Abstract: A device may include a memory and a processor configured to determine, based on first cell data representative of conditions of a cell of a mobile communication network at a first stage associated with a first instance of time, a set of configurations for an antenna array comprising a plurality of antenna elements, wherein each configuration of the set of configurations comprises a configuration in which a subset of the plurality of antenna elements are to be used to perform communications within the cell, and select one or more antenna configurations for the antenna array from the determined set of configurations, wherein each antenna configuration of the one or more antenna configurations are selected based on further cell data representative of the conditions of the cell at a further stage associated with a further instance of time after the first instance of time.

Abstract: A device may include a memory and a processor configured to obtain cell data representative of one or more attributes associated with a state of a cell of a mobile communication network, wherein radio resources of the cell are managed based on a radio resource management model, determine, for the radio resource management model, an update timescale based on the cell data, and communicate timescale information representative of the determined update timescale to the radio resource management model, wherein the timescale information is configured to cause the radio resource management model to update model parameters to manage the radio resources of the cell based on the determined update timescale.

Abstract: A memory subsystem includes memory devices with space dynamically allocated for improvement of reliability, availability, and serviceability (RAS) in the system. Error checking and correction (ECC) logic detects an error in all or a portion of a memory device. In response to error detection, the system can dynamically perform one or more of: allocate active memory device space for sparing to spare a failed memory segment; write a poison pattern into a failed cacheline to mark it as failed; perform permanent fault detection (PFD) and adjust application of ECC based on PFD detection; or, spare only a portion of a device and leave another portion active, including adjusting ECC based on the spared portion. The error detection can be based on bits of an ECC device, and error correction based on those bits and additional bits stored on the data devices.

Abstract: A wireless communication device including a memory configured to store instructions; a processor coupled to the memory configured to execute the instructions stored on the memory, wherein the instructions are configured to receive a request message to update a radio access network (RAN) quantization scheme; determine an updated quantization scheme based on properties of a RAN; determine if the updated quantization scheme satisfies a RAN performance criterion; and generate a message including instructions for the updated quantization scheme.

Abstract: A method and apparatus for estimating and/or predicting mobility metric(s) for RAN optimization. One method includes receiving a request, from at least one RAN optimization service, to provide an estimate or prediction of a mobility metric for at least one UE or group of UEs or at least one cell. The request may include attributes describing characteristics of the mobility metric. The method may then include communicating with a RAN node to request data about the at least one UE or the group of UEs or the at least one cell associated with the request, receiving the requested data, and calculating the estimate or the prediction of the mobility metric using the requested data and based on the attributes received in the request from the at least one RAN optimization service.

Abstract: A communication device in a communication network includes at least one processor. The at least one processor is configured to at least one processor configured to search a spectrum of the communication network using a Long Term Evolution Primary Synchronization/Secondary Synchronization Signals (LTE PSS/SSS), estimate the LTE interference using cell specific reference signals for Down Link (DL) when the LTE PSS/SSS signal is detected, and utilize LTE cell specific reference signals (CRS) and feed the equalized signal to a Data Over Cable Service Interface Specification (DOCSIS) Physical Layer (PHY) engine.

Abstract: To maximize power saving in a radio access network comprising cells, an optimal action amongst actions comprising switching on one or more cells, switching off one or more cells, and doing nothing is determined using a trained model, which maximizes a long term reward on tradeoff between throughput and power, the trained model taking as input a load estimate. The trained model may be updated online using measurement results on load, throughput and power consumption.

Abstract: To maximize power saving in a radio access network comprising cells, an optimal action amongst actions comprising switching on one or more cells, switching off one or more cells, and doing nothing is determined using a trained model, which maximizes a long term reward on tradeoff between throughput and power, the trained model taking as input a load estimate. The trained model may be updated online using measurement results on load, throughput and power consumption.

Abstract: An apparatus, method and computer program is described comprising: executing, in a first mode of operation, a MIMO for one or more user devices eligible to transmit data in a slot of a packet scheduler, to generate MIMO operation outputs; obtaining, in a second mode of operation, estimated MIMO operation outputs for said one or more user devices from a lookup table; and determining whether to operate in the first mode of operation or the second mode operation.

Abstract: The present disclosure relates to a system for use in a wireless network, the system including: a processor configured to determine a performance parameter representative of a performance of a model of radio resource management, the model operating on a radio access network environment; and a radio resource manager configured to perform radio resource management dependent on the performance parameter.

Abstract: A communication device in a communication network includes at least one processor. The at least one processor is configured to at least one processor configured to search a spectrum of the communication network using a Long Term Evolution Primary Synchronization/Secondary Synchronization Signals (LTE PSS/SSS), estimate the LTE interference using cell specific reference signals for Down Link (DL) when the LTE PSS/SSS signal is detected, and utilize LTE cell specific reference signals (CRS) and feed the equalized signal to a Data Over Cable Service Interface Specification (DOCSIS) Physical Layer (PHY) engine.

Abstract: Tire sensing systems operable to determine one or more physical characteristics of a tire include millimeter wave transmitting and receiving devices. A processor is communicatively coupled with a memory that includes instructions to transmit and receive a millimeter wave toward and from the tire. Memory also includes instructions to image first and second radial extents of the tire based on the received millimeter wave as well as instructions to determine a dimensional difference between the first and second radial extents of the tire. Vehicles including such tire sensing systems as well as non-transitory machine-readable storage mediums and methods are also included.

Abstract: The present disclosure relates to a device for use in a wireless network, the device including: a processor configured to: provide input data to a trained machine learning model, the input data representative of a network environment of the wireless network, wherein the trained machine learning model is configured to provide, based on the input data, output data representative of an expected performance of a plurality of configurations of network components with respect to power consumption and performance of the wireless network; select a configuration of a network component from the plurality of configurations based on the output data of the trained machine learning model; and instruct an operation of the network component according to the selected configuration; and a memory coupled with the processor, the memory storing the input data provided to the trained machine learning model and/or the output data from the trained machine learning model.

Abstract: A communication device in a communication network includes at least one processor. The processor is configured to identify a first management information base (MIB) of a first occupied channel in the communication network, and a second MIB of a second occupied channel in the communication network adjacent the first occupied channel. The second occupied channel occupies a frequency band overlapping with an interfering signal band. The processor is further configured to calculate at least one proactive network maintenance (PNM) metric for each of the first and second MIB, and determine, from the calculated PNM metric, that an ingress of the interfering signal is detected on the second occupied channel.

Abstract: An apparatus and system of providing energy saving in a network are described. A target node receives, from a source node, a handover request to handover a UE due to at least one of entry of the source node into a power saving state or mobility optimization. In response, the target node transmits a relative energy efficiency value of Bits per Joule and periodic feedback related to a status of the UE for training an AI/ML energy saving model and stops the feedback in response to a stop parameter being met. The stop parameter is a first of: a predicted period of the source node to stay in the power saving state or time for a UE to connect to the target node, a percentage of UEs handed over that enter an idle or inactive state, and a percentage of UEs handed over that are further handed to another node.

Abstract: To maximize power saving in a radio access network comprising cells, an optimal action amongst actions comprising switching on one or more cells, switching off one or more cells, and doing nothing is determined using a trained model, which maximizes a long term reward on tradeoff between throughput and power, the trained model taking as input a load estimate. The trained model may be updated online using measurement results on load, throughput and power consumption.

Abstract: A method and apparatus for estimating and/or predicting mobility metric(s) for RAN optimization. One method includes receiving a request, from at least one RAN optimization service, to provide an estimate or prediction of a mobility metric for at least one UE or group of UEs or at least one cell. The request may include attributes describing characteristics of the mobility metric. The method may then include communicating with a RAN node to request data about the at least one UE or the group of UEs or the at least one cell associated with the request, receiving the requested data, and calculating the estimate or the prediction of the mobility metric using the requested data and based on the attributes received in the request from the at least one RAN optimization service.

Abstract: In one example, the present disclosure describes a device, computer-readable medium, and method for automating the end-to-end deployment of applications in a data center. For instance, in one example, a set of characteristics is extracted from an electronic signal. The set of characteristics pertains to an application to be deployed in a data center. A load balancer on which to deploy the application is automatically selected, based at least in part on the set of characteristics. A workflow is automatically generated for deployment of the application on the load balancer. The workflow coordinates actions among a plurality of computing resources of the data center that are used to configure the application according to the set of characteristics.

Abstract: Systems, methods, apparatuses, and computer program products for dynamic target cell selection for application of RAN optimization are provided. One method includes receiving a request, from one or more radio access network optimization services, that comprises a list of attributes corresponding to characteristics of a cell and a cell selection criterion for each of the attributes, receiving, from one or more radio access network cells, a data stream comprising metrics for at least one of the cell or users in the cell.

Abstract: An apparatus, method and computer program is described comprising: executing, in a first mode of operation, a MIMO for one or more user devices eligible to transmit data in a slot of a packet scheduler, to generate MIMO operation outputs; obtaining, in a second mode of operation, estimated MIMO operation outputs for said one or more user devices from a lookup table; and determining whether to operate in the first mode of operation or the second mode operation.