Generalized Adaptive Network Coded Cooperation (GANCC): A Unified Framework for Network Coding and Channel Coding

TL;DR

This paper introduces GANCC, a unified framework combining network and channel coding for wireless data collection, enabling adaptive, distributed, and efficient coding with significant gains even with few users.

Contribution

The paper proposes GANCC, a novel unified coding framework that dynamically matches code graphs to network graphs and integrates channel coding with network coding using circulant LDPC codes.

Findings

GANCC is simple to operate and adaptive in real time.

GANCC provides remarkable coding gains with limited cooperating users.

Several code construction methods and sparse-graph code families are proposed.

Abstract

This paper considers distributed coding for multi-source single-sink data collection wireless networks. A unified framework for network coding and channel coding, termed "generalized adaptive network coded cooperation" (GANCC), is proposed. Key ingredients of GANCC include: matching code graphs with the dynamic network graphs on-the-fly, and integrating channel coding with network coding through circulant low-density parity-check codes. Several code constructing methods and several families of sparse-graph codes are proposed, and information theoretical analysis is performed. It is shown that GANCC is simple to operate, adaptive in real time, distributed in nature, and capable of providing remarkable coding gains even with a very limited number of cooperating users.