Adaptive Causal Network Coding with Feedback for Multipath Multi-hop Communications

TL;DR

This paper introduces an adaptive, causal network coding algorithm for multipath multi-hop communications that optimizes throughput and delay using feedback, packet allocation, and decentralized balancing, outperforming traditional ARQ protocols.

Contribution

It presents a novel adaptive, causal coding scheme with decentralized optimization and selective recoding for multipath multi-hop networks, improving throughput and delay performance.

Findings

Achieves over 90% of channel capacity with zero error in non-asymptotic regime.

Demonstrates up to 2x throughput gains over ARQ.

Achieves more than 3x delay reduction compared to baseline.

Abstract

We propose a novel multipath multi-hop adaptive and causal random linear network coding (AC-RLNC) algorithm with forward error correction. This algorithm generalizes our joint optimization coding solution for point-to-point communication with delayed feedback. AC-RLNC is adaptive to the estimated channel condition, and is causal, as the coding adjusts the retransmission rates using a priori and posteriori algorithms. In the multipath network, to achieve the desired throughput and delay, we propose to incorporate an adaptive packet allocation algorithm for retransmission, across the available resources of the paths. This approach is based on a discrete water filling algorithm, i.e., bit-filling, but, with two desired objectives, maximize throughput and minimize the delay. In the multipath multi-hop setting, we propose a new decentralized balancing optimization algorithm. This balancing algorithm minimizes the throughput degradation, caused by the variations in the channel quality of the paths at each hop. Furthermore, to increase the efficiency, in terms of the desired objectives, we propose a new selective recoding method at the intermediate nodes. We derive bounds on the throughput and the mean and maximum in order delivery delay of AC-RLNC, both in the multipath and multipath multi-hop case. In the multipath case, we prove that in the non-asymptotic regime, the suggested code may achieve more than 90% of the channel capacity with zero error probability. In the multipath multi-hop case, the balancing procedure is proven to be optimal with regards to the achieved rate. Through simulations, we demonstrate that the performance of our adaptive and causal approach, compared to selective repeat (SR)-ARQ protocol, is capable of gains up to a factor two in throughput and a factor of more than three in delay.