Abstract :
Let A = {a1,a2,..., a26} be a set of 26 English alphabets with probabilities P = {p1,p2,... ,p26} and C be the corresponding Huffman code that has 26 codewords {c1,c2,... ,c26} with average codeword length 4.15573. The respective lengths of the codewords are given by {lscr1,lscr2,...,lscr26}. According to P, a concatenation of 1000 symbols randomly generated from A is Huffman encoded into a bitstream x of length M and x is further encoded into a bitstream y of length N by a binary (2,1,6) convolutional code with octal generator sequence 554 and 744. Then, y is BPSK modulated and sent over an AWGN channel. Let r = (r1, r2,..., rN) denote the received bitstream. This work assumes that no bits are deleted by the channel, and that the side information N is known at the receiver.
Keywords :
AWGN channels; Huffman codes; binary codes; concatenated codes; convolutional codes; maximum likelihood decoding; phase shift keying; probability; trellis codes; AWGN channel; BPSK modulation; English alphabets; Huffman decoding; Huffman encoding; binary code; codewords; convolutional decoding; maximum a posteriori decoding; octal generator sequence; probability; soft-decision priority-first decoding; symbol concatenation; trellis-based decoding; AWGN channels; Binary phase shift keying; Computational modeling; Computer science; Convolution; Convolutional codes; Data compression; Equations; Maximum likelihood decoding; Tin;
