CN113068196A - Heterogeneous network system, sector emptying area interference determination method and application - Google Patents
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Abstract
The invention belongs to the technical field of wireless communication, and discloses a heterogeneous network system, a sector emptying area interference determination method and application. The heterogeneous network system comprises a traditional microwave base station SBS and a millimeter wave base station MBS, wherein the SBS is deployed in a PPP mode and is marked as phisDensity of λsWith a transmission power of Ps(ii) a The MBS is deployed in the MPHP mode and is recorded as phimThe reference process is recorded as
A density of
Transmitting power of Pm(ii) a The equivalent PPP density of MBS is
The power of all transmitting base stations in the same layer is the same; the user UE is deployed in PPP mode and is recorded as phiuDensity of λu. An increase in the average radius of the cells and an increase in the radius of the evacuation sectors and the angle of the centre of the circle lead to different trends in the probability of coverage. In addition, the influence degree of the density change of the two base stations with the same degree on the coverage rate is also different, and the improvement of the coverage rate is facilitated by properly reducing the number of the traditional microwave base stations.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a heterogeneous network system, a sector emptying area interference determination method and application.
Background
In recent years, the explosive growth of mobile data traffic and the spectrum shortage of conventional microwaves have prompted 5G mobile networks to use millimeter waves to achieve greater communication capacity. However, due to the characteristics of high path loss, poor diffraction and high susceptibility to obstacles of millimeter-wave signals, it is difficult to achieve universal coverage using millimeter-wave signals alone. One possible solution is to overlay the mm wave network on the conventional Sub-6GHz network, and provide general coverage and high data rate transmission by using the Sub-6GHz base station and the mmWave base station together. Recently, some research has focused on integrated Sub-6GHz and mmWave cellular networks. By establishing a heterogeneous cellular network in which base stations are K layers of mutually independent Poisson Point Processes (PPP) distributed, some documents research a hybrid cellular network with ultrahigh frequency and millimeter wave and a Device-to-Device (D2D) communication model with hybrid frequency, and it is certain that the hybrid cellular network has better performance compared with a single network.
Although PPP is easy to model for random network processing, it is impractical to assume that the base station locations of different layers are completely uniformly distributed and uncorrelated with each other, and therefore it is necessary to consider designing non-uniform spatially dependent networks. There is literature that considers both the inter-layer dependency and the intra-layer dependency and uses the Poisson Hole Process (PHP) and Thomas Cluster Process (TCP) for modeling. There is also literature deriving the lower bound of the cumulative distribution function of contact distance for PHP in two different cases and comparing it with previous approximations. For the problem that the non-uniform distribution cannot obtain an accurate expression, a density approximation method is mostly adopted in literature to calculate the PHP. Zeinab et al studied the exact characteristics of the interference received by a typical node in PHP, and calculated the PHP as approximating PPP and TCP.
Through the above analysis, the problems and defects of the prior art are as follows: due to the characteristics of millimeter wave signals, a single millimeter wave network cannot achieve a universal coverage range; under the condition that millimeter wave base stations are densely deployed, the conventional PHP model with a circular exclusion area cannot accurately capture the spatial dependence of a network and cannot flexibly deal with the partial spatial dependence which may occur in practice; the existing non-uniformly distributed interference has large calculation error and cannot be accurately analyzed.
The difficulty in solving the above problems and defects is: in order to achieve the optimal coverage range, how to reasonably set the densities of a traditional microwave base station and a millimeter wave base station when the two base stations are in mixed construction; how the relevant parameters of the emptying zone should be determined; how to balance when the influence of different parameters of the system on the performance is different; accurate theoretical analysis of interference generated by the non-uniformly distributed base station is difficult to obtain;
the significance of solving the problems and the defects is as follows: the traditional microwave and millimeter wave are mixed, two base stations are reasonably deployed, universal coverage and high-speed communication are provided at the same time, and the mobile communication requirement is met; the flexible new model can accurately capture partial space dependence conditions, is more practical, and reduces errors between theoretical analysis and a real scene; the interference is measured by using a new method, a new feasible idea is provided for the theoretical analysis of the non-uniform distribution, and the calculation error is reduced.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a heterogeneous network system, a sector emptying area interference determination method and application.
The invention is realized in such a way that a heterogeneous network system comprises a traditional microwave base station SBS and a millimeter wave base station MBS, wherein the SBS is deployed in a PPP mode and is marked as phisDensity of λsWith a transmission power of Ps(ii) a The MBS is deployed in the MPHP mode and is recorded as phimThe reference process is recorded as
A density of
Transmitting power of Pm(ii) a The equivalent PPP density of MBS is
The power of all transmitting base stations in the same layer is the same; the user UE is deployed in PPP mode and is recorded as phiuDensity of λu。
Further, the heterogeneous network system modified poisson hole process MPHP is defined as follows: formed of two separate PPPs, the density being lambda1Is/are as follows
And a density of λ2Phi of2And λ2>λ1；φ1Represents the center of the hole,. phi2Represents the baseline process for MPHP. For phi1At each point in phi, all the points located at phi are removed2∩S(x,D,θc) Point of (1), S (x, D, θ)c) Represents by phi1Is a center, D is a radius, thetacIs a sector of a central angle, then2The remaining points constitute MPHP and are defined as:
further, the directional antenna array assembled by the millimeter wave base station of the heterogeneous network system is approximated to a sector antenna model:
wherein, theta is the beam width of the main lobe, M and M are the main lobe gain and the side lobe gain respectively, perfect beam alignment is provided between the service base station and the typical user, and the main lobe gain is obtained; of interfering linksMillimeter wave base station beam direction is modeled as being at [0,2 π]Uniformly distributed on the upper part; an omnidirectional antenna model is used on a traditional microwave base station and UE, and the gain of the omnidirectional antenna of the traditional microwave base station is Gs。
Further, the line-of-sight model of the heterogeneous network system is based on whether the service base station and the user are visible, the link between the service base station and the user is divided into a line-of-sight (LOS) and a non-line-of-sight (NLOS), LOS probabilities p (r) of different links are mutually independent and defined as the probability that the link with the distance r is LOS; the LOS area is approximated to a radius R by an equivalent spherical modelLThe circle of (c). In this case, p (r) is a step function, i.e.:
further, the channel model of the heterogeneous network system is set as the path loss
αkThe path LOSs index is set as k belongs to { s, L, N }, wherein s, L and N respectively represent path LOSs index subscripts of traditional microwave, LOS millimeter wave and NLOS millimeter wave; all links experience a mutually independent parameter of NkThe small-scale fading of the ith link is denoted as hi，|hi|2To obey to a normalized gamma distribution Γ (N)k，1/Nk) Random variable of, conventional microwave link N s1, the parameters of the millimeter wave LOS and NLOS links are N respectivelyLAnd NN。
Further, the connection strategy of the heterogeneous network system adopts two different connection strategies according to the relative positions of a typical user and a service base station, defines all circular areas with the radius of D and taking SBS as the center as the inner area, and uses AinRepresents; the complementary region is the outer region AoutTypical user is located at AinHas a probability of P (O. epsilon. A)in)＝1-exp(-πλsD2) At a position ofoutHas a probability of P (O. epsilon. A)out)＝exp(-πλsD2) At AinCentral angle thetacThe corresponding sector area is AsectorThen AinThe remaining area of (A) isother(ii) a When the user is at AotherThe shortest path principle is adopted when the region is not the region; when the user is at AotherAdopting a maximum long-term average received power criterion when in a region; the user is located in area AoutIn the middle, the closest MBS is served; when the user is located in sector area AsectorIs served by the nearest SBS; when the user is at AotherArea, served by the base station providing the maximum long-term average received power:
Pk＝arg max PkGklk(x) k∈{s,L,N}。
another object of the present invention is to provide a method for determining interference in a sector evacuation area based on the heterogeneous network system, where the method for determining interference in a sector evacuation area is based on the fact that in a dense urban environment, interference of a nearest PHP evacuation area base station has a main influence on received signals, and when the base station is far away from a user, correlation between the base station and the base station is negligible, and millimeter waves are noise-limited, the reference density is used to calculate interference, and all PHP evacuation areas except the nearest PHP evacuation area are ignored, that is:
S(x,D,θc) Representing the sector-shaped evacuated region, I, corresponding to the SBS nearest the typical userm,sectorRepresenting the interference of the millimeter wave base station in the emptying area, wherein i and j represent the interference subscript on the whole plane and the interference subscript of the nearest emptying area respectively; when the user is at AotherWhen the zone is connected to the MBS, the nearest PHP emptying zone is the emptying zone corresponding to the nearest SBS.
Further, the core calculation formula of the sector emptying area interference determination method is as follows:
the principle of the step a is simple integral calculation, and the direction angle of the fan is [0,2 pi ]]And b, step b is based on a moment mother function of a gamma random variable, and step c uses the same method as that for calculating the circular area. Wherein,
another object of the present invention is to provide a computer apparatus, which includes a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, causes the processor to execute the method for measuring interference in a sector-shaped evacuation area.
Another object of the present invention is to provide an information data processing terminal for operating the heterogeneous network system.
By combining all the technical schemes, the invention has the advantages and positive effects that: the invention adopts the traditional heterogeneous network with space dependence and mixed microwave and millimeter wave, and solves the problems that the single signal of the communication network can not provide general coverage and the base station is uniformly distributed; the invention improves a Poisson hole distribution model, and compared with a circular emptying region distributed by the traditional Poisson holes, the random directivity of the fan-shaped emptying region is more flexible, the invention is more suitable for the actual situation, is more beneficial to capturing partial space dependence, and can be expanded to the circular model of PHP default configuration. On the basis of the model, the invention provides an interference measurement method based on the integration of the nearest sector emptying region, deduces an expression of coverage probability, and a simulation result proves the rationality of the expression, thereby providing a feasible thought for the interference measurement of a non-uniform distribution network. And (5) drawing a conclusion that: the increase in the average cell radius and the sector radius and the central angle results in an opposite change in coverage, requiring a trade-off between the two. In addition, the influence of the density change of two base stations with the same degree on the coverage rate is different, and the increase of the coverage rate is more favorable for properly reducing the density of the traditional microwave base station. The conclusion can help to solve the problems of reasonable deployment and emptying area parameter setting of the mixed spectrum base station, and higher coverage rate is provided.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a schematic diagram of a distribution of heterogeneous conventional microwave and millimeter wave heterogeneous cellular networks according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of interference geometry in a sector evacuation area provided by an embodiment of the present invention.
Fig. 3 is a schematic diagram of SINR coverage variation trend under different conventional microwave base station radii provided by the embodiment of the present invention.
Fig. 4 is a schematic diagram of a coverage rate change rule under different fan radii according to an embodiment of the present invention.
Fig. 5 is a schematic diagram illustrating an influence of a sector central angle on a coverage rate according to an embodiment of the present invention.
Fig. 6 is a schematic diagram for comparing the effect of radius change of the conventional microwave and millimeter wave honeycomb on coverage rate according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In view of the problems in the prior art, the present invention provides a heterogeneous network system, a method for determining interference in a sector evacuation area, and an application thereof, and the present invention is described in detail below with reference to the accompanying drawings.
The technical solution of the present invention is further described below with reference to the accompanying drawings.
1. The system model, Modified Poisson Hole Process (MPHP) is defined as follows: it is composed of two independent PPPs with a density of lambda1Is/are as follows
And a density of λ2Phi of2And λ2>λ1。φ1Represents the center of the hole,. phi2Represents the baseline process for MPHP. For phi1At each point in phi, all the points located at phi are removed2∩S(x,D,θc) A point of (D), here S (x, D, θ)c) Represents by phi1Is a center, D is a radius, thetacIs a sector of a central angle, then2The remaining points constitute MPHP and are defined as:
the invention considers a non-uniform two-layer heterogeneous downlink cellular network, which comprises a traditional microwave Base Station (SBS) and a millimeter wave Base Station (MBS). SBS is assumed to be deployed in PPP and is noted as ΦsDensity of λsWith a transmission power of Ps(ii) a The MBS is deployed in the MPHP mode and is recorded as phimThe reference process is recorded as
A density of
Transmitting power of Pm. The equivalent PPP density of MBS is
The power of all transmitting base stations within the same layer is the same. The user UE is deployed in PPP mode and is recorded as phiuDensity of λu. Without changing the statistical properties, according to Slivnyak theory, it is assumed that the representative user is located at the origin. FIG. 1 showsThe distribution of non-uniform conventional microwave and millimeter wave heterogeneous cellular networks is contemplated. In the figure, the blue circle is SBS, the sector is D in radius and theta in central anglecThe evacuated region of (a). Red dots are MBS deployed outside the drainage zone.
2. Beam forming, in the above model, a directional antenna array assembled by a millimeter wave base station is approximated to a sector antenna model, that is:
where θ is the beam width of the main lobe, and M are the main lobe gain and the side lobe gain, respectively. The main lobe gain is obtained assuming perfect beam alignment between the serving base station and the typical user. The millimeter wave base station beam direction of the interfering link is modeled as being at [0,2 π]Are uniformly distributed. Meanwhile, it is assumed here that an omni-directional antenna model is used on the conventional microwave base station and UE. Gain of traditional microwave base station omnidirectional antenna is Gs。
3. The line-of-sight model is based on whether the serving base station and the subscriber are visible, and the link between the serving base station and the subscriber is divided into line of sight (LOS) and non-line of sight (NLOS). The LOS probabilities p (r) of different links are independent of each other, and are defined as the probability that a link with distance r is LOS. The invention adopts an equivalent sphere model to approximate the LOS area to a radius RLThe circle of (c). In this case, p (r) is a step function, i.e.:
4. the channel model is characterized in that two networks with different frequency bands exist in the model. Path loss is set as
αkAnd k belongs to { s, L, N }, wherein s, L and N respectively represent path LOSs index subscripts of the traditional microwave, LOS millimeter wave and NLOS millimeter wave. It is assumed here that all links experience a mutually independent parameter of NkNakagami-m fading. The small scale fading of the ith link is denoted as hi，|hi|2To obey to a normalized gamma distribution Γ (N)k，1/Nk) Is determined. The traditional microwave link parameter is NsAnd N iss1, the parameters of the millimeter wave LOS and NLOS links are N respectivelyLAnd NN. In addition, the present invention ignores large scale fading because the blocking effect experienced by millimeter waves produces a similar effect to the shadowing effect.
5. Connection strategies, the model adopts two different connection strategies according to the relative positions of a typical user and a service base station. Define all circular areas with radius D centered on SBS as inner area, use AinRepresents; its complement region is the outer region Aout. Then the typical user is located at ainHas a probability of P (O. epsilon. A)in)＝1-exp(-πλsD2) At a position ofoutHas a probability of P (O. epsilon. A)out)＝exp(-πλsD2). In AinCentral angle thetacThe corresponding sector area is AsectorThen AinThe remaining area of (A) isother. When the user is at AotherThe shortest path principle is adopted when the region is not the region; when the user is at AotherThe maximum long-term average received power criterion is adopted when the area is in the area. The user is located in area AoutWhen in middle, it will be served by the nearest MBS; when the user is located in sector area AsectorIt will be served by the nearest SBS. When the user is at AotherWhen in zone, it will be served by the base station providing the maximum long term average received power, i.e.:
Pk＝arg max PkGklk(x) k∈{s,L,N} (3)
the invention further assumes that the link between the typical user and the MBS is LOS, and the corresponding path LOSs exponent is alphaL. This assumption is only for ease of analysis, and the results for the NLOS case can also be obtained using the same method.
The technical solution of the present invention is further described below with reference to performance analysis.
The invention considers a typical user and analyzes the connection probability and the SINR coverage probability of the downlink aiming at the traditional microwave and millimeter wave mixed heterogeneous network.
1. And in the signal-to-interference-and-noise ratio analysis, due to the orthogonality of the frequency bands of the two layers of the mixed network in the model, different layers do not interfere with each other. When a typical user is connected to the k-th layer, the received downlink SINR is:
wherein
Being thermal noise, IkInterference for base stations in the same layer, ILAnd INRespectively representing the interference of LOS and NLOS millimeter wave base stations, | hi|2Is the small scale fading of the ith link independent of each other.
2. Distance distribution and correlation analysis
2.1 distance distribution
The serving base station to which a typical subscriber is connected is either the nearest conventional microwave base station or the nearest LOS millimeter wave base station, depending on the connection policy. Here, R is used individuallysAnd RmTo indicate the distance of a typical user to the nearest conventional microwave and LOS millimeter wave base stations. The Cumulative Distribution Function (CDF) and Probability Density Function (PDF) for the three Distribution cases are as follows:
when a typical user is located within a circle:
when a typical user is located in sector area AsectorWhen the distance distribution is consistent with the distribution when the distance distribution is within the circle, namely:
when a typical user is located outside the circle:
wherein,
the approximation of equation (10) is reasonable as long as the typical user is not particularly close to the edge of the evacuated area. DLRepresenting the probability of observing at least one LOS millimeter wave base station within line of sight.
When a typical user is located in other area AotherWhen R issDistribution of (2)
The invariance is consistent with equation (8). RmIs changed when R is changedmCDF and PDF are respectively:
equation (12) is because a typical user is located within a circle and DLAre events that are independent of each other.
2.2 connection probability analysis
The maximum long-term average received power criterion is only applied to a typical userotherThe area is used. Here, A is usedsAnd AmRepresenting the probability of a typical user connecting to SBS and MBS, respectively. Then:
wherein,
formula (14) is according to
The upper bound is because the distance of two base stations to a typical user cannot exceed D. In the same way, AmCan be obtained by the same method.
2.3SINR coverage probability
According to the division into planar regions, the SINR coverage probability P will be calculated according to the following formulacov：
Typical user is located at AsectorAnd AotherThe probabilities of the regions are:
three parts of conditional coverage probabilities are calculated separately below.
When a typical user is located in a sector:
wherein
Is a laplace transform of a probability density function of the variable X. Note that r heres≤D。
Will calculate
Step a in equation (19) is due to small-scale fading h of all interfering linksiAre independently distributed. Step b generates a Functional (PGFL) according to the Probability of the PPP process, and step c generates a Function (MGF) based on the Moment mother Function of the exponential random variable. The lower limit of integration is due to the fact that the distance between the nearest interferer and the typical user is greater than rs。
When a typical user is located at AoutWhen zone, approximate density is adopted
And (6) performing calculation. The conditional coverage probability is as follows:
the formula (20) uses the approximate density for calculation, and uses
To approximate Im. Suppose NLIs a positive integer and is a non-zero integer,
step b is based on the theorem of binomial expression,
the following calculation
Equation (21) step a is because all LOS and NLOS base stations are independently distributed, and step b follows the probability generation functional of the PPP procedure.
Suppose that the interference over the entire plane is
The interference of LOS base station and the interference of NLOS base station can be divided into two cases, and the interference of base stations of two different links is respectively divided into two cases because of different gains G of directional antenna. The independence of different base stations and the randomness of antenna gain cause the first part to interfere
Can be split into a sum of 4 partial interferers. As used herein
And
respectively represent LOS and NLOS millimeter wave base station sets with antenna gain G, and the following forms are adopted:
wherein
And
are respectively as
And
the medium antenna gain is the sum of the base station interference of G. The millimeter wave base stations with different antenna gains form 2 independent poisson point processes, and the densities of the poisson point processes are respectively
PGThe probability of the antenna gain being G for the beamforming part.
Thus, it is possible to provide
The calculation is as follows:
equation (23) is based on the independence of the interference of each part and the gamma random variable | hi|2The difference between the upper and lower integral bounds is based on the line-of-sight model.
When a typical user is located at AotherThe maximum long-term average received power criterion will be used. In this case, when a typical user connects to SBS, its interference situation is consistent with the situation located in the sector area, i.e. equation (18); when typical user connects MBS, the interference condition and the nearest distance distribution change, the invention adopts a brand newTo calculate the interference experienced by a typical user. Unlike the method using approximate density, the present invention uses a new method of integrating the nearest sector-shaped evacuated region to calculate the disturbance, using the reference density to calculate the disturbance, but ignoring all PHP evacuated regions except the nearest PHP evacuated region. When a typical user connects to the MBS, its nearest PHP draining area is the draining area corresponding to the nearest SBS. The method is based on the simple fact that in dense urban environments, the nearest PHP drain region has a major influence on the received signal, and the correlation between the base station and the user is negligible when they are far away from the user, while the millimeter waves are interference limited, so it is sufficient to consider only the influence of the nearest drain region, i.e.:
where x represents the distance of SBS closest to the typical user, then S (x, D, θ)c) Refers to the sector evacuation area, I, corresponding to the SBS nearest to the typical userm,sectorRepresenting the interference of the millimeter wave base station in the emptying area, and i and j respectively represent the interference index on the whole plane and the interference index of the nearest emptying area.
Referring to equation (20), the conditional coverage probability at this time is of the form:
here smThe expression is the same as the above formula (20). Will calculate next
For ease of representation, the perturbation is written here in another form:
then:
equation (27) step a is based on the interference over the entire plane minus the interference of the nearest sector. The first partial integration region is R2\B(0,rm) Because the distance r from the millimeter wave base station closest to the typical user ism，B(0,rm) Representing the center of origin with radius rmThe circular area of (a).
The values of the last two parts of equation (27) are calculated separately below. The first part represents the interference over the whole plane
Is performed by the laplace transform.
Is similar to equation (23) except that the density is changed.
The first part is therefore calculated as:
reference calculation first part
The second part I is calculated as followsm,sectorIs performed by the laplace transform. Similar to
Im,sectorAnd can be separated into 4 parts which are independent of each other, and the description is omitted here. When a reference density is used, typical users experience more interference than the sector-shaped emptying region, and therefore the present invention uses a method based on integrating the most recently emptied sector-shaped region to calculate the interference.
A detailed description of this method is given below. FIG. 2 illustratesThe spatial geometry between a typical user, SBS and corresponding interference. As shown in fig. 2, the three vertices of the triangle are respectively any interference in the typical user, SBS and corresponding evacuated area. x, r and u are distances between the three, and r is (u)2+x2-2uxcos(φ))1/2Phi and t are two different included angles, respectively. The core calculation formula of the interference determination method of the sector emptying area is as follows:
equation (29) derives the mm-wave base station interference in the nearest sector exclusion zone. The first lower bound of the re-integration is based on the joint probability analysis, step a is a simple calculation of the integral, and the direction angle of the fan is at 0,2 pi]The step b is obtained by the same method as the formula (23), and the step c is obtained by the same method as the method for calculating the circular area. Wherein,
then the second part Im,sectorLaplace transform of (a):
to this end, when a typical user is located at AotherConditional coverage probability P (SINR) in region>γο∈Aother) All calculations are complete.
Then P finally obtainedcovThe following were used:
the symbols and expressions related to formula (31) are described above and are not described in detail here.
The technical effects of the present invention will be described in detail with reference to simulations.
The Monte Carlo simulation is carried out on the proposed heterogeneous network model, and the influence of different system parameters on the network performance is analyzed. It can be known from the figure that under the condition of a low signal to interference and noise ratio threshold, the simulation result is better fitted with mathematical analysis, and when the threshold is higher, the difference between the simulation result and the mathematical analysis is still within the allowable range of error, which shows the reasonability of the expression. Table 1 is the default parameters used for the simulations.
TABLE 1 simulation parameters Table
The effect of different SBS base station densities on SINR coverage is discussed first. Here the average cell radius r is usedoInstead of the base station density. When the density of the base station is lambda, the average cell radius is
Then, the cell radii of the SBS and MBS base stations are respectively
And
FIG. 3 shows P for different SBS cell radiuscovAnd (5) a trend of change. As can be seen from fig. 3, as the decoding threshold is continuously increased, the coverage probability is gradually decreased; as the density of conventional microwave base stations increases, the cell radius decreases, PcovAnd correspondingly decreases. This is because the increase in interference causes a decrease in the probability of coverage without the received power being constant, in which case increasing the base station density does not favor Pcov。
Secondly, in order to research the influence of the emptying area on the network performance, the relationship between the coverage rate and the signal-to-noise ratio under the two conditions of the same central angle, different emptying radiuses and the same radius and different central angles is analyzed. FIG. 4 is a graph of the effect of different fan radii on coverage for the same central angle. It can be seen that as the evacuation radius increases, PcovGradually decreases. This is because the power of the signal received by the user does not offset the increased path loss associated with a longer communication link, although as the radius increases. Meanwhile, the increase of the radius causes the average density of the millimeter wave base stations around the user to gradually decrease, the possibility of connecting to the millimeter wave base stations is reduced, and the coverage rate is also reduced. Fig. 5 shows that as the central angle increases, the signal coverage decreases but the magnitude of the change is not large. Comparing the two figures shows that the change in the central angle of the sector has less influence on the probability of coverage than the change in the evacuation radius. This figure also demonstrates the above analysis of the change in the average density of the millimeter wave base stations.
Finally, the density changes of different base stations with the same degree under the condition of constant signal to interference and noise ratio threshold are compared with PcovThe degree of influence of (c). FIG. 6 shows the cell radius and P for different base stations with a threshold of 10dBcovThe relationship (2) of (c). As can be seen from fig. 6, the density change of the millimeter wave base station has little influence on the performance, while the curve of the conventional microwave base station rises rapidly and then levels off gradually. This is because in a dense urban environment, most millimeter wave signals are NLOS, and even if the interference link is interrupted due to severe attenuation, the interference does not change to a great extent even if the density of the base station is reduced; conventional microwaves are not so limited. Thereby resulting in different impact on performance when different base station densities vary.
In summary, the following conclusions are drawn: the increase in the average cell radius and the increase in the radius of the area to be emptied and the sector center angle have opposite effects on the coverage probability, so that a tradeoff between the two radii is required when deploying the base station. In addition, the density of the millimeter wave base station is simply changed, which does not have great influence on the coverage rate, but properly reduces the density of the traditional microwave base station, thereby being beneficial to the increase of the coverage rate to a certain extent.
It should be noted that the embodiments of the present invention can be realized by hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided on a carrier medium such as a disk, CD-or DVD-ROM, programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier, for example. The apparatus and its modules of the present invention may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of hardware circuits and software, e.g., firmware.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A heterogeneous network system is characterized in that the heterogeneous network system comprises a traditional microwave base station SBS and a millimeter wave base station MBS, wherein the SBS is deployed in a PPP mode and is recorded as phisDensity of λsWith a transmission power of Ps(ii) a The MBS is deployed in the MPHP mode and is recorded as phimThe reference process is recorded as
A density of
Transmitting power of Pm(ii) a The equivalent PPP density of MBS is
The power of all transmitting base stations in the same layer is the same; the user UE is deployed in PPP mode and is recorded as phiuDensity of λu。
2. The heterogeneous network system of claim 1, wherein the heterogeneous network system modified poisson-cave process MPHP is defined as follows: formed of two separate PPPs, the density being lambda1Is/are as follows
And a density of λ2Phi of2And λ2>λ1；φ1Represents the center of the sector, phi2Reference procedure for representing MPHP for phi1At each point in phi, all the points located at phi are removed2∩S(x,D,θc) Point of (1), S (x, D, θ)c) Represents by phi1Is a center, D is a radius, thetacIs a sector of a central angle, then2The remaining points constitute MPHP and are defined as:
3. the heterogeneous network system of claim 1, wherein said heterogeneous network system millimeter wave base station equipped directional antenna array approximates a sector antenna model:
in which theta is the main lobeThe beam width M and M are respectively a main lobe gain and a side lobe gain, perfect beam alignment is achieved between the service base station and the typical user, and the main lobe gain is obtained; the millimeter wave base station beam direction of the interfering link is modeled as being at [0,2 π]Uniformly distributed on the upper part; an omnidirectional antenna model is used on a traditional microwave base station and UE, and the gain of the omnidirectional antenna of the traditional microwave base station is Gs。
4. The heterogeneous network system of claim 1, wherein the line-of-sight model of the heterogeneous network system is based on whether the links between the serving base station and the subscriber are visible or not, and the LOS probability p (r) of different links are independent and defined as the probability that the link with distance r is LOS; the LOS area is approximated to a radius R by an equivalent spherical modelLWhen p (r) is a step function, i.e.:
5. the heterogeneous network system of claim 1, wherein a channel model of the heterogeneous network system, path loss, is set to
αkThe path LOSs index is set as k belongs to { s, L, N }, wherein s, L and N respectively represent path LOSs index subscripts of traditional microwave, LOS millimeter wave and NLOS millimeter wave; all links experience a mutually independent parameter of NkThe small-scale fading of the ith link is denoted as hi，|hi|2To obey to a normalized gamma distribution Γ (N)k，1/Nk) With a random variable of N as a conventional microwave link parametersAnd N iss1, the parameters of the millimeter wave LOS and NLOS links are N respectivelyLAnd NN。
6. As claimed inThe heterogeneous network system of claim 1, wherein the connection policy of the heterogeneous network system adopts two different connection policies according to the relative positions of a typical user and a serving base station; define all circular areas with radius D centered on SBS as inner area, use AinRepresents; the complementary region is the outer region AoutTypical user is located at AinHas a probability of P (O. epsilon. A)in)＝1-exp(-πλsD2) At a position ofoutHas a probability of P (O. epsilon. A)out)＝exp(-πλsD2) At AinCentral angle thetacThe corresponding sector area is AsectorThen AinThe remaining area of (A) isother(ii) a When the user is at AotherThe shortest path principle is adopted when the region is not the region; when the user is at AotherAdopting a maximum long-term average received power criterion when in a region; the user is located in area AoutIn the middle, the closest MBS is served; when the user is located in sector area AsectorIs served by the nearest SBS; when the user is at AotherArea, served by the base station providing the maximum long-term average received power:
Pk＝argmaxPkGklk(x) k∈{s,L,N}。
7. a sector emptying area interference determination method using the heterogeneous network system of any one of claims 1 to 6, characterized in that, based on the fact that in dense urban environment, the interference of the nearest PHP emptying area base station has a main influence on the received signals, and the correlation between the base stations is negligible when the base stations are far away from the user, and the millimeter waves are noise-limited, the interference is calculated by using the reference density, and all PHP emptying areas except the nearest PHP emptying area are ignored, that is:
S(x,D,θc) Representing a typical userSector evacuation zone, I, corresponding to the nearest SBSm,sectorRepresenting the interference of the millimeter wave base station in the emptying area, wherein i and j represent the interference subscript on the whole plane and the interference subscript of the nearest emptying area respectively; when the user is at AotherWhen the zone is connected to the MBS, the nearest PHP emptying zone is the emptying zone corresponding to the nearest SBS.
8. The method for determining interference in a sector-shaped evacuated area according to claim 7, wherein the core calculation formula of the method for determining interference in a sector-shaped evacuated area is as follows:
the principle of the step a is simple integral calculation, and the direction angle of the fan is [0,2 pi ]]And b, step b is based on a moment mother function of a gamma random variable, and step c uses the same method as that for calculating the circular area. Wherein,
9. a computer device, characterized in that the computer device comprises a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the sector evacuation area interference determination method of claim 7.
10. An information data processing terminal, wherein the information data processing terminal is configured to operate the heterogeneous network system according to any one of claims 1 to 6.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1249651A (en) * | 1998-09-08 | 2000-04-05 | 三星电子株式会社 | Method for calculating coverage area based on antenna radiation pattern in sector base station |
| KR101631411B1 (en) * | 2015-03-26 | 2016-06-16 | 인하대학교 산학협력단 | Method and System for Two-Tier Heterogeneous Cellular Communication Network Model |
| CN106454919A (en) * | 2016-10-25 | 2017-02-22 | 北京科技大学 | Heterogeneous cellular network base station deployment method based on Poisson cluster process |
| CN107612745A (en) * | 2017-10-12 | 2018-01-19 | 北京科技大学 | A kind of method of determination D2D network models and the method for assessing D2D network model performances |
| CN108260132A (en) * | 2018-02-27 | 2018-07-06 | 重庆邮电大学 | The dispositions method of intensive isomery cellular network |
| CN109246714A (en) * | 2018-09-11 | 2019-01-18 | 天津大学 | Wireless sensor network node location mode based on adaptive Poisson disk |
| CN109327851A (en) * | 2018-12-04 | 2019-02-12 | 吉林大学 | Cover the super-intensive isomery cellular network subscriber cut-in method separated with data plane |
| CN110677914A (en) * | 2019-09-30 | 2020-01-10 | 大连理工大学 | Interference suppression method for communication cellular network between underlying devices |
-
2021
- 2021-02-26 CN CN202110217248.3A patent/CN113068196B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1249651A (en) * | 1998-09-08 | 2000-04-05 | 三星电子株式会社 | Method for calculating coverage area based on antenna radiation pattern in sector base station |
| KR101631411B1 (en) * | 2015-03-26 | 2016-06-16 | 인하대학교 산학협력단 | Method and System for Two-Tier Heterogeneous Cellular Communication Network Model |
| CN106454919A (en) * | 2016-10-25 | 2017-02-22 | 北京科技大学 | Heterogeneous cellular network base station deployment method based on Poisson cluster process |
| CN107612745A (en) * | 2017-10-12 | 2018-01-19 | 北京科技大学 | A kind of method of determination D2D network models and the method for assessing D2D network model performances |
| CN108260132A (en) * | 2018-02-27 | 2018-07-06 | 重庆邮电大学 | The dispositions method of intensive isomery cellular network |
| CN109246714A (en) * | 2018-09-11 | 2019-01-18 | 天津大学 | Wireless sensor network node location mode based on adaptive Poisson disk |
| CN109327851A (en) * | 2018-12-04 | 2019-02-12 | 吉林大学 | Cover the super-intensive isomery cellular network subscriber cut-in method separated with data plane |
| CN110677914A (en) * | 2019-09-30 | 2020-01-10 | 大连理工大学 | Interference suppression method for communication cellular network between underlying devices |
Non-Patent Citations (4)
| Title |
|---|
| MEHDI SATTARI，ET.AL: "《A Novel PHP-Based Coverage Analysis in Millimeter Wave Heterogeneous Cellular Networks》", 《 2019 IRAN WORKSHOP ON COMMUNICATION AND INFORMATION THEORY (IWCIT)》 * |
| MEHDI SATTARI，ET.AL: "《A Novel PHP-Based Coverage Analysis in Millimeter Wave Heterogeneous Cellular Networks》", 《2019 IRAN WORKSHOP ON COMMUNICATION AND INFORMATION THEORY (IWCIT)》 * |
| YANGJIE，ET.AL: "《Approximate Coverage Analysis of Heterogeneous Cellular Networks Modeled by Poisson Hole Process》", 《 2018 IEEE 18TH INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY (ICCT)》 * |
| 林雅雄: "《毫米波异构蜂窝网络建模与性能分析》", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
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