Communication method and device for heterogeneous Internet of Things

Abstract

The invention discloses a communication method and device for heterogeneous Internet of Things. The method comprises the following steps of: setting a first protection domain around a transmission base station for reducing the interference of cellular equipment supported by the base station on D2D (Device-to-Device) equipment; setting a second protection domain around the D2D device, wherein the second protection domain is used for reducing interference of transmission cellular devices except the cellular device on the D2D device; and determining a successful transmission probability of the D2D device based on the stochastic geometric model to evaluate and optimize communication of the D2D device. According to the method, the protection domains are respectively arranged around the transmission base station and the D2D equipment, so that the multi-source interference is effectively reduced, the communication of the D2D equipment is evaluated and optimized based on the stochastic geometric model, and the anti-interference capability and the communication efficiency of the system are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of communications, and in particular to a communication method and device for a heterogeneous Internet of Things. Background Art

[0002] In the 5G / B5G technology era, the growing demand for the Internet of Things has driven the exponential growth of the number of connected devices. It is estimated that by 2025, the number of networked devices will reach 55 billion to 80 billion. These devices have become ubiquitous, and they are deployed in a wide range of application scenarios, including smart cities, environmental monitoring, industrial automation, security systems, advanced manufacturing, and intelligent transportation. These devices continuously sense and collect various types of data - including industrial, environmental, and personal data, while transmitting, exchanging, and integrating the data for further processing. The application of these devices and data has significantly improved people's daily lives. In addition, 5G / B5G technology is expected to support nearly 10 million devices per square kilometer outdoors and 1,000 devices per 100 square meters indoors. Therefore, in the foreseeable future, various types of IoT devices under different communication networks will coexist, forming a heterogeneous IoT system.

[0003] Heterogeneous IoT systems integrate multiple communication networks, including IoT networks that support cellular networks (e.g., LTE-M and NB-IoT) and ad hoc D2D communication networks (e.g., Zigbee and WiFiHaLow). Heterogeneous IoT devices cover a variety of machines and sensors supported by these diverse networks, such as wearable devices and monitoring sensors. In general, IoT devices mainly operate on the following two types of networks: cellular networks and D2D networks. Heterogeneous IoT devices operating in these two networks are called cellular network devices and D2D network devices, respectively.

[0004] In a typical heterogeneous IoT system, IoT devices can reuse the licensed spectrum of the cellular network for communication, and this communication is carried out without the participation of base stations and core networks. In addition, unlike the traditional half-duplex mode, in which the device can only transmit or receive signals for a period of time, the advancement of hardware technology enables devices to operate in in-band full-duplex mode, that is, to send and receive signals simultaneously on the same time / frequency resource block. Undoubtedly, as two emerging innovations of 5G / B5G, the integration of D2D communication and full-duplex technology has important potential in improving spectrum efficiency and enhancing network capacity. However, due to the broadcast nature of wireless communication, large-scale D2D communication may cause significant interference problems. In addition, since cellular devices and D2D devices are usually randomly distributed in space, this mutual interference usually exhibits significant spatial randomness and is affected by location-related factors such as large-scale and small-scale fading. Therefore, in this environment, formulating effective interference management strategies is crucial to achieving higher system performance.

[0005] In order to effectively control interference issues, various networks have widely adopted the strategy of establishing protection domains (also called exclusion domains). A protection domain usually means a circular area with a fixed radius around each transmitter, within which other devices are prohibited from transmitting. This setting ensures sufficient spatial separation by suppressing potential simultaneous transmissions, thereby reducing mutual interference.

[0006] However, related technologies only focus on setting up protection domains around transmission base stations to reduce the interference of transmission base stations on other network components, but these technologies often ignore the impact of cellular devices on D2D communication. In particular, in dense heterogeneous IoT networks, cellular devices and D2D devices coexist closely, and the interference generated by cellular devices may also significantly affect the performance of D2D communication. Summary of the invention

[0007] The present invention aims to provide a communication method and device for heterogeneous Internet of Things, so as to solve the problem that when cellular devices and D2D devices closely coexist in a dense heterogeneous Internet of Things network, the interference generated by the transmitting cellular devices also significantly affects the D2D communication.

[0008] The present invention provides a communication method for a heterogeneous Internet of Things, comprising the following steps: establishing a first protection domain around a transmission base station to reduce interference of a cellular device supported by the base station to a D2D device; establishing a second protection domain around the D2D device to reduce interference of transmission cellular devices other than the cellular device to the D2D device; and determining a successful transmission probability (STP) of the D2D device based on a random geometric model to evaluate and optimize the communication of the D2D device.

[0009] According to an embodiment of the present invention, based on the random geometric model, the successful transmission probability of the D2D device is determined according to the following formula: in: r d is the transmission distance of the D2D device, d d is the maximum transmission distance given to the D2D device, For r d The probability density function of For all interference I d The expected value of the probability that the signal to interference noise ratio of the D2D device under θ is greater than the threshold θ.

[0010] According to an embodiment of the present invention, in: μ is the exponential distribution parameter that the channel power gain obeys, α is the path loss exponent, 2α<6, P d is the downlink transmission probability within the cell, and They are and In s d The Laplace transform at To transmit the interference of the base station to the D2D device, To transmit the interference of cellular devices to the D2D device, The interference of a half-duplex D2D device transmitting to the D2D device, The interference of a full-duplex D2D device transmitting to the D2D device.

[0011] According to an embodiment of the present invention, is the density of transmission base stations, is the density of transmitting cellular devices, λ H is the density of activated half-duplex mode D2D devices, λ F is the density of D2D devices in full-duplex mode, According to an embodiment of the present invention, Where: p H is the probability that the D2D device works in half-duplex mode, p F is the probability that the D2D device works in full-duplex mode, The density of the activated D2D device.

[0012] According to an embodiment of the present invention, in: p a is the probability that the D2D device is in an activated state, is the probability that the D2D device is located in the first protection domain, is the probability that the D2D device is located in the second protection domain, is the density of transmission base stations, To transmit the density of cellular devices, d b is the radius of the first protection domain, d c is the radius of the second protection domain.

[0013] The present invention also provides a communication device for a heterogeneous Internet of Things, comprising: a first establishment module, used to establish a first protection domain around a transmission base station, for reducing the interference of cellular devices supported by the base station to a D2D device; a second establishment module, used to establish a second protection domain around the D2D device, for reducing the interference of transmission cellular devices other than the cellular device to the D2D device; and a determination module, used to determine the probability of successful transmission of the D2D device based on a random geometric model, so as to evaluate and optimize the communication of the D2D device.

[0014] According to an embodiment of the present invention, the determination module determines the successful transmission probability of the D2D device according to the following formula: in: r d is the transmission distance of the D2D device, d d is the maximum transmission distance given to the D2D device, For r d The probability density function of For all interference I d The expected value of the probability that the signal to interference noise ratio of the D2D device under θ is greater than the threshold θ.

[0015] According to an embodiment of the present invention, in: p a is the probability that the D2D device is in an activated state, is the probability that the D2D device is located in the first protection domain, is the probability that the D2D device is located in the second protection domain, is the density of transmission base stations, To transmit the density of cellular devices, d b is the radius of the first protection domain, d c is the radius of the second protection domain.

[0016] The present invention effectively reduces multi-source interference by setting up protection domains around the transmission base station and the D2D device respectively, and at the same time evaluates and optimizes the communication of the D2D device based on a random geometric model, thereby significantly improving the system's anti-interference capability and communication efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0018] Figure 1 It is a schematic diagram of the information integration and communication architecture in a typical HetIoT according to the relevant technology;

[0019] Figure 2 is a schematic diagram of a heterogeneous Internet of Things based on protection domains according to an embodiment of the present invention;

[0020] Figure 3 is a flow chart of a communication method for a heterogeneous Internet of Things according to an embodiment of the present invention;

[0021] Figure 4 is the probability of the base station in transmission according to an embodiment of the present invention Probability of transmitting cellular devices and the probability p of activating a D2D device a With the downlink transmission probability p d , base station protection domain radius d b and the cellular device protection domain radius d c Schematic diagram of the changing trend of

[0022] Figure 5 A base station according to an embodiment of the present invention Cellular devices D2D devices in half-duplex mode and D2D devices in full-duplex mode The STP of 2 Schematic diagram of the changing trend of

[0023] Figure 6 A base station according to an embodiment of the present invention Cellular devices D2D devices in half-duplex mode and D2D devices in full-duplex mode The STP increases with the base station protection domain radius d b , the transmission probability of the base station Transmission probability of cellular devices and the probability p of a half-duplex D2D device H Schematic diagram of how it varies with different settings; and

[0024] Figure 7 is a base station according to an embodiment of the present invention Cellular devices D2D devices in half-duplex mode and D2D devices in full-duplex mode As the base station density λ b , Cellular device density λ c , cellular device protection domain radius d c and D2D device transmission power P d Schematic diagram of how it changes with different settings. DETAILED DESCRIPTION

[0025] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0026] Reference will now be made in detail to various embodiments of the present invention, examples of which are shown in the accompanying drawings and described below. For ease of interpretation and precise definition in the appended claims, the terms "upper", "lower", "inner" and "outer" are used to describe features of the exemplary embodiments shown in the drawings with reference to their positions.

[0027] According to an embodiment of the present invention, a communication method for a heterogeneous Internet of Things is provided. Figure 2 1 is a flow chart of a communication method for heterogeneous Internet of Things according to an embodiment of the present invention. Figure 2 As shown, the following steps are included: establishing a first protection domain around a transmission base station to reduce interference of cellular devices supported by the base station to a D2D device; establishing a second protection domain around the D2D device to reduce interference of transmission cellular devices other than the cellular device to the D2D device; and determining the probability of successful transmission of the D2D device based on a random geometric model to evaluate and optimize the communication of the D2D device.

[0028] In heterogeneous IoT, cellular devices and D2D devices share spectrum, which leads to serious mutual interference and affects communication quality. The existing technology focuses on the management of a single interference source and lacks a comprehensive interference control strategy. The present invention effectively reduces multi-source interference by setting up protection domains around transmission base stations and D2D devices respectively, and at the same time evaluates and optimizes the communication of D2D devices based on random geometric models, significantly improving the system's anti-interference ability and communication efficiency.

[0029] According to an embodiment of the present invention, based on the random geometric model, the successful transmission probability of the D2D device is determined according to the following formula: in: r d is the transmission distance of the D2D device, d d is the maximum transmission distance given to the D2D device, For r d The probability density function of For all interference I d The expected value of the probability that the signal to interference noise ratio of the D2D device under θ is greater than the threshold θ.

[0030] The embodiment of the present invention describes that given two protection domain radii d b and d c and interference I d The probability that a D2D device can successfully transmit under certain conditions. By calculating the probability of successful transmission of a D2D device based on a random geometric model, the present invention can accurately evaluate the communication performance of the device under different network environments. This method takes into account the influence of multiple interference sources (such as base stations, cellular devices, and other D2D devices), and uses the calculation of probability density functions and signal-to-interference-noise ratio (SINR) thresholds to provide an accurate prediction of the communication success rate of D2D devices. Through this method, the scheduling and spectrum allocation of D2D communications can be optimized, the resource utilization of the network can be improved, interference can be reduced, and the reliability of D2D devices can be ensured. According to an embodiment of the present invention, in: μ is the exponential distribution parameter that the channel power gain obeys, α is the path loss exponent, 2α<6, P d is the downlink transmission probability within the cell, and They are and In s d The Laplace transform at To transmit the interference of the base station to the D2D device, To transmit the interference of cellular devices to the D2D device, The interference of the half-duplex device transmitting to the D2D device, The interference of the full-duplex device transmitting to the D2D device.

[0031] The embodiment of the present invention models signal attenuation through a path loss model and Laplace transform, and accurately evaluates the communication quality of D2D devices. The channel power gain parameter μ and the path loss index α are introduced to effectively consider the impact of environmental factors on D2D communication. This method can flexibly adjust the path loss model according to different network densities, transmission powers, and device distributions, thereby improving the communication efficiency of D2D devices and optimizing communication quality in complex environments.

[0032] According to an embodiment of the present invention, is the density of transmission base stations, is the density of transmitting cellular devices, λH is the density of activated half-duplex mode D2D devices, λ F is the density of D2D devices in full-duplex mode,

[0033] The embodiment of the present invention achieves dynamic adjustment in different network environments by modeling the density of base stations and cellular devices and the maximum transmission distance given by D2D devices. The density of base stations and cellular devices affects the protection domain radius, which directly affects the maximum transmission distance and communication success rate of D2D devices. The method can optimize the regional division of D2D communication and ensure the communication stability and reliability of D2D devices in dense network environments by controlling device density and power.

[0034] According to an embodiment of the present invention, Where: p H is the probability that the D2D device works in half-duplex mode, p F is the probability that the D2D device works in full-duplex mode, The density of the D2D device to be activated.

[0035] The embodiments of the present invention achieve optimized scheduling under different communication modes by combining the activation probability of D2D devices with the protection domain radius and network density. The half-duplex and full-duplex mode switching in the claims can dynamically adjust the activation state of the D2D device according to the current network conditions, ensuring that the device switches to the optimal mode according to the communication environment, improving spectrum utilization, and reducing unnecessary interference. In a high-density environment, the flexible control of the activation probability can effectively manage the communication resources of the D2D device and improve the network throughput.

[0036] The embodiment of the present invention optimizes the maximum transmission distance of D2D devices by adjusting the transmission power of base stations and cellular devices and device density, combined with the protection domain radius. Through this dynamic adjustment mechanism, the optimal power configuration can be achieved when network conditions change, interference can be reduced and communication stability can be guaranteed. This method improves the coverage and quality of D2D communications, especially in the case of uneven device density and power, by adjusting the transmission power and the size of the protection domain, the transmission efficiency of the entire network is optimized.

[0037] According to an embodiment of the present invention, in: p a is the probability that the D2D device is in an activated state, is the probability that the D2D device is located in the first protection domain, is the probability that the D2D device is located in the second protection domain, is the density of transmission base stations, To transmit the density of cellular devices, d b is the radius of the first protection domain, d c is the radius of the second protection domain.

[0038] The embodiment of the present invention describes the activation probability of D2D devices under given base station and cellular device density and protection domain radius, that is, the probability of whether the D2D device can participate in communication under given interference and communication conditions. By combining the influence of base station density, cellular device density and protection domain radius, the present invention designs an effective activation probability adjustment mechanism. By adjusting the protection domain radius and device density, the working state of the D2D device can be adjusted under different network densities and interference conditions, thereby improving the communication efficiency of the D2D device and the overall performance of the system. This method ensures that the D2D device can work stably and efficiently in a changing network environment, and optimizes the use of spectrum and the allocation of communication resources.

[0039] The above embodiments of the present invention can achieve efficient D2D communication by accurately controlling the protection domain radius, device density, transmission power and communication mode. Whether by optimizing interference management, path loss modeling, or by intelligently adjusting activation probability and device working status, the communication success rate can be improved, interference can be reduced, and resource usage can be optimized, thereby improving the performance of the entire heterogeneous Internet of Things.

[0040] The implementation process of the embodiment of the present invention will be described in detail below with reference to examples.

[0041] In heterogeneous IoT, setting protection domains around transmission base stations and cellular devices and flexibly deploying D2D communication technologies that support half-duplex or full-duplex modes introduce significant complexity and randomness in terms of interference and spatial distribution. To address this problem, the present invention uses random geometry as a research tool to provide a probabilistic framework for modeling spatial point processes, thereby effectively capturing the complex spatial configuration of wireless networks. At the same time, although random geometry has been applied in cellular and D2D scenarios, research on their interactions is still limited in the context of introducing the concept of protection domains. The present invention fills this gap by utilizing random geometry to analyze system performance in heterogeneous IoT scenarios. Specifically, it is necessary to describe the spatial distribution of base stations, cellular devices, and D2D devices, and analyze key performance indicators in heterogeneous IoT.

[0042] In order to achieve this goal, the present invention needs to overcome several key problems:

[0043] First, the combination of D2D communication and in-band full-duplex technology makes simultaneous transmission and reception possible, significantly improving spectrum efficiency. However, as the number of D2D devices using full-duplex communication increases, the interference generated by the communication may degrade the performance of cellular communications. Therefore, it is crucial to develop an effective full-duplex mode selection strategy that can effectively mitigate D2D interference by regulating the number of D2D devices using in-band full-duplex communication.

[0044] Secondly, while establishing guard zones around transmitting base stations can indeed effectively reduce interference from cellular transmissions, the impact of large-scale D2D transmissions on cellular communications cannot be ignored. Therefore, integrating guard zones around transmitting base stations and cellular devices is a promising approach to mitigate interference in the entire system.

[0045] In addition, the randomness of cellular transmissions leads to the formation of random guard zones around transmitting base stations and cellular devices, which further contributes to the randomness of D2D transmissions. This randomness complicates the modeling of the spatial distribution of cellular and D2D devices, their interdependencies, and the complexity of various spatial interferences.

[0046] Modeling and analyzing the performance of heterogeneous IoT requires jointly considering the above factors. However, existing analytical models often fail to fully capture all these complexities. This gap requires a new analytical model that can accurately analyze the performance and provide inspiration for configuration parameters to improve the overall system efficiency.

[0047] Assume there is a typical heterogeneous Internet of Things, which has the following characteristics:

[0048] (1) Cellular devices and D2D devices coexist densely;

[0049] (2) Protection domains are established around randomly distributed base stations and cellular devices;

[0050] (3) D2D devices can perform D2D communication in full-duplex or half-duplex mode.

[0051] In this context, the present invention constructs an analytical model based on random geometry to study the information integration and communication in the network, and theoretically analyzes the successful transmission probability (STP) of cellular communication and D2D communication. Taking all these factors into consideration, the main contributions of the present invention are summarized as follows:

[0052] (1) An innovative spatial distribution model of heterogeneous IoT is established. Most existing technologies simply model the spatial distribution of base stations, cellular devices and D2D devices through two homogeneous Poisson point processes (HPPPs). However, these existing technologies cannot accurately model the heterogeneous IoT network topology, especially when considering the transmission probability and the protection domain around the transmission device. The present invention sparsifies and approximates the HPPP to adapt to the probability distribution of transmission devices. In addition, the superposition of two Poisson hole processes (PHP) is used to model the activated D2D devices located outside two different types of protection domains. This spatial model can provide an accurate and realistic representation of the network topology.

[0053] (2) A comprehensive heterogeneous IoT analytical model is established. The developed analytical model derives accurate expressions for the successful transmission probabilities (STPs) of cellular and D2D communications, taking into account key system parameters such as the transmission density of cellular devices, the density of D2D devices in half-duplex / full-duplex mode, and the protection domain radius. The model is able to capture the inherent randomness and interdependence of cellular and D2D communications, as well as the complex spatial interference within the network.

[0054] (3) Extensive simulation validation was performed. The accuracy of the analytical model was verified through extensive Monte Carlo simulations. These simulation results provide valuable references for practitioners (such as network operators or engineers) to help them choose appropriate parameter configurations to improve network performance in heterogeneous IoT scenarios. (I) Network deployment

[0055] Figure 2 is a schematic diagram of a heterogeneous Internet of Things based on protection domains according to an embodiment of the present invention, which includes a base station, a cellular device and a D2D device. Figure 2 (a) shows the Voronoi thumbnail of base stations, cellular devices, and D2D devices in a 1000×1000m square area, where λ b =10 base stations / km,λ C =100 cellular network devices / km,λ d =100D2D equipment / km,d b =60m,d C =30m,p d =0.5,p t =1.0. Figure 2 (b) Shows a cell in a heterogeneous IoT network based on protection domains. It is assumed that the base stations, cellular devices, and D2D devices are randomly distributed according to three independent homogeneous Poisson point processes (HPPPs). b ,Φ c ,Φ dThey represent the point processes of base stations, cellular devices and D2D devices, and their densities are λ b ,λ c ,λ d , where (λ c >>λ b ,λ d >>λ b ). Each cellular device is associated with the base station closest to its geographical location, so the entire cellular network forms a Voronoi partitioning topology, such as Figure 2 (a). Let S v is the area of ​​the Voronoi cell, then Each Voronoi cell is approximated as a cell of radius R v ,but In heterogeneous IoT, base stations, cellular devices, and D2D devices transmit data at fixed power P. b ,P c and P d to transfer.

[0056] Considering the limited spectrum resources, all three types of D2D cellular transmission and D2D transmission share the same frequency band, thus interfering with other devices. Specifically, cellular transmission between base stations and cellular devices, including downlink (from base stations to cellular devices) and uplink (from cellular devices to base stations), is performed within a Voronoi cell. On the same carrier in a Voronoi cell, only downlink or uplink transmission can be performed at the same time. On the same carrier in a Voronoi cell, only downlink or uplink transmission can be performed at the same time.

[0057] like Figure 2 As shown in (a), in the Voronoi cell where the base station is located, the cellular device cannot initiate a new transmission through the same carrier; on the contrary, when the base station is not transmitting, the cellular device in the Voronoi cell can transmit data to the base station. For D2D transmission, it is assumed that the D2D device can choose to work in half-duplex or full-duplex mode, and the maximum transmission distance is d d Since cellular transmission and D2D transmission may interfere with each other, protection domains are set up on both sides of the base station and cellular device in transmission. b or within the protection domain of each cellular device with a radius of d c Within the protection domain, D2D devices cannot be activated for any transmission. Figure 2As shown in (a), within the protection domain of the transmission base station or cellular device, the D2D device is not activated; while the D2D device outside the protection domain is activated. The main symbols used in the present invention and their descriptions are summarized in Table 1. Table 1. Key symbols and descriptions 2. Channel Model

[0058] Without loss of generality, all wireless signals in cellular and D2D transmissions experience both large-scale and small-scale channel fading. The former is characterized by a distance-dependent power attenuation model, where the signal power is expressed in terms of R -α The rate attenuation is , where R is the Euclidean distance between the transmitter and the receiver, and α is the path loss exponent, which usually satisfies 2<α<6. The latter is modeled by an independent and identically distributed (iid) channel power gain H, which follows an exponential distribution with mean 1 / μ, i.e. H~exp(μ). In addition, the noise at the receiver is modeled as an additive white noise Gaussian variable with mean zero and variance σ 2 . 3. Density of cellular devices in transmission

[0059] Both cellular downlink and uplink transmissions are performed within the Voronoi cell. In all cellular transmissions in heterogeneous IoT, let p d and p u are the allocation ratios for downlink and uplink transmission respectively. Therefore, p d +p u = 1. The transmission probability of a base station can be determined by the downlink transmission ratio Therefore, the base station distribution Φ b Apply the sparsification operation and generate a new distribution Its density is To represent all base stations that are transmitting (called transmitting base stations). The value of is given by: For uplink transmission, all cellular devices use the ALOHA mechanism with probability p t access channel. Therefore, the transmission probability of each cellular device is After excluding the cellular devices located in each transmitting base station Voronoi cell and those cellular devices not attempting to transmit data, the remaining transmitting cellular devices form a general point process Its density is Density of transmitting cellular devices It can be expressed as 4. Density of D2D devices in transmission

[0060] In D2D transmission, a D2D device can be activated when the following two necessary conditions are met: C1: The D2D device is located outside the protection domain of the transmission base station (i.e., the first protection domain), and its probability is recorded as and C2: The D2D device is outside the protection domain of the transmitting cellular device (i.e., the second protection domain), and its probability is recorded as Conditions C1 and C2 are independent of each other. Let p a is the activation probability of the D2D device, and its value is: Next, we need to calculate and

[0061] Given a base station in transmission and D2D devicesΦ d Located at a radius d with the transmission base station as the center b The D2D devices outside the protection domain (i.e., the hole area) form a Poisson hole process (PHP) exist The activation probability of D2D devices is It can be expressed as:

[0062] Use a density of To approximate the common point process of transmitting cellular devices Distribution of cellular devices for a given transmission and the distribution of D2D devices Φ d , located at a radius d centered on the transmitting cellular device c The D2D devices outside the protection domain (i.e., the hole area) form another exist The activation probability of D2D devices is Given by the following formula Will and Substitute the calculation formula into get

[0063] According to the formula p a It can be seen that the activated D2D devices form a point process Its density is Given by the following formula Assume that a D2D device has a probability p H and p F Work in half-duplex mode and full-duplex mode respectively, where p H +p F = 1. Density To approximate the common point process of activated D2D devices is the union of two independent PPPs, Φ H is the point process of activated half-duplex D2D devices, with a density of λ H , Φ F is the point process of activated full-duplex D2D devices, with a density of λ F . It can be obtained from this

[0064] Consider the general case in D2D transmission, that is, half of the half-duplex D2D devices are transmitters and the other half are receivers. The half-duplex D2D devices as transmitters form a Its density is in For full-duplex D2D devices, all users act as transmitters and receivers at the same time. Its density is in (V) Analysis model

[0065] In this section, an analytical model is constructed based on random geometry theory to derive expressions for successful transmission probabilities (STPs) of base stations, cellular transmissions, and D2D transmissions.

[0066] First, we introduce a general expression for the successful transmission probability STP. Consider a wireless transmission signal from a tagged transmitter x to a tagged receiver y, with a distance R x , and the position distribution of x follows the point process Φ, and Let P x and H x denote the transmission power of x and the channel power gain between x and y respectively. Let SINR y represents the signal to interference plus noise ratio (SINR) of receiver y, where S y is the signal power from x received by receiver y, I y is the interference signal power it suffers, σ 2 is the noise power.

[0067] In SINR y In the calculation formula, where x′∈Φ′ is the jammer, Φ′ is the set of jammer nodes, and P x′ represents the transmission power of x′, H x′ and R x′ are the channel gain and transmission distance between x′ and receiver y, respectively.

[0068] For receiver y, when the SINR of y y (Unitless) exceeds a certain SINR threshold θ dB (in decibels (dB)), the signal from x can be successfully received and decoded. represents the conditional success probability (CSP) of x, which is expressed as y let represents the STP of x. The overall network performance can be defined as The mean value of in YesR x The probability density function (PDF) of In the calculation formula, can be further calculated as follows. in is the expected value of the function f(X) with respect to the random variable X. (a) It is derived from H x exponential distribution, with mean 1 / μ. That is, H x ~exp(μ). According to the cumulative distribution function of exponential distribution, let (b) From interference I y The definition of the Laplace transform of is expressed in the form of Based on the general expression of STP, the STP of base stations, cellular devices and D2D devices can be represented. (VI) Base station successful transmission probability

[0069] In a Voronoi cell, a base station b 0 To the marked cellular device c 0 Perform downlink transmission. 0 Receive from b 0When the target signal is transmitted, it will also be interfered by other base stations, cellular devices, and D2D devices in half-duplex / full-duplex mode. c (R b ,I c ) represents a cellular device c 0 SINR is the signal to interference plus noise ratio. c (R b ,I c ) values ​​are as follows.

[0070] Among them, S c , I c and σ 2 Cellular devices c 0 The target signal power, total interference power and noise power on P b is the transmission power of the base station, H b and R b They are b 0 With c 0 The channel gain and transmission distance between them. and The definitions are as follows: The interference terms represent the interference caused by other transmitting base stations, cellular devices, and D2D devices (in half-duplex / full-duplex mode), which are in c 0 The values ​​at are as follows: let Represents the STP of the base station, according to the analysis model in (V) and The calculation formula is: It can be calculated by in YesR b The probability density function (PDF) of R b ∈[0,R v ] and R v is the radius of the approximate circular Voronoi cell. In the calculation formula, It can be calculated by in YesR b The cumulative distribution function of . The calculation formula can be calculated Its formula is in and are respectively in s c Evaluated and The Laplace transform of . Their expressions are derived below. first, In c 0 The Laplace transform at is given by: prove: Among them, (a) comes from R i and H i are independent of each other. (b) The result comes from the property of the exponential distribution, namely that exp(∑ i H i )=∏ i exp(H i ). This is due to H i (d) is true because H i It obeys an exponential distribution with a mean of 1 / μ, that is, According to the probability generation functional (PGFL) of HPPPΦ with density λ, that is get

[0071] In the above formula (a), Indicates the area where the interfering base station is located, which excludes the current Voronoi cell (i.e., the cellular device c receiving the origin mark) 0 unit where it is located). The origin c 0 is the center of the circle and the radius is r v (B) Convert the expression from orthogonal coordinates to polar coordinates, where α is the polar angle, uniformly distributed between [0,2π]; in formula (f), the integration limit is changed from R v to ∞, because the nearest interfering base station is at least R away v (c) By transforming the variables Get, that is Therefore, the value range of y is For the special case α=4, (A) Comply with exist The calculation formula is: 0 Where The Laplace transform is prove: In the above proof, (A) is derived from the probability generation functional (PGFL) of HPPP; in (a), R 2 is the area where the interfering cellular device is located. (b) Convert the expression from orthogonal coordinates to polar coordinates, where α is the polar angle, uniformly distributed in the interval [0,2π]. (c) From the Euler reflection formula We obtain, where Γ(x) is the complete gamma function, defined as Used in A similar derivation process is and In c 0 The Laplace transform at is as follows. (VII) Probability of successful transmission of cellular devices

[0072] In the Voronoi cell, a marked cellular device c′ 0 The marked base station b′ 0 Perform uplink transmission. When b′ 0 Received from c′ 0 When the desired signal is transmitted, it will also be subject to interference caused by other transmitting base stations, cellular devices, and D2D devices in half-duplex / full-duplex mode. b (R c ,i b ) represents base station B′ 0 SINR at b (r c ,i b ) are as follows Where S b ,I b and σ 2 Base station B′ 0 The desired signal power, total interference power and noise power at P c is the transmission power of the cellular device, H c and r c C′ 0 and B′ 0 The channel gain and transmission distance between them. In addition, They represent the traffic from other transmission base stations, cellular devices, D2D devices in half-duplex mode, and D2D devices in full-duplex mode in B′.0 Their values ​​are given by make Represents the STP of the cellular device. The calculation formula is: It can be calculated by in Yes c The probability density function (PDF) of c ∈[0,R v ]. Since the cellular devices in each Voronoi cell follow the same location distribution, R c With R b The same PDF, i.e. exist In the calculation formula, It can be calculated by the following formula in and They are and In s b The Laplace transform at . Their values ​​are shown below. 8. Successful transmission probability of D2D devices

[0073] For a tagged D2D device To another tagged D2D device exist SINR d (R d ,I d ) can be expressed as Where S d ,I d and σ 2 They are The desired signal power, total interference power and noise power at P d is the transmission power of the D2D device, H d and R d They are and The channel power gain and transmission distance between them. In addition, They are respectively transmitted by other base stations, cellular devices, half-duplex D2D devices and full-duplex D2D devices. Their values ​​are as follows

[0074] also, is the self-interference caused by the full-duplex transmission of the D2D device, k is the self-interference elimination factor, It is an indicator function. When the D2D device works in full-duplex mode, the value is 1; when the D2D device works in half-duplex mode, the value is 0. therefore, It can be expressed as Among them, d d is the maximum transmission distance of each D2D device, Yes d The probability density function (PDF) of d ∈[0,d d ],have Likewise, Can be expressed as in and They are and In s d The Laplace transforms at , their values ​​are given as follows: (IX) Performance evaluation

[0075] The present invention also demonstrates a large number of Monte Carlo simulations in MATLAB to verify the accuracy of the proposed theoretical model. The simulation environment is built based on the system model described in detail above. Table 2 summarizes the network parameter settings in the results, which are consistent with the current cutting-edge technology. Here, P d = 1dBm, which is applicable to the actual power range of D2D devices operating in WiFiHaLow (from 1mW to 1W). In each simulation, the simulation area is defined as a radius of 10 4 Each simulation is performed 10 times. 4 In all figures, the labels ‘ana’ and ‘sim’ refer to the theoretical results and simulation results, respectively. Table 2. Schematic diagram of simulation parameter settings

[0076] The symbol 'x:y:z' indicates that a parameter changes from x to z with a step size of y, and 'x,y' indicates that a parameter can take values ​​x and y. For example, in the first row of Table 2, '-20:1:20' indicates that the parameter θ changes from -20dB to 20dB with a step size of 1dB, and '4,5' indicates that the parameter α can take the values ​​4 and 5.

[0077] Figure 4 is the probability of the base station in transmission according to an embodiment of the present invention Probability of transmitting cellular devices and the probability p of activating a D2D device a With the downlink transmission probability p d , base station protection domain radius d b and the cellular device protection domain radius d c Schematic diagram of the changing trend of Figure 4 As shown, when d b =30,60,100m,d c =10,20,30,60m, the observation conclusion is: ·With the p d increase, This is because both downlink and uplink transmission can occur in each Voronoi cell, so a higher p d Will cause of reduction. For a given d b , when d c When p is small, d The increase in p a decreases; on the contrary, when d c When p is larger, d The increase in p a The reason is as follows: when d c When p is small, d As the number of increases, the probability that the D2D device is located in the protection domain of the transmission base station increases, thereby increasing the probability that the D2D device cannot be activated. a In contrast, when d c When p is larger, d increase, This reduces the probability that the D2D device is located in the protection domain of the transmitting cellular device, which reduces the probability that the D2D device cannot be activated, resulting in p a Increase. For a given d c , when d b When p is small, d The increase in p a Increase; and when d bWhen p is larger, d The increase in p a The reason is similar to the above. At a given p d and d b In the case of larger d c This will result in a smaller p a When p d =1, p a In different c remains unchanged for all values ​​of p, since no cellular device is transmitting in any Voronoi cell. Similarly, for a given p d and d c In the case of larger d b This will result in a smaller p a When p d = 0, p a In different b The value remains unchanged because no base station is transmitting in any Voronoi cell. For each Voronoi cell with radius R v Compared with the smaller d b and d c The theoretical results are in good agreement with the corresponding simulation results, thus verifying the accuracy of the model. v Compared with the larger d b and d c The theoretical results and simulation results deviate from each other because the D2D device is more likely to be located in the overlapping area of ​​the protection domain of the base station and the D2D device, causing the simulation results to exceed the theoretical prediction.

[0078] Figure 5 A base station according to an embodiment of the present invention Cellular devices D2D devices in half-duplex mode and D2D devices in full-duplex mode The STP of 2 The following observations were made in the results. Given α, k and σ 2 ,like Figure 5 As shown in (a)-(c), and It decreases as θ increases. This is because the increase of θ makes it more difficult to receive signals from cellular devices, base stations, and D2D devices. For a fixed θ, such as Figure 5 As shown in (a), a larger α will lead to and This is because a larger α causes the interference signal to decay faster during propagation, thereby increasing the SINR of the base station, cellular device, and D2D device. As the SINR increases, and The probability also increases. For a fixed θ, an increase in κ results in of the decline, while and remains relatively unchanged, such as Figure 5 (b). Note that the actual ratio of κ (in dB) is 10 κ / 10 (dimensionless). Therefore, a larger κ indicates stronger self-interference of full-duplex D2D devices, resulting in a decrease in their STP. However, the STP of individual base stations, cellular devices, and half-duplex D2D devices is not significantly affected. For a fixed θ, σ 2 The increase will lead to and The value of is reduced, as shown in the figure 5(c). This is because the larger σ 2 This will result in a decrease in the SINR of each base station, cellular device, and half-duplex D2D device. Therefore, as the SINR decreases, the probability and Will also decrease.

[0079] Figure 6 A base station according to an embodiment of the present invention Cellular devices D2D devices in half-duplex mode and D2D devices in full-duplex mode The STP increases with the base station protection domain radius d b , the transmission probability of the base station Transmission probability of cellular devices and the probability p of a half-duplex D2D device H The following observations are obtained from the schematic diagram of the changes with different settings: Given and p H , with d b Increase, and Increase, while and This is because as d b As the activation probability of D2D devices increases, a Reduced, less D2D transmission leads to and Increase. On the contrary, d b The increase of and There was no significant effect. Given d b , the larger Will cause and The value of is reduced, such as Figure 6 This is because the increased transmission from the base station to the cellular device may introduce more mutual interference, negatively affecting the STP of the base station, cellular devices, and D2D devices. Given d b , the larger It will also lead to and The value of is reduced, such as Figure 6 (b) The reason is similar to the above discussion. Given d b , the larger p H Will cause and The value of increases, such as Figure 6 This is because the increased half-duplex-D2D transmission will reduce the full-duplex-D2D transmission, thereby reducing interference and reducing the impact on the base station, cellular devices and D2D transmission respectively.

[0080] Figure 7 is a base station according to an embodiment of the present invention Cellular devices D2D devices in half-duplex mode and D2D devices in full-duplex mode As the base station density λ b , Cellular device density λ c , cellular device protection domain radius d c and D2D device transmission power P d The following observations are obtained from the schematic diagram of the changes with different settings: Given λ c d b d c and P d , as the base station density λ b increase, and Increase, while and The reason is that as λ b As the area of ​​each Voronoi region decreases, the signal transmission distance between the base station and the cellular device is shortened, resulting in and On the contrary, the increase in base station density also increases the interference power experienced by D2D devices, resulting in and reduce. For a given λ b , the larger λ c lead to and The value of is low, such as Figure 7 The reason is that more transmissions from cellular devices will introduce additional interference to the transmissions of base stations, cellular devices, and D2D devices, thereby reducing their STPs. For a given λ b , when setting protection domains on the transmitting base station and cellular devices, and When both protection domains are not set, their values ​​are minimum. Figure 6 (b) and This is because setting the protection domain reduces the activation probability p of the D2D device. a , resulting in fewer D2D transmissions, thus increasing and But yes and The impact of can be ignored. For a given λ b , the larger P d Will lead to higher and The larger P d It will also lead to lower and like Figure 7 (c). This is because the higher P d is associated with an increase in the power of the desired signal received by the D2D device, thereby enhancing and However, the larger P d It also increases the unwanted interference power received by base stations and cellular devices, thereby reducing and

[0081] All simulation results are highly consistent with the theoretical results, thus verifying the accuracy of the analytical model. Based on the simulation, the following three observations are summarized. Dense coexistence of cellular devices and D2D devices: Increasing the density of base stations helps improve the STP (successful transmission probability) of base stations and cellular devices. Protection domains around base stations and cellular devices: Increasing the radius of both protection domains can improve STP of D2D devices. Half-duplex / full-duplex mode selection: Reducing the probability of D2D devices operating in full-duplex mode can improve their STP.

[0082] Based on the above observations, the analytical model can help practitioners, such as network operators or engineers, estimate the actual performance of heterogeneous IoT. For example, it can configure key network parameters under different application scenarios - including the density of deployed base stations, the radius of two types of protection domains, and the probability of D2D devices working in full-duplex mode.

[0083] The present invention also provides a communication device for a heterogeneous Internet of Things, comprising: a first establishment module, used to establish a first protection domain around a transmission base station, for reducing the interference of cellular devices supported by the base station to a D2D device; a second establishment module, used to establish a second protection domain around the D2D device, for reducing the interference of transmission cellular devices other than the cellular device to the D2D device; and a determination module, used to determine the probability of successful transmission of the D2D device based on a random geometric model, so as to evaluate and optimize the communication of the D2D device.

[0084] In heterogeneous IoT, cellular devices and D2D devices share spectrum, which leads to serious mutual interference and affects communication quality. The existing technology focuses on the management of a single interference source and lacks a comprehensive interference control strategy. The present invention effectively reduces multi-source interference by setting up protection domains around transmission base stations and D2D devices respectively, and at the same time evaluates and optimizes the communication of D2D devices based on random geometric models, significantly improving the system's anti-interference ability and communication efficiency.

[0085] According to an embodiment of the present invention, the determination module determines the successful transmission probability of the D2D device according to the following formula: in: r d is the transmission distance of the D2D device, d d is the maximum transmission distance of the D2D device, For r d The probability density function of For all interference I d The expected value of the probability that the signal to interference noise ratio of the D2D device under θ is greater than the threshold θ.

[0086] According to an embodiment of the present invention, in: p a is the probability that the D2D device is in an activated state, is the probability that the D2D device is located in the first protection domain, is the probability that the D2D device is located in the second protection domain, is the density of transmission base stations, To transmit the density of cellular devices, d b is the radius of the first protection domain, d c is the radius of the second protection domain.

[0087] The embodiment of the present invention describes that at a given distance r d and interference I d The probability that a D2D device can successfully transmit under certain conditions. By calculating the probability of successful transmission of a D2D device based on a random geometric model, the present invention can accurately evaluate the communication performance of the device under different network environments. This method takes into account the influence of multiple interference sources (such as base stations, cellular devices, and other D2D devices), and uses the calculation of probability density functions and signal-to-interference-noise ratio (SINR) thresholds to provide an accurate prediction of the communication success rate of D2D devices. Through this method, the scheduling and spectrum allocation of D2D communications can be optimized, the resource utilization of the network can be improved, interference can be reduced, and the reliability of D2D devices can be ensured.

[0088] Heterogeneous IoT integrates a large number of cellular and D2D devices and has become a fundamental component of 5G / B5G networks. In the context of full-duplex D2D communication in heterogeneous IoT, in order to mitigate the interference between cellular and D2D transmissions, it is proposed to introduce protection domains around transmission base stations and cellular devices. This paper proposes a novel spatial distribution model that effectively captures the location randomness of cellular and D2D devices and their interdependence. Through this model, the paper develops an analytical model to derive the STP expressions of base stations, cellular devices, and D2D devices, taking into account the intrinsic randomness and interrelationship between cellular and D2D transmissions, and describing the complex mutual interference caused by the two types of protection domains. Extensive Monte Carlo simulations verify the high accuracy of the proposed theoretical model.

[0089] The embodiment of the present invention describes the activation probability of D2D devices under specific density and protection domain radius, that is, the probability of whether D2D devices can participate in communication under given interference and communication conditions. By combining the influence of base station density, cellular device density and protection domain radius, the present invention designs an effective activation probability adjustment mechanism. By adjusting the protection domain radius and device density, the working state of D2D devices can be adjusted under different network densities and interference conditions, thereby improving the communication efficiency of D2D devices and the overall performance of the system. This method ensures that D2D devices can work stably and efficiently in a changing network environment, and optimizes the use of spectrum and the allocation of communication resources.

[0090] In summary, the present invention provides a communication method and device for a heterogeneous Internet of Things. The method includes the following steps: establishing a first protection domain around a transmission base station to reduce the interference of cellular devices supported by the base station to D2D devices; establishing a second protection domain around the D2D device to reduce the interference of transmission cellular devices other than the cellular device to the D2D device; and determining the probability of successful transmission of the D2D device based on a random geometric model to evaluate and optimize the communication of the D2D device. The present invention effectively reduces multi-source interference by respectively setting protection domains around the transmission base station and the D2D device, and at the same time evaluates and optimizes the communication of the D2D device based on the random geometric model, significantly improving the anti-interference capability and communication efficiency of the system.

[0091] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A communication method for heterogeneous Internet of Things, characterized in that: include: Establishing a first protection domain around a transmission base station to reduce interference of a cellular device supported by the transmission base station to a D2D device; Establishing a second protection domain around the D2D device to reduce interference of transmission cellular devices other than the cellular device to the D2D device; as well as Based on the random geometric model, the probability of successful transmission of the D2D device is determined to evaluate and optimize the communication of the D2D device.

2. The communication method for heterogeneous Internet of Things according to claim 1, characterized in that: Based on the random geometric model, the successful transmission probability of the D2D device is determined according to the following formula: in: r d is the transmission distance of the D2D device, d d is the maximum transmission distance given by the D2D device, For r d The probability density function of For all interference I d The expected value of the probability that the signal to interference noise ratio of the D2D device is greater than the threshold θ.

3. The communication method for heterogeneous Internet of Things according to claim 2, characterized in that: in: μ is the exponential distribution parameter that the channel power gain obeys, α is the path loss exponent, 2<α<6, P d is the downlink transmission probability within the cell, and They are and In s d The Laplace transform at is the interference of the transmission base station to the D2D device, is the interference of the transmitting cellular device on the D2D device, is the interference of the transmitting half-duplex device on the D2D device, The interference of the full-duplex device transmitting to the D2D device.

4. The communication method for heterogeneous Internet of Things according to claim 3, characterized in that: in: is the density of the transmission base stations, is the density of the transmitting cellular devices, λ H is the density of activated half-duplex mode D2D devices, λ F is the density of D2D devices in full-duplex mode, 5. The communication method for heterogeneous Internet of Things according to claim 4, characterized in that: in: p H is the probability that the D2D device operates in half-duplex mode, p F is the probability that the D2D device operates in full-duplex mode, The density of the D2D devices activated.

6. The communication method for heterogeneous Internet of Things according to any one of claims 1 to 5, characterized in that: in: p a is the probability that the D2D device is in an activated state, is the probability that the D2D device is located in the first protection domain, is the probability that the D2D device is located in the second protection domain, is the density of the transmission base stations, is the density of the transmitting cellular devices, d b is the radius of the first protection domain, d c is the radius of the second protection domain.

7. A communication device for heterogeneous Internet of Things, characterized in that: include: A first establishment module is used to establish a first protection domain around a transmission base station to reduce interference of a cellular device supported by the base station to a D2D device; A second establishment module is used to establish a second protection domain around the D2D device to reduce interference of transmission cellular devices other than the cellular device to the D2D device; as well as The determination module is used to determine the success transmission probability of the D2D device based on a random geometric model to evaluate and optimize the communication of the D2D device.

8. The communication device for heterogeneous Internet of Things according to claim 7, characterized in that: The determination module determines the successful transmission probability of the D2D device according to the following formula in: r d is the transmission distance of the D2D device, d d is the maximum transmission distance given by the D2D device, For r d The probability density function of For all interference I d The expected value of the probability that the signal to interference noise ratio of the D2D device is greater than the threshold θ.

9. The communication device for heterogeneous Internet of Things according to claim 8, characterized in that: in: μ is the exponential distribution parameter that the channel power gain obeys, α is the path loss exponent, 2<α<6, P d is the downlink transmission probability within the cell, and They are and In s d The Laplace transform at is the interference of the transmission base station to the D2D device, is the interference of the transmitting cellular device on the D2D device, is the interference of the transmitting half-duplex device on the D2D device, The interference of the full-duplex device transmitting to the D2D device.

10. The communication device for heterogeneous Internet of Things according to any one of claims 7 to 9, characterized in that: in: p a is the probability that the D2D device is in an activated state, is the probability that the D2D device is located in the first protection domain, is the probability that the D2D device is located in the second protection domain, is the density of the transmission base stations, is the density of the transmitting cellular devices, d b is the radius of the first protection domain, d c is the radius of the second protection domain.

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