Systems and methods for automatically analyzing spectral power measurements to identify abnormalities. The systems and methods may receive measurements comprising RF power measured over a contiguous range of frequencies, where at least a first portion of the contiguous range is used to transmit signals and at least a second portion of the contiguous range is unused. Respective boundaries of the unused portions may be identified and infilled to provide modified measurements. The modified measurements may be automatically analyzed to identify the abnormalities.

Systems and methods for automatically analyzing spectral power measurements to identify abnormalities. The systems and methods may receive measurements comprising RF power measured over a contiguous range of frequencies, where at least a first portion of the contiguous range is used to transmit signals and at least a second portion of the contiguous range is unused. Respective boundaries of the unused portions may be identified and infilled to provide modified measurements. The modified measurements may be automatically analyzed to identify the abnormalities.

A method includes transmitting, by a transceiver configured to concurrently transmit over multiple transmit paths and receive over multiple receive paths, one or more signals, the transceiver comprising multiple transmit antennas and multiple receive antennas. The method also includes, for at least one of the multiple receive antennas: receiving one or more feedback signals from one or more power amplifiers associated with the one or more transmitted signals; calculating one or more estimated self-interference (SI) signals based on the one or more feedback signals using an equalizer array comprising a predetermined channel model; and subtracting the one or more estimated SI signals from one or more receive signals received at the at least one receive antenna to obtain one or more residual signals.

A device may receive sequential digital signals generated by a radio unit based on receipt of sequential radio frequency waveforms provided to ports of the radio unit by a signal generator and analyzer. The device may calculate uplink direction beamforming performance of the radio unit based on the sequential digital signals. The device may provide data identifying the uplink direction beamforming performance for display.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for processing communications signals using a machine-learning network are disclosed. In some implementations, pilot and data information are generated for a data signal. The data signal is generated using a modulator for orthogonal frequency-division multiplexing (OFDM) systems. The data signal is transmitted through a communications channel to obtain modified pilot and data information. The modified pilot and data information are processed using a machine-learning network. A prediction corresponding to the data signal transmitted through the communications channel is obtained from the machine-learning network. The prediction is compared to a set of ground truths and updates, based on a corresponding error term, are applied to the machine-learning network.

The disclosure provides a wireless channel scenario identification method and system. The method includes: simulating different wireless channel scenarios to obtain a channel scenario baseband signal y(t).sub.pq; extracting a feature parameter of y(t).sub.pq, extracting an autocorrelation function A.sub.h(t).sub.pq and performing a Fourier transform thereon to obtain a power spectral density function S(t).sub.pq; normalizing S(t).sub.pq to obtain a normalized channel scenario power spectral density function S(t).sub.pq; designing a deep learning network and inputting S(t).sub.pq and a category label pair to train the deep learning network; and for a system with a channel scenario to be identified, collecting a passband signal at its receiving end, obtaining the normalized scenario power spectral density function Ŝ(t).sub.pq, and using Ŝ(t).sub.pq as an input of the trained classifier, the output of the classifier being a label sequence of the channel scenario, and the channel scenario is effectively determined.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a device may receive layout information that identifies a configuration of an antenna array of antennas, wherein the antenna array is to include a plurality of antenna subarrays and a plurality of antenna chips, wherein each antenna chip is communicatively coupled to antennas of an associated antenna subarray; determine, based at least in part on a phase shift characteristic associated with the antennas, a set of phase differences between antenna subarrays; determine, based at least in part on the set of phase differences, a chip position of each antenna chip relative to the associated antenna subarray; and generate, based at least in part on the chip position of each antenna chip, a layout of an antenna package to receive the antenna array and the plurality of antenna chips. Numerous other aspects are provided.

The present invention discloses a system and method for simulating radio frequency (RF) signal propagation through a plurality of mediums using a plurality of configurable digital representations of building information model in two dimensional (2D) or augmented reality (AR) or virtual reality (VR) environments. The system comprising: a client interface, a processor and a memory. The processor comprising a building information model (BIM) generation unit, RF equipment conversion unit and a RF propagation prediction unit. The BIM generation unit is configured to translate 2D graphics into BIM data-sets, by reference to administrator input, to act as one or more parameters to control a generation of 2D or AR or VR environments. The RF equipment conversion unit is configured to transform adjunct data related to a physical configuration of one or more RF equipment into data models. The RF propagation prediction unit is configured to utilize the one or more parameters and the transformed data related to the physical configuration of the one or more RF equipment for simulating the RF signal propagation pattern predictions through the plurality of mediums.

A client device is configured to communicate with an access point over a wireless network, exchanging data with the access point over a selected communication channel. The client device stores an identifier of the selected communication channel. After the wireless connection to the access point has ended, the client device initiates a process to reconnect to the access point over the selected communication channel using the stored identifier.

A client device is configured to communicate with an access point over a wireless network, exchanging data with the access point over a selected communication channel. The client device stores an identifier of the selected communication channel. After the wireless connection to the access point has ended, the client device initiates a process to reconnect to the access point over the selected communication channel using the stored identifier.