Digital Communication Systems |
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Page viii
Peyton Z. Peebles. 4.2 OPTIMUM BINARY SYSTEMS Correlation Receiver Implementation 149 Matched Filter Implementation 149 Optimum System Output Noise Power 150 Optimum System Output Signal Levels 152 148 PROBABILITIES 4.3 OPTIMUM BINARY ...
Peyton Z. Peebles. 4.2 OPTIMUM BINARY SYSTEMS Correlation Receiver Implementation 149 Matched Filter Implementation 149 Optimum System Output Noise Power 150 Optimum System Output Signal Levels 152 148 PROBABILITIES 4.3 OPTIMUM BINARY ...
Page 245
... receiver . The composite waveform at the receiver becomes r ( t ) = [ s1 ( t ) + nu ( t ) , $ 2 ( t ) + nw ( t ) , m1 sent m2 sent . ( 5.1-1 ) The optimum receiver is that which decides m2 was transmitted if its probability of being ...
... receiver . The composite waveform at the receiver becomes r ( t ) = [ s1 ( t ) + nu ( t ) , $ 2 ( t ) + nw ( t ) , m1 sent m2 sent . ( 5.1-1 ) The optimum receiver is that which decides m2 was transmitted if its probability of being ...
Page 343
Peyton Z. Peebles. ⭑6.4 OPTIMUM RECEIVERS Even though decision regions and error probability may be difficult to calculate , the structure of the optimum receiver can readily be found . By expanding the squares in ( 6.3-16 ) and using ...
Peyton Z. Peebles. ⭑6.4 OPTIMUM RECEIVERS Even though decision regions and error probability may be difficult to calculate , the structure of the optimum receiver can readily be found . By expanding the squares in ( 6.3-16 ) and using ...
Common terms and phrases
amplitude analog applies ASK system assumed average bandlimited bandwidth baseband binary digits bit error probability bit interval carrier codeword coherent Communications cos(wot D-SM decision decoding defined delta modulation demodulator denoted density spectrum DPCM duration E₁ E₂ energy erfc example Figure Find format Fourier transform frequency Gaussian given input integrator intersymbol interference lowpass filter M-ary m₁ m₂ matched filter multiplexer noise power noncoherent Nyquist rate occur optimum receiver OQPSK orthogonal output P₁ P₂ performance phase power density power spectrum Prob probability density pulse train Px(x QPSK quantizer random variable response s₁(t sample rate sampled signal sampling pulse sampling theorem sequence shown in Fig signal f(t signal set signal vectors slope overload spectral symbol interval transfer function transmitted unipolar V₁ values w₁ waveform white noise zero δυ Ть
References to this book
Informationsübertragung: Grundlagen der Kommunikationstechnik Jürgen Lindner No preview available - 2004 |