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

Recommendations

Info

3 . 10 MATLAB Exercises 125In this example, we knew G(f) beforehand and hence could make IN TELLIGENT choicesfor B (or the sampling frequency fs). In practice, we generally do not know G(f) beforehand.In fact, that is the very thing we are trying to determine. In such a case, we must makean intelligent guess for B or fs from circumstantial evidence. We then continue reducingthe value of T s and recomputing the transform until the result stabilizes within the desirednumber of significant digits.Next, we compute the Fourier transform of g(t) = 8 TI (t).COMPUTER EXAMPLE C3.2Use DFf (implemented by the FFf algorithm) to compute the Fourier transform of 8 TT (t). Plot theresulting Fourier spectra.This rectangular function and its Fourier transform are shown in Fig. 3.41a and b. Todetermine the value of the sampling interval T s , we must first decide on the essentialbandwidth B. From Fig. 3.41b, we see that G(f) decays rather slowly with f. Hence,the essential bandwidth B is rather large. For instance, at B = 15.5 Hz (97.39 rad/s),G(f) = -0.1643, which is about 2% of the peak at G(O). Hence, the essential bandwidthmay be taken as 16 Hz. However, we shall deliberately take B = 4 for two reasons: (1) toshow the effect of aliasing and (2) because the use of B > 4 will give an enormous numberof samples, which cannot be conveniently displayed on a book-sized page without losingsight of the essentials. Thus, we shall intentionally accept approximation for the sake ofclarifying the concepts of DFT graphically.The choice of B = 4 results in the sampling interval T s = 1 /2B = 1 /8. Lookingagain at the spectrum in Fig. 3.41b, we see that the choice of the frequency resolutionJ o = 1/4 Hz is reasonable. This will give four samples in each lobe of G(f). In this caseTo = I /J o = 4 seconds and N o = To/T = 32. The duration of g(t) is only 1 second. Wemust repeat it every 4 seconds (To = 4), as shown in Fig. 3.41c, and take samples every0.125 second. This gives us 32 samples (No = 32). Also,8k = T s g (kT)1= Sg(kT)Since g(t) = 8 TI (t), the values of 8k are 1, 0, or 0.5 (at the points of discontinuity), asshown in Fig. 3.41c, where for convenience, 8k is shown as a function of t as well as k.In the derivation of the DFT, we assumed that g (t) begins at t = 0 (Fig. 3.39a), andthen took No samples over the interval (0, To). In the present case, however, g(t) begins at-½. This difficulty is easily resolved when we realize that the DFT found by this procedureis actually the DFT of 8k repeating periodically every T o seconds. From Fig. 3.41c, it isclear that repeating the segment of 8k over the interval from -2 to 2 seconds periodicallyis identical to repeating the segment of 8k over the interval from O to 4 seconds. Hence,the DFT of the samples taken from -2 to 2 seconds is the same as that of the samplestaken from O to 4 seconds. Therefore, regardless of where g (t) starts, we can always takethe samples of g(t) and its periodic extension over the interval from Oto To. In the present
126 ANALYSIS AND TRANSMISSION OF SIGNALSFigure 3.41Discrete Fouriertransform of arectangularpulse.-1 6-4 -2-4-4I '"I0.55 S k S 27k = 4, 28(a)0.5 t -(b)w--20 2 4 f(Hz) --20 2 t- 43102 4 f (Hz) -0 S k S 3 and 29 S k S 3 18; ·" G qIiJi. :• ir'IIIIIII'+tIin:!I .example, the 32 sample values are11gk = I b(d)
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 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 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 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 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 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 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 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:
4.8 Phase-locked Loop and Some Appl
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:
Page 328 and 329:
Page 330 and 331:
Page 332 and 333:
Page 334 and 335:
6.9 MATLAB Exercises 31 1Fi gure 6.
Page 336 and 337:
Page 338 and 339:
6. 9 MATLAB Exercises 315% ts new s
Page 340 and 341:
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 378 and 379:
7.4 Scrambling 355TABLE 7.2Binary D
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?