Joint Group Scheduling and Multicast Beamforming for Downlink Large-Scale Multi-Group Multicast
arxiv(2024)
摘要
Next-generation wireless networks need to handle massive user access
effectively. This paper addresses the problem of joint group scheduling and
multicast beamforming for downlink multicast with many active groups. Aiming to
maximize the minimum user throughput, we propose a three-phase approach to
tackle this difficult joint optimization problem efficiently. In Phase 1, we
utilize the optimal multicast beamforming structure obtained recently to find
the group-channel directions for all groups. We propose two low-complexity
scheduling algorithms in Phase 2, which determine the subset of groups in each
time slot sequentially and the total number of time slots required for all
groups. The first algorithm measures the level of spatial separation among
groups and selects the dissimilar groups that maximize the minimum user rate
into the same time slot. In contrast, the second algorithm first identifies the
spatially correlated groups via a learning-based clustering method based on the
group-channel directions, and then separates spatially similar groups into
different time slots. Finally, the multicast beamformers for the scheduled
groups are obtained in each time slot by a computationally efficient method.
Simulation results show that our proposed approaches can effectively capture
the level of spatial separation among groups for scheduling to improve the
minimum user throughput over the conventional approach that serves all groups
in a single time slot or one group per time slot, and can be executed with low
computational complexity.
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