Medium Access Control protocol for Collaborative Spectrum Learning in Wireless Networks

TL;DR

This paper introduces a distributed medium access control protocol for collaborative spectrum learning in congested wireless networks, achieving minimal regret and high spectral efficiency through a novel auction-based approach.

Contribution

It presents a fully-distributed algorithm for spectrum collaboration that jointly addresses channel allocation and access scheduling with proven optimal regret.

Findings

Algorithm achieves logarithmic regret

Protocol enables low-complexity distributed auction

Simulation shows significant performance improvements

Abstract

In recent years there is a growing effort to provide learning algorithms for spectrum collaboration. In this paper we present a medium access control protocol which allows spectrum collaboration with minimal regret and high spectral efficiency in highly loaded networks. We present a fully-distributed algorithm for spectrum collaboration in congested ad-hoc networks. The algorithm jointly solves both the channel allocation and access scheduling problems. We prove that the algorithm has an optimal logarithmic regret. Based on the algorithm we provide a medium access control protocol which allows distributed implementation of the algorithm in ad-hoc networks. The protocol utilizes single-channel opportunistic carrier sensing to carry out a low-complexity distributed auction in time and frequency. We also discuss practical implementation issues such as bounded frame size and speed of convergence. Computer simulations comparing the algorithm to state-of-the-art distributed medium access control protocols show the significant advantage of the proposed scheme.