Joint User Scheduling and Beamforming Design with Local CSI in Cell-Free Networks

The cell-free network (CFN) is a promising technology capable of delivering high-reliability, high-data rate wireless communication services for Metaverse communication. This paper studies a joint optimization problem of user scheduling (US) and beamforming (BF) in CFN, where constraints of per access point (AP) power and the limited number of the scheduled users per AP are considered. In order to reduce the interaction overhead, this problem is investigated using local channel state information (CSI). Since this problem is a mixed-integer nonlinear programming (MINP) program with non-convexity and high complexity, we propose an alternating optimization framework to solve this problem. Specifically, we first adopt the weighted
$l_{1}$
-norm approximation to transform the discrete variables into the continuous variables. Then, we solve the rest of the problem by fractional programming, and solve the subproblems alternatively. The analysis of complexity and convergence analysis validate the efficiency and accuracy of the proposed algorithm. Numerical results show that the cross-layer design of the US&BF scheme is superior to the separate design of US&BF schemes. In addition, the proposed algorithm with local CSI achieves a comparable data rate to the algorithms with global CSI.