Joint User Scheduling and Beamforming Design for Multiuser MISO Downlink Systems

In multiuser communication systems, user scheduling and beamforming design are two fundamental problems, which are usually investigated separately in the existing literature. In this work, we focus on the joint optimization of user scheduling and beamforming design with the goal of maximizing the set cardinality of scheduled users. Observing that this problem is computationally challenging due to the non-convex objective function and coupled constraints in continuous and binary variables. To tackle these difficulties, we first propose an iterative optimization algorithm (IOA) relying on the successive convex approximation and uplink-downlink duality theory. Then, motivated by IOA and graph neural networks, a joint user scheduling and power allocation network (JEEPON) is developed to address the investigated problem in an unsupervised manner. The effectiveness of IOA and JEEPON is verified by various numerical results, and the latter achieves a close performance but lower complexity compared with IOA and the greedy-based algorithm. Remarkably, the proposed JEEPON is also competitive in terms of the generalization ability in dynamic wireless network scenarios.