A Novel Routing Algorithm Based on Multi-Objective Optimization for Satellite Networks

The performance of satellite networks largely depends on their routing algorithm. Existing routing algorithms for satellite networks usually are not quite adaptive or have the disadvantage of a large consumption in both computation and storage resources. In this paper, we propose a novel routing algorithm based on dynamic clustering for LEO satellite networks. By dynamic forming cluster of the satellite network, the routing algorithm is both adaptive, computational effective and need much less storage space. Simulation results show that our routing algorithm performs better and are more robust when the network topology changes.

A high‐performance polarization reflector is introduced based on anisotropic metasurface. This structure can convert a linearly polarized (LP) incident electromagnetic (EM) wave into a circularly polarized (CP) reflection wave. The unit cell of the proposed metasurface is made of metallic patch imprinted on the top surface of a metal‐backed single‐layer dielectric substrate. The shape of this metallic patch is a combination of a deformed Jerusalem cross and two deformed L. The simulation results show that the LP incident EM wave is converted to CP reflected wave from 7 to 19.4 GHz, which the bandwidth of axis ratio less than 3 dB is 12.4 GHz and the relative bandwidth is 94%. The current distributions and equivalent circuit model are given to analyze the generation of circularly polarized waves. To verify the metasurface structure performance, a sample consisting of 24 × 24 unit cells is fabricated and measured. The experimental and simulation 3‐dB AR bandwidth are basically consistent with each other, which verify the properties of the design. The proposed metasurface structure has potential application in microwave sensors and antenna design to manipulate the polarization states of EM waves.

For a class of Itô stochastic linear systems with the Markov jumping and linear fractional uncertainty, the stochastic stabilization problem is investigated via state feedback and dynamic output feedback, respectively. In order to guarantee the stochastic stability of such uncertain systems, state feedback and dynamic output control law are, respectively, designed by using multiple Lyapunov function technique and LMI approach. Finally, two numerical examples are presented to illustrate our results.