Pipelined Encoding for Deterministic and Noisy Relay Networks

TL;DR

This paper explores pipelined encoding strategies in relay networks, demonstrating improved encoding delay in deterministic cases and favorable rate scaling in noisy scenarios, advancing understanding of efficient relay communication.

Contribution

It introduces pipelined encoding methods for relay networks, highlighting benefits in delay reduction and rate scaling, which are novel compared to traditional approaches.

Findings

Pipelined encoding reduces encoding delay in deterministic networks.

Decode-and-forward achieves good rate scaling at high SNR.

Pipelining improves efficiency in relay network communication.

Abstract

Recent coding strategies for deterministic and noisy relay networks are related to the pipelining of block Markov encoding. For deterministic networks, it is shown that pipelined encoding improves encoding delay, as opposed to end-to-end delay. For noisy networks, it is observed that decode-and-forward exhibits good rate scaling when the signal-to-noise ratio (SNR) increases.