DEVICE AND METHOD FOR PERFORMING HANDOVER IN MASSIVE MULTIPLE-INPUT-MULTIPLE-OUTPUT (MIMO) SYSTEMS

    公开(公告)号:US20190075496A1

    公开(公告)日:2019-03-07

    申请号:US16083894

    申请日:2016-04-14

    Abstract: In various aspects, devices and methods for performing a handover in a MIMO system are described herein. According to at least one aspect, a wireless communication device is described to include one or more receivers that measures beams of a neighbor cell in response to a command of a MIMO communication system. In some aspects, the wireless communication device further includes one or more transmitters that reports information of the beams based on the measured beams to the massive MIMO communication system. The information is, in at least one aspect, incorporated in a Beam Specific-Neighbor Cell Relation (BS-NCR).

    AN ADAPTIVE DEEP LEARNING MODEL FOR NOISY IMAGE SUPER-RESOLUTION

    公开(公告)号:US20220148130A1

    公开(公告)日:2022-05-12

    申请号:US17435653

    申请日:2019-06-21

    Inventor: Wenyi TANG Xu ZHANG

    Abstract: Embodiments described herein are generally directed to an end-to-end trainable degradation restoration network (DRN) that enhances the ability of a super-resolution (SR) subnetwork to deal with noisy low-resolution images. An embodiment of a method includes estimating, by a noise estimator (NE) subnetwork of the DRN, an estimated noise map for a noisy input image; and predicting, by the SR subnetwork of the DRN, a clean upscaled image based on the input image and the noise map by, for each of multiple conditional residual dense blocks (CRDBs) stacked within one or more cascade blocks representing the SR subnetwork, adjusting, by a noise control layer of the CRDB that follows a stacked set of a multiple residual dense blocks of the CRDB, feature values of an intermediate feature map associated with the input image by applying (i) a scaling factor and (ii) an offset factor derived from the noise map.

    METHODS OF PROCESSING SIGNALS, APPARATUS, AND BASE STATION

    公开(公告)号:US20180287673A1

    公开(公告)日:2018-10-04

    申请号:US15756991

    申请日:2015-09-10

    Abstract: A method of processing signals in a radio processing apparatus of a base station may include obtaining a plurality of aggregated data symbols, wherein each of the plurality of aggregated data symbols corresponds to a receive terminal of a plurality of receive terminals of the base station and is composed of transmitted data symbols from a plurality of transmit terminals; applying a compression filter to the plurality of aggregated data symbols to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive terminals and the plurality of transmit terminals; and transmitting the plurality of isolated data symbols to a baseband processing apparatus of the base station

    ADAPTIVE DEEP LEARNING MODEL FOR NOISY IMAGE SUPER-RESOLUTION

    公开(公告)号:US20240370972A1

    公开(公告)日:2024-11-07

    申请号:US18637594

    申请日:2024-04-17

    Inventor: Wenyi TANG Xu ZHANG

    Abstract: Embodiments described herein are generally directed to an end-to-end trainable degradation restoration network (DRN) that enhances the ability of a super-resolution (SR) subnetwork to deal with noisy low-resolution images. An embodiment of a method includes estimating, by a noise estimator (NE) subnetwork of the DRN, an estimated noise map for a noisy input image; and predicting, by the SR subnetwork of the DRN, a clean upscaled image based on the input image and the noise map by, for each of multiple conditional residual dense blocks (CRDBs) stacked within one or more cascade blocks representing the SR subnetwork, adjusting, by a noise control layer of the CRDB that follows a stacked set of a multiple residual dense blocks of the CRDB, feature values of an intermediate feature map associated with the input image by applying (i) a scaling factor and (ii) an offset factor derived from the noise map.

Patent Agency Ranking