Algebraic network information theory is an emerging facet of network information theory,
studying the achievable rates of random code ensembles that have algebraic structure, such …

In several problems in network information theory, it is important to jointly decode the
codewords transmitted by several encoders. For ensembles of iid random codes, such joint …

This paper presents a joint typicality framework for encoding and decoding nested linear
codes for multi-user networks. This framework provides a new perspective on compute …

Recent work has employed joint typicality encoding and decoding of nested linear code
ensembles to generalize the compute-forward strategy to discrete memoryless multiple …

This paper presents a joint typicality framework for encoding and decoding nested linear
codes in multi-user networks. This framework provides a new perspective on compute …

In this monograph, we develop a mathematical framework based on asymptotically good
random structured codes, ie, codes possessing algebraic properties, for network information …

In this paper, a new network coding model is proposed to unify instantly decodable network
coding (IDNC) and random linear network coding (RLNC), which have been considered to …

We consider the problem of error control in a coded, multicast network, focusing on the
scenario where the errors can occur only on a proper subset of the network edges. We …

Compute–forward is a coding technique that enables receiver (s) in a network to directly
decode one or more linear combinations of the transmitted codewords. Initial efforts focused …

Recent algorithmic developments have enabled computers to automatically determine and
prove the capacity regions of small hypergraph networks under network coding. A structural …