A Cost-Efficient Joint Optimization Approach for Downlink Multiuser Scheduling and Precoding

Joint design of multiuser scheduling and precoding is crucial in downlink multiple-input multiple-output (MIMO) transmissions, which generally involves mixed-integer programming with tightly coupled variables, making it difficult to solve. Existing methods tackle this challenging problem either by employing convex optimization techniques with high complexity, or by decoupling the problem into two subproblems: heuristic scheduling followed by separate precoding design, which often results in noticeable performance loss. In this letter, we propose a novel low-cost joint design approach for scheduling and precoding, which, compared to existing methods, can achieve superior performance while maintaining low computational complexity. Specifically, we formulate an approximate throughput maximization joint optimization problem leveraging signal-to-leakage-and-noise ratio (SLNR). This formulation facilitates the joint design by allowing us to directly determine the optimal precoding in closed forms and equivalently transform the joint design into a reformulation that relies solely on multiuser scheduling. We then propose a low-complexity iterative algorithm where closed-form solutions are derived in each iteration.

I. Introduction

In downlink multiuser multiple-input multi-output (MU-MIMO) scenarios, the optimal number of active users is often less than the number of transmit antenna to balance multiplexing gain and multiuser interference [1], [2]. Consequently, user scheduling, as well as the associated precoding design, plays a crucial role in downlink MU-MIMO transmissions [3].