Some demonstrative embodiments include devices, systems and/or methods to establish a connection to the Internet via a local gateway (L-GW) function for a LIPA or a SIPTO@LN. The establishment of the connection to the Internet may be performed, for example, by at least one of an E-RAB SETUP procedure, an INITIAL CONTEXT SETUP procedure, an INITIAL UE MESSAGE procedure or an UPLINK NAS TRANSPORT procedure.

A method for determining a Quality of Service (QoS) policy can be based on requested bandwidth. The method may initially receive a connection request which includes a requested bandwidth that corresponds to an application. The method may then determine a policy for an application data flow associated with the application based on the connection request. A bandwidth designation, which is based on the requested bandwidth, may be assigned to the application data flow based on the determined policy. Finally, the policy and the bandwidth designation may be provided so that a bearer can be assigned.

A computer implemented method allocates wireless network and adaptive video streaming resources in environments with high device density. The network has one or more access points and at least one user device. The stages of the method include obtaining the information from radio access network or video service telemetry; generating a resource allocation list between each user device and at least one channel with an associated representation index, distributing the resource allocation list, performing at least one handover and at least one video rate recommendation.

A computer implemented method allocates wireless network and adaptive video streaming resources in environments with high device density. The network has one or more access points and at least one user device. The stages of the method include obtaining the information from radio access network or video service telemetry; generating a resource allocation list between each user device and at least one channel with an associated representation index, distributing the resource allocation list, performing at least one handover and at least one video rate recommendation.

The disclosure relates to an electronic device for wireless communication, a wireless communication method and a computer readable medium. According to an embodiment, an electronic device for wireless communication includes a processing circuitry. The processing circuitry is configured to acquire a parameter related to a behavior characteristic of a mobile access point. The processing circuitry is further configure to determine a spectrum allocation manner for the mobile access point based on the parameter.

The disclosure relates to an electronic device for wireless communication, a wireless communication method and a computer readable medium. According to an embodiment, an electronic device for wireless communication includes a processing circuitry. The processing circuitry is configured to acquire a parameter related to a behavior characteristic of a mobile access point. The processing circuitry is further configure to determine a spectrum allocation manner for the mobile access point based on the parameter.

An electronic device discussed herein may include radio frequency communication circuitry for communication on a radio frequency network according to a communication configuration, a processor, and memory. The memory may store instructions that, when executed by the processor, cause the electronic device to perform operations including receiving, a first muting configuration indicating when the radio frequency communication circuitry is to communicate using a first type of communication on a first frequency band and when the radio frequency communication circuitry is to communicate using a second type of communication on a second frequency band, where the first frequency band may overlap with the second frequency band. The memory may store instructions that, when executed by the processor, cause the electronic device to perform operations including transmitting or receiving a data packet using the radio frequency communication circuitry according to the communication configuration.

An electronic device discussed herein may include radio frequency communication circuitry for communication on a radio frequency network according to a communication configuration, a processor, and memory. The memory may store instructions that, when executed by the processor, cause the electronic device to perform operations including receiving, a first muting configuration indicating when the radio frequency communication circuitry is to communicate using a first type of communication on a first frequency band and when the radio frequency communication circuitry is to communicate using a second type of communication on a second frequency band, where the first frequency band may overlap with the second frequency band. The memory may store instructions that, when executed by the processor, cause the electronic device to perform operations including transmitting or receiving a data packet using the radio frequency communication circuitry according to the communication configuration.

A space-air-ground integrated UAV-assisted IoT data collection method based on AoI comprises: constructing a UAV-assisted space-air-ground integrated IoT system, constructing a UAV channel model and an AoI model, establishing an AoI-based UAV-assisted space-air-ground integrated IoT data collection model, transforming a problem into a Markov problem, introducing a neural network to solve a high-dimensional state problem, introducing a deep reinforcement learning algorithm to train UAVs to find optimal collection points, and introducing a matching theory to match the UAVs and IoT devices. To meet the requirement for the timeliness of information collection, the invention finds the optimal configuration of flight parameters of UAVs and deduces the restrictive relation between performance indicators such as AoI, system capacity and energy utilization rate, thus effectively improving the timeliness of information collection, reducing the management and control complexity of the system, and improving the application level of AI in the IoT field.

A space-air-ground integrated UAV-assisted IoT data collection method based on AoI comprises: constructing a UAV-assisted space-air-ground integrated IoT system, constructing a UAV channel model and an AoI model, establishing an AoI-based UAV-assisted space-air-ground integrated IoT data collection model, transforming a problem into a Markov problem, introducing a neural network to solve a high-dimensional state problem, introducing a deep reinforcement learning algorithm to train UAVs to find optimal collection points, and introducing a matching theory to match the UAVs and IoT devices. To meet the requirement for the timeliness of information collection, the invention finds the optimal configuration of flight parameters of UAVs and deduces the restrictive relation between performance indicators such as AoI, system capacity and energy utilization rate, thus effectively improving the timeliness of information collection, reducing the management and control complexity of the system, and improving the application level of AI in the IoT field.