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.

Abstract: A device comprising a plurality of antennas operable to transmit and receive communication packets via a plurality of communication protocols and an integrated circuit chip coupled to the plurality of antennas. The integrated circuit chip comprises a first and a second plurality of processing elements. The first plurality of processing elements operable to receive communication packets via a first one of a plurality of communication protocols and process an optimal route. The second plurality of processing elements communicatively coupled to the first plurality of processing elements and operable to determine the optimal route to transmit the communication packets from a source device to a destination device based, at least in part, on transmission characteristics associated with at least one of the source or destination devices.

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.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of mixing input data with coefficient data specific to a processing mode selection. 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 a specific processing mode selection. The processing mode selection may include a single processing mode, a multi-processing mode, or a full processing mode. The processing mode selection may be associated with an aspect of a wireless protocol. 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.

Abstract: Methods, apparatuses, and systems for repairing defective memory cells in regions of a memory array associated with high or low priority levels are disclosed. A repair address generator may be configured to generate a memory address map for repair (e.g., blowing fuses at a fuse circuit), depending on whether certain applications may operate at a high priority level indicative of a low bit error rate or a low priority level indicative of a higher bit error rate. For example, a specified error rate associated with a low priority level may correspond to a threshold error rate for certain applications, such as a neural network application that stores trained weights. Such neural network applications may access trained weights being partially stored in defective memory cells, with the least significant bits of such trained weights being stored in defective memory cells that are not repaired according to the memory address map.

Abstract: An apparatus, and a method therefore, are described, the apparatus according to one embodiment including a security manager and a plurality of clusters of processing elements. Each cluster of the plurality of clusters includes a respective plurality of processing elements. A controller of the apparatus, which may include a security manager, may be configured to control the plurality of clusters to receive a first data stream and a second data stream, control a first plurality of processing elements in a first cluster to process the first data stream using a first security protocol, and control a second plurality of processing elements in a second cluster to process the second data stream using a second security protocol.

Abstract: Methods, systems, and devices for signal processing and wireless communication are described. For example, a device may include a plurality of antennas operable to transmit and receive communication packets via a plurality of communication protocols and an integrated circuit chip coupled to the plurality of antennas. The integrated circuit chip may comprise a first and a second plurality of processing elements. The first plurality of processing elements may be operable to receive communication packets via a first one of a plurality of communication protocols and process an optimal route. The second plurality of processing elements may be communicatively coupled to the first plurality of processing elements and operable to determine the optimal route to transmit the communication packets from a source device to a destination device based, at least in part, on transmission characteristics associated with at least one of the source or destination devices.

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.

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.

Abstract: Systems, methods, and apparatuses for wireless communication are described. Input data for in-phase branch/quadrature branch (I/Q) imbalance or mismatch may be compensated for or non-linear power amplifier noise may be used to generate compensated input data. In some examples, a transmitter may be configured to transmit communications signaling via a first antenna, the transmitter including a filter configured for digital mismatch correction; a receiver may be configured to receive communications signaling via a second antenna; and a switch may be configured to selectively activate a first switch path to couple the transmitter and the first antenna and a second switch path to couple the receiver and the transmitter to provide communications signaling received via the transmitter as feedback for the filter through the receiver.

Abstract: An apparatus is described. The apparatus includes an antenna array configured to detect one or more radio frequency signals from one or more radio emitters and an integrated circuit chip coupled to the array of antennas. The integrated circuit chip comprises a first plurality of processing elements configured to determine a location of the one or more emitters based on the one or more radio frequency signals and a second plurality of processing elements configured to process the location information for communication via a cellular network. The apparatus further includes an antenna coupled to the second plurality of processing elements and configured to communicate the processed location information via a cellular network.

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.

Abstract: Examples described herein include methods, devices, and systems which may implement different processing stages for wireless communication in processing units. Such data processing may include a source data processing stage, a baseband processing stage, a digital front-end processing stage, and a radio frequency (RF) processing stage. Data may be received from a sensor of device and then processed in the stages to generate output data for transmission. Processing the data in the various stages may occur during an active time period of a discontinuous operating mode. During the active time period, a reconfigurable hardware platform may allocate all or a portion of the processing units to implement the processing stages. Examples of systems and methods described herein may facilitate the processing of data for 5G (e.g., New Radio (NR)) wireless communications in a power-efficient and time-efficient manner.

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.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of mixing input data with coefficient data specific to a processing mode selection. 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 a specific processing mode selection. The processing mode selection may include a single processing mode, a multi-processing mode, or a full processing mode. The processing mode selection may be associated with an aspect of a wireless protocol. 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.

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.

Abstract: Apparatuses and methods are disclosed for an FPGA architecture that may improve processing speed and efficiency in processing less complex operands. Some applications may utilize operands that are less complex, such as operands that are 1, 2, or 4 bits, for example. In some examples, the DSP architecture may skip or avoid processing all received operands or may process a common operand more frequently than other operands. An example apparatus may include configurable logic blocks including DSP slices and an interconnected coupling the configurable logic blocks. An operand register of a DSP slice may include an operand input that is coupled to an output of that DSP slice.

Abstract: An apparatus is described. The apparatus includes an antenna array configured to detect one or more radio frequency signals from one or more radio emitters and an integrated circuit chip coupled to the array of antennas. The integrated circuit chip comprises a first plurality of processing elements configured to determine a location of the one or more emitters based on the one or more radio frequency signals and a second plurality of processing elements configured to process the location information for communication via a cellular network. The apparatus further includes an antenna coupled to the second plurality of processing elements and configured to communicate the processed location information via a cellular network.

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.

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).