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In this paper, we model synchronization error channels as hidden Markov models. Through this model we introduce a rhomboidal trellis for calculating information rates for synchronization error channels. In particular, the introduced trellis is novel due to being synchronized with the channel input sequence, i.e., one trellis section corresponds to one channel input symbol, but (possibly) multiple...
We analyze the problem of strong coordination over a multi-hop line network where the node initiating the coordination is a terminal network node. We provide a characterization of the capacity region when the initiating node possesses unlimited local randomness and intermediate nodes operate under a functional regime. In this regime, next-hop messages are created only using common randomness and previous-hop...
An optical orthogonal code (OOC) of length N is a set of {0, 1}-sequences of length N, all of which have a constant weight. It is employed as a spreading code in optical communication systems, where 1 means signal ‘on’ and 0 signal ‘off.’ In this paper, we present a generic construction of OOCs of length (q−1)N from an OOC of length N, where q is a prime power with gcd(q −1,N) = 1. This construction...
In the classical Secret-Key generation model, Common Randomness is generated by two terminals based on the observation of correlated components of a common source, while keeping it secret from a non-legitimate observer. It is assumed that the statistics of the source are known to all participants. In this work, the Secret-Key generation model based on a compound source is studied where the source...
We study a social network in which individuals make decisions influenced by a recommender as well as the previous actions taken by themselves or other users. The recommender aims to tailor its suggestions to maximize the benefit from utilizing social interactions. We refer to this benefit as the recommender's influence which, in essence, measures the value of controlling the specific suggestions offered...
The duality between the capacity regions of Gaussian broadcast channels and Gaussian multiple access channels has been well established. However, there have been limited results for the discrete case. In this work, we show that we can express the capacity regions of a class of broadcast channels using the rate regions of a finite number of multiple access channels.
Given a background graph with n vertices, the binary censored block model assumes that vertices are partitioned into two clusters, and every edge is labeled independently at random with labels drawn from Bern(1 − ε) if two endpoints are in the same cluster, or from Bern(ε) otherwise, where ε ∈ [0; 1/2] is a fixed constant. For Erdős-Rényi graphs with edge probability p = a log n/n and fixed a, we...
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