Location-Based Resource Allocation for OFDMA Cognitive Radio Systems

Abstract

Cognitive radio is one of the hot topics for emerging and future wireless communication. It has been proposed as a suitable solution for the spectrum scarcity caused by the increase in frequency demand. The concept is based on allowing unlicensed users, called cognitive or secondary users, to share the unoccupied frequency bands with their owners, called the primary users, under constraints on the interference they cause to them. In order to estimate this interference, the cognitive system usually uses the channel state information to the primary user, which is often impractical to obtain. However, we propose to use location information, which is easier to obtain, to estimate this interference. The purpose of this work is to propose a subchannel and power allocation method which maximizes the secondary users' total capacity under the constraints of limited budget power and total interference to the primary under certain threshold. We model the problem as a constrained optimization problem for both downlink and uplink cases. Then, we propose low-complexity resource allocation schemes based on the waterfilling algorithm. The simulation results show the efficiency of the proposed method with comparison to the exhaustive search algorithm.