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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 work addresses the cooperation facilitator (CF) model, in which network nodes coordinate through a rate limited communication device. For multiple-access channel (MAC) encoders, the CF model is known to show significant rate benefits, even when the rate of cooperation is negligible. Specifically, the benefit in MAC sum-rate, as a function of the cooperation rate C_{CF}, sometimes has an infinite slope at C_{CF} = 0 when the CF enables transmitter dependence where none was possible otherwise. This work asks whether cooperation through a CF can yield similar infinite-slope benefits when dependence among MAC transmitters has no benefit or when it can be established without the help of the CF. Specifically, this work studies the CF model when applied to relay nodes of a single-source, single-terminal, diamond network comprising a broadcast channel followed by a MAC. In the relay channel with orthogonal receiver components, careful generalization of the partial-decode-forward/compress-forward lower bound to the CF model yields sufficient conditions for an infinite-slope benefit. Additional results include derivation of a family of diamond networks for which the infinite-slope rate-benefit derives directly from the properties of the corresponding MAC studied in isolation. 

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. 

The work at hand presents a finite-blocklength analysis of the multiple access channel (MAC) sum-rate under the cooperation facilitator (CF) model. The CF model, in which independent encoders coordinate through an intermediary node, is known to show significant rate benefits, even when the rate of cooperation is limited. We continue this line of study for cooperation rates which are sub-linear in the blocklength n. Roughly speaking, our results show that if the facilitator transmits log K bits, then there is a sum-rate benefit of order √log K/n compared to the best-known achievable rate. This result extends across a wide range of K: even a single bit of cooperation is shown to provide a sum-rate benefit of order 1/√n.