Disjoint LDPC Coding for Gaussian Broadcast Channels

Low-density parity-check (LDPC) codes have been used for communication over a two-user Gaussian broadcast channel. It has been shown in the literature that the optimal decoding of such system requires joint decoding of both user messages at each user. Also, a joint code design procedure should be performed. We propose a method which uses a novel labeling strategy and is based on the idea behind the bit-interleaved coded modulation. This method does not require joint decoding and/or joint code optimization. Thus, it reduces the overall complexity of near-capacity coding in broadcast channels. For different rate pairs on the boundary of the capacity region, pairs of LDPC codes are designed to demonstrate the success of this technique.Comment: 5 pages, 1 figure, 3 tables, To appear in Proc. IEEE International Symposium on Information Theory (ISIT 2009), Seoul, Korea, June-July 200

Wireless Network-Level Partial Relay Cooperation: A Stable Throughput Analysis

In this work, we study the benefit of partial relay cooperation. We consider a two-node system consisting of one source and one relay node transmitting information to a common destination. The source and the relay have external traffic and in addition, the relay is equipped with a flow controller to regulate the incoming traffic from the source node. The cooperation is performed at the network level. A collision channel with erasures is considered. We provide an exact characterization of the stability region of the system and we also prove that the system with partial cooperation is always better or at least equal to the system without the flow controller.Comment: Submitted for journal publication. arXiv admin note: text overlap with arXiv:1502.0113

Successive Refinement of Abstract Sources

In successive refinement of information, the decoder refines its representation of the source progressively as it receives more encoded bits. The rate-distortion region of successive refinement describes the minimum rates required to attain the target distortions at each decoding stage. In this paper, we derive a parametric characterization of the rate-distortion region for successive refinement of abstract sources. Our characterization extends Csiszar's result to successive refinement, and generalizes a result by Tuncel and Rose, applicable for finite alphabet sources, to abstract sources. This characterization spawns a family of outer bounds to the rate-distortion region. It also enables an iterative algorithm for computing the rate-distortion region, which generalizes Blahut's algorithm to successive refinement. Finally, it leads a new nonasymptotic converse bound. In all the scenarios where the dispersion is known, this bound is second-order optimal. In our proof technique, we avoid Karush-Kuhn-Tucker conditions of optimality, and we use basic tools of probability theory. We leverage the Donsker-Varadhan lemma for the minimization of relative entropy on abstract probability spaces.Comment: Extended version of a paper presented at ISIT 201