Polynomial time algorithms for network information flow
Proceedings of the fifteenth annual ACM symposium on Parallel algorithms and architectures
Separating distributed source coding from network coding
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
IEEE Transactions on Information Theory
Generalized coset codes for distributed binning
IEEE Transactions on Information Theory
On code design for the Slepian-Wolf problem and lossless multiterminal networks
IEEE Transactions on Information Theory
A Random Linear Network Coding Approach to Multicast
IEEE Transactions on Information Theory
Practical source-network decoding
ISWCS'09 Proceedings of the 6th international conference on Symposium on Wireless Communication Systems
Brief paper: Min-max optimal data encoding and fusion in sensor networks
Automatica (Journal of IFAC)
Approximate decoding approaches for network coded correlated data
Signal Processing
Hi-index | 754.84 |
This paper considers the problem of communicating correlated information from multiple source nodes over a network of noiseless channels to multiple destination nodes, where each destination node wants to recover all sources. The problem involves a joint consideration of distributed compression and network information relaying. Although the optimal rate region has been theoretically characterized, it was not clear how to design practical communication schemes with low complexity. This work provides a partial solution to this problem by proposing a low-complexity scheme for the special case with two sources whose correlation is characterized by a binary symmetric channel. Our scheme is based on a careful combination of linear syndrome-based Slepian-Wolf coding and random linear mixing (network coding). It is in general suboptimal; however, its low complexity and robustness to network dynamics make it suitable for practical implementation.