Adaptive resource allocation for multiuser OFDM-based cognitive radio systems

Major challenges in the design of next generation wireless communication systems include harsh propagation environments and scarce resources such as power and spectrum. Cognitive radio (CR) is a promising concept for improving the utilization of scarce radio spectrum resources. Orthogonal frequency division multiplexing (OFDM) is regarded as a technology which is well-matched for CR systems. Dynamic resource allocation is an important task in such systems. In this thesis, a novel fair multiuser resource allocation algorithm for OFDM CR systems is presented. Although not optimal, the algorithm has low computational complexity. The algorithm attempts to maximize the total transmit bit rate (system throughput) of a group of secondary (unlicensed or CR) users subject to (1) a total transmit power constraint for secondary users, (2) a maximum tolerable interference level which can be tolerated by primary (licensed) users. The algorithm is fair in the sense that it tries whenever possible to allocate bits to users who have not received their fair share of service. Simulation results show that the proposed algorithm achieves a performance close to optimal. The effect on system throughput of changing various system parameter values is also examined. A novel cost minimization algorithm for multiuser OFDM cognitive radio systems is also proposed. The objective is to minimize a cost function which takes into account the interference power experienced by the primary user as well as the base station transmit power for secondary users given minimum bit rate requirements for each secondary user. It is found that the proposed algorithm provides a performance which is fairly close to optimal. The influence of a relative weight parameter on the base station (BS) transmit power for secondary users and the primary user interference power is also discussed.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat