Search for: All records

This paper studies a special case of the problem of source coding with side information. A single transmitter describes a source to a receiver that has access to a side information observation that is unavailable at the transmitter. While the source and true side information sequences are dependent, stationary, memoryless random processes, the side information observation at the decoder is unreliable, which here means that it may or may not equal the intended side information and therefore may or may not be useful for decoding the source description. The probability of side information observation failure, caused, for example, by a faulty sensor or source decoding error, is non-vanishing but is bounded by a fixed constant independent of the blocklength. This paper proposes a coding system that uses unreliable side information to get efficient source representation subject to a fixed error probability bound. Results include achievability and converse bounds under two different models of the joint distribution of the source, the intended side information, and the side information observation. 

This paper proposes a nested low-density parity-check (LDPC) code design. Combining this nested LDPC code with the random access coding strategy introduced by Yavas, Kostina, and Effros yields a random access LDPC (RA-LDPC) code for reliable communication in random access communication environments where neither the transmitters nor the receiver knows which or even how many transmitters wish to communicate at each moment. Coordination is achieved using sparse scheduled feedback. Bounds on the finite-blocklength performance of the RA-LDPC code under maximum likelihood (ML) decoding are derived using both error exponent and dispersion style analyses. Results include bounds on the penalty of the RA-LDPC code as a function of the LDPC code densities. 

This paper applies error-exponent and dispersionstyle analyses to derive finite-blocklength achievability bounds for low-density parity-check (LDPC) codes over the point-to-point channel (PPC) and multiple access channel (MAC). The error-exponent analysis applies Gallager's error exponent to bound achievable symmetrical and asymmetrical rates in the MAC. The dispersion-style analysis begins with a generalization of the random coding union (RCU) bound from random code ensembles with i.i.d. codewords to random code ensembles in which codewords may be statistically dependent; this generalization is useful since the codewords of random linear codes such as LDPC codes are dependent. Application of the RCU bound yields finite-blocklength error bounds and asymptotic achievability results for both i.i.d. random codes and LDPC codes. For discrete, memoryless channels, these results show that LDPC codes achieve first- and second-order performance that is optimal for the PPC and identical to the best prior results for the MAC.