Spectrum allocations algorithms in wireless networks

All wireless devices rely on access to the radio frequency spectrum, which has been chronically regulated by static allocation policies. With recent fast growing of services and devices, the remaining spectrum available for future wireless services is being exhausted, known as the spectrum scarcity problem. The current fixed spectrum allocation scheme leads to significant spectrum white spaces (including spectral, temporal, and geographic), where many allocated spectrum blocks are used only in certain geographical areas and/or in brief periods of time. In this work, we design and analyze variant allocation algorithms for better spectrum utilization and study some fundamental bounds. We first propose algorithms for offline model, in which all requests are known. We also address the problems in online model, where allocation decision should be made when only a few spectrum requests are known. In the online model, we focus on two different cases. The first one assumes no statistic of future requests are known, and the second one assumes some statistic is known or can be learned. For all these models, we design efficient spectrum allocation methods and analytically prove most of them are asymptotically optimal. Our extensive simulation results also verify our theoretical conclusion.