1 research outputs found
Constructing Linear Encoders with Good Spectra
Linear encoders with good joint spectra are suitable candidates for optimal
lossless joint source-channel coding (JSCC), where the joint spectrum is a
variant of the input-output complete weight distribution and is considered good
if it is close to the average joint spectrum of all linear encoders (of the
same coding rate). In spite of their existence, little is known on how to
construct such encoders in practice. This paper is devoted to their
construction. In particular, two families of linear encoders are presented and
proved to have good joint spectra. The first family is derived from Gabidulin
codes, a class of maximum-rank-distance codes. The second family is constructed
using a serial concatenation of an encoder of a low-density parity-check code
(as outer encoder) with a low-density generator matrix encoder (as inner
encoder). In addition, criteria for good linear encoders are defined for three
coding applications: lossless source coding, channel coding, and lossless JSCC.
In the framework of the code-spectrum approach, these three scenarios
correspond to the problems of constructing linear encoders with good kernel
spectra, good image spectra, and good joint spectra, respectively. Good joint
spectra imply both good kernel spectra and good image spectra, and for every
linear encoder having a good kernel (resp., image) spectrum, it is proved that
there exists a linear encoder not only with the same kernel (resp., image) but
also with a good joint spectrum. Thus a good joint spectrum is the most
important feature of a linear encoder.Comment: v5.5.5, no. 201408271350, 40 pages, 3 figures, extended version of
the paper to be published in IEEE Transactions on Information Theor