RU2427079C1 - Method of evaluating state of user mobile device in wireless communication system - Google Patents

Abstract

FIELD: information technology.

SUBSTANCE: external acoustic signals are periodically measured using a microphone built into the mobile device. The external acoustic signals are recorded into a file which, at the end of recording, is converted to a numerical array of values of the level of external acoustic signals. The numerical array of defined length is broken. The level of acoustic signals is calculated for each section. A series of given length consisting of a subseries of running values of the calculated levels of acoustic signals is selected. For the selected series, the minimum value of the level of acoustic signals is selected, which is then compared with a given threshold and a decision is made on the state of the user mobile device based on the comparison results.

EFFECT: broader functional capabilities owing to determining whether the mobile device is inside or outdoors.

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Description

The invention relates to the field of radio engineering, in particular to a method for assessing the status of a user's mobile device in a wireless communication system based on the analysis of the acoustic signals of the microphone of a mobile device, and can be used in wireless communication systems according to GSM, CDMA, IEEE 802.16, IEEE 802.11n, 3GPP LTE, as well as in other wireless data communication systems.

It is understood that the structure of a global wireless communication system includes, but is not limited to, mobile devices that users have at their disposal and which serve primarily to communicate with base stations in a wireless communication system, but can also perform many other functions. Such additional functions include communication functions with various devices and other devices, communication with the global positioning system, entertainment functions, listening to music, games, user notification systems about various events, etc.

To expand the functionality of mobile devices, it is of great practical importance to evaluate the various conditions in which a user's mobile device in a wireless communication system may be. Such conditions may include the state of the user's mobile device indoors or outdoors, the stationary state of the user's mobile device or the state of its movement, etc. With knowledge of these states, it is possible to carry out various actions that expand the functionality of the mobile device.

For example, it is possible to save battery power on a mobile device by disconnecting from global positioning systems when the user is indoors. Another example is the user alert system for the need for various actions that is built into many mobile devices, depending on the state of the user's mobile device. Another example is the system for adapting the volume of a call and a conversation in a mobile phone depending on whether the user is moving on foot, by car, or is stationary inside a quiet room. The next example is the system of voice call forwarding from a mobile phone to an automatic device, sound reproduction without hands when driving in a car.

Known methods for assessing the state of a user's mobile device include assessment methods based on determining the position of a user's mobile device using global navigation systems, for example (Global positioning system. Standard positioning service, Signal specification, 2th Edition, 46 p., June 2, 1995) [one]. However, the assessment of the user's position is not always possible with the help of such systems, since the signals of global navigation systems are not always available. Moreover, in conditions of multipath propagation of satellite radio signals, the estimation of the position of a user's mobile device can have significant errors. This is especially true for assessing the position of a user's mobile device in large cities. In such cases, of great practical value is the ability to determine certain conditions of a user's mobile device in a wireless communication system in other ways.

Known methods for assessing the state of a user's mobile device can also include assessment methods based on determining the position of a user's mobile device in conjunction with global navigation systems and base station signal strengths (“Location system and method.” Patent Application, GB 2454939 A, date of a publication 05/27/20096 Int. C1. G01S 5/14) [2]. However, as already mentioned, the assessment of the user's position is not always possible with the help of global navigation systems, since the signals of global navigation systems are not always available. Moreover, in conditions of multipath propagation of satellite radio signals, the estimation of the position of a user's mobile device can have significant errors. This is especially true for assessing the position of a user's mobile device in large cities. The power of the signals of base stations can vary greatly depending on various kinds of obstacles, the so-called slow logarithmic fading of the power of radio signals. In this case, errors in the estimates of the position of the mobile device can be hundreds of meters. With such errors, it is impossible to assess the condition of a mobile device located either indoors or outdoors.

Known methods for assessing the state of a user's mobile device include also methods for evaluating signals from miniature built-in mechanical devices, such as a 2D accelerometer ("Techniques for determining communication state using accelerometer data", US Patent application, 2006/0187847 Al, Publication date 24 Aug 2006 - Cisco Technology, Inc., Cl. H04W 4/02) [3]. With the help of an accelerometer it is possible to determine the state of motion or the idle state of a mobile device. The following two disadvantages are inherent in this method. The first significant drawback is that it requires updating the hardware of the mobile device, in fact, creating a new mobile device. This will increase the cost of the mobile device and its incompatibility with existing similar mobile devices. The second drawback is the very high sensitivity of miniature mechanical systems to physical influences. So, if a user drops a mobile device, then the likelihood of a breakdown of a miniature mechanical device built into the mobile device is high.

Known methods for assessing the state of a user's mobile device include also evaluation methods based on statistical analysis of radio signals from base stations in a wireless communication system, for example, "Apparatus and methods using radio signals", US Patent application, 2009/0227271 Al, Publication date 10 Sep .2009, Int. C1. H04L 12/26 [4]. An obvious drawback of this approach is the strong dependence of the level of radio signals of base stations on many uncontrollable factors. This leads to the fact that the reliability of assessing the state of a user's mobile device by the level of radio signals of base stations in a wireless communication system is extremely low. It is possible to increase the degree of reliability of assessing the state of a user's mobile device in a wireless communication system based on the level of radio signals of base stations only by increasing the observation time. With a long observation time, the accumulated statistics allows us to assess the state of the user's mobile device with greater reliability. However, a long observation time (10-15 minutes) leads to severe delays when deciding on the state of the user's mobile device, as a result of which the solution may turn out to be very outdated and even useless.

In view of the above-mentioned disadvantages of the known methods, it is of great practical value to be able to evaluate certain conditions of a user's mobile device in a wireless communication system in other ways that do not require updating the device’s hardware and are based only on updating the software of the mobile device.

The closest in technical essence the solution to the claimed method is a method for assessing the status of a user's mobile device in a wireless communication system described in the report by Ian Anderson, Henk Muller "Context Awareness via GSM Signal Strength Fluctuation", The 4th International Conference on Pervasive Computing, ISBN 3- 85403-207-2, pp. 27-31, May 2006 [5].

The prototype method, which uses at least one base station and at least one mobile device of the user, is as follows:

cyclically during a given period of time (once per second), an assessment is made of the states of the user's mobile device, for which, in each cycle:

on the user's mobile device, the number of transmitting base stations that are in its visibility zone is measured,

measure the signal power from one or more base stations,

summarize the power of the signals received from all base stations, receiving two implementations of the total signal power and the number of base stations,

the obtained two implementations of the total signal power and the number of base stations are transmitted to a pre-configured and trained neural network with eight hidden elements, software-built into the mobile device,

the neural network weighs the obtained two implementations with different weights, forming an assessment of the state of the mobile device that the user's mobile device receives.

The prototype method has the following significant disadvantage.

The prototype method for assessing the state of a mobile station uses the power of the signals of the base stations. As indicated above, the radio signal power from the base station is highly dependent on many uncontrollable factors. This leads to the fact that the reliability of assessing the state of a mobile station by the power of radio signals of base stations in a wireless communication system is extremely low. It is possible to increase the degree of reliability of assessing the state of a mobile station in a wireless communication system based on the power of radio signals from base stations only by increasing the observation time. With a long observation time, the accumulated statistics make it possible to assess the state of the mobile station with greater reliability. However, a long observation time (10-15 minutes) leads to severe delays in deciding on the state of the mobile station, as a result of which the solution may turn out to be very outdated and even useless.

The problem to which the invention is directed is to increase the efficiency of using mobile devices in a wireless communication system by more accurately assessing two states of a user's mobile device - indoors and outdoors in a large metropolis.

The technical result is achieved by developing an improved method for assessing the status of a user's mobile device in a wireless communication system, while the inventive method provides for the following operations:

on a user's mobile device, which contains at least a built-in microphone and a computing module, the microphone is periodically turned on after a predetermined period of time to record external acoustic signals,

by means of a computing module, external acoustic signals are recorded in a file over a predetermined period of time,

at the end of the recording, the recorded file is read and converted into a numerical array of level values of external acoustic signals,

divide a numerical array of values of the level of acoustic signals into adjacent sections of a given length,

for each adjacent section, an indicator of the level of acoustic signals is calculated,

choose a series of a given duration, consisting of consecutive values of the calculated indicators of the levels of acoustic signals,

for the selected row, the minimum value of the indicator of the levels of acoustic signals is selected, which is compared with a given threshold, and a solution is formed from the results of the comparison,

if the minimum value of the indicator of levels of acoustic signals is less than a predetermined threshold, then decide that the user is indoors,

if the minimum value of the indicator of the levels of acoustic signals is greater than or equal to a predetermined threshold, then decide that the user is outdoors.

In this case, for example, a file of the wav format is used as a file.

An indicator of the level of acoustic signals is, for example, the calculated standard deviation of the value of the level of acoustic signals.

The technical solution of the claimed invention is based on the following idea. Acoustic noises on the streets of a large metropolis are very large and have virtually no pauses due to the large number of passing cars and other noise factors. Acoustic noises indoors are caused, as a rule, by the conversation of one or more people. When talking, there are certain short breaks. Therefore, the inventive method for assessing the state of a user's mobile device in a wireless communication system is based on an algorithm for distinguishing acoustic signals indoors and outdoors and implements the idea of “searching for silence”, i.e. searches for short periods of time during which a low level of acoustic signals is observed. If such areas are found, then decide that the user is indoors. Otherwise, they decide that the user is outdoors.

Thus, the claimed method in comparison with the known technical solutions created in this technical field, can significantly increase the efficiency of using mobile devices in wireless communication systems due to a more accurate assessment of the state of the user's mobile device.

The description of the invention is illustrated by examples and drawings.

Figure 1 shows the structural diagram of the algorithm of the proposed method for assessing the status of a mobile device of a user in wireless communication.

Figure 2 shows the characteristic amplitude of the acoustic signals measured inside the office and near the road in the metropolis, where 201 is in the office, 202 is the road.

Figure 3 shows the characteristic autocorrelation functions of acoustic signals measured inside the office and near the road in the metropolis, where 301 is in the office, 302 is the road.

Figure 4 shows the characteristic spectral power density of acoustic signals in decibels, measured inside the office and near the road in the metropolis, where 401 in the office, 402 - the road.

Figure 5 shows the level of acoustic signals, in particular, shows the standard deviation of the acoustic signals measured inside the office and near the road in the city for 4.5 seconds, where 501 in the office, 502 - the road.

Figure 6 shows the moving minima of one hundred consecutive standard deviations of acoustic signals measured inside the office and near the road in the metropolis for 4.5 seconds, and also shows the threshold value, where 601 in the office, 602 is the road, and 603 is the threshold.

The invention is implemented using a mobile device of the user by performing the following sequence of operations provided by the claimed method (Figure 1):

it is assumed that the user's mobile device contains at least a built-in microphone and a computing module (processor module),

on a mobile device, for example, by means of software, a microphone is periodically switched on periodically over a period of time to record external acoustic signals,

by means of a computing module, external acoustic signals are recorded, for example, in a standard wav file for a predetermined period of time,

at the end of the recording, a recorded file is read, for example, of the wav format, and it is converted into a numerical array of level values of external acoustic signals,

divide a numerical array of values of the level of acoustic signals into adjacent sections of a given length,

for each adjacent section calculate the indicator of the levels of acoustic signals, for example the standard deviation of the level of acoustic signals,

choose a series of a given duration, consisting of consecutive values of the calculated indicators of the levels of acoustic signals - standard deviations of the levels of acoustic signals,

for the selected row, the minimum value of the indicator of the levels of acoustic signals is selected, which is compared with a given threshold and a solution is formed from the results of the comparison,

if the minimum value of the indicator of levels of acoustic signals is less than a predetermined threshold, then decide that the user is indoors,

if the minimum value of the indicator of the levels of acoustic signals is greater than or equal to a predetermined threshold, then they decide that the user is outdoors - on the street of a noisy metropolis.

Next, using to illustrate Fig.2-6, consider in more detail the implementation of the proposed method.

It is known that acoustic noise inside the office and near the road in the metropolis can differ markedly in their statistical characteristics. In particular, the level of acoustic noise near a road in a metropolis is usually noticeably higher than the level of acoustic noise in an office. The spectral composition of the noise is also different. Therefore, a rule was formulated to determine two states of the user's mobile device, namely, the state inside the office and the state near the road in the metropolis, based on the measured acoustic signals of the user's mobile device.

Since microphones are built into almost all mobile devices of a user, it is possible to measure acoustic noise without resorting to changing the hardware of mobile devices. By means of a computing module, the measured acoustic signals are recorded in files, for example, in the wav format. Further, from the wav files, the signals are decoded into the original implementation of the strength of the acoustic signals.

For the statistical analysis of acoustic signals, studies were conducted and implementation of such signals was obtained inside the office and near the road in the metropolis.

The sampling frequency for the obtained implementation and the time interval between adjacent samples were selected. Since acoustic noises in the office are essentially unsteady random processes, some characteristic sections were isolated from the implementation and their preliminary classification was carried out.

Figure 2 below shows two characteristic measured implementations of acoustic signals for a situation where the user's mobile device was located indoors - in the office and outdoors - near the road. The sample size was 10,000 samples for each implementation, which corresponds to a implementation duration of 0.45 seconds.

It can be seen from the above implementations that the average amplitudes of acoustic signals indoors - in the office can be either lower or higher than the average amplitudes of signals outside the room - on the side of the road.

Figure 3 shows the characteristic normalized autocorrelation functions of the corresponding acoustic signals. Figure 3 shows that the autocorrelation functions of acoustic signals measured indoors - in the office and outdoors - near the road, do not differ significantly.

, где Fs - частота дискретизации.A generally accepted approach to the analysis of acoustic signals is an approach based on the study of spectral characteristics of acoustic signals rather than correlation. Figure 4 shows the estimated spectral densities of the measured acoustic signals in the frequency band from the minimum frequency of 0 Hz to the maximum Nyquist frequency

where Fs is the sampling rate.

Figure 4 clearly shows that the main energy of the measured signals is concentrated in the frequency range 0-1 kHz. Figure 4 also shows that the spectral composition of acoustic signals inside the office and on the side of the road is somewhat different, however, the patterns of this difference are difficult to determine based on the analyzed limited data set.

From the above Fig.2-4 it follows that the method of assessing the state of the user's mobile device, based on the difference in the correlation or spectral properties of acoustic noise indoors and on the side of the road in the metropolis, should be very difficult due to the similarity of the forms of correlation functions and spectral densities corresponding to to these conditions.

Therefore, it is proposed to implement such a method for assessing the state of a user's mobile device in a wireless communication system, which is based on differences in the magnitude of fluctuations in acoustic signals, for example, indoors - in the office and outdoors - on the side of the road.

We will use, for example, a sample standard deviation of acoustic noise calculated over a given interval as an indicator of the level of acoustic noise.

Denote by x _{t the} realization of acoustic noise. Then, a selective estimate of the level of acoustic signals — the standard deviation of the acoustic signal in the interval L has the form

where µ is the average value of the acoustic signal in the interval L. The algorithm for assessing the state of a user's mobile device consists of the following steps.

Step 1. At this step, K values of the standard deviations of the level of acoustic signals at adjacent intervals are estimated

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The result is the following K standard deviations on adjacent time intervals:

SD ₀ , SD ₁ , ..., SD _K-1 .

In the particular case, you can select the value K = 100. Thus, the total interval during which the decision is made is K · L samples, which correspond to a duration of 4.5 seconds.

Figure 5 shows typical estimates of standard deviations for acoustic signals measured indoors and outdoors near the road. This figure shows that the standard deviations of the acoustic signals measured inside the office can exceed the mean square values of the acoustic signals measured outdoors - close to the road. Therefore, to reduce possible errors in evaluating the state of a user's mobile device, the next step must be performed.

Step 2. At this step, select the minimum value from the K values of the standard deviations of the acoustic signal levels as follows:

SD _min = min {SD ₀ , SD ₁ , ..., SD _K-1 }.

Figure 6 shows the characteristic minimum values of the levels of acoustic signals measured indoors and outdoors near the road. Figure 6 shows that the minimum value of the levels of acoustic signals measured indoors - in the office, do not exceed the minimum value of the levels of acoustic signals measured outdoors - near the road.

Step 3. At this step, compare the minimum values of the levels of acoustic signals with a given threshold h and form a solution based on the results of the comparison. The threshold value is obtained experimentally. The solution is formed as follows.

If the minimum value of the indicator of acoustic signal levels SD _{min is} less than a predetermined threshold h, then a decision is made that the user's mobile device is indoors - in the office.

If the minimum value of the indicator of acoustic signal levels SD _{min is} greater than or equal to a predetermined threshold h, then a decision is made that the user's mobile device is outdoors, close to the road.

Figure 6 shows the characteristic minimum values of the levels of acoustic signals measured indoors - in the office and outdoors - near the road, together with the threshold. Figure 6 shows that the minimum values of the levels of acoustic signals measured indoors - in the office are below a predetermined threshold, and the minimum values of the levels of acoustic signals measured outdoors - near the road are above a predetermined threshold. Therefore, for these specific implementations of acoustic signals, the proposed algorithm of the proposed method makes the right decisions with zero error.

The invention can also be implemented on a user's portable computer according to the described algorithm, while a portable computer requires a microphone and a computing module (processor module), which is practically every computer.

The inventive method has a significant advantage over the inventions known in the art, as it provides greater accuracy in assessing the status of a user's mobile device in a wireless communication system, which improves the efficiency of use of mobile devices in wireless communication systems. This advantage is achieved through the proposed analysis and processing of the level of external acoustic signals measured by a mobile device.

The obtained accurate estimates of the state of the user's mobile device in a wireless communication system allow for various actions that expand the functionality of the mobile device, for example,

- it is possible to save battery energy of the user's mobile device by disconnecting from the global positioning systems when the user is indoors;

- assessments of the conditions of the mobile device can be used by the mobile device to notify the user about the need for various actions depending on the state of the user's mobile device;

- assessments of the conditions of a mobile device can be used by a mobile device to adapt the volume of a call and a conversation in a mobile phone, depending on whether the user is moving on foot, by car, or is stationary inside a quiet room;

- assessments of the conditions of a mobile device can be used by a mobile device to divert a voice call from a mobile phone to an automatic device to play sound without hands when moving in a car,

and state estimates of a mobile device can be used to expand other functionalities of a user's mobile device.

Claims (3)

1. A method for evaluating the conditions of a user's mobile device in a wireless communication system, which consists in the fact that on a user's mobile device, which contains at least a built-in microphone and a computing module, the microphone is periodically turned on to record external acoustic signals through a specified period of time by the computing device writes external acoustic signals to a file for a predetermined period of time, at the end of the recording, the recorded file is read and converted to chi the array of values of the level of external acoustic signals, the numerical array of values of the level of acoustic signals is divided into adjacent sections of a given length, for each adjacent section, an indicator of the level of acoustic signals is calculated, a series of a given duration is selected, consisting of successively calculated values of the calculated indicators of levels of acoustic signals for a selected series choose the minimum value of the indicator of the levels of acoustic signals, which is compared with a given threshold, and according to the result m comparisons conclude the state of the mobile device, namely, if the minimum value of the indicator of levels of acoustic signals is less than a predetermined threshold, then it is assumed that the user is indoors, if the minimum value of the indicator of levels of acoustic signals is greater than or equal to a predetermined threshold, then it is assumed that the user located outdoors. 2. The method according to claim 1, characterized in that the file format is wav. 3. The method according to claim 1, characterized in that the indicator of the level of acoustic signals is the calculated standard deviation of the level value of the acoustic signals.

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