The Benefit of Limited Feedback to Generation-Based Random Linear Network Coding in Wireless Broadcast

TL;DR

This paper explores how limited feedback can improve generation-based random linear network coding in wireless broadcast by optimizing packet partitioning to reduce decoding delay and computational load.

Contribution

It introduces a new partitioning approach based on feedback, proves its NP-hardness, and offers an efficient heuristic that outperforms existing methods.

Findings

The proposed heuristic improves throughput and reduces decoding delay.

Limited feedback enhances partitioning efficiency in network coding.

Simulation results show superior performance over existing solutions.

Abstract

Random linear network coding (RLNC) is asymptotically throughput optimal in the wireless broadcast of a block of packets from a sender to a set of receivers, but suffers from heavy computational load and packet decoding delay. To mitigate this problem while maintaining good throughput, we partition the packet block into disjoint generations after broadcasting the packets uncoded once and collecting one round of feedback about receivers' packet reception state. We prove the NP-hardness of the optimal partitioning problem by using a hypergraph coloring approach, and develop an efficient heuristic algorithm for its solution. Simulations show that our algorithm outperforms existing solutions.