Joint 3D-Location Planning and Resource Allocation for XAPS-Enabled C-NOMA in 6G Heterogeneous Internet of Things

The sixth generation (6G) communication creates a fully connected world of terrestrial wireless and satellite communications, which achieves global seamless coverage. To obtain the tripartite balance of spectrum efficiency, system throughput and complexity at the receiving end, clustered-NOMA (C-NOMA) is recommended. With Low Altitude Platform Station (LAPS) like UAV for strengthening communication in certain areas, and High Altitude Platform Station (HAPS) for ensuring wide coverage, we put forward the XAPS-enabled (including one HAPS and multiple UAVs) C-NOMA system in 6G heterogeneous Internet of things and investigate the joint 3D-location planning and resource allocation problem by optimizing four factors systematically, which are the spectrum allocation, power control, horizontal coordinate and hovering altitude optimization of UAVs to maximize the overall system uplink achievable sum rate. Due to the strong coupling among these factors, it is a mixed integer nonlinear programming (MINLP) problem, which is extremely difficult to solve. Therefore, we decompose it and propose a two-stage solution. Specifically, in the first stage we transfer resource allocation problem into a many-to-one spectrum matching game coupled with power control, where UAVs and subchannels are two groups of participants. Then we complete the second stage by optimizing UAVs' 3D-locations, including horizontal coordinates and hovering altitudes. Finally, we repeat these two stages iteratively until the near-optimal result is obtained. Both theoretical analysis and simulations show that our proposed approach outperforms previous solutions in terms of system uplink sum rate with relatively low complexity.

Automated summary

6G communication provides global seamless coverage with C-NOMA system, and optimizes a series of factors through the XAPS-enabled system to maximize the overall system uplink achievable sum rate.