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Dynamic Programming for Quantization of q-ary Input Discrete Memoryless Channels
Conference proceeding

Dynamic Programming for Quantization of q-ary Input Discrete Memoryless Channels

Xuan He, Kui Cai, Wentu Song, Zhen Mei and IEEE
2019 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), Vol.2019-, pp.450-454
IEEE International Symposium on Information Theory
01/01/2019

Abstract

Computer Science Computer Science, Information Systems Computer Science, Theory & Methods Science & Technology Technology
In this paper, we present a general framework of applying dynamic programming (DP) to the sequential deterministic quantization for discrete memoryless channels (DMCs) with prelabelled outputs. The DP has complexity O(q(N - M)(2) M), where q, N, and M are alphabet sizes of the DMC input, DMC output, and the quantizer output, respectively. Then, starting from the quadrangle inequality (QI), we apply two techniques to reduce the DP's complexity. One technique makes use of the SMAWK algorithm with complexity O(q(N - M)M), while the other technique is much easier to be implemented and has complexity O(q(N-2 - M-2)). Moreover, we give a sufficient condition on the channel transition probability, under which the two lowcomplexity techniques can be applied for designing quantizers that maximize the alpha-mutual information, which is a generalized objective function for channel quantization. This condition works for the general q-ary input case, including the previous work for q = 2 as a subcase.

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