Low Earth Orbit （LEO） satellites networks can provide multimedia service and plays an increasingly important role in the exploitation of space. However, one of the challenges in LEO satellites networks is that the s...Low Earth Orbit （LEO） satellites networks can provide multimedia service and plays an increasingly important role in the exploitation of space. However, one of the challenges in LEO satellites networks is that the services are suffered from high symbol error, limited storage space and limited available energy. To analyze the performance of the service in LEO satellites networks, a model, based on differential game, is proposed for satisfying the QoS requirements of multimedia applications. The controller of our model is the transmitting rate and the object is to maximize the payoff depending on the error symbol rate, the available energy, the bandwidth and the process ability so as to guarantee the QoS service. In order to solve our built model, we use the Bellman theorem to make formulas on the trance of the optimal transmitting rate. Furthermore, simulation results verify that the service can be maximized by using our derived transmitting rate trance.展开更多
基金National Science Foundation Project of P.R.China，China Postdoctoral Science Foundation
文摘Low Earth Orbit （LEO） satellites networks can provide multimedia service and plays an increasingly important role in the exploitation of space. However, one of the challenges in LEO satellites networks is that the services are suffered from high symbol error, limited storage space and limited available energy. To analyze the performance of the service in LEO satellites networks, a model, based on differential game, is proposed for satisfying the QoS requirements of multimedia applications. The controller of our model is the transmitting rate and the object is to maximize the payoff depending on the error symbol rate, the available energy, the bandwidth and the process ability so as to guarantee the QoS service. In order to solve our built model, we use the Bellman theorem to make formulas on the trance of the optimal transmitting rate. Furthermore, simulation results verify that the service can be maximized by using our derived transmitting rate trance.
