Spectrum auction framework for access allocation in cognitive radio networks

Abstract

Cognitive radio networks are emerging as a promising technology for the efficient use of radio spectrum. In these networks, there are two categories of networks on different channels: primary networks and secondary networks. A primary network on a channel has prioritized access to the channel and secondary networks can use the channel when the primary network is not using it. The access allocation problem is to select the primary and secondary networks on each channel. We develop an auction-based framework that allows networks to bid for primary and secondary access based on their utilities and traffic demands, and uses the bids to solve the access allocation problem. We develop algorithms for the access allocation problem and show how they can be used either to maximize the auctioneer's revenue given the bids, or to maximize the social welfare of the bidding networks, while enforcing incentive compatibility. We first consider the case when the bids of a network depend on which other networks it will share channels with. When there can be only one secondary network on a channel, we design an optimal polynomial-time algorithm for the access allocation problem based on reduction to a maximum matching problem in weighted graphs. When there can be two or more secondary networks on a channel, we show that the optimal access allocation problem is NP-Complete. Next, we consider the case when the bids of a network are independent of which other networks it will share channels with. We design a polynomial-time dynamic programming algorithm to optimally solve the access allocation problem when the number of possible cardinalities of the set of secondary networks on a channel is upper-bounded. Finally, we design a polynomial-time algorithm which approximates the access allocation problem within a factor of 2 when the above upper bound does not exist.