NL2015668B1 - Method and system for efficient access to spectrum database. - Google Patents

Abstract

Method for querying available communication channel information from a white space database (WSDB) for a mobile device in a wireless communication system. The mobile system e.g. comprises a processor and connected components capable to determine a predicted path (P) of the mobile device and perform a first White Space Database (WSDB) query (q), the query (q) being a multi-location query based on the predicted path (P). Furthermore a direction change from the predicted path (P) is determined based on one or more previous positions and a current position of the mobile device. If the determined direction change is larger than a direction change threshold value, an updated predicted path (P) is determined and a new white space database query (q) is sent based on the updated predicted path (P).

Description

Method and system for efficient access to spectrum database Field of the invention

The present invention relates to a method for querying available communication channel information from a white space database (WSDB) for a mobile device in a wireless communication system.

Prior art US patent publication US2014/0066059 discloses a method and apparatus determining white space information. Based on a location of a mobile terminal white space information is obtained from an access network using a discovery of available white space service providers. The received information is used by the mobile terminal to actually communicate using the white space communication channels. US patent publication US2014/0334422 discloses a method and device for transmitting and receiving available channel information based on directivity in a wireless communication system using ‘white space’ communication channels, e.g. TV band White Space (TVWS). In a mobile device, a predicted moving route is determined from a start point to a destination point. The route obtained using this method is divided in a number of sections having two points defining a directivity and a width of each section. Up to eight of such sections may be included in a multi-location channel availability query (CAQ) to a (TV band) white space database (TVWS), improving system performance as the geographical area covered by the query is diminished substantially.

Summary of the invention

The present invention seeks to provide an improved white space based communication method and system components, which are more efficient than methods using single location queries and which are more flexible than the prior art method using a predicted (but fixed) moving route.

According to the present invention, a method according to the preamble defined above is provided, the method comprising: - determine a predicted path of the mobile device and performing a first White Space Database (WSDB) query, the query being a multi-location query based on the predicted path, - determine a direction change from the predicted path based on one or more previous positions and a current position of the mobile device, and, - if the determined direction change is larger than a direction change threshold value, determine an updated predicted path and send a new white space database query based on the updated predicted path.

This will result in a lower number of queries to the WSDB in many practical circumstances, and thus a lower energy consumption. At the same time, the regulatory requirements set for these type of queries are still met.

In a further embodiment, the method further comprises sending an initial white space database query based on a current location of the mobile device. This initial stage of the method steps will prove especially useful when the mobile device is moving at a high speed, as a reply to such an initial white space database query is smaller and can this be received more quickly.

The predicted path is a linear path from the present location in a direction corresponding to a predicted direction of the mobile device in a further embodiment. The current knowledge of direction is e.g. based on previously determined locations of the mobile device, and using a linear path along the current direction will in most circumstances have a high degree of probability of eventually covering the actual path of the mobile device. In a further embodiment, the predicted path is a plurality of subsequent locations with a fixed distance between two subsequent locations. In this embodiment, the amount of data to be provided by the WSDB may be less as it only relates to a number of locations for which information needs to be provided.

The number of plurality of subsequent locations in the predicted path is a fixed number in a further embodiment. This is particularly useful for slow speeds, as otherwise the number of locations in a query would become too high, which is inefficient with regard to energy and timing. The number of the plurality of subsequent locations in the predicted path in an alternative embodiment is dependent on a current speed of the mobile device, e.g. 5 to 20 depending on the actual speed of the mobile device. This also limits the possible capacity needed for data transfer in the reply following the query.

In an even further embodiment, if the current speed of the mobile device is above a speed threshold value, the method comprises perform a white space database query wherein the query is based using the predicted path and one or more parallel paths. This embodiment would provide additional benefits in the case of the mobile device executing sharp turns etc., as it would be more likely that information from the WSDB on actual future locations is included in the reply to the query.

Determining a direction change may comprise using a tolerance threshold value in a further embodiment. This allows to filter the direction change to cater for e.g. GPS errors or small turns, e.g. in case of a lane change, preventing a new query when it is actually not really needed.

The method may further comprise obtaining actual mobile device parameters (position, speed, etc.) using a satellite based positioning system in a further embodiment, which provides for reliable and precise location detection. Alternatively or additionally actual mobile device parameters may be obtained using a local positioning sensor system, such as acceleration sensors, a compass, a radio triangulation unit, etc.

In a further aspect the present invention relates to a mobile device, such as a smart phone, comprising a radio interface, a location related sensor, a memory unit, and a processor connected to the radio interface, the location related sensor, and the memory unit, wherein the processor is arranged to execute the method according to any one of the present invention method embodiments.

In an even further aspect the present invention relates to a computer program product comprising computer executable instructions, which when loaded on a processor interfacing with a radio interface, a location related sensor, and a memory unit, provides the processor with the functionality of the method according to any one of the present invention method embodiments.

Short description of drawings

The present invention will be discussed in more detail below, using a number of exemplary embodiments, with reference to the attached drawings, in which

Fig. 1 shows a schematic view of a mobile device in a communication system in which the present invention embodiments are used;

Fig. 2 shows a flow chart of an embodiment of the present invention methods;

Fig. 3 shows a graphical presentation of a predicted path and associated method parameters.

Detailed description of exemplary embodiments

The present invention embodiments relate to wireless communication using so-called white space in the radio communication spectrum. Dynamic spectrum access (DSA) is a technology to balance the spectrum usage between the heavily used and empty bands. DSA allows secondary users to have access the empty channels or bands in a licensed part of the spectrum. Of course, any secondary user’s use of the white space should not affect a primary user’s network coverage or performance.

In DSA one approach to obtain information on the available radio spectrum relies on White Space (Spectrum) Databases (WSDBs), which are internet-accessible repositories keeping spectrum information for each supported geographical location. Most national regulations require mobile devices using WSDBs to ask anew for spectrum availability with each location change. This requires heavy reliance on Internet access, and with high mobility, imposes high querying rates to WSDBs draining resources of battery-operated devices.

The most widespread protocol to govern communication with WSDB is based on a Protocol to Access White space (PAWS) Databases. PAWS is used for WSDBs, e.g. in the USA, UK and South Africa, under regulation of respective authorities. Radio spectrum regulations states that a secondary user (i.e. a mobile device) has to issue a new request once the actual position of a device is x meter away (for example as of 2015, x = 50m in UK and x = 100m in US), from the position indicated in the last available-spectrum request message. For mobile devices this is a huge overhead as the device and the database will exchange messages almost constantly, and for devices with limited battery power the querying process may consume relatively lots of energy especially if a device moves with a high speed. The present invention embodiments, described in detail below, provide a solution on how to provide white space spectrum to mobile devices in an efficient way compared to the current state-of-the-art WSDB querying technique.

The present invention embodiments employ a novel WSDB spectrum query algorithm for mobile devices, exploiting two techniques: (i) prediction of movement path of the mobile device and (ii) On-demand Multi-Location WSDB query technique to optimize the access to a WSDB and provide good support to mobility. The design is driven from the perspective of query response delay, response message sizes, multilocation query support, and energy burden minimization.

It is noted that although the acronyms WSDB, PAWS and DSA are used, the present invention embodiments are not limited to these type of implementations, but can relate to any use of secondary spectrum in a given (existing or future) communication systems, e.g. TV white space usage, radar band white space usage, IEEE 802.11 types of communication networks, etc.

Fig. 1 shows a schematic diagram of a mobile device 1 in such an environment using available white spaces in the available communication spectrum. The mobile device 1 may interact directly with a white space database 2 via radio frequency communications, or indirectly, e.g. via an access point 3 connected to the white space database 2 via a network such as the internet 4.

In Fig. 1, functional components of the mobile device 1 are shown which play a role in the present invention embodiments. Other components may also be present (such as general processor related components, e.g. data and program memory, input/output units, etc.) depending on the function or use of the mobile device 1. The mobile device 1 comprises a processor 5, to which a radio interface 6, one or more location related sensors 7 and multiple stores or memory units 8a-8c are connected. As indicated in the schematic view of Fig. 1, the memory units 8a-8c are function specific and used to store timing data T, counting data N and direction data D, as will be explained below. In general terms, the present invention may be embodied in a mobile device 1 comprising a radio interface 6, a location related sensor 7, a memory unit 8a-8c, and a processor 5 connected to the radio interface 6, the location related sensor 7, and the memory unit 8a-8c, wherein the processor is arranged to execute any one of the present invention method embodiments as described herein.

The location related sensor(s) 7 are e.g. satellite based positioning systems, which use a receiving antenna to receive signals from satellites (e.g. GPS, GLONASS, Galileo, BeiDou) to determine a position in three dimensions (and time). Alternative techniques for (outdoor) localization may be used alternatively or additionally, e.g. cell-tower triangulation using mobile communication base stations, WiFi access points, etc., or fingerprinting techniques, where a device tries to match captured signatures against a set of geo-tagged signatures. Other types of localization sensors 7 may also be used, such as inertial sensors, magnetic field sensors, etc..

It is noted that the components of such a mobile device 1 are e.g. present in smart phones. Such devices are thus well suited to act as a mobile device 1 in the sense of the present invention embodiments.

Multi-location WSDB queries are known to exist, see e.g. US patent publication US2014/0334422 (as discussed in the introductory part above). The method described in US2014/0334422 is quite different from the present invention embodiments: a user sends locations to get one common set of frequencies that are valid for the entire region that covers all the specified locations. In the present invention embodiments, the locations (concatenated in a query) are sent and a response (concatenated) is obtained for each location. The main difference is that in the method disclosed in US2014/0334422 there is a well-defined relation between the frequencies (all the frequencies have to be valid in all the queried region), whereas in the present invention embodiments it is up to the user to find the common frequencies or to switch when needed, there is no relation needed between the frequencies. Multi-location WSDB query may serve different purposes. For instance, a master device serves other slave devices in a particular region. In this scenario the interest is not in a particular path but rather the entire region. It is also possible that the master device wants to communicate over white spaces, in this situation it has to know its current location or the path of movement.

Area Multi-location (AML) provides for the situation if the starting and the farthest locations on the path are known, but the path is completely unknown. A secondary user SU can query the entire region by putting the locations within a circle. Its center is the start location and the farthest location of the path on its circumference. However, the number of locations increases quadratic with the length of the distance between the two locations. For example, if the distance is 1 km, then the number of locations in circular area is about 314. While if the distance is 10 km then the number of locations is about 31400. Additionally, this technique may impose a start-up delay.

Oracle Multi-location (OML) provides for the situation if the path and all its coordinates are known in advance, i.e. using online services such as Google Maps. A secondary user SU can query it in one multi-location query. AML and OML describe techniques to obtain the frequencies from WSDB for a particular region or path, but not exactly where and when to use it. If the device needs to communicate over white spaces spectrum it has to know its location. However, these techniques may service different purposes for example, providing data for analysis by a master device or a secondary server. A lot of similarities can be observed in the frequencies list in the response messages to such queries. This may enable a mobile device to find one common frequency band for the entire region and communicate over it without the need for localization in this region.

On-Demand Multi-location query (ODML) provides for the situation if the path is not known in advance, but a device can track the user movements. A mobile device 1 can try to predict the next direction of movement and query it in a Multi-location WSDB query fashion.

This ODML query is the basis of the present invention embodiments, which are usable in a location aware mobile device 1. In a first aspect of the present invention, a method is provided for querying available communication channel information from a white space database (WSDB) 2 for a mobile device 1 in a wireless communication system, the method comprising: - determine a predicted path of the mobile device 1 and performing a first White Space Database (WSDB) 2 query, the query being a multi-location query based on the predicted path, - determine a direction change from the predicted path based on one or more previous positions and a current position of the mobile device 1, and, - if the determined direction change is larger than a direction change threshold value, determine an updated predicted path and send a new white space database query based on the updated predicted path.

The general considerations for the present invention embodiments is that a mobile device 1 is moving with a certain speed S and queries a WSDB 2. A Query Time QT presents the time consumed by querying the WSDB 2, from sending the query until a full reception of WSDB response by the mobile device 1. According to the present invention embodiments, the query time QT is converted into a Query Distance QD, i.e. the distance crossed by the mobile device 1 while sending the query and receiving the response: QD= S * QT. This is illustrated in Fig. 3, representing a path P travelled by a mobile device, with a q indicating the query and r the following response, AD indicating the path along which parameters received in the response r are valid, and the Query Distance QD the distance travelled by the mobile device in between the query q and the response r.

As an example, querying a single location using a smartphone takes on average 3 seconds, while adding one extra location for a multi-location query adds 0.09 seconds, which means querying two locations in a multi-location WSDB query takes about 3.09 seconds. This indicates that multi-location queries are very efficient from a timing and resource efficiency viewpoint.

This also provides a Remaining Distance RD which is the distance that the mobile device 1 can cross without the need to query the WSDB 2 again. In Fig. 3 the total distance being the sum of Query Distance QD and Remaining Distance RD is indicated by AD. Dividing the remaining distance RD by the query distance QD gives an Enlarge Factor EF (rounded to the nearest lower integer value).

The enlarge factor EF shows how many time the size of a query can be increased successively, sending the queries back-to-back, while staying within the remaining distance RD. In other words, the number of locations (NoL) to be queried in the single Multi-location query can be determined: NoL = EF. It is noted that in the implementation described NoL is equal to EF if NoL is not larger than maxNoL, which parameter is determined based on the speed.

Then the direction of movement needs to be determined, e.g. from the history of movement (longitudes and latitudes) of the mobile device 1. Change factors of longitude and latitude can e.g. be determined by dividing the average change along one of the coordinates by the sum of the averages. The change factors specifies the direction of movement along a straight line. The last computed change factors can be compared to the previous ones to check if there is a change in the direction or the mobile device 1 is moving along the same direction. If there is a change in the direction the next query starts from the current location. If there is no change in the direction detected and the remaining distance is smaller than what the devices can cross with its top speed, then the next query starts form the last queried location. If the remaining distance is larger than what the device can cross then the algorithm goes to sleep and wait to the next round. A possible implementation of the present invention method embodiment is shown in the flow chart as depicted in Fig. 2, which comprises three main stages. First, the first query stage (blocks 10-14) which is used as an initialization process and in it only the current location is queried in block 11 after determining in decision block 10 that the current query is a first query (e.g. following a user input from block 9). The query is sent to the WSDB 2, and a number of parameters are stored before entering a ‘sleep’ or ‘time-out’ block 14: The number of locations NoL is stored in a number buffer N (block 13, i.e. memory unit 8b in the embodiment shown in Fig. 1), and the query time QT is stored in a timing buffer T (block 12, i.e. memory unit 8c in the embodiment shown in Fig. 1). In more general terms, in an embodiment of the present invention methods, the method further comprises sending an initial white space database query based on a current location of the mobile device. Such an initial, first stage is especially useful when the mobile device 1 has a high current speed, as a reply to request is more quickly received when doing a single location query.

Since single location query has the fastest response time it is used in the algorithm as an initialization process to minimize the startup delay, and a recovery process when needed.

The second query stage relates to blocks 18-28 in the flow chart of Fig. 2. The primary block 18 of this second query stage is e.g. reached after exiting ‘sleep’ block 14 and determining in block 15 that a next query is to be sent. Upon that determination, the locations within the previous query time QT are retrieved (block 16). An additional check is made in determination block 17 that indeed the number of location is larger than 1 before progressing to the primary block 18. If the number of locations is not larger than one, the flow continues to the Current location query block 11 (i.e. a single location query to the WSDB 2).

If indeed the flow progresses in this second query stage, the direction of movement is predicted based on the history collected from the first query stage in block 19 (Get Estimate of Direction ED), which is then stored in a direction buffer D (i.e. memory unit 8a in the embodiment in Fig. 1). Also, the size (NoL) of the Multilocation query is determined in blocks 20-25, along the lines described above: the speed S of the mobile device 1 is determined in block 20, and the query time QT of the previous query is retrieved from the timing buffer T in block 21. The Query Distance QD is determined in block 22, and the number of locations (NoL) of the previous query is retrieved from the number buffer N in block 23. The Remaining Distance RD is then calculated in block 24 in accordance with the formula RD = x * NoL - QD, wherein x is the maximum distance between two locations for obtaining white space information (i.e. 100m in USA and 50m in UK). Then, the number of locations for the second query can be determined in block 25, as NoL=RD/QD (which is also stored in the number buffer N). Then all information needed for the second query to the WSDB 2 is known, and this can be processed as the first multi-location WSDB query. Also, the Query Time QT for this second query can be determined and stored in the timing buffer T (block 26). The queried area (or distance) is obtained and stored in block 28, as it is needed to allow a start from the last queried location if there is no change in direction.

So in further method embodiments, the predicted path is a linear path from the present location in a direction corresponding to a predicted direction of the mobile device. E.g. this is based on the current knowledge of direction based on previously determined locations of the mobile device 1. Also, in even further embodiments, the predicted path is a plurality of subsequent locations with a fixed distance between two subsequent locations (e.g. determined by the relevant protocol (PAWS), i.e. 50m (UK) or 100m (USA)).

Finally, the next query stage is represented in the flow chart of Fig. 2 by blocks 29-34 (as well as blocks 20-28, which are the same as in the second query stage for determining the size NoF of the Multi-location query. Additionally, the direction of movement of the previous query is retrieved from direction buffer D (block 30), and also the current direction of movement ED is determined and stored (block 31). The current direction is compared to the direction of movement during the previous query in block 29.

If there is a significant change then the process will start again from the First query stage (in block 11), as a recovery mechanism. Otherwise, a multi-location query is started (block 34, jump to the last queried location, and then progressing with block 20 and onwards), unless the Remaining Distance RD is longer than what the mobile device 1 can cross with its maximum speed, as determined in block 32.

If the left distance is longer than that (a ‘yes’ in decision block 32) no next query is generated, and the flow halts in a further sleep or time-out block 33. This will effectively reduce the number of generated queries to the WSDB 2 and prevents querying very long unneeded paths. As a consequence, energy consumption of the mobile device 1 will be reduced while gaining more freedom to move faster.

If the mobile device 1 is moving with a relatively low speed then the Enlarge Factor EF becomes very large and consequently the number of queried locations NoF becomes very large too. To prevent that, a limit is put on the size of a Multi-location WSDB 2 query in the range from 5 to 20 depending on the (current) speed S of the mobile device 1. In more general terms, the number of plurality of subsequent locations in the predicted path is a fixed number in a further method embodiment. As mentioned, this is particularly useful for slow speeds of the mobile device 1, as otherwise the number of locations in the query (and especially the query reply to be received) would become too high (which is energy and timing inefficient). The predicted path may thus have a fixed path length, e.g. 3 km.

The possible error in (GPS) position estimation (using the location sensor(s) 7 of the mobile device 1) may result in a determination of a change in the direction (block 29 in the flow chart of Fig. 2) or make the predicted path line to be not perfectly along the real path. To reduce the number of false direction change detections and to make use of the allowed distance x of movement (i.e. 100 m the USA implementation as of 2015), for the same query, a tolerance threshold of e.g. 0.08, is included in the direction change estimation in a further embodiment. This value is chosen based on a large number of testing runs as a balance between location (GPS) estimation error and small turns that should not generate a new query (e.g. changing from one lane to another) and making the method embodiment able to correct its direction and track the mobile device 1 movement accurately.

Tests were performed using the present invention embodiments, using three different types of actual paths of the mobile device 1: A circular path (CP) of 3 km, with a top speed of 40 km/h and the number of iterations five; a long-lines path (LP) of 3 km with a top speed of 80 km/h and the number of iterations five; and a random path (RP) of 12 km with a top speed of 80 km/h and the number of iterations one.

As the present invention embodiments always predict the direction of movement along a straight line, and then check if there is a change in the direction, its best performance is along a straight line, and the worst performance is on a path of a constantly changing direction. Since the path length in all three types of paths is 3 km, the needed number of single-location SL queries would be 30. The average number of generated queries along the LP is less than one third of the number generated along the CP and SL. Thus, from the energy perspective the present invention embodiments are much more efficient than single-location query technique on a straight-lines path. Furthermore, the present invention embodiments are only marginally worse than single location query technique on the circular path CP, the reason being that Multi-location queries are generated, but mostly only one location of the query is used.

Further tests show that in general the present invention embodiments are more energy efficient as compared to single-location query techniques, because the number of total queries is reduced. This allows the processing unit 5 of the mobile device 1 go into a suspend mode in between the queries, and therefore less power is used.

The minimum time needed to react to a change in the direction of movement of the mobile device 1 is the time of querying the WSDB 2 and get a full response. E.g. the sleep or time-out blocks 14, 33 in the flow chart of Fig. 2 may be chosen such that the check direction change block 29 is entered every 8 seconds (this interval being an estimation for the longest query time QT). If a change in direction starts and ends within this interval, it will not be recognized. Therefore, turning with a relatively high speed might make the mobile device 1 exceed the 100m limit for WSDB 2 queries. To overcome this, a shorter interval can be selected. Alternatively, the multi-location query can be extended along three parallel lines when a mobile device 1 moves faster than a predefined threshold (e.g. 50km/h). In general terms, a further embodiment may be implemented wherein, if the current speed of the mobile device is above a speed threshold value, the method furthers comprises performing a white space database query wherein the query is based using the predicted path and one or more parallel paths.

Because of the manner of prediction the direction of movement, along a straight line and then checking if there is a change in direction, the present invention embodiments are slightly less efficient than straightforward execution of only single location queries on a constantly hard bending path (circular path CP). Thus, always a number of unused queried locations are obtained. However, the cost of the extra locations that were queried in terms of energy and time is only marginal.

The determination of the present location of the mobile device 1 is executed using the one or more localization sensors 7 (see Fig. 1). In one embodiment, the method thus comprises obtaining actual mobile device parameters, such as position, speed, and/or acceleration, using a satellite based positioning system (GPS, Glonass, Galileo, BeiDou, etc.).

In order to reduce the dependency of the mobile device on e.g. GPS signal reception, in a further embodiment alternatively or additionally the actual mobile device parameters are obtained using a local positioning sensor system using different types of sensors 7, such as an acceleration sensor, an inertial sensor, a compass sensor, radio triangulation sensor, etc. Using a local sensor 7 and e.g. enforce its estimation with the GPS positioning data, will help in reducing the energy consumption and make the algorithm work reasonable when the GPS signal is lost.

In a specific aspect the present invention relates to a computer program product comprising computer executable instructions, which when loaded on a processor 5 interfacing with a radio interface 6, a location related sensor 7, and a memory unit 8a-8c, provides the processor 5 with the functionality of the method embodiments as described herein. It is noted that embodiments of the present invention may comprise special purpose and/or general purpose computer devices implanting the processor 5 as described above. Each computer device may include standard computer hardware such as a central processing unit (CPU) or other processing means for executing computer executable instructions, computer readable media for storing executable instructions, a display or other output means for displaying or outputting information, a keyboard or other input means for inputting information, and so forth. Examples of suitable computer devices include hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, networked PCs, minicomputers, mainframe computers, and the like.

The invention embodiments have been described in the general context of computer-executable instructions, such as program modules, that are executed by the processor 5, including, but not limited to a personal computer. Generally, program modules include routines, programs, objects, components, data structure definitions and instances, etc., that perform particular tasks or Implement particular abstract data types. Typically the functionality of the program modules may be combined or distributed as desired in various environments.

Embodiments within the scope of the present invention also include computer readable media having executable instructions. Such computer readable media can be any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired executable instructions and which can be accessed by a general purpose or special purpose computer. Combinations of the above should also be included within the scope of computer readable media. Executable instructions comprise, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions.

The present invention as described above in detail may be summarized as a number of embodiments, of which the features may be combined as indicated below: Embodiment 1. Method for querying available communication channel information from a white space database (WSDB) for a mobile device in a wireless communication system, the method comprising: - determine a predicted path of the mobile device and performing a first White Space Database (WSDB) query, the query being a multi-location query based on the predicted path, - determine a direction change from the predicted path based on one or more previous positions and a current position of the mobile device, and, - if the determined direction change is larger than a direction change threshold value, determine an updated predicted path and send a new white space database query based on the updated predicted path.

Embodiment 2. Method according to embodiment 1, further comprising sending an initial white space database query based on a current location of the mobile device. Embodiment 3. Method according to embodiment 1 or 2, wherein the predicted path is a linear path from the present location in a direction corresponding to a predicted direction of the mobile device.

Embodiment 4. Method according to any one of embodiments 1-3, wherein the predicted path is a plurality of subsequent locations with a fixed distance between two subsequent locations.

Embodiment 5. Method according to embodiment 4, wherein the number of plurality of subsequent locations in the predicted path is a fixed number.

Embodiment 6. Method according to embodiment 4, wherein the number of plurality of subsequent locations in the predicted path is dependent on a current speed of the mobile device.

Embodiment 7. Method according to any one of embodiments 1-6, wherein if the current speed of the mobile device is above a speed threshold value, the method comprises - perform a white space database query wherein the query is based using the predicted path and one or more parallel paths.

Embodiment 8. Method according to any one of embodiments 1-7, wherein determining a direction change comprises using a tolerance threshold value. Embodiment 9. Method according to any one of embodiments 1-8, further comprising obtaining actual mobile device parameters using a satellite based positioning system. Embodiment 10. Method according to embodiment 9, wherein alternatively or additionally actual mobile device parameters are obtained using a local positioning sensor system.

Embodiment 11. Mobile device comprising a radio interface (6), a location related sensor (7), a memory unit (8a-8c), and a processor (5) connected to the radio interface (6), the location related sensor (7), and the memory unit (8a-8c), wherein the processor is arranged to execute the method according to any one of embodiments 1-10. Embodiment 12. Computer program product comprising computer executable instructions, which when loaded on a processor (5) interfacing with a radio interface (6), a location related sensor (7), and a memory unit (8a-8c), provides the processor (5) with the functionality of the method according to any one of embodiments 1-10.

The present invention embodiments have been described above with reference to a number of exemplary embodiments as shown in the drawings. Modifications and alternative implementations of some parts or elements are possible, and are included in the scope of protection as defined in the appended claims.

Claims (12)

A method for querying available communication channel information from a white space database (WSDB) for a mobile device in a wireless communication system, the method comprising: - determining a predicted path of the mobile device and performing a first interrogation of the white space database (WSDB), wherein the interrogation is a multi-location interrogation based on the predicted path, - determining a directional change of the predicted path based on one or more preceding positions and a current position of the mobile device, and, - if the determination of the direction change is greater than a direction change threshold value, determining a renewed predicted path and sending a new interrogation of the white space database based on the renewed predicted path. The method of claim 1, further comprising transmitting an initial white space database query based on a current location of the mobile device. The method of claim 1 or 2, wherein the predicted path is a linear path of the current location in a direction corresponding to a predicted direction of the mobile device. The method of any one of claims 1-3, wherein the predicted path is a plurality of consecutive locations with a fixed distance between two consecutive locations. The method of claim 4, wherein the number of the plurality of consecutive locations in the predicted path is a fixed number. The method of claim 4, wherein the number of the plurality of consecutive locations in the predicted path is dependent on a current speed of the mobile device. A method according to any of claims 1-6, wherein if the current speed of the mobile device is above a speed threshold value, the method comprises - performing a white space database query wherein the query is based on using the predicted path and one or more parallel paths. The method of any one of claims 1-7, wherein determining a direction change comprises using a tolerance threshold. The method of any one of claims 1-8, further comprising obtaining current mobile device parameters using a satellite-based positioning system. The method of claim 9, wherein alternatively or additionally additional current mobile device parameters are obtained using a local positioning sensor system. A mobile device comprising a radio interface (6), a location related sensor (7), a memory unit (8a-8c), and a processor (5) connected to the radio interface (6), the location related sensor (7) and the memory unit (8a-8c), wherein the processor is adapted to perform the method according to any of claims 1-10. A computer program product comprising computer-executable instructions which, when loaded on a processor (5) that has an interface with a radio interface (6), a location-related sensor (7), and a memory unit (8a-8c), the processor (5) provides the functionality of the method according to one of claims 1-10.