Resource Pool Configuration and Hybrid Automatic Repeat Request Transmission

    公开(公告)号:US20210029692A1

    公开(公告)日:2021-01-28

    申请号:US16934117

    申请日:2020-07-21

    IPC分类号: H04W72/04 H04W72/02

    摘要: A first wireless device receives, from a base station, configuration parameters of a resource pool of a sidelink. The configuration parameters indicate a primary zone configuration, a secondary zone configuration, and a first primary zone identifier of a first primary zone. a second primary zone identifier of a second primary zone in which the first wireless device is positioned, is determined based on a geographic location of the first wireless device using the primary zone configuration. A secondary zone identifier of a secondary zone in which the first wireless device is positioned, is determined based on the geographic location using the secondary zone configuration. The first wireless device transmits control information indicating the secondary zone identifier to second wireless device(s). The control information is transmitted via the resource pool, in response to the second primary zone identifier being the same as the first primary zone identifier.

    Wireless charger
    34.
    外观设计

    公开(公告)号:USD907575S1

    公开(公告)日:2021-01-12

    申请号:US29688232

    申请日:2019-04-19

    申请人: Kai Xu

    设计人: Kai Xu

    LAPRAN: A SCALABLE LAPLACIAN PYRAMID RECONSTRUCTIVE ADVERSARIAL NETWORK FOR FLEXIBLE COMPRESSIVE SENSING RECONSTRUCTION

    公开(公告)号:US20200234406A1

    公开(公告)日:2020-07-23

    申请号:US16745817

    申请日:2020-01-17

    摘要: This disclosure addresses the single-image compressive sensing (CS) and reconstruction problem. A scalable Laplacian pyramid reconstructive adversarial network (LAPRAN) facilitates high-fidelity, flexible and fast CS image reconstruction. LAPRAN progressively reconstructs an image following the concept of the Laplacian pyramid through multiple stages of reconstructive adversarial networks (RANs). At each pyramid level, CS measurements are fused with a contextual latent vector to generate a high-frequency image residual. Consequently, LAPRAN can produce hierarchies of reconstructed images and each with an incremental resolution and improved quality. The scalable pyramid structure of LAPRAN enables high-fidelity CS reconstruction with a flexible resolution that is adaptive to a wide range of compression ratios (CRs), which is infeasible with existing methods.