Interference-aware frame optimization for the return link of a multi-beam satellite

Abstract

High throughput satellites have proven to be an excellent solution to provide Internet services to white spots or to complement other existing infrastructures. With the use of multi-beam antennas, the same frequency may be reused dozens of times across a single satellite coverage area, increasing the system capacity and profitability. Legacy frequency reuse patterns such as uncoordinated 4-color scheme ensure interference isolation at the expense of important capacity reduction, using only one fourth of the operator's share in the scarce Ka band. Thus, to increase the per-beam available bandwidth, it is necessary to look for more aggressive and efficient Frequency Reuse schemes, generating higher Co-Channel Interference which has to be analyzed and handled. In this paper, we focus on the DVB-RCS2 return link of a multi-beam satellite and investigate the possibility of reaching the upper bound of a coordinated 2-color system capacity through the use of Interference-aware User Scheduling techniques. We first formalize the problem as an Integer Linear Program and study the impact of greedy simplifications on the optimality and processing times of our optimization models.

MF-TDMA Scheduling Algorithm for Multi-Spot Beam Satellite Systems Based on Co-Channel Interference Evaluation

“…An interesting approach considering a real-time (slot-by-slot) implementation of an interference aware algorithm is performed in [17]. The numerical results, show promising performances regarding system throughput and sub-carriers utilization.…”

“…These algorithms also do not take into account realtime constraints. There are only a few publications targeting results on throughput for interference coordination in MF-TDMA [13] and [17] that provide execution time results.…”

“…The more relevant result of this work presented in [17] is to obtain an improvement of a +49% of throughput over the non-optimal scenario. The mean resolution time to achieve these results is 40s.…”

“…In order to compare the 'greedy' algorithm execution time with State of the Art algorithms a simulation using the system parameters of [13] and [17] has been performed. For the sake of fairness, the simulation has been run in computation platforms equivalent to the ones used by the previous references.…”

“…Even the results are not optimal (>80% of throughput compared to the 99% of [13] and +20% of increase compared to the +49% of [17]), the resolution time is fixed and therefore the algorithm can run in a real time system.…”