Bounded-Contention Coding for Wireless Networks in the High SNR Regime

TL;DR

This paper introduces Bounded-Contention Coding (BCC), a novel method that leverages collisions in wireless networks to enable efficient deterministic and probabilistic communication, improving performance in high contention scenarios.

Contribution

The paper presents BCC, a new coding technique that allows decoding of collisions, enabling faster deterministic and probabilistic broadcast algorithms in wireless networks.

Findings

Deterministic local broadcast within O(a log n + al) bits for full-duplex radios.

Probabilistic global broadcast within O((D + a + log n)(a log n + l)) bits.

Effective contention estimation for adaptive broadcast in unknown contention scenarios.

Abstract

Efficient communication in wireless networks is typically challenged by the possibility of interference among several transmitting nodes. Much important research has been invested in decreasing the number of collisions in order to obtain faster algorithms for communication in such networks. This paper proposes a novel approach for wireless communication, which embraces collisions rather than avoiding them, over an additive channel. It introduces a coding technique called Bounded-Contention Coding (BCC) that allows collisions to be successfully decoded by the receiving nodes into the original transmissions and whose complexity depends on a bound on the contention among the transmitters. BCC enables deterministic local broadcast in a network with n nodes and at most a transmitters with information of l bits each within O(a log n + al) bits of communication with full-duplex radios, and O((a log n + al)(log n)) bits, with high probability, with half-duplex radios. When combined with random linear network coding, BCC gives global broadcast within O((D + a + log n)(a log n + l)) bits, with high probability. This also holds in dynamic networks that can change arbitrarily over time by a worst-case adversary. When no bound on the contention is given, it is shown how to probabilistically estimate it and obtain global broadcast that is adaptive to the true contention in the network.