In this work, we consider the problem of multiuser scheduling for the downlink of cell-free massive multi-input multi-output networks with clustering. In particular, we develop a multiuser scheduling algorithm based on an enhanced greedy method that is deployed with linear precoding and clustering. Closed-form expressions for the sum-rate performance are derived when imperfect channel state information is considered. The proposed scheduling algorithm is then analyzed along with its computational cost and network signaling load. Numerical results show that the proposed scheduling method outperforms the existing methods and in low signal-to-noise ratios, its performance becomes much closer to the optimal approach.

In this work, we investigate the sum-rate performance of multicell and cell-free massive MIMO systems using linear precoding and multiuser scheduling algorithms. We consider the use of a network-centric clustering approach to reduce the computational complexity of the techniques applied to the cellfree system. We then develop a greedy algorithm that considers multiple candidates for the subset of users to be scheduled and that approaches the performance of the optimal exhaustive search. We assess the proposed and existing scheduling algorithms in both multicell and cell-free networks with the same coverage area. Numerical results illustrate the sum-rate performance of the proposed scheduling algorithm against existing approaches.