Scattering interference control method of intelligent reflecting surface auxiliary network

Abstract

The embodiment of the invention provides a scattering interference control method for an intelligent reflector-assisted network, which comprises the following steps of: estimating the characteristics of a link where a ground user is located, and determining information such as environmental parameters and base station density of a region where the ground user is located; according to scattering electromagnetic characteristics of the intelligent reflecting surface, constructing a scattering power model of the intelligent reflecting surface; a scattering power control factor is introduced to quantify the scattering power control characteristic of the intelligent reflecting surface; quantifying distribution characteristics of the intelligent reflecting surface according to the scattering power control range; quantizing useful and interference signal power distribution received by a user side under the scattering power control of the intelligent reflecting surface, and deducing a signal to interference plus noise ratio; and determining optimal deployment parameters of the intelligent reflecting surface under scattering power control by giving a coverage rate expression under the model. According to the embodiment of the invention, the problems of how to introduce scattering power control on the intelligent reflecting surface and how to configure deployment parameters and power control intensity and range of the 5G network are solved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a parameter configuration method for intelligent reflective surface-assisted coverage extension under scattering power control in a cellular network in fifth-generation mobile communications 5G and future 6G. Background Art

[0002] Smart reflective surface-assisted terrestrial cellular networks have become a research hotspot in the field of wireless communications. They have the following advantages: reconstruction of line-of-sight transmission and large-scale coverage expansion:

[0003] However, due to the passive random scattering characteristics of the smart reflective surface, the cumulative interference in the system is too serious, which limits the performance of the smart reflective surface and makes it impossible to fully utilize its advantages.

[0004] Therefore, how to introduce scattered power control of the smart reflector and configure its deployment parameters as well as power control intensity and range is an urgent problem to be solved. Summary of the invention

[0005] The purpose of the present invention is to provide a method for controlling scattering interference of an intelligent reflector-assisted network to reduce the accumulated interference of passive scattering of the intelligent reflector and improve system performance. The specific technical solution is as follows:

[0006] Step 200, estimate the link characteristics of the ground user to determine the environmental parameters of the area, base station density and other information.

[0007] Step 210: construct a scattering power model of the smart reflective surface according to its scattering electromagnetic characteristics.

[0008] Step 220: introducing a scattered power control factor to quantify the scattered power control characteristics of the smart reflector.

[0009] Step 230: quantify the distribution characteristics of the smart reflective surface according to the scattered power control range.

[0010] Step 240: quantify the power distribution of useful and interfering signals received by the user end under the control of the scattering power of the intelligent reflector, and derive the signal-to-interference-noise ratio.

[0011] Step 250, by providing a coverage expression under the model, the optimal deployment parameters of the smart reflective surface under scattering power control are determined.

[0012] Optionally, estimating the link characteristics of the ground user to determine the environmental parameters of the area, base station density and other information specifically includes:

[0013] According to the different environments, the corresponding environmental parameters are quantified to facilitate the determination of subsequent channel modeling parameters; at the same time, the number of deployed base stations is determined according to the deployment area.

[0014] Optionally, constructing a scattering power model of the smart reflective surface according to its scattering electromagnetic characteristics specifically includes:

[0015] The smart reflector reoptimizes the radio propagation environment by dynamically adjusting the phase of the independent reflector units, thereby enhancing the useful signal. That is, the smart reflector can change the phase of the reflection path to match the transmission direction with the direction of the intended receiver. Since the distance between the base station and the smart reflector is large enough relative to the size of the smart reflector, it can be assumed that the incident electromagnetic wave on the smart reflector is a plane wave. According to the generalized Snell's law, the incident angle and the expected reflection angle distribution are expressed as θ i and θ r , the optimal phase of the smart reflector can be expressed as:

[0016]

[0017] Wherein, k = 2π / λ represents the wave number, λ represents the wavelength, and y represents the coordinate of the reflection unit of each smart reflection surface along the transmission direction of the incoming electromagnetic wave. Represents the local surface phase of each smart reflector unit.

[0018] Since the phase of the smart reflective surface is carefully designed to serve the associated base station and the user, for other non-associated base stations, the smart reflective surface only acts as a metasurface with a given configuration phase, and the undesired reflection of the incident signal is also called a scattered signal. Assume that the incident angle of scattering and the undesired reflection angle are defined as θ f and θ u , we can get

[0019]

[0020] Where z = sin(θ f )-sin(θ i )+sin(θ r ), the scattered signal will be reflected only when |z|∈[0,1), otherwise, the scattered signal will attenuate along the metasurface. At the same time, since all angles obey uniform distribution, the probability density function of z can be obtained by convolution, which is expressed as:

[0021]

[0022] Then the probability of a signal that can be scattered by the smart reflector without attenuation along the surface of the smart reflector can be expressed as:

[0023]

[0024] Therefore, θ u=arcsin(z) can be expressed as:

[0025]

[0026] The signal scattered from the smart reflector will be transmitted in many different directions. Due to the non-uniform distribution of the undesired reflection angle, the scattered power emitted by the smart reflector in different spatial directions is different. Therefore, it is necessary to introduce the concept of spatial density to identify the scattered power emitted by the smart reflector in different spatial directions. In other words, the power spatial density function of the scattered smart reflector is:

[0027]

[0028] Among them, P IRS is the incident power that can be scattered by the smart reflector, θ u ∈(-π / 2,π / 2) represents the angle between the scattered signal and the normal of the smart reflective surface.

[0029] Optionally, the introducing of the scattered power control factor to quantify the scattered power control characteristics of the smart reflector specifically includes:

[0030] In order to suppress the interference caused by the passive random scattering of the smart reflector, a smart reflector scattering power control strategy is proposed. According to the reference signal received power, a typical user selects the nearest base station and smart reflector as the service base station and associated reflector. The user will require the smart reflector within the circular area of ​​radius v0 to μv0 to perform power control to reduce interference, where v0 is the distance between the user and its associated reflector IRS0, and μ is defined as the radius coefficient of the smart reflector scattering power control. The value of μ is the same for all users. The relationship function between the power of the signal reflected by the smart reflector and the reflection angle is similar to the main sidelobe distribution of the antenna. For the desired reflection angle, the reflected power of the smart reflector can be expressed as P IRS cos 2 (θ i ), where θ i is the incident signal angle of the smart reflector. Therefore, this chapter will add a tilt angle φ to the smart reflector that is requested to be controlled, where φ∈[0,π / 2], and the scattered power of the smart reflector in the circular area from radius v0 to μv0 is:

[0031]

[0032] Where φ is defined as the scattering power control factor of the smart reflector. Since the μv0 ranges of different users may overlap, this means that the user-associated reflector may also receive a power control request and thus tilt. The reflected signal provided by the tilted smart reflector to the user can be expressed as P IRS cos2 (θ i +φ). According to the properties of the Poisson point process, the average reflected power of the smart reflector when the phase is aligned is:

[0033]

[0034] Optionally, quantifying the distribution characteristics of the intelligent reflector surface according to the scattered power control range specifically includes:

[0035] Assume that a typical user is located at the origin o and is served by the base station closest to the typical user, that is, its serving base station BS0 is located at the origin (d0,0), then the distribution of the distance from the typical user to BS0 is:

[0036]

[0037] Similarly, the distribution of the distance from a typical user to the nearest IRS0 is:

[0038]

[0039] Under the conditions of given d0 and v0, IRS0 is evenly distributed on a circle with typical user UE0 as the center and v0 as the radius. Assume that the complementary angle of ∠IRS0-BS0-UE0 is Then given d0 and v0, u 0,0 The cumulative distribution function can be expressed as:

[0040]

[0041] Therefore, its probability density function can be expressed as:

[0042]

[0043] Optionally, under the quantized intelligent reflector scattering power control, the user end receives the useful and interference signal power distribution, and derives the signal to interference noise ratio, specifically including:

[0044] In order to focus on the impact of the scattering power control of the intelligent reflector in the network on the performance of the downlink transmission network, we do not consider the direct signal from the base station to the user. Assuming that all channels are independent and identically distributed, each reflector unit of the intelligent reflector receives the superimposed multipath signal from the base station and scatters the combined signal with an adjustable phase as if it came from the signal source. According to the independent phase adjustment of each reflector unit, and They represent the base station BS i To the intelligent reflective surface IRS j and intelligent reflective surface IRS j The channel matrix to the typical user UE0, where represents a complex matrix of dimension N×1, [·] T Represents matrix transpose. IRS j The phase shift matrix of , where diag{x} represents a diagonal matrix, and each diagonal element is the corresponding element in x. Therefore, BS i -IRS j -The cascaded channel of UE0 can be expressed as:

[0045]

[0046] in, Indicates the BS corresponding to reflection unit n i -IRS j -UE0 cascade channel.

[0047] For B.S. i -IRS j -UE0 cascade channel, using distance-dependent large-scale path loss model and Rayleigh fading. BS i -n th IRS j Link and n th IRS j -The channel power gain of the UE0 link can be expressed as:

[0048]

[0049] Where β=(4πf c / c) -2 represents the average signal power gain at a reference distance of 1m based on the free space path loss model, where c represents the speed of light, and f c Indicates the carrier frequency, with u i,j BS i -IRS j Average channel gain vs. distance of the channel, With v j IRS j - Average channel gain and distance of UE0 channel, G b,n and G r,n represents small-scale fading. For simplicity, we assume that G b,n and G r,n is Rayleigh fading, that is, G~exp(1). Therefore, the amplitude Obey scale parameter Rayleigh distribution, amplitude Obey scale parameter The Rayleigh distribution of .

[0050] Without considering the direct signal from the base station to the user, the signal received by the typical user UE0 from the serving base station BS0 is composed of the signals reflected / scattered by all metasurfaces. The nearest IRS0 can adjust its own electromagnetic properties to achieve phase matching of the reflected signals of each reflection unit of IRS0, while other non-auxiliary smart reflection surfaces will generate scattered signals. Therefore, the useful signal can be expressed as S = S bf +S sc Given the distance between BS0 and IRS0 is u 0,0 , the distance between IRS0 and UE0 is v0, and the power S received by a typical user from IRS0 is bf It can be expressed as:

[0051]

[0052] Among them, χ b,n and χ r,n Represents the amplitude of small-scale fading, all of which obey the scale parameter Rayleigh distribution, then χ b,n χ r,n represents a double-Ray leigh random variable, and for a double-Rayleigh random variable Y = X1X2, where X1 and X2 are independent and The overall fading coefficient of the cascade channel is the sum of N independent and identically distributed double-Ray random variables. Then, when the number of elements N is large, using the central limit theorem, the overall fading coefficient obeys a Gaussian distribution:

[0053]

[0054] Therefore, for the fading power gain ξ r It obeys the non-central chi-square distribution of first-order scaling, and its probability density function can be expressed as:

[0055]

[0056] According to the scattering power model of the smart reflector, the scattering power of the useful signal can be expressed as:

[0057]

[0058] Where Q represents the probability that the incident signal can be scattered by the smart reflector, θ j IRS j The signal scattered to a typical user and the IRS j The angle between the normals.

[0059] Given the distance from IRS0 to BS0 is u 0,0, when the distance from UE0 to IRS0 is v0 and the distance from UE0 to BS0 is d0, the first-order moment of S can be expressed as:

[0060]

[0061] The second-order moment can be expressed as:

[0062]

[0063] E3=(E1) 2 +E2

[0064] Using Gamma moment matching, S can be approximated as a Gamma distribution Γ(k S ,θ S ), where the shape parameter k S and the scale parameter θ S It can be expressed as:

[0065]

[0066]

[0067] For the interference signal power, we first consider the scattering probability of the random incident interference signal, and define the typical IRS o The transmission equivalent power is:

[0068]

[0069] Using the scattered power model of the smart reflective surface, the smart reflective surface can be regarded as a spatially distributed interference source. Therefore, a typical user will receive reflected interference from the smart reflective surface, and its power density depends on its angle with these smart reflective surfaces. Then the interference received by the typical user can be expressed as:

[0070]

[0071] Among them, θ u represents the angle between the signal scattered by the smart reflective surface to the typical user and the normal line of the smart reflective surface. Since the distribution of the smart reflective surface follows the Poisson point process, then Θ v It can be expressed as:

[0072]

[0073] Given the distance u from IRS0 to BS0 0,0 , when the distance from UE0 to IRS0 is v0 and the distance from UE0 to BS0 is d0, the Lap lace transformation of the interference power is:

[0074]

[0075] Among them, (a) follows the exponential function operation rule, (b) follows the moment generator function of the negative exponential distribution random variable, and (c) follows the measure strength λ I The probability generating functional of the Poisson point process. According to the power distribution characteristics of the useful and interfering signals, the signal-to-interference-to-noise ratio of the user end can be quantified.

[0076] Optionally, determining the optimal deployment parameters of the smart reflective surface under scattering power control by providing a coverage expression under the model specifically includes:

[0077] According to the definition of coverage, the coverage can be expressed as:

[0078]

[0079] Combining the useful and interference signal powers, the coverage can finally be expressed as:

[0080]

[0081] Furthermore, the optimal deployment parameters, control intensity and range of the intelligent reflector for scattering power control in different environments can be obtained based on the coverage expression.

[0082] Beneficial Effects

[0083] It can be seen from the above that the present invention provides a method for controlling scattering interference of a smart reflective surface-assisted network, which effectively reduces the accumulated interference at the user and improves the user communication performance by controlling the scattering power of the smart reflective surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a system model diagram of a scattering interference control method of an intelligent reflector-assisted network of the present invention;

[0085] Figure 2 It is an implementation flow chart of the present invention;

[0086] Figure 3 It is a schematic diagram of the variation of user coverage with power control intensity;

[0087] Figure 4 It is a schematic diagram showing the variation of user coverage with the deployment density of smart reflective surfaces; DETAILED DESCRIPTION

[0088] In order to clarify the purpose, implementation scheme and technical advantages of the present invention, the present invention is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0089] Figure 1This is a practical application scenario of the scattering interference control method of the intelligent reflector-assisted network of the present invention: the intelligent reflector acts as a passive network node to expand coverage and enhance the received signal strength at the user. The intelligent reflector suppresses the accumulated interference at the user through scattering power control.

[0090] Figure 2 A schematic flow chart of a scattering interference control method for an intelligent reflector-assisted network provided by the present invention includes:

[0091] Step 200, estimate the link characteristics of the ground user to determine the environmental parameters of the area, base station density and other information.

[0092] Step 210: construct a scattering power model of the smart reflective surface according to its scattering electromagnetic characteristics.

[0093] Step 220: introducing a scattered power control factor to quantify the scattered power control characteristics of the smart reflector.

[0094] Step 230: quantify the distribution characteristics of the smart reflective surface according to the scattered power control range.

[0095] Step 240: quantify the power distribution of useful and interfering signals received by the user end under the control of the scattering power of the intelligent reflector, and derive the signal-to-interference-noise ratio.

[0096] Step 250, by providing a coverage expression under the model, the optimal deployment parameters of the smart reflective surface under scattering power control are determined.

[0097] In step 200, the corresponding environmental parameters are quantified according to the different environments so as to determine the subsequent channel modeling parameters; at the same time, the number of deployed base stations is determined according to the deployment area.

[0098] In step 210, the smart reflective surface re-optimizes the radio propagation environment by dynamically adjusting the phase of the independent reflective unit, thereby enhancing the useful signal. That is, the smart reflective surface can change the phase of the reflection path so that the transmission direction matches the direction of the intended receiver. Since the distance between the base station and the smart reflective surface is large enough relative to the size of the smart reflective surface, it can be assumed that the incident electromagnetic wave on the smart reflective surface is a plane wave. According to the generalized Snell's law, the incident angle and the expected reflection angle distribution are assumed to be expressed as θ i and θ r , the optimal phase of the smart reflector can be expressed as:

[0099]

[0100] Wherein, k = 2π / λ represents the wave number, λ represents the wavelength, and y represents the coordinate of the reflection unit of each smart reflection surface along the transmission direction of the incoming electromagnetic wave. Represents the local surface phase of each smart reflector unit.

[0101] Since the phase of the smart reflective surface is carefully designed to serve the associated base station and the user, for other non-associated base stations, the smart reflective surface only acts as a metasurface with a given configuration phase, and the undesired reflection of the incident signal is also called a scattered signal. Assume that the incident angle of scattering and the undesired reflection angle are defined as θ f and θ u , we can get

[0102]

[0103] Where z = sin(θ f )-sin(θ i )+sin(θ r ), the scattered signal will be reflected only when |z|∈[0,1), otherwise, the scattered signal will attenuate along the metasurface. At the same time, since all angles obey uniform distribution, the probability density function of z can be obtained by convolution, which is expressed as:

[0104]

[0105] Then the probability of a signal that can be scattered by the smart reflector without attenuation along the surface of the smart reflector can be expressed as:

[0106]

[0107] Therefore, θ u =arcsin(z) can be expressed as:

[0108]

[0109] The signal scattered from the smart reflector will be transmitted in many different directions. Due to the non-uniform distribution of the undesired reflection angle, the scattered power emitted by the smart reflector in different spatial directions is different. Therefore, it is necessary to introduce the concept of spatial density to identify the scattered power emitted by the smart reflector in different spatial directions. In other words, the power spatial density function of the scattered smart reflector is:

[0110]

[0111] Among them, P IRS is the incident power that can be scattered by the smart reflector, θ u ∈(-π / 2,π / 2) represents the angle between the scattered signal and the normal of the smart reflective surface.

[0112] In step 220, in order to suppress the interference caused by the passive random scattering of the smart reflector, a smart reflector scattering power control strategy is proposed. According to the reference signal received power, a typical user selects the nearest base station and smart reflector as the service base station and associated reflector. The user will require the smart reflector within the circular area of ​​radius v0 to μv0 to perform power control to reduce interference, where v0 is the distance between the user and its associated reflector IRS0, μ is defined as the radius coefficient of the smart reflector scattering power control, and the value of μ is the same for all users. The relationship function between the power of the signal reflected by the smart reflector and the reflection angle is similar to the main sidelobe distribution of the antenna, and for the desired reflection angle, the reflected power of the smart reflector can be expressed as P IRS cos 2 (θ i ), where θ i is the incident signal angle of the smart reflector. Therefore, this chapter will add a tilt angle φ to the smart reflector that is requested to be controlled, where φ∈[0,π / 2], and the scattered power of the smart reflector in the circular area from radius v0 to μv0 is:

[0113]

[0114] Where φ is defined as the scattering power control factor of the smart reflector. Since the μv0 ranges of different users may overlap, this means that the user-associated reflector may also receive a power control request and thus tilt. The reflected signal provided by the tilted smart reflector to the user can be expressed as P IRS cos 2 (θ i +φ). According to the properties of the Poisson point process, the average reflected power of the smart reflector when the phase is aligned is:

[0115]

[0116] In step 230, it is assumed that the typical user is located at the origin o and is served by the base station closest to the typical user, that is, its serving base station BS0 is located at the origin (d0,0), then the distribution of the distance from the typical user to BS0 is:

[0117]

[0118] Similarly, the distribution of the distance from a typical user to the nearest IRS0 is:

[0119]

[0120] Under the conditions of given d0 and v0, IRS0 is evenly distributed on a circle with typical user UE0 as the center and v0 as the radius. Assume that the complementary angle of ∠IRS0-BS0-UE0 is Then given d0 and v0, u0,0 The cumulative distribution function can be expressed as:

[0121]

[0122] Therefore, its probability density function can be expressed as:

[0123]

[0124] In step 240, in order to focus on the impact of the scattering power control of the intelligent reflector in the network on the downlink transmission network performance, we do not consider the direct signal from the base station to the user. Assuming that all channels are independent and identically distributed, each reflector unit of the intelligent reflector receives the superimposed multipath signal from the base station and scatters the combined signal with an adjustable phase as if it came from the signal source. According to the independent phase adjustment of each reflector unit, and They represent the base station BS i To the intelligent reflective surface IRS j and intelligent reflective surface IRS j The channel matrix to the typical user UE0, where represents a complex matrix of dimension N×1, [·] T Represents matrix transpose. IRS j The phase shift matrix of , where diag{x} represents a diagonal matrix, and each diagonal element is the corresponding element in x. Therefore, BS i -IRS j -The cascaded channel of UE0 can be expressed as:

[0125]

[0126] in, Indicates the BS corresponding to reflection unit n i -IRS j -UE0 cascade channel.

[0127] For B.S. i -IRS j -UE0 cascade channel, using distance-dependent large-scale path loss model and Rayleigh fading. BS i -n th IRS j Link and n th IRS j -The channel power gain of the UE0 link can be expressed as:

[0128]

[0129] Where β=(4πf c / c)-2 represents the average signal power gain at a reference distance of 1m based on the free space path loss model, where c represents the speed of light, and f c Indicates the carrier frequency, with u i,j BS i -IRS j Average channel gain vs. distance of the channel, With v j IRS j - Average channel gain and distance of UE0 channel, G b,n and G r,n represents small-scale fading. For simplicity, we assume that G b,n and G r,n is Rayleigh fading, that is, G~exp(1). Therefore, the amplitude Obey scale parameter Rayleigh distribution, amplitude Obey scale parameter The Rayleigh distribution of .

[0130] Without considering the direct signal from the base station to the user, the signal received by the typical user UE0 from the serving base station BS0 is composed of the signals reflected / scattered by all metasurfaces. The nearest IRS0 can adjust its own electromagnetic properties to achieve phase matching of the reflected signals of each reflection unit of IRS0, while other non-auxiliary smart reflection surfaces will generate scattered signals. Therefore, the useful signal can be expressed as S = S bf +S sc Given the distance between BS0 and IRS0 is u 0,0 , the distance between IRS0 and UE0 is v0, and the power S received by a typical user from IRS0 is bf It can be expressed as:

[0131]

[0132] Among them, χ b,n and χ r,n Represents the amplitude of small-scale fading, all of which obey the scale parameter Rayleigh distribution, then χ b,n χ r,n represents a double-Ray leigh random variable, and for a double-Rayleigh random variable Y = X1X2, where X1 and X2 are independent and The overall fading coefficient of the cascade channel is the sum of N independent and identically distributed double-Ray random variables. Then, when the number of elements N is large, using the central limit theorem, the overall fading coefficient obeys a Gaussian distribution:

[0133]

[0134] Therefore, for the fading power gain ξ r It obeys the non-central chi-square distribution of first-order scaling, and its probability density function can be expressed as:

[0135]

[0136] According to the scattering power model of the smart reflector, the scattering power of the useful signal can be expressed as:

[0137]

[0138] Where Q represents the probability that the incident signal can be scattered by the smart reflector, θ j IRS j The signal scattered to a typical user and the IRS j The angle between the normals.

[0139] Given the distance from IRS0 to BS0 is u 0,0 , when the distance from UE0 to IRS0 is v0 and the distance from UE0 to BS0 is d0, the first-order moment of S can be expressed as:

[0140]

[0141] The second-order moment can be expressed as:

[0142]

[0143] E3=(E1) 2 +E2

[0144] Using Gamma moment matching, S can be approximated as a Gamma distribution Γ(k S ,θ S ), where the shape parameter k S and the scale parameter θ S It can be expressed as:

[0145]

[0146] For the interference signal power, we first consider the scattering probability of the random incident interference signal, and define the typical IRS o The transmission equivalent power is:

[0147]

[0148]

[0149] Using the scattered power model of the smart reflective surface, the smart reflective surface can be regarded as a spatially distributed interference source. Therefore, a typical user will receive reflected interference from the smart reflective surface, and its power density depends on its angle with these smart reflective surfaces. Then the interference received by the typical user can be expressed as:

[0150]

[0151] Among them, θ u represents the angle between the signal scattered by the smart reflective surface to the typical user and the normal line of the smart reflective surface. Since the distribution of the smart reflective surface follows the Poisson point process, then Θ v It can be expressed as:

[0152]

[0153] Given the distance u from IRS0 to BS0 0,0 , when the distance from UE0 to IRS0 is v0 and the distance from UE0 to BS0 is d0, the Lap lace transformation of the interference power is:

[0154]

[0155] Among them, (a) follows the exponential function operation rule, (b) follows the moment generator function of the negative exponential distribution random variable, and (c) follows the measure strength λ I The probability generating functional of the Poisson point process. According to the power distribution characteristics of the useful and interfering signals, the signal-to-interference-to-noise ratio of the user end can be quantified.

[0156] In step 250, according to the definition of coverage, the coverage can be expressed as:

[0157]

[0158] Combining the useful and interference signal powers, the coverage can finally be expressed as:

[0159]

[0160] Furthermore, the optimal deployment parameters, control intensity and range of the intelligent reflector for scattering power control in different environments can be obtained based on the coverage expression.

[0161] Figure 3It is the intention of user coverage rate changing with the power control intensity factor. As can be seen from the figure, when the density of the intelligent reflective surface is large, the coverage rate increases first and then decreases with the increase of the scattering power control factor. There is an optimum that maximizes the coverage rate. When the number of reflection units of the intelligent reflective surface is N=300, the maximum gain can be 23.3%. At that time, as the scattering power control factor increases, the coverage rate increases, but the overall gain is very small. When the number of reflection units of the intelligent reflective surface is N=300, the maximum gain is only 8.1%. This is because when the density of the intelligent reflective surface is too large, the overlapping area of ​​power control of different users increases, and the service transmission link also needs to be power controlled, resulting in a reduction in the data link power, which makes the gain brought by the power control of the scattered signal small.

[0162] Figure 4 It is the intention that user coverage changes with the density of smart reflective surfaces. Regardless of whether the scattered signal is controlled in power, the system coverage will increase first and then decrease as the density of smart reflective surfaces increases. There is an optimal smart reflective surface density that maximizes the coverage, and changing the power of the scattered signal of the smart reflective surface will not change this optimal smart reflective surface density. And as can be seen from the figure, when N = 50, compared with no scattered power control, scattered power control at the optimal smart reflective surface density can achieve a performance gain of 42.4%. By controlling the power of the scattered signal of the smart reflective surface, the intensity and distribution of the scattered signal can be effectively adjusted, the interference level of the system can be reduced, and thus the system performance loss can be reduced.

Claims

1. A method for controlling scattering interference of an intelligent reflector-assisted network, characterized in that: include: Estimate the link characteristics of ground users and determine the environmental parameters of the area, base station density and other information; According to the electromagnetic characteristics of the smart reflector, a scattering power model is constructed; a scattering power control factor is introduced to quantify the scattering power control characteristics of the smart reflector; and the distribution characteristics of the smart reflector are quantified according to the scattering power control range. The power distribution of useful and interfering signals received by the user end under the scattering power control of the intelligent reflector is quantified, and the signal-to-interference-noise ratio is derived. The optimal deployment parameters of the intelligent reflector under scattering power control are determined by giving the coverage expression under the model.

2. The method according to claim 1, characterized in that The estimating of the link characteristics of the ground user to determine the environmental parameters of the area, base station density and other information specifically includes: According to the different environments, the corresponding environmental parameters are quantified to facilitate the determination of subsequent channel modeling parameters; at the same time, the number of deployed base stations is determined according to the deployment area.

3. The method according to claim 1, characterized in that The step of constructing a scattering power model of the smart reflector according to its scattering electromagnetic characteristics specifically includes: The smart reflector reoptimizes the radio propagation environment by dynamically adjusting the phase of the independent reflector unit, thereby enhancing the useful signal. That is, the smart reflector can change the phase of the reflection path to match the transmission direction with the direction of the expected receiver. Since the distance between the base station and the smart reflector is large enough relative to the size of the smart reflector, it can be assumed that the incident electromagnetic wave on the smart reflector is a plane wave. According to the generalized Snell's law, the incident angle and the expected reflection angle distribution are expressed as θ i and θ r , the optimal phase of the smart reflector can be expressed as: Wherein, k = 2π / λ represents the wave number, λ represents the wavelength, and y represents the coordinate of the reflection unit of each smart reflection surface along the transmission direction of the incoming electromagnetic wave. represents the local surface phase of each smart reflector unit; Since the phase of the smart reflective surface is carefully designed to serve the associated base station and the user, for other non-associated base stations, the smart reflective surface only acts as a metasurface with a given configuration phase, and the undesired reflection of the incident signal is also called a scattered signal. Assume that the incident angle of scattering and the undesired reflection angle are defined as θ f and θ u , we can get Where z = sin(θ f )-sin(θ i )+sin(θ r ), the scattered signal will be reflected only when |z|∈[0,1), otherwise, the scattered signal will attenuate along the metasurface. At the same time, since all angles obey uniform distribution, the probability density function of z can be obtained by convolution, which is expressed as: Then the probability of a signal that can be scattered by the smart reflector without attenuation along the surface of the smart reflector can be expressed as: Therefore, θ u =arcsin(z) can be expressed as: The signal scattered from the smart reflector will be transmitted in many different directions. Due to the non-uniform distribution of the undesired reflection angle, the scattered power emitted by the smart reflector in different spatial directions is different. Therefore, it is necessary to introduce the concept of spatial density to identify the scattered power emitted by the smart reflector in different spatial directions. In other words, the power spatial density function of the scattered smart reflector is: Among them, P IRS is the incident power that can be scattered by the smart reflector, θ u ∈(-π / 2,π / 2) represents the angle between the scattered signal and the normal of the smart reflective surface.

4. The method according to claim 1, characterized in that: The introduction of the scattered power control factor to quantify the scattered power control characteristics of the intelligent reflector specifically includes: In order to suppress the interference caused by the passive random scattering of the smart reflector, a smart reflector scattering power control strategy is proposed. According to the reference signal received power, a typical user selects the nearest base station and smart reflector as the service base station and associated reflector. The user will require the smart reflector within the circular area of ​​radius v0 to μv0 to perform power control to reduce interference, where v0 is the distance between the user and its associated reflector IRS0, and μ is defined as the radius coefficient of the smart reflector scattering power control. The value of μ is the same for all users. The relationship function between the power of the signal reflected by the smart reflector and the reflection angle is similar to the main sidelobe distribution of the antenna. For the desired reflection angle, the reflected power of the smart reflector can be expressed as P IRS cos 2 (θ i ), where θ i is the incident signal angle of the smart reflector. Therefore, this chapter will add a tilt angle φ to the smart reflector that is requested to be controlled, where φ∈[0,π / 2], and the scattered power of the smart reflector in the circular area from radius v0 to μv0 is: Where φ is defined as the scattering power control factor of the smart reflector. Since the μv0 ranges of different users may overlap, this means that the user-associated reflector may also receive a power control request and thus tilt. The reflected signal provided by the tilted smart reflector to the user can be expressed as P IRS cos 2 (θ i +φ). According to the properties of the Poisson point process, the average reflected power of the smart reflector when the phase is aligned is:

5. The method according to claim 1, characterized in that: The quantifying the distribution characteristics of the intelligent reflector surface according to the scattered power control range specifically includes: Assume that a typical user is located at the origin o and is served by the base station closest to the typical user, that is, its serving base station BS0 is located at the origin (d0,0), then the distribution of the distance from the typical user to BS0 is: Similarly, the distribution of the distance from a typical user to the nearest IRS0 is: Under the given conditions of d0 and v0, IRS0 is evenly distributed on a circle with the typical user UE0 as the center and v0 as the radius. Assuming that the complementary angle of ∠IRS0-BS0-UE0 is θ, then under the given conditions of d0 and v0, u 0,0 The cumulative distribution function can be expressed as: Therefore, its probability density function can be expressed as:

6. The method according to claim 1, characterized in that Under the quantized intelligent reflector scattering power control, the user end receives the useful and interference signal power distribution and derives the signal to interference noise ratio, specifically including: In order to focus on the impact of the scattering power control of the intelligent reflector in the network on the performance of the downlink transmission network, we do not consider the direct signal from the base station to the user; assume that all channels are independent and identically distributed, and each reflector unit of the intelligent reflector receives the superimposed multipath signal from the base station and scatters the combined signal with an adjustable phase as if it came from the signal source; according to the independent phase adjustment of each reflector unit and They represent the base station BS i To the intelligent reflective surface IRS j and intelligent reflective surface IRS j The channel matrix to the typical user UE0, where represents a complex matrix of dimension N×1, [·] T Represents matrix transpose; IRS j The phase shift matrix, where diag{x} represents a diagonal matrix, each diagonal element is the corresponding element in x; therefore BS i -IRS j -The cascaded channel of UE0 can be expressed as: in, Indicates the BS corresponding to reflection unit n i -IRS j -UE0 cascade channel; For B.S. i -IRS j -UE0 cascade channel, using distance-dependent large-scale path loss model and Rayleigh fading. BS i -n th IRS j Link and n th IRS j -The channel power gain of the UE0 link can be expressed as: Where β=(4πf c / c) -2 represents the average signal power gain at a reference distance of 1m based on the free space path loss model, where c represents the speed of light, and f c Indicates the carrier frequency, with u i,j BS i -IRS j Average channel gain vs. distance of the channel, With v j IRS j - Average channel gain and distance of UE0 channel, G b,n and G r,n represents small-scale fading. For simplicity, we assume that G b,n and G r,n is Rayleigh fading, that is, G~exp(1). Therefore, the amplitude Obey scale parameter Rayleigh distribution, amplitude Obey scale parameter Rayleigh distribution of Without considering the direct signal from the base station to the user, the signal received by the typical user UE0 from the serving base station BS0 is composed of the signals reflected / scattered by all metasurfaces. The nearest IRS0 can adjust its own electromagnetic properties to achieve phase matching of the reflected signals of each reflection unit of IRS0, while other non-auxiliary smart reflection surfaces will generate scattered signals. Therefore, the useful signal can be expressed as S = S bf +S sc Given the distance between BS0 and IRS0 is u 0,0 , the distance between IRS0 and UE0 is v0, and the power S received by a typical user from IRS0 is bf It can be expressed as: Among them, χ b,n and χ r,n Represents the amplitude of small-scale fading, all of which obey the scale parameter Rayleigh distribution, then χ b,n χ r,n represents a double-Rayleigh random variable, and for a double-Rayleigh random variable Y = X1X2, where X1 and X2 are independent and The overall fading coefficient of the cascade channel is the sum of N independent and identically distributed double-Rayleigh random variables. When the number of elements N is large, the overall fading coefficient follows a Gaussian distribution using the central limit theorem: Therefore, for the fading power gain ξ r It obeys the non-central chi-square distribution of first-order scaling, and its probability density function can be expressed as: According to the scattering power model of the smart reflector, the scattering power of the useful signal can be expressed as: Where Q represents the probability that the incident signal can be scattered by the smart reflector, θ j IRS j The signal scattered to a typical user and the IRS j The angle between the normals; Given the distance from IRS0 to BS0 is u 0,0 , when the distance from UE0 to IRS0 is v0 and the distance from UE0 to BS0 is d0, the first-order moment of S can be expressed as: The second-order moment can be expressed as: <h2 style=";text-align:left;direction:ltr">E3=(E1)<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +E2 Using Gamma moment matching, S can be approximated as a Gamma distribution Γ(k S ,θ S ), where the shape parameter k S and the scale parameter θ S It can be expressed as: For the interference signal power, we first consider the scattering probability of the random incident interference signal, and define the typical IRS o The transmission equivalent power is: Using the scattered power model of the smart reflective surface, the smart reflective surface can be regarded as a spatially distributed interference source; therefore, a typical user will receive reflected interference from the smart reflective surface, and its power density depends on its angle with these smart reflective surfaces. Then the interference received by the typical user can be expressed as: Among them, θ u represents the angle between the signal scattered by the smart reflective surface to the typical user and the normal line of the smart reflective surface. Since the distribution of the smart reflective surface follows the Poisson point process, then Θ v It can be expressed as: Given the distance u from IRS0 to BS0 0,0 , when the distance from UE0 to IRS0 is v0 and the distance from UE0 to BS0 is d0, the Laplace transform of the interference power is: Among them, (a) follows the exponential function operation rule, (b) follows the moment generator function of the negative exponential distribution random variable, and (c) follows the measure strength λ I The probability generating functional of the Poisson point process is obtained; according to the power distribution characteristics of the useful and interfering signals, the signal-to-interference-noise ratio properties of the user end reception can be quantified.

7. The method according to claim 1, characterized in that The optimal deployment parameters of the smart reflector under scattering power control are determined by providing a coverage expression under the model, specifically including: According to the definition of coverage, the coverage can be expressed as: Combining the useful and interference signal powers, the coverage can finally be expressed as: Furthermore, the optimal deployment parameters, control intensity and range of the intelligent reflector for scattering power control in different environments can be obtained based on the coverage expression.

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