CN103533554A - Method for predicting coverage of 4G LTE (Long-Term Evolution) network based on 3G path measurement data - Google Patents
Method for predicting coverage of 4G LTE (Long-Term Evolution) network based on 3G path measurement data Download PDFInfo
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Abstract
A method for predicting the coverage of a 4G LTE (Long-Term Evolution) network based on 3G path measurement data comprises a process for measuring the key coverage indexes of base stations in the existing 3G network and a process for calculating measuring results, wherein the key coverage indexes of each related base station in the existing 3G network are acquired by a test tool, the wireless signal propagation loss of each related base station is calculated, the extra wireless propagation loss, which is caused by frequency variation, of each related base station is measured and calculated according to a freedom space propagation model, the key indexes for evaluating the quality of the 4G LTE network are obtained, a predicting result is obtained, and the predicting result is finally presented by a secondary development tool of a geographic information system. The coverage of the 4G network deployed by the existing 3G network can be predicted, and the deviation degree between the predicting result and a test result after the deployment of an actual test network is within 6dB.
Description
Technical field:
The present invention relates to electricity field, relate in particular to mobile communication technology, particularly a kind of method based on the 3G drive test data prediction 4G LTE network coverage.
Background technology:
At present, telecom operators have all disposed the 3rd ripe third generation mobile communication network.But the 4th third generation mobile communication network (LTE) is about to dispose.For the factors such as investment, intensive construction, rapid deployment, energy-saving and emission-reduction of saving, consider, operator need to be at basic deploy the 4th generation LTE network of existing the 3rd third generation mobile communication network.Because communication standard is different, the equal reason of wireless frequency, be therefore difficult to predict the covering quality after 4G network design is on 3G network.For example, 4G network can bring excess loss to radio propagation with respect to the frequency change of 3G network, thereby affects the covering quality of 4G network.In prior art, the method for prediction 4G network coverage quality has two kinds, and a kind of is based on empirical model Ru Ao village-Ha Ta, Cost231 model carries out coverage prediction to 4G network, because this class model does not support 1km with interior prediction, so it is undesirable to predict the outcome, deviation value is greater than 8dB.And do not possess the prediction of 5 meters of precision.Another kind is that the ray trace model based on 5 meters of precision carries out coverage prediction to 4G network, and deviation value can be controlled at below 8dB, but needs Three-dimensional Numeric Map and the ray trace model supports of 5 meters of precision, is difficult to generally use.
Summary of the invention:
The object of the present invention is to provide a kind of method based on the 3G drive test data prediction 4G LTE network coverage, described this method will solve the technical problem that is difficult to predict 4G network design rear covering quality on 3G network in prior art.
This method based on the 3G drive test data prediction 4G LTE network coverage of the present invention, comprise process and a process that measurement result is calculated of measuring the key covering index of base station in existing 3G network, wherein, in the existing 3G network of described measurement, the key of base station covers in the process of index, the key of utilizing testing tool to obtain each relevant base station in existing network 3G network covers index, calculate the propagation loss of each relevant base station wireless signal, again according to free space propagation model, calculate the extra radio transmission loss that bring due to frequency change each relevant base station, obtain the key index for assessment of 4G LTE network quality, predicted the outcome and presented, in described 3G network, the key of base station covering index comprises pilot signal strength, base station parameters, pilot transmit power and antenna gain, described free space propagation model is as follows:
L=32.44+20*lg(d)+20*lg(f)
Wherein, L is path loss, the dB of unit; D is the distance of future position and base station, the km of unit; F is wireless signal frequency, the MHz of unit,
Then calculate as follows the discrepancy delta L between the path loss producing under 3G and 4G frequency,
ΔL=L
4G-L
3G
Wherein, L
4Gfor the path loss producing under 4G frequency, L
3Gfor the path loss producing under 3G frequency,
Wherein, P
rSRPfor future position Reference Signal Received Power; Pt is 4G LTE network reference channel emission power, and Li ' is the path loss after adjusting.
According to the 4G LTE principle of eating dishes without rice or wine, reference signal signal to noise ratio RS-SINR value is characterized by
Wherein ∑ Pi is the 4G LTE RSRP signal summation of the relevant base station of test point; No is white noise, under normal temperature-and 174dBm.
Further, described testing tool comprises that sweep generator device and device have the computer of 3G network testing software.
Further, after being predicted the outcome, utilize GIS-Geographic Information System to predict the outcome and present in conjunction with map.
Concrete, Computing Principle and the method for excess loss, 4G network-critical quality of evaluation index RSRP, RS-SINR and the downstream rate brought to radio propagation due to frequency change described in the present invention, those skilled in the art all understands, and does not repeat them here.
Operation principle of the present invention is: utilize testing tool (frequency sweep instrument) and 3G network testing software, obtain existing network 3G network from the key covering index Ec of the relevant base station of difference, calculate the propagation loss of each point wireless signal.According to free space model, the extra radio transmission loss that measuring and calculating brings due to frequency change.According to the transmitting power of LTE, each path radio transmission loss that calculate early stage, key index RSRP, the RS-SINR, the speed that calculate assessment LTE network quality are equivalent.By utilizing GIS-Geographic Information System secondary development tool MAPBAISIC establishment relative program, can be completely achieved said method function, and obtain better result and present.
The present invention and prior art are compared, and its effect is actively with obvious.The present invention utilizes testing tool, obtain existing network 3G network from the key covering index of the relevant base station of difference, calculate the propagation loss of each point wireless signal, according to free space propagation model, the extra radio transmission loss that measuring and calculating brings due to frequency change, according to the transmitting power of LTE, each path radio transmission loss that calculate early stage, calculate the key index RSRP for assessment of LTE network quality, RS-SINR, speed is equivalent, finally utilizing GIS-Geographic Information System secondary development tool to present predicts the outcome, after can disposing 4G network to existing 3G network, carry out coverage prediction, predict the outcome and affix one's name to rear test result irrelevance in 6dB with actual tests wet end.
Accompanying drawing explanation:
Fig. 1 is the schematic flow sheet based on 3G drive test data prediction 4GLTE network coverage method of the present invention.
Fig. 2 is 3G, the method for adjustment schematic diagram of 4G different frequency to path loss in the present invention.
Fig. 3 mainly covers index, the mapping relations figure of RSRP, RS-SINR, up-downgoing speed based on a large amount of test 4G LTE systems in the present invention.
Fig. 4 is that of the present invention predicting the outcome schemed with contrasting of actual test result.
Fig. 5 be of the present invention predict the outcome with actual test result another according to figure.
Embodiment:
Embodiment 1:
As shown in Figure 1, Figure 2, Figure 3 and Figure 4, of the present invention this based on 3G drive test data prediction 4GLTE network coverage method, first, by the test to existing network, obtain 3G relevant test data; Secondly by theoretical and actual test, contrast, propose from the loss of 3G network radio transmission to 4G propagation loss to conversion; The Forecasting Methodology of 4G network coverage quality is proposed again; Last put forward the methods is realized means and presentation mode.
Further, 3G relevant test data comprises the relevant parameters in pilot signal strength Ec, base station of all relevant base stations of future position, pilot transmit power, antenna gain etc.From the loss of 3G network radio transmission to 4G propagation loss, conversion is based on free-space loss model and actual test empirical model.The Forecasting Methodology of 4G network coverage quality comprises utilizing above-mentioned model and LTE system principle, and the prediction of 4G network-critical quality of evaluation index RSRP, RS-SINR, downstream rate is realized.
Operation principle of the present invention is: utilize testing tool (frequency sweep instrument) and 3G network testing software, obtain existing network 3G network from the key covering index Ec of the relevant base station of difference, calculate the propagation loss of each point wireless signal.According to free space model, the extra radio transmission loss that measuring and calculating brings due to frequency change.According to the transmitting power of LTE, each path radio transmission loss that calculate early stage, key index RSRP, the RS-SINR, the speed that calculate assessment LTE network quality are equivalent.By utilizing GIS-Geographic Information System secondary development tool MAPBAISIC establishment relative program, can be completely achieved said method function, and obtain better result and present.
Concrete, first utilize testing tool, be generally the test chart that 3G road measuring device and sweep generator obtain relevant base station, estimation range, as shown in the table:
According to the 3G principle of eating dishes without rice or wine, known pilot transmitting power Po is base station transmitting power 15%, can extrapolate this test point and i sector path loss is:
Li=Po-Pi
According to upper table test result and base station configuration parameter, calculate the path loss of this test point and all same carrier frequency sector.
Because 4G network is often used different frequencies from 3G network, according to radio wave free-space loss characteristic, need revise link load, correction value can utilize free-space loss model or actual test relatively to draw and Li '=Li+ Δ L
According to the 4G LTE principle of eating dishes without rice or wine, known reference signal transmitting power Pt and 4G LTE bandwidth, base station total emission power are relevant, and 0.16% left and right that this example is base station transmitting power can dope RSRP intensity and the RS-SINR value of this test point according to formula below
Up-downgoing speed is relevant with the modulation demodulation system of base station assigns resource situation, terminal distance, employing, more complicated, be difficult to by the derivation of equation, but as shown in Figure 3, known according to the test result of 4G LTE try net, up-downgoing speed and RSRP, RS-SINR value have corresponding relation, from RSRP and RS-SINR value, can release corresponding speed interval.
The present invention relates to 3G, the method for adjustment of 4G different frequency to path loss.
Utilize the personal spatial model of radio wave:
L(dB)=32.44+20*lgdkm+20*lgf(MHz)
Calculate the path loss difference Δ L of 3G, the generation of 4G different frequency
ΔL=L
4G-L
3G
The present invention relates to the measuring and calculating that 4G covers key index: RSRP, RS-SINR.
P
RSRP=Pt-Li’
Pr is 4G LTE network reference channel emission power, and Li ' is the path loss after adjusting.
According to the 4G LTE principle of eating dishes without rice or wine, RS-SINR value is characterized by
Wherein ∑ Pi is the 4G LTE RSRP signal summation of the relevant base station of test point; No is white noise, under normal temperature-and 174dBm.
Predict the outcome and run the actual test result of upper 4GLTE and contrast:
The estimation range that the present embodiment is selected is the 4G LTE try net region that operator has opened, utilizes MAPBASIC program means, and said method has been carried out to mass realization.Test according to result as shown in Figure 5.In Fig. 5, discrete point shown in right figure is the RS-SINR value result of utilizing the prediction of this patent method, and as shown in Figure 4, in 10%, RSRP index is because relation is simple for statistics irrelevance, and irrelevance is better than RS-SINR value.What predict the outcome and be greatly better than carrying out with traditional empirical model predicts the outcome, and is also better than the result of utilizing 5m high accuracy map and ray trace model prediction.
Claims (4)
1. the method based on the 3G drive test data prediction 4G LTE network coverage, comprise process and a process that measurement result is calculated of measuring the key covering index of base station in existing 3G network, it is characterized in that: in the existing 3G network of described measurement, the key of base station covers in the process of index, the key of utilizing testing tool to obtain each relevant base station in existing network 3G network covers index, calculate the propagation loss of each relevant base station wireless signal, again according to free space propagation model, calculate the extra radio transmission loss that bring due to frequency change each relevant base station, obtain the key index for assessment of 4GLTE network quality, predicted the outcome and presented, in described 3G network, the key of base station covering index comprises pilot signal strength, base station parameters, pilot transmit power and antenna gain, described free space propagation model is as follows:
L=32.44+20*lg(d)+20*lg(f)
Wherein, L is path loss, the dB of unit; D is the distance of future position and base station, the km of unit; F is wireless signal frequency, and then the MHz of unit calculates the discrepancy delta L between the path loss producing under 3G and 4G frequency as follows,
ΔL=L
4G-L
3G
Wherein, L
4Gfor the path loss producing under 4G frequency, L
3Gfor the path loss producing under 3G frequency.
2. the method based on the 3G drive test data prediction 4G LTE network coverage as claimed in claim 1, it is characterized in that: the described key index for assessment of 4G LTE network quality comprises Reference Signal Received Power RSRP and reference signal signal to noise ratio RS-SINR, and described RSRP calculates as follows:
P
RSRP=Pt-Li’
Wherein, P
rSRPfor future position Reference Signal Received Power; Pt is 4G LTE network reference channel emission power, and Li ' is the path loss after adjusting.
According to the 4G LTE principle of eating dishes without rice or wine, RS-SINR value is characterized by
Wherein ∑ Pi is the 4G LTE RSRP signal summation of the relevant base station of test point; No is white noise, under normal temperature-and 174dBm.
3. the method based on the 3G drive test data prediction 4G LTE network coverage as claimed in claim 1, is characterized in that: described testing tool comprises that sweep generator device and device have the computer of 3G network testing software.
4. the method based on the 3G drive test data prediction 4G LTE network coverage as claimed in claim 1, is characterized in that: after being predicted the outcome, utilize GIS-Geographic Information System to predict the outcome and present in conjunction with map.
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Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9788214B2 (en) | 2015-08-24 | 2017-10-10 | Sercomm Corporation | Method for measurement control and base station using the same |
US10057836B2 (en) | 2015-09-09 | 2018-08-21 | Sercomm Corporation | Smallcell and operating method thereof |
CN108513306A (en) * | 2018-06-12 | 2018-09-07 | 北京中网华通设计咨询有限公司 | Network coverage prediction technique based on test big data |
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WO2022193757A1 (en) * | 2021-03-17 | 2022-09-22 | 中兴通讯股份有限公司 | Network coverage prediction method and device, and computer readable storage medium |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2006105716A1 (en) * | 2005-04-06 | 2006-10-12 | Huawei Technologies Co., Ltd. | A implementing method for planning a network of wireless communication system |
CN102883338A (en) * | 2011-07-11 | 2013-01-16 | 同济大学 | Correction method for propagation model in TD-LTE system |
CN103052081A (en) * | 2012-12-20 | 2013-04-17 | 大唐移动通信设备有限公司 | Network coverage planning method and device of evolution communication system |
-
2013
- 2013-10-21 CN CN201310493521.0A patent/CN103533554A/en active Pending
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2006105716A1 (en) * | 2005-04-06 | 2006-10-12 | Huawei Technologies Co., Ltd. | A implementing method for planning a network of wireless communication system |
CN102883338A (en) * | 2011-07-11 | 2013-01-16 | 同济大学 | Correction method for propagation model in TD-LTE system |
CN103052081A (en) * | 2012-12-20 | 2013-04-17 | 大唐移动通信设备有限公司 | Network coverage planning method and device of evolution communication system |
Cited By (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9788214B2 (en) | 2015-08-24 | 2017-10-10 | Sercomm Corporation | Method for measurement control and base station using the same |
US10057836B2 (en) | 2015-09-09 | 2018-08-21 | Sercomm Corporation | Smallcell and operating method thereof |
CN110731096B (en) * | 2017-11-15 | 2021-06-01 | 华为技术有限公司 | Predicting received signal strength in a telecommunications network using a deep neural network |
CN110731096A (en) * | 2017-11-15 | 2020-01-24 | 华为技术有限公司 | Predicting received signal strength in a telecommunications network using a deep neural network |
CN108513306A (en) * | 2018-06-12 | 2018-09-07 | 北京中网华通设计咨询有限公司 | Network coverage prediction technique based on test big data |
CN108513306B (en) * | 2018-06-12 | 2021-12-14 | 北京中网华通设计咨询有限公司 | Network coverage prediction method based on test big data |
CN108966242A (en) * | 2018-06-26 | 2018-12-07 | 中国联合网络通信集团有限公司 | The covering estimation method and device of narrowband Internet of Things |
CN108966242B (en) * | 2018-06-26 | 2021-10-22 | 中国联合网络通信集团有限公司 | Coverage estimation method and device for narrow-band Internet of things |
CN111225382A (en) * | 2018-11-27 | 2020-06-02 | 中国移动通信集团上海有限公司 | LTE functional characteristic selection method and system |
CN111225382B (en) * | 2018-11-27 | 2023-04-25 | 中国移动通信集团上海有限公司 | LTE functional characteristic selection method and system |
CN111988785A (en) * | 2019-05-21 | 2020-11-24 | 大唐移动通信设备有限公司 | 5G network coverage processing method and device |
CN111988785B (en) * | 2019-05-21 | 2022-04-05 | 大唐移动通信设备有限公司 | 5G network coverage processing method and device |
WO2022193757A1 (en) * | 2021-03-17 | 2022-09-22 | 中兴通讯股份有限公司 | Network coverage prediction method and device, and computer readable storage medium |
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