2026-09-19T00:02:39Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/601662022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Lizhong Zheng.
Huang, Shao-Lun, Ph. D. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2010-12-06T17:32:22Z
2010-12-06T17:32:22Z
2010
2010
http://hdl.handle.net/1721.1/60166
681763441
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
Includes bibliographical references (p. 35).
In information theory, in order to maximize the total throughput, it is required that the codebook has an empirical distribution that maximizes the mutual information over the channel. In coding theory, however, most codes we can generate have Bernoulli (1/2) distribution. In this thesis, we present a new coding scheme to efficiently generate binary codes with different distributions. Our main approach is to first encode the information bits by a linear code C, and then quantized the codeword to the closest codeword in another linear code C,. The quantization error is then treated as the encoded codeword in our coding scheme. We discuss the practicality and advantage of such codes and give a design example.
by Shao-Lun Huang.
S.M.
35 p.
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
The design of binary shaping filter of binary code
Thesis
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