Abstract:
A method for managing operational temperature conditions of one or more base stations being executed at a central computing device in a communication system is provided. The method includes acquiring initial operational parameters for each local computing device of a first group of local computing devices associated with the one or more base stations. The method further includes determining one or more clusters by grouping each local computing device of the first group of local computing devices under one of the determined clusters based on the acquired operational parameters. The method further includes training, a central machine learning (ML) model for each determined cluster. The method further includes acquiring, for each local computing device of a second group of local computing devices associated with the one or more base stations, updated operational parameters. The method further includes computing an operational difference measure of the second group of local computing devices using the acquired updated operational parameters. The method further includes determining optimized operational temperature conditions to be transmitted to the second group of local computing devices by using distributed ML, in response to determining that the computed operational difference measure is less than a threshold value.
Abstract:
Embodiments herein disclose, e.g., a method performed by a network node (12), in a wireless communications network (1), for charging a rechargeable power source in the network node (12). The network node (12) obtains an operational parameter to an operation of the network node (12), wherein the operational parameter is based on an output of a computational model. The computational model is based on a state of charge of the rechargeable power source, a parameter related to outage of a power grid, and a QoS parameter relating to radio communication in the wireless communications network. The network node (12) further applies, during a charging of the rechargeable power source, the operational parameter to the operation of the network node (12).
Abstract:
Embodiments herein disclose e.g. a method performed by a mobile device (15) for handling identification of equipment. The mobile device records an image, in a recording direction at a first location, of the equipment. Upon recording the image, the mobile device 5further obtains one or more radiation indications for determining a direction of radiation from the equipment; and provides the obtained one or more radiation indications associated with the recorded image, to an internal identifying process at the mobile device and/or a network node (11) for identifying the equipment.
Abstract:
A method performed by a first network node (111). The method is for handling charging of a wireless device (130). The first network node (111) and the wireless device (130) operate in a wireless communications network (100). The first network node (111) modulates (307) one or more beam forming beams (121) in an antenna array (124) controlled by the first network node (111) with a pulse width modulation. The first network node (111) then charges(308), wirelessly, the wireless device (130), with the modulated one or more beam forming beams (121).
Abstract:
A method (10) performed by a serving network node (2a) for handover of a communication device (1a, 1b) to a target network node (2b) is provided. The method (10) comprises determining (11), based on content of an Information Centric Networking, ICN, request, a need for handover, and initiating (12), in response to the determining, a handover of the communication device (1a, 1b) to the target network node (2b). A method (40) performed by a network entity (5a) is also provided, and a network node (2a), network entity (5a), computer programs and computer program products.
Abstract:
Method and apparatus for guidance of one or more transport vehicles (100). The presence of passengers at a vehicle stop (104) is detected by sensors (106a-c), each sensor (106a-c) being associated with a predefined destination or vehicle route. A traveling intention of the passengers is identified (1:2) based on the detected presence,and a notification (1:3) related to the traveling intention of the passengers is then provided to a transport vehicle (100) driving on a predefined route that includes said vehicle stop (104). Thereby, the transport vehicle (100) is able to adapt its driving route according to the traveling intention of the passenger, e.g. by skipping the vehicle stop (104) if the passenger does not intend to enter the vehicle at the vehicle stop (104).
Abstract:
A method performed by a first sensor device, a first sensor device and a computer program performed by a first sensor device (100:A) in a communications network (50) for calibration of a sensor (110:A) of the first sensor device (100:A), the sensor (110:A) being arranged to sense values of a first quantity, the first sensor device (100:A) further being arranged for communication with at least one second sensor device (100:B) located in the vicinity of the first sensor device (100:A), the method comprises, detecting (S100) a second sensor device (100:B) located in the vicinity of the first sensor device (100:A), the second sensor device (100:B) having a sensor (110:B) for sensing the first quantity, receiving (S110), from the second sensor device (100:B), a sensor value of the first quantity sensed by the sensor of the second sensor device (100:B), determining (S120) a difference value indicating the difference between the sensor value received from the second sensor device (100:B) and a reading of a sensor value of the sensor of the first sensor device (100:A), calibrating (S130) the sensor (110:A) of the first sensor device (100:A) based on the difference value. (Fig. 1)
Abstract:
In accordance with an example embodiment of the present invention, disclosed is a method and an apparatus thereof for broadcasting information about one or more environmental requirements at a location of the network entity. The information about environmental requirements is intended for use by mobile devices located within a transmission range of the network entity for configuring their operational characteristics.
Abstract:
There is provided a method for training a reinforcement learning system for optimising routing for a network including a plurality of Integrated Access and Backhaul (IAB) nodes connected to a IAB donor. The method comprises: acquiring observations characterising a current state of the plurality of IAB nodes, determining an action to be performed based on latest acquired observations, executing the action by initiating update of the routing information based on the determined action, acquiring observations characterising an updated state of the plurality of IAB nodes, determining a reward for the determined action, based on the updated state of the plurality of IAB nodes, storing an experience set, and training the reinforcement learning system to maximise reward with respect to an optimisation objective, using the one or more stored experience sets in the buffer.
Abstract:
A computer implemented method (300) for managing QoS of wireless devices in a 5communication network is disclosed. The method comprises receiving a QoS intent from a first node (310), the QoS intent comprising an identification of a wireless device to which the QoS intent applies and a QoS requirement for the identified wireless device. The method further comprises obtaining a specification of available QoS in the communication network (320) and a specification of QoS policies in the communication 0network (330), using an ML model to determine, based on the received QoS intent and obtained specifications, at what time the at least one QoS requirement of the QoS intent can be fulfilled for the identified wireless device (340), and informing the first node of a result of the determination (350). Also disclosed is a QoS management node (500).