Overbooking Approach For Dynamic Spectrum Management

With the rapid development of the radio communication, the demands for the radiospectrum is increasing dramatically, and the contradiction between supply and demandof the spectrum is more and more prominent, so it is urgent to exploit a new technologyof utilizing the spectrum efficiency. Regarded as a new dynamic spectrum management(DSM) strategy, spectrum trading can effectively solve the contradiction betweenspectrum limitation and business bandwidth, optimize the spectrum allocation.This report independently considers the transaction process of spectrum and theactual use process. The primary user adopts the booking scheme to lease theuse-permission of spectrum and the secondary users submit their reservations and usethose spectrum in a future time slot. Considered the over-sale risk and the spare risk, arisk-based overbooking approach for dynamic spectrum management is conceived forimproving the attainable spectral efficiency and the revenue for the primary user. Firstly,we analyze the effect of no-show of the reservations, and develop an algorithm to derivethe optimal number of excess reservations, while minimizing the total compensationcosts. Secondly, a capacity allocation algorithm is developed to derive the optimalbooking limits for different classes of secondary users. At further, a LC-DCF denialscheme is analyzed, which can make sure the service for the higher class users and thenimprove the revenues.According to the time dynamicity of overbooking, we also conceive a slidingwindow-based overbooking approach for dynamic spectrum management. In the slidingwindow model, the time dependency and the delay sensitivity of service are considered,which can improve the primary user’s revenue whilst make sure the quality of servicefor the higher class users. In the overbooking mechanism with cancellations, thereservation problem is simplified to a final-value-decision problem, the booking periodand waiting period for each class SUs is recognized as a MDP problem. By solving theoptimal booking limits for different SUs, the PU can finally decide its optimalreservation strategy.