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

This paper considers the problem of distributed lossy compression where the goal is to
recover one or more linear combinations of the sources at the decoder, subject to distortion …

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 …

Nested linear coding is a widely used technique in wireless communication systems for
improving both security and reliability. Some parameters, such as the relative generalized …

We prove that the ensemble of the nested coset codes built on finite fields achieves the
capacity of arbitrary discrete memoryless point-to-point channels. Exploiting its algebraic …

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 …

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 …

In this paper, we study the asymptotic performance of Abelian group codes for the channel
coding problem for arbitrary discrete (finite alphabet) memoryless channels as well as the …

This work considers an information-theoretic characterization of the set of achievable rates,
costs, and distortions in a broad class of distributed communication and function …

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 …