Stochastic Channel Access in Underwater Networks with Statistical Interference Modeling

Designing efficient medium access control protocols for underwater acoustic sensor networks (UW-ASNs) is a major challenge because of the spatial and temporal interference uncertainty caused by asynchronous transmissions and by the low propagation speed of sound. To address these challenges, in this article we propose a new approach for distributed underwater medium access based on lightweight and asynchronous distributed algorithms that optimize the access probability profile over a series of time slots based on a new statistical physical interference model. The latter is based on measuring the level of interference at multiple instants of time in each time slot in order to capture the effects of temporal uncertainty and of unaligned interference. At each measurement instant, the statistical properties of time-varying interference are represented by a Gamma probability distribution. The model is validated through extensive channel measurement experiments conducted with an underwater acoustic testbed in Lake LaSalle. Based on this model, we formulate the problem of queue-aware stochastic channel access. The objective is to maximize the sum throughput of a set of concurrent and mutually interfering source-destination pairs by letting the transmitters adjust their own transmission probability profiles, without collaborating with each other, over a series of time slots based on a statistical characterization of interference obtained through past observations. We propose an iterative distributed solution algorithm for this problem based on a best-response strategy. At each iteration, each node individually solves a non-convex optimization problem of logarithmic complexity. The performance of the proposed distributed algorithm is evaluated by comparing it with two alternative distributed schemes and with the global optimum obtained through a newly-developed centralized globally optimal solution algorithm. Results indicate that by jointly taking the queueing and multi-slot optimization into consideration considerable improvement in terms of sum-throughput can be achieved by the proposed distributed algorithm.