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: 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.

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.

Abstract: Examples of systems and method described herein provide for accessing memory devices and, concurrently, generating access codes using an authenticated stream cipher at a memory controller. For example, a memory controller may use a memory access request to, concurrently, perform translation logic and/or error correction on data associated with the memory access request; while also utilizing the memory address as an initialization vector for an authenticated stream cipher to generate an access code. The error correction may be performed subsequent to address translation for a write operation (or prior to address translation for a read operation) to improve processing speed of memory access requests at a memory controller; while the memory controller also generates the encrypted access code.

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.

Abstract: Examples of systems and method described herein or generating, in a memory controller and/or memory device, access codes for memory regions of the memory device using authentication logic, and for accessing the memory device using the access codes. For example, a memory controller and/or a coupled memory device may generate access codes that a host computing device may include in a memory access request to access one or more memory regions of the memory device. Data read or written at the memory device may in some examples only be accessed in accordance with the access codes for memory regions of the memory device. Accordingly, the systems and methods described herein may provide security for specific memory regions of a memory device because the access code are updated periodically (e.g., based on obtained reset indication) or in accordance with an updated count value from a counter.

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.

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.

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: Methods and apparatus for utilizing non-traditional (e.g., probabilistic or statistically-based) refresh schemes in non-volatile memory. In one embodiment, the memory is characterized in terms of its performance, such as based on BER (bit error rate) as a function of refresh rate based on statistical data for decay of capacitance within the cells of the device with time. In one variant, error-tolerant applications make use of the non-traditionally refreshed (or unrefreshed) memory with enhanced memory bandwidth, since refresh operations have been reduced or eliminated. In another variant, an extant refresh scheme is modified based on a specified minimum allowable performance level for the memory device, In yet another embodiment, error-intolerant applications operate the memory with a reduced or eliminated refresh, and cells or regions of the memory not adequately refreshed by presumed random read/write operations of the memory over time are actively refreshed.

Abstract: Methods, systems, and devices for protective actions for a memory device based on detecting an attack are described. In some systems, a memory device may detect whether a fault is injected into the memory device. The memory device may apply a delay during boot up if a fault is detected. To ensure the delay is applied, the memory device may default to applying the delay and may remove an indication to apply the delay if a fault is not detected. Additionally or alternatively, the memory device may erase information from non-volatile memory during boot up, for example, if a fault is detected. The memory device may be configured to ensure at least a specific portion of memory resources (e.g., resources configured to store sensitive information) is erased during boot up. In some examples, the memory device may store data using a stream cipher to improve security of the data.

Abstract: Methods, systems, and devices for temperature change measurement to detect an attack on a memory device are described. A memory device may measure a rate of change for temperature readings at a dynamic random access memory (DRAM) component of the memory device (e.g., using sensors at the DRAM component). The memory device may compare the rate of change for the temperature to a threshold, for example, using circuitry, a threshold value stored in memory, or both. If the memory device determines that the rate of change for the temperature satisfies the threshold, the memory device may disable one or more features of the memory device to protect against a potential attack. For example, an attack on the memory device may be indicated by the change in temperature readings at the DRAM component, and the memory device may perform one or more protective measures based on detecting the temperature change.

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.

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: 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 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 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 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 input data is mixed with coefficient data at layers of multiplication/accumulation processing units (MAC units). 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: 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: 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.