Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
  • H04W64/003—Locating users or terminals or network equipment for network management purposes, e.g. mobility management locating network equipment
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
  • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
  • G01S5/0295—Proximity-based methods, e.g. position inferred from reception of particular signals
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
  • H04W88/02—Terminal devices
  • H04W88/06—Terminal devices adapted for operation in multiple networks or having at least two operational modes, e.g. multi-mode terminals

Definitions

• the present invention belongs to the field of geolocation.
• the invention relates to a method and a device for geolocation of a base station of an access network of a wireless communication system.
• a base station is not necessarily permanently installed at a known geographical position which does not vary over time.
• a local base station can be installed in a user's home or in a company building without the access network operator being informed.
• the pricing of data exchanges carried out by a base station may vary depending on the country in which the base station is located. Also, the beneficiary of the costs of the data exchanges carried out by a base station generally depends on the country in which the base station is operating. It is therefore important to be able to determine the position of a base station over time when the base station can be moved.
• the objective of the present invention is to remedy all or part of the drawbacks of the prior art, in particular those set out above.
• a method of geolocation of a base station called a “searched base station”, of an access network of a wireless communication system. thread.
• the wireless communication system also comprises at least one terminal suitable for sending messages to said access network.
• a message sent by a terminal can be received simultaneously by several base stations of the access network.
• the geographical position of the desired base station is determined based on the geographical position of at least one other base station of the access network, called a "reference base station".
• a reference base station is a base station whose geographical position is known and which has received a message sent by said terminal which has also been received by the base station sought.
• the position of the terminal does not need to be known by the access network. Also, the position of the desired base station can be determined without the latter needing to transmit information relating to its geographical position. No software or hardware modification of the base stations of the communication system is necessary to implement the geolocation method according to the invention.
• the geolocation method according to the invention can therefore be implemented in a simple and inexpensive manner.
• the invention may further include one or more of the following characteristics, taken in isolation or in any technically possible combination.
• the geographical position of the base station sought is further determined as a function of a measurement carried out for each reference base station by a value representative of a level of radio link quality. between the terminal and said reference base station.
• the radio link in question corresponds to the radio link established between the terminal and the reference base station for the transmission of this message.
• the geographical position of the base station sought is a weighted average of the geographical positions of the reference base stations.
• Each geographical position of a reference base station is weighted by a coefficient whose value is representative of the level of radio link quality between the terminal and said reference base station.
• the geographical position of the base station sought is further determined as a function of a measurement carried out for the base station sought by a value representative of a level of radio link quality between the terminal and the base station sought.
• the geographical position of the base station sought is a weighted average of the geographical positions of the reference base stations.
• Each geographical position of a reference base station is weighted by a coefficient whose value is representative of the difference between the radio link quality level between the terminal and the reference base station and the radio link quality level between the terminal and the desired base station.
• the geographic position of the desired base station is determined using a machine learning algorithm as a function of the measurements made and as a function of the geographic positions of the reference base stations.
• a group of several messages are considered to determine the geographical position of the base station sought, each message of the group having been sent by a terminal of the communication system and received by at least one communication station. reference base and the desired base station. For each message, for the base station sought and for each of the reference base stations having received said message, a measurement of a value representative of a level of radio link quality between said base station and the terminal having transmitted said message is carried out.
• the geographical position of the base station sought is determined as a function of a geographical position of the estimated base station searched for each message in the group.
• a virtual measurement is calculated for each reference base station from the measurements made for said reference base station for the various messages received by said reference base station.
• the geographical position of the sought base station is then determined as a function of the virtual measurements obtained and the geographical positions of the reference base stations.
• the virtual measurement calculated for a reference base station is a weighted average of the measurements taken for said reference base station for the various messages received by said reference base station.
• Each measurement is weighted by a coefficient, the value of which is representative of the measurement of the level of radio link quality carried out for the base station sought for the corresponding message.
• the geographical position of the base station sought is a weighted average of the geographical positions of the reference base stations.
• Each geographical position of a reference base station is weighted by a coefficient whose value is representative of the virtual measurement calculated for said reference base station.
• the geographic position of the desired base station is determined by an automatic regression learning algorithm as a function of the measurements made and as a function of the geographic positions of the reference base stations.
• the present invention relates to a computer program product comprising a set of program code instructions which, when they are executed by one or more processors, configure the processor or processors to implement a method of geolocation of a base station according to any one of the preceding embodiments.
• the present invention relates to a server of a wireless communication system.
• the wireless communication system comprises a plurality of base stations and at least one terminal suitable for transmitting messages to said base stations.
• a message sent by the terminal can be received simultaneously by several base stations.
• the server is connected by a communication link to each base station of the plurality of base stations.
• the server is configured to implement a method of geolocation of a base station according to any of the preceding embodiments.
• the present invention relates to an access network a wireless communication system.
• the access network comprises a plurality of base stations and a server as described above.
• FIG. 1 a schematic representation of a wireless communication system comprising at least one terminal and an access network comprising a plurality of base stations,
• FIG. 2 a schematic representation of the main steps of a method of geolocation of a base station according to the invention
• FIG. 3 a schematic representation of the main steps of a first particular embodiment of a geolocation method according to the invention
• FIG. 4 a schematic representation of the main steps of a second particular embodiment of a geolocation method according to the invention
• FIG. 5 a schematic representation of the main steps of a third particular embodiment of a geolocation method according to the invention.
• FIG. 6 a schematic representation of the main steps of a fourth particular embodiment of a geolocation method according to the invention.
• FIG. 7 a schematic representation of the main steps of a particular fifth mode of implementing a geolocation method according to the invention
• FIG. 8 a schematic representation of a model used by a machine learning algorithm implementing a geolocation method according to the invention.
• the present invention finds a particularly advantageous application, although in no way limiting, in wireless communication systems of the Internet of Things type (loT, for “Internet Of Things” in the English literature) or of the M2M type (English acronym). Saxon for "Machine to Machine”).
• FIG. 1 schematically represents a wireless communication system 10, comprising one or more terminals 20 and an access network 30.
• the network access 30 comprises several base stations 31 and a server 32 connected to said base stations 31.
• the data exchanges are essentially one-way, in this case on an uplink from the terminals 20 to the access network 30 of said wireless communication system 10.
• the planning of the access network 30 is often carried out such that a given geographical area is simultaneously covered by several base stations 31, such that a message sent by a terminal 20 can be received by several base stations 31.
• a message sent by a terminal 20 can be received by several base stations 31.
• the same message sent by the terminal 20 can be received, decoded, and processed by several base stations 31 (and not only by a single base station with which the terminal is associated).
• Each base station 31 is adapted to receive messages from terminals 20 which are within its range.
• a message sent by a terminal 20 includes in particular an identifier of the terminal making it possible to identify said terminal 20.
• Each message thus received is for example transmitted to the server 32 of the access network 10, possibly accompanied by other information such as an identifier of the base station 31 which received it, a value representative of the quality of the radio signal carrying the message, the central frequency on which the message was received, a date on which the message was received, etc.
• the server 32 processes, for example, all the messages received from the different base stations 31.
• the wireless communication system 10 is, for example, a low power consumption wireless wide area network known by the term LPWAN (acronym for “Low Power Wide Area Network”).
• LPWAN Low Power Wide Area Network
• Such a wireless communication system is a long-range access network (greater than one kilometer, or even greater than a few tens of kilometers), with low energy consumption (for example energy consumption during transmission or reception. of a message less than 100 mW, or even less than 50 mW, or even less than 25 mW), and whose rates are generally less than 1 Mbits / s.
• Such wireless communication systems are particularly suitable for applications involving connected objects.
• the wireless communication system 10 may be an ultra-narrowband communication system.
• ultra narrow band (“Ultra Narrow Band” or UNB in English literature) is meant that the instantaneous frequency spectrum of the radio signals emitted by the terminals has a frequency width of less than two kilohertz, or even less than one kilohertz.
• Ultra Narrow Band or UNB in English literature
• Such a system makes it possible to significantly limit the electrical consumption of the terminals when they communicate with the access network.
• the geographical position of a particular base station 31 of the access network 30 is sought.
• the base station sought bears the reference BSx.
• One or more base stations 31 distinct from the sought base station BSx correspond to reference base stations BS Ref .
• a reference base station BS Ref is a base station 31 of the access network 30 whose geographical position is known and which has received a message sent by a terminal 20 which has also been received by the sought base station BSx.
• the server 32 can in particular be used to implement all or part of a method of geolocation of the desired base station BSx.
• the server 32 comprises a processing circuit comprising one or more processors and storage means (magnetic hard disk, electronic memory, optical disc, etc.) in which a computer program product is stored, in the form a set of program code instructions to be executed to implement at least part of the steps of a method for geolocation of a base station 31 of the access network 30 of the wireless communication system 10.
• the processing circuit of the server 32 comprises one or more programmable logic circuits (FPGA, PLD, etc.), and / or one or more specialized integrated circuits (ASIC), and / or a set of discrete electronic components , etc., adapted to implement steps of the geolocation method.
• the server 32 includes software and / or hardware means for implementing a geolocation method according to the invention.
• FIG. 2 schematically represents the main steps of a method 100 for geolocation of the desired base station BSx.
• the geolocation method 100 comprises in particular a step 101 of determining at least one reference base station BS Ref whose geographical position is known and which has received a message sent by a terminal 20 which has also been received by the base station. wanted BSx.
• the server 32 can in fact determine, for a given message, which are the base stations 31 which have received this message.
• the message received comprises for example an identifier of the terminal 20 which sent the message as well as a sequence number allowing this message to be identified, and a base station which receives the message transmits the message to the server accompanied by 'an identifier of the base station.
• the method 100 then comprises a step 102 of determining the geographical position of the sought base station BSx as a function of the geographical position of each reference base station BS Ref determined in step 101.
• the server has access to a database comprising the geographical positions a whole set of base stations 31 which can then play the role of reference base stations BS Ref .
• the geographical position of the searched base station BSx can be determined in step 102 as being the geographical position of said base station of reference BS Ref .
• the geolocation precision of the sought-after base station BSx is relatively low because it presents a geolocation error which can be up to twice the transmission range of the terminal 20 having sent the message.
• the geographical position of the searched base station BSx can be defined in step 102 as being an average of the geographical positions of the different stations.
• geographical position is understood to mean, for example, a system of two coordinates corresponding to the latitude and the longitude. An average geographic position calculated between several geographic positions will then have for latitude the average value of the latitudes of the various geographic positions and for longitude the average value of the longitudes of the various geographic positions. None prevents, however, also considering a third coordinate corresponding to an altitude above sea level.
• the value representative of the quality of the radio link used is a received power level (“Received Signal Strength Indicator” or RSSI in English literature) measured for a base station 31 for a signal carrying a message transmitted by a terminal 20.
• RSSI Received Signal Strength Indicator
• other values representative of the quality of the radio link could be used, such as for example signal attenuation, a signal to noise ratio of the signal (“Signal on Noise Ratio” or SNR in English literature) or a quality indicator of the communication channel (“Channel Quality Indicator” or CQI in English).
• the choice of a particular value representative of the quality of the radio link constitutes only one variant of the invention.
• the measurement can be carried out either directly by the base station which received the message, or indirectly by the server 32 on the basis of information supplied by the base station which received the message.
• FIG. 3 schematically represents the main steps of a first particular embodiment of the geolocation method 100 according to the invention.
• a single message is considered received both by the sought base station BSx and by at least one reference base station BS Ref .
• An RSSI measurement of the power level with which the message is received is then performed for each BS Ref reference base station used.
• Step 201 is identical to step 101 described above with reference to Figure 2.
• step 202 an RSSI value is measured for each reference base station BS Ref determined in step 201 for the message considered.
• the geographical position of the sought base station BSx is determined not only as a function of the geographical position of each reference base station BS Ref determined in step 201, but also as a function of the RSSI values measured at step 202 for these reference base stations BS Ref .
• the geographical position of the searched base station BSx is determined as being a weighted average of the geographical positions of the reference base stations BS Ref , each geographical position of a reference base station BS Ref being weighted by a coefficient the value of which is representative of the quality level of the radio link (that is to say the value of RSSI in the example considered) established between the terminal 20 and said reference base station BS Ref during the exchange of the message considered.
• - K is the number of reference base stations BS Ref used to determine the geographical position of the sought base station BSx,
• Z k is the known geographical position of a reference base station BS Ref of index k, - a k is the weighting coefficient associated with the reference base station BSR ef of index k,
• - Z x is the determined geographical position of the searched base station BSx (in other words, X is the index of the searched base station).
• Each weighting coefficient a k is for example calculated according to the expression below:
• - rssi k is the measurement of the received power level (RSSI measurement) performed for the reference base station BS Ref of index k,
• - Y is a normalization factor whose value is constant. Note that the same symbol g is used hereafter in different mathematical expressions to represent a normalization factor. However, the value of the normalization factor may vary from one expression to another.
• the RSSI measurement is expressed in dBm (power ratio in decibels between the measured power and one milliwatt).
• the RSSI metric is a negative value. The greater the absolute value of the RSSI measurement, the lower the measured received power level. Conversely, the smaller the absolute value of the RSSI measurement, the stronger the measured received power level.
• Such arrangements make it possible to determine the geographical position of the desired base station BSx as a function of the geographical positions of the reference base stations BS Ref while favoring the reference base stations BS Ref for which the message in question was received with a high RSSI level. In other words, to determine the geographical position of the sought base station BSx, greater confidence is given to the reference base stations BS Ref which received the message considered with a high RSSI level.
• FIG. 4 schematically represents the main steps of a second particular embodiment of the geolocation method 100 according to the invention.
• This second particular embodiment comprises in particular a step 301 of determining at least one reference base station BS Ref and a step 302 of determining an RSSI measurement for each identified reference base station BS Ref.
• Steps 301 and 302 are identical respectively to steps 201 and 202 of the first particular embodiment previously described with reference to FIG. 3.
• this second particular embodiment includes a step 303 for determining an RSSI measurement of the power level with which the considered message is received by the sought base station BSx.
• a step 304 the geographical position of the sought base station BSx is then determined as a function of the RSSI measurements performed not only for the reference base stations BS Ref but also for the sought base station BSx.
• the geographical position of the searched base station BSx is a weighted average of the geographical positions of the reference base stations BS Ref , in which each geographical position of a reference base station is weighted by a coefficient whose value is representative of the difference between the RSSI level measured for said reference base station BS Ref and the RSSI level measured for the sought base station BSx.
• the geographical position Z x of the sought base station BSx can be determined according to the expression [Math. 1] using weighting coefficients a k defined by the expression below:
• - rssi k is the measurement of the received power level (RSSI measurement) performed for the reference base station BS Ref of index k,
• - rssix is the measurement of the received power level (RSSI measurement) performed for the sought base station BSx.
• Such arrangements make it possible to determine the geographical position of the desired base station BSx as a function of the geographical positions of the reference base stations BS Ref while favoring the reference base stations for which the message in question was received with an RSSI level. close to the RSSI level with which said message was received by the sought base station BSx.
• greater confidence is given to the reference base stations BS Ref which received the message with an RSSI level close to the RSSI level with which the message was received by the desired base station BSx.
• the taking into account of the RSSI level with which the message was received by the sought base station BSx makes it possible to improve the precision of the geolocation of the base station sought.
• the geographical position of the desired base station BSx using a machine learning algorithm based on a pre-established model from RSSI level measurements or of RSSI level differences.
• the model is for example built during a learning phase by associating known geographical positions with values of weighting coefficients such as those described by the expressions [Math. 2] and [Math. 3].
• the machine learning algorithm is configured to determine, during a search phase, a geographical position of a base station sought from the model thus constructed and from values of weighting coefficients calculated for base stations of reference having received a particular message which was also received by the sought base station.
• FIG. 5 schematically represents the main steps of a third particular embodiment of the geolocation method 100 according to the invention.
• a group of several messages (Msg # 1, Msg # 2, ... Msg #N) are considered to determine the geographical position of the sought base station BSx.
• Each message considered was sent by a terminal 20 of the communication system 10 and received both by at least one reference base station BS Ref and by the sought base station BSx.
• the various messages considered may have been sent by the same terminal 20 or by several different terminals 20.
• the different messages considered may have been sent at substantially the same time or else at different times during a predetermined period of time.
• a determination of at least one reference base station BS Ref which received said message considered is identical to the steps 201 and 301 described previously respectively for the first and for the second particular mode of implementation. with reference to FIGS. 3 and 4.
• an RSSI measurement of the power level with which said message was received is carried out for each of the reference base stations BS Ref having received said message (step 402).
• This determination of an RSSI measurement for each reference base station BS Ref for a particular message is identical to the steps 202 and 302 described previously respectively for the first and for the second particular mode of implementation with reference to FIGS. 3 and 4. .
• FIG. 6 schematically represents the main steps of a fourth particular embodiment of the geolocation method 100 according to the invention.
• This fourth particular mode of implementation is based on the third particular mode of implementation previously described with reference to FIG. 5.
• the step 501 of determining, for each message considered, at least one communication station. reference base, and the step 502 of determining, for each message considered, an RSSI measurement for each reference base station having received said message are respectively identical to steps 401 and 402 of the third particular mode of implementation described with reference to Figure 5.
• This fourth particular embodiment further comprises a step 503 in which, for each message considered, an estimated geographical position of the base station sought is determined, as well as a step 504 in which the geographical position of the station. base sought is determined as a function of the various positions estimated at step 503.
• the estimated geographical position of the sought base station can be determined as being the average of the geographical positions of the reference base stations BS Ref having received said message.
• this average can be weighted according to weighting coefficients whose values are representative of the RSSI measurements measured for the reference base stations having received said message.
• the estimated geographical position Z m, x of the sought base station BSx can be defined by the expression below:
• K m is the number of reference base stations BS Ref having received the message of index m
• k is the weighting coefficient associated with the reference base station of index k
• weighting coefficient a m, k can be defined according to the expression below:
• rssi m k is the received power level measurement (RSSI measurement) for the reference base station BS Ref of index k for the message of index m
• y is a constant normalization value
• the geographical position Z x of the desired base station BSx can for example be defined as a simple average of the geographical positions thus estimated:
• M corresponds to the total number of messages considered.
• weighting this average with weighting coefficients whose values are representative of the RSSI levels with which the sought base station BSx has received the message of index m: [Math. 7]
• the estimation made for a particular message at step 503 of the geographical position of the sought-after base station BSx and / or the final determination at step 504 of the geographical position of the desired base station BSx could also be produced using a machine learning algorithm, for example an algorithm of the data partitioning type (“data clustering” in the English literature) . Also, other weighting factors than the RSSI measurement could be taken into consideration to determine weighting coefficients for the different BS Ref reference base stations.
• FIG. 7 schematically represents the main steps of a fifth particular embodiment of the geolocation method 100 according to the invention.
• This fifth particular mode of implementation is based on the third particular mode of implementation previously described with reference to FIG. 5.
• BS Ref reference base and step 602 of determining, for each message considered, an RSSI measurement for each BS Ref reference base station having received said message, are respectively identical to steps 401 and 402 of the third particular mode implementation described with reference to Figure 5.
• This fifth particular embodiment further comprises a step 603 in which a virtual measurement is calculated for each reference base station BS Ref from the RSSI measurements carried out for said reference base station for the various messages received by said reference base station. reference base station.
• the virtual measurement calculated for a reference base station BS Ref can correspond to a simple average of the RSSI measurements taken for said reference base station for the various messages received by said reference base station.
• reference base station which can be translated into the expression below: [Math. 8]
• Vrssi k is the virtual measurement calculated for a reference base station BSR ef of index k
• - rssi mk is the RSSI measurement performed for the reference base station of index k for a message of index m chosen from among the M k messages received.
• the virtual measurement calculated for a reference base station BS Ref can correspond to a weighted average of the RSSI measurements taken for said reference base station for the various messages received by said reference base station.
• Each RSSI measurement is for example weighted by a coefficient, the value of which is representative of the RSSI measurement performed for the sought base station BSx for the corresponding message. This can be translated into the expression below:
• rssi m, x is the RSSI measurement performed for the sought base station BSx for a message of index m chosen from among the M k messages which were received at the same time by the reference base station BS Ref of index k and by the desired base station BSx.
• step 604 the geographical position of the sought base station BSx is determined as a function of the virtual measurements thus obtained and as a function of the geographical positions of the reference base stations BS Ref .
• the geographical position Z x of the sought base station BSx can for example be defined as a weighted average of the geographical positions Z k of the K reference base stations BS Ref .
• each geographical position of a reference base station is weighted by a weighting coefficient representative of the virtual measurement calculated for said reference base station: [Math. 10]
• each geographical position of a reference base station BS Ref is weighted by a weighting coefficient representative of the difference between the virtual measurement calculated for said reference base station and a virtual measurement calculated for the reference station.
• base sought BSx a weighting coefficient representative of the difference between the virtual measurement calculated for said reference base station and a virtual measurement calculated for the reference station.
• Vrssix corresponds to the virtual measurement calculated for the sought base station BSx, which may for example correspond to the average of the RSSI levels measured for the sought base station BSx for the M different messages considered:
• the geographic position of the desired base station BSx is determined by an automatic regression learning algorithm as a function of the measurements made and as a function of the geographic positions of the reference base stations BS Ref .
• Figure 8 shows an example of a model used by the machine learning algorithm.
• the model corresponds to a matrix of characteristics stored in a database accessible by the server 32.
• the machine learning algorithm is configured to generate a regression function to determine the geographic position (longitude, latitude) of a base station from this feature matrix. Each row of the matrix corresponds to a sought-after base station BSx of the access network 30. To determine the geographical position of the sought-after base station BSx, we consider: a group of P messages received by the sought-after base station BSx,
• the first 3N columns of the characteristic matrix correspond respectively to the RSSI measurement, the longitude and the latitude of N BS Ref reference base stations having the largest RSSI measurement values for a first message received at the same time by the searched base station BSx and by each of the reference base stations.
• the column (3N + 1) corresponds to the RSSI measurement for the searched base station BSx for this first message.
• Columns (3N + 2) through (6N + 2) correspond to similar values for a particular second message.
• the columns ((P-1) (3N + 1) +1) to P (3N + 1) correspond to similar values for a particular P th message. It should be noted that if some values of the characteristic matrix are not available (eg if there are less than N reference base stations identified for a given message) default values can be used. Also, other characteristics specific to each base station can be added in the matrix of characteristics, for example the altitude of the reference base station, or the environment in which it is located (urban, mountainous, maritime environment , etc.).
• the base stations to be geolocated correspond to base stations whose geographical position is known.
• the P messages of the same line correspond to messages received consecutively (possibly from different terminals) during a certain period of time, and different lines associated with the same base station correspond to different periods of time (and therefore to different sequences of messages received during said periods of time).
• the P messages of the same line correspond to messages sent consecutively by one and the same terminal for a certain period of time, and different lines associated with the same base station correspond to different terminals (and possibly to different time periods too).
• the regression function can be used to predict the geographic position of a desired base station BSx from the model stored in the database on the one hand and from the measurements on the other hand.
• RSSIs performed for a group of messages.
• regression machine learning algorithms can be used, for example algorithms of the “Forest of trees” type. decision-making ”(“ Random forest ”in Anglo-Saxon literature) or of the“ Gradient improvement ”type (“ Gradient boosting ”in Anglo-Saxon literature”).
• a selection of N reference base stations BS Ref having the largest measured RSSI values is carried out for each message considered. It should however be noted that it is possible to make a selection of N reference base stations or of P messages according to different criteria. For example, the P messages and the N base stations could be selected to maximize the number of common base stations having received the P messages. According to another, the P messages and the N base stations could be selected to maximize the spatial diversity of the base stations.
• the present invention achieves the objectives set.
• the invention makes it possible to geolocate a base station of an access network of a wireless communication system in a simple and inexpensive manner, without it being necessary to modify the software and / or hardware. the base stations of the system.

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