1. Overview
During the planning stage and network optimization of mobile communication networks, the most important propagation issue is path loss, which represents large-scale propagation characteristics and has power law propagation characteristics. Path loss is an important basis for the planning and design of mobile communication systems, and has an impact on the coverage, signal-to-noise ratio, and near-far effect in cellular design. Therefore, path loss prediction is required during the initial planning stage of mobile communication networks, or during future expansion and network optimization. Wireless propagation models are used to predict path loss in different propagation environments, so as to better build local wireless communication networks.
The radio signals sent from the base station not only have the path loss encountered in the atmosphere, but also the path loss of ground propagation, which is greatly affected by the ground topography. The low height of the mobile station antenna, generally very close to the ground plane, is one of the reasons for this additional propagation loss. Generally speaking, the texture and roughness of the ground tend to cause energy dissipation, reducing the received signal strength of the mobile station and the base station. This type of loss, combined with free space loss, together constitutes the propagation path loss.
Mobile radio signals are also subject to a variety of multipath phenomena - they can cause severe signal fading, which originate from the mobile radio communication medium. Mobile radio signal fading includes long-term fading and short-term fading, which are statistical classifications. Long-term fading is generally caused by smaller-scale changes in terrain and objects along the propagation path. Short-term fading is generally caused by reflections from various signal scatterers (both fixed and moving). This type of fading is called "multipath" fading.
It is a very difficult task to accurately characterize the changes in propagating signals in such a complex environment. The various models introduced below predict the changes in wireless signals through a large amount of measured data or accurate electromagnetic theory calculations.
2. Classification of propagation models
In the design of mobile communication networks, a major task is to achieve satisfactory quality coverage, voice quality, call drop rate and connection rate under the condition of meeting the traffic capacity required by mobile users. A large part of this is related to the quality of the received signal, which is mainly determined by the propagation conditions between transmission and reception. In the process of analyzing the radio wave propagation of mobile communications, the propagation path loss is one of the main parameters that people are concerned about. We can use the wireless propagation model analysis method to predict the propagation path loss of radio waves.
According to the nature of wireless propagation models, they can be divided into the following categories:
(1) Empirical model
(2) Semi-empirical or semi-deterministic model
(3) Deterministic model
The empirical model is a formula derived from a large number of test results. The method of predicting path loss using the empirical model is simple and does not require accurate information about the relevant environment, but it cannot provide a very accurate path loss estimate.
Deterministic models are methods that directly apply electromagnetic theoretical calculations to a specific field environment, where the description of the environment is obtained from a database of terrain features, and where different levels of accuracy can be found. In deterministic models, several techniques have been used, usually based on ray tracing methods: geometric diffraction theory, physical optics, and less frequently used exact methods such as the integral equation method or the finite-difference time-domain method. Deterministic wireless propagation prediction is an extremely complex electromagnetic problem in urban, mountainous and indoor environments.
Semi-empirical or semi-deterministic models are based on equations derived by applying deterministic methods to typical urban or indoor environments. Sometimes, to improve their agreement with experimental results, the equations are modified based on experimental results and the resulting equations are a function of some specified characteristic of the area around the antenna.
Due to the diversity of mobile communication environments, each propagation model is designed for a specific type of environment. Therefore, the propagation models can be classified according to their application environment. Three types of environmental cells are usually considered: macro cell, micro cell or micro cell, and pico cell or pico cell.
(1) Macro cell
A macro cell is a large area with a coverage radius of about 1 to 30 km. The base station transmitting antennas are usually erected above surrounding buildings. Usually, there is no direct line of sight between the transmitter and the receiver.
(2) Microcell
The coverage radius of a microcell is between 0.1 and 1 km, and the coverage area is not necessarily circular. The height of the transmitting antenna can be the same as, or slightly higher or lower than, the height of surrounding buildings. Usually, there are two types of situations based on the relative positions of the transmitting and receiving antennas and environmental obstacles: LOS line-of-sight situation and NLOS non-line-of-sight situation.
(3) Picocell
The typical radius of a picocell is between 0.01 and 0.1 km. Picocells can be divided into two categories: indoor and outdoor. The transmitting antenna is under the roof or inside the building. In both indoor and outdoor situations, LOS and NLOS are usually considered separately.
Generally, there is a mutually adaptive relationship between the three types of models and the three types of cells. For example, the empirical model and the semi-empirical model are suitable for macro cells with uniform characteristics, and the semi-empirical formula is also applicable to uniform micro cells. The parameters considered by the model can well characterize the entire environment. The deterministic model is applicable to micro cells and pico cells, regardless of their shape, but it is not applicable to macro cells because the CPU time required for such an environment makes these technologies inefficient.
2.1 Macrocell Propagation Model
2.1.1 Okumura-Hata model
The Okumura-Hata model was obtained by Hata using a formula based on a large amount of Okumura test data. Since the use of the Okumura model requires looking up various curves given by it, it is not conducive to computer prediction. Based on Okumura's basic median field strength prediction curve, Hata proposed an empirical formula for propagation loss through curve fitting, namely the Okumura-Hata model.
The following three assumptions were made in this model for simplicity:
(1) Treat it as the propagation loss between two omnidirectional antennas;
(2) Treat it as quasi-smooth terrain rather than irregular terrain;
(3) Take the propagation loss formula of urban areas as the standard, and use the correction formula for other areas.
Applicable conditions:
(1) f is 150～1500MHz;
(2) the effective height of the base station antenna hb is 30～200m;
(3) the height of the mobile station antenna hm is 1～10m;
(4) the communication distance is 1～35km;
The propagation loss formula is as follows:
Formula Description:
The unit of d is km;
The unit of f is MHz;
L bcity is the median value of basic propagation loss in urban areas;
h b , h m ——effective height of base station and mobile station antennas, in meters;
Calculation of the effective height of the base station antenna: suppose the height of the base station antenna from the ground is hs , the altitude of the base station ground is hg , the height of the mobile station antenna from the ground is hm , and the altitude of the ground at the mobile station location is hmg , then the effective height of the base station antenna is hb = hs + hg - hmg , and the effective height of the mobile station antenna is hm .
Note: There are many methods to calculate the effective height of the base station antenna, such as the average of the ground altitude within 5 to 10 kilometers around the base station; the terrain fitting line of the ground altitude within 5 to 10 kilometers around the base station; etc. Different calculation methods are related to the propagation model used on the one hand, and the calculation accuracy requirements on the other.
Mobile station antenna height correction factor:
Long-range propagation correction factor:
2.1.2 COST-231-Hata model
The COST-231-Hata model is also based on the test results of Okumura et al. and is a formula obtained by analyzing the Okumura propagation curve in the higher frequency band.
Applicable conditions:
(1) f is 1500～2000MHz;
(2) the effective height of base station antenna hb is 30～200m;
(3) the height of mobile station antenna hm is 1～10m;
(4) the communication distance is 1～35km.
Propagation loss formula:
Formula Description:
The unit of d is km, the unit of f is MHz;
L b city is the median value of basic propagation loss in urban areas;
h b , hm ——effective heights of base station and mobile station antennas, in meters;
Calculation of effective height of base station antenna: Let the height of base station antenna from the ground be hs , the altitude of base station ground be hg , the height of mobile station antenna from the ground be hm , and the altitude of the ground where the mobile station is located be hmg . Then the effective height of base station antenna is hb = hs + hg - hmg , and the effective height of mobile station antenna is hm .
Mobile station antenna height correction factor:
Long-range propagation correction factor:
2.2 Microcell Propagation Model
2.2.1 Two-ray model
The two-ray propagation model considers only the contributions of the direct ray and the ground-reflected ray when calculating the field at the receiver. It is adequate for flat rural environments and is also suitable for micro-cells with low base station antennas because there is a LOS path between the transmit and receive antennas. In this case, if the walls of the building also reflect and diffract the radio waves, they will cause rapid changes in the amplitude of the field strength in the simple two-ray model, but will not change the value of the overall path loss power law exponent n predicted by the two-ray.
The path loss given by the two-ray pattern is written as a function of the distance d between the transmitter and the receiver , and can be approximated by two straight line segments with different slopes n 1 and n 2. The abrupt point between the two line segments, also called the inflection point, occurs at a distance from the transmitter of:
Where h r and h t are the heights of the transmitting and receiving antennas respectively.
The path loss can be expressed as follows:
This approximation is called the dual slope model. For the theoretical dual ray ground reflection model, the values of n1 and n2 are 2 and 4 respectively . The measurement results of 1800-1900MHz in urban micro-cells show that the value of n1 is between 2.0 and 2.3, and the value of n2 is between 3.3 and 13.3. Lb is the path loss at the mutation point:
2.2.2 Multi-ray model
Multi-ray models have been used in urban microcells in LOS situations when the transmit and receive antennas are much lower than the rooftop plane. These models assume that the so-called streets are "dielectric canyons" also known as waveguide structures, and the field at the receiver comes from the direct ray between the transmitter and receiver, the reflected rays along the ground, and the rays reflected from the vertical plane of the canyon by the building walls. The two-ray model can be viewed as a multi-ray model that only considers two rays. Four-ray and six-ray models have been proposed: the four-ray model is obtained by adding the direct ray, the ground-reflected ray, and two rays reflected once by the building walls; the six-ray model is the same as the four-ray model, plus two rays reflected twice by the building walls.
2.2.3 Multi-slot waveguide model
When the multi-ray model is used in an urban environment, it is usually assumed that the buildings on the street are arranged continuously with no gaps between the buildings. Blaunstein and Levin proposed a multi-slot waveguide structure model that takes into account the actual dielectric properties of the building walls, the actual distribution of street widths, and the reflections from the road as shown in Figure 1. This model assumes that the urban structure is formed by gaps between two rows of parallel buildings with randomly distributed gaps, and takes into account the direct field, multiple reflections from the building walls, multiple diffraction theory at the corners of the wall, and reflections from the ground.
Figure 1. Multi-slot waveguide model
2.3 Indoor Propagation Model
Experimental studies have shown that within buildings, propagation paths with obstructions (NLOS) will experience Rayleigh fading, and line-of-sight paths (LOS) will experience Ricean fading, regardless of the building type. Ricean fading is caused by the combination of a strong line-of-sight LOS path plus many weakly reflecting ground paths. Building materials, aspect ratios of building sides, and window types have been shown to have an effect on RF attenuation between floors. Measurements have shown that the loss between floors does not increase linearly in decibels with increasing separation distance. Typical values for attenuation between floors are 15 dB for the first layer of separation, and then an additional 6-10 dB for each layer of separation, up to a maximum of 4 layers of separation. For 5 or more layers of separation, the path loss increases by only a few dB for each additional layer.
For systems that use outdoor base stations to cover indoor areas, experimental studies have shown that the signal strength received inside buildings increases with the height of the building. In the lower floors of buildings, there is greater attenuation due to urban agglomerations, so the signal level penetrating into the building is very small. In higher floors, if there is a line-of-sight path, a stronger signal will be generated directly to the outer wall of the building. The penetration loss of the signal is a function of the frequency and the height inside the building. The penetration loss increases with increasing frequency. Measurements show that the penetration loss of a building with windows is 6dB less than that of a building without windows.
2.3.1 Logarithmic distance path loss model
The average path loss is a function of the distance raised to the power of n , as follows:
Where L 50 ( d ) is the average path loss in dB, d is the distance between the transmitter and the receiver in m, L ( d 0 ) is the path loss from the transmitter to the reference distance d 0 , d 0 is the reference distance in m, and n is the average path loss exponent that depends on the environment. The reference path loss can be obtained by testing or by calculating the free space path loss expression.
From the above formula, it is found that the path loss is log-normally distributed. The average path loss exponent n and the standard deviation σ are parameters that depend on the building type, building side, and the number of floors between the transmitter and the receiver. The path loss at the transceiver separation distance d meters can be given as:
L(d )=L 50 (d)+ X σ (dB)
This is an empirical model, where Xσ is a zero-mean log-normally distributed random variable with standard deviation σ(dB ) , representing the influence of environmental features.
2.3.2 Attenuation Factor Model
The previous formula can also be replaced by the following formula:
Where n1 is the path loss exponent on the same floor, which depends on the type of building and its typical value is 2.8; FAF is the floor attenuation factor, which is a function of the number of floors and the type of building.
3. Application of propagation models in cellular design
In wireless cellular design, in order to predict the coverage radius of the base station or the received power link budget of the receiver, the following formula can be used:
P r = P t + G t + G r - L t - L r - L bf
Where, P r and P t are the received power and transmitted power respectively, in dBm; G r and G t are the gains of the transmitting and receiving antennas respectively, in dB; L r and L t are the feeder losses of the uplink and downlink respectively, in dB; L bf is the propagation path loss, in dB. L bf can be predicted by the model introduced above.
In order to improve the prediction accuracy and reduce the workload of wireless network planning engineers, more computer programs are used to predict the propagation loss and the covered area. The prediction of path loss is closely related to the terrain, objects and distance around the base station. Therefore, we can store the terrain, objects and other information in the electronic map, and the computer can call this information at any time during calculation. Figure 2 is an electronic map of a certain place, and different colors in the figure represent different objects.
Figure 2. Electronic map of a place
By inputting the electronic map, base station information, and selecting a suitable model, the software can calculate the receiving power and other information at different distances from the base station and display it on the screen. Figure 3 shows the coverage prediction of a city through the software. Different colors in the figure represent different predicted receiving powers. For example, green in the figure means that the receiving power of the receiver in this area is between -65dBm and -75dBm.
Figure 3. Coverage map of a city. Forward received power.
The reverse coverage can also be predicted by software, as shown in Figure 4:
Figure 4. Coverage map of a city. Mobile phone reverse received power
The above is what I want to share with you. I hope it will be helpful to you~~
Original engineer for this issue: Altair Tang
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