USES OF CODED DATA AT MULTI-ACCESS EDGE COMPUTING SERVER

    公开(公告)号:US20240155025A1

    公开(公告)日:2024-05-09

    申请号:US18550856

    申请日:2022-06-09

    CPC classification number: H04L67/10 G06F17/18 H04L67/289

    Abstract: An apparatus of an edge computing node, a method, and a machine-readable storage medium. The apparatus is to decode messages from a plurality of clients within the edge computing network, the messages including respective coded data for respective ones of the plurality of clients; computing estimates of metrics related to a global model for federated learning using the coded data, the metrics including a gradient on the coded data; use the metrics to update the global model to generate an updated global model, wherein the edge computing node is to update the global model by calculating the gradient on the coded data based on a linear fit of the global model to estimated labels from the federated learning; and send a message including the updated global model for transmission to at least some of the clients.

    APPARATUS, SYSTEM, METHOD AND COMPUTER-IMPLEMENTED STORAGE MEDIA TO IMPLEMENT RADIO RESOURCE MANAGEMENT POLICIES USING MACHINE LEARNING

    公开(公告)号:US20220377614A1

    公开(公告)日:2022-11-24

    申请号:US17712050

    申请日:2022-04-01

    Abstract: An apparatus of a transmitter computing node n (TX node n) of a wireless network, one or more computer readable media, a system, and a method. The apparatus includes one or more processors to: implement machine learning (ML) based training rounds, each training round including: determining a local action value function Qn(hn, an; θn) corresponding to a value of performing a radio resource management (RRM) action an at a receiving computing node n (RX node n) associated with TX node n using policy parameter θn and based on hn, hn including channel state information at RX node n; and determining, based on an overall action value function Qtot at time t, an estimated gradient of an overall loss at time t for overall policy parameter θt(∇Lt(θt)), wherein Qtot corresponds to a mixing of local action value functions Qi(hi, ai; θi) for all TX nodes i in the network at time t including TX node n; and determine, in response to a determination that ∇Lt(θt) is close to zero for various values of t during training, a trained local action value function Qn,trained to generate a trained action value relating to data communication between TX node n and RX node n.

    Power reduction in a wireless network

    公开(公告)号:US10813061B2

    公开(公告)日:2020-10-20

    申请号:US16134400

    申请日:2018-09-18

    Abstract: Methods, apparatuses, and computer readable media for power reduction in a wireless network are disclosed. An apparatus of a first access point is disclosed comprising processing circuitry configure to decode a first PPDU, the first PPDU including a trigger for control (TOC) frame, the TOC frame comprising resource allocations for deferral transmissions, the TOC frame including a first duration field indicating a duration of a transmission opportunity (TXOP). The processing circuitry may be further configured to respond to a determination that the TOC frame includes a resource allocation by encoding a second PPDU including a preamble portion and a media access control (MAC) portion including a receive with condition (ARC) frame, the ARC frame including a second duration field indicating a remaining duration of the TXOP, an address field indicating a MAC address of the first AP, and a condition field indicating a condition.

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