  This paper presents a centralized framework for optimizing the joint design
of beam placement, power, and bandwidth allocation in an MEO satellite
constellation to fulfill the heterogeneous traffic demands of a large number of
global users. The problem is formulated as a mixed integer programming problem,
which is computationally complex in large-scale systems. To overcome this
challenge, a three-stage solution approach is proposed, including user
clustering, cluster-based bandwidth and power estimation, and MEO-cluster
matching. A greedy algorithm is also included as a benchmark for comparison.
The results demonstrate the superiority of the proposed algorithm over the
benchmark in terms of satisfying user demands and reducing power consumption.
