Measurement of the propagation conditions of high-frequency signals

Abstract

A method for determining the characteristics of a cellular signal comprises receiving and recording a plurality of cellular signal data at one of a plurality of locations in an environment. The method may further comprise identifying one or more individual cellular signals received at one of the plurality of locations based at least in part on the plurality of cellular signal data. The method may further comprise determining one or more cellular signal characteristics of each of the one or more individual cellular signals received at one of the plurality of locations based at least in part on the plurality of cellular signal data.The method may further comprise simulating the one or more individual cellular signals at the one of the plurality of locations in the environment based at least in part on the one or more cellular signal characteristics.

Description

[0001] The present disclosure relates to systems and methods for characterizing radio frequency (RF) propagation conditions and determining cellular signal characteristics.

[0002] To increase occupant alertness and comfort, vehicles may be equipped with vehicle communication systems configured to transmit and receive cellular signals from cellular base stations. The performance of vehicle communication systems can be affected by the RF propagation conditions in the vehicle's environment. RF propagation conditions can vary greatly between different locations within an environment due to several factors. For example, RF propagation conditions in dense urban areas may be characterized by a low signal-to-noise ratio caused by electromagnetic interference. In another example, RF propagation conditions in rural or remote areas may be characterized by low signal strength and high latency due to long transmission distances.Current systems and procedures for developing, testing, and validating vehicle communication systems may not consider the effects of varying RF propagation conditions and cellular signal characteristics at different locations in the environment.

[0003] DE 10 2021 211 118 B4 describes a method for functionally testing a C-V2X communication of a motor vehicle, wherein the testing is carried out in a test chamber, wherein the motor vehicle is arranged or is arranged on a turntable, wherein a GNSS signal for specifying a time signal is provided in the test chamber by means of a GNSS antenna, wherein for testing a C-V2X scenario, at least one C-V2X signal is generated by means of a signal generator and a test antenna arranged in the test chamber, wherein in order to set a predetermined angle of arrival of the at least one C-V2X signal at a vehicle antenna of the motor vehicle, a rotation angle corresponding to the angle of arrival is set on the turntable, wherein the at least one C-V2X signal is generated taking into account channel transmission properties specified for the C-V2X scenario,and wherein communication performance parameters and / or a behavior of the motor vehicle are detected and evaluated in response to the generated at least one C-V2X signal, and wherein an evaluation result is provided.

[0004] EP 1 606 965 B1 describes a method for adapting a radio network model to the conditions of a real radio network, which provides location-dependent model variables, using measurement data of the model variables from the real radio network obtained at measurement locations. The method comprises the following steps: a) defining a fine grid of a radio cell, by which small surface patches are formed, wherein the radio network model assigns a value of the model variable to each surface patch; b) defining a coarse grid superimposed on the fine grid, by which regions are formed, each comprising a plurality of surface patches of the fine grid; c) obtaining measurement data at measurement locations; and d) modifying the model variables assigned to the surface patches in the various regions by a mathematical operation that is directly determined by the measurement variables obtained in the respective region and the position of the surface patch.

[0005] While vehicle communication systems and methods serve their purpose, there is a need for a new and improved system and method for characterizing radio frequency (RF) propagation conditions and determining RF characteristics for a vehicle.

[0006] Accordingly, it is the object of the present invention to provide a system and method that takes into account the effects of different radio frequency propagation conditions and cellular signal characteristics at different locations in the environment.

[0007] The problem is solved by the subject matter of the independent claim.

[0008] According to the invention, a method for determining cellular signal characteristics is provided. The method may comprise receiving and recording a plurality of cellular signal data at one of a plurality of locations in an environment. The plurality of cellular signal data comprises cellular signals received at one of the plurality of locations in the environment. The method may further comprise identifying one or more individual cellular signals received at one of the plurality of locations based at least in part on the plurality of cellular signal data. The method may further comprise determining one or more cellular signal characteristics of each of the one or more individual cellular signals received at one of the plurality of locations based at least in part on the plurality of cellular signal data.The method may further comprise simulating the one or more individual cellular signals at the one of the plurality of locations in the environment based at least in part on the one or more cellular signal characteristics of each of the one or more individual cellular signals received at the one of the plurality of locations. Identifying the one or more individual cellular signals further comprises determining an environmental noise floor based at least in part on the plurality of cellular signal data. Identifying the one or more individual cellular signals comprises identifying one or more regions of interest in the environment that have higher energy than the noise floor using receive beamforms based at least in part on the plurality of cellular signal data.Identifying the one or more individual cellular signals further comprises locating each of the one or more individual cellular signals within the one or more regions of interest using receive beamforms. Identifying the one or more regions of interest further comprises spatially scanning the plurality of cellular signal data using a first beam having a first beamwidth to identify the one or more regions of interest. Locating each of the one or more individual cellular signals further comprises spatially scanning each of the one or more regions of interest using a second beam having a second beamwidth to locate the one or more individual cellular signals. The second beamwidth is less than the first beamwidth.

[0009] In another embodiment, receiving and recording the plurality of cellular signal data further comprises traveling through the plurality of locations with a measurement vehicle. The measurement vehicle is equipped with a measurement antenna array and a global navigation satellite system (GNSS). Receiving and recording the plurality of cellular signal data may further comprise continuously receiving and recording the plurality of cellular signal data using the measurement antenna array. Receiving and recording the plurality of cellular signal data may further comprise continuously determining and recording a plurality of vehicle locations using the GNSS.Receiving and recording the plurality of cellular signal data may further comprise aligning a subset of the plurality of cellular signal data with each of the plurality of locations based at least in part on the plurality of vehicle locations.

[0010] In another embodiment, determining the one or more cellular signal characteristics of each of the one or more individual cellular signals further comprises determining a direction of arrival of each of the one or more individual cellular signals. Determining the one or more cellular signal characteristics of each of the one or more individual cellular signals may further comprise determining an amplitude of each of the one or more individual cellular signals. Determining the one or more cellular signal characteristics of each of the one or more individual cellular signals may further comprise determining a phase of each of the one or more individual cellular signals.Determining the one or more cellular signal characteristics of each of the one or more individual cellular signals may further comprise determining an arrival time of each of the one or more individual cellular signals.

[0011] In another embodiment, determining the one or more cellular signal characteristics of each of the one or more individual cellular signals further comprises determining identifying metadata about each of the one or more individual cellular signals. The identifying metadata provides at least information about a base station that generated each of the one or more individual cellular signals.

[0012] In another embodiment, determining the identifying metadata further comprises determining identifying metadata about each of the one or more individual cellular signals. The identifying metadata comprises at least one of the following elements: a cell identifier (Cell ID), a system information block (SIB), a master information block (MIB), and a service set identifier (SSID).

[0013] In another embodiment, the method further comprises identifying which of the one or more individual cellular signals are multipath signals based at least in part on the one or more cellular signal characteristics of each of the one or more individual cellular signals.

[0014] In another embodiment, simulating the one or more individual cellular signals further comprises reproducing each of the one or more individual cellular signals in an anechoic chamber having a test vehicle.

[0015] In one application, a system for determining cellular signal characteristics using the method according to the invention is provided. The system may include a measurement system with a measurement antenna array arranged on a measurement vehicle and a measurement controller in electrical communication with the measurement antenna array. The controller is programmed to receive a plurality of cellular signal data using the measurement antenna array. The plurality of cellular signal data comprises cellular signals received in an environment.

[0016] In another embodiment, the system further comprises a test system having a test controller. The controller is programmed to receive the plurality of cellular signal data from the measurement system. The test controller is further programmed to identify one or more regions of interest in the environment that have higher energy than an ambient noise floor by performing receive beamforming based at least in part on the plurality of cellular signal data. The test controller is further programmed to locate each individual cellular signal(s) within the one or more regions of interest using receive beamforming. The controller is further programmed to determine one or more cellular signal characteristics of each of the one or more individual cellular signals based at least in part on the plurality of cellular signal data.

[0017] In another embodiment, to identify the one or more individual cellular signals, the controller is further programmed to determine an ambient noise floor based at least in part on the plurality of cellular signal data. To identify the one or more individual cellular signals, the test controller is further programmed to spatially scan the plurality of cellular signal data using a first beam having a first beamwidth to identify one or more regions of interest in the ambient noise floor having higher energy than the ambient noise floor, using receive beamforms based at least in part on the plurality of cellular signal data.To identify the one or more individual cellular signals, the test controller is further programmed to spatially scan each of the one or more regions of interest using a second beam having a second beamwidth to locate each of the one or more individual cellular signals within the one or more regions of interest using receive beamforms. The second beamwidth is less than the first beamwidth.

[0018] In another embodiment, the controller for determining the one or more cellular signal characteristics of each of the one or more individual cellular signals is further programmed to determine a direction of arrival of each of the one or more individual cellular signals. To determine the one or more cellular signal characteristics of each of the one or more individual cellular signals, the test controller is further programmed to determine an amplitude of each of the one or more individual cellular signals. To determine the one or more cellular signal characteristics of each of the one or more individual cellular signals, the test controller is further programmed to determine a phase of each of the one or more individual cellular signals.To determine the one or more cellular signal characteristics of each of the one or more individual cellular signals, the test controller is further programmed to determine an arrival time of each of the one or more individual cellular signals.

[0019] In another embodiment, the controller for determining the one or more cellular signal characteristics of each of the one or more individual cellular signals is further programmed to determine identifying metadata about each of the one or more individual cellular signals. The identifying metadata provides at least information about a base station that generated each of the one or more individual cellular signals.

[0020] In another embodiment, the test controller for determining the identifying metadata is further programmed to determine the identifying metadata about each of the one or more individual cellular signals. The identifying metadata includes at least one of the following elements: a cell identifier (Cell ID), a system information block (SIB), a master information block (MIB), and a service set identifier (SSID).

[0021] In another embodiment, the test system may further include an anechoic chamber and one or more transmit antenna arrays in electrical communication with the test controller and disposed within the anechoic chamber. The controller is further programmed to reproduce each of the one or more individual cellular signals within the anechoic chamber using the one or more transmit antenna arrays. A test vehicle is disposed within the anechoic chamber.

[0022] In a further application, a method according to the invention for determining cellular signal characteristics is provided. The method may comprise traveling through a plurality of locations in an environment using a measurement vehicle. The measurement vehicle is equipped with a measurement antenna array and a global navigation satellite system (GNSS). The method may further comprise continuously receiving and recording a plurality of cellular signal data using the measurement antenna array. The plurality of cellular signal data comprises cellular signals received at one of the plurality of locations in the environment. The method may further comprise continuously determining and recording a plurality of vehicle locations using the GNSS.The method may further comprise matching a subset of the plurality of cellular signal data with each of the plurality of locations based at least in part on the plurality of vehicle locations. The method may further comprise identifying one or more individual cellular signals received at one of the plurality of locations based at least in part on the plurality of cellular signal data. The method may further comprise determining one or more cellular signal characteristics of each of the one or more individual cellular signals received at one of the plurality of locations based at least in part on the plurality of cellular signal data.

[0023] In another embodiment, identifying the one or more individual cellular signals further comprises determining a noise level of the environment based at least in part on the plurality of cellular signal data. Identifying the one or more individual cellular signals may further comprise spatially scanning the plurality of cellular signal data using a first beam having a first beamwidth to identify one or more regions of interest in the environment that have higher energy than the noise floor, wherein the receive beamforming is based at least in part on the plurality of cellular signal data.Identifying the one or more individual cellular signals may further comprise spatially scanning each of the one or more regions of interest using a second beam having a second beamwidth to locate each of the one or more individual cellular signals within the one or more regions of interest using receive beamforms.

[0024] In another embodiment, determining the one or more cellular signal characteristics of each of the one or more individual cellular signals further comprises determining a direction of arrival of each of the one or more individual cellular signals. Determining the one or more cellular signal characteristics of each of the one or more individual cellular signals may further comprise determining an amplitude of each of the one or more individual cellular signals. Determining the one or more cellular signal characteristics of each of the one or more individual cellular signals may further comprise determining a phase of each of the one or more individual cellular signals.Determining the one or more cellular signal characteristics of each of the one or more individual cellular signals may further comprise determining the arrival time of each of the one or more individual cellular signals. Determining the one or more cellular signal characteristics of each of the one or more individual cellular signals may further comprise determining identifying metadata about each of the one or more individual cellular signals. The identifying metadata provides at least information about a base station from which each of the one or more individual cellular signals originates.

[0025] Further areas of applicability will become apparent from the present description. It should be understood that the description and specific examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure.

[0026] The drawings described herein are for illustrative purposes only and are not intended to limit the scope of the present disclosure in any way. Fig. 1 is a schematic diagram of a measurement system for measuring cellular signals according to an exemplary embodiment; Fig. 2 is a schematic diagram of a test system for testing a test vehicle according to an exemplary embodiment; and Fig. 3 is a flowchart of a method for determining cellular signal characteristics according to an exemplary embodiment.

[0027] The following description is merely exemplary and is not intended to limit the present disclosure, application, or uses.

[0028] In aspects of the present disclosure, radio frequency (RF) propagation conditions can vary widely between different locations within an environment due to several factors. For example, in dense urban areas, RF propagation conditions can be characterized by many reflections and multipath signals caused by environmental obstructions (e.g., large buildings). In another example, RF propagation conditions in rural or remote areas can be characterized by low signal strength and high latency due to long transmission distances. The present disclosure provides a new and improved system and method for measuring and recording RF propagation conditions in various different environments so that realistic RF propagation conditions can be replicated in a controlled environment for testing and developing wireless systems.

[0029] In Fig. 1, a measurement system for measuring cellular signals is shown and generally designated by reference numeral 10a. The measurement system 10a is shown with a measurement vehicle 12a. Although a passenger car is shown, the measurement vehicle 12a may be any type of vehicle without exceeding the scope of the present disclosure.

[0030] The measurement system 10a generally comprises a measurement controller 14, a measurement antenna group 16 and a global navigation satellite system (GNSS) 18.

[0031] The measurement controller 14 is used to implement a method 100 for determining cellular signal characteristics, as described below. The measurement controller 14 includes at least one processor 20 and a non-transitory computer-readable device or medium 22. The processor 20 may be a custom or off-the-shelf processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor among a plurality of processors connected to the measurement controller 14, a semiconductor-based microprocessor (in the form of a microchip or chipset), a macroprocessor, a combination thereof, or generally an instruction-executing device.

[0032] The computer-readable devices or media 22 may include volatile and non-volatile memory, such as read-only memory (ROM), random-access memory (RAM), and keep-alive memory (KAM). KAM is volatile or non-volatile memory that can be used to store various operating variables while the processor 20 is powered off. The computer-readable memory device(s) 22 may be implemented using a variety of storage devices such as PROMs (programmable read-only memory), EPROMs (electrically erasable PROMs), EEPROMs (electrically erasable PROMs), flash memory, or other electrical, magnetic, optical, or combination storage devices capable of storing data, some of which may be executable instructions used by the measurement controller 14 to control various systems of the measurement vehicle 12a.

[0033] The measurement controller 14 can also consist of multiple controllers that are electrically connected to one another. The measurement control unit 14 can be connected to other systems and / or controllers of the measuring vehicle 12a, so that the measurement control unit 14 can access data such as speed, acceleration, braking, and steering angle of the measuring vehicle 12a.

[0034] The measurement controller 14 is in electrical communication with the measurement antenna array 16 and the GNSS 18. In an exemplary embodiment, the electrical connection is established, for example, via a CAN network, a FLEXRAY network, a local area network (e.g., WiFi, Ethernet, and the like), a serial peripheral interface (SPI) network, or the like. It is understood that various additional wired and wireless technologies and communication protocols for communicating with the measurement controller 14 are within the scope of the present disclosure. Within the scope of the present disclosure, the electrical connection also includes the transfer of power and / or energy between electrical devices (e.g., using conductive wires and / or wireless energy transfer technologies).

[0035] The measurement antenna array 16 is used to receive radio frequencies (RF) from an environment 24 surrounding the measurement vehicle 12a. In one non-limiting example, the measurement antenna array 16 is configured to receive cellular network signals, such as 2G signals, 3G signals, 4G signals, 5G signals, 6G signals, and / or the like. In one exemplary embodiment, the measurement antenna array 16 includes a plurality of antenna elements of different types, designs, and / or operating principles. In one non-limiting example, the measurement antenna array 16 includes one or more monopole antennas. In another non-limiting example, the measurement antenna array 16 includes one or more dipole antennas. It is understood that the measurement antenna array 16 may include any number, type, and / or configuration of antennas without departing from the scope of the present disclosure.It should be further understood that the measuring antenna array 16 may also include additional signal processing components in electrical communication with the plurality of antenna elements, such as filters, amplifiers, receiver modules and / or the like.

[0036] In one exemplary embodiment, the measurement antenna array 16 is disposed on an exterior surface of the measurement vehicle 12a, for example, on a roof, a trunk, a door, and / or a window of the measurement vehicle 12a. In another exemplary embodiment, the measurement antenna array 16 is disposed on an interior surface of the measurement vehicle 12a, for example, on a headliner, a dashboard, a door, and / or a window of the measurement vehicle 12a. In some examples, the measurement antenna array 16 is temporarily attached to the measurement vehicle 12a. In one exemplary embodiment, the measurement antenna array 16 is configured with omnidirectional reception capability to receive signals from all directions relative to the measurement vehicle 12a.By way of non-limiting example, the measurement controller 14 is configured to simultaneously scan each of the plurality of antenna elements of the measurement antenna array 16 and store the RF signal data received from the measurement antenna array 16 for further processing, as explained in more detail below. The measurement antenna array 16 is in electrical communication with the measurement controller 14, as described above.

[0037] The GNSS 18 is used to determine the geographic location of the measurement vehicle 12a. In one exemplary embodiment, the GNSS 18 is a global positioning system (GPS). In one non-limiting example, the GPS includes a GPS receiving antenna (not shown) and a GPS controller (not shown) electrically connected to the GPS receiving antenna. The GPS receiving antenna receives signals from a plurality of satellites, and the GPS controller calculates the geographic location of the measurement vehicle 12a based on the signals received by the GPS receiving antenna. In one exemplary embodiment, the GNSS 18 additionally includes a map. The map includes information about infrastructure, such as municipal boundaries, roads, railroads, sidewalks, buildings, and the like. Therefore, the geographic location of the measurement vehicle 12a is contextualized using the map information.In one non-limiting example, the map is retrieved from a remote source via a wireless connection. In another non-limiting example, the map is stored in a database of the GNSS 18. It is understood that various additional types of satellite-based radio navigation systems, such as the Global Positioning System (GPS), Galileo, GLONASS, and the BeiDou Navigation Satellite System (BDS), are within the scope of the present disclosure. The GNSS 18 is in electrical communication with the measurement controller 14, as described above.

[0038] In Fig. 2, a test system for testing a test vehicle 12b is illustrated and generally designated by reference numeral 10b. The test system 10b is illustrated with a test vehicle 12b. Although a passenger car is depicted, the test vehicle 12b may be any type of vehicle without departing from the scope of the present disclosure. The test system 10b generally includes a controller 30, an anechoic chamber 32, and one or more transmit antenna arrays 34.

[0039] Test controller 30 is used to implement method 100 for determining cellular signal characteristics, as described below. Test controller 30 includes at least one processor 36 and a non-transitory computer-readable device or medium 38. Processor 36 may be a custom or off-the-shelf processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor among a plurality of processors connected to test controller 30, a semiconductor-based microprocessor (in the form of a microchip or chipset), a macroprocessor, a combination thereof, or generally an instruction-executing device.

[0040] The computer-readable devices or media 38 may include volatile and non-volatile memory, such as read-only memory (ROM), random access memory (RAM), and keep-alive memory (KAM). KAM is volatile or non-volatile memory that can be used to store various operating variables while the processor 36 is powered off. The computer-readable storage device or media 38 may be implemented using a variety of storage devices such as PROMs (programmable read-only memory), EPROMs (electrical PROMs), EEPROMs (electrically erasable PROMs), flash memory, or other electrical, magnetic, optical, or combination storage devices capable of storing data, some of which may be executable instructions.

[0041] The test controller 30 may also consist of multiple controllers that are electrically connected to one another. The test controller 30 is in electrical communication with one or more transmit antenna groups 34. In an exemplary embodiment, the electrical connection is established, for example, via a CAN network, a FLEXRAY network, a local area network (e.g., WiFi, Ethernet, and the like), a serial peripheral interface (SPI) network, or the like. It is understood that various additional wired and wireless technologies and communication protocols for communicating with the test controller 30 are within the scope of the present disclosure. Within the context of the present disclosure, electrical communication also includes the transfer of power and / or energy between electrical devices (e.g., using conductive wires and / or wireless energy transfer technologies).

[0042] The anechoic chamber 32 is used to create a controlled RF environment for testing the test vehicle 12b. In an exemplary embodiment, the anechoic chamber 32 is an RF acoustic enclosure coated with radiation absorbent material (RAM) 40. The RAM 40 is configured to effectively absorb incident RF radiation to mitigate and / or eliminate the reflection of RF signals within the anechoic chamber 32. In one non-limiting example, the RAM 40 includes pyramid-shaped urethane foam blocks filled with conductive carbon material. In some examples, the anechoic chamber 32 also includes a Faraday cage (not shown) to reduce the ingress of ambient RF noise into the anechoic chamber 32.

[0043] The one or more transmit antenna groups 34 are used to generate RF signals within the anechoic chamber 32 for testing the test vehicle 12b. In an exemplary embodiment, at least one of the one or more transmit antenna groups 34 is a phased array having a plurality of antenna elements that generate a beam of radio waves that can be electronically steered (i.e., beamformed) without physically moving the one or more transmit antenna groups 34. In another exemplary embodiment, at least one of the one or more transmit antenna groups 34 includes a directional or omnidirectional antenna element with an actuator that enables physical movement or orientation of the antenna element.In one non-limiting example, the one or more transmit antenna groups 34 are configured to be controllable by the controller 30 to create any RF environment within the anechoic chamber 32, including, for example, signals effectively emanating from any location within the anechoic chamber 32.

[0044] In one exemplary embodiment, the one or more transmit antenna groups 34 are arranged within the anechoic chamber 32. In another exemplary embodiment, the one or more transmit antenna groups 34 are arranged outside the anechoic chamber 32 and introduce RF signals into the anechoic chamber 32 via waveguides. Fig. 2 shows two transmit antenna groups 34, the test system 10b may include any number of transmit antenna groups 34 disposed within the anechoic chamber 32. In one non-limiting example, the test system 10b includes transmit antenna groups 34 disposed at multiple heights within the anechoic chamber 32 (e.g., one transmit antenna group 34 in each of the six corners of a rectangular chamber). The one or more transmit antenna groups 34 are in electrical communication with the test controller 30, as described above.

[0045] As in Fig. 2, the test vehicle 12b includes a test vehicle system 50. In an exemplary embodiment, the test vehicle system 50 includes a test vehicle controller 52 and a test vehicle communication system 54.

[0046] The test vehicle controller 52 is used to control the test vehicle communication system 54, as described below. The test vehicle controller 52 includes at least one processor 56 and a non-transitory computer-readable device or medium 58. The processor 56 may be a custom or off-the-shelf processor, a central processing unit (CPU), a graphics processing unit (GPU), an auxiliary processor among multiple processors connected to the test vehicle controller 52, a semiconductor-based microprocessor (in the form of a microchip or chipset), a macroprocessor, a combination thereof, or generally any device for executing instructions.

[0047] The computer-readable devices or media 58 may include volatile and non-volatile memory, such as read-only memory (ROM), random access memory (RAM), and keep-alive memory (KAM). KAM is persistent or non-volatile memory that can be used to store various operating variables while the processor 56 is powered off. The computer-readable memory device(s) 58 may be implemented using a variety of storage devices such as PROMs (programmable read-only memory), EPROMs (electrically erasable PROMs), EEPROMs (electrically erasable PROMs), flash memory, or other electrical, magnetic, optical, or combination storage devices capable of storing data, some of which may be executable instructions used by the test vehicle controller 52 to control various systems of the test vehicle 12b.

[0048] The test vehicle controller 52 may also consist of multiple controllers that are electrically connected to one another. The test vehicle controller 52 may be connected to other systems and / or control units of the test vehicle 12b, so that the test vehicle controller 52 can access data such as speed, acceleration, braking, and steering angle of the test vehicle 12b.

[0049] The test vehicle controller 52 is in electrical communication with the communication system 54 of the test vehicle. In an exemplary embodiment, the electrical communication is established, for example, via a CAN network, a FLEXRAY network, a local area network (e.g., WiFi, Ethernet, and the like), a serial peripheral interface (SPI) network, or the like. It is understood that various additional wired and wireless technologies and communication protocols for communicating with the test vehicle controller 52 are within the scope of the present disclosure. For the purposes of the present disclosure, electrical communication also includes the transfer of power and / or energy between electrical devices (e.g., using conductive wires and / or wireless energy transfer technologies).

[0050] The test vehicle communication system 54 is used by the test vehicle controller 52 to communicate with other systems external to the test vehicle 12b. For example, the test vehicle communication system 54 includes capabilities for communicating with vehicles ("V2V" communication), the infrastructure ("V2I" communication), remote systems at a remote call center (e.g., ON-STAR from GENERAL MOTORS), and / or personal devices. In general, the term vehicle-to-everything ("V2X" communication) refers to communication between the test vehicle 12b and any remote system (e.g., vehicles, infrastructure, and / or remote systems).

[0051] In certain embodiments, the test vehicle communication system 54 is a wireless communication system configured to communicate over a wireless local area network (WLAN) using IEEE 802.11 standards or using cellular data communication (e.g., using GSMA standards such as SGP.02, SGP.22, SGP.32, and the like). Accordingly, the test vehicle communication system 54 may further include an embedded universal integrated circuit card (eUICC) configured to store at least one cellular connectivity configuration profile, for example, an embedded subscriber identity module (eSIM) profile.

[0052] The test vehicle communication system 54 is further configured to communicate via a personal area network (e.g., BLUETOOTH), near-field communication (NFC), and / or any other type of radio frequency communication. However, additional or alternative communication methods, such as a dedicated short-range communication channel (DSRC) and / or mobile telecommunications protocols based on the 3rd Generation Partnership Project (3GPP) standards, are also contemplated within the scope of this disclosure. DSRC channels refer to short- to medium-range, one-way or two-way wireless communication channels specifically designed for use in motor vehicles, as well as a set of protocols and standards. The 3GPP is a partnership between several standards organizations that develop protocols and standards for mobile telecommunications. The 3GPP standards are structured as "releases."Therefore, communication methods based on 3GPP versions 14, 15, 16 and / or future 3GPP versions fall within the scope of the present disclosure.

[0053] Accordingly, the test vehicle communication system 54 may include one or more antennas and / or communication transceivers for receiving and / or transmitting signals, such as cooperative sensing messages (CSMs). The test vehicle communication system 54 is configured to wirelessly communicate information between the test vehicle 12b and another vehicle. Furthermore, the test vehicle communication system 54 is configured to wirelessly transmit information between the test vehicle 12b and infrastructure or other vehicles. It is understood that the test vehicle communication system 54 may be integrated into the test vehicle controller 52 (e.g., on the same circuit board as the test vehicle controller 52 or otherwise as part of the test vehicle controller 52) without departing from the scope of the present disclosure.

[0054] In an exemplary embodiment, the test vehicle controller 52 is configured to receive, with the test vehicle communication system 54, signals transmitted from the one or more transmit antenna arrays 34. In one non-limiting example, the test vehicle controller 52 evaluates signal characteristics, such as signal strength, signal-to-noise ratio, and / or the like. The test vehicle controller 52 also evaluates link characteristics, such as transmission speed / bandwidth, latency, and / or the like. In an exemplary embodiment, the test vehicle controller 52 is in electrical communication with the test controller 30 to transmit the signal characteristics, link characteristics, and / or additional signal measurement data to the test controller 30 for further analysis.

[0055] It should be understood that the test vehicle 12b and the test vehicle system 50 are exemplary only and that the system 10b may be used to test any device capable of wireless communication, including, for example, mobile devices (e.g., smartphones), aircraft, watercraft, spacecraft, and / or the like.

[0056] In Fig.3 is a flowchart of the method 100 for determining cellular signal characteristics. The measurement system 10a and the test system 10b are collectively referred to as a system for determining radio signal characteristics. The system for determining cellular signal characteristics is used to perform the method 100 for determining cellular signal characteristics. The method 100 begins at block 102 and proceeds to blocks 104 and 106. At block 104, the controller 14 uses the measurement antenna array 16 to continuously receive a plurality of cellular signal data as the measurement vehicle 12a traverses (i.e., drives through) the environment 24. For the purposes of the present disclosure, the plurality of cellular signal data includes all cellular signals in the environment 24 that are received by the measurement antenna array 16.As one non-limiting example, the measurement controller 14 records the plurality of cellular signal data along with a reception timestamp for each of the plurality of cellular signal data in the media 22 of the measurement controller 14. It should be understood that the system 10 and method 100 of the present disclosure may be used to determine signal characteristics of other RF signals, including, for example, wireless local area network (WLAN) signals, personal area network (e.g., BLUETOOTH) signals, near field communication (NFC) signals, and / or the like. The signal characteristics of other RF signals may be generally referred to as RF signal characteristics. After block 104, the method 100 proceeds to block 108, as explained in more detail below.

[0057] In block 106, the measurement controller 14 uses the GNSS 18 to continuously determine a plurality of vehicle positions as the measurement vehicle 12a traverses the environment 24. In one non-limiting example, the controller 14 records the plurality of vehicle locations, along with a location timestamp for each of the plurality of vehicle locations, in the media 22 of the controller 14. After block 106, the method 100 proceeds to block 108.

[0058] In block 108, the measurement controller 14 compares a subset of the plurality of cellular signal data with each of a plurality of locations in the environment 24. In an exemplary embodiment, the measurement controller 14 uses the received timestamp of each of the plurality of cellular signal data and the location timestamp for each of the plurality of vehicle locations to spatially align the plurality of cellular signal data. For example, the result of block 108 is that at each of the plurality of locations in the environment 24 (e.g., locations spaced every fifty meters along a particular roadway), all cellular signals in the environment 24 received by the measurement antenna array 16 are known. In one non-limiting example, the alignment data is stored in the form of a database in the media 22 of the measurement controller 14. After block 108, the method 100 proceeds to block 110.

[0059] In block 110, the location-targeted cellular signal data determined in block 108 is transmitted to the test controller 30. In one exemplary embodiment, the location-targeted radio signal data is transmitted via the Internet and wireless and / or wired communication. In another exemplary embodiment, the location-targeted cellular signal data is transmitted directly from the measurement controller 14 to the test controller 30 using wireless and / or wired peer-to-peer communication. It should be understood that the location-targeted cellular signal data may first be transmitted to an intermediate system (e.g., a desktop computer, a server system, and / or the like) for additional backup, storage, and / or post-processing prior to transmission to the test controller 30 without departing from the scope of the present disclosure. After block 110, the method 100 proceeds to block 112.

[0060] In block 112, the controller 30 determines a noise floor for each of the plurality of locations in the environment 24 based at least in part on the plurality of location-based cellular signal data received in block 110. For the purposes of the present disclosure, the noise floor is a measure of received signals other than cellular signals (e.g., thermal noise, atmospheric noise, other non-cellular RF signals, and / or the like). In an exemplary embodiment, the test controller 30 determines the noise floor by identifying a minimum received signal magnitude at each of the plurality of locations in the environment 24. After block 112, the method 100 proceeds to block 114.

[0061] In block 114, the controller 30 identifies one or more regions of interest at each of the plurality of locations in the environment 24. For the purposes of the present disclosure, a region of interest is a region of the environment 24 from which a cellular signal is approaching the test vehicle 12a. In one non-limiting example, a region of interest at any one of the plurality of locations is defined as a region of the environment 24 that has higher received RF energy than the noise floor determined in block 112 at that particular one of the plurality of locations. In an exemplary embodiment, the test controller 30 uses receive beamforming to identify the one or more regions of interest at each of the plurality of locations.

[0062] In an exemplary embodiment, receive beamforming means that the test controller 30 applies a set of weighted coefficients to the signals received by each antenna element in the measurement antenna array 16 to generate a first virtual receive beam. Cellular signals whose azimuth and zenith arrival angles fall within the first virtual receive beam are detected by the first virtual receive beam. By adjusting the set of weighted coefficients, the test controller 30 moves the first virtual receive beam (i.e., adjusts an azimuth angle and a zenith angle of a center of the first virtual receive beam relative to the measurement vehicle 12a) to spatially sample the plurality of cellular signal data. In one non-limiting example, the first virtual receive beam has a first beamwidth (e.g., three meters).

[0063] In one non-limiting example, the controller 30 uses receive beamforming with the first virtual receive beam to scan the measurement vehicle 12a in all directions at each of the plurality of locations and identify the one or more regions of interest (e.g., defined as one or more azimuth angle and zenith angle ranges) at each of the plurality of locations. After block 114, the method 100 proceeds to block 116.

[0064] At block 116, the controller 30 locates each individual cellular signal or multiple individual cellular signals at each of the plurality of locations in the environment 24. For the purposes of the present disclosure, an individual cellular signal is a particular RF transmission originating from a particular cellular device (e.g., a smartphone) or a particular cellular base station (i.e., a cell tower). An individual cellular signal may include, for example, a broadcast control channel signal, a synchronization signal, a reference signal, and / or the like. In an exemplary embodiment, the controller 30 uses receive beamforms to locate one or more individual cellular signals.

[0065] In an exemplary embodiment, the controller 30 applies a set of weighted coefficients to the signals received by each antenna element of the measurement antenna array 16 to generate a second virtual receive beam. Cellular signals whose azimuth and zenith arrival angles fall within the second virtual receive beam are detected by the second virtual receive beam. By adjusting the set of weighted coefficients, the controller 30 moves the second virtual receive beam (i.e., adjusts an azimuth angle and a zenith angle of a center of the second virtual receive beam relative to the measurement vehicle 12a) to spatially sample the plurality of cellular signal data. In one non-limiting example, the second virtual receive beam has a second beamwidth (e.g., ten centimeters) that is less than the first beamwidth.

[0066] In one non-limiting example, the test controller 30 uses receive beamforming with the second virtual receive beam to search within each of the one or more regions of interest at each of the plurality of locations determined in block 114. In an exemplary embodiment, the controller 30 decodes the received data to identify the one or more individual cell signals. For example, the test controller 30 may distinguish between the one or more individual cellular signals based on network-identifying information included in each of the one or more individual cellular signals (e.g., cell ID). In another example, the controller 30 may distinguish between the one or more individual radio signals based on additional signal characteristics such as frequency band, channel number, and / or the like.

[0067] In an exemplary embodiment, the controller 30 records the data transmitted by each of the one or more individual cellular signals, as well as the azimuth and zenith angle of arrival of each of the one or more individual cellular signals, in the medium 38 of the controller 30. After block 116, the method 100 continues with blocks 118 and 120.

[0068] In block 118, the test controller 30 determines one or more physical cellular signal characteristics of each of the one or more individual cellular signals at each of the plurality of locations. In an exemplary embodiment, the one or more physical cellular signal characteristics (a) comprise at least one of the following features: a direction of arrival of each of the one or more individual cellular signals (ie,, the azimuth angle of arrival, and the zenith angle of arrival of each of the one or more individual cellular signals), an amplitude of each of the one or more individual cellular signals, a phase of each of the one or more individual cellular signals, a signal strength of each of the one or more individual cellular signals, a signal-to-noise ratio of each of the one or more individual cellular signals, and / or a time of arrival of each of the one or more individual cellular signals. In one non-limiting example, the test controller 30 determines the one or more physical cellular signal characteristics (a) of each of the one or more individual cellular signals by performing signal processing on each of the one or more individual cellular signals. After block 118, the method 100 proceeds to block 122, as explained in more detail below.

[0069] In block 120, the controller 30 determines identifying metadata about each of the one or more individual cellular signals at each of the plurality of locations. In one exemplary embodiment, the identifying metadata provides at least information about a base station from which each of the one or more individual cellular signals originates. In another exemplary embodiment, the identifying metadata further includes at least one of the following: a cell identifier (cell ID), a system information block (SIB), a main information block (MIB), and / or a service set identifier (SSID).In one non-limiting example, test controller 30 determines the identifying metadata about each of the one or more individual cellular signals by decoding each of the one or more individual cellular signals and extracting identifying information from each of the one or more individual cellular signals. After block 120, method 100 proceeds to block 122.

[0070] In block 122, the controller 30 determines additional relevant information about each of the one or more individual cellular signals at each of the plurality of locations. In an exemplary embodiment, the controller 30 identifies which of the one or more individual cellular signals are multipath signals (i.e., signals that have been reflected) and which of the one or more individual cellular signals are direct signals (i.e., signals that have been received directly from a base station without reflection).In one non-limiting example, the test controller 30 identifies the multipath versus direct signals based at least in part on the one or more physical cellular signal characteristics of each of the one or more individual cellular signals determined in block 118 and / or the identifying metadata about each of the one or more individual cellular signals determined in block 120. In one non-limiting example, to identify multipath versus direct signals, the controller 30 identifies signals originating from the same base station based on the identifying metadata and distinguishes between direct and multipath signals based on the one or more physical cellular signal characteristics (e.g., time of arrival). After block 122, the method 100 proceeds to block 124.

[0071] In block 124, the test controller 30 uses the one or more transmit antenna groups 34 to reproduce each of the one or more individual cellular signals at each of the plurality of locations within the anechoic chamber 32 with the test vehicle 12b. In one exemplary embodiment, the controller 30 uses the one or more transmit antenna groups 34 to generate signals having at least the same physical cellular signal characteristics as each of the one or more individual cellular signals determined in block 118. In another exemplary embodiment, the controller 30 uses the one or more transmit antenna groups 34 to generate signals having at least the same identifying metadata as each of the one or more individual cellular signals determined in block 120.

[0072] In an exemplary embodiment, the controller 30 reproduces each of the individual cell signals at each of the plurality of locations sequentially to simulate driving the test vehicle 12b through the environment 24 at each of the plurality of locations. After block 124, the method 100 proceeds to block 126.

[0073] In block 126, the test vehicle controller 52 uses the test vehicle communication system 54 to receive the signals transmitted by the one or more transmit antenna groups 34 in block 124. In an exemplary embodiment, the test vehicle controller 52 records signal quality information, such as the received signal strength, signal-to-noise ratio, and / or the like. In one non-limiting example, the test vehicle controller 52 transmits the signal quality information to the test controller 30 for data processing and aggregation. In an exemplary embodiment, the data collected by performing blocks 124 and 126 is used to optimize the design, orientation, size, and / or placement of the test vehicle communication system 54 for the test vehicle 12b to maximize the performance of the test vehicle communication system 54.After block 126, the method 100 enters a standby state in block 128.

[0074] In an exemplary embodiment, the method 100 repeatedly exits the standby state 128 and restarts at block 102. In one non-limiting example, the method 100 exits the standby state 128 and restarts after a timer, e.g., every three hundred milliseconds.

[0075] The systems 10a, 10b and method 100 of the present disclosure provide several advantages. Measurement system 10a can collect real cellular signal data for various environments (e.g., urban, suburban, rural, remote), under various environmental conditions (e.g., weather conditions), and at various locations around the world. Using measurement antenna arrays 16 to continuously receive all signals in the environment 24 allows the test vehicle 12a to traverse the environment at normal speed without disrupting traffic flow. By performing receive beamforming in post-processing with test system 10b, the data collected by measurement system 10a can be analyzed, and individual cellular signals can be isolated and characterized without requiring real-time processing capabilities on the test vehicle 12a.Using the test system 10b with the anechoic chamber 32 enables the simulation of various RF environments and thus the rapid testing of the test vehicle 12b or other device under test (DUT) under a variety of operating conditions that reflect the measured real-world conditions.

Claims

[1] A method (100) for determining the properties of a cellular signal, the method (100) comprising: Receiving (104) and recording a plurality of cellular signal data at one of a plurality of locations in an environment (24), the plurality of cellular signal data comprising cellular signals received at the one of the plurality of locations in the environment; identifying one or more individual cellular signals received at one of the plurality of locations based at least in part on the plurality of cellular signal data; determining (106) one or more cellular signal characteristics of each of the one or more individual cellular signals received at one of the plurality of locations based at least in part on the plurality of cellular signal data; and Simulating (108) the one or more individual cellular signals at one of the plurality of locations in the environment (24) based at least in part on the one or more cellular signal characteristics of each of the one or more individual cellular signals received at the one of the plurality of locations; wherein identifying the one or more individual cellular signals further comprises: Determining (112) a noise floor of the environment (24) based at least in part on the plurality of cellular signal data; Identifying (114) one or more areas of interest in the environment (24) that have higher energy than the noise floor using receive beamforms based at least in part on the plurality of cellular signal data; and locating (116) each of the one or more individual cellular signals within the one or more regions of interest using receive beamforms; wherein identifying the one or more regions of interest further comprises: spatially scanning the plurality of cellular signal data using a first beam having a first beamwidth to identify the one or more regions of interest; and wherein locating each of the one or more individual cellular signals further comprises: spatially scanning each of the one or more regions of interest using a second beam having a second beamwidth to locate the one or more individual cellular signals, wherein the second beamwidth is less than the first beamwidth. [2] The method of claim 1, wherein receiving and recording the plurality of cellular signal data further comprises: traversing the plurality of locations using a survey vehicle, the survey vehicle being equipped with a survey antenna array and a global navigation satellite system (GNSS); continuously receiving and recording the plurality of cellular signal data using the measuring antenna array; continuously determining and recording a variety of vehicle locations using GNSS; and Aligning a subset of the plurality of cellular signal data with each of the plurality of locations based at least in part on the plurality of vehicle locations. [3] The method of claim 1, wherein determining the one or more cellular signal characteristics of each of the one or more individual cellular signals further comprises: determining (118) the direction of arrival of each of the individual cellular signals; determining (118) the amplitude of each of the individual cellular signals; determining (118) the phase of each of the individual cellular signals; and Determining (118) the arrival time of each of the individual cellular signals. [4] The method of claim 3, wherein determining the one or more cellular signal characteristics of each of the one or more individual cellular signals further comprises: Determining (120) identifying metadata about each of the one or more individual cellular signals, the identifying metadata providing at least information about a base station that generated each of the one or more individual cellular signals. [5] The method of claim 4, wherein determining (120) the identifying metadata further comprises: Determining identifying metadata about each of the one or more individual cellular signals, wherein the identifying metadata comprises at least one of the following elements: a cell identifier (cell ID), a system information block (SIB), a main information block (MIB), and a service set identifier (SSID). [6] The method of claim 4, further comprising: Identifying (122) which of each of the one or more individual cellular signals are multipath signals based at least in part on the one or more cellular signal characteristics of each of the one or more individual cellular signals. [7] The method of claim 1, wherein simulating the one or more individual cellular signals further comprises: Reproducing (124) each of the individual cellular signals in an anechoic chamber (32) with a test vehicle (12b).

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