WO2015192880A1

WO2015192880A1 - Handling radio models

Info

Publication number: WO2015192880A1
Application number: PCT/EP2014/062611
Authority: WO
Inventors: Pavel Ivanov; Jari Syrjärinne; Muhammad Irshan KHAN
Original assignee: Here Global B.V.
Priority date: 2014-06-17
Filing date: 2014-06-17
Publication date: 2015-12-23

Abstract

A positioning method is improved by reducing the number of radio models derived from measured fingerprints by clustering those access points together for which similar radio models could be derived from the measured fingerprints. The clusters are assigned a unique ID. The similar access points are named MIMO device or MIMO group.

Description

Handling Radio Models Field of the Invention

The invention relates to handling radio models for use in radio model-based positioning.

Background to the Invention

Modern global cellular and non-cellular positioning technologies are based on generating large global databases containing information on cellular and non-cellular communication network nodes, e.g. cellular radio network base stations (BSs) or non-cellular radio network, e.g. WLAN (Wi-Fi) access points (APs), and their signals. All such transmitting network nodes can be termed access points or APs. The information may originate entirely or partially from users of these positioning technologies using their mobile terminals acting as data collectors. The data provided by these data collecting mobile terminals is typically in the form of "fingerprints", which contain radio measurement values, i.e. measurements of radio parameters. A fingerprint also comprises, for the radio measurement values from an access point (AP) location information, e.g. obtained based on received satellite signals of a global navigation satellite system (GNSS), and communication network node

identification information identifying a node that is observed by the collector and being associated with the radio measurement values pertaining to that node.

This data is then transferred to a server or cloud, where the data (usually of a multitude of users) may be collected and where a radiomap for positioning purposes may be generated (or updated) based on the data.

In the end, this radiomap may be used for estimating a position, e.g. the position of a mobile terminal. This may function in two modes. The first mode is the terminal-assisted mode, in which the mobile terminal performs the measurements of radio parameters to obtain radio measurement values via a cellular and/ or non-cellular air interface, provides the measurements to a remote server, which in turn, based on the radiomap, determines and provides the position estimate back to the mobile terminal. The second mode is the terminal-based mode, in which the mobile terminal has a local copy of the radiomap (or only a subset of a global radiomap), e.g. downloaded by the mobile terminal from a remote server or pre-installed in the mobile terminal. The actual position estimate may then be obtained based on the radiomap or parts thereof by obtaining identification information of nodes that are observed at the respective position and/or obtaining radio measurement values at that position. Based on the radiomap or parts thereof, properties of a respective node may be modelled. The model may then be used for position estimation. For instance, the coverage area of nodes may be modelled. For each node that is observed at the respective position, the modelled coverage area may be considered and the position estimate may then be the centre of the area of intersection of the coverage area models of all observed nodes. As an alternative to coverage area models (or as an addition allowing more accurate position estimation), also radio channel models (aka radio propagation models) for

communication network nodes may serve as a basis for determining a position based on, for instance, a received signal strength and/or a path loss measured at the respective position. A radio channel model may for instance describe how the power of a signal emitted by a communication network node decays with increasing distance from the communication network, for instance under consideration of further parameters as for instance the radio transmission frequency. Now, if radio channel model information is available for an identified communication network node, for instance if a strength of a signal from this communication network node as received at the respective position (or, as another example, the path loss experienced by this signal) has been measured at that position, an estimate of the distance towards the communication network node can be determined and exploited (e.g. among further information) to determine a position estimate. This specification is concerned primarily with the creation and maintenance of radio models at a server or in the cloud.

It is an aim of embodiments of the invention to reduce the amount of data needed to be stored, used and/or transmitted in maintaining radio models and using radio models in positioning.

Summary Of The Invention

A first aspect of the invention provides apparatus configured to:

store a radio model in respect of each of multiple transmitting devices;

use the radio models to identify transmitting devices that form part of a MIMO device; and following identifying that first and second ones of the multiple transmitting devices form part of a MIMO device:

create a MIMO group for the first and second transmitting devices, and consolidate radio models for the first and second devices into a radio model for the MIMO group.

The apparatus may be configured to use identifiers relating to the transmitting devices and the radio models to identify transmitting devices that form part of a MIMO device. The MIMO group may comprise a MIMO group identifier and the apparatus may be configured to store group identification information comprising the MIMO identifier and identifiers for transmitting devices that are part of the MIMO group.

The apparatus may be configured to cause transmission of the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group.

The apparatus may be configured to use the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group to perform position estimates based on radio parameter information received from a mobile terminal.

The radio models may comprise coverage area models or radio propagation models. The apparatus may be configured to identify that the first and second transmitting devices form part of a MIMO device by identifying that an average of differences between radio models of the first and second transmitting devices falls below a threshold.

The apparatus may be configured to determine that a MIMO group assumption is invalid and, in response, to cease using the consolidated radio model for the MIMO group.

Alternatively, the apparatus may be configured to determine that a MIMO group assumption is invalid and, in response, to separate the MIMO group into individual access points and to create radio models for the individual access points. The apparatus may be configured to consolidate the radio models for the first and second devices into a radio model for the MIMO group by providing a model with averages, for instance a mean or weighted mean or median, of values from the radio models of the first and second devices.

A second aspect of the invention provides a method comprising:

storing a radio model in respect of each of multiple transmitting devices;

using the radio models to identify transmitting devices that form part of a MIMO device; and

following identifying that first and second ones of the multiple transmitting devices form part of a MIMO device:

creating a MIMO group for the first and second transmitting devices, and consolidating radio models for the first and second devices into a radio model for the MIMO group.

The method may comprise using identifiers relating to the transmitting devices and the radio models to identify transmitting devices that form part of a MIMO device.

The MIMO group may comprise a MIMO group identifier and the method may comprise storing group identification information comprising the MIMO identifier and identifiers for transmitting devices that are part of the MIMO group.

The method may comprise causing transmission of the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group.

The method may comprise using the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group to perform position estimates based on radio parameter information received from a mobile terminal.

The radio models may comprise coverage area models or radio propagation models.

The method may comprise identifying that the first and second transmitting devices form part of a MIMO device by identifying that an average of differences between radio models of the first and second transmitting devices falls below a threshold.

The method may comprise determining that a MIMO group assumption is invalid and, in response, ceasing using the consolidated radio model for the MIMO group. The method may comprise determining that a MIMO group assumption is invalid and, in response, separating the MIMO group into individual access points and creating radio models for the individual access points.

The method may comprise consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with averages, for instance a mean or weighted mean or median, of values from the radio models of the first and second devices.

The method may comprise consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with most recently recorded values or maximum values from the radio models of the first and second devices. The invention also provides a computer program comprising machine readable instructions that when executed by computing apparatus causes it to perform any method above.

A third aspect of the invention provides a non-transitory computer-readable storage medium having stored thereon computer-readable code, which, when executed by computing apparatus, may cause the computing apparatus to perform a method comprising:

storing a radio model in respect of each of multiple transmitting devices;

The computer-readable code when executed may cause the computing apparatus to perform: using identifiers relating to the transmitting devices and the radio models to identify transmitting devices that form part of a MIMO device.

The MIMO group may comprise a MIMO group identifier and the computer-readable code when executed may cause the computing apparatus to perform: storing group identification information comprising the MIMO identifier and identifiers for transmitting devices that are part of the MIMO group.

The computer-readable code when executed may cause the computing apparatus to perform: causing transmission of the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group.

The computer-readable code when executed may cause the computing apparatus to perform: using the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group to perform position estimates based on radio parameter information received from a mobile terminal.

The radio models may comprise coverage area models or radio propagation models. The computer-readable code when executed may cause the computing apparatus to perform: identifying that the first and second transmitting devices form part of a MIMO device by identifying that an average of differences between radio models of the first and second transmitting devices falls below a threshold. The computer-readable code when executed may cause the computing apparatus to perform: determining that a MIMO group assumption is invalid and, in response, ceasing using the consolidated radio model for the MIMO group.

The computer-readable code when executed may cause the computing apparatus to perform: determining that a MIMO group assumption is invalid and, in response, separating the MIMO group into individual access points and creating radio models for the individual access points.

The computer-readable code when executed may cause the computing apparatus to perform: consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with averages, for instance a mean or weighted mean or median, of values from the radio models of the first and second devices.

The computer-readable code when executed may cause the computing apparatus to perform: consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with most recently recorded values or maximum values from the radio models of the first and second devices. A fourth aspect of the invention provides apparatus having at least one processor and at least one memory having computer-readable code stored thereon which when executed controls the at least one processor to perform:

storing a radio model in respect of each of multiple transmitting devices;

The computer-readable code when executed may cause the at least one processor to perform: using identifiers relating to the transmitting devices and the radio models to identify transmitting devices that form part of a MIMO device.

The MIMO group may comprise a MIMO group identifier and the computer-readable code when executed may cause the at least one processor to perform: storing group

identification information comprising the MIMO identifier and identifiers for transmitting devices that are part of the MIMO group.

The computer-readable code when executed may cause the at least one processor to perform: causing transmission of the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group.

The computer-readable code when executed may cause the at least one processor to perform: using the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group to perform position estimates based on radio parameter information received from a mobile terminal.

The radio models may comprise coverage area models, or radio propagation models.

The computer-readable code when executed may cause the at least one processor to perform: identifying that the first and second transmitting devices form part of a MIMO device by identifying that an average of differences between radio models of the first and second transmitting devices falls below a threshold. The computer-readable code when executed may cause the at least one processor to perform: determining that a MIMO group assumption is invalid and, in response, ceasing using the consolidated radio model for the MIMO group.

The computer-readable code when executed may cause the at least one processor to perform: determining that a MIMO group assumption is invalid and, in response, separating the MIMO group into individual access points and creating radio models for the individual access points.

The computer-readable code when executed may cause the at least one processor to perform: consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with averages, for instance a mean or weighted mean or median, of values from the radio models of the first and second devices.

The computer-readable code when executed may cause the at least one processor to perform: consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with most recently recorded values or maximum values from the radio models of the first and second devices.

Other features of the present invention will become apparent from the following detailed description considered in conjunction with the accompanying drawings. It is to be understood, however, that the drawings are designed solely for purposes of illustration and not as a definition of the limits of the invention, for which reference should be made to the appended claims. It should be further understood that the drawings are not drawn to scale and that they are merely intended to conceptually illustrate the structures and procedures described herein.

Brief Description Of The Figures

Embodiments of the invention will now be described, by way of example only, with reference to the accompanying figures, in which:

Figure l is a schematic illustration of a positioning system in which example embodiments of the present invention may be employed;

Figure 2 is a flow chart illustrating operation of a server of the Figure l system according to various embodiments;

Figure 3 is a block diagram of a details of the server shown in Figure l according to embodiment of the invention; and

Figure 4 is a schematic illustration of examples of tangible storage media according to embodiments of the present invention.

Detailed Description of Embodiments of the Invention

In brief, embodiments of the invention involve a server, that may be discreet or may be part of cloud infrastructure, identifying radio models of access points that are the same or sufficiently similar to indicate that the access points form part of a MIMO group of access points, consolidating the radio models for the access points of the MIMO group, and using the consolidated radio models in place of the radio models for the individual access points that form the MIMO group. This involves the server identifying substantially identical radio models, that is where the access points provide substantially the same radio footprint, and consolidating radio models for such access points. Access points with substantially identical radio models typically are part of a common multiple input multiple output (MIMO) device, such as an IEEE 802.1m router. Consolidation occurs by allocating the co-located access points to a MIMO group, and providing a radio model for the group as a whole instead of for each of the members of the group individually. This can allow radio models to be created from which positioning can be performed with the same accuracy as would be achievable in the corresponding arrangement in which radio models were used for each access point instead of for MIMO groups, however without requiring as much memory space to store the radio models nor as much bandwidth to transmit the radio models.

In the embodiments, the server uses identifiers of the APs, as determined from the transmissions from the APs and relayed by surveying devices, to identify candidate MIMO groups. Candidate MIMO groups are then verified using radio models constructed from signals received from the APs. For verified MIMO groups, radio models are consolidated. This can provide reliable detection of access points that do form part of actual MIMO groups whilst requiring relatively little data processing.

Figure l shows a positioning system 100, in which embodiments of the present invention may be employed. In Figure l, mobile terminal 120 is capable of identifying nodes 131, 132 and 133 of one or more communication networks. Each of nodes 131, 132 and 133 constitutes an access point and provides radio coverage in a respective coverage area 161, 162 and 163. As just one possible example, the node 131 may be a WLAN AP, node 132 may be a BS of an LTE cellular network and node 133 may be a UMTS Node B. Each of the nodes 131, 132 and 133 transmits node identification information identifying the respective node. The identification information may comprise an identifier. Namely, WLAN AP 131 may transmit a MAC identifier, BS 132 an LTE Cell Identity and UMTS Node B 133 transmits a UTRAN Cell ID (UC-ID).

A MIMO node 137 comprises three access points 134-136. The nodes 134-136 form part of the same MIMO device, for instance an 802.1m router device. Each access point 134-136 may be associated with a respective antenna. The antennas may be separated by a relatively small distance (typically no more than a few tens of centimetres) and thus the access points 134-136 are co-located. The MIMO node 137 provides radio coverage in a coverage area 164. This can be considered to be a common coverage area 164, although in actuality each access point 134-136 has its own coverage area and there may be slight differences between them because of the slightly different locations of the antennas and because of the slightly different environments in which the different antennas are located. Each access point 134-136 in the MIMO node 137 transmits a different identifier, for instance MAC identifier or MAC address.

Mobile terminal 120 comprises several communication interfaces. It inter alia comprises a WLAN interface, an LTE interface and a UMTS interface. By means of these interfaces, the mobile terminal 120 is capable of receiving the MAC identifier, the LTE Cell Identity and the UC-ID. At server 140 of system 100, radiomap datasets (RMDSs) are stored. Each RMDS comprises radio measurement values of a radio parameter. The radio measurement values have been previously measured by mobile terminals such as mobile terminal 120 and have then been reported to server 140.

The server 140 uses the RMDSs to calculate radio channel models for each of the nodes 131, 132 and 133 or only some of these nodes based on one or several of the stored RMDSs. The calculated radio channel models are then stored for use in positioning. Positioning can be performed by the server 140 or it can be performed by the mobile terminal 120 based on radio models sent by the server 140 to the mobile terminal 120. The radio models are stored at the server 140 so that they may be ready for access when a mobile terminal 120 request a position estimate or requests radio models. When a mobile terminal (such as mobile terminal 120) does not have GNSS capabilities, or does not want to use these capabilities or demands position information in addition to position information obtained by means of GNSS signals, a positioning request may be provided to server 140. The server that calculates the models and the server to which actual radio measurement values have been provided for generating RMDSs may be different entities. If they are different entities, they may be termed a server system. The servers of the server system may be located proximally or they may be remote to each other. In the following, references to a server or to the server 140 will be understood to be references to a single server or to a server system unless otherwise stated.

Figure 2 is a flow chart illustrating a method according to the embodiments of the invention. The method steps of the flow chart of Figure 2 are performed by the server 140, such as the server that is depicted in Figure 13 and which is explained later in this specification.

Operation of the server 140 will now be described with reference to Figure 2.

The operation starts at step 200. At step 200, the server 140 maintains a database of fingerprints. The fingerprints are data that has been collected by mobile terminals, such as the mobile terminal 120, and includes information that can be used by the server 140 to create a radio maps and/or radio models. In particular, the fingerprints include data that indicates a location, an identifier relating to an access point, and radio parameter data, such as an RSS measurement. The location indicates a location at which the RSS measurement was performed, and the identifier identifies the transmitting device (access point) from which the radio signal having the corresponding RSS measurement was transmitted. The fingerprints may additionally include other information, such as an identification of the mobile terminal 120 that created the fingerprint data and/or a time at which the fingerprint data was created by the mobile terminal 120 or was received at the server 140 from the mobile terminal 120. The identifiers that form part of the fingerprint data uniquely or pseudo-uniquely identify the transmitting access point. For instance, the identifier may be a MAC address or similar. Equally well, a node of a communication network may for instance have an identifier that is not unique (e.g. only locally unique) in the communication network, but that is at least unique in a subregion of the region covered by the communication network. The identifier of the node may for instance be a cell identifier. Examples of as cellular cell identifiers include e.g. a Mobile Country Code (MCC), a Mobile Network Code (MNC), a Local Area Code (LAC) and/or a Cell Identity (CID) in case of coverage areas of a 2G mobile communications system, a UTRAN Cell ID (UC-ID) in case of a 3G mobile communications system, or an LTE Cell Identity in case of a 4G communications system. Examples of non-cellular identifiers include identifiers of WLAN access points (e.g. a basic service set identification (BSSID), like a medium access control (MAC) identifier of a WLAN access point or a service set identifier (SSID)).

The radio measurement values may take any suitable form. For instance, the

measurement parameter may be an RSS, e.g. measured in dBm, for instance with a reference value of 1 mW, with or without the Doppler effect being averaged out therein.

The fingerprints are stored in a fingerprint database 921 that is shown in Figure 3. It will be appreciated that the database of fingerprints that is maintained at step 201 may be quite large. It includes fingerprint data from potentially a large number of mobile terminals, and for each mobile terminal there may be fingerprint data for many different locations. Additionally, there may be fingerprint data from a given mobile terminal for the same location at different instances in time. Depending on the geographical area that is covered by the database of fingerprints, the database may contain thousands, tens of thousands, hundreds of thousands or millions of records. The server 140 may be configured to maintain the database in any suitable way. For instance, the server 140 may delete fingerprint records that are relatively old. Additionally or alternatively, the server 140 may delete fingerprint records that are not useful on the basis that the database includes sufficient numbers of records for the relevant locations. At step 202, radio models for the access points that are referenced in the fingerprint database are created. This may be performed in any suitable way. The creation of the radio models from the fingerprint data may involve the intermediate step of creating radio maps. If radio maps are created as an intermediate step in creating radio models, the radio maps may be stored in the server 140 in place of the database of fingerprints.

The resulting radio models are stood in a radio model database 922, which is shown in Figure 3.

The result of performance of step 202 is the provision of a radio model for each of the multiple access points that are able to be modelled satisfactorily from the database of fingerprints. A radio model or radio map for a given access point typically is different from the radio models of the other access points. An exception, however, is when the access points form part of a MIMO device. In step 203, the server 140 identifies MIMO groups in the modelled access points. In brief, the server 140 identifies radio models that are substantially the same as each other and for which the access points have identifiers that are sufficiently close to indicate that they form part of a single MIMO device. Step 203 may result in multiple MIMO groups being identified in the radio models.

To identify a MIMO group, the server 140 first selects a next access point, for which a radio model has been created. On the first performance of this step, this results in the first access point being selected. On subsequent executions of the step, different access points are selected. The radio models here are ones that have been stored in the radio model database 922 of the server 140.

Next the server 140 determines whether the MAC address for the selected access point selected indicates that there is a candidate MIMO group or there are candidate MIMO groups in the radio model database 922. This is achieved by the server 140 comparing the MAC addresses of the access points that are included in the radio model database 922 with each other. Where the MAC addresses for two access points are very similar, and for instance fall within 8 or F (in hexadecimal) from one another, it is determined that the MAC addresses indicate a candidate MIMO group. This may result in a determination that there are more than two access points that are candidates for a single MIMO group, for instance because the MAC addresses of the multiple access points have values that differ by no more than 8 or F. This may also result in a determination that there are multiple candidate MIMO groups in the radio model database 922. Here, first and second access points may have MAC addresses with values that are separated by a small value and third and fourth access points may have MAC addresses that are separated by a small value but are separated from the MAC addresses of the first and second access points by a larger value.

In this example, three access point identifiers are separated by a small amount, for instance with values oo:aa:bb:cc:do, oo:aa:bb:cc:di and oo:aa:bb:cc:d2, and these identifiers relate to the access points 134, 135 and 136 that together form the MIMO group 137. In this example, all other access point identifiers are separated from each other by at least 8 or F.

Next the server 140 determines whether there are further access points for which radio models are stored in the radio model database 922 and that have not yet been processed. If there are further radio models that are determined not to have been processed, the operation returns to select the next radio model for processing.

Once it is determined that there are no further access points to check, and that candidate MIMO groups for all of the access points have been identified, the operation proceeds to attempt to validate the candidate MIMO groups.

This is achieved by comparing the radio models for the access points and calculating a degree of similarity of the radio models. A higher degree of similarity results where there is a large correlation between the radio models for the access points. The closeness of the MAC address (in terms of the difference between the values of the MAC addresses for the access points) is not used in determining the probability that the access points are in the same MIMO groups, although in other embodiments the MAC addresses may be so used.

The calculation of a degree of similarity of the radio models many include consideration of the calculated transmit power of the separate radio models. The same or similar transmit powers is indicative of a high degree of similarity. If the calculated transmit powers are significantly different (by more than a threshold amount or proportion), a determination of a low degree of similarity may be made.

The calculation of a degree of similarity of the radio models many include consideration of the measured frequencies of transmission of the separate radio models. The same or similar transmit frequencies is indicative of a high degree of similarity. If the measured frequencies are significantly different (by more than a threshold amount or proportion), a determination of a low degree of similarity may be made. The calculation of a degree of similarity of the radio models many include consideration of the determined locations of the transmitters, which often is the centre of the coverage areas of the separate radio models. The same or similar location is indicative of a high degree of similarity. If the calculated locations are significantly different (by more than a threshold amount or proportion), a determination of a low degree of similarity may be made.

An example equation for determining that the access points are in the same MIMO group will now be described. The radiomodels {RM RNP) from APs i andj are considered the same (from the same MIMO group) if the average (probability) of the absolute RSS-differences in the radiomodels CRM^1', RNP) among the occupied radiomodel grid nodes is smaller than a predefined threshold dRM_MIMO:

dRM_ABS = l/Nx [SUM^RM^k)- RM>(k) \), k = i...N] < dRM_MIMO where:

N number of occupied grid nodes in the both radiomodels for APs z and j BM^k) the k h co-located and occupied RM grid node with an estimated/ measured value of the Received Signal Strength (RSS).

N typically is much greater than 1 (e.g. more than 50) in order to have enough

measurements to calculate the radiomodel similarity. The average can also be calculated as the mean of squared differences, root mean square, weighted mean (if some grid nodes are considered more valuable than others) etc.. If one or more MIMO groups are identified, the MIMO groups are stored in a MIMO group database 923 in the server 140. The result of the performance of step 402 by the mobile terminal 120 is a number of MIMO groups, each of which indicates multiple access points (by indicating their MAC addresses). For each identified MIMO group, MIMO group data is created. The MIMO group data includes an identifier for the MIMO group, which is unique amongst MIMO group identifiers. The MIMO group information also includes a list of the identifiers of the access points that are included in the MIMO group. The MIMO group information thus allows identification of the access points that form part of the MIMO group, and associates those access points with a MIMO group identifier. The MIMO group information for a MIMO group constitutes a record in the MIMO group database 923.

Although in the above the identifiers of the access points (e.g. MAC addresses) are used to identify candidate MIMO groups, in some embodiments the identifiers are not used in the identification of access points that can be grouped into MIMO groups. In these embodiments, the identification of access points that can be grouped into MIMO groups can be made based on radio models alone.

At step 204, the server 140 consolidates the radio models for the access points of the MIMO groups. This can be performed in any suitable way.

In some embodiments, for a given MIMO group, the consolidated radio model is formed by creating a blank model (without RSS values) having the same physical coverage as the union of the individual models, relating to each of the individual access points, and filling the blank model with the mean of the RSS values from the radio models of the individual access points. The resulting radio model is then associated with the MIMO group identifier. This is repeated for each of the other MIMO groups, if there are any others.

Alternatively the consolidated radio model could be formed in a different way. For instance, the consolidated radio model may be formed by filling the blank model with the weighted mean of the RSS values, by filling the blank model with the latest measured RSS values, by filling the blank model with the strongest measured RSS value at the node or by filling the blank model with the median of the RSS values. At step 205, the server 140 stores the consolidated radio models for the MIMO groups and thereby updates the radio model database 922. The updated radio model database 922 includes the consolidated radio models for the access points in the MIMO group and does not include radio models for the specific access points, at least not individually.

Following 205, it is the radio models of the updated radio model database 922 that are used in positioning mobile devices based on RSS measurements. In the case of server- assisted positioning, the updated radio models, representing MIMO groups instead of individual access points where appropriate, is used as follows. On receipt of fingerprint data from a mobile terminal, the identifiers of the access points that are included in the fingerprints are used to scan a database of MIMO groups. Where access points are identified in the MIMO groups, the MIMO group identifier from the corresponding MIMO group is used to look up the radio model for the MIMO group that is stored in the server 140. The radio model for the MIMO group is then used to perform the positioning of the mobile terminal. The use of radio models for MIMO groups in this way reduces the number of radio models that are needed for a given positioning fix of a mobile terminal because the radio model for a MIMO group replaces radio models for two or more access points that form part of the MIMO group. As such, less processing is needed by the server to perform positioning of the mobile terminal that is on the fingerprint data received from the mobile terminal.

In the case where radio models are communicated to the mobile terminals so that the mobile terminals themselves can perform positioning based on fingerprint data created by the mobile terminals during a scan for access points, there is an additional advantage. In particular, the amount of data that is required to communicate the radio models to the mobile terminal is less than in the corresponding case where there are no MIMO groups. In the case where the mobile terminal receives radio models for MIMO groups from the sever 140, the mobile terminal 120 also receives the MIMO group information, including the MIMO group identifier and the identifiers of the access points that form part of the MIMO group, for instance by receiving the records of the MIMO group database 923. However, the MIMO group information requires significantly less data in its

representation than the quantity of data that is required to represent a radio model. As such, there is a significant saving in the amount of data that is required to be

communicated in this instance. Additionally, there is the advantage that the mobile terminal 120 needs to perform less processing in order to calculate its position. In particular, fewer radio models need to be processed in positioning the mobile terminal 120, as is the case when the positioning is performed by the server 140.

In addition to lower utilisation of communication resources, the use of MIMO groups results in a lower memory utilisation, since there is less data that needs to be stored, in the mobile terminal 120.

When the mobile terminal 120 requires to perform positioning based on radio models that are stored locally within the mobile terminal 120, it first performs a scan for access points. In respect of the identifiers for access points whose transmissions are received during the scan, the mobile terminal 120 first searches a database of MIMO group information to identify whether the corresponding access points are included in MIMO groups. For the access points that are included in MIMO groups, the radio models for the MIMO groups are used instead of individual radio models for each access point. For access points for which there is no MIMO group, the radio model for the access point itself is used in positioning the mobile terminal 120.

Referring back to Figure 2, the server 140 is configured to check occasionally that MIMO groups remain valid and to take remedial action when it is detected that MIMO groups are no longer valid.

In particular, in step 206 the server 140 uses new fingerprints, which are newly received from mobile devices, to check the validity of MIMO groups. The validity check involves determining whether the newly received fingerprint data is consistent with the radio models for the corresponding MIMO groups. The fingerprint data can be determined to be consistent with an existing radio models if it has a high degree of correspondence with the radio model. If the degree of correspondence between the new fingerprint data and a radio model for the corresponding MIMO group does not have a suitably high degree of correspondence, then the MIMO group is deemed to be invalid. This can be checked by calculating a measure of the correspondence between the fingerprint data and the radio model and comparing the measure of correspondence to a threshold. If the measure of correspondence is high it exceeds the threshold, and vice versa.

The server checks at step 207 whether MIMO groups are determined to be invalid. On a negative determination, the operation ends at step 209. On a positive determination, the server 140 at step 208 separates the MIMO groups' individual access points. This involves deletion of the MIMO group from the MIMO group database. It also involves the generation of radio models for the individual access points and the updating of the radio model database 922 with the radio models for the individual access points. Radio models for the access points can be created in any suitable way. For instances, they may be created using the MIMO group radio models for access points that are not determined to be inconsistent with the pre-existing MIMO group radio models. For access points for which the pre-existing MIMO group radio models is not consistent with the new fingerprints, new radio models may be created from the new fingerprints. If there is any insufficient data, the server 140 is configured to wait until sufficient data is available before creating a radio models for the access points.

Figure 3 is a schematic diagram of the server 140 according to embodiments of the invention. The server 140 may a single server, a cluster of two or more servers or a system of two or more remote servers or clusters of servers. A server is a computer comprising one or more processors (single core, multi core etc.), one or more volatile memories (RAM, flash memory etc.) and one or more non-volatile memories (SSDs, ROMs, hard disks etc.) and software in the form of one or more computer programs residing permanently in non-volatile memory and being stored at least transiently in volatile memory whilst being executed by the one or more processors. A server typically is nonportable and is powered in on the main part by mains electricity and not by energy stored in a battery. The server may generically be termed 'apparatus'.

The server 140 comprises a processor 960. Processor 960 may represent a single processor or two or more processors, which are for instance at least partially coupled, for instance via a bus. Processor 960 executes a program code stored in program memory 910 (for instance program code causing server 140 to perform one or more of the

embodiments of a method according to the invention (as for instance further described above with reference to the flow charts of Figure 2), when executed on processor 960), and interfaces with a main memory 920. Some or all of memories 910 and 920 may also be included into processor 960. One of or both of memories 910 and 920 may be fixedly connected to processor 960 or at least partially removable from processor 960, for instance in the form of a memory card or stick. Program memory 910 may for instance be a non-volatile memory. Examples of such tangible storage media will be presented with respect to Figure 4 below. It may for instance be a FLASH memory (or a part thereof), any of a ROM, PROM, EPROM and EEPROM memory (or a part thereof) or a hard disc (or a part thereof), to name but a few examples. Program memory 910 may also comprise an operating system for processor 960. Program memory 910 may for instance comprise a first memory portion that is fixedly installed in server 140, and a second memory portion that is removable from the server 140, for instance in the form of a removable SD memory card. Main memory 920 may for instance be a volatile memory. It may for instance be a RAM or DRAM memory, to give but a few non-limiting examples. It may for instance be used as a working memory for processor 960 when executing an operating system and/or programs.

The radio model database 922 is stored in the program memory 910. The fingerprint database 921 is stored in the program memory 910.

The MIMO group database 923 is stored in the program memory 910.

One or more, or all, of the databases 921-923 may alternatively be stored in a separate memory.

Processor 960 may further control a communication interface 930 (or several

communication interfaces) configured to receive and transmit data to the outside world, including to the mobile terminal 120. Processor 960 may further control an optional user interface 940 configured to present information to an administrator of the server 140 and/or to receive information from such n administrator.

The components 910-940 of the server 140 may for instance be connected with processor 960 by means of one or more serial and/or parallel busses.

It is to be noted that the circuitry formed by the components of the server 140 may be implemented in hardware alone, partially in hardware and in software, or in software only, as further described at the end of this specification.

A step performed by the server 140 may preferably be understood such that corresponding program code is stored in memory 910 and that the program code and the memory are configured to, with processor 960, cause the server 140 to perform the step. Equally well, a step performed by the server 140 may preferably be understood such that the server 140 comprises according means for performing this step. When the server 140 performs a method according to the invention, the server may thus be considered as an embodiment of the invention. Likewise, the program memory 910 of the server 140, which may in particular be a non-transitory storage medium, may be considered as an embodiment of the invention if corresponding computer program code (for instance a set of instructions) is stored therein.

Figure 4 schematically illustrates examples of tangible storage media according to the present invention that may for instance be used to implement program memory 910 of Figure 3. To this end, Figure 4 displays a flash memory 1000, which may for instance be soldered or bonded to a printed circuit board, a solid-state drive 1100 comprising a plurality of memory chips (e.g. Flash memory chips), a magnetic hard drive 1200, a Secure Digital (SD) card 1300, a Universal Serial Bus (USB) memory stick 1400, an optical storage medium 1500 (such as for instance a CD-ROM or DVD) and a magnetic storage medium 1600.

Non-limiting examples of communication networks nodes (also denoted simply as nodes herein) are base stations (or sectors thereof) of a cellular communication network, such as for instance a second generation (2G, for instance the Global System for Mobile

Communication (GSM), the General Packet Radio System (GPRS), the Enhanced Data Rates for GSM Evolution (EDGE) or the High Speed Circuit-Switched Data (HSCSD)), third generation (3G, for instance the Universal Mobile Telecommunication System, UMTS, or CDMA-2000) or fourth generation (4G, for instance the Long Term Evolution, LTE, system, the LTE Advanced (LTE-A) system or the IEEE 802.16m WiMAX system) communication network, or an AP or beacon of a non-cellular radio communication network, such as for instance a WLAN network, a Bluetooth system, a Bluetooth Low Energy (BT LE) system, a radio-frequency identification (RFID) system a broadcasting system such as for instance Digital Video Broadcasting (DVB), Digital Audio Broadcasting (DAB) or Frequency-Modulated (FM) / Amplitude-Modulated (AM) radio, a Near Field Communication (NFC) system, etc.). A cellular communication network may for instance be characterised by a basically seamless pavement of a geographical area (usually in the order of at least hundreds or thousands of square kilometres) with cells in which coverage is provided by respective communication network nodes that are operated by the same operator, which network may for instance support communication handover between cells. Consequently, a non-cellular communication network may be characterised as a communication network that does not have all of these properties. Any presented connection in the described embodiments is to be understood in a way that the involved components are operationally coupled. Thus, the connections can be direct or indirect with any number or combination of intervening elements, and there may be merely a functional relationship between the components.

Further, as used in this text, the term 'circuitry' refers to any of the following:

(a) hardware-only circuit implementations (such as implementations in only analog and/or digital circuitry)

(b) combinations of circuits and software (and/or firmware), such as: (i) to a combination of processor(s) or (ii) to portions of processor(s)/ software (including digital signal processor(s)), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone, to perform various functions) and

(c) to circuits, such as a microprocessor(s) or a portion of a microprocessor(s), that require software or firmware for operation, even if the software or firmware is not physically present.

This definition of 'circuitry' applies to all uses of this term in this text, including in any claims. As a further example, as used in this text, the term 'circuitry' also covers an implementation of merely a processor (or multiple processors) or portion of a processor and its (or their) accompanying software and/or firmware. The term 'circuitry' also covers, for example, a baseband integrated circuit or applications processor integrated circuit for a mobile phone.

Any of the processors mentioned in this text, in particular but not limited to processors 960 of Figure 3, could be a processor of any suitable type. Any processor may comprise but is not limited to one or more microprocessors, one or more processor(s) with accompanying digital signal processor(s), one or more processor(s) without accompanying digital signal processor(s), one or more special-purpose computer chips, one or more field-programmable gate arrays (FPGAS), one or more controllers, one or more application-specific integrated circuits (ASICS), or one or more computer(s). The relevant structure/hardware has been programmed in such a way to carry out the described function.

Moreover, any of the actions described or illustrated herein may be implemented using executable instructions in a general-purpose or special-purpose processor and stored on a computer-readable storage medium (e.g., disk, memory, or the like) to be executed by such a processor. References to 'computer-readable storage medium' should be understood to encompass specialised circuits such as FPGAs, ASICs, signal processing devices, and other devices.

It will be understood that all presented embodiments are only exemplary, and that any feature presented for a particular exemplary embodiment may be used with any aspect of the invention on its own or in combination with any feature presented for the same or another particular exemplary embodiment and/or in combination with any other feature not mentioned. It will further be understood that any feature presented for an example embodiment in a particular category may also be used in a corresponding manner in an example embodiment of any other category.

Claims

1. Apparatus configured to:

store a radio model in respect of each of multiple transmitting devices;

use the radio models to identify transmitting devices that form part of a MIMO device; and

2. Apparatus as claimed in claim 1, configured to use identifiers relating to the transmitting devices and the radio models to identify transmitting devices that form part of a MIMO device.

3. Apparatus as claimed in claim 1 or claim 2, wherein the MIMO group comprises a MIMO group identifier and wherein the apparatus is configured to store group

4. Apparatus as claimed in any preceding claim, configured to cause transmission of the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group.

5. Apparatus as claimed in any preceding claim, configured to use the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group to perform position estimates based on radio parameter information received from a mobile terminal.

6. Apparatus as claimed in any preceding claim, wherein the radio models comprise coverage area models.

7. Apparatus as claimed in any of claims 1 to 5, wherein the radio models comprise radio propagation models.

8. Apparatus as claimed in any preceding claim, configured to identify that the first and second transmitting devices form part of a MIMO device by identifying that an average of differences between radio models of the first and second transmitting devices falls below a threshold.

9. Apparatus as claimed in any preceding claim, configured to determine that a MIMO group assumption is invalid and, in response, to cease using the consolidated radio model for the MIMO group.

10. Apparatus as claimed in any of claims 1 to 7, configured to determine that a MIMO group assumption is invalid and, in response, to separate the MIMO group into individual access points and to create radio models for the individual access points.

11. Apparatus as claimed in any preceding claim, configured to consolidate the radio models for the first and second devices into a radio model for the MIMO group by providing a model with averages, for instance a mean or weighted mean or median, of values from the radio models of the first and second devices.

12. Apparatus as claimed in any preceding claim, configured to consolidate the radio models for the first and second devices into a radio model for the MIMO group by providing a model with most recently recorded values or maximum values from the radio models of the first and second devices.

13. A method comprising:

storing a radio model in respect of each of multiple transmitting devices;

14. A method as claimed in claim 13, comprising using identifiers relating to the transmitting devices and the radio models to identify transmitting devices that form part of a MIMO device.

15. A method as claimed in claim 13 or claim 14, wherein the MIMO group comprises a MIMO group identifier and wherein the method comprises storing group identification information comprising the MIMO identifier and identifiers for transmitting devices that are part of the MIMO group.

16. A method as claimed in any of claims 13 to 15, comprising causing transmission of the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group.

17. A method as claimed in any of claims 13 to 16, comprising using the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group to perform position estimates based on radio parameter information received from a mobile terminal.

18. A method as claimed in any of claims 13 to 17, wherein the radio models comprise coverage area models.

19. A method as claimed in any of claims 13 to 17, wherein the radio models comprise radio propagation models.

20. A method as claimed in any of claims 13 to 19, comprising identifying that the first and second transmitting devices form part of a MIMO device by identifying that an average of differences between radio models of the first and second transmitting devices falls below a threshold.

21. A method as claimed in any of claims 13 to 20, comprising determining that a MIMO group assumption is invalid and, in response, ceasing using the consolidated radio model for the MIMO group.

22. A method as claimed in any of claims 13 to 20, comprising determining that a MIMO group assumption is invalid and, in response, separating the MIMO group into individual access points and creating radio models for the individual access points.

23. A method as claimed in any of claims 13 to 22, comprising consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with averages, for instance a mean or weighted mean or median, of values from the radio models of the first and second devices.

24. A method as claimed in any of claims 13 to 23, comprising consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with most recently recorded values or maximum values from the radio models of the first and second devices.

25. A non-transitory computer-readable storage medium having stored thereon computer-readable code, which, when executed by computing apparatus, causes the computing apparatus to perform a method comprising:

storing a radio model in respect of each of multiple transmitting devices;

26. A medium as claimed in claim 25, wherein the computer-readable code when executed causes the computing apparatus to perform: using identifiers relating to the transmitting devices and the radio models to identify transmitting devices that form part of a MIMO device.

27. A medium as claimed in claim 25, wherein the MIMO group comprises a MIMO group identifier and wherein the computer-readable code when executed causes the computing apparatus to perform: storing group identification information comprising the MIMO identifier and identifiers for transmitting devices that are part of the MIMO group.

28. A medium as claimed in claim 25, wherein the computer-readable code when executed causes the computing apparatus to perform: causing transmission of the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group.

29. A medium as claimed in claim 25, wherein the computer-readable code when executed causes the computing apparatus to perform: using the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group to perform position estimates based on radio parameter information received from a mobile terminal.

30. A medium as claimed in claim 25, wherein the radio models comprise coverage area models.

31. A medium as claimed in claim 25, wherein the radio models comprise radio propagation models.

32. A medium as claimed in claim 25, wherein the computer-readable code when executed causes the computing apparatus to perform: identifying that the first and second transmitting devices form part of a MIMO device by identifying that an average of differences between radio models of the first and second transmitting devices falls below a threshold.

33. A medium as claimed in claim 25, wherein the computer-readable code when executed causes the computing apparatus to perform: determining that a MIMO group assumption is invalid and, in response, ceasing using the consolidated radio model for the MIMO group.

34. A medium as claimed in claim 25, wherein the computer-readable code when executed causes the computing apparatus to perform: determining that a MIMO group assumption is invalid and, in response, separating the MIMO group into individual access points and creating radio models for the individual access points.

35. A medium as claimed in claim 25, wherein the computer-readable code when executed causes the computing apparatus to perform: consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with averages, for instance a mean or weighted mean or median, of values from the radio models of the first and second devices.

36. A medium as claimed in claim 25, wherein the computer-readable code when executed causes the computing apparatus to perform: consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with most recently recorded values or maximum values from the radio models of the first and second devices.

37. Apparatus, the apparatus having at least one processor and at least one memory having computer-readable code stored thereon which when executed controls the at least one processor to perform:

storing a radio model in respect of each of multiple transmitting devices;

38. Apparatus as claimed in claim 37, wherein the computer-readable code when executed causes the at least one processor to perform: using identifiers relating to the transmitting devices and the radio models to identify transmitting devices that form part of a MIMO device.

39. Apparatus as claimed in claim 37, wherein the MIMO group comprises a MIMO group identifier and wherein the computer-readable code when executed causes the at least one processor to perform: storing group identification information comprising the MIMO identifier and identifiers for transmitting devices that are part of the MIMO group.

40. Apparatus as claimed in claim 37, wherein the computer-readable code when executed causes the at least one processor to perform: causing transmission of the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group.

41. Apparatus as claimed in claim 37, wherein the computer-readable code when executed causes the at least one processor to perform: using the group identification information comprising the MIMO group identifier and identifiers for transmitting devices that are part of the group to perform position estimates based on radio parameter information received from a mobile terminal.

42. Apparatus as claimed in claim 37, wherein the radio models comprise coverage area models.

43. Apparatus as claimed in claim 37, wherein the radio models comprise radio propagation models.

44. Apparatus as claimed in claim 37, wherein the computer-readable code when executed causes the at least one processor to perform: identifying that the first and second transmitting devices form part of a MIMO device by identifying that an average of differences between radio models of the first and second transmitting devices falls below a threshold.

45. Apparatus as claimed in claim 37, wherein the computer-readable code when executed causes the at least one processor to perform: determining that a MIMO group assumption is invalid and, in response, ceasing using the consolidated radio model for the MIMO group.

46. Apparatus as claimed in claim 37, wherein the computer-readable code when executed causes the at least one processor to perform: determining that a MIMO group assumption is invalid and, in response, separating the MIMO group into individual access points and creating radio models for the individual access points.

47. Apparatus as claimed in claim 37, wherein the computer-readable code when executed causes the at least one processor to perform: consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with averages, for instance a mean or weighted mean or median, of values from the radio models of the first and second devices.

48. Apparatus as claimed in claim 37, wherein the computer-readable code when executed causes the at least one processor to perform: consolidating the radio models for the first and second devices into a radio model for the MIMO group by providing a model with most recently recorded values or maximum values from the radio models of the first and second devices.

49. A computer program comprising machine readable instructions that when executed by computing apparatus causes it to perform the method of any of claims 12 to 23·