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Description code = convenc(msg,trellis) encodes the binary vector msg using the convolutional encoder whose MATLAB trellis structure is trellis. For details about MATLAB trellis structures, see. Each symbol in msg consists of log2(trellis.numInputSymbols) bits. The vector msg contains one or more symbols. The output vector code contains one or more symbols, each of which consists of log2(trellis.numOutputSymbols) bits.
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Code = convenc(msg,trellis,puncpat) is the same as the syntax above, except that it specifies a puncture pattern, puncpat, to allow higher rate encoding. Puncpat must be a vector of 1s and 0s, where the 0s indicate the punctured bits. Puncpat must have a length of at least log2(trellis.numOutputSymbols) bits. Code = convenc(msg,trellis.,init_state) allows the encoder registers to start at a state specified by init_state.
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Init_state is an integer between 0 and trellis.numStates-1 and must be the last input parameter. [code,final_state] = convenc(.) encodes the input message and also returns the encoder's state in final_state. Final_state has the same format as init_state. • Generate binary data.
• Convolutionally encode the data. • Apply QAM modulation to the data symbols. Specify unit average power for the transmitted signal.
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• Pass the modulated signal through an AWGN channel. • Demodulate the received signal using hard decision and approximate LLR methods. Specify unit average power for the received signal.
• Viterbi decode the signals using hard and unquantized methods. • Calculate the number of bit errors. The while loop continues to process data until either 100 errors are encountered or 1e7 bits are transmitted. For n = 1:length(EbNoVec)% Convert Eb/No to SNR snrdB = EbNoVec(n) + 10*log10(k*rate);% Noise variance calculation for unity average signal power. NoiseVar = 10.^(-snrdB/10);% Reset the error and bit counters [numErrsSoft,numErrsHard,numBits] = deal(0); while numErrsSoft.