Millimeter-wave beam alignment assisted by ultra wide band (UWB) radio

    公开(公告)号:US11616548B2

    公开(公告)日:2023-03-28

    申请号:US17410091

    申请日:2021-08-24

    Abstract: A first device and second device communicate using mmWave communication with antenna alignment based on processing of ultra wide band (UWB) pulses. A limit on angle resolution due to a small number of antennas on either of the devices is relieved by using two or more carrier frequencies in the UWB pulses. A limit on angle resolution is further overcome in some situations by use of a neural network to refine angle estimates. In some situations, received power values are further used to select an angle for beam alignment.

    METHOD OF PERFORMING COMMUNICATION LOAD BALANCING WITH MULTI-TEACHER REINFORCEMENT LEARNING, AND AN APPARATUS FOR THE SAME

    公开(公告)号:US20250168255A1

    公开(公告)日:2025-05-22

    申请号:US19028822

    申请日:2025-01-17

    Abstract: A server may be provided to obtain a load balancing artificial intelligence (AI) model for a plurality of base stations in a communication system. The server may obtain teacher models based on traffic data sets collected from the base stations, respectively; perform a policy rehearsal process including obtaining student models based on knowledge distillation from the teacher models, obtaining an ensemble student model by ensembling the student models, and obtaining a policy model by interacting with the ensemble student mode; provide the policy model to each of the base stations for a policy evaluation of the policy model; and based on a training continue signal being received from at least one of the base stations as a result of the policy evaluation, update the ensemble student model and the policy model by performing the policy rehearsal process on the student models.

    Method of performing communication load balancing with multi-teacher reinforcement learning, and an apparatus for the same

    公开(公告)号:US12238190B2

    公开(公告)日:2025-02-25

    申请号:US18351201

    申请日:2023-07-12

    Abstract: A server may be provided to obtain a load balancing artificial intelligence (AI) model for a plurality of base stations in a communication system. The server may obtain teacher models based on traffic data sets collected from the base stations, respectively; perform a policy rehearsal process including obtaining student models based on knowledge distillation from the teacher models, obtaining an ensemble student model by ensembling the student models, and obtaining a policy model by interacting with the ensemble student mode; provide the policy model to each of the base stations for a policy evaluation of the policy model; and based on a training continue signal being received from at least one of the base stations as a result of the policy evaluation, update the ensemble student model and the policy model by performing the policy rehearsal process on the student models.

    SYSTEM AND METHOD FOR COMMUNICATION LOAD BALANCING IN UNSEEN TRAFFIC SCENARIOS

    公开(公告)号:US20230047986A1

    公开(公告)日:2023-02-16

    申请号:US17872667

    申请日:2022-07-25

    Abstract: Several policies are trained for determining communication parameters used by mobile devices in selecting a cell of a first communication network to operate on. The several policies form a policy bank. By adjusting the communication parameters, load balancing among cells of the first communication network is achieved. A policy selector is trained so that a target communication network, different than the first communication network, can be load balanced. The policy selector selects a policy from the policy bank for the target communication network. The target communication network applies the policy and the load is balanced on the target communication network. Improved load balancing leads to a reduction of the number of base stations needed in the target communication network.

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