Elements of information theory
Elements of information theory
Separating distributed source coding from network coding
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Source-channel diversity for parallel channels
IEEE Transactions on Information Theory
Capacity of wireless erasure networks
IEEE Transactions on Information Theory
Slepian-Wolf coding over broadcast channels
IEEE Transactions on Information Theory
Source and channel coding for correlated sources over multiuser channels
IEEE Transactions on Information Theory
Approximate decoding approaches for network coded correlated data
Signal Processing
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We consider a set of S independent encoders that must transmit a set of correlated sources through a network of noisy, independent, broadcast channels to T receivers, with no interference at the receivers. For the general problem of sending correlated sources through broadcast networks, it is known that the source-channel separation theorem breaks down and the achievable rate region as well as the proper method of coding are unknown. For our scenario, however, we establish the optimal rate region using a form of joint source-channel coding. When the optimal channel input distribution from transmitter i to receiver j is independent of j, our result has a max-flow/min-cut interpretation. Specifically, in this case, our result implies that if it is possible to send the sources to each receiver separately while ignoring the others, then it is possible to send to all receivers simultaneously.