Efficient Resource Allocation Scheduling for MIMO-OFDMA-CR Downlink Systems

In this paper, we consider the resource allocation problem in a Cognitive Radio (CR) downlink system employing both Orthogonal Frequency Division Multiple Access (OFDMA) and Multiple-Input Multiple-Output (MIMO) technologies. We aim at maximizing the total cognitive system throughput subject to the interference power constraint at the Primary Receiver (PR), the total transmission power constraint at the Secondary Base Station (SBS), and the Quality of Service (QoS) requirement for each SU in terms of the data rate and Bit Error Rate (BER). This joint resource allocation problem integrates subcarrier assignment, power allocation, bit loading, and interference management, and can be formulated as a Binary Linear Programming (BLP) framework. Although the Branch and Bound (BnB) algorithm is a general approach to obtain the optimal solution for a BLP problem, it is impractical in this joint resource allocation problem due to the high computational complexity. In order to provide a good balance between performance and computational complexity, a Novel Two-Step based (NTS) algorithm is proposed in this paper. Numerical results show that the NTS algorithm can reduce the computational complexity significantly with only marginal performance degradation.