Convex Optimization
WUWNet '06 Proceedings of the 1st ACM international workshop on Underwater networks
Understanding spatio-temporal uncertainty in medium access with ALOHA protocols
Proceedings of the second workshop on Underwater networks
Distributed CDMA-based MAC Protocol for Underwater Sensor Networks
LCN '07 Proceedings of the 32nd IEEE Conference on Local Computer Networks
A CDMA-based medium access control for underwater acoustic sensor networks
IEEE Transactions on Wireless Communications
IEEE Transactions on Mobile Computing
Shallow water acoustic networks
IEEE Communications Magazine
Underwater acoustic network with random access: a physical layer perspective
Proceedings of the Eighth ACM International Conference on Underwater Networks and Systems
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Designing 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, respectively. To deal with this uncertainty, this paper proposes a queue-aware distributed access scheme, in which each transmitter optimizes a transmission probability profile based on which it decides whether to transmit or to enqueue its packets over a series of time slots based on a statistical characterization of interference obtained through its past observations. To model the effect of unaligned interference, we propose a so-called L-measurement method, where interference is measured at multiple instants of time in each time slot to capture the effects of temporal uncertainty. We present a mathematical formulation of the problem of dynamic transmission strategy optimization and propose an iterative distributed solution algorithm designed based on a best-response strategy. At each iteration, each node individually solves a nonconvex optimization problem of logarithmic complexity with the number of time slots jointly considered. The performance of the proposed distributed solution algorithm is evaluated by comparing it to two alternative distributed schemes and to the global optimum obtained through a newly-developed centralized globally optimal solution algorithm. Results indicate that considerable improvement in terms of sum-throughput can be achieved by the proposed distributed algorithm by jointly taking the queueing and multi-slot optimization into consideration.