Section: New Results
Distributed Spectrum Management in TV White Space Networks
The radio frequency (RF) spectrum is a scarce resource that has recently become particularly critical with the increased wireless demand. For this reason, the Federal Communications Commission (FCC) has recently allowed for opportunistic access to the unused spectrum in the TV bands (also called “white space”). With opportunistic access, however, there is a need to deploy enhanced channel allocation and power control techniques to mitigate interference, including Adjacent-Channel Interference (ACI). TV White Space (TVWS) spectrum access is often investigated without taking into account ACI between the transmissions of TV Bands Devices (TVBDs) and licensed TV stations. Guard Bands (GBs) can be used to protect data transmissions and mitigate the ACI problem. Therefore, in  we consider a spectrum database that is administrated by a database operator, and an opportunistic secondary system, in which every TVBD is equipped with a single antenna that can be tuned to a subset of licensed channels. This can be done, for example, through adaptive channel aggregation or bonding techniques.
We investigate the distributed spectrum management problem in opportunistic TVWS systems using a game theoretical approach that accounts for adjacent channel interference and spatial reuse. TVBDs compete to access idle TV channels and select channel “blocks” that optimize an objective function. This function provides a tradeoff between the achieved rate and a cost factor that depends on the interference between TVBDs. We consider practical cases where contiguous or non-contiguous channels can be accessed by TVBDs, imposing realistic constraints on the maximum frequency span between the aggregated/bonded channels. We show that under general conditions, the proposed TVWS management games admit a potential function. Accordingly, a “best response” strategy allows us to determine the spectrum assignment of all players. This algorithm is shown to converge in a few iterations to a Nash Equilibrium (NE). Furthermore, we propose an effective algorithm based on Imitation dynamics, where a TVBD probabilistically imitates successful selection strategies of other TVBDs in order to improve its objective function. Numerical results show that our game theoretical framework provides a very effective tradeoff (close to optimal, centralized spectrum allocations) between efficient TV spectrum use and reduction of interference between TVBDs.