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The algorithm performs quantizers with a low and medium number of quantization levels and with a fixed codeword length by using a pixel value prediction in preprocessing.
First, for given symbol length m and codeword length n, we determine the optimal codebook with the least average number of high bits per codeword and give the corresponding average codeword weight as a function of m and n.
Then, we study the minimum transmission energy (MTE) code design problem with codeword length and codeword rate constraints and investigate how the transmission energy changes when m and n are varied.
The codeword length is N=1024 bits.
Note that, now, the codeword length is m.
σ2 = 0.5 and codeword length is 106 bits.
First, the codeword length considered in [3] is almost ten times higher than the codeword length considered for the RC UEP-LDPC codes.
The decoding error probability is 10-6, σ2 = 1, and the codeword length is 106 bits.
The codeword length equals n, so the code rate is R=k/n.
The decoding complexity increases linearly with codeword length and also depends on the sparseness of H.
In the simulations of the direct link, the codeword length is 2,592 bits.
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