In 5G and 6G, a message received with even a single-bit fault generally discarded and a retransmission is requested. However, the faulted message contains a wealth of information that the receiver can use to avoid, or at least mitigate, such faults thereafter. Disclosed is a method for comparing a faulted message with an unfaulted copy, thereby determining which part of the message is faulted, and specifically how it was faulted. For example, the fault may have been an amplitude fault in which a demodulated amplitude differs by one level from the initially modulated amplitude, or it may be a phase fault in which the received phase differs by one phase level, or there may be a displacement by multiple amplitude or phase levels (a non-adjacent fault). Different mitigation strategies are disclosed for each situation, including AI models configured to select a suitable modulation scheme to combat specific faults.

The embodiments disclosed herein include capturing images via cameras or light sensors of a mobile communication device, processing the image to determine obstructed (e.g., by foliage) portions and unobstructed (e.g., open sky) portions of the images, and generating a grid indicating the obstructed and unobstructed portions. The device may then adjust operating characteristics, such as synchronizing with a communication hub or other mobile communication device, performing a handover with the communication hub or other mobile communication device, determining transmission power or an amount to increase transmission power, selecting an antenna, determining a beam direction, determining a discontinuous reception cycle or a frequency for receiving data, providing an indication to stop or proceed through certain areas (e.g., to take advantage of areas with higher signal quality or avoid areas with lower signal quality), and the like, based on the obstructed and unobstructed portions identified in the grid.

A system described herein may provide a technique for generating one or more predictive models of device availability, which may be used to predict whether a given device will be able to be reached via one or more networks to receive information, such as Over-the-Air (“OTA”) updates. The predictive models may be based on, for example, radio frequency (“RF”) metrics, device availability metrics, and timing offsets between times associated with such RF metrics and availability metrics. For a given device, based on RF metrics associated with the device and further based on a candidate time, the predictive model may be used to determine whether the device will be available at the candidate time.

An operation method in a communication system may comprise: obtaining information on a per-beam required traffic amount; determining whether the per-beam required traffic amount can be serviced while satisfying a first condition according to a first model generated through pre-training in a first machine learning structure; in response to determining that the per-beam required traffic amount can be serviced while satisfying the first condition, calculating per-beam bandwidth allocation information based on the per-beam required traffic amount; calculating per-beam power allocation information based on the per-beam bandwidth allocation information; identifying whether an SNR condition included in the first condition is satisfied based on the per-beam power allocation information; and in response to identifying that the SNR condition is satisfied, outputting the per-beam bandwidth allocation information and the per-beam power allocation information.

Embodiments of disclosure relate to a method and an electronic device for identifying aggressor nodes in communication network. The method comprises receiving data related to a plurality of nodes of the communication network, from a network management entity, wherein the data comprises information on aggressor nodes and one or more victim nodes associated with the aggressor nodes; predicting an interference pattern indicating an interference caused by each of the aggressor nodes on the one or more victim nodes for at least one of a plurality of time instances, using a trained estimation model; and identifying at least one aggressor node having a possibility to interfere with the one or more victim nodes during the at least one of the plurality of time instances based on the interference pattern.

Systems and methods for intelligent packet repetition in mobile satellite service links to overcome channel blockages. One example method includes transmitting and receiving packetized wireless communications between first and second communications devices via a bidirectional wireless link. The method includes receiving, by a first communications device from a second communications device, feedback information including an indication of a blockage in the communication channel, the indication including information indicating the presence and extent of the blockage, wherein the feedback does not include status indications for individual received packets. The method includes, responsive to receiving the indication of a blockage in the communication channel, determining a packet repeat value based on the feedback information, wherein the packet repeat value may be greater than one. The method includes modifying a transmit signal of the bidirectional wireless link to repeat transmitted packets based on the packet repeat value.

[Object] To enhance a shared model in a case of predicting a wireless environment by machine learning securely and efficiently in terms of personal information protection.

[Solving Means] This information processing system includes: one or more information processing apparatuses including a first arithmetic processing unit that learns a model for predicting a wireless environment, uploads a result of the learning to a server, and predicts a wireless environment by using a shared model obtained by integrating one or more learning results in the server; and a server including a second arithmetic processing unit that integrates one or more learning results in the one or more information processing apparatuses and generates a shared model, and distributes the shared model to the one or more information processing apparatuses.

The system stores process information including information on processes before starting at a manufacturing site, and management information that manages radio performance estimation methods usable for each of applications and information for determining a processing time of each of the radio performance estimation methods. The process information includes information on applications used in each process of the processes and information on a time associated with each process. The system refers to the process information and the management information so as to determine radio performance estimation methods usable in each process, and refers to the process information and the management information so as to select a wireless communication method, through which radio performance estimation processing is completed by a time associated with each process, from the radio performance estimation methods usable in each process.

Aspects of the subject disclosure may include, for example, a method in which a processing system identifies a plurality of performance indicators comprising device performance indicators for a plurality of communication devices on a cellular network and network performance indicators for the cellular network. The method also includes obtaining historical data regarding the plurality of performance indicators for each of a series of time points during a past time period; the historical data for each of the plurality of performance indicators form an array of values for that performance indicator. The method further includes generating from each array a set of inputs to an algorithm for predicting a throughput of the cellular network during a future time period; the set of inputs comprises quantiles of the array, and the algorithm comprises a machine learning algorithm. Other embodiments are disclosed.

Systems and methods for selecting a worst service first optimized test path are provided. Such systems and methods can include using previously collected RF results that are relevant to a target building to calculate predictive RF results for a plurality of test points in the target building, using the predictive RF results to calculate the optimized test path through the target building, measuring a respective actual RF signal value of each of the plurality of test points in succession along the optimized test path, counting failing ones of the plurality of test points, and stopping measurements of the respective actual RF signal value of each of the plurality test points when a counted number of the failing ones of the plurality of test points exceeds a failure threshold value.