An algebraic approach to network coding
IEEE/ACM Transactions on Networking (TON)
Error Control Coding, Second Edition
Error Control Coding, Second Edition
Convex Optimization
Ad Hoc Wireless Networks
Fundamentals of wireless communication
Fundamentals of wireless communication
IEEE Transactions on Signal Processing
Generalized minimum-distance decoding of Euclidean-space codes and lattices
IEEE Transactions on Information Theory - Part 1
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
A separation theorem for single-source network coding
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
Network planning in wireless ad hoc networks: a cross-Layer approach
IEEE Journal on Selected Areas in Communications
Design of network codes for multiple-user multiple-relay wireless networks
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
Multiple-user cooperative communications based on linear network coding
IEEE Transactions on Communications
ML performance analysis of digital relaying in bi-directional relay channels
Wireless Communications & Mobile Computing
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We investigate sink decoding approaches and performance analysis for a network with intermediate node encoding (coded network). The network consists of statistically independent noisy channels. The sink bit error probability (BEP) is the performance measure. First, we investigate soft-decision decoding without statistical information on the upstream channels (the channels not directly connected to the sink). Numerical results show that the decoder cannot significantly improve the performance from a hard-decision decoder. We develop union bounds for analysis. The bounds show the asymptotic (regarding SNR: signal-to-noise ratio) performance of the decoder. Using statistical information about the upstream channels, we can find the error patterns of final hop channels (channels directly connected to sinks). With the error patterns, maximum-likelihood (ML) decoding can be performed, and a significant improvement in the BEP is obtained. To evaluate the union bound for the ML decoder, we use an equivalent point procedure. It is reduced to the least-squares problem with a linear constraint in the medium-to-high SNR region. With deterministic knowledge of the errors in the upstream channels, a genie-aided decoder can further improve the performance. We give the union bound for the genie decoder, which is straightforward to evaluate. By analyzing these decoders, we find that knowledge about the upstream channels is essential for good sink decoding.