B. P. Lathi, Zhi Ding - Modern Digital and Analog Communication Systems-Oxford University Press (2009)

Recommendations

Info

7.4 Scrambling 355TABLE 7.2Binary Duobinary Signaling with Differential EncodingTime k 0 2 3 4 5 6 7 8 9 10 11 12 13h 1 0 1 0 0 0 0 1 1Pk 0 0 0 0 0 0 0 0 0ak -1 1 -1 -1 -1 -1 -1 -1 -1 I -1bk 0 0 -2 0 0 -2 -2 -2 0 2 0 0 0Detected bits 0 0 0 0 0Therefore, the incorporation of differential encoding with duobinary signaling not only simplifiesthe decision rule but also makes the decision independent of the previous digit andeliminates error propagation. In Table 7.2, the example of Table 7.1 is recalculated withdifferential encoding. The decoding relationship of Eq. (7.45) is clearly shown in this example.The differential encoding defined for binary information symbols can be convenientlygeneralized to nonbinary symbols. When the information symbols I k are M -ary, the only changeto the differential encoding block is to replace "modulo 2" with "modulo M ." Similarly, othergeneralized partial-response signaling such as the modified duobinary must also face the errorpropagation problem at its detection. A suitable type of differential encoding can be similarlyadopted to prevent error propagation.7.3.7 Pulse GenerationA pulse p(t) satisfying a Nyquist criterion can be generated as the unit impulse response of afilter with transfer function P(f). This will not always be easy. A better method is to generatethe waveform directly, using a transversal filter (tapped delay line) discussed here. The pulsep(t) to be generated is sampled with a sufficiently small sampling interval T, (Fig. 7.19a),and the filter tap gains are set in proportion to these sample values in sequence, as shownin Fig. 7. 19b. When a narrow rectangular pulse with the width T s , the sampling interval, isapplied at the input of the transversal filter, the output will be a staircase approximation ofp(t). This output, when passed through a low-pass filter, is smoothed out. The approximationcan be improved by reducing the pulse sampling interval T s .It should be stressed once again that the pulses arriving at the detector input of the receiverneed to meet the desired Nyquist criterion. Hence, the transmitted pulses should be so shapedthat after passing through the channel, they are received in the desired (Nyquist) form. Inpractice, however, pulses need not be shaped rigidly at the transmitter. The final shaping canbe carried out by an equalizer at the receiver, as discussed later (Sec. 7.5).7.4 SCRAMBLINGIn general, a scrambler tends to make the data more random by removing long strings ofls or Os. Scrambling can be helpful in timing extraction by removing long strings of Os inbinary data. Scramblers, however, are primarily used for preventing unauthorized access tothe data, and they are optimized for that purpose. Such optimization may actually result ingeneration of a long string of zeros in the data. The digital network must be able to cope withthese long zero strings by using the zero replacement techniques discussed in Sec. 7.2.
Fi g ure 7.19Pulse generationby transversalfilter.p(t), __-□- Ts(a)Smoot h ing--- filter ,__ ___ _Fi gure 7.20(a) Scrambler.(b) Descrambler.3232I---- (±) ---------<►STTR__,► C lock recovery(a)(b)
Page 1 and 2:
INTERNATIONAL FOURTH EDITIONModern
Page 3 and 4:
Oxford University Press, Inc., publ
Page 6 and 7:
CONTENTSPREFACE xvii1INTRODUCTION1
Page 8 and 9:
Contents1x3 .6 SIGNAL DISTORTION OV
Page 10 and 11:
7PRINCIPLES OF DIGITAL DATATRANSMIS
Page 12 and 13:
Contentsxiii1 0.3 COHERENT RECEIVER
Page 14 and 15:
Contentsxv13.3 ERROR-FREE COMMUNICA
Page 16 and 17:
PREFACE (INTERNATIONALEDITION)The c
Page 18 and 19:
Preface (International Edition)xixM
Page 20:
Preface (International Edition)xx,m
Page 24 and 25:
l INTRODUCTIONOver the past decade,
Page 26 and 27:
1 . 1 Communication Systems 3Figure
Page 28 and 29:
1 .2 Analog and Di gital Messag es
Page 30 and 31:
l .2 Analog and Digital Messages 7H
Page 32 and 33:
1 .3 Channel Effect, Signal-to-Nois
Page 34 and 35:
1 .4 Modulation and Detection 11In
Page 36 and 37:
1.5 Digital Source Coding and Error
Page 38 and 39:
1.6 A Brief Historical Review of Mo
Page 40 and 41:
1.6 A Brief Historical Review of Mo
Page 42 and 43:
References 19to transmit the tones
Page 44 and 45:
2.1 Size of a Signal 21Figure 2.1Ex
Page 46 and 47:
2.2 Classification of Signals 233.
Page 48 and 49:
2.2 Classification of Signals 25Fig
Page 50 and 51:
2.3 Unit Impulse Signal 27Figure 2.
Page 52 and 53:
2.4 Signals Versus Vectors 29Fi gur
Page 54 and 55:
2 .4 Signals Versus Vectors 31andf/
Page 56 and 57:
2.4 Signals Versus Vectors 33functi
Page 58 and 59:
2 .5 Correlation of Signals 35Thus,
Page 60 and 61:
2.6 Orthogonal Signal Set 37orthogo
Page 62 and 63:
2 .7 The Exponential Fourier Series
Page 64 and 65:
2 .7 The Exponential Fourier Series
Page 66 and 67:
2.7 The Exponential Fourier Series
Page 68 and 69:
2.7 The Exponential Fourier Series
Page 70 and 71:
2.8 MATLAB Exercises 47Basic Signal
Page 72 and 73:
2.8 MATLAB Exercises 49% (file name
Page 74 and 75:
2.8 MATLAB Exercises 51subplot (231
Page 76 and 77:
2.8 MATLAB Exercises53Figure 2.22Ex
Page 78 and 79:
Problems 55Figure P.2. 1-2x(t)y(t):
Page 80 and 81:
Problems 57Figure P.2.3-3g(t)t -han
Page 82 and 83:
Problems 592.5-1 Find the correlati
Page 84 and 85:
Problems 61(b) Determine the odd an
Page 86 and 87:
3 .1 Aperiodic Signal Representatio
Page 88 and 89:
3.1 Aperiodic Signal Representation
Page 90 and 91:
3 .1 Aperiodic Signal Representatio
Page 92 and 93:
3.2 Transforms of Some Useful Funct
Page 94 and 95:
Page 96 and 97:
Page 98 and 99:
3.3 Some Properties of the Fourier
Page 100 and 101:
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
3 .3 .5 Frequency-Shifting Property
Page 108 and 109:
3 .3 Some Properties of the Fourier
Page 110 and 111:
Here D n = I/To. Therefore, from Eq
Page 112 and 113:
Page 114 and 115:
TABLE 3.2Properties of Fourier Tran
Page 116 and 117:
3.4 Signal Transmission Through a L
Page 118 and 119:
3.5 Ideal versus Practical Filters
Page 120 and 121:
3.6 Signal Distortion Over a Commun
Page 122 and 123:
Page 124 and 125:
Page 126 and 127:
3 .7 Signal Energy and Energy Spect
Page 128 and 129:
Figure 3.32Interpretation ofthe ene
Page 130 and 131:
3.7 Signal Energy and Energy Spectr
Page 132 and 133:
3.7 Signal Energy and Energy Spectr
Page 134 and 135:
3.8 Signal Power and Power Spectral
Page 136 and 137:
Page 138 and 139:
Page 140 and 141:
Page 142 and 143:
3.9 Numerical Computation of Fourie
Page 144 and 145:
3.9 Numerical Computation of Fourie
Page 146 and 147:
3.10 MATLAB Exercises 123Using the
Page 148 and 149:
3 . 10 MATLAB Exercises 125In this
Page 150 and 151:
3. 10 MATLAB Exercises 127Observe t
Page 152 and 153:
3.10 MATLAB Exercises 129We multipl
Page 154 and 155:
This is the trigonometric form of t
Page 156 and 157:
3.3-2 The Fourier transform of the
Page 158 and 159:
Problems 1353.3-7 Use the frequency
Page 160 and 161:
Problems 137(b) Discuss how this ch
Page 162 and 163:
Problems 139the autocorrelation fun
Page 164 and 165:
4.1 Baseband Ve rsus Carrier Commun
Page 166 and 167:
4.2 Double-Sideband Amplitude Modul
Page 168 and 169:
Page 170 and 171:
Page 172 and 173:
Page 174 and 175:
4.3 Amplitude Modulation (AM) 151Th
Page 176 and 177:
4.3 Amplitude Modulation (AM) 153Fi
Page 178 and 179:
4.3 Amplitude Modulation (AM) 155In
Page 180 and 181:
4.3 Amplitude Modulation (AM) 157Fi
Page 182 and 183:
either utilize or remove the 100% s
Page 184 and 185:
4.4 Bandwidth-Efficient Amplitude M
Page 186 and 187:
Page 188 and 189:
Page 190 and 191:
4.5 Amplitude Modulations: Vestigia
Page 192 and 193:
4.5 Amplitude Modulations: Vestigia
Page 194 and 195:
4.6 Local Carrier Synchronization 1
Page 196 and 197:
4.8 Phase-locked Loop and Some Appl
Page 198 and 199:
Page 200 and 201:
Page 202 and 203:
Page 204 and 205:
4. 9 MATLAB Exercises 181whereE(t)
Page 206 and 207:
4. 9 MATLAB Exercises 183Fi g ure 4
Page 208 and 209:
4. 9 MATLAB Exercises 185s_dem=s_ds
Page 210 and 211:
4. 9 MATLAB Exercises187Figure 4.35
Page 212 and 213:
4.9 MATLAB Exercises189Figure 4.36
Page 214 and 215:
4. 9 MATLAB Exercises 191subplot (2
Page 216 and 217:
Figure 4.41Frequencydomain signalsd
Page 218 and 219:
title ('second demodulator output '
Page 220 and 221:
Problems 1974.2-5 You are asked to
Page 222 and 223:
Problems 1994.3-3 For the AM signal
Page 224 and 225:
Problems 201Figure P.4.4·6'PL5B (t
Page 226 and 227:
5.1 Nonlinear Modulation 203the AM
Page 228 and 229:
Figure 5.2Phase andfrequencymodulat
Page 230 and 231:
5.1 Nonlinear Modulation 207Dividin
Page 232 and 233:
5.2 Bandwidth of Angle-Modulated Wa
Page 234 and 235:
Page 236 and 237:
Page 238 and 239:
Page 240 and 241:
Page 242 and 243:
Alternately, the deviation ratio f3
Page 244 and 245:
Page 246 and 247:
5.3 Generating FM Waves 223Figure 5
Page 248 and 249:
5.3 Generating FM Waves 225Indirect
Page 250 and 251:
5.3 Generating FM Waves 227Amplitud
Page 252 and 253:
5.3 Generating FM Waves 229We may a
Page 254 and 255:
5.4 Demodulation of FM Signals 23 1
Page 256 and 257:
5.4 Demodulation of FM Signals 233B
Page 258 and 259:
5.5 Effects of Nonlinear Distortion
Page 260 and 261:
5.5 Effects of Nonlinear Distortion
Page 262 and 263:
5.6 Superheterodyne Analog AM/FM Re
Page 264 and 265:
5.7 FM BROADCASTING SYSTEM5.7 FM Br
Page 266 and 267:
5.8 MATLAB Exercises 243Figure 5.19
Page 268 and 269:
5.8 MATLAB Exercises 245title ('PM
Page 270 and 271:
Problems 2476. H. R. Slotten, '"Rai
Page 272 and 273:
Problems 249Figure P.5.4-15.4-1 (a)
Page 274 and 275:
6SAMPLING ANDANALOG-TO-DIGITALCONVE
Page 276 and 277:
6. 1 Sampling Theorem 253by nfs . T
Page 278 and 279:
6.1 Sampling Theorem 255identical t
Page 280 and 281:
6. 1 Sampling Theorem 257Figure 6.5
Page 282 and 283:
6.1 Sampling Theorem 259Figure 6.7S
Page 284 and 285:
6. 1 Sampling Theorem 261known as s
Page 286 and 287:
6.1 Sampling Theorem 263Figure 6.9(
Page 288 and 289:
6. l Sampling Theorem 265whereq T s
Page 290 and 291:
6.1 Sampling Theorem 267Moreover, t
Page 292 and 293:
6.2 Pulse Code Modulation (PCM) 269
Page 294 and 295:
Page 296 and 297:
6.2 Pulse Code Modulation {PCM) 273
Page 298 and 299:
Page 300 and 301:
Page 302 and 303:
Page 304 and 305:
6.3 Digital Telephony: PCM in Tl Ca
Page 306 and 307:
6.3 Digital Telephony: PCM in Tl Ca
Page 308 and 309:
6.4 DIGITAL MULTIPLEXING6.4 Digital
Page 310 and 311:
6.4 Digital Multiplexing 287Figure
Page 312 and 313:
6.4 Digital Multiplexing 289Figure
Page 314 and 315:
6.5 Differential Pulse Code Modulat
Page 316 and 317:
6.5 Differential Pulse Code Modulat
Page 318 and 319:
6.7 Delta Modulation 295deploy. Unl
Page 320 and 321:
6.7 Delta Modulation 297Figure 6.31
Page 322 and 323:
6.7 Delta Modulation 299Figure 6.32
Page 324 and 325:
6.8 Vocoders and Video Compression
Page 326 and 327:
6.8 Vocoders and Video Compression
Page 328 and 329: 6.8 Vocoders and Video Compression
Page 334 and 335: 6.9 MATLAB Exercises 31 1Fi gure 6.
Page 336 and 337: 6.9 MATLAB Exercises 313Figure 6.40
Page 338 and 339: 6. 9 MATLAB Exercises 315% ts new s
Page 340 and 341: 6.9 MATLAB Exercises 317Figure 6.42
Page 342 and 343: t= [O:td :1.]; %time interval of 1
Page 344 and 345: PROBLEMSFigure P.6. 1 - 1Problems 3
Page 346 and 347: Problems 323(c) This filter, being
Page 348 and 349: Problems 325the transmission bandwi
Page 350 and 351: 7. 1 Digital Communication Systems
Page 352 and 353: 7.2 Line Coding 329Figure 7.3An on-
Page 354 and 355: 7.2 Line Coding 33 1in Fig. 7 .4b,
Page 356 and 357: 7.2 Line Coding 333and from Eq. (7.
Page 358 and 359: 7.2 Line Coding 335Moreover, both G
Page 360 and 361: 7.2 Line Coding 337Figure 7.7Split-
Page 362 and 363: 7.2 Line Coding 339Fi gure 7.8Power
Page 364 and 365: 7.2 Line Coding 341Figure 7.9PSD of
Page 366 and 367: 7.3 Pulse Shaping 343Binary with N
Page 368 and 369: 7.3 Pulse Shaping 345to be positive
Page 370 and 371: 7.3 Pulse Shaping 347Fi g ure 7. 13
Page 372 and 373: 7.3 Pulse Shaping 349the case of th
Page 374 and 375: TABLE 7. 1Transmitted Bits and the
Page 376 and 377: 7.3 Pulse Shaping 353In fact, many
Page 380 and 381: 7.4 Scrambling 357Figure 7.20 shows
Page 382 and 383: Figure 7.21Regenerativerepeater.7.5
Page 384 and 385: 7 .5 Digital Receivers and Regenera
Page 386 and 387: 7.5 Digital Receivers and Regenerat
Page 388 and 389: 7.5 Digital Receivers and Regenerat
Page 390 and 391: 7.6 Eye Diagrams: An Important Tool
Page 392 and 393: 7.7 Pam: M-Ary Baseband Signaling f
Page 394 and 395: 7.7 Pam: M-Ary Baseband Signaling f
Page 396 and 397: Figure 7.30(a) The carriercos Wet.
Page 398 and 399: where 'VT (f) is the Fourier transf
Page 400 and 401: 7.8 Digital Carrier Systems 377we c
Page 402 and 403: 7. 8 Digital Carrier Systems 379Fi
Page 404 and 405: 7.9 MAry Digital Carrier Modulation
Page 406 and 407: 7.9 M-Ary Digital Carrier Modulatio
Page 408 and 409: 7.9 M-Ary Digital Carrier Modulatio
Page 410 and 411: 7. l O MATLAB Exercises 387The firs
Page 412 and 413: Problems 389(a) Assuming half-width
Page 414 and 415: Problems 39 1sequence T is applied
Page 416 and 417: 8FUNDAMENTALS OFPROBABILITY THEORYT
Page 418 and 419: 8.1 Concept of Probability 395Figur
Page 420 and 421: 8.1 Concept of Probability 397Exam
Page 422 and 423: 8.1 Concept of Probability 399Let t
Page 424 and 425: 8.1 Concept of Probability 401But t
Page 426 and 427: 8.1 Concept of Probability 403Hence
Page 428 and 429:
8.1 Concept of Probability 405Figur
Page 430 and 431:
8.1 Concept of Probability 407IP(F
Page 432 and 433:
8.2 Random Va riables 409Figure 8.5
Page 434 and 435:
8 .2 Random Variables 41 1Similarly
Page 436 and 437:
8.2 Random Variables 413Because x :
Page 438 and 439:
8.2 Random Va riables 415From Eq. (
Page 440 and 441:
8.2 Random Variables 417This integr
Page 442 and 443:
8.2 Random Variables 419TABLE 8.2Co
Page 444 and 445:
8.2 Random Va riables 421Figure 8.1
Page 446 and 447:
8.2 Random Variables 423Figure 8.13
Page 448 and 449:
8.2 Random Va riables 425Independen
Page 450 and 451:
8.3 Statistical Averages (Means) 42
Page 452 and 453:
Page 454 and 455:
Page 456 and 457:
Page 458 and 459:
Page 460 and 461:
8.4 Correlation 437RVs x and y. We
Page 462 and 463:
8.4 Correlation 439Thus, if x and y
Page 464 and 465:
Since by definition xy = R x y and
Page 466 and 467:
8.6 Sum of Random Va riables 443Fig
Page 468 and 469:
Upon carrying out this convolution
Page 470 and 471:
8.7 Central Limit Theorem 447is kno
Page 472 and 473:
PROBLEMSProblems4498.1-1 A card is
Page 474 and 475:
Problems 45 18.1-16 In a binary com
Page 476 and 477:
Problems 453where M = ab - c 2 . Sh
Page 478 and 479:
Problems 4558.6-3 If x(t) and y(t)
Page 480 and 481:
9. 1 From Random Va riable to Rando
Page 482 and 483:
9. 1 From Random Va riable to Rando
Page 484 and 485:
9 .2 Classification of Random Proce
Page 486 and 487:
Because pe(0) = 1/2n over (0, 2n) a
Page 488 and 489:
9 .3 Power Spectral Density 465resp
Page 490 and 491:
9.3 Power Spectral Density 467Figur
Page 492 and 493:
9.3 Power Spectral Density 469It is
Page 494 and 495:
9.3 Power Spectral Density 471Hence
Page 496 and 497:
9.3 Power Spectral Density 473where
Page 498 and 499:
9.3 Power Spectral Density 475Recal
Page 500 and 501:
In each case we shall first determi
Page 502 and 503:
9.4 MULTIPLE RANDOM PROCESSES9 .4 M
Page 504 and 505:
9.5 Transmission of Random Processe
Page 506 and 507:
9.6 Application: Optimum Filtering
Page 508 and 509:
9.6 Application: Optimum Filtering
Page 510 and 511:
9.7 Application: Performance Analys
Page 512 and 513:
9.8 Application: Optimum Preemphasi
Page 514 and 515:
9.9 Bandpass Random Processes 491an
Page 516 and 517:
9.9 Bandpass Random Processes 493Th
Page 518 and 519:
It follows from this equation and f
Page 520 and 521:
9.9 Bandpass Random Processes 497Ba
Page 522 and 523:
References 499Figure 9.26Rican PDF.
Page 524 and 525:
Problems 5019.2-1 For each of the f
Page 526 and 527:
Problems 503by first finding its tr
Page 528 and 529:
Problems 5059.8-1A white process of
Page 530 and 531:
10.1 Optimum Linear Detector for Bi
Page 532 and 533:
10. 1 Optimum Linear Detector for B
Page 534 and 535:
10.1 Optimum Linear Detector for Bi
Page 536 and 537:
10.2 General Binary Signaling 513Fi
Page 538 and 539:
10.2 General Binary Signaling 515Th
Page 540 and 541:
10.2 General Binary Signaling 517Fi
Page 542 and 543:
Additionally, substituting q(t) = 0
Page 544 and 545:
where the pulse energy is simplyl 0
Page 546 and 547:
To compute P b from Eq. (10.25b), w
Page 548 and 549:
10.4 Signal Space Analysis of Optim
Page 550 and 551:
Page 552 and 553:
Page 554 and 555:
10.5 Vector Decomposition of White
Page 556 and 557:
Page 558 and 559:
Page 560 and 561:
10.6 Optimum Receiver for White Gau
Page 562 and 563:
Page 564 and 565:
Page 566 and 567:
l 0.6 Optimum Receiver for White Ga
Page 568 and 569:
Page 570 and 571:
Page 572 and 573:
Figure 10.21Determiningoptimumdecis
Page 574 and 575:
Page 576 and 577:
(M - 2) symbols. Hence,10.6 Optimum
Page 578 and 579:
Page 580 and 581:
Page 582 and 583:
Page 584 and 585:
10.7 General Expression for Error P
Page 586 and 587:
Page 588 and 589:
Page 590 and 591:
Page 592 and 593:
10.8 Equivalent Signal Sets 569and
Page 594 and 595:
10.8 Equivalent Signal Sets 571Assu
Page 596 and 597:
10.8 Equivalent Signal Sets 573Obse
Page 598 and 599:
10.8 Equivalent Signal Sets 575As a
Page 600 and 601:
10. 9 Nonwhite (Colored) Channel No
Page 602 and 603:
l 0. 10 Other Useful Performance Cr
Page 604 and 605:
10.1 1 Noncoherent Detection 581err
Page 606 and 607:
10.1 1 Noncoherent Detection 583Bec
Page 608 and 609:
10.1 1 Noncoherent Detection 585Fig
Page 610 and 611:
10.1 1 Noncoherent Detection 587Sub
Page 612 and 613:
Figure 10.42Error probability P Pof
Page 614 and 615:
l 0.12 MATLAB Exercises 591yrect=xr
Page 616 and 617:
Figure 1 0.45Power spectraldensity
Page 618 and 619:
10.12 MATLAB Exercises 595set (figw
Page 620 and 621:
10.12 MATLAB Exercises 597Figure 1
Page 622 and 623:
Page 624 and 625:
10.12 MATLAB Exercises 601noiseq=ra
Page 626 and 627:
Problems 603legend ('Analytical BER
Page 628 and 629:
Problems 605where Am sin wet is the
Page 630 and 631:
10.4-4 For the three basis signals
Page 632 and 633:
FigureP. 10.6·5r--a• "v • •s
Page 634 and 635:
Problems 61 110. 7-1 The vertices o
Page 636 and 637:
Problems 613Hint: Use Gram-Schmidt
Page 638 and 639:
11 . 1 Frequency Hopping Spread Spe
Page 640 and 641:
11.1 Frequency Hopping Spread Spect
Page 642 and 643:
11 .2 Multiple FHSS User Systems an
Page 644 and 645:
l l .3 APPLICATIONS OF FHSS11 .3 Ap
Page 646 and 647:
11.3 Applications of FHSS 623To com
Page 648 and 649:
l l .4 Direct Sequence Spread Spect
Page 650 and 651:
11 .4 Direct Sequence Spread Spectr
Page 652 and 653:
11 .5 Resilient Features of DSSS 62
Page 654 and 655:
11.6 Code Division Multiple-Access
Page 656 and 657:
11 .6 Code Division Multiple-Access
Page 658 and 659:
11 .6 Code Division Multiple-Access
Page 660 and 661:
11 .7 Multiuser Detection (MUD) 637
Page 662 and 663:
Page 664 and 665:
Page 666 and 667:
11. 8 Modern Practical DSSS CDMA Sy
Page 668 and 669:
l l .8 Modern Practical DSSS CDMA S
Page 670 and 671:
11.8 Modern Practical DSSS CDMA Sys
Page 672 and 673:
11. 8 Modern Practical DSSS CDMA Sy
Page 674 and 675:
11 . 9 MATLAB Exercises 651Figure 1
Page 676 and 677:
11 . 9 MATLAB Exercises 653% can be
Page 678 and 679:
11.9 MATLAB Exercises 655% Add jamm
Page 680 and 681:
11.9 MATLAB Exercises 657The first
Page 682 and 683:
11.9 MATLAB Exercises 659y_out=x_in
Page 684 and 685:
11 . 9 MATLAB Exercises 661Eb2N_num
Page 686 and 687:
References 663awgnois=signois*noise
Page 688 and 689:
Problems 665(a) Find the probabilit
Page 690 and 691:
12.1 Linear Distortions of Wireless
Page 692 and 693:
12.1 Linear Distortions of Wireless
Page 694 and 695:
12.2 Receiver Channel Equalization
Page 696 and 697:
Page 698 and 699:
Page 700 and 701:
12.3 Linear T-Spaced Equalization (
Page 702 and 703:
Page 704 and 705:
Minimum MSE and Optimum DelayBecaus
Page 706 and 707:
Page 708 and 709:
12.4 Linear Fractionally Spaced Equ
Page 710 and 711:
12.4 Linear Fractionally Spaced Equ
Page 712 and 713:
12.6 Decision Feedback Equalizer 68
Page 714 and 715:
12.6 Decision Feedback Equalizer 69
Page 716 and 717:
12.7 OFDM (Multicarrier) Communicat
Page 718 and 719:
h[0] h[l] h[L] 0 012.7 OFDM (Multic
Page 720 and 721:
X __!:_ [ :Nl1H[O]H[O]=N __!:_ :H[O
Page 722 and 723:
Page 724 and 725:
Page 726 and 727:
Figure 12. 13DMT transmissionof Ndi
Page 728 and 729:
12.8 Discrete Multitone (DMT) Modul
Page 730 and 731:
12.9 Real-Life Applications of OFDM
Page 732 and 733:
Digital Broadcasting12.9 Real-Life
Page 734 and 735:
12.10 Blind Equalization and Identi
Page 736 and 737:
the maximum Doppler shift is bounde
Page 738 and 739:
12.12 MATLAB Exercises 715is known
Page 740 and 741:
12.12 MATLAB Exercises 717% Generat
Page 742 and 743:
12.12 MATLAB Exercises 719After a m
Page 744 and 745:
Fi g ure 12.22Scatter plots ofsigna
Page 746 and 747:
12.12 MATLAB Exercises 723% It show
Page 748 and 749:
12.12 MATLAB Exercises 725Fi g ure
Page 750 and 751:
Page 752 and 753:
References 729Figure 1 2.28Average
Page 754 and 755:
PROBLEMSProblems 73 112.1-1 In a QA
Page 756 and 757:
Problems 73312.7-3 Consider an FIR
Page 758 and 759:
13. l Measure of Information 735The
Page 760 and 761:
13. 1 Measure of Information 737Hen
Page 762 and 763:
13.2 Source Encoding 739on the aver
Page 764 and 765:
13.2 Source Encoding 74 1TABLE 13.1
Page 766 and 767:
13.2 Source Encoding 743TABLE 13.3O
Page 768 and 769:
13.3 Error-Free Communication Over
Page 770 and 771:
13.3 Error-Free Communication Over
Page 772 and 773:
13.4 Channel Capacity of a Discrete
Page 774 and 775:
Page 776 and 777:
Page 778 and 779:
Page 780 and 781:
13.5 Channel Capacity of a Continuo
Page 782 and 783:
subject to the following constraint
Page 784 and 785:
Page 786 and 787:
13.5 Channel Capacity of a Conti nu
Page 788 and 789:
Page 790 and 791:
Page 792 and 793:
Page 794 and 795:
13.5 Channel Capacity of a Conti nu
Page 796 and 797:
13.6 Practical Communication System
Page 798 and 799:
13.6 Practical Communication System
Page 800 and 801:
13 .7 Frequency-Selective Channel C
Page 802 and 803:
13.7 Frequency-Selective Channel Ca
Page 804 and 805:
13.8 MULTIPLE-INPUT-MULTIPLE-OUTPUT
Page 806 and 807:
13.8 Multiple-Input-Multiple-Output
Page 808 and 809:
Page 810 and 811:
Page 812 and 813:
1 3. 9 MATLAB Exercises 789Fi gure
Page 814 and 815:
% probabilities of each source inpu
Page 816 and 817:
13.9 MATLAB Exercises 793estimate=e
Page 818 and 819:
13.9 MATLAB Exercises 795% Matlab P
Page 820 and 821:
Problems 7973. H. Nyquist, "Certain
Page 822 and 823:
Problems 79913.2-3 A source emits o
Page 824 and 825:
Problems 80113.4-5 A cascade of two
Page 826 and 827:
14.2 Redundancy for Error Correctio
Page 828 and 829:
14.2 Redundancy for Error Correctio
Page 830 and 831:
14.3 Linear Block Codes 807codeword
Page 832 and 833:
14.3 Linear Block Codes 809where th
Page 834 and 835:
14.3 Linear Block Codes 81 1TABLE 1
Page 836 and 837:
14.4 Cyclic Codes 813This is precis
Page 838 and 839:
14.4 Cyclic Codes 815Regardless of
Page 840 and 841:
14.4 Cyclic Codes 817Example 1 4.4
Page 842 and 843:
Consider a Hamming (7, 4, 3) code w
Page 844 and 845:
14.4 Cyclic Codes 821TABLE 14.6e100
Page 846 and 847:
TABLE 14.7Commonly Used CRC Codes a
Page 848 and 849:
Figure 14.3Performancecomparison of
Page 850 and 851:
14.6 Convolutional Codes 827check d
Page 852 and 853:
14.6 Convolutional Codes 829Figure
Page 854 and 855:
14.6 Convolutional Codes 83 1Fi gur
Page 856 and 857:
Figure 14, 10 !Iii! Received bits:
Page 858 and 859:
Figure 14. 1 1Convolutionalencoder.
Page 860 and 861:
14.7 Trellis Diagram of Block Codes
Page 862 and 863:
14.8 CODE COMBINING AND INTERLEAVIN
Page 864 and 865:
14.9 Soft Decoding 841Figure 14. 1
Page 866 and 867:
14.9 Soft Decoding 843modify the ha
Page 868 and 869:
14. 10 Soft-Output Viterbi Algorith
Page 870 and 871:
14.1 1 Turbo Codes 847following sim
Page 872 and 873:
14.1 1 Turbo Codes 849derived from
Page 874 and 875:
14.1 1 Turbo Codes 851Figure 14.20
Page 876 and 877:
14. 1 1 Turbo Codes 853whereas from
Page 878 and 879:
14. 1 2 Low-Density Parity Check (L
Page 880 and 881:
14. 12 Low-Density Parity Check (LD
Page 882 and 883:
14. 12 Low-Density Parity Check (LD
Page 884 and 885:
14. 13 MATLAB EXERCISES14. 1 3 MATL
Page 886 and 887:
14.13 MATLAB Exercises 863Exl4 3r =
Page 888 and 889:
References 865rig_l= (l+sign ( xig_
Page 890 and 891:
Problems 867generates a ( 4,2) code
Page 892 and 893:
Problems 869Hint: A third-order pol
Page 894 and 895:
Problems 871FigureP. 14.5-2(b) Use
Page 896 and 897:
APPENDIX AORTHOGONALITY OF SOME SIG
Page 898 and 899:
APPENDIX BCAUCHY-SCHWARZ INEQUALITY
Page 900 and 901:
APPENDIX CGRAM-SCHMIDT ORTHOGONALIZ
Page 902 and 903:
Appendix C: Gram-Schmidt Orthogonal
Page 904 and 905:
Appendix D: Basic Matrix Properties
Page 906 and 907:
Appendix D: Basic Matrix Properties
Page 908 and 909:
APPENDIX EMISCELLANEOUSE.1 L'Hopita
Page 910 and 911:
1cos 3 x = (3 cosx4 + cos 3x)1sin 3
Page 912 and 913:
IND EXAdaptive delta modulation (AD
Page 914 and 915:
Index 891of discrete memoryless cha
Page 916 and 917:
Index 893Energyof modulated signals
Page 918 and 919:
Index 895Ideal vs. practical filter
Page 920 and 921:
Index 897discrete multitone (DMT),
Page 922 and 923:
Index 899of digital carrier modulat
Page 924 and 925:
Index 90 1transmitter power loading
Page 926:
Index 903vector decomposition of ra
show all

B. P. Lathi, Zhi Ding - Modern Digital and Analog Communication Systems-Oxford University Press (2009)

Create successful ePaper yourself

Delete template?

Save as template?