The release 15 of the 3GPP standard 1020\u003c\/p\u003e \u003cp\u003e18.1.3 Radio access network 1021\u003c\/p\u003e \u003cp\u003eTime-frequency plan 1022\u003c\/p\u003e \u003cp\u003eNR data transmission chain 1023\u003c\/p\u003e \u003cp\u003eOFDM numerology 1023\u003c\/p\u003e \u003cp\u003eChannel estimation 1024\u003c\/p\u003e \u003cp\u003e18.1.4 Downlink 1024\u003c\/p\u003e \u003cp\u003eSynchronization 1026\u003c\/p\u003e \u003cp\u003eInitial access or beam sweeping 1027\u003c\/p\u003e \u003cp\u003eChannel estimation 1028\u003c\/p\u003e \u003cp\u003eChannel state information reporting 1028\u003c\/p\u003e \u003cp\u003e18.1.5 Uplink 1029\u003c\/p\u003e \u003cp\u003eTransform precoding numerology 1029\u003c\/p\u003e \u003cp\u003eChannel estimation 1029\u003c\/p\u003e \u003cp\u003eSynchronization 1030\u003c\/p\u003e \u003cp\u003eTiming advance 1031\u003c\/p\u003e \u003cp\u003e18.1.6 Network slicing 1031\u003c\/p\u003e \u003cp\u003e18.2 GSM 1032\u003c\/p\u003e \u003cp\u003eRadio subsystem 1034\u003c\/p\u003e \u003cp\u003e18.3 Wireless local area networks 1036\u003c\/p\u003e \u003cp\u003eMedium access control protocols 1036\u003c\/p\u003e \u003cp\u003e18.4 DECT 1037\u003c\/p\u003e \u003cp\u003e18.5 Bluetooth 1040\u003c\/p\u003e \u003cp\u003e18.6 Transmission over unshielded twisted pairs 1041\u003c\/p\u003e \u003cp\u003e18.6.1 Transmission over UTP in the customer service area 1041\u003c\/p\u003e \u003cp\u003e18.6.2 High speed transmission over UTP in local area networks 1045\u003c\/p\u003e \u003cp\u003e18.7 Hybrid fibre\/coaxial cable networks 1048\u003c\/p\u003e \u003cp\u003eRanging and power adjustment in OFDMA systems 1051\u003c\/p\u003e \u003cp\u003eRanging and power adjustment for uplink transmission 1052\u003c\/p\u003e \u003cp\u003eBibliography 1053\u003c\/p\u003e \u003cp\u003eAppendixes 1057\u003c\/p\u003e \u003cp\u003e18.A Duplexing 1058\u003c\/p\u003e \u003cp\u003eThree methods 1058\u003c\/p\u003e \u003cp\u003e18.B Deterministic access methods 1059\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 High-speed communications over twisted-pair cables 1063\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e19.1 Quaternary partial response class-IV system 1063\u003c\/p\u003e \u003cp\u003eAnalog filter design 1064\u003c\/p\u003e \u003cp\u003eReceived signal and adaptive gain control 1064\u003c\/p\u003e \u003cp\u003eNear-end crosstalk cancellation 1065\u003c\/p\u003e \u003cp\u003eDecorrelation filter 1065\u003c\/p\u003e \u003cp\u003eAdaptive equalizer 1065\u003c\/p\u003e \u003cp\u003eCompensation of the timing phase drift 1066\u003c\/p\u003e \u003cp\u003eAdaptive equalizer coefficient adaptation 1066\u003c\/p\u003e \u003cp\u003eConvergence behaviour of the various algorithms 1067\u003c\/p\u003e \u003cp\u003e19.1.1 VLSI implementation 1069\u003c\/p\u003e \u003cp\u003eAdaptive digital NEXT canceller 1069\u003c\/p\u003e \u003cp\u003eAdaptive digital equalizer 1071\u003c\/p\u003e \u003cp\u003eTiming control 1075\u003c\/p\u003e \u003cp\u003eViterbi detector 1077\u003c\/p\u003e \u003cp\u003e19.2 Dual duplex system 1077\u003c\/p\u003e \u003cp\u003eDual duplex transmission 1077\u003c\/p\u003e \u003cp\u003ePhysical layer control 1080\u003c\/p\u003e \u003cp\u003eCoding and decoding 1080\u003c\/p\u003e \u003cp\u003e19.2.1 Signal processing functions 1083\u003c\/p\u003e \u003cp\u003eThe 100BASE-T2 transmitter 1083\u003c\/p\u003e \u003cp\u003eThe 100BASE-T2 receiver 1084\u003c\/p\u003e \u003cp\u003eComputational complexity of digital receive filters 1086\u003c\/p\u003e \u003cp\u003eBibliography 1087\u003c\/p\u003e \u003cp\u003eAppendixes 1087\u003c\/p\u003e \u003cp\u003e19.A Interference suppression 1088\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Electronics \u0026amp; communications engineering [\u003ca title=\"See our other books on Electronics \u0026amp; communications engineering\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Electronics%20\u0026amp;%20communications%20engineering%20%5BTJ%5D%22\"\u003eTJ\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand New","offer_id":52428625412376,"sku":"9781119567967","price":116.19,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781119567967.jpg?v=1784682239","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/algorithms-for-communications-systems-and-their-applications-hardback-9781119567967","provider":"Freshly Printed Books","version":"1.0","type":"link"}