Devices and methods enable optimizing a signal of interest based on identifying and analyzing the signal of interest based on radio frequency energy measurements. Signal data is compared with stored data to identify the signal of interest. Signal degradation data is calculated based on noise figure parameters, hardware parameters and environment parameters. The signal of interest is optimized based on the signal degradation data. Terrain data may also be used for optimizing the signal of interest.

Systems, methods, and devices enable spectrum management by identifying, classifying, and cataloging signals of interest based on radio frequency measurements. In an embodiment, signals and the parameters of the signals may be identified and indications of available frequencies may be presented to a user. In another embodiment, the protocols of signals may also be identified. In a further embodiment, the modulation of signals, data types carried by the signals, and estimated signal origins may be identified.

Methods for tracking a signal origin by a spectrum analysis and management device are disclosed. Signal characteristics of other known emitters are used for obtaining a position of an emitter of a signal of interest. In one embodiment, frequency difference of arrival technique is implemented. In another embodiment, time difference of arrival technique is implemented.

A method and a test device for testing the CSI Type 2 channel estimation capability of a DUT are provided. The method includes: a) stimulating certain variance of PMI feedback values from the DUT, especially those belonging to the finer grained Type 2 CSI, b) a statistical collection of one or more PMI reports received through CSI reporting from the DUT during the test execution, c) an identification of Type 1/Type 2 PMI feedback type based on the CSI reports received from the DUT, and d) applying a pass criterion: a minimum threshold of Type 2 specific feedback reports must have been received.

Systems, methods, and devices enable spectrum management by identifying, classifying, and cataloging signals of interest based on radio frequency measurements. In an embodiment, signals and the parameters of the signals may be identified and indications of available frequencies may be presented to a user. In another embodiment, the protocols of signals may also be identified. In a further embodiment, the modulation of signals, data types carried by the signals, and estimated signal origins may be identified.

Methods and systems are provided for dynamically disabling beamforming functionality of one or more frequency bands. For example, a frequency band may have beamforming enabled. One or more user devices may be connected to the frequency band having beamforming enabled for access to a wireless telecommunications network. User devices connected with the frequency band may be at various locations of a network cell of the wireless telecommunications network (e.g., a cell center, middle cell, cell edge). Fading information may be received by one or more of the user devices connected with the frequency band. One or more fading channel measurements of the first frequency band may be above a threshold. In some embodiments, a fading channel measurement of the first frequency band is higher than another available frequency band having beamforming enabled. As such, beamforming of the first frequency band can be dynamically disabled.

Systems, methods and apparatus for spectrum data management for a radio frequency (RF) environment are disclosed. An apparatus comprises at least one receiver, an automatic signal detection (ASD) module, and a learning and conflict detection engine. The apparatus is at the edge of a communication network. The at least one receiver processes RF energy received from the RF environment, thereby generating processed data. The ASD module is configured to extract meta data and detect anomaly based on the processed data. The learning and conflict detection engine is configured for conflict recognition and anomaly identification based on the processed data. The apparatus is operable to generate at least one report for the RF environment.

Systems, methods and apparatus for spectrum data management for a radio frequency (RF) environment are disclosed. An apparatus comprises at least one receiver, an automatic signal detection (ASD) module, and a learning and conflict detection engine. The apparatus is at the edge of a communication network. The at least one receiver processes RF energy received from the RF environment, thereby generating processed data. The ASD module is configured to extract meta data and detect anomaly based on the processed data. The learning and conflict detection engine is configured for conflict recognition and anomaly identification based on the processed data. The apparatus is operable to generate at least one report for the RF environment.

The disclosed system for testing a massive MIMO beamforming antenna array of arbitrary size includes an anechoic chamber, and a mount for a MIMO array antenna positioned in the chamber, wherein the array has at least 8×4 antenna elements that are individually activated to steer transmissions from the array. The system includes dual element antenna probes positionable in the anechoic chamber, with feeds coupling one or more UE sources to the antenna probes; and the UE sources generate RF in OTA communication with the array, emulating multiple UE devices. Additionally the system includes base station electronics coupled to the array, and a test controller coupled to the base station electronics. The test controller signals the UE sources OTA via the array to invoke a connection to the UE sources and measure OTA channel performance between the array and the multiple UE devices emulated, the performance including at least throughput.

A network equipment test device includes per-UE uplink signal generation processing chains for generating per-UE time domain uplink signals. Per-UE signal faders simulate per-UE signal fading for the per-UE time domain uplink signals. Different phases and amplitudes are used over time to simulate different signal fading. Fourier transformation units perform Fourier transformation of each of the time domain uplink signals to produce per-UE frequency domain uplink signals with simulated per-UE signal fading. A subcarrier mapping unit performs subcarrier mapping of the per-UE frequency domain uplink signals to produce a frequency domain multi-UE uplink signal with simulated per-UE signal fading. An inverse Fourier transformation unit performs inverse Fourier transformation of the frequency domain multi-UE uplink signal to produce a multi-UE time domain uplink signal with simulated per-UE signal fading. A network interface transmits the time domain multi-UE uplink signal with simulated per-UE signal fading to the DUT.