The main goal of the activity is devising a joint system, payload and antenna co-design methodology for maximizing pre-determined performance figures of merit in ACM broadband systems. Although the explicit target of the joint design approach is the system capacity maximization, also cost aspects are expected to be duly taken into account. In particular, platform limitations in terms of mass, power and accommodation are to be included in the design as additional constraints to the optimization problem. The final outcome is the implementation of the devised optimization methodology in a software co-design tool and its validation by means of a simulation campaign applied to a number of representative system/payload architectures.
The key issue allowing the assessment of the performance of Flexible Systems consists of the system optimization leading to the optimum System Configuration, i.e. optimum Frequency, Polarization (and Power, if needed) Plans, which meet at best the target Capacity Requirements, generally non-uniformly distributed, with the assigned resources (Bandwidth and Power Budget).
Such optimization approach is envisaged to be carried out on a combinatorial basis by means of a hybrid procedure generally starting with a Genetic Algorithms step which is followed by a Neighbourhood Search refinement.
The optimization approach is intended to be of the constrained type in order to make the optimum System Configuration complying with the above mentioned performance and platform limitations.
When possible, parallel implementation is addressed in order to allow getting optimization results with acceptable computation time even for scenarios with high number of beams, otherwise prohibitive in terms of serial search.
Another key issue is assessing the level of flexibility of the system in terms of capability to fit changes in traffic distribution due to market evolution during satellite mission lifetime. This can be verified by making the system optimization to target different sets of capacity requirements which are representative of potential market developments over the selected coverage area on a specified time period.
The activity is mainly aimed at providing a SW tool able to exploit at their maximum the resources made available to payloads for Ka-Band Multi-Beam Broadband Satellite Systems in order to generate a Throughput Capacity Performance which meets to the highest level a specified Capacity Requirement distribution over the service area. Such a Co-Design Tool can be particularly useful for commercial satellite operators, which are recently requested to face non-uniform traffic demand distributions over the coverage and their evolution during the satellites mission lifetime.
It allows the design of flexible payloads, i.e. payloads able to allocate non-uniform bandwidth and power to beams in order to meet non-uniform traffic demand distributions, along with the assessment of their capacity performance. The benefits of introducing on-board satellite payload flexibility w.r.t. more classical payload design methods based on uniform bandwidth/power allocation can be pointed out by the comparison of the capacity and consumption performance of the two approaches.
The main driver of the activity is the identification of the most suitable optimization procedure able to cope with the environment under investigation. Due to the need of managing the frequency/polarization plan, the natural approach is expected to fall into the category of combinatorial optimization methods which, in case of a complex scenario (e.g. high number of beams), generally implies high computational effort with no guarantee of achieving the global optimum. Applicable optimization strategies can be found in the area of Evolutionary Algorithms (e.g. Genetic Algorithms), Neighbourhood Search, Simulated Annealing, etc.. Among them, or combination of them, the most appropriate approach, in terms of computational affordability, efficiency, etc, is to be selected.
Moreover such a combinatorial optimization has to comply with the constraints imposed by the problem (e.g. bandwidth and power budget made available by the selected payload/platform configuration, or system availability figures required by the service link). Therefore a constrained version of the combinatorial optimization procedure implementing direct and/or indirect techniques of compliance verification is to be addressed also taking into account their efficiency from the computational point of view.
Another basic aspect to be addressed is the maximum computational efficiency of the system, payload and antenna models used in the system performance assessment. This is required by their iterated use within an optimization loop so that computational effort can be minimised. In this respect a proper trade-off between modelling accuracy vs. computational efficiency has to be carried out.
The study is divided in 4 tasks as described below:
The project has been successfully completed.