AUTOCORRELATION AND MEMORY ALLOCATION FOR WIRELESS COMMUNICATION

    公开(公告)号:US20190123793A1

    公开(公告)日:2019-04-25

    申请号:US16116878

    申请日:2018-08-29

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of an autocorrelation calculator. An electronic device including an autocorrelation calculator may be configured to calculate an autocorrelation matrix including an autocorrelation of symbols indicative of a first radio frequency (“RF”) signal and a second RF signal. The electronic device may calculate the autocorrelation matrix based on a stored autocorrelation matrix and the autocorrelation of symbols indicative of the first RF signal and symbols indicative of the second RF signal. The stored autocorrelation matrix may represent another received signal at a different time period than a time period of the first and second RF signals. Examples of the systems and methods may facilitate the processing of data for wireless and may utilize less memory space than a device than a scheme that stores and calculates autocorrelation from a large dataset computed from various time points.

    FULL DUPLEX DEVICE-TO-DEVICE COOPERATIVE COMMUNICATION

    公开(公告)号:US20190081767A1

    公开(公告)日:2019-03-14

    申请号:US16116365

    申请日:2018-08-29

    Abstract: Examples described herein include apparatuses and methods for full duplex device-to-device cooperative communication. Example systems described herein may include self-interference noise calculators. The output of a self-interference noise calculator may be used to compensate for the interference experienced due to signals transmitted by another antenna of the same wireless device or system. In implementing such a self-interference noise calculator, a selected wireless relaying device or wireless destination device may operate in a full-duplex mode, such that relayed messages may be transmitted as well as information from other sources or destinations during a common time period (e.g., symbol, slot, subframe, etc.).

    APPARATUSES AND METHODS FOR ADAPTIVE SPATIAL DIVERSITY IN A MIMO-BASED SYSTEM

    公开(公告)号:US20180337710A1

    公开(公告)日:2018-11-22

    申请号:US15600420

    申请日:2017-05-19

    CPC classification number: H04B7/0413 H04B7/0848

    Abstract: Examples described herein include apparatuses and methods to perform adaptive spatial diversity in a MIMO system. An example apparatus may include a plurality of receiving antennas and a wireless receiver configured to receive a respective plurality of receive signals each from a respective receiving antenna of the plurality of receiving antennas. The wireless signal may be further configured to apply a corresponding weight to each of the plurality of signals to provide a plurality of weighted signals and to apply an eigenfilter to the plurality of weighted signals provide a transfer function. The wireless receiver further configured to perform a fast Fourier transform (FFT) on the transfer function to provide output signals in the frequency domain.

    WIRELESS DEVICES AND SYSTEMS INCLUDING EXAMPLES OF MIXING INPUT DATA WITH COEFFICIENT DATA

    公开(公告)号:US20180324021A1

    公开(公告)日:2018-11-08

    申请号:US16034751

    申请日:2018-07-13

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of mixing input data with coefficient data. For example, a computing system with processing units may mix the input data for a transmission in a radio frequency (RF) wireless domain with the coefficient data to generate output data that is representative of the transmission being processed according to the wireless protocol in the RF wireless domain. A computing device may be trained to generate coefficient data based on the operations of a wireless transceiver such that mixing input data using the coefficient data generates an approximation of the output data, as if it were processed by the wireless transceiver. Examples of systems and methods described herein may facilitate the processing of data for 5G wireless communications in a power-efficient and time-efficient manner.

    Wireless devices and systems including examples of configuration modes for baseband units and remote radio heads

    公开(公告)号:US10070432B1

    公开(公告)日:2018-09-04

    申请号:US15447699

    申请日:2017-03-02

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of configuration modes for baseband units (BBU) and remote radio heads (RRH). For example, a computing system including a BBU and a RRH may receive a configuration mode selection including information indicative of a configuration mode for respective processing units of the BBU and the RRH. The computing system allocates the respective processing units to perform wireless processing stages associated with a wireless protocol. The BBU and/or the RRH may generate an output data stream based on the mixing of coefficient data with input data at the BBU and/or the RRH. Examples of systems and methods described herein may facilitate the processing of data for 5G wireless communications in a power-efficient and time-efficient manner.

    Methods and apparatus for integrated image signal processing

    公开(公告)号:US12267612B2

    公开(公告)日:2025-04-01

    申请号:US16989724

    申请日:2020-08-10

    Inventor: Fa-Long Luo

    Abstract: Methods and apparatus for performing multi-step image processing using a reconfigurable fabric device (RFD) in place of multiple discrete ICs. In one embodiment, the methods and apparatus operate according to a flexible time-divided schedule, and the processing is configured to process image sensor data by at least: (i) receiving RAW image data, programming an RFD to operate as a first functional unit such as an image signal processor (ISP), using the programmed RFD to perform image signal processing on the RAW image data, storing the ISP-result in temporary memory; and (ii) programming the RFD to operate as a second functional unit (e.g., deep learning accelerator (DLA)), using the programmed RFD to read out ISP-result from the temporary memory, perform deep learning processing on the ISP-result, and storing the DLA-result back into the temporary memory. In one variant, an on-die controller and memory are used in support of the RFD operations, thereby enabling a single-die processing solution.

    Mixing coefficient data for processing mode selection

    公开(公告)号:US12237862B2

    公开(公告)日:2025-02-25

    申请号:US18053310

    申请日:2022-11-07

    Inventor: Fa-Long Luo

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of mixing input data delayed versions of at least a portion of the respective processing results with coefficient data specific to a processing mode selection. For example, a computing system with processing units may mix the input data delayed versions of respective outputs of various layers of multiplication/accumulation processing units (MAC units) for a transmission in a radio frequency (RF) wireless domain with the coefficient data to generate output data that is representative of the transmission being processed according to a wireless processing mode selection. In another example, such mixing input data with delayed versions of processing results may be to receive and process noisy wireless input data. Examples of systems and methods described herein may facilitate the processing of data for 5G wireless communications in a power-efficient and time-efficient manner.

    Systems for error reduction of encoded data using neural networks

    公开(公告)号:US12237846B2

    公开(公告)日:2025-02-25

    申请号:US18158332

    申请日:2023-01-23

    Abstract: Examples described herein utilize multi-layer neural networks, such as multi-layer recurrent neural networks to estimate an error-reduced version of encoded data based on a retrieved version of encoded data (e.g., data encoded using one or more encoding techniques) from a memory. The neural networks and/or recurrent neural networks may have nonlinear mapping and distributed processing capabilities which may be advantageous in many systems employing a neural network or recurrent neural network to estimate an error-reduced version of encoded data for an error correction coding (ECC) decoder, e.g., to facilitate decoding of the error-reduced version of encoded data at the decoder. In this manner, neural networks or recurrent neural networks described herein may be used to improve or facilitate aspects of decoding at ECC decoders, e.g., by reducing errors present in encoded data due to storage or transmission.

    COLLABORATIVE BASEBAND PROCESSING IN MIMO SYSTEMS USING NEURAL NETWORKS

    公开(公告)号:US20250047320A1

    公开(公告)日:2025-02-06

    申请号:US18583689

    申请日:2024-02-21

    Abstract: A system includes a first wireless communication device comprising a first baseband processor neural network configured to process at least part of data for transmission to a second wireless communication device according to a collaborative processing configuration while collaborative processing is enabled to generate a first radio frequency (RF) signal. The first wireless communication device is configured to transmit the first RF signal. The system further includes a third wireless communication device comprising a second baseband processor neural network configured to, while the collaborative processing is enabled, process at least part of the data for transmission to the second wireless communication device according to a collaborative processing configuration to generate a second RF signal. The third wireless communication device is configured to transmit the second RF signal in collaboration with transmission of the first RF signal by the first baseband processor.

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