Simultaneous Communication in Noisy Channels

A sender wishes to broadcast a message of length n over an alphabet to r users, where each user i, 1 ≤ i ≤ r, should be able to receive one m, possible messages. The broadcast channel has noise for each of the users (possibly different noise for different users), who cannot distinguish between some...

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Veröffentlicht in:IEEE transactions on information theory 2011-10, Vol.57 (10), p.6455-6462
1. Verfasser: Weinstein, A.
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description A sender wishes to broadcast a message of length n over an alphabet to r users, where each user i, 1 ≤ i ≤ r, should be able to receive one m, possible messages. The broadcast channel has noise for each of the users (possibly different noise for different users), who cannot distinguish between some pairs of letters. The vector (m 1 , m 2 ,...,m r ) (n) is said to be feasible if length n encoding and decoding schemes exist enabling every user to decode his message. A rate vector (R 1 , R 2 ...,R r ) is feasible if there exists a sequence of feasible vectors (m 1 , m 2 ...,m r ) (n) such that R i = lim n→∞ Log 2 m i /n for all i. We determine the feasible rate vectors for several different scenarios and investigate some of their properties. An interesting case discussed is when one user can only distinguish between all the letters in a subset of the alphabet. Tight restrictions on the feasible rate vectors for some specific noise types for the other users are provided. The simplest nontrivial cases of two users and alphabet of size three are fully characterized. To this end a more general previously known result, to which we sketch an alternative proof, is used. This problem generalizes the study of the Shannon capacity of a graph, by considering more than a single user.
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subjects Applied sciences
Broadcast channels
Channel coding
Codes
Coding, codes
Communication channels
Data transmission
Electric noise
Entropy
Exact sciences and technology
graph powers
Information theory
Information, signal and communications theory
Noise
Noise measurement
Probability distribution
Random variables
Shannon capacity
Signal and communications theory
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Transmission and modulation (techniques and equipments)
title Simultaneous Communication in Noisy Channels
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