Systems and methods for supporting more flexible coverage areas and spatial capacity assignments using satellite communications systems are disclosed. A hub-spoke, bent-pipe satellite communications system includes: terminals; gateways; a controller for specifying data for controlling satellite operations in accordance with a frame definition including timeslots for a frame and defining an allocation of capacity between forward and return traffic. The satellite communications system may employ a satellite with a feed array assembly and may use on-board beamforming or ground-based beamforming. Beam hopping within timeslots of the frame may be used to provide coverage to different cells in different time periods. The flexible coverage areas may be provided using changes in satellite position, antenna patterns, or beam resource allocations.

A tool comprises a distal portion and a proximal portion spaced apart by a shaft along a longitudinal axis. The distal portion includes a distal link and the proximal portion including a proximal link. The distal link and proximal link form a pair of links. The tool also comprises a set of tension load bearing members connecting the proximal link and the distal link and terminating at the links of the pair to transfer movement therebetween. The tool also comprises an articulation lock positioned between the distal portion and the proximal portion and configured to allow through passage of the set of tension load bearing members. The articulation lock is adjustable between an unlocked configuration in which the proximal and distal links are moveable and a locked configuration in which an effective length of the shaft is increased, creating a force to impede movement of the proximal and distal links.

A communications system for line-of-sight (LOS) and beyond-line-of-sight (BLOS) communications using a single aperture includes one or more operators positioned within an environment, wherein each operator includes a common aperture, one or more low-earth orbit satellites communicatively coupled to a plurality of communications sub-systems disposed on the operators. In one embodiment, the communications sub-systems may include a first antenna element to transmit and receive first radio frequency signals along a first directional link via the common aperture. In another embodiment, the communications sub-systems may include a second antenna element to transmit and receive second radio frequency signals along a second directional link via the common aperture.

A communications system for line-of-sight (LOS) and beyond-line-of-sight (BLOS) communications using a single aperture includes one or more operators positioned within an environment, wherein each operator includes a common aperture, one or more low-earth orbit satellites communicatively coupled to a plurality of communications sub-systems disposed on the operators. In one embodiment, the communications sub-systems may include a first antenna element to transmit and receive first radio frequency signals along a first directional link via the common aperture. In another embodiment, the communications sub-systems may include a second antenna element to transmit and receive second radio frequency signals along a second directional link via the common aperture.

32 The present disclosure proposes schemes, techniques, designs and methods pertaining to frequency synchronization for integration of terrestrial network (TN) and non-terrestrial network (NTN) communications. Communications between a user equipment (UE) and a terrestrial network (TN) and communications between the UE and a non-terrestrial network (NTN) are established. A frequency shift in the communications between the UE and the NTN is compensated regardless of availability of information related to a movement of the UE and a relative location of the NT network node of the NTN with respect to the UE.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for bandwidth allocation using machine learning. In some implementations, a request for bandwidth in a communications system is received. Data indicative of a measure of bandwidth requested and a status of the communication system are provided as input to a machine learning model. One or more outputs from the machine learning model indicate an amount of bandwidth to allocate to the terminal, and bandwidth is allocated to the terminal based on the one or more outputs from the machine learning model.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for bandwidth allocation using machine learning. In some implementations, a request for bandwidth in a communications system is received. Data indicative of a measure of bandwidth requested and a status of the communication system are provided as input to a machine learning model. One or more outputs from the machine learning model indicate an amount of bandwidth to allocate to the terminal, and bandwidth is allocated to the terminal based on the one or more outputs from the machine learning model.

The disclosure relates to a method for transmitting sensor data from multiple sensors to a satellite. In a first phase, which is designated as a registration phase, the satellite registers the sensors in question and allocates each sensor a time window for transmitting the respective sensor data, and in a second phase, which is designated as a transmission phase, the satellite requests the sensor data in the individual sensors in a controlled manner, e.g., according to a list generated by the satellite during the registration phase. Thus, it is possible for satellites to access a ground-based sensor system in an optimized and self-learning manner. The disclosure additionally relates to a satellite suitable for carrying out the aforementioned method.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for bandwidth allocation using machine learning. In some implementations, a request for bandwidth in a communications system is received. Data indicative of a measure of bandwidth requested and a status of the communication system are provided as input to a machine learning model. One or more outputs from the machine learning model indicate an amount of bandwidth to allocate to the terminal, and bandwidth is allocated to the terminal based on the one or more outputs from the machine learning model.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for bandwidth allocation using machine learning. In some implementations, a request for bandwidth in a communications system is received. Data indicative of a measure of bandwidth requested and a status of the communication system are provided as input to a machine learning model. One or more outputs from the machine learning model indicate an amount of bandwidth to allocate to the terminal, and bandwidth is allocated to the terminal based on the one or more outputs from the machine learning model.