A telematics verification system for testing of a vehicle telematics system, the telematics verification system comprising: an electromagnetically shielded compartment adapted to be arranged to cover antennas of the vehicle when testing the vehicle telematics system using the telematics verification system while operating the vehicle; a set of downlink antennas adapted to be arranged inside the electromagnetically shielded compartment, the set of downlink antennas are configured to wirelessly transmit a downlink signal inside the electromagnetically shielded compartment, wherein the signal indicative of the downlink signal is wirelessly receivable by the antennas of the vehicle, and an uplink antenna adapted to be arranged inside the electromagnetically shielded compartment, the uplink antenna is adapted to wirelessly receive uplink signals transmitted by the antennas of the vehicle.

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 is also operable to be used for optimizing the signal of interest.

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.

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.

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 comprises: 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.

In one embodiment, a method is provided. The method comprises determining a free space path loss distance at a frequency of a transmitter; determining a morphology class for a geographic location of the transmitter; determining a scaling factor P corresponding to the determined morphology class; determining a circular analysis region based upon the scaling factor P; and generating a contour.

A method for determining a pre-equalization matrix to be used for testing is provided. A radio communication tester is provided that has a base station emulator and a channel emulator. A device under test is provided that has at least two branches. A N×M multiple-input multiple-output (MIMO) connection is established between the radio communication tester and the device under test. The N×M MIMO connection includes at least two channels. Reference signal received power per branch measurement values are continuously forwarded from the device under test to the radio communication tester. A pre-equalization matrix is determined by the radio communication tester, wherein the reference signal received power per branch measurement values and presence of additive white Gaussian noise (AWGN) are taken into account when calculating the pre-equalization matrix. The pre-equalization matrix compensates cross-talk between the at least two channels and balances the branches such that the device under test receives equal power at its reception antennas. Further, a test setup is described.

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.

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.