Broadband satellites, operating at Ka band and above, are playing more and more important roles in future satellite networks. Meanwhile, rain attenuation is the dominant impairment in these bands. In this context, a dynamic power allocation scheme based on rain attenuation prediction is proposed. By this scheme, the system can dynamically adjust the allocated power according to the time-varying predicted rain attenuation. Extensive simulation results demonstrate the improvement of the dynamic scheme over the static allocation. It can be concluded that the allocated capacities match the traffic demands better by introducing such dynamic power allocation scheme and the waste of power resources is also avoided.

A novel and efficient coding method is proposed to improve person re-identification in the XQDA subspace. Traditional CRC (Collaborative Representation based Classification) conducts independent dictionary coding for each image and can not guarantee improved results over conventional euclidian distance. In this letter, however, a specific model is separately constructed for each probe image and each gallery image, i.e. in probe-galley pairwise manner. The proposed pairwise-specific CRC method can excavate extra discriminative information by enforcing a similarity item to pull similar sample-pairs closer. The approach has been evaluated against current methods on two benchmark datasets, achieving considerable improvement and outstanding performance.