WIRELESS DEVICES AND SYSTEMS INCLUDING EXAMPLES OF CONFIGURATION MODES FOR BASEBAND UNITS AND REMOTE RADIO HEADS

    公开(公告)号:US20230262731A1

    公开(公告)日:2023-08-17

    申请号:US18306694

    申请日:2023-04-25

    CPC classification number: H04W72/29 H04W88/085 Y02D30/70

    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.

    DATA FLOWS IN A PROCESSOR WITH A DATA FLOW MANAGER

    公开(公告)号:US20220171634A1

    公开(公告)日:2022-06-02

    申请号:US17673712

    申请日:2022-02-16

    Abstract: Methods, apparatuses, and systems for implementing data flows in a processor are described herein. A data flow manager may be configured to generate a configuration packet for a compute operation based on status information regarding multiple processing elements of the processor. Accordingly, multiple processing elements of a processor may concurrently process data flows based on the configuration packet. For example, the multiple processing elements may implement a mapping of processing elements to memory, while also implementing identified paths, through the processor, for the data flows. After executing the compute operation at certain processing elements of the processor, the processing results may be provided. In speech signal processing operations, the processing results may be compared to phonemes to identify such components of human speech in the processing results. Once dynamically identified, the processing elements may continue comparing additional components of human speech to facilitate processing of an audio recording, for example.

    APPARATUS AND METHOD TO SWITCH CONFIGURABLE LOGIC UNITS

    公开(公告)号:US20210182074A1

    公开(公告)日:2021-06-17

    申请号:US17184945

    申请日:2021-02-25

    Abstract: Examples described herein include systems and methods which include an apparatus comprising a plurality of configurable logic units and a plurality of switches, with each switch being coupled to at least one configurable logic unit of the plurality of configurable logic units. The apparatus further includes an instruction register configured to provide respective switch instructions of a plurality of switch instructions to each switch based on a computation to be implemented among the plurality of configurable logic units. For example, the switch instructions may include allocating the plurality of configurable logic units to perform the computation and activating an input of the switch and an output of the switch to couple at least a first configurable logic unit and a second configurable logic unit. In various embodiments, configurable logic units can include arithmetic logic units (ALUs), bit manipulation units (BMUs), and multiplier-accumulator units (MACs).

    AUTOCORRELATION AND MEMORY ALLOCATION FOR WIRELESS COMMUNICATION

    公开(公告)号:US20200235794A1

    公开(公告)日:2020-07-23

    申请号:US16844178

    申请日:2020-04-09

    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.

    APPARATUS AND METHOD TO SWITCH CONFIGURABLE LOGIC UNITS

    公开(公告)号:US20180307483A1

    公开(公告)日:2018-10-25

    申请号:US15493551

    申请日:2017-04-21

    CPC classification number: G06F9/3001 G06F9/30098 G06F9/30145

    Abstract: Examples described herein include systems and methods which include an apparatus comprising a plurality of configurable logic units and a plurality of switches, with each switch being coupled to at least one configurable logic unit of the plurality of configurable logic units. The apparatus further includes an instruction register configured to provide respective switch instructions of a plurality of switch instructions to each switch based on a computation to be implemented among the plurality of configurable logic units. For example, the switch instructions may include allocating the plurality of configurable logic units to perform the computation and activating an input of the switch and an output of the switch to couple at least a first configurable logic unit and a second configurable logic unit. In various embodiments, configurable logic units can include arithmetic logic units (ALUs), bit manipulation units (BMUs), and multiplier-accumulator units (MACs).

    AUTOCORRELATION AND MEMORY ALLOCATION FOR WIRELESS COMMUNICATION

    公开(公告)号:US20220060226A1

    公开(公告)日:2022-02-24

    申请号:US17453914

    申请日:2021-11-08

    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 narrowband Internet of Things (IoT) transmission and a second narrowband IoT transmission. The electronic device may calculate the autocorrelation matrix based on a stored autocorrelation matrix and the autocorrelation of symbols indicative of the first narrowband IoT transmission and symbols indicative of the second narrowband IoT transmission. The stored autocorrelation matrix may represent another received signal at a different time period than a time period of the first and second narrowband IoT transmission. 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.

    WIRELESS DEVICES AND SYSTEMS INCLUDING EXAMPLES OF CROSS CORRELATING WIRELESS TRANSMISSIONS

    公开(公告)号:US20210058227A1

    公开(公告)日:2021-02-25

    申请号:US17090123

    申请日:2020-11-05

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of cross correlation including symbols indicative of radio frequency (RF) energy. An electronic device including a statistic calculator may be configured to calculate a statistic including the cross-correlation of the symbols. The electronic device may include a comparator configured to provide a signal indicative of a presence or absence of a wireless communication signal in the particular portion of the wireless spectrum based on a comparison of the statistic with a threshold. A decoder/precoder may be configured to receive the signal indicative of the presence or absence of the wireless communication signal and to decode the symbols responsive to a signal indicative of the presence of the wireless communication signal. Examples of systems and methods described herein may facilitate the processing of data for wireless communications in a power-efficient and time-efficient manner.

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

    公开(公告)号:US20200280348A1

    公开(公告)日:2020-09-03

    申请号:US16678753

    申请日:2019-11-08

    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.

    NEURON CALCULATOR FOR ARTIFICIAL NEURAL NETWORKS

    公开(公告)号:US20200177244A1

    公开(公告)日:2020-06-04

    申请号:US16786637

    申请日:2020-02-10

    Abstract: Examples described herein include systems and methods, including wireless devices and systems with neuron calculators that may perform one or more functionalities of a wireless transceiver. The neuron calculator calculates output signals that may be implemented, for example, using accumulation units that sum the multiplicative processing results of ordered sets from ordered neurons with connection weights for each connection between an ordered neuron and outputs of the neuron calculator. The ordered sets may be a combination of some input signals, with the number of signals determined by an order of the neuron. Accordingly, a kth-order neuron may include an ordered set comprising product values of k input signals, where the input signals are selected from a set of k-combinations with repetition. As an example in a wireless transceiver, the neuron calculator may perform channel estimation as a channel estimation processing component of the receiver portion of a wireless transceiver.

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