Abstract: A task scheduling system that can be used to improve task assignment for multiple satellites, and thereby improve resource allocation in the execution of a task. In some implementations, configuration data for one or more satellites is obtained. Multiple objectives corresponding to a task to be performed using the satellites, and resource parameters associated with executing the task to be performed using the satellites are identified. A score for each objective included in the multiple objectives is computed by the terrestrial scheduler based on the resource parameters and the configuration data for the one or more satellites. The multiple objectives are assigned to one or more of the satellites. Instructions are provided to the one or more satellites that cause the one or more satellites to execute the task according to the assignment of the objectives to the one or more satellites.

Abstract: A task scheduling system that can be used to improve task assignment for multiple satellites, and thereby improve resource allocation in the execution of a task. In some implementations, configuration data for one or more satellites is obtained. Multiple objectives corresponding to a task to be performed using the satellites, and resource parameters associated with executing the task to be performed using the satellites are identified. A score for each objective included in the multiple objectives is computed by the terrestrial scheduler based on the resource parameters and the configuration data for the one or more satellites. The multiple objectives are assigned to one or more of the satellites. Instructions are provided to the one or more satellites that cause the one or more satellites to execute the task according to the assignment of the objectives to the one or more satellites.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learning estimation networks in a communications system. One of the methods includes: processing first information with ground truth information to generate a first RF signal by altering the first information by channel impairment having at least one channel effect, using a receiver to process the first RF signal to generate second information, training a machine-learning estimation network based on a network architecture, the second information, and the ground truth information, receiving by the receiver a second RF signal transmitted through a communication channel including the at least one channel effect, inferring by the trained estimation network the receiver to estimate an offset of the second RF signal caused by the at least one channel effect, and correcting the offset of the RF signal with the estimated offset to obtain a recovered RF signal.

Abstract: A task scheduling system that can be used to improve task assignment for multiple satellites, and thereby improve resource allocation in the execution of a task. In some implementations, configuration data for one or more satellites is obtained. Multiple objectives corresponding to a task to be performed using the satellites, and resource parameters associated with executing the task to be performed using the satellites are identified. A score for each objective included in the multiple objectives is computed by the terrestrial scheduler based on the resource parameters and the configuration data for the one or more satellites. The multiple objectives are assigned to one or more of the satellites. Instructions are provided to the one or more satellites that cause the one or more satellites to execute the task according to the assignment of the objectives to the one or more satellites.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learning estimation networks in a communications system. One of the methods includes: processing first information with ground truth information to generate a first RF signal by altering the first information by channel impairment having at least one channel effect, using a receiver to process the first RF signal to generate second information, training a machine-learning estimation network based on a network architecture, the second information, and the ground truth information, receiving by the receiver a second RF signal transmitted through a communication channel including the at least one channel effect, inferring by the trained estimation network the receiver to estimate an offset of the second RF signal caused by the at least one channel effect, and correcting the offset of the RF signal with the estimated offset to obtain a recovered RF signal.

Abstract: A task scheduling system that can be used to improve task assignment for multiple satellites, and thereby improve resource allocation in the execution of a task. In some implementations, configuration data for one or more satellites is obtained. Multiple objectives corresponding to a task to be performed using the satellites, and resource parameters associated with executing the task to be performed using the satellites are identified. A score for each objective included in the multiple objectives is computed by the terrestrial scheduler based on the resource parameters and the configuration data for the one or more satellites. The multiple objectives are assigned to one or more of the satellites. Instructions are provided to the one or more satellites that cause the one or more satellites to execute the task according to the assignment of the objectives to the one or more satellites.

Abstract: A task scheduling system that can be used to improve task assignment for multiple satellites, and thereby improve resource allocation in the execution of a task. In some implementations, configuration data for one or more satellites is obtained. Multiple objectives corresponding to a task to be performed using the satellites, and resource parameters associated with executing the task to be performed using the satellites are identified. A score for each objective included in the multiple objectives is computed by the terrestrial scheduler based on the resource parameters and the configuration data for the one or more satellites. The multiple objectives are assigned to one or more of the satellites. Instructions are provided to the one or more satellites that cause the one or more satellites to execute the task according to the assignment of the objectives to the one or more satellites.

Abstract: A task scheduling system that can be used to improve task assignment for multiple satellites, and thereby improve resource allocation in the execution of a task. In some implementations, configuration data for one or more satellites is obtained. Multiple objectives corresponding to a task to be performed using the satellites, and resource parameters associated with executing the task to be performed using the satellites are identified. A score for each objective included in the multiple objectives is computed by the terrestrial scheduler based on the resource parameters and the configuration data for the one or more satellites. The multiple objectives are assigned to one or more of the satellites. Instructions are provided to the one or more satellites that cause the one or more satellites to execute the task according to the assignment of the objectives to the one or more satellites.

Abstract: A task scheduling system that can be used to improve task assignment for multiple satellites, and thereby improve resource allocation in the execution of a task. In some implementations, configuration data for one or more satellites is obtained. Multiple objectives corresponding to a task to be performed using the satellites, and resource parameters associated with executing the task to be performed using the satellites are identified. A score for each objective included in the multiple objectives is computed by the terrestrial scheduler based on the resource parameters and the configuration data for the one or more satellites. The multiple objectives are assigned to one or more of the satellites. Instructions are provided to the one or more satellites that cause the one or more satellites to execute the task according to the assignment of the objectives to the one or more satellites.

Abstract: The present invention relates to an authentication method for wireless distribution system including at least one base station providing access service to mobile stations in a coverage of the base station. In the authentication method, an unregistered base station receives an authentication request from a mobile station, multicast an identity request for identifying the mobile station over the wireless distribution system, receives identity responses from at least one base station in response to the identity request, and performs authentication of the mobile station on the basis of the identity responses. The distributed authentication method of the present invention is performed without AAA server, when a new base station is installed or isolated base stations are joined, such that it is possible to extend the network in an easy manner without degradation of the security degree and additional labor burden of the operator.