A methodology to benchmark flexible payload architectures in a megaconstellation use case

This paper proposes a methodology to benchmark satellite payload architectures and find the optimal trade-offs between high flexibility and low complexity. High flexibility would enable the satellite to adapt to various distributions of user terminals on the ground and fulfill the data rate demand of these users. Besides, low complexity is required to keep satellite networks competitive in the context of emerging 5G networks. To estimate the flexibility of a payload, an indicator to characterize the non-uniformity of user distributions is proposed. Each benchmarked payload may be characterized by a graph relating the throughput to this parameter further denoted (Formula presented.). The payload provides the same throughput trends for different scenarios of user distributions with the same (Formula presented.) parameter. As a consequence, the average capacity of the system may be estimated by (a) calculating the probability distribution of (Formula presented.) over the orbit and (b) integrating the throughput based on this payload response. It thus results in a straightforward way for benchmarking payloads directly on an estimation of the averaged capacity, accounting for the user distribution over the earth. A simulation platform has been developed to characterize the payload throughput including the implementation of a resource allocation algorithm that accounts for constraints of various payloads. Using this definition and the developed tool, we benchmark a bent-pipe architecture, a beam hopping architecture and a hybrid beam-steering architecture for a LEO megaconstellation use case. The methodology showcases the interest for investigating different payload architectures depending on realistic traffic scenario analysis.