Joint Channel Coding and Intrinsic Randomness

友彦 植松, Tomohiko Uyematsu, 哲直 松田 +1 more

Alexandre J. Pierrot, Matthieu R. Bloch

This paper investigates the separation of channel intrinsic randomness and channel resolvability. We derive joint exponents, which are compared to the tandem exponents obtained with a separate approach. We prove at once, in a simple manner, achievability results for channel intrinsic randomness, random number generation, and channel resolvability. We also provide converse results in different special settings.

Mohammad Bavarian, Dmitry Gavinsky, Tsuyoshi Ito

Hadi Ahmadi, Reihaneh Safavi–Naini

Joint Channel-State Estimation and Decoding of Low-Density Parity-Check Codes on the Two-State Noiseless/Useless BSC Block Interference Channel We apply the density-evolution technique to determine the thresholds of low-density parity-check (LDPC) codes when the sum-product algorithm is employed to perform joint channel-state estimation and decoding. The channel considered is the two-state noiseless/useless binary symmetric channel (BSC) block interference channel, where a block of $h$ consecutive symbols shares the same channel state, which is either a noiseless BSC (crossover probability 0) or a useless BSC (crossover probability 1/2). The channel state is selected independently and at random from block to block, according to a known prior distribution. The threshold of the joint channel-state estimation/decoding scheme when used over such a channel is shown to be greatly superior to that of a decoder that makes no attempt to estimate the channel state. These results are also confirmed by simulation. The maximum-likelihood performance of LDPC codes when used over this channel is investigated. Lower bounds on the error exponents of regular LDPC codes, when maximum-likelihood decoded, are shown to be close to the random coding channel-error exponent when the LDPC variable node degree is high.

Wongkot Vijacksungsithi, Kim A. Winick

We apply the density-evolution technique to determine the thresholds of low-density parity-check (LDPC) codes when the sum-product algorithm is employed to perform joint channel-state estimation and decoding. The channel considered is the two-state noiseless/useless binary symmetric channel (BSC) block interference channel, where a block of h consecutive symbols shares the same channel state, which is either a noiseless BSC (crossover probability 0) or a useless BSC (crossover probability 1/2). The channel state is selected independently and at random from block to block, according to a known prior distribution. The threshold of the joint channel-state estimation/decoding scheme when used over such a channel is shown to be greatly superior to that of a decoder that makes no attempt to estimate the channel state. These results are also confirmed by simulation. The maximum-likelihood (ML) performance of LDPC codes when used over this channel is investigated. Lower bounds on the error exponents of regular LDPC codes, when ML decoded, are shown to be close to the random coding channel error exponent when the LDPC variable node degree is high.