CN108235364A - A kind of WLAN based on user is averaged electromagnetic radiation Forecasting Methodology - Google Patents
A kind of WLAN based on user is averaged electromagnetic radiation Forecasting Methodology Download PDFInfo
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- CN108235364A CN108235364A CN201810009482.5A CN201810009482A CN108235364A CN 108235364 A CN108235364 A CN 108235364A CN 201810009482 A CN201810009482 A CN 201810009482A CN 108235364 A CN108235364 A CN 108235364A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/147—Network analysis or design for predicting network behaviour
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Abstract
It is averaged electromagnetic radiation Forecasting Methodology the invention discloses a kind of WLAN based on user, its step are as follows：According to the peaceful probability distribution for being all connected with duration, calculating number of users N in WLAN of the arrival rate of customers of connection WLAN；The probability distribution of number of users N in the WLAN obtained according to step 1 calculates the probability distribution of active users M；The probability distribution of active users M obtained according to step 2, calculates active time total duration, and calculates the duty ratio of WLAN；Maximum electromagnetic radiation intensity is measured using spectrum analyzer, with reference to the duty ratio for the WLAN that step 3 obtains, WLAN is calculated and is averaged electromagnetic radiation intensity.The present invention is by analyzing in wlan system, the number of users of connection, and user averagely connects duration and user conversation active period probability, calculates the duty ratio of WLAN.And predict average electromagnetic radiation intensity using the maximum electromagnetic radiation intensity and duty ratio of WLAN.This method influences evaluation and environmental protection to WLAN electromagnetic radiation environments great reference value, has good social benefit.
Description
Technical field
It is averaged electromagnetic radiation Forecasting Methodology the present invention relates to a kind of WLAN based on user.
Background technology
With popularizing for WLAN (Wireless Local Area Network, WLAN), to WLAN electromagnetic radiation
Strength assessment is more and more important.Main research WLAN electromagnetic radiation situations at present, are all based on measurement.Document《Procedure
for assessment of general public exposure from WLAN in offices and in
wireless sensor network testbed》(L.Verlook,W.Joseph,et al.Procedure for
assessment of general public exposure from WLAN in offices and in wireless
Sensor network testbed [J] .Health Phys., vol.98, pp.628-638,2010.), it analyzes and uses frequency spectrum
Instrument calculates the method for duty ratio in the time domain, and analyzes the parameter setting of frequency spectrograph to duty ratio measuring and electromagnetic radiation intensity
The influence of measurement.Document《Determination of the duty cycle of WLAN for realistic radio
frequency electromagnetic field exposure assessment》(Wout Joseph,Daan Pareit,
et al.Determination of the duty cycle of WLAN for realistic radio frequency
electromagnetic field exposure assessment[J].Prog.Biophys.Mol.Biol.,111
(2013), pp.30-36), the duty ratio of the WLAN under field survey different scenes, such as factory, city, office, countryside
Deng, but above-mentioned document cannot be used for WLAN electromagnetic radiation prediction, if desired for estimate some WLAN electromagnetic radiation size, often
It needs to expend a large amount of man power and material.The electromagnetic radiation size of WLAN actually exists with number of users to be associated with, and number of users is got over
More, portfolio is bigger, and electromagnetic radiation will be bigger, but proposes a kind of solution currently without pertinent literature and patent.
For the deficiencies in the prior art, this patent proposes that a kind of WLAN based on the user electromagnetic radiation that be averaged is predicted
Method, this method connects duration by number of users to being connected to WLAN, averagely and session enlivens probability analysis, obtains work
Jump and enlivens total duration at number of users, finally obtains the duty ratio of WLAN, just can Accurate Prediction WLAN electromagnetic radiation intensities.Pass through reality
It tests and shows that the Forecasting Methodology that this patent proposes accurately can be predicted and be assessed to WLAN electromagnetic radiation.
Invention content
To achieve the above object, the technical solution adopted by the present invention is as follows：A kind of WLAN based on user is averaged electromagnetism spoke
Penetrate Forecasting Methodology, which is characterized in that include the following steps：
1), according to the peaceful probability point for being all connected with duration, calculating number of users N in WLAN of the arrival rate of customers of connection WLAN
Cloth；
2), the probability distribution that number of users is N in the WLAN obtained according to step 1, calculates the probability that active users are M
Distribution；
3), the probability distribution for being M according to the active users that step 2 obtains, calculates active time total duration, and calculate
Go out the duty ratio of WLAN；
4) maximum electromagnetic radiation intensity, is measured using spectrum analyzer, with reference to the duty ratio for the WLAN that step 3 obtains,
WLAN is calculated to be averaged electromagnetic radiation intensity.
A kind of above-mentioned WLAN based on user is averaged electromagnetic radiation Forecasting Methodology, in the step 1), according to connection
The arrival rate of customers of WLAN and Connection Time, quote M/G/ ∞ models, number of users N be random number, the probability distribution of number of users N
For：
N is the number of users reached in formula (1), and unit is a, and λ is arrival rate of customers, and unit is a/hour,It is flat
Duration is all connected with, unit is hour.
A kind of above-mentioned WLAN based on user is averaged electromagnetic radiation Forecasting Methodology, in the step 2), active users M
For random number, Bayesian formula is quoted, under conditions of WLAN user number N is n, the probability distribution of active users M is：
N user reaches mutual indepedent, and is respectively in session active period and session quiet period probability in formula (2)WithBi-distribution is quoted, the probability distribution of active users M is：
M is the quantity of any active ues in formula (3), and unit is a, and n is the number of users reached, and unit is a, and λ is arrived for user
Up to rate, unit is a/hour,For average connection duration, unit is hour,For session active period probability, be handling capacity with
The ratio of transmision peak rate.
A kind of above-mentioned WLAN based on user is averaged electromagnetic radiation Forecasting Methodology, in the step 3), according to step 2
The probability distribution of active users M arrived, calculates active time total duration, and calculation expression is as follows：
τ in formula (4)i(t) the active time length for i-th of user, unit are hour,During for average connection
Long, unit is hour, and m is the quantity of any active ues, unit be it is a,It is handling capacity and transmision peak for session active period probability
The ratio of rate；
And the duty ratio of WLAN is calculated, calculation expression is as follows：
D is expressed as the duty ratio of WLAN in the unit interval in formula (5), and T is expressed as total length of time, and unit is hour.
A kind of above-mentioned WLAN based on user is averaged electromagnetic radiation Forecasting Methodology, in the step 4), utilizes frequency spectrum point
Analyzer measures maximum electromagnetic radiation intensity, and with reference to the duty ratio for the WLAN that step 3 obtains, it is strong to calculate the WLAN electromagnetic radiation that is averaged
It is as follows to calculate the WLAN electromagnetic radiation intensities that are averaged for degree：
E in formula (6)avgRepresent average electromagnetic radiation intensity, unit V/m, EmaxRepresent the maximum electromagnetic radiation of WLAN
Intensity, unit V/m are measured under " maximum is kept " pattern by frequency spectrograph and obtained, D represents the duty ratio of WLAN.
The beneficial effects of the present invention are：This method is when prediction WLAN is averaged electromagnetic radiation, it is contemplated that user is to WLAN
The influence of average electromagnetic radiation, and user is combined to WLAN theory analysis duty ratios, finally obtain the average electricity of more accurately WLAN
Magnetic radiation assessment result.This method can allow people to fully understand the radiation profiles situation of WLAN, and the influence of WLAN environment is and guided to comment
Valency and environmental protection have certain social value.
Description of the drawings
Fig. 1 is flow diagram of the present invention.
Specific embodiment
The present invention is further illustrated with reference to the accompanying drawings and examples.
Objective for implementation of the present invention is IEEE802.11b and 802.11gWLAN, is operated in 2.4GHz frequency ranges, total available bandwidth
For 83.5MHz (2.4GHz~2.483GHz), it is divided into the channel that 13 bandwidth are 22MHz.The model of safe and sound letter company production
Scanning for AT6030D tunes frequency spectrograph (frequency range 9kHz-3GHz) and PCD82_50 omnidirectional antennas, and (frequency range is
It 80MHz-3GHz) forms, antenna factor 30dB/m, cable loss 3dB.
A kind of WLAN based on user of the present invention is averaged electromagnetic radiation Forecasting Methodology, includes the following steps：
1), according to the peaceful probability point for being all connected with duration, calculating number of users N in WLAN of the arrival rate of customers of connection WLAN
Cloth；
2), the probability distribution that number of users is N in the WLAN obtained according to step 1, calculates the probability that active users are M
Distribution；
3), the probability distribution for being M according to the active users that step 2 obtains, calculates active time total duration, and calculate
Go out the duty ratio of WLAN；
4) maximum electromagnetic radiation intensity, is measured using spectrum analyzer, with reference to the duty ratio for the WLAN that step 3 obtains,
WLAN is calculated to be averaged electromagnetic radiation intensity.
In above-mentioned steps 1, duration is all connected with according to the arrival rate of customers of connection WLAN is peaceful, calculates number of users N in WLAN
Probability distribution, including the following contents：
In the present embodiment, in 0.5 hour, arrival rate of customers λ is obtained as 9/hour from router management interface, user
Averagely connect durationIt is 0.28 hour, Poisson distribution is obeyed based on arrival rate of customers, quotes M/G/ ∞ models, Ke Yiji
It calculates, the probability distribution that number of users N is n in WLAN is as follows：
In above-mentioned steps 2, the probability distribution of number of users N in the WLAN obtained according to step 1, calculating active users is
The probability distribution of M, including the following contents：
Bayesian formula is quoted, number of users N is under conditions of n, the probability that active users M is m is expressed in calculating WLAN
Formula is as follows：
It is obtained from router management interface, handling capacity 1.81Mbit/s, transmision peak rate is 3.5Mbit/s, then
The probability distribution that active users M is m calculates as follows：
According to above formula, the desired value of active users m can be calculated, is 1.31.
In above-mentioned steps 3, the active users obtained according to step 2 are the probability distribution of M, calculate active time it is total when
It is long, and the duty ratio of WLAN is calculated, including the following contents：
Active time total duration calculates as follows：
Wherein τi(t) the active time length for i-th of user, unit are hour,It is single for average connection duration
Position is hour, and m is the quantity of any active ues, and unit is a；
The duty ratio of WLAN calculates as follows：
Wherein D is expressed as the duty ratio of WLAN in the unit interval, and T is expressed as total length of time, and unit is hour.
In above-mentioned steps 4, maximum electromagnetic radiation intensity is measured using spectrum analyzer, the WLAN obtained with reference to step 3
Duty ratio, calculate WLAN and be averaged electromagnetic radiation intensity, content is as follows：
The channel that router sends is monitored by frequency spectrograph, in the present embodiment, router, which is operated in 2.4GHz frequency ranges 1, to be believed
On road (centre frequency 2.412GHz, frequency coverage 2.401-2.423GHz).By using frequency spectrograph in " maximum guarantor
Hold " under pattern, maximum electromagnetic radiation intensity is measured as 4.1963V/m, then in conjunction with the WLAN duty ratios obtained in step 3,
Its value is 38.14%, you can calculates the average electromagnetic radiation intensity of WLAN：
In order to prove the validity of invention, we are with the actual average electromagnetic radiation intensity that frequency spectrograph measurement obtains with calculating
Average electromagnetic radiation intensity compare, it is as a result as follows：
| Arrival rate (a/hour) | Electromagnetic radiation predicted value (V/m) | Actual electromagnetic radiometric value (V/m) |
| 9 | 2.5915 | 2.6207 |
By comparison, this patent be averaged to WLAN electromagnetic radiation intensity predicted value and actual measured value it is very consistent, demonstrate,prove
The validity of real invention content.
Claims (5)
- The electromagnetic radiation Forecasting Methodology 1. a kind of WLAN based on user is averaged, which is characterized in that include the following steps：1), according to the peaceful probability distribution for being all connected with duration, calculating number of users N in WLAN of arrival rate of customers of connection WLAN；2) probability distribution of number of users N in the WLAN, obtained according to step 1 calculates the probability distribution of active users M；3), the probability distribution of active users M obtained according to step 2, calculates active time total duration, and calculate WLAN Duty ratio；4) maximum electromagnetic radiation intensity, is measured using spectrum analyzer, with reference to the duty ratio for the WLAN that step 3 obtains, is calculated WLAN is averaged electromagnetic radiation intensity.
- The electromagnetic radiation Forecasting Methodology 2. a kind of WLAN based on user as described in claim 1 be averaged, in the step 1), use Amount N is random number, and the probability distribution of number of users N is：N is the number of users reached in formula (1), and unit is a, and λ is arrival rate of customers, and unit is a/hour,For average connection Duration, unit are hour.
- The electromagnetic radiation Forecasting Methodology 3. a kind of WLAN based on user as described in claim 1 is averaged, in the step 2), Under conditions of WLAN user number N is n, active users M is random number, and the probability distribution of active users M is：M is the quantity of any active ues in formula (2), and unit is a, and n is the number of users reached, and unit is a, and λ is arrival rate of customers, Unit is a/hour,For average connection duration, unit is hour,It is handling capacity and transmission for session active period probability The ratio of peak rate.
- The electromagnetic radiation Forecasting Methodology 4. a kind of WLAN based on user as described in claim 1 is averaged, in the step 3), root The probability distribution of active users M obtained according to step 2, calculates active time total duration, and calculation expression is as follows：τ in formula (3)i(t) the active time length for i-th of user, unit are hour,For average connection duration, unit For hour, m is the quantity of any active ues, unit be it is a,It is handling capacity and transmision peak rate for session active period probability Ratio；And calculate the duty ratio of WLAN：D is expressed as the duty ratio of WLAN in the unit interval in formula (4), and T is expressed as total length of time, and unit is hour.
- The electromagnetic radiation Forecasting Methodology 5. a kind of WLAN based on user as described in claim 1 is averaged, in the step 4), It is characterized in that, maximum electromagnetic radiation intensity is measured using spectrum analyzer, with reference to the duty ratio for the WLAN that step 3 obtains, meter WLAN is calculated to be averaged electromagnetic radiation intensity：E in formula (5)avgRepresent average electromagnetic radiation intensity, unit V/m, EmaxRepresent the maximum electromagnetic radiation intensity of WLAN, Its unit is V/m, is measured and obtained under " maximum is kept " pattern by frequency spectrograph, D represents the duty ratio of WLAN.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109245969A (en) * | 2018-11-27 | 2019-01-18 | 湘潭大学 | A kind of electromagnetic radiation of mobile telephone prediction technique based on microblogging Social behaviors |
| CN109639375A (en) * | 2018-12-27 | 2019-04-16 | 湘潭大学 | A kind of base station electromagnetic radiation prediction technique based on zone user distribution |
| CN109661003A (en) * | 2018-12-11 | 2019-04-19 | 湘潭大学 | A kind of electromagnetic radiation of mobile telephone prediction technique based on news browsing behavior |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2017038284A (en) * | 2015-08-11 | 2017-02-16 | 日本電信電話株式会社 | Radio environment estimation method, radio environment estimation device and radio environment estimation program |
| CN107124238A (en) * | 2017-04-27 | 2017-09-01 | 湘潭大学 | A kind of new TD SCDMA communication base station electromagnetic radiation Forecasting Methodologies |
-
2018
- 2018-01-05 CN CN201810009482.5A patent/CN108235364B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2017038284A (en) * | 2015-08-11 | 2017-02-16 | 日本電信電話株式会社 | Radio environment estimation method, radio environment estimation device and radio environment estimation program |
| CN107124238A (en) * | 2017-04-27 | 2017-09-01 | 湘潭大学 | A kind of new TD SCDMA communication base station electromagnetic radiation Forecasting Methodologies |
Non-Patent Citations (3)
| Title |
|---|
| AMITABHA GHOSH，ET AL.: "Modeling and Characterization of Large-Scale Wi-Fi Traffic in Public Hot-Spots", 《2011 PROCEEDINGS IEEE INFOCOM》 * |
| 官培堃: "CDMA***容量分析与多用户检测技术研究", 《中国优秀博硕士学位论文全文数据库（硕士）信息科技辑》 * |
| 顾竞雄: "无线蜂窝网络中基于业务信息的基站主动存储", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109245969A (en) * | 2018-11-27 | 2019-01-18 | 湘潭大学 | A kind of electromagnetic radiation of mobile telephone prediction technique based on microblogging Social behaviors |
| CN109661003A (en) * | 2018-12-11 | 2019-04-19 | 湘潭大学 | A kind of electromagnetic radiation of mobile telephone prediction technique based on news browsing behavior |
| CN109661003B (en) * | 2018-12-11 | 2022-04-19 | 湘潭大学 | Mobile phone electromagnetic radiation prediction method based on news browsing behaviors |
| CN109639375A (en) * | 2018-12-27 | 2019-04-16 | 湘潭大学 | A kind of base station electromagnetic radiation prediction technique based on zone user distribution |
| CN109639375B (en) * | 2018-12-27 | 2021-06-22 | 湘潭大学 | Base station electromagnetic radiation prediction method based on regional user distribution |
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