General radio channel modeling method based on full-wave electromagnetic simulation

Abstract

The invention discloses a general radio channel modeling method based on full-wave electromagnetic simulation, and the method comprises the following steps: firstly depicting the response of radio channel key components such as a receiving and transmitting end antenna, a wireless transmission channel, a receiving and transmitting end matching network and internal and external noise sources, and the antenna parameters are determined through full-wave electromagnetic simulation; then calculating the total response of each component of the radio channel after cascading according to a cascading multi-port circuit network theory, and obtaining radio channel matrixes in physical significance and information theory significance; and finally, radio channel statistical characteristics and radio channel capacity are analyzed. Compared with an existing wireless propagation channel modeling method, the method has the advantages that topological parameters, radiation parameters and circuit parameters of the antenna are fully considered, and joint modeling of the antenna and the wireless propagation channel is achieved. Based on wireless propagation channel parameters and antenna parameters obtained through full-wave electromagnetic simulation, the radio channel modeling method can support various wireless propagation environments and antenna types.

Description

Technical Field

[0001] The present invention belongs to the field of radio channel modeling, and in particular relates to a universal radio channel modeling method based on full-wave electromagnetic simulation. Background Art

[0002] Sixth-generation (6G) mobile communication technology has garnered widespread attention worldwide. 6G will utilize key technologies such as intelligent metasurfaces, ultra-large-scale multiple-input multiple-output (MIMO), and aperture-restricted MIMO. Wireless channel research is fundamental to communication system design, performance evaluation and optimization, deployment, and standardization. New 6G technologies introduce new channel characteristics, making existing channel models inapplicable and necessitating the construction of new 6G channel models. 6G antenna arrays feature increased numbers of elements and decreased spacing between elements, making the antennas inextricably linked to the wireless propagation environment. Therefore, it is imperative to consider the radio channel, encompassing both the transmit and receive antennas and the wireless propagation channel.

[0003] Radio channel modeling methods can be mainly divided into methods based on basis function decomposition and methods based on circuit network representation of antennas, which are based on the perspectives of electromagnetic field theory ("field") and circuit theory ("path") respectively.

[0004] The radio channel modeling method based on basis function decomposition involves selecting appropriate basis functions, decomposing the electromagnetic field of the transmitting antenna, the electromagnetic field of the wireless propagation channel, and the electromagnetic field of the receiving antenna, examining the relationship between the basis function decomposition coefficients, and obtaining the radio channel matrix. Its shortcomings are: 1) This modeling method directly integrates electromagnetic field theory and information theory. The solution based on continuous space partial differential equations in electromagnetic field theory is incompatible with the solution based on probability theory and linear algebra in information theory. This makes the basis function decomposition method dependent on complete information about the antenna current density and the electromagnetic field of the wireless propagation environment. In practical engineering, it is difficult to fully and accurately obtain this data, resulting in high storage and computational complexity. 2) Random noise is difficult to measure in deterministic electromagnetic field theory. In fact, the radio channel modeling method based on basis function decomposition does not provide a physical entity corresponding to noise, yet both signal and noise are crucial in calculating channel capacity.

[0005] The steps of the radio channel modeling method using circuit networks to represent antennas are to accurately characterize the responses of the circuit networks corresponding to the key components of the radio channel, cascade the circuit network responses of the key components according to the principles of microwave networks, and obtain the radio channel matrix. Its shortcomings are: 1) Most studies assume that the antenna array elements used are ideal omnidirectional units, and do not use antenna data closer to reality, such as antenna radiation patterns and antenna impedance matrices obtained by full-wave electromagnetic simulation, as simulation inputs, which is inconsistent with the engineering reality in existing wireless communication systems; 2) In most studies, the array topology is limited to uniform linear arrays or uniform planar arrays, and no research is conducted on non-uniform or arbitrary planar array topologies; 3) All studies do not consider the universal wireless propagation channel model, and cannot accurately reflect the transmission mechanism of electromagnetic waves in the wireless propagation environment in full-band channels, full-coverage scenario channels, and full-application scenario channels. In most studies, the modeling of wireless propagation channels is limited to free space and line-of-sight scenarios; 4) Most studies do not fully consider important influencing factors and key components of radio channels, such as the impedance matching network at the transmit and receive ends, antenna thermal loss, antenna impedance matrix and radiation pattern under coupling, and internal and external noise sources; 5) Current research lacks a comprehensive and systematic analysis of channel statistical characteristics and channel capacity. Summary of the Invention

[0006] In response to the problems existing in the prior art, the present invention provides a universal radio channel modeling method based on full-wave electromagnetic simulation, which can provide model support for wireless communication systems enabled by key air interface technologies such as smart metasurfaces, ultra-large-scale MIMO, and aperture-limited MIMO.

[0007] To solve the above technical problems, the present invention provides the following technical solution: a general radio channel modeling method based on full-wave electromagnetic simulation, comprising the following steps:

[0008] S1. Generate a wireless propagation channel matrix based on the impulse response of the wireless propagation channel between the transmitting antenna and the receiving antenna, as well as the various losses of wireless propagation.

[0009] S2. Acquire antenna data based on full-wave electromagnetic simulation and generate an impedance matrix representing the circuit network between the antenna and the wireless propagation channel;

[0010] S3. Determine the transmitter impedance matching network matrix Z MT , receiving end impedance matching network matrix Z MR , emitter source voltage v G , set the source impedance to z G , the load impedance is z L , based on the statistical characteristics of the internal and external noise sources at the receiving end, generate the external noise voltage source at the receiving end Internal noise voltage source v at the receiving end N, the internal noise current source i at the receiving end N ;

[0011] S4: Integrate the wireless propagation channel matrix, antenna equivalent circuit, impedance matching network, and noise source cascade in steps S1 to S3 to obtain the transmitter source voltage v G and the receiving end load voltage v L The conversion relationship between them is used to generate the radio channel matrix D in the physical sense and the radio channel matrix H in the information theory sense, and then the radio channel statistical characteristics and radio channel capacity are obtained by analysis.

[0012] Furthermore, the aforementioned transmitting end antenna The angle calculation is as follows:

[0013] S1-A.1. Define the elevation angles and azimuth angles of the columns and rows of the plane where the transmitting antenna array is located as and

[0014] At the initial time t0, the origin of the local coordinate system of the transmitter is located at O ​​in the global coordinate system. T =[0,0,0], the initial distance between the transmitter and receiver is D, and the time t is arrive The distance is D qp (t),

[0015] S1-A.2. Definition: Global Coordinate System GCS (x, y, z), Transmitter Local Coordinate System LCS OT (x′ OT ,y′ OT ,z′ OT ), Local Coordinate System LCS p (x′ p ,y′ p ,z′ p );

[0016] In the LCS OT In the OT The axis is the normal direction of the plane where the transmitter array is located, y′ OT oz′ OT Coincident with the plane where the transmitting end array is located;

[0017] In the LCS p(q) In the p The axis is Normal direction of the plane, y′ p oz′ p and The planes where the array elements are located coincide with each other;

[0018] In the LCSOT middle, The coordinates are expressed as (0,y′ p,A ,z′ p,A ).

[0019] Furthermore, the aforementioned transmitting end antenna The angle calculation is as follows:

[0020] S1-B.1. Definition: The elevation and azimuth angles of the columns and rows of the plane where the receiving antenna array is located are and At the initial time t0, the origin of the local coordinate system of the receiving end is located at O ​​in the global coordinate system. R =[D,0,0], the initial distance between the transmitter and receiver is D, and the time t is arrive The distance is D qp (t),

[0021] S1-B.2. Definition: Global Coordinate System GCS (x, y, z), Receiver Local Coordinate System LCS OR (x′ OR ,y′ OR ,z′ OR ), Local Coordinate System LCS q (x′ q ,y q ′,z′ q ), in LCS OR In the OR is the normal direction of the plane where the receiving array is located,

[0022] y′ OR oz′ OR coincides with the plane where the receiving end array is located,

[0023] In the LCS q In the q The axis is Normal direction of the plane, y q 'oz' q and The planes where the array elements are located coincide with each other;

[0024] In the LCS OR middle, The coordinates are expressed as (0,y′ q,A ,z′ q,A ).

[0025] Furthermore, in the aforementioned step S1, the impulse response of the wireless propagation channel between the transmitting antenna and the receiving antenna is specifically: The qth receiving antenna The impulse response of the wireless propagation channel h qp (t,τ) represents the sight distance component Non-line-of-sight component The superposition is calculated as follows:

[0026]

[0027]

[0028]

[0029] Where e is the base of natural logarithm, π is the ratio of the circumference of a circle, K R is the Rice factor, [] T represents the transpose, δ(·) is the Dirac impulse function, f c is the carrier frequency, λ is the wavelength corresponding to the carrier frequency,

[0030] F p(q),H and F p(q),V Array elements The horizontal polarization pattern and vertical polarization pattern are obtained through full-wave electromagnetic simulation of the antenna. The scatterer cluster number n traverses n=1,2,...,N qp (t), scatterer number m traverses m=1,2,...,M n , μ is the co-polarization imbalance factor, is the cross-polarization power ratio, is time t and The line-of-sight propagation delay between and At time t and The time delay and power of the mth scatterer in the nth cluster between them;

[0031] and Represented in LCS q From arrive The line-of-sight pitch arrival angle and azimuth arrival angle, and Represented in LCS p From arrive The line of sight pitch departure angle and azimuth departure angle, and Represented in LCS q From arrive The pitch arrival angle and azimuth arrival angle, and Represented in LCS p From arrive Pitch departure angle and azimuth departure angle;

[0032] At time t, there is N between the transmitter and the receiver. qp (t) For twin scatterer clusters, in the nth pair of twin scatterer clusters, the scatterer cluster close to the emission end is The scatterer cluster close to the receiver is The number of scatterers contained in scatterer cluster n is M n , The mth scatterer in The mth scatterer in

[0033] Furthermore, the aforementioned general radio channel modeling method based on full-wave electromagnetic simulation, at time t and The time delay of the mth scatterer in the nth cluster The calculation is as follows:

[0034]

[0035] in represents the propagation delay of the virtual link, c represents the speed of light, and Representing from arrive and from arrive , ‖·‖ represents the vector modulus.

[0036] Furthermore, the aforementioned general radio channel modeling method based on full-wave electromagnetic simulation, starting from the transmitting antenna To the scatterer cluster is The mth scatterer in Vector The calculation is as follows:

[0037]

[0038]

[0039]

[0040] in They are With O T The relative distance, elevation and azimuth between According to the array element Calculate each specific position in the planar array topology and define and Where arg{·} represents the angle of deflection of the vector relative to the x-axis;

[0041] The transmitter, receiver and scatterer cluster all move in a uniform linear motion in the horizontal plane xoy. Further calculation is as follows:

[0042]

[0043] in It is from O T arrive The vector and the T arrive The angle between the vectors, the cosine value is:

[0044]

[0045] The direction of movement of the transmitter is the same as that of the arrive The angle between the vectors, the cosine value is:

[0046]

[0047] Furthermore, the aforementioned general radio channel modeling method based on full-wave electromagnetic simulation, at time t and The unnormalized power corresponding to the mth scatterer of the nth cluster between is:

[0048]

[0049] where r τ is the delay distribution scaling factor, DS is the root mean square delay spread, and Z n represents the degree of energy attenuation at each scatterer cluster; ξ n (y′ p,A ,z′ p,A ,y′ q,A ,z′ q,A ) is the same as and The 4-dimensional spatial log-normal process related to the position in each local coordinate system is used to simulate the smooth variation of the power of the clusters in the transmitting array and the receiving array at each array element. Finally, Perform normalization to obtain

[0050] make and The distance vector between

[0051]

[0052] The transmitter and receiver both move in a uniform linear motion in the horizontal plane xoy, D qp (t) is expanded as follows:

[0053]

[0054] Furthermore, the aforementioned general radio channel modeling method based on full-wave electromagnetic simulation is based on h qp The time delay τ in (t,τ) is Fourier transformed to obtain the channel transfer function of the wireless propagation channel,

[0055]

[0056] Considering large-scale fading, define:

[0057]

[0058] Furthermore, in the aforementioned step S2, for the transmitting end antenna Wireless propagation channel and receiving antenna The two-port circuit network Port qp , definition: R r,T,p is the radiation resistance of the transmitter, R r,R,q is the radiation resistance at the receiving end, X r,T,p is the emitter reactance, X r,R,q is the reactance of the receiving end;

[0059] γ T,p R r,T,p is the thermal loss resistance of the transmitting antenna, γ R,q R r,R,q is the heat loss resistance of the receiving antenna, and the two-port circuit network Port qp The impedance matrix Z qp for:

[0060]

[0061] The impedance matrix of the circuit network representing the antenna and the wireless propagation channel is as follows

[0062]

[0063] Among them, Z AT is the transmitting antenna impedance matrix, Z AR is the receiving antenna impedance matrix, Z ATR is the transimpedance matrix between the receiving antenna and the transmitting antenna, Z ARTis the transimpedance matrix between the transmitting antenna and the receiving antenna, Z A The elements in each block matrix satisfy (Z ART ) q,p =(Z qp ) 2,1 、(Z ATR ) p,q =(Z qp ) 1,2 、(Z AT ) p,p =(Z qp ) 1,1 、(Z AR ) q,q =(Z qp ) 2,2 , where (X) M,N Represents the element in the Mth row and Nth column of the matrix X; Among them O M×N The all-zero matrix representing M×N dimensions, the radiation resistance, reactance, heat loss resistance and antenna impedance matrix of the transmitting end and the receiving end are obtained through full-wave electromagnetic simulation of the antenna.

[0064] Furthermore, in the aforementioned step S3, the transmit end impedance matching network matrix is:

[0065]

[0066] The receiving end impedance matching network matrix is:

[0067]

[0068] Re{·} represents the real part of the element in the curly brackets, Im{·} represents the imaginary part of the element in the curly brackets, and {·} 1 / 2 Represents the square root operation of the matrix, I M×M Represents the M×M dimensional identity matrix, define R G =Re{z G}, R L =Re{z L},

[0069] Among them, Z opt is the impedance parameter related to the impedance matching network at the receiving end, let Represents a complex Gaussian distribution with mean μ and covariance matrix R. The distribution of noise in internal and external noise sources satisfies: External noise voltage source Where the external noise covariance matrix R N =4k B T A f B Re{Z AR}, k Bis the Boltzmann constant, T A is the antenna noise temperature, f B is the noise bandwidth;

[0070] Internal noise voltage source The internal noise voltage standard deviation σ u >0; internal noise current source The internal noise current standard deviation σ i >0, internal noise voltage source v N and the internal noise current source i N Both with external noise voltage source Not relevant;

[0071] Internal noise v N and i N The correlation coefficient of the corresponding elements satisfies in Represents the mathematical expectation of the elements in the brackets, {·} * Represents finding the conjugate of the elements in the brackets.

[0072] Furthermore, in the aforementioned step S4, the transmitting end source voltage v G and the receiving end load voltage v L The conversion relationship between them is:

[0073]

[0074] Among them, the matrix D is M R ×M T The physical radio channel matrix of M R ×1-dimensional noise vector, the calculation formula of D is as follows:

[0075]

[0076] where Z T M T ×M T dimensional matrix, Z RT M R ×M T dimensional matrix, Z R M R ×M R The matrix of dimension is determined by the following formula:

[0077] Z T =Z MT11 -Z MT12 (Z AT +Z MT22 ) -1 Z MT21

[0078] ZRT =Z MR12 (Z AR +Z MR22 ) -1 Z ART (Z AT +Z MT22 ) -1 Z MT21

[0079] Z R =Z MR11 -Z MR12 (Z MR22 +Z AR ) -1 Z MR21

[0080] The power coupling matrix is ​​defined as:

[0081]

[0082] in{·} -H It means to first find the inverse of the matrix and then find the conjugate transpose. Define the intermediate parameter matrix F R =Z MR12 (Z AR +Z MR22 ) -1 and the intermediate parameter matrix The noise vector η is

[0083]

[0084] The noise covariance matrix is:

[0085]

[0086] The radio channel matrix in the information theory sense is

[0087]

[0088] in{·} -1 / 2 represents the operation of first taking the square root of the matrix and then finding its inverse, {·} -H / 2 Represents the operation of first taking the square root of the matrix, then finding the inverse, and finally finding the conjugate transpose. The variance of the additive noise satisfy where tr{·} represents the trace operation of the matrix.

[0089] Furthermore, in the aforementioned step S4, according to the radio channel matrix D in the physical sense, the space-time-frequency correlation function of the radio channel Calculated by the following formula:

[0090]

[0091] Among them, Δr is the spatial interval, Δt is the time interval, Δf is the frequency interval, D qp (t,f) is the value of the element in the qth row and pth column of matrix D at the frequency f at time t, The matrix D is Rank The value of the elements of the column at the frequency f-Δf at time t-Δt;

[0092] According to the radio channel matrix H in the sense of information theory, the radio channel capacity C is calculated as follows when the transmitter has unknown channel state information:

[0093]

[0094] Among them, P Tx is the transmit power, det(·) represents the matrix determinant operation.

[0095] Compared with the prior art, the beneficial technical effects of the present invention using the above technical solution are as follows:

[0096] The radio channel modeling method proposed in the present invention comprehensively considers key components of the radio channel, such as the excitation source and load, wireless propagation channel, antenna equivalent circuit, transceiver matching network, internal and external noise sources, and provides a technical path for joint modeling of antenna and wireless propagation channel. It can provide model support for wireless communication systems enabled by key air interface technologies such as smart metasurfaces, ultra-large-scale MIMO, and aperture-limited MIMO. Based on the wireless propagation channel parameters and the antenna parameters obtained by full-wave electromagnetic simulation, the radio channel modeling method proposed in the present invention can support a variety of wireless propagation environments and antenna types. BRIEF DESCRIPTION OF THE DRAWINGS

[0097] Figure 1 This is a flow chart of the radio channel modeling method of the present invention.

[0098] Figure 2 Schematic diagram of the wireless propagation channel model of the present invention.

[0099] Figure 3 Schematic diagram of the positional relationship between the transmitting antenna array of the present invention and the mth scatterer in the nth scatterer cluster.

[0100] Figure 4 This is a simulation comparison diagram of the time autocorrelation function of the radio channel modeling method of the present invention and the existing wireless propagation channel modeling method as the position of the investigated array element changes in an embodiment of the present invention.

[0101] Figure 5This is a simulation comparison diagram of the channel capacity variation with the number of antenna array elements of the radio channel modeling method of the present invention and the existing wireless propagation channel modeling method under the consideration of the antenna impedance matrix under the influence of coupling in an embodiment of the present invention. DETAILED DESCRIPTION

[0102] In order to better understand the technical content of the present invention, specific embodiments are given below in conjunction with the accompanying drawings.

[0103] Various aspects of the present invention are described herein with reference to the accompanying drawings, which show a number of illustrative embodiments. The embodiments of the present invention are not limited to those described in the accompanying drawings. It should be understood that the present invention can be implemented by any of the various concepts and embodiments described above, as well as the concepts and implementations described in detail below, because the concepts and embodiments disclosed herein are not limited to any particular implementation. In addition, some aspects disclosed herein may be used alone or in any appropriate combination with other aspects disclosed herein.

[0104] The radio channel modeling method of the present invention comprehensively considers key radio channel components, including the transceiver antennas, wireless propagation channels, transceiver impedance matching networks, and internal and external noise sources. Transceiver antenna parameters are derived through full-wave electromagnetic simulation of the antennas. After obtaining the responses of each radio channel component, the overall radio channel response is calculated based on cascaded multi-port circuit network theory, and the radio channel statistical characteristics and capacity are analyzed.

[0105] refer to Figure 1 The present invention provides a general radio channel modeling method based on full-wave electromagnetic simulation, comprising the following steps:

[0106] S1. Generate a wireless propagation channel matrix based on the impulse response of the wireless propagation channel between the transmitting antenna and the receiving antenna, as well as the various losses of wireless propagation. Where PL is the path loss, SH is the shadow fading, BL is the blocking effect loss, and OL is the atmospheric absorption loss. represents small-scale fading, where M T is the number of transmitting antennas, M R is the number of antennas at the receiving end, h qp (t,τ) is the pth transmitting antenna at time t and delay τ With the qth receiving antenna The impulse response of the wireless propagation channel between (p=1,2,...,M T q=1,2,...,M R );

[0107] S2. Acquire antenna data based on full-wave electromagnetic simulation and generate an impedance matrix representing the circuit network between the antenna and the wireless propagation channel;

[0108] S3. Determine the transmitter impedance matching network matrix Z MT , receiving end impedance matching network matrix Z MR , emitter source voltage v G , set the source impedance to z G , the load impedance is z L , based on the statistical characteristics of the internal and external noise sources at the receiving end, generate the external noise voltage source at the receiving end Internal noise voltage source v at the receiving end N , the internal noise current source i at the receiving end N ;

[0109] S4: Integrate the wireless propagation channel matrix, antenna equivalent circuit, impedance matching network, and noise source cascade in steps S1 to S3 to obtain the transmitter source voltage v G and the receiving end load voltage v L The conversion relationship between them is used to generate the radio channel matrix D in the physical sense and the radio channel matrix H in the information theory sense, and then the radio channel statistical characteristics and radio channel capacity are obtained by analysis.

[0110] See also Figure 2 , the elevation angle and azimuth angle of the column and row of the plane where the transmitting antenna array is located are defined as and The elevation angles and azimuth angles of the columns and rows of the plane where the receiving antenna array is located are and At the initial time t0, the origin of the local coordinate system of the transmitter is located at O ​​in the global coordinate system. T = [0,0,0], the origin of the local coordinate system of the receiving end is located at O ​​in the global coordinate system R =[D,0,0], the initial distance between the transmitter and receiver is D, and the time t is arrive The distance is D qp (t).

[0111] Definition: Global coordinate system GCS (x, y, z), transmitter local coordinate system LCS OT (x′ OT ,y′ OT ,z′ OT ), Local Coordinate System LCS p (x′ p ,y′ p ,z′ p ), receiving end local coordinate system LCS OR (x′ OR ,y′ OR ,z′ OR), Local Coordinate System LCS q (x′ q ,y q ′,z′ q ).

[0112] In the LCS OT In the OT The axis is the normal direction of the plane where the transmitter array is located, y′ OT oz′ OT coincides with the plane where the transmitting end array is located; in LCS p(q) In the p The axis is Normal direction of the plane, y′ p oz′ p and The planes where the array elements are located coincide with each other; in LCS OT middle, The coordinates are expressed as (0,y′ p,A ,z′ p,A );

[0113] In the LCS OR In the OR is the normal direction of the plane where the receiving array is located, y′ OR oz′ OR Coincident with the plane where the receiving array is located, in LCS q In the q The axis is Normal direction of the plane, y q 'oz' q and The planes where the array elements are located coincide with each other; in LCS OR middle, The coordinates are expressed as (0,y′ q,A ,z′ q,A );

[0114] At time t, there is N between the transmitter and the receiver. qp (t) For twin scatterer clusters, in the nth pair of twin scatterer clusters, the scatterer cluster close to the transmitting end is recorded as The cluster of scatterers close to the receiver is denoted as The number of scatterers contained in scatterer cluster n is denoted as M n , The mth scatterer in Initial time t0, through From O T(R) arrive The distance is At time t, the motion vectors of the transmitter, receiver, and scatterer cluster are expressed as and express. and Represent the initial time from to O R The pitch arrival angle and azimuth arrival angle, and Represent the initial time from O T arrive The pitch departure angle and azimuth departure angle, and Represent the initial time from O T arrive The distance from to O R distance, and Respectively represent the time t from arrive The distance from arrive distance.

[0115] In step S1, the impulse response of the wireless propagation channel between the transmitting antenna and the receiving antenna is: The qth receiving antenna The impulse response of the wireless propagation channel h qp (t,τ) represents the sight distance component Non-line-of-sight component The superposition is calculated as follows:

[0116]

[0117]

[0118]

[0119] Where e is the base of natural logarithm, π is the ratio of the circumference of a circle, K R is the Rice factor, [] T represents the transpose, δ(·) is the Dirac impulse function, f c is the carrier frequency, λ is the wavelength corresponding to the carrier frequency,

[0120] F p(q),H and F p(q),V Array elements The horizontal polarization pattern and vertical polarization pattern are obtained through full-wave electromagnetic simulation of the antenna. The scatterer cluster number n traverses n=1,2,...,N qp (t), scatterer number m traverses m=1,2,...,M n, μ is the co-polarization imbalance factor, is the cross-polarization power ratio, is time t and The line-of-sight propagation delay between and At time t and The time delay and power of the mth scatterer in the nth cluster between them; is a random phase and obeys a uniform distribution in the range (-π,π]. and Represented in LCS q From arrive The line-of-sight pitch arrival angle and azimuth arrival angle, and Represented in LCS p From arrive The line of sight pitch departure angle and azimuth departure angle, and Represented in LCS q From arrive The pitch arrival angle and azimuth arrival angle, and Represented in LCS p From arrive Pitch departure angle and azimuth departure angle;

[0121] At time t, there is N between the transmitter and the receiver. qp (t) For twin scatterer clusters, in the nth pair of twin scatterer clusters, the scatterer cluster close to the emission end is The scatterer cluster close to the receiver is The number of scatterers contained in scatterer cluster n is M n , The mth scatterer in The mth scatterer in

[0122] Among them, the delay It can be further written as in represents the propagation delay of the virtual link, c represents the speed of light, and Representing from arrive and from arrive , ‖·‖ represents the vector modulus.

[0123] The calculation process is as follows, see Figure 3 , which is further expanded into:

[0124]

[0125]

[0126]

[0127] in They are With O T The relative distance, elevation and azimuth between According to the array element Calculate each specific position in the planar array topology. Definition and Where arg{·} represents the angle of deflection of the vector relative to the x-axis. The transmitter, receiver, and scatterer cluster all move in a uniform linear motion in the horizontal plane xoy. Further estimated to be

[0128]

[0129] in It is from O T arrive The vector and the T arrive The angle between the vectors, the cosine of which is

[0130]

[0131] The direction of movement of the transmitter is the same as that of the arrive The angle between the vectors, the cosine value is:

[0132]

[0133] Time t and The unnormalized power corresponding to the mth scatterer of the nth cluster between

[0134]

[0135] where r τ is the delay distribution scaling factor, DS is the root mean square delay spread, and Z n Represents the degree of energy attenuation at each scatterer cluster. ξ n (y′ p,A ,z′p,A ,y′ q,A ,z′ q,A ) is the same as and The 4-dimensional spatial log-normal process related to the position in each local coordinate system is used to simulate the smooth variation of the power of the clusters in the transmitting array and the receiving array at each array element. Perform normalization to get

[0136] make and The distance vector between is:

[0137]

[0138] The transmitter and receiver both move in a uniform linear motion in the horizontal plane xoy, D qp (t) is expanded as follows:

[0139]

[0140] Based on h qp The channel transfer function of the wireless propagation channel obtained by Fourier transform of the time delay τ in (t,τ) is:

[0141]

[0142] Considering large-scale fading, define:

[0143]

[0144] In step S2, for the transmitting antenna Wireless propagation channel and receiving antenna The two-port circuit network Port qp , definition: R r,T,p is the radiation resistance of the transmitter, R r,R,q is the radiation resistance at the receiving end, X r,T,p is the emitter reactance, X r,R,q is the reactance of the receiving end;

[0145] γ T,p R r,T,p is the thermal loss resistance of the transmitting antenna, γ R,q R r,R,q is the heat loss resistance of the receiving antenna, and the two-port circuit network Port qp The impedance matrix Z qp for:

[0146]

[0147] The impedance matrix of the circuit network representing the antenna and the wireless propagation channel

[0148]

[0149] Among them, Z AT is the transmitting antenna impedance matrix, Z AR is the receiving antenna impedance matrix, Z ATR is the transimpedance matrix between the receiving antenna and the transmitting antenna, Z ART is the transimpedance matrix between the transmitting antenna and the receiving antenna. A The elements in each block matrix satisfy (Z ART ) q,p =(Z qp ) 2,1 、(Z ATR ) p,q =(Z qp ) 1,2 、(Z AT ) p,p =(Z qp ) 1,1 、(Z AR ) q,q =(Z qp ) 2,2 , where (X) M,N represents the element in the Mth row and Nth column of the matrix X. Under the one-sided assumption, we have Among them O M×N Represents an M×N-dimensional all-zero matrix. The radiation resistance, reactance, heat loss resistance, and antenna impedance matrix of the transmitter and receiver are obtained through full-wave electromagnetic simulation of the antenna.

[0150] In step S3, let Re{·} represent the real part of the element in the curly brackets, Im{·} represent the imaginary part of the element in the curly brackets, and {·} 1 / 2 Represents the square root operation of the matrix, I M×M Represents the M×M dimensional identity matrix, define R G =Re{z G}, R L =Re{z L}, then the transmitter impedance matching network matrix is:

[0151]

[0152] The receiving end impedance matching network matrix is

[0153]

[0154] where Z opt Is the impedance parameter related to the impedance matching network at the receiving end. Represents a complex Gaussian distribution with mean μ and covariance matrix R. The distribution of noise in internal and external noise sources satisfies: External noise voltage source Where the external noise covariance matrix R N =4k B T A f B Re{Z AR}, k B is the Boltzmann constant, T A is the antenna noise temperature, f B is the noise bandwidth;

[0155] Internal noise voltage source The internal noise voltage standard deviation σ u >0; internal noise current source The internal noise current standard deviation σ i >0. Internal noise voltage source v N and the internal noise current source i N Both with external noise voltage source Not relevant.

[0156] Internal noise v N and i N The correlation coefficient of the corresponding elements satisfies in Represents the mathematical expectation of the elements in the brackets, {·} * Represents finding the conjugate of the elements in the brackets.

[0157] In step S4, the transmitter source voltage v G and the receiving end load voltage v L The conversion relationship between them is:

[0158]

[0159] Among them, the matrix D is M R ×M T The physical radio channel matrix of M R ×1-dimensional noise vector, the calculation formula of D is as follows:

[0160]

[0161] where Z T M T ×M T dimensional matrix, Z RT M R ×M T dimensional matrix, Z R M R ×M R The matrix of dimension can be determined by the following formula:

[0162] Z T =Z MT11 -Z MT12 (Z AT +Z MT22 ) -1 Z MT21

[0163] Z RT =Z MR12 (Z AR +Z MR22 ) -1 Z ART (Z AT +Z MT22 ) -1 Z MT21

[0164] Z R =Z MR11 -Z MR12 (Z MR22 +Z AR ) -1 Z MR21

[0165] The power coupling matrix is ​​defined as

[0166]

[0167] in{·} -H It means to first find the inverse of the matrix and then find the conjugate transpose. Define the intermediate parameter matrix F R =Z MR12 (Z AR +Z MR22 ) -1 and the intermediate parameter matrix Then the noise vector η is:

[0168]

[0169] The noise covariance matrix is

[0170]

[0171] The radio channel matrix in the information theory sense is:

[0172]

[0173] in{·} -1 / 2 represents the operation of first taking the square root of the matrix and then finding its inverse, {·} -H / 2 It represents the operation of first taking the square root of the matrix, then taking the inverse, and finally taking the conjugate transpose. satisfy where tr{·} represents the trace operation of the matrix.

[0174] Furthermore, in step S4, according to the radio channel matrix D in the physical sense, the space-time-frequency correlation function of the radio channel Calculated by the following formula:

[0175]

[0176] Among them, Δr is the spatial interval, Δt is the time interval, Δf is the frequency interval, D qp (t,f) is the value of the element in the qth row and pth column of matrix D at the frequency f at time t, The matrix D is Rank The value of the elements of the column at the frequency f-Δf at time t-Δt.

[0177] Furthermore, in step S4, based on the radio channel matrix H in the sense of information theory, the radio channel capacity C is calculated by the following formula when the transmitting end has unknown channel state information:

[0178]

[0179] Among them, P Tx is the transmit power, det(·) represents the matrix determinant operation.

[0180] Figure 4 This is a simulation comparison of the temporal autocorrelation function of the radio channel modeling method of the present invention and the existing wireless propagation channel modeling method as the position of the investigated array element changes. The transmitting end and the receiving end are respectively equipped with a uniform linear array composed of a patch antenna and a dipole antenna, and f c =3.5GHz (corresponding wavelength is λ c ), M T =9,M R =5, D = 50m. The aperture of the transmitting antenna array is fixed at 2λ c , the receiving antenna array element spacing δ R =λ c / 2, the inclination angles of the transmitter (receiver) array in the row and column directions are: The transmitter is fixed and the receiver is The pitch angle, The azimuth and v R =1m / s uniform linear motion, the antenna temperature is T A =300K, resistor R L and R G= 50Ω, q = 1. It can be seen that, unlike the time autocorrelation function obtained by the wireless propagation channel modeling method, the time autocorrelation function obtained by the radio channel modeling method of the present invention is more sensitive to the position of the array element.

[0181] Figure 5 This is a simulation comparison of the channel capacity of the radio channel modeling method of the present invention with and without considering the antenna impedance matrix under the influence of coupling and the existing wireless propagation channel modeling method as the number of antenna array elements changes. The transmitting end and the receiving end are respectively equipped with a uniform linear array composed of a patch antenna and a dipole antenna, f c =3.5GHz (corresponding wavelength is λ c ), M T =9,M R =5, D = 50m. The antenna array aperture at the transmitting end is fixed at 2λ c , the receiving antenna array element spacing δ R =λ c / 2, the tilt angles of the array rows and columns at the transmitter (receiver) are: The transmitter is fixed and the receiver is The pitch angle, The azimuth and v R =1m / s uniform linear motion, the antenna temperature is T A =300K, resistor R L and R G 50Ω. It can be seen that the noise matching strategy can achieve higher radio channel capacity than the imaginary impedance matching strategy. Furthermore, regardless of the number of transmitting antenna elements, after imaginary impedance matching, the channel capacity calculated using the radio channel modeling method proposed in this invention is lower than the channel capacity calculated using the wireless propagation channel modeling method. This embodiment demonstrates that the choice of different impedance matching techniques also has a significant impact on radio channel capacity.

[0182] In summary, the present invention provides a universal radio channel modeling method based on full-wave electromagnetic simulation. Compared with existing wireless propagation channel modeling methods, the method comprehensively considers key components of the radio channel, such as the excitation source and load, the wireless propagation channel, the antenna equivalent circuit, the transceiver matching network, and internal and external noise sources, thereby achieving joint modeling of the antenna and the wireless propagation channel. This method can provide model support for wireless communication systems enabled by key air interface technologies such as smart metasurfaces, ultra-large-scale MIMO, and aperture-limited MIMO. The wireless channel modeling method proposed in the present invention can use wireless propagation channel parameters and antenna parameters obtained from full-wave electromagnetic simulation, which is closer to reality, as model inputs, and supports different wireless propagation environments and different antenna types.

[0183] While the present invention has been described above with reference to preferred embodiments, this is not intended to limit the present invention. Persons skilled in the art will readily appreciate that various modifications and variations can be made without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A general radio channel modeling method based on full-wave electromagnetic simulation, characterized in that: The following steps are involved: S1. Generate a wireless propagation channel matrix based on the impulse response of the wireless propagation channel between the transmitting antenna and the receiving antenna, as well as the various losses of wireless propagation S2. Acquire antenna data based on full-wave electromagnetic simulation and generate an impedance matrix representing the circuit network between the antenna and the wireless propagation channel; S3. Determine the transmitter impedance matching network matrix Z MT , receiving end impedance matching network matrix Z MR , emitter source voltage v G , set the source impedance to z G , the load impedance is z L , based on the statistical characteristics of the internal and external noise sources at the receiving end, generate the external noise voltage source at the receiving end The internal noise voltage source v at the receiving end N , the internal noise current source i N ; S4: Integrate the wireless propagation channel matrix, antenna equivalent circuit, impedance matching network, and noise source cascade in steps S1 to S3 to obtain the transmitter source voltage v G and the receiving end load voltage v L The conversion relationship between them is used to generate the radio channel matrix D in the physical sense and the radio channel matrix H in the information theory sense, and then the radio channel statistical characteristics and radio channel capacity are obtained by analysis.

2. A general radio channel modeling method based on full-wave electromagnetic simulation according to claim 1, characterized in that: Transmitter antenna The angle calculation is as follows: S1-A.

1. Define the elevation angles and azimuth angles of the columns and rows of the plane where the transmitting antenna array is located as and At the initial time t0, the origin of the local coordinate system of the transmitter is located at O ​​in the global coordinate system. T =[0,0,0], the initial distance between the transmitter and receiver is D, and the time t is arrive The distance is D qp (t), S1-A.

2. Definition: Global Coordinate System GCS (x, y, z), Transmitter Local Coordinate System LCS OT (x′ OT ,y′ OT ,z′ OT ), Local Coordinate System LCS p (x′ p ,y p ′,z′ p ); In the LCS OT In the OT The axis is the normal direction of the plane where the transmitter array is located, y′ OT oz′ OT Coincident with the plane where the transmitting end array is located; In the LCS p(q) In the p The axis is Normal direction of the plane, y′ p oz′ p and The planes where the array elements are located coincide with each other; In the LCS OT middle, The coordinates are expressed as (0,y′ p,A ,z′ p,A ).

3. A general radio channel modeling method based on full-wave electromagnetic simulation according to claim 1, characterized in that: Transmitter antenna The angle calculation is as follows: S1-B.

1. Definition: The elevation and azimuth angles of the columns and rows of the plane where the receiving antenna array is located are and At the initial time t0, the origin of the local coordinate system of the receiving end is located at O ​​in the global coordinate system. R =[D,0,0], the initial distance between the transmitter and receiver is D, and the time t is arrive The distance is D qp (t), S1-B.

2. Definition: Global Coordinate System GCS (x, y, z), Receiver Local Coordinate System LCS OR (x′ OR ,y′ OR ,z′ OR ), Local Coordinate System LCS q (x′ q ,y′ q ,z′ q ), In the LCS OR In the OR is the normal direction of the plane where the receiving array is located, y′ OR oz′ OR coincides with the plane where the receiving end array is located, In the LCS q In the q The axis is Normal direction of the plane, y′ q oz′ q and The planes where the array elements are located coincide with each other; In the LCS OR middle, The coordinates are expressed as (0,y′ q,A ,z′ q,A ).

4. A general radio channel modeling method based on full-wave electromagnetic simulation according to claim 1, characterized in that: In step S1, the impulse response of the wireless propagation channel between the transmitting antenna and the receiving antenna is: The qth receiving antenna The impulse response of the wireless propagation channel h qp (t,τ) represents the sight distance component Non-line-of-sight component The superposition is calculated as follows: Where e is the base of natural logarithm, π is the ratio of the circumference of a circle, K R is the Rice factor, [] T represents the transpose, δ(·) is the Dirac impulse function, f c is the carrier frequency, λ is the wavelength corresponding to the carrier frequency, F p(q),H and F p(q),V Array elements The horizontal polarization pattern and vertical polarization pattern are obtained through full-wave electromagnetic simulation of the antenna. The scatterer cluster number n traverses n=1,2,...,N qp (t), scatterer number m traverses m=1,2,...,M n , μ is the co-polarization imbalance factor, is the cross-polarization power ratio, is time t and The line-of-sight propagation delay between and At time t and The time delay and power of the mth scatterer in the nth cluster between them; and Represented in LCS q From arrive The line-of-sight pitch arrival angle and azimuth arrival angle, and Represented in LCS p From arrive The line of sight pitch departure angle and azimuth departure angle, and Represented in LCS q From arrive The pitch arrival angle and azimuth arrival angle, and Represented in LCS p From arrive Pitch departure angle and azimuth departure angle; At time t, there is N qp (t) For twin scatterer clusters, in the nth pair of twin scatterer clusters, the scatterer cluster close to the emission end is The scatterer cluster close to the receiver is The number of scatterers contained in scatterer cluster n is M n , The mth scatterer is denoted as The mth scatterer in 5. A general radio channel modeling method based on full-wave electromagnetic simulation according to claim 4, characterized in that: Time t and The time delay of the mth scatterer in the nth cluster The calculation is as follows: in represents the propagation delay of the virtual link, c represents the speed of light, and Representing from arrive and from arrive , ‖·‖ represents the vector modulus.

6. A general radio channel modeling method based on full-wave electromagnetic simulation according to claim 5, characterized in that: From the transmitting antenna To the scatterer cluster is The mth scatterer in Vector The calculation is as follows: in They are With O T The relative distance, elevation and azimuth between According to the array element Calculate each specific position in the planar array topology and define and Where arg{·} represents the angle of deflection of the vector relative to the x-axis; The transmitter, receiver and scatterer cluster all move in a uniform linear motion in the horizontal plane xoy. Further calculation is as follows: in It is from O T arrive The vector and the T arrive The angle between the vectors, the cosine value is: The direction of motion of the transmitter and the direction of arrive The angle between the vectors, the cosine value is:

7. A general radio channel modeling method based on full-wave electromagnetic simulation according to claim 4, characterized in that: Time t and The unnormalized power corresponding to the mth scatterer of the nth cluster between is: where r τ is the delay distribution scaling factor, DS is the root mean square delay spread, and Z n represents the degree of energy attenuation at each scatterer cluster; ξ n (y′ p,A ,z′ p,A ,y′ q,A ,z′ q,A ) is the same as and The 4-dimensional spatial log-normal process related to the position in each local coordinate system is used to simulate the smooth variation of the power of the clusters in the transmitting array and the receiving array at each array element. Finally, Perform normalization to obtain make and The distance vector between The transmitter and receiver both move in a uniform linear motion in the horizontal plane xoy, D qp (t) is expanded as follows:

8. The general radio channel modeling method based on full-wave electromagnetic simulation according to claim 3, characterized in that: Based on h qp The time delay τ in (t,τ) is Fourier transformed to obtain the channel transfer function of the wireless propagation channel, Considering large-scale fading, define:

9. The general radio channel modeling method based on full-wave electromagnetic simulation according to claim 1, characterized in that: In step S2, for the transmitting antenna Wireless propagation channel and receiving antenna The two-port circuit network Port qp , definition: R r,T,p is the radiation resistance of the transmitter, R r,R,q is the radiation resistance at the receiving end, X r,T,p is the emitter reactance, X r,R,q is the reactance of the receiving end; γ T,p R r,T,p is the thermal loss resistance of the transmitting antenna, γ R,q R r,R,q is the heat loss resistance of the receiving antenna, and the two-port circuit network Port qp The impedance matrix Z qp for: The impedance matrix of the circuit network representing the antenna and the wireless propagation channel is as follows Among them, Z AT is the transmitting antenna impedance matrix, Z AR is the receiving antenna impedance matrix, Z ATR is the transimpedance matrix between the receiving antenna and the transmitting antenna, Z ART is the transimpedance matrix between the transmitting antenna and the receiving antenna, Z A The elements in each block matrix satisfy (Z ART ) q,p =(Z qp ) 2,1 、(Z ATR ) p,q =(Z qp ) 1,2 、(Z AT ) p,p =(Z qp ) 1,1 、(Z AR ) q,q =(Z qp ) 2,2 , where (X) M,N Represents the element in the Mth row and Nth column of the matrix X; Among them O M×N The all-zero matrix representing M×N dimensions, the radiation resistance, reactance, heat loss resistance and antenna impedance matrix of the transmitting end and the receiving end are obtained through full-wave electromagnetic simulation of the antenna.

10. A universal radio channel modeling method based on full-wave electromagnetic simulation according to claim 1, characterized in that: In step S3, the transmit end impedance matching network matrix is: The receiving end impedance matching network matrix is: Re{·} represents the real part of the element in the curly brackets, Im{·} represents the imaginary part of the element in the curly brackets, and {·} 1 / 2 Represents the square root operation of the matrix, I M×M Represents the M×M dimensional identity matrix, define R G =Re{z G }, R L =Re{z L }, Among them, Z opt is the impedance parameter related to the impedance matching network at the receiving end, let Represents a complex Gaussian distribution with mean μ and covariance matrix R. The distribution of noise in internal and external noise sources satisfies: External noise voltage source Where the external noise covariance matrix R N =4k B T A f B Re{Z AR }, k B is the Boltzmann constant, T A is the antenna noise temperature, f B is the noise bandwidth; Internal noise voltage source The internal noise voltage standard deviation σ u >0; internal noise current source The internal noise current standard deviation σ i >0, internal noise voltage source v N and the internal noise current source i N Both with external noise voltage source Not relevant; Internal noise v N and i N The correlation coefficient of the corresponding elements satisfies in Represents the mathematical expectation of the elements in the brackets, {·} * Represents the conjugate of the elements in the brackets.

11. A universal radio channel modeling method based on full-wave electromagnetic simulation according to claim 1, characterized in that: In step S4, the source voltage v G and the receiving end load voltage v L The conversion relationship between them is: Among them, the matrix D is M R ×M T The physical radio channel matrix of M R ×1-dimensional noise vector, the calculation formula of D is as follows: where Z T M T ×M T dimensional matrix, Z RT M R ×M T dimensional matrix, Z R M R ×M R The matrix of dimension is determined by the following formula: WITH T =Z MT11 -WITH MT12 (WITH AT +Z MT22 ) -1 WITH MT21 WITH RT =Z MR12 (WITH AR +Z MR22 ) -1 WITH ART (WITH AT +Z MT22 ) -1 WITH MT21 WITH R =Z MR11 -WITH MR12 (WITH MR22 +Z AR ) -1 WITH MR21 The power coupling matrix is ​​defined as: in{·} -H It means to first find the inverse of the matrix and then find the conjugate transpose; Define the intermediate parameter matrix F R =Z MR12 (Z AR +Z MR22 ) -1 and the intermediate parameter matrix The noise vector η is The noise covariance matrix is: The radio channel matrix in the information theory sense is in{·} -1 / 2 represents the operation of first taking the square root of the matrix and then finding its inverse, {·} -H / 2 Represents the operation of first taking the square root of the matrix, then finding the inverse, and finally finding the conjugate transpose. The variance of the additive noise satisfy where tr{·} represents the trace operation of the matrix.

12. A universal radio channel modeling method based on full-wave electromagnetic simulation according to claim 1, characterized in that: In step S4, according to the radio channel matrix D in the physical sense, the space-time-frequency correlation function of the radio channel Calculated by the following formula: Among them, Δr is the spatial interval, Δt is the time interval, Δf is the frequency interval, D qp (t,f) is the value of the element in the qth row and pth column of matrix D at the frequency f at time t, The matrix D is Rank The value of the elements of the column at the frequency f-Δf at time t-Δt; According to the radio channel matrix H in the sense of information theory, the radio channel capacity C is calculated as follows when the transmitter has unknown channel state information: Among them, P Tx is the transmit power, det(·) represents the matrix determinant operation.

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