In this paper, we investigate a method for clustering user equipment (UE)-specific transmission access points (APs) in downlink cell-free multiple-input multiple-output (MIMO) assuming that the APs distributed over the system coverage know only part of the instantaneous channel state information (CSI). As a beamforming (BF) method based on partial CSI, we use a layered partially non-orthogonal zero-forcing (ZF) method based on channel matrix muting, which is applicable to the case where different transmitting AP groups are selected for each UE under partial CSI conditions. We propose two AP clustering methods. Both proposed methods first tentatively determine the transmitting APs independently for each UE and then iteratively update the transmitting APs for each UE based on the estimated throughput considering the interference among the UEs. One of the two proposed methods introduces a UE cluster for each UE into the iterative updates of the transmitting APs to balance throughput performance and scalability. Computer simulations show that the proposed methods achieve higher geometric-mean and worst user throughput than those for the conventional methods.

This paper extends our previously reported non-orthogonal multiple access (NOMA)-based highly-efficient and low-latency hybrid automatic repeat request (HARQ) method for ultra-reliable low latency communications (URLLC) to the case with inter-base station cooperation. In the proposed method, delay-sensitive URLLC packets are preferentially multiplexed with best-effort enhanced mobile broadband (eMBB) packets in the same channel using superposition coding to reduce the transmission latency of the URLLC packet while alleviating the throughput loss in eMBB. Although data transmission to the URLLC terminal is conducted by multiple base stations based on inter-base station cooperation, the proposed method allocates radio resources to URLLC terminals which include scheduling (bandwidth allocation) and power allocation at each base station independently to achieve the short transmission latency required for URLLC. To avoid excessive radio resource assignment to URLLC terminals due to independent resource assignment at each base station, which may result in throughput degradation in eMBB terminals, we employ an adaptive path-loss-dependent weighting approach in the scheduling-metric calculation. This achieves appropriate radio resource assignment to URLLC terminals while reducing the packet error rate (PER) and transmission delay time thanks to the inter-base station cooperation. We show that the proposed method significantly improves the overall performance of the system that provides simultaneous eMBB and URLLC services.