Tunable fairness-based capacity allocation for satellite systems with adaptive physical layer

Abstract

Systems with an adaptive physical layer make use of the channel conditions information in order to adapt their transmission to the channel with adaptive coding and modulation (ACM) techniques. The adaptability of the physical layer introduces new challenges as well as degrees of freedom in the higher layers since the system no longer has a fixed capacity but the capacity becomes time-and-location dependant. This adaptability also has a huge impact in the capacity allocation since the resource is not constant anymore. Moreover, a main challenge lies in providing Quality-of-Service (QoS) suitable for multimedia applications meeting at the same time the required Service Level Agreements (SLA). This situation requires the development of powerful and dynamic strategies for adaptive capacity allocation. In this paper, we present a novel adaptive capacity allocation solution to conciliate the higher resources needs of users that require higher levels of protection (lower spectral efficiencies), with the ability of offering higher throughput to users that require lower levels of protection (higher spectral efficiencies). We have developed a capacity allocation algorithm that introduces fairness as a tunable parameter. This approach makes it possible to adapt the resource manager behavior at any moment in order to guarantee the fulfillment of short-term and long-term user requirements in presence of time-and-location variant capacity. The proposed algorithm also supports differentiation of services that comply with the requirements for implementing QoS. An example scenario is proposed and system performance is computed as a function of the tunable fairness index and compared against other approaches. Our results show that tunable fairness is an effective scheduling tool for broadand satellite systems with adaptive physical layer.