Communication Systems EngineeringThorough coverage of basic digital communication system principles ensures that readers are exposed to all basic relevant topics in digital communication system design. The use of CD player and JPEG image coding standard as examples of systems that employ modern communication principles allows readers to relate the theory to practical systems. Over 180 worked-out examples throughout the book aids readers in understanding basic concepts. Over 480 problems involving applications to practical systems such as satellite communications systems, ionospheric channels, and mobile radio channels gives readers ample opportunity to practice the concepts they have just learned. With an emphasis on digital communications, Communication Systems Engineering, Second Edition introduces the basic principles underlying the analysis and design of communication systems. In addition, this book gives a solid introduction to analog communications and a review of important mathematical foundation topics. New material has been added on wireless communication systems -- GSM and CDMA/IS-94; turbo codes and iterative decoding; multicarrier (OFDM) systems; multiple antenna systems. Includes thorough coverage of basic digital communication system principles -- including source coding, channel coding, baseband and carrier modulation, channel distortion, channel equalization, synchronization, and wireless communications. Includes basic coverage of analog modulation such as amplitude modulation, phase modulation, and frequency modulation as well as demodulation methods. |
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Page 155
... correlation of X and Y. In the case where g ( X , Y ) = ( X − mx ) ( Y — my ) , we obtain E ( XY ) - mxmy , which is called the covariance of X and Y. Note that if X = Y , then COV ( X , Y ) = VAR ( X ) . The normalized version of the ...
... correlation of X and Y. In the case where g ( X , Y ) = ( X − mx ) ( Y — my ) , we obtain E ( XY ) - mxmy , which is called the covariance of X and Y. Note that if X = Y , then COV ( X , Y ) = VAR ( X ) . The normalized version of the ...
Page 482
... correlation between the received vector and the mth signal . For this reason , we call C ( r , Sm ) , m = 1 , 2 , ... , M , the correlation metrics for deciding which of the M signals was transmitted . Finally , the terms Sm | 2 Em m ...
... correlation between the received vector and the mth signal . For this reason , we call C ( r , Sm ) , m = 1 , 2 , ... , M , the correlation metrics for deciding which of the M signals was transmitted . Finally , the terms Sm | 2 Em m ...
Page 883
... Correlation coefficient , 155 Correlation metrics , 482 Correlation - type demodulator , 470 Coset , 762 coset leader , 763 Covariance , 155 Crosscorrelation coefficient , 451 Crosscorrelation function , 175 at output of LTI systems ...
... Correlation coefficient , 155 Correlation metrics , 482 Correlation - type demodulator , 470 Coset , 762 coset leader , 763 Covariance , 155 Crosscorrelation coefficient , 451 Crosscorrelation function , 175 at output of LTI systems ...
Contents
Introduction | 1 |
Analog Signal Transmission and Reception | 5 |
Signals and Linear Systems | 26 |
Copyright | |
21 other sections not shown
Common terms and phrases
additive noise algorithm amplitude amplitude modulation analog autocorrelation function bandlimited bandpass signal bandwidth baseband binary carrier coefficients communication system components decoder defined demodulator denoted detector Determine digital communication distortion DSB-SC encoder entropy equal Example Fourier series Fourier transform frequency domain frequency response fx(x Gaussian random variables given Hence Hilbert transform Huffman code impulse response information source input jointly Gaussian linear lowpass filter LTI system M-ary matched filter modulated signal Nyquist rate obtain orthogonal periodic signal phase power content power spectrum power-spectral density probability of error pulse quadrature quantization radio random process received signal receiving filter relation result Rx(t sequence Show shown in Figure sideband signal waveforms signal x(t sinusoidal source output SQNR stationary process Sx f symbol theorem transmission transmitted signal values vector zero zero-mean