FIELD

Various exemplary embodiments relate to wireless communications. BACKGROUND

In sensing technologies, for example radars, it is desirable to optimize the accuracy of target detection and localization, particularly in a multi-target environment where there may be an unknown number of possibly moving targets.

SUMMARY

The scope of protection sought for various exemplary embodiments is set out by the independent claims. The exemplary embodiments and features, if any, described in this specification that do not fall under the scope of the independent claims are to be interpreted as examples useful for understanding various exemplary embodiments.

According to an aspect, there is provided an apparatus comprising means for transmitting a plurality of packets, receiving a signal comprising one or more echoes generated by the plurality of packets, the one or more echoes comprising information on one or more targets, extracting the one or more echoes iteratively one-by-one from the received signal, and detecting and localizing the one or more targets based at least partly on information obtained from the one or more echoes.

According to another aspect, there is provided an apparatus comprising at least one processor, and at least one memory including computer program code, wherein the at least one memory and the computer program code are configured, with the at least one processor, to cause the apparatus to: transmit a plurality of packets, receive a signal comprising one or more echoes generated by the plurality of packets, the one or more echoes comprising information on one or more targets, extract the one or more echoes iteratively one-by-one from the received signal, and detect and localize the one or more targets based at least partly on information obtained from the one or more echoes.

According to another aspect, there is provided a system comprising at least a transmitter and a receiver, means for transmitting a plurality of packets, means for receiving a signal comprising one or more echoes generated by the plurality of packets, the one or more echoes comprising information on one or more targets, means for extracting the one or more echoes iteratively one-by-one from the received signal, and means for detecting and localizing the one or more targets based at least partly on information obtained from the one or more echoes.

According to another aspect, there is provided a system comprising a transmitter configured to transmit a plurality of packets, and a receiver configured to receive a signal comprising one or more echoes generated by the plurality of packets, the one or more echoes comprising information on one or more targets, extract the one or more echoes iteratively one-by-one from the received signal, and detect and localize the one or more targets based at least partly on information obtained from the one or more echoes.

According to another aspect, there is provided a method comprising transmitting a plurality of packets, receiving a signal comprising one or more echoes generated by the plurality of packets, the one or more echoes comprising information on one or more targets, extracting the one or more echoes iteratively one-by-one from the received signal, and detecting and localizing the one or more targets based at least partly on information obtained from the one or more echoes.

According to another aspect, there is provided a computer program comprising instructions for causing an apparatus to perform at least the following: transmit a plurality of packets, receive a signal comprising one or more echoes generated by the plurality of packets, the one or more echoes comprising information on one or more targets, extract the one or more echoes iteratively one-by-one from the received signal, and detect and localize the one or more targets based at least partly on information obtained from the one or more echoes.

According to another aspect, there is provided a computer readable medium comprising program instructions for causing an apparatus to perform at least the following: transmit a plurality of packets, receive a signal comprising one or more echoes generated by the plurality of packets, the one or more echoes comprising information on one or more targets, extract the one or more echoes iteratively one-by-one from the received signal, and detect and localize the one or more targets based at least partly on information obtained from the one or more echoes.

According to another aspect, there is provided a non-transitory computer readable medium comprising program instructions for causing an apparatus to perform at least the following: transmit a plurality of packets, receive a signal comprising one or more echoes generated by the plurality of packets, the one or more echoes comprising information on one or more targets, extract the one or more echoes iteratively one-by- one from the received signal, and detect and localize the one or more targets based at least partly on information obtained from the one or more echoes.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following, various exemplary embodiments will be described in greater detail with reference to the accompanying drawings, in which

FIG. 1 illustrates an exemplary embodiment of a cellular communication network;

FIG. 2 illustrates baseband spectrum mask of the IEEE 802.1 lad standard;

FIG. 3 illustrates a preamble of a single carrier physical packet in the IEEE 802.1 lad standard;

FIG. 4 illustrates examples of echoes generated by transmitted packets according to an exemplary embodiment;

FIG. 5 illustrates a processing interval of an exemplary embodiment;

FIG. 6 illustrates a flow chart of an exemplary embodiment;

FIG. 7 illustrates a flow chart of an exemplary embodiment;

FIG. 8 and FIG. 9 illustrate apparatuses according to exemplary embodiments.

DETAILED DESCRIPTION

The following embodiments are exemplifying. Although the specification may refer to "an", "one", or "some" embodiment(s) in several locations of the text, this does not necessarily mean that each reference is made to the same embodiment(s), or that a particular feature only applies to a single embodiment. Single features of different embodiments may also be combined to provide other embodiments.

In the following, different exemplary embodiments will be described using, as an example of an access architecture to which the exemplary embodiments may be applied, a radio access architecture based on long term evolution advanced (LTE Advanced, LTE-A) or new radio (NR, 5G), without restricting the exemplary embodiments to such an architecture, however. It is obvious for a person skilled in the art that the exemplary embodiments may also be applied to other kinds of communications networks having suitable means by adjusting parameters and procedures appropriately. Some examples of other options for suitable systems are the universal mobile telecommunications system (UMTS) radio access network (UTRAN or E-UTRAN), long term evolution (LTE, the same as E-UTRA), wireless local area network (WLAN or WiFi), worldwide interoperability for microwave access (WiMAX), Bluetooth®, personal communications services (PCS), ZigBee®, wideband code division multiple access (WCDMA), systems using ultra-wideband (UWB) technology, sensor networks, mobile ad- hoc networks (MANETs) and Internet Protocol multimedia subsystems (IMS) or any combination thereof.

FIG. 1 depicts examples of simplified system architectures only showing some elements and functional entities, all being logical units, whose implementation may differ from what is shown. The connections shown in FIG. 1 are logical connections; the actual physical connections may be different. It is apparent to a person skilled in the art that the system typically comprises also other functions and structures than those shown in FIG. 1.

The exemplary embodiments are not, however, restricted to the system given as an example but a person skilled in the art may apply the solution to other communication systems provided with necessary properties.

The example of FIG. 1 shows a part of an exemplifying radio access network.

FIG. 1 shows user devices 100 and 102 configured to be in a wireless connection on one or more communication channels in a cell with an access node (such as (e/g)NodeB) 104 providing the cell. The physical link from a user device to a (e/g)NodeB is called uplink or reverse link and the physical link from the (e/g)NodeB to the user device is called downlink or forward link. It should be appreciated that (e/g)NodeBs or their functionalities may be implemented by using any node, host, server or access point etc. entity suitable for such a usage.

A communication system typically comprises more than one (e/g)NodeB in which case the (e/g)NodeBs may also be configured to communicate with one another over links, wired or wireless, designed for the purpose. These links may be used for signaling purposes. The (e/g)NodeB is a computing device configured to control the radio resources of communication system it is coupled to. The NodeB may also be referred to as a base station, an access point or any other type of interfacing device including a relay station capable of operating in a wireless environment. The (e/g)NodeB includes or is coupled to transceivers. From the transceivers of the (e/g) NodeB, a connection is provided to an antenna unit that establishes bi-directional radio links to user devices. The antenna unit may comprise a plurality of antennas or antenna elements. The (e/g)NodeB is further connected to core network 110 (CN or next generation core NGC). Depending on the system, the counterpart on the CN side can be a serving gateway (S-GW, routing and forwarding user data packets), packet data network gateway (P-GW), for providing connectivity of user devices (UEs) to external packet data networks, or mobile management entity (MME), etc.

The user device (also called UE, user equipment, user terminal, terminal device, etc.) illustrates one type of an apparatus to which resources on the air interface are allocated and assigned, and thus any feature described herein with a user device may be implemented with a corresponding apparatus, such as a relay node. An example of such a relay node is a layer 3 relay (self-backhauling relay) towards the base station.

The user device typically refers to a portable computing device that includes wireless mobile communication devices operating with or without a subscriber identification module (SIM), including, but not limited to, the following types of devices: a mobile station (mobile phone), smartphone, personal digital assistant (PDA), handset, device using a wireless modem (alarm or measurement device, etc.), laptop and/or touch screen computer, tablet, game console, notebook, and multimedia device. It should be appreciated that a user device may also be a nearly exclusive uplink only device, of which an example is a camera or video camera loading images or video clips to a network. A user device may also be a device having capability to operate in Internet of Things (loT) network which is a scenario in which objects are provided with the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. The user device may also utilise cloud. In some applications, a user device may comprise a small portable device with radio parts (such as a watch, earphones or eyeglasses) and the computation is carried out in the cloud. The user device (or in some exemplary embodiments a layer 3 relay node) is configured to perform one or more of user equipment functionalities. The user device may also be called a subscriber unit, mobile station, remote terminal, access terminal, user terminal or user equipment (UE) just to mention but a few names or apparatuses.

Various techniques described herein may also be applied to a cyber-physical system (CPS) (a system of collaborating computational elements controlling physical entities). CPS may enable the implementation and exploitation of massive amounts of interconnected 1CT devices (sensors, actuators, processors microcontrollers, etc.) embedded in physical objects at different locations. Mobile cyber physical systems, in which the physical system in question has inherent mobility, are a subcategory of cyber physical systems. Examples of mobile physical systems include mobile robotics and electronics transported by humans or animals.

Additionally, although the apparatuses have been depicted as single entities, different units, processors and/or memory units (not all shown in FIG. 1) may be implemented.

5G enables using multiple input - multiple output (MIMO) antennas, many more base stations or nodes than the LTE (a so-called small cell concept), including macro sites operating in co-operation with smaller stations and employing a variety of radio technologies depending on service needs, use cases and/or spectrum available. 5G mobile communications supports a wide range of use cases and related applications including video streaming, augmented reality, different ways of data sharing and various forms of machine type applications (such as (massive) machine-type communications (mMTC), including vehicular safety, different sensors and real-time control. 5G is expected to have multiple radio interfaces, namely below 6GHz, cmWave and mmWave, and also being integradable with existing legacy radio access technologies, such as the LTE. Integration with the LTE may be implemented, at least in the early phase, as a system, where macro coverage is provided by the LTE and 5G radio interface access comes from small cells by aggregation to the LTE. In other words, 5G is planned to support both inter-RAT operability (such as LTE-5G) and inter-Rl operability (inter-radio interface operability, such as below 6GHz - cmWave, below 6GHz - cmWave - mmWave). One of the concepts considered to be used in 5G networks is network slicing in which multiple independent and dedicated virtual sub-networks (network instances) may be created within the same infrastructure to run services that have different requirements on latency, reliability, throughput and mobility.

The current architecture in LTE networks is fully distributed in the radio and fully centralized in the core network. The low latency applications and services in 5G require to bring the content close to the radio which leads to local break out and multi access edge computing (MEC). 5G enables analytics and knowledge generation to occur at the source of the data. This approach requires leveraging resources that may not be continuously connected to a network such as laptops, smartphones, tablets and sensors. MEC provides a distributed computing environment for application and service hosting. It also has the ability to store and process content in close proximity to cellular subscribers for faster response time. Edge computing covers a wide range of technologies such as wireless sensor networks, mobile data acquisition, mobile signature analysis, cooperative distributed peer-to-peer ad hoc networking and processing also classifiable as local cloud/fog computing and grid/mesh computing, dew computing, mobile edge computing, cloudlet, distributed data storage and retrieval, autonomic self-healing networks, remote cloud services, augmented and virtual reality, data caching, Internet of Things (massive connectivity and/or latency critical), critical communications (autonomous vehicles, traffic safety, real-time analytics, time-critical control, healthcare applications).

The communication system is also able to communicate with other networks, such as a public switched telephone network or the Internet 112, or utilise services provided by them. The communication network may also be able to support the usage of cloud services, for example at least part of core network operations may be carried out as a cloud service (this is depicted in FIG. 1 by "cloud" 114). The communication system may also comprise a central control entity, or a like, providing facilities for networks of different operators to cooperate for example in spectrum sharing.

Edge cloud may be brought into radio access network (RAN) by utilizing network function virtualization (NVF) and software defined networking (SDN). Using edge cloud may mean access node operations to be carried out, at least partly, in a server, host or node operationally coupled to a remote radio head or base station comprising radio parts. It is also possible that node operations will be distributed among a plurality of servers, nodes or hosts. Application of cloudRAN architecture enables RAN real time functions being carried out at the RAN side (in a distributed unit, DU 104) and non-real time functions being carried out in a centralized manner (in a centralized unit, CU 108).

It should also be understood that the distribution of labour between core network operations and base station operations may differ from that of the LTE or even be non-existent. Some other technology advancements probably to be used are Big Data and all-IP, which may change the way networks are being constructed and managed. 5G (or new radio, NR) networks are being designed to support multiple hierarchies, where MEC servers can be placed between the core and the base station or nodeB (gNB). It should be appreciated that MEC can be applied in 4G networks as well.

5G may also utilize satellite communication to enhance or complement the coverage of 5G service, for example by providing backhauling. Possible use cases are providing service continuity for machine-to-machine (M2M) or Internet of Things (IoT) devices or for passengers on board of vehicles, or ensuring service availability for critical communications, and future railway/maritime/aeronautical communications. Satellite communication may utilise geostationary earth orbit (GEO) satellite systems, but also low earth orbit (LEO) satellite systems, in particular mega-constellations (systems in which hundreds of (nano) satellites are deployed). Each satellite 106 in the mega-constellation may cover several satellite-enabled network entities that create on-ground cells. The on ground cells may be created through an on-ground relay node 104 or by a gNB located on ground or in a satellite.

It is obvious for a person skilled in the art that the depicted system is only an example of a part of a radio access system and in practice, the system may comprise a plurality of (e/g)NodeBs, the user device may have an access to a plurality of radio cells and the system may comprise also other apparatuses, such as physical layer relay nodes or other network elements, etc. At least one of the (e/g)NodeBs or may be a Home(e/g)nodeB. Additionally, in a geographical area of a radio communication system a plurality of different kinds of radio cells as well as a plurality of radio cells may be provided. Radio cells may be macro cells (or umbrella cells) which are large cells, usually having a diameter of up to tens of kilometers, or smaller cells such as micro-, femto- or picocells. The (e/g)NodeBs of FIG. 1 may provide any kind of these cells. A cellular radio system may be implemented as a multilayer network including several kinds of cells. Typically, in multilayer networks, one access node provides one kind of a cell or cells, and thus a plurality of (e/g)NodeBs are required to provide such a network structure.

For fulfilling the need for improving the deployment and performance of communication systems, the concept of "plug-and-play" (e/g)NodeBs has been introduced. Typically, a network which is able to use "plug-and-play" (e/g)Node Bs, includes, in addition to Home (e/g)NodeBs (H(e/g)nodeBs), a home node B gateway, or HNB-GW (not shown in FIG. 1). A HNB Gateway (HNB-GW), which is typically installed within an operator’s network may aggregate traffic from a large number of HNBs back to a core network.

Millimeter waves, mmWaves, may be defined as the band of radio frequencies between 30 GHz and 300 GHz, i.e. having a wavelength range between 1 mm and 10 mm. mmWave carrier frequencies for example in the V band, i.e. 40-75 GHz, may be used for fulfilling the high data rate requirements envisioned in wireless networks, in particular in 5G systems, due to the possibility of exploiting the large spectral channels available on those frequencies. mmWaves may also be used in sensing technologies to detect objects and provide for example the range, velocity and angle of these objects. A key requisite with mmWaves may be the establishment of a proper beam alignment between a pair of communicating nodes. For example, the IEEE 802. Had standard operating at 60 GHz may support beam steering towards up to 128 distinct sectors to cope with channel attenuation, and may implement a periodic search procedure, comprising a preliminary sector level sweep, SLS, phase aimed at acquiring a coarse-grain antenna sector configuration, and a beam refinement phase, to establish a highly directional communication. The IEEE 802.1 lad standard allows directional multi-gigabit, DMG, communication at mmWaves, supporting transmission rates of up to 8 Gbit/s using a single-input single-output, S1S0, wireless transmission.

Opportunistic sensing may be defined as the exploitation of communication signals, enabled by coordination between a communication transmitter and a co-located radar receiver chain, for the purpose of target detection and localization. An exemplary embodiment of an opportunistic sensing scheme using the IEEE 802. llad standard may exploit the pair of complementary Golay sequences comprised in the preamble of the single carrier physical, SCPHY, packet to extract relevant parameters from a reflecting object in front of the transmitter. Another exemplary embodiment using the IEEE 802.1 lad standard may leverage the control physical, CPHY, packet sent in SLS phase carried out in the beacon header interval, BH1, to implement a short-range surveillance radar patrolling a wide angular sector. CPHY packets may be used to exchange signaling and/or control messages in order to establish and monitor connections between devices. In other words, such an exemplary embodiment may exploit the correlation property of the transmitted signal for target detection and parameter estimation.

However, correlation-based processing may suffer from target masking and spurious detections caused by the secondary lobes of the cross-ambiguity function in a multi-target environment. To address this possible limitation, in an exemplary embodiment echoes may be adaptively extracted one-by-one from the received signal, after removing the interference caused by the previously detected, i.e. stronger, targets, thus realizing a form of CLEAN algorithm. The CLEAN algorithm is a computational algorithm used for example to perform a deconvolution on images created in the field of radio astronomy. In addition, in order to improve accuracy of Doppler measurements, the processed data samples may span multiple packets. However, this may rule out the use of the SLS, since one CPHY packet per sector is transmitted during the SLS.

Therefore, an exemplary embodiment using the IEEE 802.1 lad standard may utilize the data transmission interval, DTI. During the DTI, a sequence of SCPHY packets may be exchanged for example between a source node and a destination node. SCPHY packets may enable low-complexity and energy-efficient transceiver implementations. The source node may be a device comprising a transmitter, TX, and a receiver, RX. The source node may be, for example, an access point or a terminal device. The destination node may be a device comprising a transmitter, TX, and a receiver, RX. The destination node may be, for example, an access point or a terminal device. The transmissions occurring in the DTI may be directional, hence sensing a small sector illuminated by the antenna beam of the source node. Terminal devices with sensing capability may periodically report the list of detected objects for example to an access point, in order to create and maintain a global map of the area. An access point may be a device that allows other wireless devices, for example terminal devices, to connect to a network.

The DTI may comprise contention-based access periods, CBAP, and scheduled service periods, SP, as specified for example by an access point. Access periods may be used by a source node, for example an access point or a terminal device, to send an SCPHY packet to a destination node. It should be noted that different access periods may be used by different source nodes. A number of SCPHY packets may be sent by a source node to the same destination node during the same number of access periods, which may or may not be consecutive. If the source node supports full-duplex operations, these signals may be used to sense the illuminated angular sector.

It should be noted that various exemplary embodiments are not limited to using SCPHY or CPHY packets, as any physical packet of the IEEE 802.1 lad standard may be used by some exemplary embodiments. It should also be noted that various exemplary embodiments are not limited to the IEEE 802.1 lad standard, as some exemplary embodiments may use data packets of other current or future communication standards. For example, IEEE 802.1 lay may be used by some exemplary embodiments instead of IEEE 802. Had.

In addition, it should be noted that the opportunistic sensing performed in the SLS and in the DTI may not be mutually exclusive, but may be complementary in some exemplary embodiments. In an exemplary embodiment, a CPHY packet may be transmitted during the SLS phase and an echo generated by the CPHY packet may be leveraged in order to detect one or more targets and thus periodically get a rough map of the surrounding environment. Then subsequent SCPHY packet transmissions in the DTI may be employed to confirm and/or refine the previously detected targets, thus realizing a form of alert-confirm detection, which may also be referred to as two-step sequential detection, as well as to measure the range-rate of the detected targets. The alert-confirm procedure may also be facilitated by reserving some access periods of the DTI to send dummy SCPHY packets towards those directions that have generated an alert during the SLS. The transmission of dummy signals may be done when the system is idle, but it may also be feasible in the presence of active links, as the consequent throughput loss remains under the control of the source node and may be dynamically adjusted based on the requested services.

A packet at a physical layer of the IEEE 802.1 lad standard, for example an SCPHY packet or a CPHY packet, may comprise at least a preamble, a header, and a payload. Optionally, a packet may also comprise a training field used for optimizing beamforming settings. The payload may be used to transmit actual data with different modulation and coding schemes, and the payload may be protected by a cyclic redundancy check. The header may comprise information such as the modulation and coding scheme used for the payload, the length of the data field, and/or a checksum. FIG. 2 illustrates a preamble of an SCPHY packet in the IEEE 802. Had standard. The preamble may be formed by the concatenation of a pair of Golay complementary sequences of length K _g = 128, for example G _a and Gb in FIG. 2. Overall, the preamble may comprise K _P = 3328 symbols, grouped in the short training field, STF, and channel estimation field, CEF, which may be modulated by using a tt/2-binary phase shift keying, BPSK, mapping. The header field may carry 64 control bits, which specify the structure of the rest of the packet. These control bits may be scrambled, padded with zeros, encoded by using a systematic low- density parity-check code, and modulated by using a tt/2-BPSK mapping, resulting in two blocks of 448 symbols. A block may be prepended by a guard interval comprising a known sequence of 64 tt/2-BPSK symbols. Finally, the payload may carry a number of information bits variable from 1 to 262143 bytes. Information bits may be scrambled, padded with zeros, encoded, modulated, and separated by guard intervals, as specified in the header field. For example, 16 different modulation and coding schemes may be supported. In an exemplary embodiment, the baseband signal sent by the source node towards the angular sector F may be written as: where T is the transmit power, T is the symbol interval, Ψ _tx is a unit-energy causal pulse, and is the waveform corresponding to the /- th SCPHY packet, which starts at time instant Ti and comprises the unit-energy symbols

FIG. 3 illustrates the baseband spectrum mask of the IEEE 802. Had standard. The standard may specify the symbol rate as 1/G = 1760 MHz, for example. The one-sided effective bandwidth of the baseband signal may be approximately W = 1/(2T). It may be assumed in the following that ip _tx (_t ) has support in [0, T _f, tx] and complies with the given spectrum mask.

An echo may be a reflected signal generated by a transmitted packet being reflected from a reflecting object, i.e. target. An echo may comprise information on the location and distance of the target. Echoes may come from any target in the environment, for example another network device, a wall, a person, a tree, or a car. In some exemplary embodiments, any reverberation from the environment, including surface clutter, may be deemed as a signal to be detected, and there may be no discrimination among scatterers of different nature. Each echo may be generated by a different point-like scatterer, deferring to a possible subsequent stage the task of exploiting some prior knowledge on the inspected area, if any, to associate adjacent detected targets to extended objects, and/or remove ghosts generated by multi-path propagation. An extended object may be a single object for which multiple targets are detected, for example a tree comprising multiple tree branches. A ghost may be defined as a false detection that is not an actual target. For example, a ghost may be a multi-path reflection of an actual target. It may also be assumed that no range/Doppler migration occurs, as the point scatterer is illuminated by . This requirement may pose a constraint on the duration of , for example f. For example, if v _ax and α _max are the maximum radial velocity and acceleration of a prospective scatterer, then range and Doppler migration may be neglected if: where λ ₀ is the carrier wavelength, for example 5 mm, and c is the speed of light. It should also be noted that and are the maximum range and range-rate variation during the illumination time, respectively, while D and are approximately the range and range-rate resolution granted by the transmitted signal, respectively. D _G may equal approximately 17 cm, for example. There may be an inherent trade-off between the maximum radial velocity to be measured and the achievable range-rate resolution. For example, if v _max = 5 m/s and a _max = 0, then it may be beneficial to have « 34 ms in order to avoid range migration, which may imply that D _n » 7 dm/s. If the granted service periods are consecutive and if a packet conveys 2000 bytes of information, then Ki = ... = K _L = K = 28992 and = LKT with L« 2069.

FIG. 4 illustrates examples of echoes generated by transmitted packets according to an exemplary embodiment. Under the above assumptions, the received baseband signal may be modeled as: where: is the unknown number of echoes generated by , with Pmax being an upper bound to the number of prospective echoes; are the amplitude, delay, and Doppler shift of the p- th echo generated by (t), for p = 1, ... , P, where Vmax, and are the maximum Doppler shift and the minimum and maximum delay of a prospective echo, respectively, and α _p is a function of the two-way antenna gain, the two-way channel response, and the radar cross section, RCS, of the scatterer causing the reflection; i(t) accounts for the other echoes, if any, that are generated by the SCPHY packets transmitted during the other access periods of the DTI; is a circularly-symmetric complex Gaussian process, independent of the received echoes accounting for the thermal noise, and, possibly, the residual interference after self- interference cancellation, and weather clutter, if any. Its autocorrelation function is , where () ^* denotes the complex conjugate operation. The thermal noise, also known as Johnson-Nyquist noise, is the electronic noise generated as a result of thermal agitation of charge carriers, for example electrons, within an electrical conductor. Self-interference cancellation is a signal processing technique, which may be used to remove self-interference caused by a radio transmitter to a receiver comprised in the same device. However, some residual interference may remain after self-interference cancellation. Weather clutter may comprise unwanted echoes caused by weather phenomena, for example rain or snow.

The signal may be sent to a low-pass causal linear time-invariant filter with an impulse response ψp _rx (t) to remove the out-of-bandwidth noise. For example, this may be a filter matched to the transmitted baseband pulse. In the following, it may be assumed that ψp _rx (t) has support in [0, \. Let * denote the mathematical convolution operation. The filtered signal may be written as: where:

It should be noted that the following approximation has been used in the above formula: which follows from having an effective duration of approximately 1/W with v _p « W.

FIG. 5 illustrates a processing interval Di of an exemplary embodiment. The processing interval may be set as desired. The portion of r(t) falling in the time intervals for l = 1, as shown in FIG. 5, is elaborated in the following. It may be assumed that where is the maximum traveling time of an echo that is generated by an SCPHY packet transmitted in the DTI and, after possibly being reflected by a scatterer, is received by the source node under analysis. This may imply that only the echoes generated by fall in Du It may also be assumed that T. This may imply that the portion of an echo generated by and falling in Di comprises the data symbols from the preamble. Consequently, it may be written that: where:

The above assumptions together may imply that for all Doppler shifts of interest, it follows that exp exp for t E D _t . Hence:

The continuous-time signal r(t) maybe sampled at time instants + ( mi — 1)T _c formι = I, .,.,Mi and l = 1, where is the number of data samples taken in Di ,and T _c ³ 0 is the sampling interval.

Let () ^t denote the transpose operation. After collecting the samples in Di into the vector , the following discrete-time model may be obtained: where: and:

Let Q denote the mathematical Hadamard product operation, also known as elementwise product; let () ^H denote the conjugate transpose operation; let 1 _d denote a d- dimensional vector with all one entries; let r = vec{r ₁ ... ,r _L } be the M-dimensional column vector with M = , obtained by stacking up the column vectors r ₁ ...,r _L . Then, r may be expressed as follows: where x(v _p , t _r ) is the signature vector of an echo hitting the radar receiver with a delay T _p and a Doppler shift v _p , which may be expanded as follows: where: is the Doppler signature, also known as the Doppler steering vector, and = ^vec {g ₁ (τ _p ) _> — _> g _L (t _P )} i ^s the delay signature. Also, w = vec{w ₁ , ... , w _L } is a circularly symmetric complex Gaussian vector counting for the overall disturbance with covariance matrix: where: and: for denoting the autocorrelation function of overall disturbance.

The following pseudo-code algorithm describes an exemplary embodiment, wherein an iterative adaptive process may be used to attempt to extract and detect the prospective echoes one-by-one from the received signal, after removing interference from previously detected targets:

1. Set g based on the desired P^ _a = Pr(reject H ₀ under H ₀ )

2. Set and = 0

3. for p = l, ..., P _max do

4.

5. then

6. P = P + 1

7.

8. Update the search set

9. else

10. break

11. end if

12. end for

13. The number of detected targets is ; if 1, the estimated amplitudes, delays, and Doppler shifts are

In the above algorithm, Q is the feasible search region in the delay-Doppler domain. In practice, this continuous set may be approximated by a discrete set. For example, we can use a uniformly spaced grid: where A _g and Q _g are the quantization step sizes in the delay and Doppler domain, i.e. tied to the delay and Doppler resolution, respectively, and ·

In the above algorithm, the scoring metric M _tn (r ) is defined as where: and: and ε _n and θ _n are independent random variables with a uniform distribution in [—E _n , E _n \ and , respectively. are positive design parameters accounting for the inherent localization errors at the previous steps of the algorithm. A possible choice suggested by Cramer-Rao bound analysis may be: where λ _n is a tuning parameter proportional to , taking into account that a smaller estimation error may occur if the estimated signal-to-interference-plus-noise ratio, S1NR, is larger. Since a target is declared as detected only if g, it may be beneficial to set An proportional to the detection threshold g.

It should be noted that the detection threshold may be chosen to get a desired probability of a false alarm, which may be defined as: where H ₀ is the hypothesis that no echo is present, i.e. P = 0.

FIG. 6 illustrates a flow chart according to an exemplary embodiment, wherein an opportunistic radar system may be at a collocated receiver for detecting an unknown number of echoes and estimating their parameters, i.e. amplitude, delay, and Doppler shift. In S 6.1, the probability of a false alarm P _a , the feasible search set Q, the noise covariance matrix C _w , and the received vector r are received as input to the system. The vector r comprises samples of the received continuous-time signal r(t). Then in S 6.2, the iteration counter p is set as zero, the number of detected targets P is set as zero, and the detection threshold g is computed based on the input P _a . The value of g as a function of Pf _a may have been previously obtained by using for example numerical or experimental data.

In S 6.3, the iteration counter p is incremented by one, i.e. p = p + 1, and the scoring metric for the delay and Doppler shift pairs (t, v) in the feasible search set _p is computed for example with:

The scoring metric may be regarded as the squared magnitude of the output of an interference-plus-noise whitening matched filter normalized by the average interference- plus-noise power at the output of such a filter.

Next, in S 6.4, estimates of Doppler shift and delay are computed for example with:

In S 6.5, it is determined whether the test statistic is greater than the detection threshold, i.e., > g. If the test statistic is greater than the detection threshold (S 6.5: yes), then in S 6.51 a target is declared as detected and the number of detected targets is therefore increased by 1, i.e. P = P + 1. In addition, the estimated delay and Doppler shift corresponding to the detected target may be computed from the location of the maximum of the scoring metric M _tn (r), and an estimate of the target amplitude _p may be computed for example with:

Next, in S 6.52, the search set is updated for example by setting: which amounts to removing from the feasible search set all delay and Doppler shift pairs that are substantially close to the estimated delay and Doppler shift of the newly detected target. After S 6.52, the process returns to S 6.3 and continues from there as described previously.

If the test statistic is not greater than the detection threshold in S 6.5 (S 6.5: no), then the process continues to S 6.6, wherein the number of detected targets is given as output. If the number of detected targets is one or more, i.e., P > 1, then the estimated amplitudes, delays, and Doppler shifts of the targets are also given as output. The process ends after S 6.6.

In an exemplary embodiment, if P > 0, a refined parameter estimation procedure may be used to further improve performance. The following scoring metric may then be calculated for p = 1, ... , P: with which differs from the expression used previously in that all detected targets, except the p-th target, are included in the construction of the interference covariance matrix. A refined estimate of the delay and Doppler shift of the p-th target may now be obtained as follows: where is a small search region around the initial estimate , namely:

The local maximization in may be implemented by using a fine-grid search in _p . Accordingly, a refined estimate of the amplitude of the target may be calculated as follows:

FIG. 7 illustrates a flow chart according to an exemplary embodiment. The steps in FIG. 7 may be executed for example by an apparatus comprising at least a transmitter and a receiver. Such an apparatus may be, for example, a terminal device or an access point. In S 7.1, a plurality of packets are transmitted. For example, mmWaves may be used to transmit a plurality of SCPHY packets during a DTI according to the IEEE 802.1 lad standard. In S 7.2, a signal is received, wherein the received signal comprises one or more echoes generated by the plurality of packets being reflected from one or more targets. The one or more echoes comprise information on the one or more targets that the one or more echoes are reflected from. In step 7.3, the one or more echoes are iteratively extracted one-by-one from the received signal, for example as described previously with regard to FIG. 6. In S 7.4, the one or more targets are detected and localized based at least partly on information obtained from the one or more extracted echoes. For example, the obtained information may comprise estimated parameters, such as delay, Doppler shift and/or amplitude, corresponding with the one or more targets. Herein localization may be understood as estimating a physical location of a target.

Various exemplary embodiments may be used for applications such as, but not limited to, collision avoidance, traffic management, intrusion detection, restricted area surveillance, and patient monitoring. A technical advantage provided by various exemplary embodiments may be that they enable a communication device, such as a terminal device or an access point, to be used as a radar, and therefore there may be no need for a separate/dedicated radar device. For example, various exemplary embodiments may enable to measure range, Doppler frequency and/or velocity of a target. In addition, various exemplary embodiments may improve accuracy of detecting and localizing multiple targets, as well as accuracy of Doppler measurement. Various exemplary embodiments may also improve accuracy of estimating the target amplitude. Various exemplary embodiments may help the communication transmitter to track the destination nodes, whereby future communication protocols may exploit this feature to reduce the signalling overhead.

FIG. 8 illustrates an apparatus 800, which may be an apparatus such as, or comprised in, a terminal device, according to an exemplary embodiment. The apparatus 800 comprises a processor 810. The processor 810 interprets computer program instructions and processes data. The processor 810 may comprise one or more programmable processors. The processor 810 may comprise programmable hardware with embedded firmware and may, alternatively or additionally, comprise one or more application specific integrated circuits, ASICs.

The processor 810 is coupled to a memory 820. The processor is configured to read and write data to and from the memory 820. The memory 820 may comprise one or more memory units. The memory units may be volatile or non-volatile. It is to be noted that in some exemplary embodiments there may be one or more units of non-volatile memory and one or more units of volatile memory or, alternatively, one or more units of non-volatile memory, or, alternatively, one or more units of volatile memory. Volatile memory may be for example RAM, DRAM or SDRAM. Non-volatile memory may be for example ROM, PROM, EEPROM, flash memory, optical storage or magnetic storage. In general, memories may be referred to as non-transitory computer readable media. The memory 820 stores computer readable instructions that are execute by the processor 810. For example, non-volatile memory stores the computer readable instructions and the processor 810 executes the instructions using volatile memory for temporary storage of data and/or instructions.

The computer readable instructions may have been pre-stored to the memory 820 or, alternatively or additionally, they may be received, by the apparatus, via electromagnetic carrier signal and/or may be copied from a physical entity such as computer program product. Execution of the computer readable instructions causes the apparatus 800 to perform functionality described above.

In the context of this document, a "memory" or "computer-readable media" may be any non-transitory media or means that can contain, store, communicate, propagate or transport the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer.

The apparatus 800 further comprises, or is connected to, an input unit 830. The input unit 830 comprises one or more interfaces for receiving a user input. The one or more interfaces may comprise for example one or more motion and/or orientation sensors, one or more cameras, one or more accelerometers, one or more microphones, one or more buttons and one or more touch detection units. Further, the input unit 830 may comprise an interface to which external devices may connect to.

The apparatus 800 also comprises an output unit 840. The output unit comprises or is connected to one or more displays capable of rendering visual content such as a light emitting diode, LED, display, a liquid crystal display, LCD and a liquid crystal on silicon, LCoS, display. The output unit 840 may comprise two displays to render stereoscopic visual content. One display to render content to the left eye and the other display to render content to the right eye. The output unit 840 may further comprise a transmission unit, such as one or more waveguides or one or more lenses, to transfer the rendered visual content to the user’s field of view. The output unit 840 further comprises one or more audio outputs. The one or more audio outputs may be for example loudspeakers or a set of headphones.

The apparatus 800 may further comprise a connectivity unit 850. The connectivity unit 850 enables wired and/or wireless connectivity to external networks. The connectivity unit 850 may comprise one or more antennas and one or more receivers that may be integrated to the apparatus 800 or the apparatus 800 may be connected to. The connectivity unit 850 may comprise an integrated circuit or a set of integrated circuits that provide the wireless communication capability for the apparatus 800. Alternatively, the wireless connectivity may be a hardwired application specific integrated circuit, ASIC.

It is to be noted that the apparatus 800 may further comprise various components not illustrated in FIG. 8. The various components may be hardware components and/or software components.

The apparatus 900 of FIG. 9 illustrates an exemplary embodiment of an apparatus that may be an access point or comprised in an access point. The apparatus may be, for example, a circuitry or a chipset applicable to an access point to realize the described exemplary embodiments. The apparatus 900 may be an electronic device comprising one or more electronic circuitries. The apparatus 900 may comprise a communication control circuitry 910 such as at least one processor, and at least one memory 920 including a computer program code (software) 922 wherein the at least one memory and the computer program code (software) 922 are configured, with the at least one processor, to cause the apparatus 900 to carry out any one of the exemplary embodiments of the access point described above.

The memory 920 may be implemented using any suitable data storage technology, such as semiconductor-based memory devices, flash memory, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory. The memory may comprise a configuration database for storing configuration data.

The apparatus 900 may further comprise a communication interface 930 comprising hardware and/or software for realizing communication connectivity according to one or more communication protocols. The communication interface 930 may provide the apparatus with radio communication capabilities. The communication interface may, for example, provide a radio interface to terminal devices. The apparatus 900 may further comprise another interface towards a core network such as a network coordinator apparatus and/or to access node(s) of a cellular communication system. The apparatus 900 may further comprise a scheduler 940 that is configured to allocate resources.

As used in this application, the term "circuitry" may refer to one or more or all of the following: a. hardware-only circuit implementations (such as implementations in only analog and/or digital circuitry) and b. combinations of hardware circuits and software, such as (as applicable): i. a combination of analog and/or digital hardware circuit(s) with software/firmware and ii. any portions of hardware processor(s) with software (including digital signal processor(s)), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions) and c. hardware circuit(s) and or processor(s), such as a microprocessor(s) or a portion of a microprocessor(s), that requires software (e.g., firmware) for operation, but the software may not be present when it is not needed for operation.

This definition of circuitry applies to all uses of this term in this application, including in any claims. As a further example, as used in this application, the term circuitry also covers an implementation of merely a hardware circuit or processor (or multiple processors) or portion of a hardware circuit or processor and its (or their) accompanying software and/or firmware. The term circuitry also covers, for example and if applicable to the particular claim element, a baseband integrated circuit or processor integrated circuit for a mobile device or a similar integrated circuit in server, a cellular network device, or other computing or network device.

The techniques and methods described herein may be implemented by various means. For example, these techniques may be implemented in hardware (one or more devices), firmware (one or more devices), software (one or more modules), or combinations thereof. For a hardware implementation, the apparatus (es) of exemplary embodiments may be implemented within one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), graphics processing units (GPUs), processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof. For firmware or software, the implementation can be carried out through modules of at least one chipset (e.g. procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in a memory unit and executed by processors. The memory unit may be implemented within the processor or externally to the processor. In the latter case, it can be communicatively coupled to the processor via various means, as is known in the art. Additionally, the components of the systems described herein may be rearranged and/or complemented by additional components in order to facilitate the achievements of the various aspects, etc., described with regard thereto, and they are not limited to the precise configurations set forth in the given figures, as will be appreciated by one skilled in the art.

It will be obvious to a person skilled in the art that, as technology advances, the inventive concept may be implemented in various ways. The embodiments are not limited to the exemplary embodiments described above, but may vary within the scope of the claims. Therefore, all words and expressions should be interpreted broadly, and they are intended to illustrate, not to restrict, the exemplary embodiments.