Quantum Inspired Evolutionary algorithm for joint user selection and power allocation for uplink cognitive MIMO systems

In this paper, we consider the uplink communication in a network of cognitive radio nodes. The transmitting nodes and the receiver are equipped with multiple antennas and MIMO processing abilities. For this network, we study the problem of interference-aware joint secondary user (SU) selection/scheduling and power control (JSUS-QPC). The main objective of the JSUS-QPC is to maximize the sum-rate capacity of the cognitive MIMO uplink communication system under the constraint that the interference to the primary users (PU) is below a specified level. We formulate this optimization problem as nonlinear integer programming problem. The computational complexity of finding an optimal solution to the JSUS-QPC problem by exhaustive search grows exponentially with the number of users and power levels. Therefore, we apply a Quantum Inspired Evolutionary algorithm (QIEA) to determine the suboptimal solution to the JSUS-QPC problem. The proposed scheme has low computational complexity and its results are comparable to the optimal exhaustive search algorithm.