Multi-band collaborative content cache deployment method for millimeter wave self-organizing network

Abstract

The invention discloses a multi-band collaborative content cache deployment method of a millimeter wave self-organizing network, which relates to the technical field of wireless communication, and adopts self-organizing network modeling based on Poisson point process (PPP) to describe random distribution characteristics of small base stations and user equipment, and analyzes signal transmission characteristics in combination with a directional antenna gain model. The probability caching strategy is adopted, the cache placement probability is optimized, the cache hit rate is increased, and meanwhile content diversity is considered. Based on a millimeter wave LOS / NLOS propagation model, a mathematical expression of a content successful delivery probability (SCDP) is established to quantify the influence of a caching strategy on the network performance. According to the method, the network delay can be effectively reduced, the bandwidth consumption is reduced, the resource allocation is optimized, and the network adaptability and reliability are enhanced.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of wireless communication, in particular to a multi-band cooperative content cache deployment method of a millimeter wave self-organizing network. BACKGROUND

[0002] The millimeter wave self-organizing network is an architecture based on millimeter wave band (30 GHz to 300 GHz) communication, has high data rate and low delay characteristics, and is widely used in 5G and future wireless communication. However, this technology faces challenges such as high path loss, channel blocking, multi-band interference, limited cache strategy and high energy consumption in content distribution and cache. Millimeter wave signals are easily blocked in urban environments, resulting in an increase in non-line-of-sight (NLOS) transmission, affecting network stability. At the same time, traditional cache strategies are mostly based on fixed or popularity ranking methods, and cannot combine the dynamic characteristics of millimeter wave channels, resulting in low cache hit rate and reduced data transmission efficiency. In addition, millimeter wave devices have high power consumption, and the calculation complexity of content cache increases, affecting resource management efficiency. SUMMARY

[0003] The technical problem to be solved by the application is to overcome the shortcomings of the prior art and provide a multi-band cooperative content cache deployment method of a millimeter wave self-organizing network, which realizes the deployment of content cache in a self-organizing network and proposes a self-organizing network content cache deployment scheme under multiple frequency bands, which is reasonable in resource allocation, simple in method and high in content successful transmission rate.

[0004] The application adopts the following technical solutions to solve the above technical problems:

[0005] According to the multi-band cooperative content cache deployment method of a millimeter wave self-organizing network provided by the application, the method comprises the following steps:

[0006] A self-organizing network model based on a homogeneous Poisson point process (PPP) distribution is established;

[0007] Based on the antenna model, the effective antenna gain of the antenna model is obtained;

[0008] According to the self-organizing network model and the effective antenna gain of the antenna model, the signal-to-interference-and-noise ratio (SINR) of the communication link is obtained;

[0009] Based on the effective antenna gain and the signal-to-interference-and-noise ratio (SINR) of the communication link, a LoS probability model is used to simulate different urban environments;

[0010] On the basis of the signal-to-interference-and-noise ratio (SINR) of the communication link, the influence of different urban environments on the link quality is considered, and content cache deployment is performed on the transmitting nodes of the self-organizing network model.

[0011] As a further optimization of the multi-band collaborative content caching deployment method for millimeter-wave self-organizing networks described in this invention, a self-organizing network model based on homogeneous Poisson point process PPP distribution is established; including:

[0012] Consider a millimeter-wave ad hoc network, where a group of transmission nodes is modeled as a density of in a two-dimensional plane. homogeneous Poisson point process The Poisson process Represented as The transmission nodes include sending nodes and receiving nodes, and each group of sending nodes satisfies , For the set of sending nodes, The location of each sending node, Represents a two-dimensional plane;

[0013] In the self-organizing network model, the positions of the sending nodes are generated according to a homogeneous Poisson point distribution; each sending node corresponds to one receiving node, and the distance between the receiving node and its paired sending node is a fixed value. .

[0014] As a further optimization of the multi-band collaborative content caching deployment method for millimeter-wave self-organizing networks described in this invention, based on the antenna model, the effective antenna gain of the antenna model is obtained; including:

[0015] The transmitting and receiving nodes are modeled using a dipole antenna model, and the radiation pattern of the dipole antenna is distributed in a figure-eight shape.

[0016] Assume that both the transmitting node and its corresponding receiver use directional beamforming for data transmission;

[0017] Considering directional beamforming, a segmented beam model is introduced to describe the beam direction, thus obtaining the effective antenna gain of a typical receiving node when receiving both the desired and interfering signals.

[0018]

[0019] in, It's the main lobe gain. For beamwidth, For back lobe gain, This represents the effective antenna gain of an antenna model obtained by a typical receiving node when receiving both the desired signal and interference signals. This indicates that both the receive antenna gain and the transmit antenna gain are 1. The probability, Indicates the receiving antenna gain is The transmitting antenna gain is The probability, Indicates the receiving antenna gain is The transmitting antenna gain is The probability, This indicates that both the receive antenna gain and the transmit antenna gain are 1. The probability of.

[0020] As a further optimization of the multi-band collaborative content caching deployment method for millimeter-wave self-organizing networks described in this invention, the signal-to-interference-plus-noise ratio (SINR) of the communication link is derived based on the effective antenna gain of the self-organizing network model and the antenna model; including:

[0021] Using a short-range propagation model, the transmission distance between different communication links is defined as... , Different values ​​represent different communication links; this is the path loss function corresponding to the short-range propagation model. Represented as

[0022]

[0023] in, Indicates the reference distance. This refers to the path loss index. Loss of Path (LoS) indicates a line-of-sight (LOS) link, while Non-LoS (NLoS) indicates a non-LOS link. When a link is LosS... When NLoS link ,in, and These represent the path loss indices for line-of-sight links and non-line-of-sight links, respectively. This refers to the frequency-independent constant parameter of path loss, expressed as... , Represents the speed of light. It is the carrier frequency;

[0024] The signal-to-interference-plus-noise ratio (SINR) of a typical receiving node in a communication link is expressed as:

[0025]

[0026] in, Represents a group of nodes with density of The set of interfering nodes, Representing another group with a density of The set of interfering nodes, For the first The probability that a piece of content is cached in the sending node. Indicates the transmission power. It is noise power. denotes the small-scale fading of the different communication links, subject to a Nakagami distribution; denotes the different communication links, denotes the small-scale fading of the main communication link, denotes the transmission distance of the main communication link, is the path loss function for the main communication link.

[0027] As a further optimization of the multi-band cooperative content caching deployment method of the millimeter wave self-organizing network, the content caching deployment is performed on the transmitting nodes of the self-organizing network model; including:

[0028] In the self-organizing network, the content is deployed by using a probability-based caching strategy, wherein whether each content is cached is regarded as a random event subject to a specific probability distribution; there is a limited content library , denoted as , is the most popular content, is the number of contents, assuming that each content is normalized, each receiving node can store at most contents; assuming , the request probability of the content is , satisfying ; without loss of generality, it is assumed that the contents are sorted in descending order of , subject to Zipf distribution, and the expression is as follows:

[0029]

[0030] wherein, is the Zipf distribution index, taken from the interval , the counting index from 1 to , used to represent all contents; Let

[0031] denote the probability that the content is cached in the transmitting node, in the probability-based caching strategy, the caching probability needs to satisfy the following conditions:

[0032] .

[0033] ​​As a further optimization of the multi-band collaborative content caching deployment method for millimeter-wave self-organizing networks described in this invention, a performance evaluation metric based on the probability of successful content delivery is adopted; including:

[0034] By deploying content caching at the sending nodes in the ad hoc network and combining this with SINR analysis of the communication link, the probability of successful content delivery in the ad hoc network after adding caching is calculated. , Used to evaluate network performance;

[0035] Content successful delivery probability Defined as

[0036]

[0037] in, It is millimeter wave bandwidth. The bit rate representing the content. This represents the maximum sending time for each piece of content. , It is an intermediate variable value. Indicates the first Signal-to-interference-to-noise ratio for each content This indicates that the probability of content caching is... hour, Greater than The probability, This represents the probability of satisfying the condition within the parentheses;

[0038]

[0039]

[0040] Formula (8) is expanded using a binomial form. Indicates the first The signal-to-interference-to-noise ratio under each content is greater than The probability, It is a parameter in the tight upper bound of the gamma distribution. Depend on An intermediate variable was obtained. , It is a process from 0 to variables, This represents the path loss function, where L represents a Loss-of-Speed ​​(LoS) link and N represents an NLoS (Non-LoS) link. This indicates a variable that takes the value L or N. The density under the Loss link is Interference, represents the density of interference under NLoS link represents the density of interference under LoS link represents the density of interference under NLoS link represents the expectation of the function in the bracket under the condition that the density of interference under LoS link is represents the expectation of the function in the bracket under the condition that the density of interference under NLoS link is represents the expectation of the function in the bracket under the condition that the density of interference under LoS link is represents the expectation of the function in the bracket under the condition that the density of interference under NLoS link is represents the probability density function of the best path distance between the receiving node and the transmitting node, y is the integral variable, and e is the natural base;

[0041] The probability generating function of the Poisson point process is used in combination with the adopted LoS probability model to calculate:

[0042]

[0043] wherein, represents the function of the LoS probability model, is the effective antenna gain, is the path loss function, represents the integral variable, represents the probability that the receiving antenna gain is and the transmitting antenna gain is and are temporary variables, correspond to the main lobe of the antenna model, correspond to the side lobe of the antenna model, represents that there are four cases, when , is taken as , which represents taking the probability that the receiving antenna gain is and the transmitting antenna gain is , when , is taken as , which represents taking the probability that the receiving antenna gain is and the transmitting antenna gain is , when , is taken as ​​​​​​​​, represents the probability that the receiving antenna gain is and the transmitting antenna gain is , when , is taken as , represents the probability that the receiving antenna gain is and the transmitting antenna gain is ; is a path loss function.

[0044] As a further optimization of the multi-band cooperative content caching deployment method of the millimeter wave self-organizing network described in the present application, is derived by , is the cumulative distribution function of the optimal path distance between the receiving node and the transmitting node;

[0045] ;

[0046] wherein, is the probability of the first content cached in the transmitting node, is a function of the LoS probability model.

[0047] Compared with the prior art, the above technical solution has the following technical effects:

[0048] The present application deploys content caching in a millimeter wave self-organizing network, taking into account the influence of different urban environments, and solves the problems of excessively high delay, excessive bandwidth consumption, excessive network load, and serious interference. It can improve data access efficiency, reduce core network load, reduce delay, and enhance the adaptability and reliability of the network by deploying popular content in edge nodes or devices close to users. This not only improves user experience, but also improves network performance, energy efficiency, and resource utilization. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 is a schematic diagram of the transmitting node and the receiving node of the self-organizing network based on the PPP distribution of the present application;

[0050] Figure 2 is a simulation curve of the content success delivery probability of the present application embodiment 1 for different carrier frequencies under the same communication scenario, changing with content ;

[0051] Figure 3 is a simulation curve of the content success delivery probability of the present application embodiment 2 for 60GHZ under the same communication scenario, changing with ;

[0052] Figure 4is the content success delivery probability of embodiment 3 of the present application for different communication scenarios under 60GHz Simulation curves of changes. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be described in detail below with reference to the drawings and specific embodiments.

[0054] Content caching technology refers to pre-storing commonly used or popular data (such as videos, web pages, software updates, etc.) in the network in network nodes or devices close to users, so as to improve data transmission efficiency, reduce delay, and reduce network load, thereby optimizing user experience and improving network performance. Content caching technology is widely used in various networks (such as the Internet, mobile communication networks, CDNs, 5G, etc.), and is one of the indispensable technologies in network architecture.

[0055] Content caching deployment in millimeter wave ad hoc networks solves the problems of excessively high delay, excessive bandwidth consumption, excessive network load, and serious interference. It can improve data access efficiency, reduce core network load, reduce delay, and enhance the adaptability and reliability of the network by deploying popular content in edge nodes or devices close to users. This not only improves user experience, but also improves network performance, energy efficiency and resource utilization.

[0056] Figure 1 is a simulation distribution diagram of the transmitting node and the receiving node;

[0057] Embodiment 1

[0058] In Figure 2 , the simulation method of the average rate of the channel in different communication scenarios of the present embodiment consists of the following steps:

[0059] (1) Establish a self-organizing network model based on homogeneous Poisson point process (PPP) distribution

[0060] In the present embodiment, the node density is taken as , the transmission distance of the node is , the transmission power is , the four different carrier frequencies are , , .

[0061] (2) Obtain the effective antenna gain of the antenna model based on the antenna model

[0062] In the present embodiment, the antenna array related parameters are shown in Table 1, and Table 1 is the antenna array related parameters.

[0063]

[0064] Table 1

[0065] In this implementation example, the number of antennas , main lobe gain .

[0066] (3) According to the effective gain of the self-organizing network model and the antenna model, the signal-to-interference-and-noise ratio of the communication link is obtained

[0067] In this implementation example, the millimeter wave bandwidth , the noise index , the noise power , and the reference distance . The millimeter wave outdoor channel loss index is as shown in Table 2:

[0068]

[0069] Table 2

[0070] (4) The LoS probability model is used to simulate the environment

[0071] In this implementation example, the LoS probability model is taken as , represents the function of the LoS probability model, represents the visible distance.

[0072] (5) The content successful delivery probability is calculated to evaluate the communication performance

[0073] In this implementation example, the intermediate variable value is taken as , the millimeter wave bandwidth , and the nakagami parameter .

[0074] Example 2

[0075] The example results are shown in Figure 3 , and the simulation method of this embodiment consists of the following steps:

[0076] (1) Establish a self-organizing network model based on the homogeneous Poisson point process PPP distribution;

[0077] In this implementation example, this step is the same as in implementation example 1, and the carrier frequency is taken.

[0078] (2) Obtain the effective antenna gain of the antenna model based on the antenna model

[0079] In this implementation example, this step is the same as in implementation example 1.

[0080] (3) Obtain the signal-to-interference-and-noise ratio of the communication link according to the effective gain of the self-organizing network model and the antenna model

[0081] In this implementation example, this step is the same as that in the implementation example 1.

[0082] (4) LoS probability model simulates different urban environments

[0083] In this implementation example, this step is the same as that in the implementation example 1.

[0084] (5) Calculate the content successful delivery probability for evaluating the communication performance

[0085] In this implementation example, the probability of the th content in the transmitting node buffer is , and the intermediate variable value is .

[0086] Example 3

[0087] The simulation results are shown in Table 1, and this embodiment is simulated by the following steps: Figure 4

[0088] (1) Establish a self-organizing network model based on the homogeneous Poisson point process (PPP) distribution

[0089] In this implementation example, this step is the same as that in the implementation example 1, and the carrier frequency is taken.

[0090] (2) Obtain the effective antenna gain of the antenna model based on the antenna model

[0091] In this implementation example, this step is the same as that in the implementation example 1.

[0092] (3) Obtain the signal-to-interference-and-noise ratio of the communication link according to the effective gain of the self-organizing network model and the antenna model

[0093] In this implementation example, this step is the same as that in the implementation example 1.

[0094] (4) LoS probability model simulates different urban environments

[0095] In this implementation example, four different LoS probability models are taken to simulate the influence of different urban environments.

[0096] The first one is the line-of-sight probability expression defined in the 3GPP TR 38.901 standard

[0097] (1) ​​

[0098] Here , are parameters for different densities of the model, represent the visual distance. In this implementation example, we take , to simulate dense urban environment, and take to simulate sparse urban environment.

[0099] The second one is METIS line-of-sight probability model, whose expression is:

[0100] (2)

[0101] where and are parameters related to the urban density and building characteristics. In this implementation example, we take , to simulate dense urban environment, and take , to simulate sparse urban environment.

[0102] The third one is NYU WIRELESS line-of-sight probability model, whose expression is:

[0103] (3)

[0104] is the distance threshold, is an exponential parameter that controls the decay of the LoS probability, which depends on the building density and height of the scenario. In this implementation example, we take = 30, to simulate dense urban environment, and take to simulate sparse urban environment. The fourth one is a LoS probability model based on 3D space, whose expression is:

[0105]

[0106] (4)

[0107] (5)

[0108] and are the heights of two points in 3D space, is the visual distance between the two points, denotes the building density, denotes the average radius of the buildings, and are the average and variance of the building height, is an intermediate function, ​is the integral variable. In this embodiment, the height of the two points in space is respectively , . The parameter is taken to simulate the dense urban environment, and the parameter is taken to simulate the sparse urban environment.

[0109] (5) The content success delivery probability is calculated to evaluate the communication performance

[0110] In this embodiment, the , millimeter wave bandwidth is taken.

[0111] The above merely describes the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any changes or replacements easily thought of by those skilled in the art within the technical range disclosed by the present application should be encompassed in the protection scope of the present application.

Claims

1. A multi-band cooperative content caching deployment method for a millimeter wave ad hoc network, characterized in that, The application comprises the following steps: establishing a self-organizing network model based on a homogeneous Poisson point process (PPP) distribution; obtaining effective antenna gain of an antenna model based on the antenna model; obtaining a signal-to-interference-and-noise ratio (SINR) of a communication link according to the self-organizing network model and the effective antenna gain of the antenna model; adopting a LoS probability model for simulating different urban environments based on the effective antenna gain and the SINR of the communication link; deploying content caching on a transmitting node of the self-organizing network model based on the SINR of the communication link and considering the influence of different urban environments on link quality. 2.The method of claim 1, wherein, The application comprises the following steps: Consider a mmWave ad hoc network in which a set of transmitting nodes is modeled as a homogeneous Poisson point process of density on a two-dimensional plane , the Poisson process is denoted by , the transmitting nodes include transmitting nodes and receiving nodes, each set of transmitting nodes satisfies , is a set of transmitting nodes, is a location of each transmitting node, denotes a two-dimensional plane; In the self-organizing network model, the positions of the sending nodes are generated according to a homogeneous Poisson point process; each sending node corresponds to a receiving node, and the distance between the receiving node and the sending node paired with it is a fixed value . 3.The method of claim 1, wherein, establishing a self-organizing network model based on a homogeneous Poisson point process (PPP) distribution; obtaining effective antenna gain of an antenna model based on the antenna model; the transmitting node and the receiving node are modeled by using a dipole antenna model, and the radiation pattern of the dipole antenna is in an 8-shaped distribution; the transmitting node and the corresponding receiver both adopt directional beamforming for data transmission; ； wherein is the main lobe gain, is the beam width, is the side lobe gain, is the effective antenna gain of the antenna model obtained by a typical receiving node when receiving the desired signal and the interference signal, denotes the probability that both the receiving antenna gain and the transmitting antenna gain are denotes the probability that the receiving antenna gain is and the transmitting antenna gain is denotes the probability that the receiving antenna gain is and the transmitting antenna gain is denotes the probability that both the receiving antenna gain and the transmitting antenna gain are .​​​ 4.The method of claim 3, wherein, on the basis of considering the directional beamforming, a segmented beam model is introduced to describe the beam direction, so that the effective antenna gain of the antenna model of a typical receiving node when receiving an expected signal and an interference signal is A short-range propagation model is used to define the transmission distance of different communication links as , where different values represent different communication links. The path loss function corresponding to this short-range propagation model is expressed as ​ ； wherein, denotes the reference distance, denotes the path loss exponent, LoS link denotes that the communication link is a line-of-sight link, and NLoS link denotes that the communication link is a non-line-of-sight link, when LoS link when NLoS link wherein, and denote the path loss exponents for line-of-sight and non-line-of-sight links, respectively; denotes a frequency-independent constant parameter of the path loss, denoted as , denotes the speed of light, is the carrier frequency; obtaining a signal-to-interference-and-noise ratio (SINR) of a communication link according to the self-organizing network model and the effective antenna gain of the antenna model; ； where, denotes a set of interfering nodes with density denotes another set of interfering nodes with density is the probability of the th content being buffered in the transmitting node, denotes the transmit power, is the noise power, denotes the small-scale fading of different communication links, following a Nakagami distribution; denotes taking different communication links, denotes the small-scale fading of the main communication link, denotes the transmission distance of the main communication link, is the path loss function of the main communication link.​​ 5. The method of claim 1, wherein, the SINR of the communication link received by a typical receiving node is represented as In self-organizing networks, a probability-based caching strategy is used to deploy contents, where whether each content is cached is considered as a random event subject to a certain probability distribution; there is a finite content library , denoted as , is the most popular content, is the number of contents, assuming that each content is normalized, each receiving node can store at most contents; assuming , the request probability of the content is , satisfying ; without loss of generality, it is assumed that the contents are sorted in descending order of , and obeys Zipf distribution, whose expression is as follows: ； wherein, is the Zipf distribution exponent taken from interval, count index from 1 to to represent all content; Let denote the probability that the th content is buffered in the sending node, in a probability-based caching strategy, the caching probability needs to satisfy the following condition: 。 6. The multi-band coordinated content caching deployment method for millimeter wave ad hoc networks of claim 3, wherein, deploying content caching on a transmitting node of the self-organizing network model; The content success delivery probability of the self-organizing network after the content cache deployment of the sending node in the self-organizing network is analyzed combined with the SINR of the communication link , for assessing network performance; Content success delivery probability is defined as ； wherein, is a millimeter wave bandwidth, represents a bit rate of content, represents a maximum transmission time of each content, , is an intermediate variable value, represents a signal-to-interference noise ratio value under the th content, represents a probability that the content buffer probability is , is greater than , represents a probability that the conditions in the brackets are satisfied; ； ； Equation (8) adopts binomial expansion, denotes the probability that the signal-to-interference-and-noise ratio under the th content is greater than is a parameter in the tight upper bound of the gamma distribution, is an intermediate variable derived from , is a variable ranging from 0 to denotes a path loss function, L represents a LoS link, and N represents a NLoS link, denotes a variable taking L or N, represents interference with a density of under a LoS link, represents interference with a density of under a NLoS link, and represents interference with a density of under a LoS link, represents interference with a density of under a NLoS link, denotes the expectation of the function in the parentheses under the condition of interference with a density of under a LoS link, denotes the expectation of the function in the parentheses under the condition of interference with a density of under a NLoS link, denotes the expectation of the function in the parentheses under the condition of interference with a density of under a LoS link, denotes the expectation of the function in the parentheses under the condition of interference with a density of under a NLoS link, denotes the probability density function of the best path distance between the receiving node and the transmitting node, y is the integral variable, and e is the natural base.​​​ adopting a successful content delivery probability to verify a performance evaluation index; the probability generating function of the Poisson point process is used in combination with the adopted LoS probability model to calculate ； wherein is a function representing the LoS probability model, is the effective antenna gain, is a path loss function, is an integral variable, is the probability that the receive antenna gain is and the transmit antenna gain is and are temporary variables, correspond to the main lobe of the antenna model, correspond to the side lobes of the antenna model, there are four cases, when is taken as , the probability that the receive antenna gain is and the transmit antenna gain is is taken, when is taken as , the probability that the receive antenna gain is and the transmit antenna gain is is taken, when is taken as , the probability that the receive antenna gain is and the transmit antenna gain is is taken, when is taken as , the probability that the receive antenna gain is and the transmit antenna gain is is taken, when is taken as , the probability that the receive antenna gain is and the transmit antenna gain is is taken; is a path loss function.​ 7. The multi-band coordinated content caching deployment method for millimeter wave ad hoc networks of claim 6, wherein, By Taking the derivative, is the cumulative distribution function of the optimal path distance from the receiving node to the transmitting node; ； wherein, is the probability of the th content being cached at the sending node, is a function of the LoS probability model.

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