Issue No.01 - January (2011 vol.10)
Amir-Hamed Mohsenian-Rad , University of British Columbia, Vancouver
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2010.152
The aggregate capacity of wireless ad hoc networks can be increased substantially if each node is equipped with multiple network interface cards (NICs) and each NIC operates on a distinct frequency channel. Most of the recently proposed channel assignment algorithms are based on combinatorial techniques. Combinatorial channel assignment schemes may sometimes result in computationally complicated algorithms as well as inefficient utilization of the available frequency spectrum. In this paper, we analytically model channel and interface assignment problems as tractable continuous optimization problems within the framework of network utility maximization (NUM). In particular, the link data rate models for both single-channel reception and multichannel reception scenarios are derived. The assignment of both nonoverlapped and partially overlapped channels is also considered. We then propose two distributed multi-interface multichannel random access (DMMRA) algorithms for single-channel reception and multichannel reception scenarios. The DMMRA algorithms are fast, distributed, and easy to implement. Each algorithm solves the formulated NUM problem for each scenario. DMMRA requires each node to only iteratively solve a local, myopic, and convex optimization problem. Convergence and optimality properties of our algorithms are studied analytically. Simulation results show that our proposed algorithms significantly outperform utility-optimal combinatorial channel assignment algorithms in terms of both achieved network utility and throughput.
Multi-interface multichannel wireless ad hoc networks, random access, persistent probabilities, network utility maximization, convex optimization, single-channel reception, multichannel reception, partially overlapped frequency channels.
Amir-Hamed Mohsenian-Rad, "Distributed Multi-Interface Multichannel Random Access Using Convex Optimization", IEEE Transactions on Mobile Computing, vol.10, no. 1, pp. 67-80, January 2011, doi:10.1109/TMC.2010.152