MEMORY DEVICES AND METHODS WHICH MAY FACILITATE TENSOR MEMORY ACCESS WITH MEMORY MAPS BASED ON MEMORY OPERATIONS

    公开(公告)号:US20200257633A1

    公开(公告)日:2020-08-13

    申请号:US16864437

    申请日:2020-05-01

    Abstract: Examples described herein include systems and methods which include an apparatus comprising a memory array including a plurality of memory cells and a memory controller coupled to the memory array. The memory controller comprises a memory mapper configured to configure a memory map on the basis of a memory command associated with a memory access operation. The memory map comprises a specific sequence of memory access instructions to access at least one memory cell of the memory array. For example, the specific sequence of memory access instructions for a diagonal memory command comprises a sequence of memory access instructions that each access a memory cell along a diagonal of the memory array.

    Autocorrelation and memory allocation for wireless communication

    公开(公告)号:US10651903B2

    公开(公告)日:2020-05-12

    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.

    REMOTELY EXECUTABLE INSTRUCTIONS
    53.
    发明申请

    公开(公告)号:US20200100270A1

    公开(公告)日:2020-03-26

    申请号:US16142025

    申请日:2018-09-26

    Abstract: Systems, apparatuses and method related to remotely executable instructions are described. A device may be wirelessly coupled to (e.g., physically separated) another device, which may be in a physically separate device. The another device may remotely execute instructions associated with performing various operations, which would have been entirely executed at the device absent the another device. The outputs obtained as a result of the execution may be transmitted, via the transceiver, back to the device via a wireless communication link (e.g., using resources of an ultra high frequency (UHF), super high frequency (SHF), extremely high frequency (EHF), and/or tremendously high frequency (THF) bands). The another device at which the instructions are remotely executable may include memory resources, processing resources, and transceiver resources; they may be configured to use one or several communication protocols over licensed or shared frequency spectrum bands, directly (e.g., device-to-device) or indirectly (e.g., via a base station).

    WIRELESSLY UTILIZABLE MEMORY
    54.
    发明申请

    公开(公告)号:US20200100264A1

    公开(公告)日:2020-03-26

    申请号:US16142013

    申请日:2018-09-26

    Abstract: Methods, apparatuses, and systems related to wireless main memory for computing are described. A device may include a processor that is wirelessly coupled to a memory array, which may be in a physically separate device. The processor may execute instructions stored in and wirelessly communicated from the memory array. The processor may read data from or write data to the memory array via a wireless communication link (e.g., using resources of an ultra high frequency, super high frequency, and/or extremely high frequency band). Several devices may have a small amount of local memory (or no local memory) and may share, via a wireless communication link, a main memory array. Memory devices may include memory resources and transceiver resources; they may be configured to use one or several communication protocols over licensed or shared frequency spectrum bands, directly (e.g., device-to-device) or indirectly (e.g., via a base station).

    Wireless devices and systems including examples of compensating power amplifier noise

    公开(公告)号:US10432240B1

    公开(公告)日:2019-10-01

    申请号:US15986555

    申请日:2018-05-22

    Abstract: Examples described herein include methods, devices, and systems which may compensate input data for non-linear power amplifier noise to generate compensated input data. In compensating the noise, during an uplink transmission time interval (TTI), a switch path is activated to provide amplified input data to a receiver stage including a coefficient calculator. The coefficient calculator may calculate an error representative of the noise based partly on the input signal to be transmitted and a feedback signal to generate coefficient data associated with the power amplifier noise. The feedback signal is provided, after processing through the receiver, to a coefficient calculator. During an uplink TTI, the amplified input data may also be transmitted as the RF wireless transmission via an RF antenna. During a downlink TTI, the switch path may be deactivated and the receiver stage may receive an additional RF wireless transmission to be processed in the receiver stage.

    SELF INTERFERENCE NOISE CANCELLATION TO SUPPORT MULTIPLE FREQUENCY BANDS

    公开(公告)号:US20190245566A1

    公开(公告)日:2019-08-08

    申请号:US16113995

    申请日:2018-08-27

    CPC classification number: H04B1/0475 H04L5/14

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of full duplex compensation with a self-interference noise calculator that compensates for the self-interference noise generated by power amplifiers at harmonic frequencies of a respective wireless receiver. The self-interference noise calculator may be coupled to antennas of a wireless device and configured to generate the adjusted signals that compensate self-interference. The self-interference noise calculator may include a network of processing elements configured to combine transmission signals into sets of intermediate results. Each set of intermediate results may be summed in the self-interference noise calculator to generate a corresponding adjusted signal. The adjusted signal is receivable by a corresponding wireless receiver to compensate for the self-interference noise generated by a wireless transmitter transmitting on the same or different frequency band as the wireless receiver is receiving.

    Wireless devices and systems including examples of compensating power amplifier noise

    公开(公告)号:US10333567B1

    公开(公告)日:2019-06-25

    申请号:US16118017

    申请日:2018-08-30

    Abstract: Examples described herein include methods, devices, and systems which may compensate input data for non-linear power amplifier noise to generate compensated input data. In compensating the noise, during an uplink transmission time interval (TTI), a switch path is activated to provide amplified input data to a receiver stage including a coefficient calculator. The coefficient calculator may calculate an error representative of the noise based partly on the input signal to be transmitted and a feedback signal to generate coefficient data associated with the power amplifier noise. The feedback signal is provided, after processing through the receiver, to a coefficient calculator. During an uplink TTI, the amplified input data may also be transmitted as the RF wireless transmission via an RF antenna. During a downlink TTI, the switch path may be deactivated and the receiver stage may receive an additional RF wireless transmission to be processed in the receiver stage.

    COOPERATIVE LEARNING NEURAL NETWORKS AND SYSTEMS

    公开(公告)号:US20190065951A1

    公开(公告)日:2019-02-28

    申请号:US16114923

    申请日:2018-08-28

    Abstract: Systems, methods, and apparatuses related to cooperative learning neural networks are described. Cooperative learning neural networks may include neural networks which utilize sensor data received wirelessly from at least one other wireless communication device to train the neural network. For example, cooperative learning neural networks described herein may be used to develop weights which are associated with objects or conditions at one device and which may be transmitted to a second device, where they may be used to train the second device to react to such objects or conditions. The disclosed features may be used in various contexts, including machine-type communication, machine-to-machine communication, device-to-device communication, and the like. The disclosed techniques may be employed in a wireless (e.g., cellular) communication system, which may operate according to various standardized protocols.

    Wireless devices and systems including examples of full duplex transmission

    公开(公告)号:US10142137B2

    公开(公告)日:2018-11-27

    申请号:US15447731

    申请日:2017-03-02

    Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of full duplex compensation with a self-interference noise calculator. The self-interference noise calculator may be coupled to antennas of a wireless device and configured to generate adjusted signals that compensate self-interference. The self-interference noise calculator may include a network of processing elements configured to combine transmission signals into sets of intermediate results. Each set of intermediate results may be summed in the self-interference noise calculator to generate a corresponding adjusted signal. The adjusted signal is received by a corresponding wireless receiver to compensate for the self-interference noise generated by a wireless transmitter transmitting on the same frequency band as the wireless receiver is receiving.

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