الفهرس 
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Abstract
The unprecedented growth of massive satellite constellations, as well as the advent of a significant number of steerable beams and digital payloads, poses new challenges in determining how to distribute satellite resources. New resource management strategies that operate in high-dimensional and dynamic environments will be required to meet these new challenges. Under the context of satellite communications, the resource allocation (RA) problem is decomposed into six sub-problems: frequency assignment, power allocation, beam placement, user grouping, gateway routing, and satellite routing.
Existing conventional techniques of satellite resource allocation become unfeasible to deal with new challenges. The majority of frequency assignment and beam placement methods fail to fulfill the requirements of the high-dimensional and dynamic environments without defaulting on bandwidth utilization and power efficiency.
This thesis presents a groundbreaking approach to satellite communication system design through the introduction of two novel algorithms: a meticulously optimized multi-beam placement algorithm and a new optimized frequency assignment algorithm based on a mathematical programming language (AMPL) that can completely design a dynamic frequency plan with bearing in mind system constraints like handovers and interference.
The beam placement model’s exceptional efficiency became unmistakably apparent as it successfully provided coverage for a18,000 users while utilizing 2,751 beams, showcasing a remarkable reduction in beam count compared to the baseline benchmark, which employed a substantially larger tally of 9,633 beams. Notably, the model efficiency is particularly advantageous in large-scale deployments where the model’s ability to strategically group numerous users within a single beam leads to a significant reduction in redundancy. This accomplishment firmly establishes the model’s robustness and reliability in densely populated user scenarios, setting a new standard for satellite communication system design.
The proposed frequency planning algorithms are evaluated with multiple objective functions such as bandwidth maximization and produces optimal solutions. Experimentally, the frequency assignment optimized algorithm can allocate at least 155% more bandwidth compared to previous baseline benchmarks.