Spectrum Allocation for Frequency-Agile Radio Networks under Physical Interference Models

Spectrum frequency allocation problems are fundamen- tal problems in wireless spectrum auctions and wireless LAN management. Due to their complexity, most ex- isting proposals simplify the allocation problems by re- ducing physical interference to a graph-based interfer- ence model. In this paper, we propose LIGHTHOUSE, a new line of efficient approximation algorithms that oper- ate directly on physical interference models and perform within a constant bound from the optimum under geo- metric signal propagation. Our design is motivated by the fact that conventional greedy methods become brittle un- der physical interference models although they perform well under graph interference models. We overcome such brittleness by building a new globalized optimiza- tion path, first reducing the optimization constraints into linear constraints to produce a starting solution and then applying iterative improvements to approach the global optimum. To our best knowledge, our solution is the first to achieve a constant approximation bound. It also has low complexity and supports a wide-range of optimiza- tion goals. Experiments show that our solution outper- forms existing solutions by 50+ % in utilization, and is within 10% gap from the optimal solution.