FIELD OF THE INVENTION

This invention relates to sensing in a communications network, in particular to the extraction of information from polarized signals to infer information about an environment using polarimetry sensing.

BACKGROUND

Mobile telecommunications technology has evolved rapidly, shifting from voice-centric communication usages to predominantly data-centric services usages. The next generation of telecommunications technology will further pursue the increase of data channel capacity and coverage for more users at an unseen scale, but will also include new types of services, such as sensing.

Sensing technologies are traditionally designed as a stand-alone function through dedicated systems such as radar, or image processing based systems. However, the concept of sensing integrated with communications has recently drawn significant attention.

Promisingly, the goal of combining sensing and communications features is to reach a mutual benefit. On one hand, communication signals can be used for sensing purposes and can help to achieve high accuracy localization, activity sensing or environment scouting. On the other hand, sensing features can be used in order to increase the quality of service and the performance of communication with better interference mitigation, channel prediction or beam steering/focusing/alignment.

So far, the design of waveforms of wireless communication signals and their processing has mainly focused on the quality of the signal and its level after the antenna. Such an approach has motivated consideration of the wireless channel, including propagation and antennas, as a black box for which a model is inferred through sounding signals (pilots). The aim is to acquire state information which helps to decode the embedded information. This strategy focuses on the signal-to-noise ratio seen before an analogue to digital converter (ADC). For sensing applications, a significant amount of information related to the environment is neglected, distorted or completely squeezed in non-useful information. A first cause of this situation is that radio frequency (RF) signals propagate in the field domain, as three-dimensionnal vectors. All interactions between the environment and the RF signals involve the field domain (in general, electric field). With most antennas employed in wireless communication devices, these interactions are squeezed out, since they are converted to single dimension signals represented by currents or voltages.

Empowering wireless communication devices with sensing applications requires hardw are and algorithm tools to perform measurements of impinging electric field. Polarimetry is an important capability to enable such applications.

Such sensing capabilities are in general embedded in specific imagery setups, or in apparatus with controlled deployment in terms of location and orientation.

Many prior techniques rely on devices that are equipped to control the polarization pattern of their radio wave emission and reception antennas to create a sufficient state of polarization diversity to detect Line of Sight presence between two devices. Therefore, such techniques require specific hardware support and configuration in order to switch between polarization patterns and multiple signals must be emitted with different polarization patterns in order to achieve the required polarization diversity state.

Only a minor subset of wireless devices can benefit from such methods, since most consumer off-the-shelf (COTS) wireless devices have fixed polarization radiation.

In general, integrating new sensing feature into wireless communication devices will negatively impact production cost, runtime energy consumption and thereby compromise the performance of sensing or communication.

Polarimetry sensing therefore cannot generally be implemented with COTS wireless communication devices. This feature is usually implemented using dedicated devices and setups, where location and orientation are fixed, or requires dedicated hardware components to perform polarimetry sensing.

In mobile devices, such facilities are generally not available, since such devices can be placed in any location and any orientation.

It is desirable to develop a method to overcome such problems. SUMMARY OF THE INVENTION

According to a first aspect, there is provided a receiver being configured to: receive polarized electromagnetic radiation, an indication of an orientation of a transmitter that transmitted the polarized electromagnetic radiation, and a polarization configuration of the transmitter, wherein the receiver has a known orientation and polarization configuration; transform the polarized electromagnetic radiation to a reference coordinate system with respect to at least one of the polarization configuration of the receiver, the polarization configuration of the transmitter, the known orientation of the receiver, and the orientation of the transmitter to form a transformed signal; and convey the transformed signal and an indication of at least one of the reference coordinate system, the orientation of the transmitter, the orientation of the receiver, the polarization configuration of the transmitter, and the polarization configuration of the receiver to a processor configured to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

According to another aspect, there is provided a transmitter being configured to: transmit polarized electromagnetic radiation to a receiver; receive a measured polarized signal from the receiver, an indication of an orientation of the receiver, and a polarization configuration of the receiver, wherein the transmitter has a known orientation and polarization configuration; transform the measured polarized signal to a reference coordinate system with respect to at least one of the polarization configuration of the receiver, the polarization configuration of the transmitter, the orientation of the receiver, and the orientation of the transmitter to form a transformed signal; and convey the transformed signal and an indication of at least one of the reference coordinate system, the orientation of the transmitter, the orientation of the receiver, the polarization configuration of the transmitter, and the polarization configuration of the receiver to a processor configured to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

This may allow for polarimetry sensing on a wide range of devices, including those with a single polarization configuration, which are not equipped for multiple polarity radiation, and does not require prior knowledge of the environment geometry. This technique has several applications, ranging from Line of Sight path distinction to object detection and material identification of reflecting surfaces.

The information about the one or more paths of the polarized electromagnetic radiation may comprise an indication of the presence of an obstacle in one or more of the paths of the polarized electromagnetic radiation between the transmitter and the receiver and/or an indication of a composition and/or property of one or more materials of the obstacle. This may allow for Line of Sight path distinction, object detection and/or material identification of reflecting surfaces.

The orientation of the transmitter and the orientation of the receiver may be determined with respect to a common vector. The common vector may be, for example, a vector in the direction of the Earth’s centre.

The orientation of the receiver and/or the transmitter relative to the receiver may be fixed. For example, the receiver and/or the transmitter may static. They may be positioned on a stationary building or tower. The receiver and/or the transmitter may be base stations in a telecommunications network. This may allow for implementation of the technique in an existing communications network.

The receiver may be configured to send the transformed signal to the transmitter for processing by the processor. This may allow the processor to infer information about the environment from the transformed signal. Alternatively, the receiver may be configured to send the transformed signal to a remote device for processing by the processor. The receiver may comprise a transceiver configured to transmit the transformed signal to the processor. Alternatively, the receiver may comprise the processor and the receiver may infer said information.

Each of the receiver and the transmitter may be one of a base station, a user equipment device and a communication equipped vehicle. This may allow the technique to be used in a variety of different network configurations, with static or mobile endpoints.

The receiver may be configured to receive a request from the transmitter to receive the polarized electromagnetic radiation emitted by the transmitter. The receiver may be configured to receive the polarized electromagnetic radiation in response to accepting the request. This may allow the receiver to enter a sensing mode in which it anticipates the sensing signal from the transmitter.

The receiver may be further configured to receive one or more signals comprising the polarized electromagnetic radiation and the indication of the orientation of the transmitter and the polarization configuration of the transmitter, wherein the one or more signals further comprise one or more transmission parameters. This may allow the receiver to be informed of the transmission parameters of the transmitter. The one or more transmission parameters may comprise one or more of a frequency channel of the one or more signals and a selected bandwidth of the one or more signals. This may allow the receiver to receive the polarized electromagnetic radiation on an appropriate channel at an appropriate bandwidth.

The one or more signals may be radio frequency signals. This may allow the approach to be used in a telecommunications network where multiple devices are configured to transmit and/or receive radio frequency signals.

The receiver may be further configured to compute a model for transforming subsequently received polarized electromagnetic radiation from the transmitter. This may improve the efficiency of the sensing procedure.

The receiver may comprise at least one orientation sensor for determining the known orientation of the receiver. For example, the receiver may comprise a gyroscope. This may be a convenient implementation, as such orientation sensors are common components in mobiles phones and other user equipment devices.

According to a further aspect, there is provided a method for implementation at a receiver having a known orientation and polarization configuration, the method comprising: receiving polarized electromagnetic radiation, an indication of an orientation of a transmitter that transmitted the polarized electromagnetic radiation, and a polarization configuration of the transmitter; transforming the polarized electromagnetic radiation to a reference coordinate system with respect to at least one of the polarization configuration of the receiver, the polarization configuration of the transmitter, the known orientation of the receiver, and the orientation of the transmitter to form a transformed signal; and conveying the transformed signal and an indication of at least one of the reference coordinate system, the orientation of the transmitter, the orientation of the receiver, the polarization configuration of the transmitter, and the polarization configuration of the receiver to a processor configured to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

According to a further aspect, there is provided a method for implementation at a transmitter having a known orientation and polarization configuration, the method comprising: transmitting polarized electromagnetic radiation to a receiver; receiving a measured polarized signal from the receiver, an indication of an orientation of the receiver, and a polarization configuration of the receiver; transforming the measured polarized signal to a reference coordinate system with respect to at least one of the polarization configuration of the receiver, the polarization configuration of the transmitter, the orientation of the receiver, and the orientation of the transmitter to form a transformed signal; and conveying the transformed signal and an indication of at least one of the reference coordinate system, the orientation of the transmitter, the orientation of the receiver, the polarization configuration of the transmitter, and the polarization configuration of the receiver to a processor configured to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

These methods may permit polarimetry sensing on a wide range of devices, including those with a single polarization configuration, which are not equipped for multiple polarity radiation, and does not require prior knowledge of the environment geometry.

According to another aspect, there is provided a processor configured to process data from a receiver, the data comprising a transformed signal formed by transforming polarized electromagnetic radiation received by the receiver from a transmitter into a reference coordinate system with respect to at least one of an orientation of the receiver, an orientation of the transmitter, a polarization configuration of the receiver, and a polarization configuration of the transmitter to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

The information about the one or more paths of the polarized electromagnetic radiation may comprise an indication of the presence of an obstacle in one or more of the paths of the polarized electromagnetic radiation between the transmitter and the receiver and/or an indication of a composition and/or property of one or more materials of the obstacle. This may allow for Line of Sight path distinction, object detection and/or material identification of reflecting surfaces.

The processor may be configured to decompose the transformed signal into two or more paths and estimate a polarization of each path of the transformed signal to infer information about the paths of the polarized electromagnetic radiation between the transmitter and the receiver.

The processor may be configured to compute a degree of depolarization for each of one or more paths of the polarized electromagnetic radiation with respect to the emitted polarization by the transmitter and infer the information about the environment in dependence on the degree of depolarization. Polarized electromagnetic radiation may undergo different degrees of depolarization on interacting with different materials and/or being reflected from objects at different angles. Computing the degree of polarization may therefore allow the processor to effectively infer information about the environment.

The processor may be further configured to form a map of an environment between the transmitter and the receiver. Such a map may, for example, be used to allow mobile devices to avoid collisions with obstacles in their surrounding environment.

The processor may be configured to estimate a ratio of a component of the transformed signal having an electric field polarized perpendicular to a plane of incidence (i.e. for an obstacle in the path of the polarized electromagnetic radiation between the transmitter and the receiver) and a component of the transformed signal having an electric field polarized parallel to the plane of incidence (i.e. a ratio of S- and P-polarizations of the transformed signal). This may allow the processor to infer information about the environment surrounding the receiver and the transmitter, including the materials of reflecting objects in the environment.

The processor may be configured to send the inferred information and one or more corresponding labels to a storage medium. The one or more corresponding labels may comprise one or more of time of capture, path identification, obstacle presence and nature, angle of arrival and relative delay. This may allow the processor to effectively map the environment.

The processor may be located at one of the receiver, the transmitter and at a location remote to the receiver and the transmitter. This may allow for flexibility in the processing.

According to a further aspect, there is provided a method for implementation at a processor, the method comprising processing data from a receiver, the data comprising a transformed signal formed by transforming electromagnetic radiation received by the receiver from a transmitter into a reference coordinate system with respect to an orientation of the receiver, an orientation of the transmitter, a polarization configuration of the receiver, and a polarization configuration of the transmitter to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

According to a further aspect, there is provided a communication system comprising: a transmitter configured to transmit polarized electromagnetic radiation and an indication of an orientation of the transmitter and a polarization configuration of the transmitter; a receiver having a known orientation and polarization configuration and being configured to receive the polarized electromagnetic radiation, the indication of the orientation of the transmitter and the polarization configuration of the transmitter; and one or more processors configured to: transform the polarized electromagnetic radiation to a reference coordinate system with respect to at least one of the polarization configuration of the receiver, the polarization configuration of the transmitter, the known orientation of the receiver, and the orientation of the transmitter to form a transformed signal;and process the transformed signal in dependence on at least one of an indication of the reference coordinate system, the orientation of the transmitter, the orientation of the receiver, the polarization configuration of the transmitter, and the polarization configuration of the receiver to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

The receiver may comprise the one or more processors and/or the transmitter may comprise the one or more processors. Alternatively, or additionally, the one or more processors may be located at an entity remote from the transmitter and the receiver. This may allow for flexibility in the processing for transforming the radiation and inferring the information about the environment.

The orientation of the receiver may be an absolute orientation. The orientation of the transmitter may be an absolute orientation.

The orientation of the receiver may be a relative orientation. The orientation may be measured relative to an orientation of the receiver when it received a previous signal. The orientation of the transmitter may be a relative orientation. The orientation may be measured relative to an orientation of the transmitter when it transmitted a previous signal.

The receiver and the transmitter may be wireless devices in a communications network. By enabling polarimetry sensing, wireless devices in a communications network can have an increased capability to measure radio frequency propragation paths in the electric field domain. This may allow for polarimetry sensing on a wide range of devices, including those with a single polarization configuration, which are not equipped for multiple polarity radiation, and does not require prior knowledge of the environment geometry.

According to a further aspect, there is provided a computer-readable storage medium having stored thereon computer-readable instructions that, when executed at a computer system, cause the computer system to perform the method set out above. The computer system may comprise one or more processors. The computer-readable storage medium may be a non- transitory computer-readable storage medium. BRIEF DESCRIPTION OF THE FIGURES

The present disclosure will now be described by way of example with reference to the accompanying drawings. In the drawings:

Figures 1 (a), 1(b) and 1 (c) schematically illustrate depolarization effects for polarized electromagnetic radiation travelling between a transmitter and a receiver.

Figure 2 schematically illustrates polarization diversity in an environment.

Figure 3 schematically illustrates a communications network comprising a base station and multiple user devices in an environment.

Figure 4 shows the variation of polarization ratio (ratio of P- and S-polarizations) with angle of incidence for different materials.

Figure 5(a) shows a schematic illustration of an example of a transmitting device.

Figure 5(b) shows a schematic illustration of an example of a receiving device.

Figure 6 shows an environment with a fixed transmitter and a mobile unmanned aerial vehicle (UAV) in an urban area which act as transmitting and receiving devices in a communications network.

Figure 7 illustrates an exemplary sensing protocol initiated by a receiver in a communications network.

Figure 8 illustrates an exemplary sensing protocol initiated by a transmitter in a communications network.

Figure 9 shows an environment with two unmanned aerial vehicles (UAVs) in an urban area which act as transmitting and receiving devices in a communications network.

Figure 10 shows an exemplary signalling procedure in a sensing session initiated by a receiver in a communications network, using mobile endpoints.

Figure 11 shows an exemplary signalling procedure in a sensing session initiated by a transmitter in a communications network, using relative orientations.

Figure 12 shows an exemplary signalling procedure in a sensing session initiated by a receiver in a communications network, using relative orientations.

Figure 13 shows an example of a method for implementation at a receiver.

Figure 14 shows an example of a method for implementation at a transmitter.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the present invention can allow for information extraction from the environment surrounding transmitting and receiving devices in a telecommunications network, with limited prior knowledge of the environment, using polarimetry sensing. Polarimetry sensing is made possible through the capability of the transmission and measurement of polarized electromagnetic waves. The way electric and magnetic fields oscillate along the direction of the wave propagation characterizes the polarization of a wave.

Electromagnetic radiation may have different polarization configurations, including linear, circular and elliptical. For linear polarization, the electric field of the electromagnetic radiation is confined to a single plane along the direction of propagation. For circular polarization, the electric field has two linear components that are perpendicular to each other and equal in amplitude, but have a phase difference of TT/2. The resulting electric field rotates in a circle around the direction of propagation and, depending on the rotation direction, the radiation is referred to as left- or right-hand circularly polarized radiation. For elliptical polarization, the electric field describes an ellipse. This results from the combination of two linear components with different amplitudes and/or a phase difference that is not TT/2.

As a non-limiting example, the polarization of a radio wave signal can be measured from the intensity of a linearly polarized source signal received by one antenna in a particular orientation in space.

In the following description, the term transmitter applies to a transmitting device whose role is to transmit a polarized signal. The term receiver applies to a receiving device whose role is to receive and measure the transmitted polarized signal.

As schematically illustrated in Figure 1 (a), under a direct line of sight (LoS) condition between the transmitter 101 and the receiver 102, it is expected that no, or very little, depolarization effect is to be observed by the receiver on polarized radio wave signal 103.

In contrast, an electromagnetic wave will undergo a depolarization effect when reflected upon or transmitted through a medium. For example, as schematically illustrated in Figure 1 (b), when polarized radio wave signal 104a emitted by the transmitter 101 encounters an obstacle 105, the transmitted wave 104b is depolarized relative to wave 104a. In Figure 1(c), polarized radio wave signal 106 emitted by the transmitter 101 travels under a direct LoS condition to the receiver 102, whereas wave 107a encounters an obstacle 108 and the transmitted wave 107b is depolarized relative to wave 107a.

This assessment may therefore serve as a first criteria for classifying direct and non-direct paths between a transmitter and a receiver. Figure 2 further illustrates an environment 200 where a transmitter 201 transmits signals comprising polarized electromagnetic radiation to a receiver 202. Signal 202 travels under a direct LoS condition from transmitter 201 to receiver 202. However, signal 203a is reflected from boundary 204. The reflected signal 203b will undergo depolarization relative to signal 203a. Similarly, signal 205a encounters obstacle 206 and the reflected signal 205b will undergo depolarization relative to the emitted signal 205a.

Measuring depolarization in electromagnetic waves can therefore be used to determine the presence of obstacles in the environment of a radio frequency network comprising multiple transmitting and receiving devices. For example, in an environment 300, radio frequency signals may be sent between user equipment (UE) devices 301 and 302, and base station (BS) 303. Polarimetry sensing may be used to determine the presence and/or location of the objects 304, 305. Signals 306, 307, 308 travel between their transmitting and receiving entities under a direct LoS condition, whereas transmitted signals 309a and 310a encounter objects 304 and 305 respectively in their paths. The respective reflected signals 309b and 310b therefore undergo depolarization relative to the transmitted signals.

The depolarization phenomenon is modelled by the Fresnel equations (see, for example https://en.wikipedia.org/wiki/Fresnel_equations), which describe the reflection and transmission of electromagnetic waves upon and through a medium and modelled as a complex refractive index of the medium. This complex value represents a phase velocity (real part) and the attenuation or permittivity (imaginary part) of the medium.

Different categories of materials in common surroundings have a defined range of refractive indices. For example, in the case of metallic surface, which has a refractive index with high conductivity, an incident electromagnetic radio wave energy will be reflected and partially absorbed by the medium. In contrast, in the case of a concrete surface, an incident electromagnetic wave will be reflected and transmitted through the medium.

Different methods may be used to process the measured depolarization of transmitted electromagnetic signals to determine the material properties of an obstacle and therefore estimate its nature.

The two orthogonal linear polarization states that are most important for reflection and transmission are referred to as P- and S-polarization. P-polarized radiation has an electric field polarized parallel to the plane of incidence for an obstacle, while S-polarized radiation has an electric field polarized perpendicular to this plane. As a non-limiting example, estimation of a reflecting material can be performed based on the S- and P-polarization ratio measured by a receiver upon reflection of a transmitted polarized signal from different materials. As shown in Figure 4, metal surfaces reflect almost all the incident energy, with respect to the S- and P- coordinate systems, whereas for other materials, part of the incident wave energy may be transmitted through the medium. Thus, reflected waves will exhibit different polarization pattern than those reflected from metallic surfaces. This phenomenon is illustrated in Figure 4 for a variety of materials.

Therefore, in the following implementations, a processor may determine the S- and P- polarization ratio of the received signal and, based on the polarization ratio, estimate from which material the signal has been reflected from and/or the angle of incidence/reflection. Other methods using polarimetry sensing may alternatively be used. This may allow the processor to infer information about the environment surrounding the receiver and the transmitter using polarimetry sensing.

For reflected signals which have undergone depolarization, the processor can estimate the probability that the polarization deviation is caused by a potential material from a known set of complex refractive indices. This may be done using a stored database of known material properties. The processor may be configured to estimate the material composition of an obstacle in the path of the polarized electromagnetic radiation between the transmitter and the receiver based on the measured depolarization of the transmitted polarized electromagnetic radiation. For example, inside a factory, the known set of large reflecting surface may either be metal or concrete. In an urban area, buildings surfaces can be composed of metal, glass or concrete.

In another instance, path and material estimation can be based on computing a deviation model of the depolarization versus the expected polarization, based on a known polarization configuration of the transmitter.

Embodiments of the present invention can allow for two or more wireless devices with a single polarization configuration for their respective antennas to perform polarimetry sensing. The approach may also be applied for devices that are capable of multiple polarization transmission. In embodiments of the present invention, it is assumed that the devices are self- aware of their orientation in space and self-aware of their polarization configuration. Figure 5(a) shows a schematic illustration of an example of a transmitting device 500, referred to herein as a transmitter. The transmitter may comprise at least one processor, such as processor 501 , and at least one memory, such as memory 502. The memory stores in a nontransient way code that is executable by the processor(s) to implement the device in the manner described herein. The transmitter also comprises a transmit antenna 503 for transmitting polarized electromagnetic radiation and receiving other feedback signals from the receiver. The transmitter further comprises an orientation sensor 504. References herein to the orientation of the transmitter refer to the orientation of the transmit antenna.

Figure 5(b) shows a schematic illustration of an example of a receiving device 550, referred to herein as a receiver. The receiver may comprise at least one processor, such as processor 551 , and at least one memory, such as memory 552. The memory stores in a non-transient way code that is executable by the processor(s) to implement the device in the manner described herein. The receiver also comprises a receive antenna 553 for receiving polarized electromagnetic radiation and an orientation sensor 554. References herein to the orientation of the receiver refer to the orientation of the receive antenna.

As mentioned above, the devices can each be equipped with an orientation sensor, such as a gyroscope. The orientation sensor can be used to determine the orientation of the device. These sensors are common components of mobiles phones and user equipment devices. For other devices which can act as transmitters and/or receivers, such as fixed base stations or access points, orientation information can be collected and configured at the deployment stage, such that the device as self-aware of their respective orientations.

As will be described with respect to the following examples, a receiver has a known orientation and polarization configuration. The receiver is configured to receive polarized electromagnetic radiation from a transmitter. The transmitter can also send the receiver an indication of its orientation and the polarization configuration of the transmitter.

The received polarized electromagnetic radiation can be transformed to a reference coordinate system with respect to at least one of the polarization configuration of the receiver, the polarization configuration of the transmitter, the known orientation of the receiver, and the orientation of the transmitter to form a transformed signal. The transformation can be performed at the receiver, at the transmitter or at a remote processing entity.

From the transformed signal, a processor can infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver, such as the presence of an obstacle in one or more of the paths of the polarized electromagnetic radiation between the transmitter and the receiver and/or an indication of a composition and/or property of one or more materials of the obstacle. This inference can be performed at the receiver, at the transmitter or at a remote processing entity.

Generally, a transmitter (Tx) sends a polarized signal, along with information about its absolute (or relative in some embodiments) orientation in space (with respect to a known common reference, such as the centre of the Earth) and its current polarization configuration in the same referential.

The transmitter is therefore aware of its antenna polarization configuration and orientation in space. Therefore, the transmitted polarization is known in an absolute referential.

A receiver (Rx) acquires the polarized signal. The receiver is aware of its antenna polarization configuration and orientation in space. The orientation and polarization information for the transmitter can also be provided to the receiver. The receiver can correlate the orientation of the transmitter with its own orientation. At this point, the polarized signal can be compared to the polarization configuration of the receiver in the same referential (i.e. a reference coordinate system).

Thus, if the receiver is aware of the orientation and polarization configuration of the transmitter, the transmitted and received polarizations can be expressed in the same referential.

The measured signal can be decomposed into sub-paths and a processor located at the receiver, at the transmitter, or at a remote entity can perform polarization analysis in the electric field domain.

There may be multiple paths that an electromagnetic signal may take when travelling between the transmitter and the receiver. For each of the perceived paths I e {1, the deviation a _t = -(pi ^x ,p ^x ) can be computed, where p ^x is the polarization of the electromagnetic radiation measured at the receiver for path I and p ^x is the polarization of the transmitted electromagnetic radiation for path I.

Once reflecting surface estimation is performed, the processor can associate geometrical information, such as the angle of arrival, with this estimation. This data association can be used as feedback to the system model to improve accuracy. Therefore, in some embodiments, the transmitter is equipped with absolute control and/or awareness of field polarization emission and orientation awareness. The receiver is equipped with orientation awareness and field polarization measurement capabilities.

A protocol and related signalling can be implemented to estimate the impact of environment on the field direction (polarization), as will be described in more detail below.

In the following examples, the transmitter and the receiver are nodes in a communications network. Each node is a connection point in the communications network and can act as an endpoint for data transmission or redistribution. In the following examples, Node 1 acts as the transmitting device and Node 2 acts as the receiving device.

Figure 6 depicts an urban scenario in an environment 600 where a base station 601 (Node 1 1 the transmitter) is positioned at the top of a building 603. Its orientation and antenna polarization are known. A UAV 602 (Node 21 the receiver) is equipped with orientation sensors, and its antenna polarization is known and fixed.

In the environment 600 are multiple obstacles: a concrete building 604 and a metallic object 605, for example a vehicle.

As shown in Figure 6, polarized electromagnetic signal 606 is transmitted by base station 601 and travels under a direct LoS condition to UAV 602.

Polarized electromagnetic signal 607a is transmitted by base station 601 and encounters building 604. The signal 607a is partially absorbed by the building 604 and partially reflected. The reflected signal 607b has undergone depolarization relative to transmitted signal 607a.

Polarized electromagnetic signal 608a is transmitted by base station 601 and encounters metallic object 605. A large proportion of the signal 608a is reflected by metallic object 605. The reflected signal 608b has undergone depolarization relative to transmitted signal 608a.

The depolarization of the transmitted signals 606, 607b and 608b can be measured by the receiver 602.

Two exemplary signalling protocols will now be described with reference to Figures 7 and 8. The sensing signals sent by the transmitter in these examples may be signals such as 606, 607a or 608a shown in Figure 6. The signals received by the receiver may be signals such as 606, 607b or 608b shown in Figure 6.

Figure 7 illustrates one example of a sensing procedure initiated by the receiver 602 (Node 2). This embodiment exemplifies polarimetry sensing at the receiver side, in a monostatic mode (i.e. the transmitter’s spatial position is fixed, but the receiver is mobile, as shown in Figure 6).

As indicated at 701 , Node 2, 602, sends a request for initiating a sensing session with Node 1 , 601. As indicated at 702, Node 1 , 601 , sends back an acknowledgement to Node 2, 602, that the sensing service is available and ready to be used for Node 2.

As shown at 703, Node 1 estimates the absolute orientation of the transmit antenna. The absolute orientation may, for example, be determined with respect to the horizon. Node 1 also sets its transmission parameters, as shown at 704. The transmission parameters may include, for instance (but not limited to) the frequency channel of the signal, the selected bandwidth of the signal, along with information about the polarization configuration of the transmit antenna and the absolute orientation of the transmit antenna.

As shown at 705, Node 2 also estimates the absolute orientation of the receive antenna. The absolute orientation may, for example, be determined with respect to the horizon. Node 2 is also aware of the polarization configuration of the receive antenna.

Node 2 can then trigger a request to start a sensing procedure. At 706, Node 2 transmits a sensing signal 707 via the transmit antenna. The sensing signal 707 is a signal comprising polarized electromagnetic radiation. The sensing signal is received by the receive antenna of Node 1 at 708.

At 709, Node 1 communicates one or more of its transmission parameters (including the polarization configuration of the transmit antenna), as defined above, along with the absolute orientation of the transmit antenna.

In some implementations, a single signal may used to send the sensing signal 707 and the transmission parameters/antenna orientation 709 from Node 1 to Node 2.

From the received information, Node 2 is able to compute a model for transposing subsequent received signals to a unique reference. In one non-limiting example, the reference model may be implemented as a three-dimensional matrix, where the coefficients of the matrix represent magnitudes of the current polarization configuration of the receive antenna in three-dimensional space, at the receiver side. The absolute orientations from the Node 1 and Node 2 antennas can be used to rotate this reference matrix. In another possible implementation, rotations may be applied on the received signals directly, instead of the reference matrix. The purpose of such matrix is to be used to produce correlation metrics against each received radio frequency (RF) channel path.

At 710, Node 2 then applies a material identification procedure. From the RF measurements, Node 2 decomposes the acquired signal into RF propagation paths. Each received path can be correlated against its computed reference model and estimates the presence of LoS, and/or the nature of reflecting surfaces present in the environment in one or more paths of the signal between the transmitter and the receiver, using techniques as described previously (for example, polarization ratio methods).

Node 2 can associate information with preceding estimations, such as the angle of arrival and relative delay from each propagation path. This data association can optionally be exploited for determining a relative location of the Node 2 with respect to Node 1 .

Node 2 can, optionally, provide environment information, such as the composing materials and the locations of objects in the path(s) of the sensing signal(s), to Node 1 , as shown at 711 . At 712, Node 2 sends a signal to Node 1 to close the sensing session.

Figure 8 illustrates an alternative example of the sensing procedure initiated by the transmitter 601 (Node 1). This embodiment exemplifies polarimetry sensing at the transmitter side, in a monostatic mode (i.e. the transmitter’s spatial position is fixed, but the receiver is mobile, as shown in Figure 6).

In this embodiment, the transmitter 601 initiates the sensing session. The measured polarization at the receiver side is fed back to the transmitter, where RF path identification and the material identification procedure is performed.

As indicated at 801 , the transmitter (Node 1) 601 sends a request for initiating a sensing session with the receiver. As indicated at 802, the receiver (Node 2) 602 sends back an acknowledgement that the sensing service is available and ready to be used for the transmitter 601. As shown at 803, Node 1 estimates the absolute orientation of the transit antenna. The absolute orientation may, for example, be determined with respect to the horizon. Node 1 also sets its transmission parameters, as shown at 804. The transmission parameters may include, for instance (but not limited to) the frequency channel, the selected bandwidth, along with information about the polarization configuration of the transmit antenna.

As shown at 805, Node 2, 602, also estimates the absolute orientation of the receive antenna. The absolute orientation may, for example, be determined with respect to the horizon. Node 2 is also aware of the polarization configuration of the receive antenna.

At 806, Node 2 transmits a sensing signal 807 to Node 1. The sensing signal 807 is a signal comprising polarized electromagnetic radiation. The sensing signal is received by Node 1 at 808.

Node 1 can also communicate its transmission parameters, including the polarization configuration of the transmit antenna, to Node 2 (not shown in Figure 8).

Node 2 measures the received sensing signal. As shown at 809, Node 2 then sends back its measurements of the received signal to Node 1 , along with the absolute orientation and polarization configuration of the receive antenna.

The feedback information about the received signal can allow Node 1 to decompose this signal into RF sub-path(s) and quantify the polarization of the signal received from the receiver’s (Node 2) point of view.

Node 1 , upon reception of the feedback signal and the receiver antenna’s orientation and polarization configuration, is able to compute a model for transposing the received signal and the transmitted signal to a unique reference for evaluating the polarization differences between the transmitted polarization and perceived polarization at receiver side.

From the feedback RF measurements, the Node 1 decomposes the acquired signal into RF propagation paths. Each received path can be correlated against its computed reference model and the presence of LoS and/or the nature of reflecting surfaces present in the environment can be estimated, as indicated at 810. The transmitter can associate information with preceding estimations, such as the angle of arrival and relative delay from each propagation path. This data association can optionally be exploited for determining a relative location of the receiver with respect to the transmitter.

At 811 , Node 1 determines whether the sensing session has finished.

Optionally, the estimation results may be shared to the receiver, as shown at 812. At 813, Node 1 sends a signal to Node 2 to close the sensing session.

Another application may involve both a mobile transmitter and receiver (dual mobility). Figure 9 shows two UAVs 901 , 902 in an urban area 900. Therefore, in this scenario, Node 1 (the transmitter) and Node 2 (the receiver) are both communication-equipped vehicles.

Polarized electromagnetic signal 905 is transmitted by UAV 901 and travels under a direct LOS condition to UAV 902.

Polarized electromagnetic signal 906a is transmitted by UAV 901 and encounters building 903. The signal 906a is partially absorbed by the building 903 and partially reflected. The reflected signal 906b has undergone depolarization relative to transmitted signal 906a.

Polarized electromagnetic signal 907a is transmitted by UAV 901 and encounters metallic object 904. A large proportion of the signal 907a is reflected by metallic object 904. The reflected signal 907b has undergone depolarization relative to transmitted signal 907a.

The depolarization of the transmitted signals 905, 906b and 907b can be measured by the receiver 902.

Three exemplary signalling protocols that can be utilised for the exemplary arrangement shown in Figure 9 will now be described with reference to Figures 10 to 12.

For purposes of tracking one or more of the communication-equipped vehicles, the polarimetry sensing procedures described below may be repeated in loop until the end of the sensing session.

In a first example in which there is dual mobility of transmitter and receiver (for example using a transmitter and a receiver each located on a vehicle, as illustrated in Figure 9), the sensing procedure may be initiated at the receiver side. As indicated at 1001 , Node 2, 902, sends a sensing session request to Node 1 , 901. As indicated at 1002, Node 1 sends back an acknowledgement for session allocation and enters a sensing mode.

As shown at 1003, Node 2 triggers a request for a sensing procedure. Node 1 and Node 2 can then both enter a monitoring state, in which they each monitor the orientation of their own antenna.

As shown at 1004, Node 1 estimates the absolute orientation of the transmit antenna. The absolute orientation may, for example, be determined with respect to the horizon. Node 1 also sets its transmission parameters, as shown at 1005. The transmission parameters may include, for instance (but not limited to) the frequency channel, the selected bandwidth along with the information about the transmit antenna’s polarization configuration and absolute orientation.

As shown at 1006, Node 2 also estimates the absolute orientation of the receive antenna. The absolute orientation may, for example, be determined with respect to the horizon. Node 2 is also aware of the polarization configuration of the receive antenna.

At 1007, Node 1 sends one or more of its transmission parameters to Node 2 (including the polarization configuration of the transmit antenna), along with the absolute orientation of the transmit antenna.

The steps of estimating the absolute orientations of the antenna and/or setting the transmission parameters of the transmitter may be performed for the first sensing procedure. These steps can optionally be repeated periodically during the sensing session each time a sensing procedure is performed between the transmitter and the receiver.

As shown at 1008, Node 1 sends a polarized sensing signal 1009 to Node 2. Node 2 receives the polarized sensing signal 1009 at 1010.

From the received information (i.e. the polarized signal, the absolute orientation of the transmit antenna and the polarization configuration of the transmit antenna) and using its own known absolute orientation and polarization configuration of the receive antenna, Node 2 is able to compute a model for transposing subsequent received signals to a unique reference. In one non-limiting example, the reference model may be implemented as a three-dimensional matrix where the coefficients represent the magnitudes of the current polarization configuration of the receive antenna in three-dimensional space. The absolute orientations of the antennas of Nodes 1 and 2 (the transmit and receive antennas respectively) can be used to rotate this reference matrix. In another possible implementation, rotations may be applied on the received signals instead of the reference matrix. The purpose of such a matrix is to be used to produce correlation metrics against each received RF channel path.

From the RF measurements, Node 2 can apply the material identification procedure (as previously described), shown at 1101 , by decomposing the acquired signal into RF propagation paths. Each received path can be correlated against its computed reference model and can be used to estimate the presence of LoS and/or the nature of reflecting surfaces present in the environment.

Node 2 can associate information with preceding estimations, such as the angle of arrival and relative delay from each propagation path. This data association can be usefully exploited for tracking purposes.

At 1012, Node 2 can determine whether the reception process has finished. If the reception process has not finished, further iterations of the process can be performed, as shown at 1013. The steps can be repeated until the end of the sensing session.

If the sensing session has finished, Node 2 may share its estimations data with Node 1 , as shown at 1014. At 1015, Node 1 sends a signal to Node 2 to close the sensing session.

In the example shown in Figure 10, the processing to infer the information about the environment is performed by a processor of the receiver. The sensing procedure can alternatively be initiated at the transmitter (Node 1), and/or the processing to infer the information about the environment can be carried out by a processor of the transmitter, using a similar procedure to that described above with reference to Figure 8. The processing may alternatively be performed at a remote processing entity.

Another example in which the transmitter and receiver are both mobile is illustrated in Figure 11. In this example, the sensing procedure is initiated at the receiver 902 (Node 2). In this embodiment, the orientation information is updated with relative reference, instead of absolute reference. As indicated at 1101 , Node 1 , 901 , initiates the sensing session with a request sent to Node 2, 902. As indicated at 1102, Node 2 acknowledges to allocate a session for Node 1 and enters the sensing mode. Node 2 expects a polarized signal.

As shown at 1103, Node 1 defines one or more transmission parameters (including the polarization configuration of the transmit antenna), as defined above. At 1104, Node 1 transmits a polarized sensing signal 1105 to Node 2.

Node 2 receives and measures the sensing signal at 1106. Node 2 then sends its measurement of the received sensing signal and the polarization of the receive antenna back to the transmitter at 1107. This feedback information about the receiving signal is sufficient for Node 1 to decompose this signal into RF sub-path(s) and quantify the polarization of the signal received from the receiver’s (Node 2’s) point of view.

At 1108, Node 1 can update its one or more transmission parameters and at 1109, Node 1 then sends a further polarized sensing signal 1110, which is received by Node 2 at 1111 .

At 1112, Node 1 evaluates the orientation difference of its transmit antenna between the time of sending the previous polarized sensing signal 1105 and the further polarized sensing signal 1110.

At 1113, Node 2 also evaluates the orientation difference of its receive antenna between the time of reception of the previous polarized sensing signal 1105 (at 1106) and the further polarized sensing signal 1110 (at 1111).

At 1114, Node 2 sends feedback information for the received sensing signal 1110 to allow signal processing at Node 1 , along with the relative orientation of the receive antenna when the signal 1110 was received with respect to the orientation of the receive antenna at the time of receiving the previous polarized signal 1105.

From the information received by Node 1 , Node 1 estimates the transmit antenna’s polarization orientation drift relative to the previous transmitted signal, as well the receiver antenna’s polarization orientation drift from the previous received feedback payload sent by Node 2 (shown at 1107). Both drifts allow for computation of the relative physical orientation of the Node 1 antenna with respect to the Node 2 antenna, and vice versa, that may have occurred in the time frame between the two polarized signal emissions (1105 and 1110), in the same referential coordinate system.

Based on the aforementioned knowledge, at 1115, Node 1 can proceed to apply the material identification/location procedure by decomposing the feedback signal information into RF subpaths and proceed to perform depolarization quantification on each RF sub-path. Estimation of LoS or material presence can be computed from the depolarization effects of each RF subpath.

At 1116, Node 1 can determine whether the sensing session has finished. If so, Node 1 can share its inferred environment information with Node 2, as shown at 1117. At 1118, Node 1 sends a signal to Node 2 to close the sensing session.

Figure 12 shows an alternative signalling procedure for the polarimetry sensing process initiated at the receiver. This example also features mobile end points and relative orientation measurement.

As indicated at 1201 , Node 2 initiates the sensing session with a request sent to Node 1. As indicated at 1202, Node 1 acknowledges to allocate a session for Node 2. At 1203, Node 2 requests a polarized signal for iteration i=1 of the sensing procedure.

As shown at 1204 and 1205 respectively, the transmitter and receiver enable monitoring and tracking of the relative orientation of their respective antennas.

At 1206, Node 1 defines one or more transmission parameters, as defined above.

As shown at 1207, Node 1 transmits an initial sensing signal 1208 to the receiver. Node 2 receives the sensing signal at 1209.

At 1210, Node 1 sends the transmission parameters, including the polarization configuration of the transmit antenna, to Node 2.

After an elapsed time, which can be freely set by the application and optionally adapted to the time of movement of the Nodes, Node 1 estimates the relative orientation of the transmit antenna at 1211 with respect to its orientation at the time of transmitting the initial sensing signal 1208 and can update its transmission parameters at 1212. At 1213 Node 1 sends a further polarized signal 1214 to Node 2, along with its relative orientation in space (estimated at 1211) and transmission parameters at 1215.

Node 2 also estimates the relative orientation of the receive antenna at 1216 with respect to its orientation at the time of receiving the initial sensing signal 1208 and receives the further sensing signal 1214 at 1217.

Node 2 therefore measures the two polarized signals 1208 and 1214, along with the changes in the orientation of the antenna of Node 1 at the time of the two transmitted signals. Node 2 can estimate the transmitter polarization orientation drift, as well as its own polarization orientation drift at the time of the two transmitted signals 1208 and 1214.

Both drifts allow for the computation of the relative physical orientation of the transmit antenna with respect to the receive antenna, and vice versa, that may have occurred in the time frame between the two polarized signal emissions, in the same referential coordinate system. Based on the aforementioned knowledge, Node 2 can proceed to decompose the feedback signal information into RF sub-paths and proceed to depolarization quantification on each RF subpath. Estimation of LoS or material presence is computed from the depolarization effects of each RF sub-path at 1218.

At 1219, Node 2 can determine whether the reception process has finished. If the reception process has not finished, further iterations of the process can be performed, as shown at 1220. The steps can be repeated until the end of the sensing session.

At 1221 , Node 2 can determine whether the sensing session has finished. If so, Node 2 can share its computed environment information with Node 1 , as shown at 1222. At 1223, Node 2 sends a signal to Node 1 to close the sensing session.

In some further alternative implementations, the material identification procedure may be performed by a processor at an entity that is remote from both the transmitter and the receiver. In this case, the receiver will send the necessary information, including orientation and polarization configuration information for the transmit and receive antennas and the measurement of the received signal(s) at the receiver, to the remote processor to determine the information about the environment. Processing algorithms used by the processor (located at the transmitting entity, the receiving entity, or a remote processing entity) can allow the device to infer environment impact, decompose the channel into several paths in the electric field domain and/or build an environment map. The processor may also map and/or classify the estimated environment impact into identification assertions, such as obstacle material and LoS presence.

In further implementations, the processor can be configured to send the inferred information about the environment and one or more corresponding labels to a storage medium. The one or more corresponding labels may comprise one or more of time of capture, path identification, obstacle presence and nature, angle of arrival and relative delay.

Figure 13 shows an example of a method for implementation at a receiver having a known orientation and polarization configuration. At step 1301 , the method comprises receiving polarized electromagnetic radiation, an indication of an orientation of a transmitter that transmitted the polarized electromagnetic radiation, and a polarization configuration of the transmitter. At step 1302, the method comprises transforming the polarized electromagnetic radiation to a reference coordinate system with respect to at least one of the polarization configuration of the receiver, the polarization configuration of the transmitter, the known orientation of the receiver, and the orientation of the transmitter to form a transformed signal. At step 1303, the method comprises conveying the transformed signal and an indication of at least one of the reference coordinate system, the orientation of the transmitter, the orientation of the receiver, the polarization configuration of the transmitter, and the polarization configuration of the receiver to a processor configured to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

At the processor, data from the receiver is processed, the data comprising a transformed signal formed by transforming electromagnetic radiation received by the receiver from a transmitter into a reference coordinate system with respect to an orientation of the receiver, an orientation of the transmitter, a polarization configuration of the receiver, and a polarization configuration of the transmitter to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

Figure 14 shows an example of a method for implementation at a transmitter having a known orientation and polarization configuration. At step 1401 , the method comprises transmitting polarized electromagnetic radiation to a receiver. At step 1402, the method comprises receiving a measured polarized signal from the receiver, an indication of an orientation of the receiver, and a polarization configuration of the receiver. At 1403, the method comprises transforming the measured polarized signal to a reference coordinate system with respect to at least one of the polarization configuration of the receiver, the polarization configuration of the transmitter, the orientation of the receiver, and the orientation of the transmitter to form a transformed signal. At step 1404, the method comprises conveying the transformed signal and an indication of at least one of the reference coordinate system, the orientation of the transmitter, the orientation of the receiver, the polarization configuration of the transmitter, and the polarization configuration of the receiver to a processor configured to infer information about one or more paths of the polarized electromagnetic radiation between the transmitter and the receiver.

By enabling polarimetry sensing, wireless devices in a communications network can have an increased capability to measure RF propragation paths in the electric field domain. This technique has several applications, ranging from LoS path distinction to object detection and material identification of reflecting surfaces, as described above. It may also allow for map building for the environment and tracking of mobile objects.

The application scenario may be adapted to monostatic or mobile end points (for example, nodes in the communications network, such as base stations). The sensing session request may be initiated from any of the end points. Similarly, the estimation processing may be performed at either of the end points (i.e. the transmitter or the receiver), or at a remote processing device.

Compared to prior methods, using the approach described herein, polarimetry sensing is possible for devices having a fixed polarization pattern using external information (i.e. the orientations of the transmitting and receiving devices), instead of requiring multiple polarization patterns. The approach described herein does not require prior knowledge of the environment geometry and can apply for any combination of near-field and far-field incidence and reception cases.

Existing commercial off-the-shelf devices which are not capable of multiple polarity can be conveniently upgraded to use polarimetry sensing through a software update to utilize the techniques described herein.

The applicant hereby discloses in isolation each individual feature described herein and any combination of two or more such features, to the extent that such features or combinations are capable of being carried out based on the present specification as a whole in the light of the common general knowledge of a person skilled in the art, irrespective of whether such features or combinations of features solve any problems disclosed herein, and without limitation to the scope of the claims. The applicant indicates that aspects of the present invention may consist of any such individual feature or combination of features. In view of the foregoing description it will be evident to a person skilled in the art that various modifications may be made within the scope of the invention.