Dynamic Resource Management Optimisation for Flexible Satellite Payloads

This dissertation addresses the topic of dynamic resource management optimization for flexible satellite payloads. The capability to flexibly allocate on-board resources over the service coverage is becoming a must for future broadband satellite systems. The trend for future satellite flexible payloads is to assign resources in an intelligent manner according to the heterogeneous traffic demands. In particular, this thesis focuses on Beam Hopping (BH)-enabled systems, where a subset of beams can be illuminated at a given time. Conventional BH illumination pattern design provides all available spectrum to a selected set of beams as long as they are not adjacent to each other (to avoid inter-beam interference). In this thesis, advanced BH illumination pattern designs are explored and assessed. First, we address the BH design for geostationary satellites and target the shortcomings of adjacent beam avoidance requirements of conventional BH illumination designs. In particular, we propose a dynamic beam illumination scheme combined with selective precoding, where only sub-sets of beams that are subject to strong inter-beam interference implement interference mitigation techniques like precoding. The formulated binary quadratic programming (BQP) problem is proved to converge to a local optimum solution. Next, we propose a two-stage framework with a probabilistic perspective that exploits flexibility in the time and power domains at the same time. The first stage addresses the coupling relationship between power and beam activation probability. Conditioned on the optimal solution, we reformulate the problem and prove its convexity, and lastly propose a method for solving it iteratively. The second stage designs the detailed beam illumination pattern by mapping the beam activation probability obtained in the first stage. Last but not least, we address the BH illumination design problem for Lower Earth Orbit (LEO) satellite constellation systems, where a virtual cell on the ground can be served by multiple beams belonging to multiple satellites. As a consequence, we extend the flexibility in the time and power domains with the flexibility of serving a cell with different satellites. This additional degree of flexibility is shown to minimize transmission energy consumption. More precisely, we address the demand satisfaction constraint with the load coupling model, where parameters are given by their expectations. Based on the optimum condition, the three-variable problem is reformulated to an inverse matrix optimization problem with two variables. We prove the convexity of the objective and propose an iterative algorithm to solve the problem.