According to one embodiment, an electronic apparatus includes processing circuitry. The processing circuitry estimates a first AoA of an arrival wave corresponding to a received signal from a receiving element array. The processing circuitry determines whether the estimated first AoA is an outlier or not. The processing circuitry outputs the first AoA as a second AoA, when the first AoA is not to be an outlier. The processing circuitry acquires one or more main-lobe angles assuming that the first AoA is a side-lobe angle of the receiving element array, when the first AoA is to be an outlier. The processing circuitry determines whether the main-lobe angle is an outlier or not. The processing circuitry outputs the main-lobe angle as the second AoA, when the main-lobe angle is not to be an outlier.

In an aspect, a wireless node (e.g., UE, gNB, etc.) receives a reference signal for positioning (RS-P) over a respective bandwidth on one or more paths including an earliest path, and measures a reference signal received power (RSRP) associated with the earliest path of the RS-P based on a sum of energy on the respective bandwidth within at least one number of samples from a peak of the earliest path.

Systems, methods, and apparatus for processing signals using a sensor arrays are disclosed. In one aspect, an apparatus comprising a sensor array and a computing device is provided. The computing device may comprise one or more processors configured to generate a data matrix based on one or more signals received at each of the plurality of sensor and to determine a covariance matrix based on the data matrix. The one or more processors may also be configured to decompose the covariance matrix into a matrix of eigenvalues and a matrix of eigenvectors and to determine a projected data matrix based on applying the data matrix to the eigenvector matrix. Further, the one or more processors may be configured to determine a denoised projected data matrix based on denoising the projected data matrix and to determine a denoised data matrix based on the denoised projected data matrix.

Systems, methods, and apparatus for processing signals using a sensor arrays are disclosed. In one aspect, an apparatus comprising a sensor array and a computing device is provided. The computing device may comprise one or more processors configured to generate a data matrix based on one or more signals received at each of the plurality of sensor and to determine a covariance matrix based on the data matrix. The one or more processors may also be configured to decompose the covariance matrix into a matrix of eigenvalues and a matrix of eigenvectors and to determine a projected data matrix based on applying the data matrix to the eigenvector matrix. Further, the one or more processors may be configured to determine a denoised projected data matrix based on denoising the projected data matrix and to determine a denoised data matrix based on the denoised projected data matrix.

An apparatus may identify a first set of antenna settings and a second set of antenna settings based on beamforming training with a second apparatus, the first set of antenna settings corresponding to a first path with the second apparatus different from a second path with the second apparatus corresponding to the second set of antenna settings. The apparatus may generate a first frame including an indication to use the first path instead of the second path for at least a portion of a fine timing measurement (FTM) session. The apparatus may transmit the first frame for transmission to the second apparatus. The apparatus may receive, from the second apparatus based on the first set of antenna settings, a plurality of FTM measurement frames associated with the at least the portion of the FTM session.

A multi-port antenna and associated systems having extremely wide bandwidth and capable of maintaining directivity as frequency decreases and is made arbitrarily low, allowing DF systems to operate to arbitrarily low frequency regardless of size. Construction may be rugged, lightweight, and low cost, allowing reliable service in harsh environments. The systems allow utilization of both the E and H fields occupying a common area of space. The disclosed DF system takes advantage of knowledge of the as-installed array manifold, uses pattern matching to determine the angle of arrival (AoA) of incoming waves, and enhances sensitivity by using integration on cross-correlation products between the multiple ports to achieve SNR improvement.

A multi-port antenna and associated systems having extremely wide bandwidth and capable of maintaining directivity as frequency decreases and is made arbitrarily low, allowing DF systems to operate to arbitrarily low frequency regardless of size. Construction may be rugged, lightweight, and low cost, allowing reliable service in harsh environments. The systems allow utilization of both the E and H fields occupying a common area of space. The disclosed DF system takes advantage of knowledge of the as-installed array manifold, uses pattern matching to determine the angle of arrival (AoA) of incoming waves, and enhances sensitivity by using integration on cross-correlation products between the multiple ports to achieve SNR improvement.

An antenna direction calculation device acquires a plurality of relationships, each indicating a relationship between: weather data on a radio wave communication path between a transmitting-side antenna and a receiving-side antenna; and an optimal reception direction for the receiving-side antenna in a case of: a radio wave transmission direction of the transmitting-side antenna being a predetermined transmission direction; and the weather data. The antenna direction calculation device generates, using the plurality of relationships and a machine learning technique, a direction calculation model that, upon receiving an input of weather data on the radio wave communication path, outputs a reception direction for the receiving-side antenna, using the plurality of relationships and a machine learning technique.

An antenna direction calculation device acquires a plurality of relationships, each indicating a relationship between: weather data on a radio wave communication path between a transmitting-side antenna and a receiving-side antenna; and an optimal reception direction for the receiving-side antenna in a case of: a radio wave transmission direction of the transmitting-side antenna being a predetermined transmission direction; and the weather data. The antenna direction calculation device generates, using the plurality of relationships and a machine learning technique, a direction calculation model that, upon receiving an input of weather data on the radio wave communication path, outputs a reception direction for the receiving-side antenna, using the plurality of relationships and a machine learning technique.

Disclosed are techniques for wireless communication. In an aspect, a base station performs one or more angle-based measurements in a first coordinate system, determines whether to report, to a positioning entity, the one or more angle-based measurements in a local coordinate system (LCS) or a global coordinate system (GCS), and reports the one or more angle-based measurements to the positioning entity in the LCS or the GCS based on the determination. In an aspect, a positioning entity receives, from a base station, one or more angle-based measurements in an LCS of the base station or a GCS, determines whether the one or more angle-based measurements are in the LCS or the GCS, and processes the one or more angle-based measurements based on the determination.