CN109639375B - Base station electromagnetic radiation prediction method based on regional user distribution - Google Patents
Base station electromagnetic radiation prediction method based on regional user distribution Download PDFInfo
- Publication number
- CN109639375B CN109639375B CN201811616785.XA CN201811616785A CN109639375B CN 109639375 B CN109639375 B CN 109639375B CN 201811616785 A CN201811616785 A CN 201811616785A CN 109639375 B CN109639375 B CN 109639375B
- Authority
- CN
- China
- Prior art keywords
- base station
- electromagnetic radiation
- user
- location
- users
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/373—Predicting channel quality or other radio frequency [RF] parameters
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
Abstract
The invention discloses a base station electromagnetic radiation prediction method based on regional user distribution, which considers the influence of the user distribution in a prediction region on the electromagnetic radiation of a base station, calculates the average user number of different places in the prediction region by establishing a place transfer matrix of users in the prediction region, and calculates the actual emission power of the base station of different places according to the probability distribution of the active user number, thereby obtaining the electromagnetic radiation intensity of different places in the prediction region. The method can quickly and accurately predict and evaluate the electromagnetic radiation intensity of the base station at different places in the prediction area, has a higher reference value for researching the electromagnetic radiation exposure condition of the base station, and has certain social benefits.
Description
Technical Field
The invention relates to a base station electromagnetic radiation prediction method based on regional user distribution.
Background
With the continuous deepening of social informatization degree, wireless communication services are increased explosively, a large number of newly-built base stations are put into use, and great convenience is provided for communication between people and social information. Meanwhile, the communication base station uses electromagnetic waves as information transmission carriers, resulting in a serious electromagnetic radiation problem. The traditional base station electromagnetic radiation research is generally analyzed by combining the maximum transmission power of the base station and the signal duty ratio of the base station, but actually, the base station electromagnetic radiation intensity is related to the user distribution in the coverage area of the base station, and no method for carrying out base station electromagnetic radiation research on the user distribution exists at present.
Aiming at the defects of the prior art, the invention provides a base station electromagnetic radiation prediction method based on regional user distribution. The method considers the influence of user distribution in a prediction area on electromagnetic radiation of a base station, calculates the average user number of different places in the prediction area by establishing a place transfer matrix of users in the prediction area, and calculates the actual emission power of the base station of different places according to the probability distribution of the active user number, thereby obtaining the electromagnetic radiation intensity of different places in the prediction area. Experiments show that the prediction method provided by the invention can accurately predict the electromagnetic radiation intensity of the base station at different places in the area.
Disclosure of Invention
In order to solve the above technical problem, the present invention provides a method for predicting electromagnetic radiation of a base station based on regional user distribution, which comprises the following steps:
1) establishing a place transfer matrix of users in the prediction area;
2) calculating the average user number of different sites in the prediction area according to the site transfer matrix obtained in the step 1) and the total user number in the prediction area;
3) establishing probability distribution of the number of active users at different places in the prediction area, and calculating the actual transmitting power of the base station at different places by combining the average number of users at different places in the prediction area obtained in the step 2);
4) calculating the electromagnetic radiation intensity of different places in the predicted area according to the actual transmitting power of the base station of different places obtained in the step 3).
In the above method for predicting electromagnetic radiation of base station based on regional user distribution, in step 1), the prediction region includes n places, and the place transfer matrix is:
wherein M represents a place transfer matrix, pijThe transition probability represents the probability that the user is transferred from the ith place to the jth place; all transition probabilities in the location transition matrix are obtained by the communication base station user management system.
In the above method for predicting electromagnetic radiation of base station based on regional user distribution, in step 2), the average number of users at different locations is:
in the above formula, NiRepresents the average number of users at the ith location, N is the total number of users in the area, pjiTo transition the probability, representing the probability that the user has transitioned from the jth location to the ith location, pjThe initial probability that a user is located at the jth location is determined by the initial user distribution within the region.
In the foregoing method for predicting electromagnetic radiation of base stations based on regional user distribution, in step 3), actual transmission powers of base stations at different locations are:
in the above formula, PiThe actual transmitting power of the base station of the ith place is expressed in W; n is a radical ofiRepresents the average number of users, P, of the ith locationtRepresents the rated transmitting power of the base station and has the unit of W; m denotes the number of active users, Pi(m) a probability distribution representing the number of active users for the ith site expressed as:
in the above formula, betaiIndicating the user activity at the ith location, the value of which is determined by the particular location.
In the above method for predicting electromagnetic radiation of base station based on regional user distribution, in step 4), the electromagnetic radiation intensities of different locations in the predicted region are:
in the above formula, SiRepresents the electromagnetic radiation intensity of the base station at the ith site, and has the unit of mu W/cm2，PiDenotes the actual transmit power of the base station at the ith location in W, G denotes the gain of the transmit antenna in dB, diWhich represents the distance in meters between the ith location and the base station antenna.
The invention has the beneficial effects that: the influence of user distribution in the prediction area on the electromagnetic radiation of the base station is considered, the average user number of different places in the prediction area is calculated by establishing a place transfer matrix of users in the prediction area, the actual emission power of the base station of different places is calculated according to the probability distribution of the active user number, and the electromagnetic radiation intensity of different places in the prediction area is obtained. The method can be used for rapidly and accurately predicting and evaluating the electromagnetic radiation intensity of the base station at different places in the prediction area, has a high reference value for researching the electromagnetic radiation exposure condition of the base station, and has certain social benefits.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments. The present embodiment is performed on the premise of the present disclosure, and detailed implementation procedures are given, but the scope of the present disclosure is not limited to the following embodiments.
The embodiment predicts the electromagnetic radiation intensity of the WCDMA base station near the student apartment in the university campus, and the experimental measurement equipment for verifying the prediction result is a portable spectrum analyzer Keysight FieldFox N9918A and a periodic logarithmic antenna HyperLOG 60180.
The invention provides a base station electromagnetic radiation prediction method based on regional user distribution, which comprises the following steps:
1) establishing a place transfer matrix of users in the prediction area;
2) calculating the average user number of different sites in the prediction area according to the site transfer matrix obtained in the step 1) and the total user number in the prediction area;
3) establishing probability distribution of the number of active users at different places in the prediction area, and calculating the actual transmitting power of the base station at different places by combining the average number of users at different places in the prediction area obtained in the step 2);
4) calculating the electromagnetic radiation intensity of different places in the predicted area according to the actual transmitting power of the base station of different places obtained in the step 3).
In the step 1), the prediction area includes 5 places of a teaching building, an experimental building, a library, a dining room and a student apartment, and the place transfer matrix obtained by the user management system of the communication base station is:
where M represents a place transition matrix, the ith row and the jth column of which represent the probability that a user will transition from the ith place to the jth place, e.g., the 4 th row and the 5 th column represent the probability that a user will transition from the 4 th place (dining room) to the 5 th place (student apartment) is 0.41.
In step 2), the total number N of users in the prediction area is 31842, and the initial probabilities that the users are located in the teaching building, the experimental building, the library, the dining hall and the student apartment are 0.31,0.09,0.12,0.06 and 0.42, respectively, so the average number N of users in the student apartment is 0.315＝31842·(0.16·0.31+0.19·0.09+0.21·0.12+0.41·0.06+0.03·0.42)≈752
In the step 3), the WCDMA base station rated transmitting power P near the student apartmenttThe probability distribution for the number of active users in a student apartment is 20W:
the actual transmitting power of the WCDMA base station near the student apartment is as follows:
in the step 4), the gain G of the transmitting antenna of the WCDMA base station near the student apartment is 16dB, and the distance d between the student apartment and the base station5Therefore, the predicted value of the electromagnetic radiation intensity of the WCDMA base station in the student apartment is as follows:
in the embodiment, the electromagnetic radiation intensity of the WCDMA base station of the student apartment is measured by using a spectrum analyzer, and the measured value is 2.0138 mu W/cm2The prediction value of the method used by the invention is basically consistent, which shows that the method can realize the accurate prediction of the electromagnetic radiation of the base station at different places in the prediction area, thereby verifying the effectiveness of the method used by the invention.
Claims (4)
1. A base station electromagnetic radiation prediction method based on regional user distribution is characterized by comprising the following steps:
1) establishing a place transfer matrix of users in the prediction area;
2) calculating the average user number of different sites in the prediction area according to the site transfer matrix obtained in the step 1) and the total user number in the prediction area;
3) establishing probability distribution of the number of active users at different places in the prediction area, and calculating the actual transmitting power of the base station at different places by combining the average number of users at different places in the prediction area obtained in the step 2):
in the above formula, PiThe actual transmitting power of the base station of the ith place is expressed in W; n is a radical ofiRepresents the average number of users, P, of the ith locationtRepresents the rated transmitting power of the base station and has the unit of W; m denotes the number of active users, Pi(m) a probability distribution representing the number of active users for the ith site expressed as:
in the above formula, betaiRepresenting the user activity of the ith location, the value of which is determined by the specific location;
4) calculating the electromagnetic radiation intensity of different places in the predicted area according to the actual transmitting power of the base station of different places obtained in the step 3).
2. The method as claimed in claim 1, wherein in step 1), the prediction region includes n locations, and the location transfer matrix is:
wherein M represents a place transfer matrix, pijThe transition probability represents the probability that the user is transferred from the ith place to the jth place; all transition probabilities in the location transition matrix are obtained by the communication base station user management system.
3. The method as claimed in claim 1, wherein in step 2), the average number of users at different locations is:
in the above formula, NiRepresents the average number of users at the ith location, N is the total number of users in the area, pjiTo transition the probability, representing the probability that the user has transitioned from the jth location to the ith location, pjThe initial probability that a user is located at the jth location is determined by the initial user distribution within the region.
4. The method according to claim 1, wherein in the step 4), the electromagnetic radiation intensities of different locations in the area are predicted as follows:
in the above formula, SiRepresents the electromagnetic radiation intensity of the base station at the ith site, and has the unit of mu W/cm2，PiDenotes the actual transmit power of the base station at the ith location in W, G denotes the gain of the transmit antenna in dB, diWhich represents the distance in meters between the ith location and the base station antenna.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811616785.XA CN109639375B (en) | 2018-12-27 | 2018-12-27 | Base station electromagnetic radiation prediction method based on regional user distribution |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811616785.XA CN109639375B (en) | 2018-12-27 | 2018-12-27 | Base station electromagnetic radiation prediction method based on regional user distribution |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109639375A CN109639375A (en) | 2019-04-16 |
| CN109639375B true CN109639375B (en) | 2021-06-22 |
Family
ID=66078594
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811616785.XA Active CN109639375B (en) | 2018-12-27 | 2018-12-27 | Base station electromagnetic radiation prediction method based on regional user distribution |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109639375B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111065109B (en) * | 2020-01-16 | 2023-08-22 | 湘潭大学 | Rural area heterogeneous cellular network base station electromagnetic radiation prediction method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6600456B2 (en) * | 1998-09-21 | 2003-07-29 | Tantivy Communications, Inc. | Adaptive antenna for use in wireless communication systems |
| CN103076505A (en) * | 2012-12-27 | 2013-05-01 | 广东省辐射防护协会 | Three-dimensional space prediction method for electromagnetic radiation of TD-SCDMA (Time Division-Synchronization Code Division Multiple Access) mobile communication base station environment |
| CN104749447A (en) * | 2013-12-31 | 2015-07-01 | 中国移动通信集团广东有限公司 | Method and device for estimating environmental electromagnetic radiation of base station |
| CN108111237A (en) * | 2018-01-25 | 2018-06-01 | 湘潭大学 | A kind of TD-LTE base stations PDCCH channel electromagnetics radiate Forecasting Methodology |
| CN108235364A (en) * | 2018-01-05 | 2018-06-29 | 湘潭大学 | A kind of WLAN based on user is averaged electromagnetic radiation Forecasting Methodology |
-
2018
- 2018-12-27 CN CN201811616785.XA patent/CN109639375B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6600456B2 (en) * | 1998-09-21 | 2003-07-29 | Tantivy Communications, Inc. | Adaptive antenna for use in wireless communication systems |
| CN103076505A (en) * | 2012-12-27 | 2013-05-01 | 广东省辐射防护协会 | Three-dimensional space prediction method for electromagnetic radiation of TD-SCDMA (Time Division-Synchronization Code Division Multiple Access) mobile communication base station environment |
| CN104749447A (en) * | 2013-12-31 | 2015-07-01 | 中国移动通信集团广东有限公司 | Method and device for estimating environmental electromagnetic radiation of base station |
| CN108235364A (en) * | 2018-01-05 | 2018-06-29 | 湘潭大学 | A kind of WLAN based on user is averaged electromagnetic radiation Forecasting Methodology |
| CN108111237A (en) * | 2018-01-25 | 2018-06-01 | 湘潭大学 | A kind of TD-LTE base stations PDCCH channel electromagnetics radiate Forecasting Methodology |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109639375A (en) | 2019-04-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106879016B (en) | A kind of base station electromagnetic radiation prediction technique based on user distribution | |
| Joseph et al. | Urban area path loss propagation prediction and optimisation using hata model at 800mhz | |
| CN109738710B (en) | Base station indoor electromagnetic radiation estimation method based on path loss | |
| CN107181545B (en) | Electromagnetic radiation prediction method for TD-SCDMA base station under channel sharing | |
| Elsawy et al. | Base station ordering for emergency call localization in ultra-dense cellular networks | |
| CN109639375B (en) | Base station electromagnetic radiation prediction method based on regional user distribution | |
| Austin et al. | Modeling the effects of nearby buildings on inter-floor radio-wave propagation | |
| CN109459640B (en) | Scenic spot area base station electromagnetic radiation prediction method | |
| Mahbub | Comparative link-level analysis and performance estimation of channel models for IIoT (industrial-IoT) wireless communications | |
| CN110536255B (en) | Access point transmitting power optimization method based on indoor propagation loss model | |
| Yang et al. | Partition-based analytic evaluation of building wireless performance | |
| Ahaneku et al. | GSM base station radiation level: a case study of University of Nigeria environment | |
| Garba et al. | Assessment of radio-frequency radiation exposure from selected mobile base stations in Kaduna state, Nigeria. | |
| CN111030761B (en) | Electromagnetic radiation prediction method for mountain base station | |
| Tong et al. | A tractable analysis of positioning fundamentals in low-power wide area Internet of Things | |
| Ahaneku et al. | Investigation of electromagnetic radiations by GSM base stations in Nigeria for compliance testing | |
| CN110932804B (en) | Base station average electromagnetic radiation prediction method | |
| Mardeni et al. | Path loss model development for urban outdoor coverage of code division multiple access (CDMA) system in Malaysia | |
| Nahuku et al. | Measurement And Analysis of Radiation Levels From Mobile Phone Base Station in Lilongwe Urban | |
| Sallomi et al. | A novel theoretical model for cellular base station radiation prediction | |
| CN110995380B (en) | Indoor base station electromagnetic radiation prediction method | |
| Ekata et al. | Model for monitoring GSM base station radiation safety in Nigeria | |
| CN115913418A (en) | 5G base station electromagnetic exposure prediction method | |
| Geidam et al. | Evaluation of Radiofrequency Radiation Emissions from Mobile Telephony Base Stations In Geidam Town, Yobe State. | |
| CN108738060B (en) | WLAN electromagnetic radiation prediction method based on joint interference power |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |