CN110677914A - Interference suppression method for communication cellular network between underlying devices - Google Patents

Interference suppression method for communication cellular network between underlying devices Download PDF

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CN110677914A
CN110677914A CN201910937333.XA CN201910937333A CN110677914A CN 110677914 A CN110677914 A CN 110677914A CN 201910937333 A CN201910937333 A CN 201910937333A CN 110677914 A CN110677914 A CN 110677914A
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interference
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exclusion
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CN110677914B (en
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邓娜
陈立波
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Dalian University of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/541—Allocation or scheduling criteria for wireless resources based on quality criteria using the level of interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/14—Spectrum sharing arrangements between different networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/51—Allocation or scheduling criteria for wireless resources based on terminal or device properties
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality

Abstract

An interference suppression method for a communication cellular network between underlying devices belongs to the technical field of wireless communication. The method first performs information collection and modeling. Secondly, a rejection region is set, and interference generated by activated D2D communication and received by cellular users outside the rejection region is reduced by adopting a mixed spectrum allocation mode, so that interference suppression is realized. Thirdly, based on the established model and the interference suppression method, under the exclusion area setting of the given base station, the key performance indexes of the cellular user and the D2D user are evaluated based on three analysis methods proposed by the random geometric theory, so as to find the optimal exclusion area. And finally, making a decision and releasing. The decision making by the invention can be effective in a longer time range, avoids a large amount of complicated calculation and resource consumption caused by frequent decision making, has the advantages of simplicity, rapidness and universality, can obviously reduce signaling overhead and system complexity, and can reduce user burden.

Description

Interference suppression method for communication cellular network between underlying devices
Technical Field
The invention belongs to the technical field of wireless communication, and relates to an interference suppression method for a communication cellular network between underlying devices.
Background
The explosive growth of emerging devices and high-speed applications exacerbates the imbalance between the increasing demand for radio spectrum resources and the limited available spectrum resources. To address this problem, a promising technique is to integrate Device-to-Device (D2D) communication into cellular communication. This is because it has the advantages of high spectral efficiency, low delay and reduced base station load. According to the spectrum sharing schemes of D2D communication and cellular communication, the schemes can be divided into a filling type sharing (overlay) mode and an underlay type sharing (underlay) mode, where the underlay mode has higher spectrum utilization rate, but introduces severe mutual interference, which reduces communication performance. Therefore, it is important to design efficient schemes (such as interference management, resource scheduling and mode switching of D2D) to avoid the adverse effects of the underlying mode and to obtain the corresponding performance advantage interval through a unified analysis framework.
In order to solve the problems of D2D resource scheduling, interference management, and mode switching, a general method is to maximize a certain performance index based on an optimization theory, and then add different limiting conditions to further design an algorithm. The scenes usually focused by the above methods are mostly multiple base stations with fixed positions or only one base station (see the documents: P.S. Bithas, K.Malatassos, and F.Foukalas, An SINR-aware joint model, scheduling, and resource allocation scheme for D2D communications [ J ]. IEEE Transactions on Vehicular Technology,2019,68(5):4949 and 4963.). However, the heterogeneity and the density in the current cellular network make the optimization process more complicated, and the multi-base station model with fixed positions cannot reflect the spatial distribution characteristics of real network nodes, thereby further exciting another type of research based on random geometry theory. For simplicity of analysis, many documents assume that the base station (or cellular user) and the D2D transmitter follow mutually independent homogeneous Poisson Point Process (PPP) (see Y. Wang, M. Haenggi, and Z. tan. SIR statistical distribution of K-tier downlink terrestrial networks with cellular extensions [ J. IEEE Transactions on Communications,2019,67(4): 3069-. However, given the cost constraints of deployment and resource scheduling, it is not practical to assume that the locations of the base stations or transmitters are independent of each other. Thus, to capture the proximity of D2D devices, the D2D user is modeled as a modified Thomas Cluster Process (TCP), where the active cluster center follows the Poisson Hole Process (PHP) (see documents M.Afshift and H.S.Dhillon, Spatial modeling of device-to-device networks: Poisson processor units Hole Process [ C ]. in 201549 a hierarchical reference on Signals, Systems and Computers,2015, pp.317-321.). In addition, the scheduling scheme may also affect the spatial characteristics of the active D2D transmitter locations. For example, in order to study the uplink performance of cellular communication, z.chen et al proposed a D2D link activation method that takes into account the signal-to-interference ratio perception and the setting of exclusion zones around the base station (reference: z.chen and m.koutouris, Decentralized optical access for D2D underlay cells networks J IEEE Transactions on Communications,2018,66(10), pp.4842-4853.). However, the analysis results of this approach are too complex to reduce computational efficiency, and the corresponding activation scheme only protects cellular users from strong interference of the D2D link, without paying attention to the interference of cellular communication to D2D communication. Based on the interference suppression method, the invention provides the interference suppression method for the underlying D2D communication cellular network, downlink cellular transmission and D2D communication can be protected from being influenced by strong interference between the downlink cellular transmission and the D2D communication, and meanwhile, the adopted spatial model is easier to research and optimize key performance indexes.
In consideration of spatial correlation, the invention provides an interference suppression method of an underlying D2D communication cellular network and a matching analysis method based on a random geometric theory. Specifically, each base station is provided with a exclusion area, and only the D2D transmitters outside the exclusion area are in an active state, then under this activation method, the spatial position distribution of the base station and the active D2D transmitters follows the poisson point process and the poisson hole process, respectively. Since the exclusion region destroys the independence of the poisson point process, it is difficult to give an accurate expression of the interference characteristic, and thus it is difficult to search and optimize the optimal exclusion region size under the strategy. Therefore, the present invention proposes to solve the above problems by using a method of deriving a lower bound of interference characteristics and a method of approximating the interference characteristics by using other point processes whose spatial characteristics are similar and easy to analyze. Further, although the exclusion area is set to effectively protect the cellular users in the area from the interference caused by D2D communication, the cellular users outside the exclusion area still experience the interference caused by D2D communication. The performance of the user is worse due to the distance from the serving base station, and the interference caused by D2D communication is added, so the performance is further deteriorated. For this reason, the present invention proposes to use a frequency band independent of the frequency band used for communication in the exclusion zone and D2D communication for cellular users outside the exclusion zone, thereby solving the problem of performance degradation of this part of users due to the introduction of D2D communication.
Disclosure of Invention
In the prior art, when the D2D communication shares a frequency spectrum with the cellular communication, very serious mutual interference is caused, and the communication performance of the user is reduced. In view of the above problems, the present invention provides an interference suppression method for an underlay D2D communication cellular network, and provides a performance evaluation and optimization method matching with the interference suppression method. The interference suppression mode can effectively suppress mutual interference between the D2D communication and the cellular communication.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a method for interference mitigation in an underlay D2D communication cellular network, comprising the steps of:
the method comprises the following steps: information collection and modeling
Step 1.1 collect information: according to different information sources, the process of collecting information by the base station mainly comprises two processes: 1) the user feeds back information to the base station, including user position information and user transmitting power muDAnd whether there is a user with which to initially pair and the communication distance d between it and the paired user. The base station can estimate the density lambda of the initial paired users (potential D2D users) according to the informationDAnd initial cellular user density (i.e., non-paired user) density Λc. 2) The base station obtains other system information through the network side, including a path loss model l (x) and a base station density lambdabBase station transmit power mubAnd the like.
The path loss model l (x) | | x | | non-woven phosphor-αα is a path loss exponent and α>2。
Step 1.2, establishing a model: based on collected information, i.e. base station density lambdabInitial paired user density ΛDAnd initial cell user density ΛcThe spatial position distribution of three network nodes, namely a base station, an initial paired user (potential D2D user) and an initial cellular user (non-paired user) is respectively modeled into three mutually independent network nodes with the density of lambdab、ΛDAnd ΛcPoisson point process model of (1). Under this model, cellular users are typically served by the nearest base station, while D2D users transmit information directly from the D2D transmitter to the D2D receiver (i.e., paired users communicate directly without relaying the information through the base station).
Step two: method for realizing interference suppression
Step 2.1, setting the exclusion zone, reducing the interference from D2D communication to the cellular users in the exclusion zone, and improving the communication performance of the cellular users in the exclusion zone. Specifically, the exclusion area of each base station is set, and this is used as a basis for determining which potential D2D users can be activated: 1) activating potential D2D users outside the exclusion zone; 2) other users, including potential D2D users and the initial cellular user in the exclusion zone, are cellular users. The activated D2D user will be in D2D communication with their pre-paired recipients. In conjunction with the Poisson Process model of the potential D2D user, the active D2D transmitter now obeys the Poisson Hole Process (PHP), denoted as ΦDDensity of λD。
The exclusion zone is: the area of the base station is not more than 1/lambdabMay be a square, circular or other symmetrically shaped area; the area is preferably circular, and when the area is circular, the radius of the circular area is called as exclusion radius, which is expressed as R and has a value range ofIn the meantime.
Step 2.2, a mixed spectrum allocation mode is adopted, so that the interference caused by the activated D2D communication on the cellular users outside the exclusion area is reduced, and the communication performance of the cellular users outside the exclusion area is improved. Specifically, 1) cellular users inside the exclusion zone share the same frequency band or the same frequency spectrum with activated D2D users for communication; 2) cellular users outside the exclusion zone communicate using another frequency band or spectrum that is different (or independent) from the cellular users inside the exclusion zone and the activated D2D users. In this spectrum allocation scheme, cellular users outside the exclusion zone are protected from interference from D2D communications by communicating using a different spectrum than D2D users.
The combination of the above steps 2.1 and 2.2 constitutes the interference suppression method proposed by the present invention.
Step three: performance evaluation and optimization
Step 3.1 evaluation procedure: based on the model established in step 1 and the interference suppression method proposed in step 2, under the exclusion area setting of a given base station, the key performance indexes of cellular users and D2D users are evaluated based on three analysis methods proposed by a random geometry theory, and the evaluation methods are used for finding the size (or the value of the optimal exclusion radius) of the optimal exclusion area.
The exclusion area is set by selecting not less than two values for analyzing the performance of the cellular user and the D2D user in the case of adopting the proposed interference suppression method under the condition of different exclusion areas in the value range of the exclusion radius R, that is, analyzing the gain effect of the proposed interference suppression method under the condition of different exclusion areas.
The key performance indexes include link-level and network-level performance indexes, and are determined according to specific scenes and requirements: 1) the link level indexes comprise link transmission success probability, link average reachable rate, link rate distribution and the like; 2) network level metrics include single user capacity, regional spectral efficiency, network energy efficiency, etc. The performance indicators listed are derived from simple transform transformations based on the statistical distribution of the SIR.
The analysis method refers to three methods for analyzing the statistical distribution of Signal-to-Interference ratios (SIRs) of cellular users and D2D users by using the stochastic geometry theory: 1) the method comprises the steps of giving a theoretical lower bound of signal-to-interference ratio distribution of different types of users based on a Poisson point process of potential D2D users; 2) diluting the Poisson point process to be the same as the Poisson hole process in the step 2.1, and approximating the Poisson hole process to obtain an approximation result of the signal-to-interference ratio distribution of different types of users; 3) and (3) approximating the distribution by adopting a Poisson cluster process with similar spatial characteristics to the Poisson hole process so as to obtain another approximation result of the signal-to-interference ratio distribution of different types of users. The three methods specifically comprise the following steps:
step 3.2, optimizing process: and 3.1, setting different exclusion areas to evaluate key performance indexes by adopting an evaluation process in the step 3.1, selecting an exclusion radius corresponding to a maximum performance value (such as the maximum probability of link transmission success, the maximum network energy efficiency and the like) as an optimal activation area based on an obtained analysis result, and setting the exclusion radius value as a final exclusion area.
Step four: decision making and publishing
Step 4.1 decision making process: based on the user location and the estimated optimal activation region, activation of the D2D user is performed, activating paired users outside the exclusion region as D2D users, with the remaining users being cellular users.
Step 4.2 feedback process: the base station feeds back the classification information to the user, the user works according to the received instruction, and the user switches the working mode and obtains the working frequency band according to the base station scheduling information.
The invention has the beneficial effects that: the interference suppression method of the underlying D2D cellular network and the proposed matching model and evaluation method can effectively suppress the mutual interference existing between cellular communication and D2D communication, and ensure that the communication performance of cellular users is not deteriorated due to the introduction of D2D communication. In particular, the proposed evaluation method is a statistically optimized network-wide approach. The method is significantly different from most existing joint optimization methods based on single-cell optimization or limited multiple cells. For example, the information collected by this method is mostly relatively static (or slowly changing) and does not need to be measured and reported frequently. Therefore, decisions made based on this evaluation method (e.g., optimal exclusion zone size) can be valid over a longer time frame, avoiding the extensive computational and resource consumption introduced by frequent decisions. In conclusion, the interference suppression and evaluation method has the advantages of simplicity, rapidness and universality, can obviously reduce signaling overhead and system complexity, is transparent to users, does not need the users to carry out additional measurement and report, and reduces user burden.
Drawings
FIG. 1 is a schematic diagram of the system architecture of the present invention.
Fig. 2(a) is a base station side work flow diagram of the present invention.
FIG. 2(b) is a user-side workflow diagram of the present invention.
Detailed Description
The following detailed description of the invention refers to the accompanying drawings.
The schematic diagram is shown in fig. 1. The analysis is performed by taking a circular exclusion area as an example, but the invention is not limited to a circle, and can be a square, a sector, a triangle or other irregular shapes.
The specific implementation mode of the base station end comprises the following steps:
the method comprises the following steps: information collection and modeling
Step 1.1: information collection
The base station acquires user related information including user transmitting power, user position information and whether the user has an initial paired user through user report, and estimates the density lambda of the initial paired user (potential D2D user)DAnd initial cellular user density (i.e., non-paired user) density Λc. Transmit power allocation of users, in muDAnd (4) showing. The base station obtains other information, such as a large-scale fading model,non-woven fabric woven with | | | x |)-αFor example, α is the path loss exponent and α>2. Small scale channel fading model, exemplified by Rayleigh fading, i.e. fading factor hxObey an exponential distribution. Obtaining an estimate of base station densityb. Configuration of transmission power of base station by mubAnd (4) showing.
Step 1.2: model building
Information collected according to step 1.1, base station density λbInitial paired user density ΛDAnd initial cell user density ΛcModeling the base station, initial cellular user and potential D2D transmitter (i.e., sender of initial paired user) locations as having a density of λb、ΛDAnd ΛcPoisson Point Process (PPP) phib、ΨDAnd Ψc. Under this model, cellular users are served by the closest base station to the user, while D2D users transmit information directly from the D2D transmitter to the D2D receiver (i.e., paired users communicate directly without relaying the information through the base station).
Step two: interference suppression processing
Step 2.1: D2D activation mechanism based on exclusion zone
And setting the exclusion area, reducing the interference from D2D communication on the cellular users in the exclusion area, and improving the communication performance of the cellular users in the exclusion area. Specifically, a repulsion area with a repulsion radius R is set for the base station as a center, and the transmitters outside the repulsion area are all in an activated state and communicate with a matching receiver D2D. The remaining users, including the potential D2D user and the initial cellular user in the exclusion zone, are both cellular users, served by the base station. The value range of the exclusion radius R satisfies
Figure BDA0002221925280000051
In the meantime. In this setting, the active D2D transmitter obeys the Poisson Hole Process (PHP), denoted as ΦDA density of
Figure BDA0002221925280000052
Step 2.2: hybrid spectrum resource allocation
The spectrum allocation for the investigated underlay D2D communication network is as follows: 1) cellular users inside the exclusion zone share the same frequency band or the same frequency spectrum with activated D2D users for communication; 2) cellular users outside the exclusion zone communicate using another frequency band or spectrum that is different (or independent) from the cellular users inside the exclusion zone and the activated D2D users. In this spectrum allocation scheme, cellular users outside the exclusion zone are protected from interference from D2D communications by communicating using a different spectrum than D2D users.
Step three: performance evaluation and optimization
Step 3.1 Performance evaluation
Since future networks are densely deployed, interference limited networks are considered, i.e. the impact of thermal noise on performance is neglected. Based on the stationarity of the poisson point process, considering only typical cellular users located at the origin may result in an average performance of the cellular users. Likewise, considering only typical D2D transmit-receive pairs located at the origin may result in an average performance for the D2D user. Specifically, the invention takes three indexes of success probability (link level performance index), area spectrum efficiency (network level performance index) and network energy efficiency (network level performance index) of the user as key performance indexes, and one of the indexes can be selected as a basis for searching the optimal exclusion radius R according to the specific performance and requirement concerned at present. (for example, if the transmission reliability is concerned, that is, the reliability requirement is high, the success probability of the user should be selected as the key performance index for optimizing.)
The three indexes of the success probability, the regional spectrum efficiency and the network energy efficiency of the user are specifically defined as follows:
1. probability of success for a user
The success probability of a user can be generally expressed as the probability that the received SIR of the user is greater than a Signal-to-interference ratio (SIR) threshold given the threshold. By adopting the total probability formula, the success probability p of the whole user can be obtainedsIs shown as
Figure BDA0002221925280000061
Wherein
Figure BDA0002221925280000062
For a given cellular user density outside the exclusion zone,
Figure BDA0002221925280000063
and
Figure BDA0002221925280000064
complementary cumulative distribution functions, θ, of the signal-to-interference ratios of cellular users within the exclusion zone, cellular users outside the exclusion zone, and activated D2D users, respectivelycAnd thetaDAre the signal-to-interference ratio thresholds for the cellular user and the D2D user, respectively.
2. Regional spectral Efficiency (ASE)
The regional spectral efficiency is the spectral efficiency that can be achieved per unit area. Based on a given SIR threshold, one can obtain
Figure BDA0002221925280000065
3. Network Energy Efficiency (NEE)
Since the energy consumption of the cellular network mainly comes from the energy consumption of the base station, a linear power consumption model is used for calculating the power consumed by a certain base station, as follows:
ξb＝aμb+w
wherein a denotes the transmission power mubThe efficiency of the power amplifier, w, is the static power consumption (such as circuit power consumption and signal processing) independent of the transmit power, and these parameters can be derived from the network side at step one. Energy efficiency can be defined as the ratio of the spectral efficiency achieved per unit area to the total power consumed and can therefore be expressed as
Figure BDA0002221925280000071
According to the definition of three indexes of success probability of users, regional spectrum efficiency and network energy efficiency, the signal-to-interference ratio is a basic physical quantity reflecting the accessibility of the users and the network, and the analysis of the SIR statistical characteristics of cellular users and D2D users is a necessary way to realize the evaluation of the three indexes. Therefore, it will be explained in detail how to analyze the SIR statistics of cellular users and D2D users based on the established point process model and the proposed interference suppression method. Specifically, the present invention proposes the following three analysis methods: 1) the method comprises the steps that a theoretical lower bound of statistical distribution of signal-to-interference ratios of different types of users is given based on a Poisson point process of potential D2D users (namely initial paired users); 2) diluting the Poisson point process of the active D2D user to be the same as the Poisson hole process in the step 2.1, and approximating the Poisson hole process to obtain an approximation result of the signal-to-interference ratio distribution of different types of users; 3) and (3) approximating the distribution by adopting a Poisson cluster process with similar spatial characteristics to the Poisson hole process so as to obtain another approximation result of the signal-to-interference ratio distribution of different types of users. The specific process is as follows:
3.1.1 theoretical lower bound on the SIR statistical distribution of different types of users based on initial PPP
Since the active D2D users are a subset of the potential D2D users (i.e., the initial pair of users), if all potential D2D users are active, the interference from co-channel D2D users is greater than the actual interference. Therefore, the SIR statistics distribution for different types of users will get a lower theoretical bound.
1. Theoretical lower bound for cellular user SIR statistical distribution inside exclusion zone
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical lower bound of the cellular user SIR statistical distribution (specifically, the complementary cumulative distribution function of SIR) inside the exclusion area is
Figure BDA0002221925280000072
Wherein IbcIs interference from co-channel base stations to cellular users,
Figure BDA0002221925280000073
is the upper bound of interference from co-channel D2D transmitters to cellular users,
Figure BDA0002221925280000074
and
Figure BDA0002221925280000075
are each IbcAnd
Figure BDA0002221925280000076
is expressed as
Figure BDA0002221925280000077
Figure BDA0002221925280000078
Wherein δ is 2/α and
2. statistical distribution of SIR of cellular users outside exclusion zone
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the statistical distribution of the SIR (specifically, the complementary cumulative distribution function of the SIR) of the cellular users located outside the exclusion area is only related to the interference from the co-frequency base station, and an accurate theoretical result can be obtained, which is expressed as
Figure BDA0002221925280000082
Theoretical lower bound of statistical distribution of SIR for 3.D2D users
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical lower bound of the statistical distribution (specifically, the complementary cumulative distribution function of SIR) of the SIR of D2D users is
Figure BDA0002221925280000083
Wherein IbDIs interference from co-channel base stations to D2D users,
Figure BDA0002221925280000084
is the upper bound of interference from co-channel D2D transmitters to D2D users,
Figure BDA0002221925280000085
and
Figure BDA0002221925280000086
are each IbDAnd
Figure BDA0002221925280000087
is expressed as
Figure BDA0002221925280000088
Figure BDA0002221925280000089
3.1.2 approximation of SIR statistical distribution for different types of users based on a diluted PPP model
The activation of D2D users will be approximated as a fairly dense dilution of PPP, then the interference from D2D users is an approximation of the actual interference. Therefore, the SIR statistical distribution of different types of users will get an approximate theoretical result.
1. Cellular user SIR approximate statistical distribution within exclusion zone
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical result of the statistical distribution of the SIR (specifically, the complementary cumulative distribution function of the SIR) of the cellular users located in the exclusion area is approximated to be
Wherein
Figure BDA00022219252800000811
Is an approximation of the interference from the co-channel D2D transmitter to the cellular user, an
Figure BDA00022219252800000812
Is that
Figure BDA00022219252800000813
Is expressed as the Laplace transform of
Figure BDA00022219252800000814
2. Statistical distribution of SIR of cellular users outside exclusion zone
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the statistical distribution of the SIR (specifically, the complementary cumulative distribution function of the SIR) of the cellular users located outside the exclusion area is only related to the interference from the co-frequency base station, and an accurate theoretical result can be obtained, which is expressed as
Figure BDA0002221925280000091
3. Approximation of D2D user SIR statistical distribution based on PPP model
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical result of D2D user SIR statistical distribution (specifically, the complementary cumulative distribution function of SIR) is
Wherein
Figure BDA0002221925280000093
Are from co-channel D2D transmitter pair D2D usersThe approximation of the interference of (a) is,
Figure BDA0002221925280000094
is that
Figure BDA0002221925280000095
Is expressed as
Figure BDA0002221925280000096
3.1.3 approximation of SIR statistical distribution for different types of users based on PCP model
Due to the existence of the exclusion zone, the activated D2D transmitter exhibits clustering in space, and the PCP model with similar clustering characteristics can be used to obtain an approximation of the actual interference. Therefore, the SIR statistical distribution of different types of users will get an approximate theoretical result.
1. Approximation of cellular user SIR statistical distribution inside exclusion zone based on PCP model
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical result of the statistical distribution of the cellular user SIR (specifically, the complementary cumulative distribution function of the SIR) in the exclusion area is approximated to
Wherein IDc,PCPIs an approximation of the interference from the co-channel D2D transmitter to the cellular user, an
Figure BDA0002221925280000098
Is IDc,PCPIs expressed as the Laplace transform of
Wherein the content of the first and second substances,
Figure BDA00022219252800000910
ζ(v, R) is
Figure BDA00022219252800000911
As a region of the disk whose center is R radius, and
Figure BDA00022219252800000912
parameter λ of PCPp,
Figure BDA00022219252800000913
σ2Is obtained by a moment matching method, particularly by nonlinear fitting of the following equation,
Figure BDA0002221925280000101
wherein g (r) is a pairwise correlation function obtained by PHP simulation and is obtained by solving an equation
Figure BDA0002221925280000102
To obtain
Figure BDA0002221925280000103
2. Approximation of cellular user SIR statistical distribution outside exclusion zone based on PCP model
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the statistical distribution of the cellular user SIR (specifically, the complementary cumulative distribution function of the SIR) outside the exclusion area is only related to the interference from the co-frequency base station, and is approximately free of hanging with the PCP, so that an accurate theoretical result can be obtained, which is expressed as
Figure BDA0002221925280000104
3. Approximation of D2D user SIR statistical distribution based on PCP model
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical result of D2D user SIR statistical distribution (specifically, the complementary cumulative distribution function of SIR) is
Figure BDA0002221925280000105
Wherein IDD,PCPIs an approximation of the interference from co-channel D2D transmitters to D2D users, an
Figure BDA0002221925280000106
Is IDD,PCPIs expressed as the Laplace transform of
Figure BDA0002221925280000107
Step 3.2: optimization process
In that
Figure BDA0002221925280000108
N different values R of the activation radius are set between1，R2，R3，…RN，N>And 2, selecting one key performance index and an analysis method in the step 3.1 for each activation radius value, evaluating the selected performance index, researching the relation between the key performance and the exclusion radius, and selecting the exclusion radius value with the maximum performance as the optimal activation area radius.
Step four: decision making and publishing
Step 4.1: decision making process
Based on the user location and the resulting activation area radius, an optimal exclusion area is set, activating paired users outside the exclusion area as D2D users, with the remaining users being cellular users.
Step 4.2: feedback process
And the base station feeds back the user classification information to the users according to the decision of the last step, and allocates frequency bands different from the users in the exclusion area and the D2D users to the users outside the exclusion area. And the user works according to the received instruction, and the user switches the working mode and the working frequency according to the scheduling information of the base station.
As can be seen from the above description, the interference suppression method of the underlying D2D cellular network of the present invention is significantly different from the existing interference suppression schemes. The proposed scheme directly performs physical isolation on the interference sources based on distance, and simultaneously performs further frequency domain isolation on the interference sources which cannot be solved by a physical isolation method from another dimension by combining a spectrum allocation means. The scheme is simple to operate, is convenient for the realization of an actual system, can carry out fine and effective interference suppression on the communication between the cellular user and the D2D, is transparent to the user, and does not increase the burden of the user. In addition, the scheme also provides a limit of success probability and two approximate methods, and provides a quick, effective and accurate evaluation method for calculating the optimal exclusion area size on the base station side. The regional spectral efficiency and energy efficiency can be solved based on the success probability.
The above-mentioned embodiments only express the embodiments of the present invention, but not should be understood as the limitation of the scope of the invention patent, it should be noted that, for those skilled in the art, many variations and modifications can be made without departing from the concept of the present invention, and these all fall into the protection scope of the present invention.

Claims (3)

1. A method for interference mitigation in an underlay D2D communication cellular network, comprising the steps of:
the method comprises the following steps: information collection and modeling
Step 1.1, collecting information: according to different information sources, the process of collecting information by the base station mainly comprises two processes: 1) the user feeds back information to the base station, including user position information and user transmitting power muDAnd whether there is a user with which to initially pair and the communication distance d between it and the paired user; the base station can estimate the initial paired user density Lambda according to the informationDAnd initial cell user density ΛcWherein the initial paired user is a potential D2D user, and the initial cellular user is an unpaired user; 2) the base station obtains other system information through the network side, including a path loss model l (x) and a base station density lambdabBase station transmit power mub；
The path loss model l (x) | | x||-αα is a path loss exponent and α>2；
Step 1.2, establishing a model: based on collected information, i.e. base station density lambdabInitial paired user density ΛDAnd initial cell user density ΛcThe position distribution of three network nodes, namely a base station, an initial pairing user and an initial cellular user, on the space is respectively modeled into three mutually independent network nodes with the density of lambdab、ΛDAnd ΛcThe poisson point process model of (a); under the above model, cellular users are usually served by the nearest base station, and D2D users directly transmit information from the D2D transmitter to the D2D receiver, i.e. paired users communicate directly without relaying the information through the base station;
step two: method for realizing interference suppression
Step 2.1, setting a rejection area, reducing interference from D2D communication to cellular users in the rejection area, and improving communication performance of the cellular users in the rejection area; specifically, the exclusion area of each base station is set and used as a potential D2D user to determine the following two cases: 1) activating potential D2D users outside the exclusion zone; 2) other users including potential D2D users and initial cellular users in the exclusion area are cellular users;
the activated D2D user will be in D2D communication with their pre-paired recipients; combining the Poisson Point Process model of the potential D2D user, at this time, the active D2D transmitter obeys the Poisson cave Process, and is marked as phiDDensity of λD；
The exclusion zone is: the area of the base station is not more than 1/lambdabA region of (a);
step 2.2, adopting a mixed spectrum allocation mode to reduce the interference of cellular users outside the exclusion area, which is generated by activated D2D communication, and improve the communication performance of the cellular users outside the exclusion area; specifically, 1) cellular users inside the exclusion zone share the same frequency band or the same frequency spectrum with activated D2D users for communication; 2) cellular users outside the exclusion zone communicate using another frequency band or spectrum that is different or independent of cellular users inside the exclusion zone and activated D2D users; in this spectrum allocation scheme, cellular users outside the exclusion zone can be protected from interference from D2D communications by communicating using a different spectrum than D2D users;
step three: performance evaluation and optimization
Step 3.1 evaluation procedure: based on the model established in step 1 and the interference suppression method proposed in step 2, under the exclusion area setting of a given base station, the key performance indexes of cellular users and D2D users are evaluated based on three analysis methods proposed by a random geometric theory, and the evaluation methods are used for determining the size of the optimal exclusion area;
the exclusion area is set, so that in the value range of the exclusion radius R, not less than two values are selected for analyzing the performance of the cellular user and the D2D user which can be obtained by adopting the proposed interference suppression method under the condition of different exclusion areas, and the benefit effect of the proposed interference suppression method under the condition of different exclusion areas is analyzed;
the analysis method is three methods for analyzing the statistical distribution of the signal-to-interference ratios of cellular users and D2D users by using a random geometric theory: 1) the method comprises the steps of giving a theoretical lower bound of signal-to-interference ratio distribution of different types of users based on a Poisson point process of potential D2D users; 2) diluting the Poisson point process of the active D2D user to be the same as the Poisson hole process in the step 2.1, and approximating the Poisson hole process to obtain an approximation result of the signal-to-interference ratio distribution of different types of users; 3) approximating the Poisson cluster process with similar space characteristics to the Poisson hole process to obtain another approximation result of the signal-to-interference ratio distribution of different types of users;
the key performance indexes comprise link-level performance indexes and network-level performance indexes, and are determined according to specific scenes and requirements;
step 3.2, optimizing process: 3.1, setting different exclusion areas to evaluate key performance indexes by adopting an evaluation process in the step 3.1, selecting the exclusion area corresponding to the maximum performance value as an optimal activation area based on an obtained analysis result, and setting the optimal activation area as a final exclusion area;
step four: decision making and publishing
Step 4.1 decision making process: based on the user position and the estimated optimal activation area, activating the D2D user, and activating the paired users outside the exclusion area as D2D users, wherein the rest users are cellular users;
step 4.2 feedback process: the base station feeds back the classification information to the user, the user works according to the received instruction, and the user switches the working mode and obtains the working frequency band according to the base station scheduling information.
2. The method as claimed in claim 1, wherein in step 2.1), the exclusion area is preferably circular, and when the exclusion area is circular, the radius of the circular area is called exclusion radius, denoted as R, and ranges from the exclusion radius to the exclusion radius R
Figure FDA0002221925270000021
In the meantime.
3. The method as claimed in claim 2, wherein in step 3.1), when the exclusion area is circular, the three methods for analyzing the statistical distribution of the signal-to-interference ratios of the users of the cell and the users of the D2D are:
1) since active D2D users are a subset of potential D2D users, if all potential D2D users are active, the interference from co-channel D2D users is greater than the actual interference; therefore, the SIR statistical distribution of different types of users will get a lower theoretical bound;
1. theoretical lower bound for cellular user SIR statistical distribution inside exclusion zone
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical lower bound of the SIR statistical distribution of the cellular users located inside the exclusion area is:
wherein, IbcInterference from co-frequency base stations to cellular users;
Figure FDA0002221925270000032
is the upper bound of interference from co-channel D2D transmitters to cellular users;
Figure FDA0002221925270000033
andare each IbcAnd
Figure FDA0002221925270000035
(ii) a laplace transform of; r is the exclusion zone radius; thetacIs the signal-to-interference ratio threshold of the cellular user; mu.sbIs the transmit power;
2. statistical distribution of SIR of cellular users outside exclusion zone
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the statistical distribution of SIR of the cellular users located outside the exclusion area is only related to the interference from the co-frequency base station, and an accurate theoretical result can be obtained, which is expressed as:
Figure FDA0002221925270000036
theoretical lower bound of statistical distribution of SIR for 3.D2D users
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical lower bound of the statistical distribution of D2D user SIR is:
Figure FDA0002221925270000037
wherein, IbDInterference from co-channel base stations to D2D users;
Figure FDA0002221925270000038
is the upper bound of interference from co-channel D2D transmitters to D2D users;
Figure FDA0002221925270000039
and
Figure FDA00022219252700000310
are each IbDAnd
Figure FDA00022219252700000311
(ii) a laplace transform of;
2) approximating the active D2D users as a fairly dense dilute PPP, then the interference from the D2D users is an approximation of the actual interference; therefore, the SIR statistical distribution of different types of users can obtain approximate theoretical results;
1. cellular user SIR approximate statistical distribution within exclusion zone
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical result of the SIR statistical distribution of the cellular users located inside the exclusion area is approximated as:
Figure FDA00022219252700000312
wherein the content of the first and second substances,
Figure FDA00022219252700000313
is an approximation of the interference from the co-channel D2D transmitter to the cellular user, an
Figure FDA00022219252700000314
Is that
Figure FDA00022219252700000315
(ii) a laplace transform of;
2. statistical distribution of SIR of cellular users outside exclusion zone
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the statistical distribution of SIR of the cellular users located outside the exclusion area is only related to the interference from the co-frequency base station, and then an accurate theoretical result can be obtained, which is expressed as:
Figure FDA0002221925270000041
3. approximation of D2D user SIR statistical distribution based on PPP model
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical result of the statistical distribution of D2D user SIR is:
wherein the content of the first and second substances,
Figure FDA0002221925270000043
is an approximation of the interference from co-channel D2D transmitters to D2D users,
Figure FDA0002221925270000044
is that
Figure FDA0002221925270000045
(ii) a laplace transform of;
3) due to the existence of the exclusion region, the activated D2D transmitter presents a clustering phenomenon in space, and the PCP model with similar clustering characteristics can be adopted to obtain an approximation of actual interference; therefore, the SIR statistical distribution of different types of users can obtain approximate theoretical results;
1. approximation of cellular user SIR statistical distribution inside exclusion zone based on PCP model
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical result of the SIR statistical distribution of the cellular users located inside the exclusion area is approximated as:
Figure FDA0002221925270000046
wherein, IDc,PCPIs an approximation of the interference from co-channel D2D transmitters to cellular users;is IDc,PCP(ii) a laplace transform of;
2. approximation of cellular user SIR statistical distribution outside exclusion zone based on PCP model
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the statistical distribution of SIR of the cellular users located outside the exclusion area is only related to the interference from the co-frequency base station, and is not related to PCP approximation, so that an accurate theoretical result can be obtained, which is expressed as:
Figure FDA0002221925270000048
3. approximation of D2D user SIR statistical distribution based on PCP model
Based on the network model established in step 1 and the interference suppression strategy proposed in step 2, the theoretical result of the statistical distribution of D2D user SIR is:
Figure FDA0002221925270000049
wherein IDD,PCPIs an approximation of the interference from co-channel D2D transmitters to D2D users, an
Figure FDA00022219252700000410
Is IDD,PCPIs performed by the laplace transform.
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