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Wireless Communications


Wireless Communications

Principles, Theory and Methodology
1. Aufl.

von: Keith Q. T. Zhang

83,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 13.10.2015
ISBN/EAN: 9781119113287
Sprache: englisch
Anzahl Seiten: 448

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Beschreibungen

<p><strong>Understand the mechanics of wireless communication</strong> <p><em>Wireless Communications: Principles, Theory and Methodology</em> offers a detailed introduction to the technology. Comprehensive and well-rounded coverage includes signaling, transmission, and detection, including the mathematical and physics principles that underlie the technology's mechanics. Problems with modern wireless communication are discussed in the context of applied skills, and the various approaches to solving these issues offer students the opportunity to test their understanding in a practical manner. With in-depth explanations and a practical approach to complex material, this book provides students with a clear understanding of wireless communication technology.
<p>Preface xvii</p> <p>Acknowledgments xix</p> <p><b>1 Introduction 1</b></p> <p>1.1 Resources for wireless communications 3</p> <p>1.2 Shannon’s theory 3</p> <p>1.3 Three challenges 4</p> <p>1.4 Digital modulation versus coding 5</p> <p>1.5 Philosophy to combat interference 6</p> <p>1.6 Evolution of processing strategy 7</p> <p>1.7 Philosophy to exploit two-dimensional random fields 7</p> <p>1.8 Cellular: Concept, Evolution, and 5G 8</p> <p>1.9 The structure of this book 10</p> <p>1.10 Repeatedly used abbreviations and math symbols 10</p> <p>Problems 12</p> <p>References 12</p> <p><b>2 Mathematical Background 14</b></p> <p>2.1 Introduction 14</p> <p>2.2 Congruence mapping and signal spaces 14</p> <p>2.3 Estimation methods 19</p> <p>2.3.1 Maximum likelihood estimation (MLE) 20</p> <p>2.3.2 Maximum a posteriori estimation 21</p> <p>2.4 Commonly used distributions in wireless 21</p> <p>2.4.1 Chi-square distributions 21</p> <p>2.4.2 Gamma distribution 25</p> <p>2.4.3 Nakagami distribution 26</p> <p>2.4.4 Wishart distribution 26</p> <p>2.5 The calculus of variations 28</p> <p>2.6 Two inequalities for optimization 29</p> <p>2.6.1 Inequality for Rayleigh quotient 29</p> <p>2.6.2 Hadamard inequality 29</p> <p>2.7 Q-function 30</p> <p>2.8 The CHF method and its skilful applications 32</p> <p>2.8.1 Gil-Pelaez’s lemma 32</p> <p>2.8.2 Random variables in denominators 32</p> <p>2.8.3 Parseval’s theorem 33</p> <p>2.9 Matrix operations and differentiation 33</p> <p>2.9.1 Decomposition of a special determinant 33</p> <p>2.9.2 Higher order derivations 33</p> <p>2.9.3 Kronecker product 34</p> <p>2.10 Additional reading 34</p> <p>Problems 34</p> <p>References 35</p> <p><b>3 Channel Characterization 37</b></p> <p>3.1 Introduction 37</p> <p>3.2 Large-scale propagation loss 38</p> <p>3.2.1 Free-space propagation 39</p> <p>3.2.2 Average large-scale path loss in mobile 40</p> <p>3.2.3 Okumura’s model 40</p> <p>3.2.4 Hata’s model 42</p> <p>3.2.5 JTC air model 42</p> <p>3.3 Lognormal shadowing 43</p> <p>3.4 Multipath characterization for local behavior 44</p> <p>3.4.1 An equivalent bandwidth 44</p> <p>3.4.2 Temporal evolution of path coefficients 49</p> <p>3.4.3 Statistical description of local fluctuation 50</p> <p>3.4.4 Complex Gaussian distribution 50</p> <p>3.4.5 Nakagami fading 51</p> <p>3.4.6 Clarke–Jakes model 52</p> <p>3.5 Composite model to incorporate multipath and shadowing 53</p> <p>3.6 Example to illustrate the use of various models 54</p> <p>3.6.1 Static design 54</p> <p>3.6.2 Dynamic design 55</p> <p>3.6.3 Large-scale design 56</p> <p>3.7 Generation of correlated fading channels 56</p> <p>3.7.1 Rayleigh fading with given covariance structure 56</p> <p>3.7.2 Correlated Nakagami fading 57</p> <p>3.7.3 Complex correlated Nakagami channels 62</p> <p>3.7.4 Correlated lognormal shadowing 62</p> <p>3.7.5 Fitting a lognormal sum 64</p> <p>3.8 Summary 65</p> <p>3.9 Additional reading 66</p> <p>Problems 66</p> <p>References 68</p> <p><b>4 Digital Modulation 70</b></p> <p>4.1 Introduction 70</p> <p>4.2 Signals and signal space 71</p> <p>4.3 Optimal MAP and ML receivers 72</p> <p>4.4 Detection of two arbitrary waveforms 74</p> <p>4.5 MPSK 77</p> <p>4.5.1 BPSK 77</p> <p>4.5.2 QPSK 79</p> <p>4.5.3 MPSK 81</p> <p>4.6 <i>M-ary</i> QAM 85</p> <p>4.7 Noncoherent scheme–differential MPSK 88</p> <p>4.7.1 Differential BPSK 88</p> <p>4.7.2 Differential MPSK 89</p> <p>4.7.3 Connection to MPSK 89</p> <p>4.8 MFSK 90</p> <p>4.8.1 BFSK with coherent detection 90</p> <p>4.9 Noncoherent MFSK 92</p> <p>4.10 Bit error probability versus symbol error probability 93</p> <p>4.10.1 Orthogonal MFSK 93</p> <p>4.10.2 Square M-QAM 93</p> <p>4.10.3 Gray-mapped MPSK 94</p> <p>4.11 Spectral efficiency 96</p> <p>4.12 Summary of symbol error probability for various schemes 97</p> <p>4.13 Additional reading 98</p> <p>Problems 98</p> <p>References 102</p> <p><b>5 Minimum Shift Keying 103</b></p> <p>5.1 Introduction 103</p> <p>5.2 MSK 104</p> <p>5.3 de Buda’s approach 105</p> <p>5.3.1 The basic idea and key equations 105</p> <p>5.4 Properties of MSK signals 106</p> <p>5.5 Understanding MSK 108</p> <p>5.5.1 MSK as FSK 108</p> <p>5.5.2 MSK as offset PSK 109</p> <p>5.6 Signal space 109</p> <p>5.7 MSK power spectrum 110</p> <p>5.8 Alternative scheme–differential encoder 113</p> <p>5.9 Transceivers for MSK signals 115</p> <p>5.10 Gaussian-shaped MSK 116</p> <p>5.11 Massey’s approach to MSK 117</p> <p>5.11.1 Modulation 117</p> <p>5.11.2 Receiver structures and error performance 117</p> <p>5.12 Summary 119</p> <p>Problems 119</p> <p>References 120</p> <p><b>6 Channel Coding 121</b></p> <p>6.1 Introduction and philosophical discussion 121</p> <p>6.2 Preliminary of Galois fields 123</p> <p>6.2.1 Fields 123</p> <p>6.2.2 Galois fields 124</p> <p>6.2.3 The primitive element of GF(<i>q</i>) 124</p> <p>6.2.4 Construction of GF(<i>q</i>) 124</p> <p>6.3 Linear block codes 126</p> <p>6.3.1 Syndrome test 129</p> <p>6.3.2 Error-correcting capability 132</p> <p>6.4 Cyclic codes 134</p> <p>6.4.1 The order of elements: a concept in GF(<i>q</i>) 134</p> <p>6.4.2 Cyclic codes 136</p> <p>6.4.3 Generator, parity check, and syndrome polynomial 137</p> <p>6.4.4 Systematic form 138</p> <p>6.4.5 Syndrome and decoding 140</p> <p>6.5 Golay code 141</p> <p>6.6 BCH codes 141</p> <p>6.6.1 Generating BCH codes 142</p> <p>6.6.2 Decoding BCH codes 143</p> <p>6.7 Convolutional codes 146</p> <p>6.7.1 Examples 146</p> <p>6.7.2 Code generation 147</p> <p>6.7.3 Markovian property 148</p> <p>6.7.4 Decoding with hard-decision Viterbi algorithm 150</p> <p>6.7.5 Transfer function 152</p> <p>6.7.6 Choice of convolutional codes 155</p> <p>6.7.7 Philosophy behind decoding strategies 156</p> <p>6.7.8 Error performance of convolutional decoding 160</p> <p>6.8 Trellis-coded modulation 162</p> <p>6.9 Summary 166</p> <p>Problems 166</p> <p>References 170</p> <p><b>7 Diversity Techniques 171</b></p> <p>7.1 Introduction 171</p> <p>7.2 Idea behind diversity 173</p> <p>7.3 Structures of various diversity combiners 174</p> <p>7.3.1 MRC 174</p> <p>7.3.2 EGC 175</p> <p>7.3.3 SC 176</p> <p>7.4 PDFs of output SNR 176</p> <p>7.4.1 MRC 176</p> <p>7.4.2 EGC 178</p> <p>7.4.3 SC 178</p> <p>7.5 Average SNR comparison for various schemes 179</p> <p>7.5.1 MRC 179</p> <p>7.5.2 EGC 180</p> <p>7.5.3 SC 181</p> <p>7.6 Methods for error performance analysis 182</p> <p>7.6.1 The chain rule 182</p> <p>7.6.2 The CHF method 183</p> <p>7.7 Error probability of MRC 183</p> <p>7.7.1 Error performance in nondiversity Rayleigh fading 183</p> <p>7.7.2 MRC in i.i.d. Rayleigh fading 185</p> <p>7.7.3 MRC in correlated Rayleigh fading 187</p> <p>7.7.4 P<sub>e</sub> for generic channels 188</p> <p>7.8 Error probability of EGC 189</p> <p>7.8.1 Closed-form solution to order-3 EGC 189</p> <p>7.8.2 General EGC error performance 191</p> <p>7.8.3 Diversity order of EGC 192</p> <p>7.9 Average error performance of SC in Rayleigh fading 193</p> <p>7.9.1 Pure SC 193</p> <p>7.9.2 Generalized SC 195</p> <p>7.10 Performance of diversity MDPSK systems 196</p> <p>7.10.1 Nondiversity MDPSK in Rayleigh fading 196</p> <p>7.10.2 Remarks on use of the chain rule 199</p> <p>7.10.3 Linear prediction to fit the chain rule 199</p> <p>7.10.4 Alternative approach for diversity MDPSK 200</p> <p>7.11 Noncoherent MFSK with diversity reception 201</p> <p>7.12 Summary 203</p> <p>Problems 204</p> <p>References 206</p> <p><b>8 Processing Strategies for Wireless Systems 209</b></p> <p>8.1 Communication problem 209</p> <p>8.2 Traditional strategy 210</p> <p>8.3 Paradigm of orthogonality 211</p> <p>8.4 Turbo processing principle 211</p> <p>Problems 213</p> <p>References 213</p> <p><b>9 Channel Equalization 214</b></p> <p>9.1 Introduction 214</p> <p>9.2 Pulse shaping for ISI-free transmission 215</p> <p>9.3 ISI and equalization strategies 216</p> <p>9.4 Zero-forcing equalizer 217</p> <p>9.4.1 Orthogonal projection 217</p> <p>9.4.2 ZFE 219</p> <p>9.4.3 Equivalent discrete ZFE receiver 221</p> <p>9.5 MMSE linear equalizer 225</p> <p>9.6 Decision-feedback equalizer (DFE) 227</p> <p>9.7 SNR comparison and error performance 229</p> <p>9.8 An example 230</p> <p>9.9 Spectral factorization 233</p> <p>9.10 Summary 234</p> <p>Problems 234</p> <p>References 236</p> <p><b>10 Channel Decomposition Techniques 238</b></p> <p>10.1 Introduction 238</p> <p>10.2 Channel matrix of ISI channels 239</p> <p>10.3 Idea of channel decomposition 239</p> <p>10.4 QR-decomposition-based Tomlinson–Harashima equalizer 240</p> <p>10.5 The GMD equalizer 242</p> <p>10.6 OFDM for time-invariant channel 243</p> <p>10.6.1 Channel SVD 243</p> <p>10.6.2 OFDM: a multicarrier modulation technique 244</p> <p>10.6.3 PAPR and statistical behavior of OFDM 246</p> <p>10.6.4 Combating PAPR 247</p> <p>10.7 Cyclic prefix and circulant channel matrix 248</p> <p>10.8 OFDM receiver 251</p> <p>10.9 Channel estimation 251</p> <p>10.10 Coded OFDM 252</p> <p>10.11 Additional reading 252</p> <p>Problems 252</p> <p>References 254</p> <p><b>11 Turbo Codes and Turbo Principle 257</b></p> <p>11.1 Introduction and philosophical discussion 257</p> <p>11.1.1 Generation of random-like long codes 258</p> <p>11.1.2 The turbo principle 259</p> <p>11.2 Two-device mechanism for iteration 259</p> <p>11.3 Turbo codes 261</p> <p>11.3.1 A turbo encoder 261</p> <p>11.3.2 RSC versus NRC 261</p> <p>11.3.3 Turbo codes with two constituent RSC encoders 264</p> <p>11.4 BCJR algorithm 266</p> <p>11.5 Turbo decoding 270</p> <p>11.6 Illustration of turbo-code performance 270</p> <p>11.7 Extrinsic information transfer (EXIT) charts 272</p> <p>11.8 Convergence and fixed points 276</p> <p>11.9 Statistics of LLRs 277</p> <p>11.9.1 Mean and variance of LLRs 277</p> <p>11.9.2 Mean and variance of hard decision 277</p> <p>11.10 Turbo equalization 278</p> <p>11.11 Turbo CDMA 281</p> <p>11.12 Turbo IDMA 283</p> <p>11.13 Summary 283</p> <p>Problems 284</p> <p>References 287</p> <p><b>12 Multiple-Access Channels 289</b></p> <p>12.1 Introduction 289</p> <p>12.2 Typical MA schemes 291</p> <p>12.3 User space of multiple-access 292</p> <p>12.3.1 User spaces for TDMA 293</p> <p>12.3.2 User space for CDMA 294</p> <p>12.3.3 User space for MC-CDMA 294</p> <p>12.3.4 MC-DS-CDMA 295</p> <p>12.3.5 User space for OFDMA 296</p> <p>12.3.6 Unified framework for orthogonal multiaccess schemes 297</p> <p>12.4 Capacity of multiple-access channels 298</p> <p>12.4.1 Flat fading 299</p> <p>12.4.2 Frequency-selective fading 300</p> <p>12.5 Achievable MI by various MA schemes 301</p> <p>12.5.1 AWGN channel 301</p> <p>12.5.2 Flat-fading MA channels 304</p> <p>12.6 CDMA-IS-95 306</p> <p>12.6.1 Forward link 306</p> <p>12.6.2 Reverse link 308</p> <p>12.7 Processing gain of spreading spectrum 310</p> <p>12.8 IS-95 downlink receiver and performance 310</p> <p>12.9 IS-95 uplink receiver and performance 317</p> <p>12.10 3GPP-LTE uplink 318</p> <p>12.11 <i>m</i>-Sequences 321</p> <p>12.11.1 PN sequences of a shorter period 322</p> <p>12.11.2 Conditions for <i>m</i>-sequence generators 322</p> <p>12.11.3 Properties of <i>m</i>-sequence 323</p> <p>12.11.4 Ways to generate PN sequences 324</p> <p>12.12 Walsh sequences 327</p> <p>12.13 CAZAC sequences for LTE-A 327</p> <p>12.14 Nonorthogonal MA schemes 329</p> <p>12.15 Summary 330</p> <p>Problems 330</p> <p>References 334</p> <p><b>13 Wireless MIMO Systems 337</b></p> <p>13.1 Introduction 337</p> <p>13.2 Signal model and mutual information 338</p> <p>13.3 Capacity with CSIT 339</p> <p>13.4 Ergodic capacity without CSIT 340</p> <p>13.4.1 i.i.d. MIMO Rayleigh channels 341</p> <p>13.4.2 Ergodic capacity for correlated MIMO channels 341</p> <p>13.5 Capacity: asymptotic results 344</p> <p>13.5.1 Asymptotic capacity with large MIMO 344</p> <p>13.5.2 Large SNR approximation 345</p> <p>13.6 Optimal transceivers with CSIT 346</p> <p>13.6.1 Optimal eigenbeam transceiver 347</p> <p>13.6.2 Distributions of the largest eigenvalue 348</p> <p>13.6.3 Average symbol-error probability 350</p> <p>13.6.4 Average mutual information of MIMO-MRC 350</p> <p>13.6.5 Average symbol-error probability 351</p> <p>13.7 Receivers without CSIT 352</p> <p>13.8 Optimal receiver 352</p> <p>13.9 Zero-forcing MIMO receiver 353</p> <p>13.10 MMSE receiver 355</p> <p>13.11 VBLAST 357</p> <p>13.11.1 Alternative VBLAST based on QR decomposition 358</p> <p>13.12 Space–time block codes 359</p> <p>13.13 Alamouti codes 359</p> <p>13.13.1 One receive antenna 359</p> <p>13.13.2 Two receive antennas 360</p> <p>13.14 General space–time codes 362</p> <p>13.14.1 Exact pairwise error probability 363</p> <p>13.15 Information lossless space–time codes 365</p> <p>13.16 Multiplexing gain versus diversity gain 365</p> <p>13.16.1 Two frameworks 366</p> <p>13.16.2 Derivation of the DMT 367</p> <p>13.16.3 Available DFs for diversity 368</p> <p>13.17 Summary 370</p> <p>Problems 370</p> <p>References 374</p> <p><b>14 Cooperative Communications 377</b></p> <p>14.1 A historical review 377</p> <p>14.2 Relaying 378</p> <p>14.3 Cooperative communications 379</p> <p>14.3.1 Cooperation protocols 380</p> <p>14.3.2 Diversity analysis 382</p> <p>14.3.3 Resource allocation 384</p> <p>14.4 Multiple-relay cooperation 385</p> <p>14.4.1 Multi-relay over frequency-selective channels 386</p> <p>14.4.2 Optimal matrix structure 389</p> <p>14.4.3 Power allocation 390</p> <p>14.5 Two-way relaying 395</p> <p>14.5.1 Average power constraints 397</p> <p>14.5.2 Instantaneous power constraint 399</p> <p>14.6 Multi-cell MIMO 400</p> <p>14.7 Summary 401</p> <p>Problems 401</p> <p>References 402</p> <p><b>15 Cognitive Radio 405</b></p> <p>15.1 Introduction 405</p> <p>15.2 Spectrum sensing for spectrum holes 406</p> <p>15.3 Matched filter versus energy detector 407</p> <p>15.3.1 Matched-filter detection 407</p> <p>15.3.2 Energy detection 408</p> <p>15.4 Detection of random primary signals 410</p> <p>15.4.1 Energy-based detection 411</p> <p>15.4.2 Maximum likelihood ratio test 412</p> <p>15.4.3 Eigenvalue ratio test 413</p> <p>15.5 Detection without exact knowledge of σ<sup>2</sup>n 414</p> <p>15.5.1 LRT with σ<sup>2</sup>n 414</p> <p>15.5.2 LRT without noise-level reference 415</p> <p>15.6 Cooperative spectrum sensing 416</p> <p>15.7 Standardization of CR networks 418</p> <p>15.8 Experimentation and commercialization of CR systems 418</p> <p>Problems 419</p> <p>References 420</p> <p>Index 423</p>
<p>Keith Q.T. Zhang, electronics engineer, educator. Achievements include research in wireless communications. Member of Institute of Electrical and Electronics Engineers (associate editor letters 2000-2008). B. England, Tsinghua University, Beijing, 1970. Doctor of Philosophy, McMaster University, Hamilton, Ontario, Canada, 1985. Senior member technical staff Spar Aerospace Ltd, Satellite Communications Division, Montreal, 1991—1993. Professor Ryerson, Toronto, Canada, 1993—2002, City University, Hong Kong, since 2000.</p>

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