Irs-aided terahertz mimo wireless communication channel modeling method and device

Abstract

The application provides an IRS-aided terahertz MIMO wireless communication channel modeling method and device, including: acquiring a transmission power, first position information of each antenna unit of a transmission end, second position information of each antenna unit of a receiving end, and third position information of each reflecting unit of an IRS reflecting surface; calculating first distances between each antenna unit of the transmission end and each antenna unit of the receiving end, second distances between each antenna unit of the transmission end and each reflecting unit of the IRS reflecting surface, and third distances between each antenna unit of the receiving end and each reflecting unit of the IRS reflecting surface; determining first channel gains based on the first distances, determining second channel gains based on the second distances, and determining third channel gains based on the third distances; determining a phase shift matrix of a signal received by each antenna unit of the receiving end on a propagation path; and determining a received signal based on a transmitted signal, the transmission power, the channel gains, and the phase shift matrix. The method improves the scene coverage range of the wireless communication channel model.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, and in particular to an IRS-assisted terahertz MIMO wireless communication channel modeling method and device. BACKGROUND

[0002] Due to the rise of data-intensive applications such as VR / AR, holographic projection, and autonomous driving, and the higher requirements for traffic by large-scale industrial Internet of Things and Internet of Vehicles, global mobile communication traffic continues to grow exponentially, and the ITU (International Telecommunication Union) predicts that monthly traffic may reach 5ZB by 2030. 5G networks may not be able to bear such a huge amount of data, and there are deficiencies in cost and energy consumption and design complexity. Although many complex physical layer technologies have been used, such as adaptive modulation and coding, multi-carrier signals, large-scale MIMO systems, relays, beamforming, etc., the current wireless system has reached a saturated level. The next generation of wireless systems needs to enable software control and make a complete change at each layer to meet the needs of 6G networks, so the research and development of 6G technology has become a hot issue.

[0003] The traditional long-distance transmission compensation method is relay. Wireless relay technology uses its wireless relay function to transfer wireless signals from one relay point to the next relay point, achieving the effect of expanding the wireless coverage range. However, the relay needs to process the received signal before amplifying and retransmitting the signal, which will introduce antenna noise and self-interference. For example, when using traditional wireless relay technology, for amplify-and-forward (AF) relays, the noise in the inter-user channel will also be amplified and forwarded, and when the transmission link quality is poor, the amplified noise will directly affect the decision at the receiving end. For decode-and-forward (DF) relays, decoding and re-encoding are required when forwarding, which has high complexity, and in poor channel conditions, decoding may also be incorrect. For compressed forwarding (CF), it is only suitable for special networks such as double-hop one-way relays and diamond networks. In order to alleviate the above problems, an IRS-assisted wireless communication system appears in the prior art, that is, the base station controls the IRS to adjust the amplitude and phase of its structural units, thereby realizing the reflection of the base station's transmitted signal with control. The IRS expands the coverage of the wireless network and improves the spectrum utilization and energy efficiency by controlling the propagation environment. Compared with traditional relay communication, IRS can work in full-duplex mode, has higher spectrum efficiency, and the relay needs to be equipped with active antenna elements to generate new relay signals, and the energy gain brought by IRS is also much higher than that of the relay system. IRS does not require an RF link and does not need large-scale power supply, and has advantages in power consumption and deployment cost, and meets the requirements of future green communication.

[0004] And the current research on IRS is mainly focused on the field of traditional microwave and millimeter wave communication, and the research on the channel characteristics of IRS assisted communication is only based on the SISO (Single Input Single Output) model. In actual communication scenarios, the existing SISO wireless communication channel model assisted by IRS has the problem of small scene coverage range. Therefore, for the wireless communication channel model assisted by IRS, how to improve the scene coverage range of the wireless communication channel model is a technical problem to be solved. SUMMARY

[0005] Therefore, the present application provides an IRS-assisted terahertz MIMO wireless communication channel modeling method and device to solve one or more problems in the prior art.

[0006] According to one aspect of the present application, an IRS-assisted terahertz MIMO wireless communication channel modeling method is disclosed, the method comprising:

[0007] Obtaining the transmission power, the first position information of each antenna unit of the transmission end, the second position information of each antenna unit of the receiving end, and the third position information of each reflecting unit of the IRS reflecting surface, calculating the first distance between each antenna unit of the transmission end and each antenna unit of the receiving end, the second distance between each antenna unit of the transmission end and each reflecting unit of the IRS reflecting surface, and the third distance between each antenna unit of the receiving end and each reflecting unit of the IRS reflecting surface based on the first position information, the second position information and the third position information.

[0008] Determining the first channel gain between the transmission end and the receiving end based on the first distance, determining the second channel gain between the transmission end and the IRS reflecting surface based on the second distance, and determining the third channel gain between the receiving end and the IRS reflecting surface based on the third distance.

[0009] Determining the phase shift matrix of the signal received by each antenna unit of the receiving end on the propagation path.

[0010] Determining the received signal of each receiving unit of the receiving end based on the transmission signal of each antenna unit of the transmission end, the transmission power, the first channel gain, the second channel gain, the third channel gain and the phase shift matrix.

[0011] In some embodiments of the present application, the calculation formula of the received signal of each receiving unit of the receiving end is:

[0012]

[0013] Where y represents the received signal, s represents the transmission signal, βsd β represents the first channel gain. sr β represents the second channel gain. rd E represents the third channel gain. MN E represents an identity matrix of size M×N. RM E represents an identity matrix of size R×M. RN Let represent an identity matrix of size R×N, where n represents Gaussian additive white noise, Φ represents the phase shift matrix, and p is the transmit power.

[0014] In some embodiments of the present invention, determining the phase shift matrix of the signal received by each antenna element at the receiving end on the propagation path includes:

[0015] Obtain the wavelength;

[0016] The phase shift matrix is ​​determined based on the second distance, the third distance, and the wavelength.

[0017] In some embodiments of the present invention, determining the phase shift matrix of the signal received by each antenna element at the receiving end on the propagation path includes:

[0018] Obtain the wavelength;

[0019] Determine a first direction vector of the path between the transmitter and the IRS reflector, and determine a second direction vector of the path between the receiver and the IRS reflector;

[0020] Determine the first vector of each reflective element of the IRS reflector surface;

[0021] The phase shift matrix is ​​determined based on the wavelength, the first direction vector, the second direction vector, and the first vector.

[0022] In some embodiments of the present invention, the phase shift matrix Where j is a complex number, r = 1, 2…R, d mr d represents the second distance between the transmitting antenna element m and the IRS reflector element r. rn λ represents the third distance between the receiving antenna element n and the IRS reflector element r, m = 1, 2…M, n = 1, 2…N, R represents the number of IRS reflector elements, M represents the number of transmitting antenna elements, and N represents the number of receiving antenna elements.

[0023] In some embodiments of the present invention, the phase shift matrix Where j is a complex number, r = 1, 2…R, where R represents the number of reflective elements on the IRS reflector surface, τ r Let be the first vector. The second unit represents the vector. is a first unit representation vector, and λ is a wavelength.

[0024] In some embodiments of the present application, the method comprises:

[0025] The calculation formula of the first channel gain is:

[0026]

[0027] The calculation formula of the second channel gain is:

[0028]

[0029] The calculation formula of the third channel gain is:

[0030]

[0031] wherein G S is a transmitting end antenna gain, G D is a receiving end antenna gain, M is the number of antenna units of the transmitting end, N is the number of antenna units of the receiving end, R is the number of reflecting units of the IRS reflecting surface, d mn represents the distance between the antenna unit m of the transmitting end and the antenna unit n of the receiving end, d mr represents the distance between the antenna unit m of the transmitting end and the reflecting unit r of the IRS reflecting surface, d rn represents the distance between the antenna unit n of the receiving end and the reflecting unit r of the IRS reflecting surface, r = 1, 2…R, m = 1, 2…M, n = 1, 2…N.

[0032] In some embodiments of the present application, m = 1, 2, …M, n = 1, 2, …N;

[0033] wherein d SR is the distance between the center position of the transmitting end and the center position of the IRSW reflecting surface, d RD is the distance between the center position of the receiving end and the center position of the IRS reflecting surface, τ S is a second vector of the antenna unit of the transmitting end, τ D is a third vector of the antenna unit of the receiving end, τ r is a first vector of the reflecting unit of the IRS reflecting surface.

[0034] According to another aspect of the present application, there is also disclosed an IRS-aided terahertz MIMO wireless communication channel modeling system, comprising a processor and a memory, the memory having computer instructions stored therein, the processor being configured to execute the computer instructions stored in the memory, and the system implementing the steps of the method according to any one of the above embodiments when the computer instructions are executed by the processor.

[0035] According to still another aspect of the present application, there is also disclosed a computer readable storage medium having a computer program stored thereon, the program being configured to implement the steps of the method according to any one of the above embodiments when executed by a processor.

[0036] The IRS-aided terahertz MIMO wireless communication channel modeling method and device disclosed by the embodiments of the present application are based on the theory of IRS-aided intelligent metasurface, and a terahertz MIMO channel model under IRS assistance is constructed, the model has universality, and by adjusting the distance between the receiving end and the transmitting end, the offset angle, and the number of antenna elements of the IRS surface, different channel scenes can be flexibly simulated, so that the coverage range of the channel model is improved. In addition, the modeling method is suitable for 6G terahertz base station signal transmission environment, and due to the limitation of the coverage range of the base station, the signal strength at the edge of the base station can be expanded by the IRS.

[0037] Additional advantages, objects, and features of the application will be set forth in part by the description that follows, and will become apparent to those skilled in the art upon examination of the following detailed description and drawings, or can be learned by practice of the application. The objects and other advantages of the application can be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0038] It will be understood by those skilled in the art that the objects and advantages of the present application can be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings. BRIEF DESCRIPTION OF DRAWINGS

[0039] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the principles of the application. The components in the drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the application. For purposes of clarity and understanding, parts shown in the drawings have been suitably exaggerated, i.e., made larger in proportion than in an actual implementation of an exemplary device according to the present application. In the drawings:

[0040] Figure 1 Flowchart of the IRS-aided terahertz MIMO wireless communication channel modeling method according to an embodiment of the present application.

[0041] Figure 2A model schematic diagram of a terahertz MIMO wireless communication channel based on IRS assistance according to an embodiment of the present application.

[0042] Figure 3 A comparison diagram of coverage of a MIMO wireless communication channel with and without deployment of IRS according to an embodiment of the present application.

[0043] Figure 4 Variation of path loss of a transceiver and an IRS reflecting surface at different distances under a long distance according to an embodiment of the present application.

[0044] Figure 5 Variation of path loss of a transceiver and an IRS reflecting surface at different distances under a short distance according to an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the objects, technical solutions and advantages of embodiments of the present application clearer, further detailed description of the embodiments of the present application will be given below with reference to the accompanying drawings. Herein, the illustrative embodiments of the present application and the description thereof are used to explain the present application, but are not intended to limit the present application.

[0046] Here, it should be noted that, in order to avoid obscuring the present application due to unnecessary details, only structures and / or processing steps closely related to the scheme according to the present application are shown in the accompanying drawings, and other details not closely related to the present application are omitted.

[0047] It should be emphasized that the terms “comprise / comprises / comprising” used herein refer to the presence of a feature, element, step or component, but do not exclude the presence or addition of one or more other features, elements, steps or components.

[0048] 6G wireless communication technology mainly includes expanding the frequency band to terahertz and using super large antenna arrays to further promote spatial diversity and expand available spectrum resources; 5G networks are based on the basic assumption that the wireless transmission environment cannot be artificially controlled and can only be compensated by complex transmission and reception schemes. In this case, IRS-assisted wireless communication has changed the status quo by manipulating wireless signals during transmission, and IRS technology has attracted widespread attention because it can manipulate related characteristics such as phase and amplitude of electromagnetic waves during transmission, and is considered one of the key technologies of 6G.

[0049] The emergence of mMIMO technology has promoted the development of high-speed wireless communication systems, but has not changed the nature of wireless system performance depending on the channel. The purpose of technologies such as beamforming, diversity, and channel coding is to offset or take advantage of the impact of the channel without changing the behavior of the channel. The MIMO (Multiple Input Multiple Output) model has the following advantages: (1) Multi-beam capability, which can improve network capacity through multi-user spatial division multiplexing gain; (2) Large array beamforming, which can suppress inter-user interference through algorithms and significantly improve single-user SINR (Signal to Interference and Noise Ratio); (3) 3D beamforming, which can achieve coverage requirements in various scenarios; (4) Multi-channel uplink reception, which can maximize uplink reception gain.

[0050] According to different research fields and focuses, RIS can be divided into IRS (Intelligent reflecting surfaces), LIS (Large intelligent surfaces), DCS (Digitally controllable scatterers), SCS (Software controllable surfaces), etc. Among them, IRS is the most discussed and most achievable, which can significantly improve the transmission performance of wireless networks by changing the phase to realize beam control and focusing. Current application scenarios of IRS mainly include: (1) Edge intelligence: by applying IRS in edge caching, edge computing and learning, work efficiency can be effectively improved and the energy limitation problem of edge devices can be solved; (2) D2D communication: by introducing IRS, low-power transmission between devices can be supported, information transmission rate can be improved, and inter-device interference can be reduced; (3) UAV communication: IRS is deployed on the UAV body, further taking advantage of the convenience of UAV communication deployment, flexibility, and wide coverage. As a complementary device, IRS is deployed in existing wireless systems in wireless networks, without the need to change standards and hardware, only necessary modifications to the communication protocol are required, so integrating IRS into wireless networks can be transparent to users, thereby providing high flexibility and superior compatibility.

[0051] Existing communication technologies improve performance by optimizing communication terminals, while IRS technology improves performance by optimizing the propagation environment. Wireless communication technology assisted by IRS is a promising research direction, and as communication frequencies increase, the disadvantages of short wavelength, high path loss, and small coverage range of high-frequency communication are gradually exposed, so it is necessary to use the beamforming gain generated by mMIMO technology to compensate for path loss. The IRS surface is distributed with a large number of low-cost, high-energy-efficiency reflecting units, which can greatly improve weak propagation paths and meet the actual transmission needs of future 6G high-speed, large-capacity, and low-power consumption.

[0052] Current research on IRS primarily focuses on traditional microwave and millimeter-wave communications, specifically the 5G / B5G frequency bands. However, channel characteristics change with increasing frequency. Compared to microwaves and millimeter waves, terahertz links exhibit stronger directionality and cannot ignore molecular absorption losses, rendering existing models inadequate for the terahertz band. Furthermore, most current IRS-assisted communication channels are based solely on the SISO model, lacking a suitable IRS-assisted MIMO channel model for terahertz applications. Current research includes channel capacity and reachability optimization, joint design of active and passive beamforming, joint design of power allocation and beamforming, hybrid analog and digital beamforming, channel estimation algorithms, user association, and secure transmission. Most research on terahertz band MIMO channel modeling focuses on channel detection and modeling constrained by the initial physical environment of indoor / outdoor and microsystem scenarios. Traditional methods to improve signal transmission quality include enhancing the capabilities of base stations and terminals, or optimizing the network architecture, such as employing high-low frequency coordination, MIMO, multi-point cooperation, and micro-site blind spot filling. However, existing technologies rarely consider deploying IRS to directly improve wireless transmission channels. This invention utilizes IRS during transmission. Due to its passive nature, IRS achieves lower hardware costs and energy consumption compared to traditional reflective antenna arrays and active surfaces. Furthermore, IRS is typically lightweight, has a fixed planar structure, is easy to install and remove from the environment, and can be integrated into other devices. Additionally, IRS is suitable for large-scale deployment in wireless networks, enabling the transformation from IRS-free MIMO systems to IRS-assisted medium / small-sized MIMO systems, and from existing heterogeneous wireless networks to IRS-assisted hybrid networks.

[0053] To address the shortcomings of existing models, this invention proposes an IRS-assisted terahertz MIMO channel model. This model not only considers more complex scenarios and a more practical approach but also analyzes channel characteristic parameters such as path loss, signal-to-noise ratio, and coverage. Specifically, this application models and analyzes the characteristics of terahertz MIMO channels based on the unique structure of the IRS and its principle of intelligent reconfiguration of the wireless propagation environment.

[0054] In the following description, embodiments of the invention will be illustrated with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar parts, or the same or similar steps.

[0055] Figure 1 This is a flowchart illustrating an embodiment of the IRS-assisted terahertz MIMO wireless communication channel modeling method of the present invention, as shown below. Figure 1 As shown, the IRS-assisted terahertz MIMO wireless communication channel modeling method includes at least steps S10 to S40.

[0056] Step S10: Obtain the transmission power, the first position information of each antenna unit of the transmission end, the second position information of each antenna unit of the receiving end, and the third position information of each reflecting unit of the IRS reflecting surface. Calculate the first distance between each antenna unit of the transmission end and each antenna unit of the receiving end, the second distance between each antenna unit of the transmission end and each reflecting unit of the IRS reflecting surface, and the third distance between each antenna unit of the receiving end and each reflecting unit of the IRS reflecting surface based on the first position information, the second position information, and the third position information.

[0057] In this embodiment, since the MIMO wireless communication channel is adopted, at this time, the transmission end and the receiving end both have multiple antenna units, and the IRS reflecting surface has multiple reflecting units. For example, the IRS-assisted MIMO wireless communication channel is applied to the terahertz frequency band (100 GHz-10 THz), and at this time, the IRS-assisted terahertz MIMO communication model is as shown in Figure 2 , S represents the transmission end, which is composed of M antenna units, D represents the receiving end, which is composed of N antenna units, the IRS reflecting surface is placed on the y-z plane of the Cartesian coordinate system, and contains R antenna units in total. The geometric center of the IRS is located at the origin of the coordinate system. Specifically, the first distance between the antenna unit m of the transmission end and the antenna unit n of the receiving end is denoted as d mn , m takes 1, 2…M, and n takes 1, 2…N; the third distance between the antenna unit m of the transmission end and the reflecting unit r of the IRS reflecting surface is denoted as d mr , m takes 1, 2…M, and r takes 1, 2…R; the second distance between the antenna unit n of the receiving end and the reflecting unit r of the IRS reflecting surface is denoted as d rn , r takes 1, 2…R, and n takes 1, 2…N. Referring to Figure 2 , the distance between the center position of the transmission end and the center position of the IRS reflecting surface is denoted as d SR , the distance between the center position of the receiving end and the center position of the IRS reflecting surface is denoted as d RD , the distance between the center position of the transmission end and the center position of the receiving end is denoted as d SD ; ξ S and ξ D represent the pitch angles of the transmission end and the receiving end, respectively, ζ S and ζ D represent the azimuth angles of the transmission end and the receiving end, respectively; and represent the azimuth angles of the transmission end and the receiving end, respectively; and represent the included angles between the normal directions of the antenna units of the transmission end, the antenna units of the receiving end, and the reflecting units of the IRS reflecting surface.

[0058] Step S20: determining a first channel gain between the transmitting end and the receiving end based on the first distances, determining a second channel gain between the transmitting end and the IRS reflecting surface based on the second distances, and determining a third channel gain between the receiving end and the IRS reflecting surface based on the third distances.

[0059] In this step, the first channel gain, the second channel gain and the third channel gain are further determined based on the first distances, the second distances and the third distances determined in step S10.

[0060] For example, each channel gain can be determined according to the channel gain model in the UMi scenario of 3GPP TS 36.814, which is specifically as follows:

[0061]

[0062] The expression of the first channel gain between the transmitting end and the receiving end is:

[0063]

[0064] The expression of the second channel gain between the transmitting end and the IRS reflecting surface is:

[0065]

[0066] The expression of the third channel gain between the receiving end and the IRS reflecting surface is:

[0067]

[0068] wherein G S is the transmitting end antenna gain, G D is the receiving end antenna gain, M is the number of antenna units of the transmitting end, N is the number of antenna units of the receiving end, R is the number of reflecting units of the IRS reflecting surface, d mn represents the distance between the antenna unit m of the transmitting end and the antenna unit n of the receiving end, d mr represents the distance between the antenna unit m of the transmitting end and the reflecting unit r of the IRS reflecting surface, d rn represents the distance between the antenna unit n of the receiving end and the reflecting unit r of the IRS reflecting surface, and r takes 1, 2, …, R, n takes 1, 2, …, N, and m takes 1, 2, …, M. Further, d SR is the distance between the center position of the transmitting end and the center position of the IRS reflecting surface, d RD is the distance between the center position of the receiving end and the center position of the IRS reflecting surface, τS is the vector expression of the transmitting-end antenna unit, τ D is the vector expression of the receiving-end antenna unit, τ r is the first vector of the IRS reflecting surface reflecting unit; τ S = δ S (cosξ S cosζ S ,cosξ S ,sinξ S ), τ D = δ D (cosξ D cosζ D ,cosξ D sinζ D ,sinξ D ), δ S and δ D respectively represent the distance between the transmitting-end and receiving-end antenna units, ξ S and ξ D respectively represent the elevation angles of the transmitting-end and receiving-end, ζ S and ζ D respectively represent the azimuth angles of the transmitting-end and receiving-end.

[0069] Step S30: determining the phase shift matrix of the received signal of each antenna unit of the receiving-end on the propagation path.

[0070] In this step, the transmitting signal output by each antenna unit of the transmitting-end is reflected by each reflecting unit of the IRS reflecting surface, and the received signal received by each antenna unit of the receiving-end on the propagation path will produce a phase shift, at which time the phase shift matrix can be determined based on the phase shift corresponding to each reflecting unit.

[0071] And according to the distance between the transmitting-end, the transmitting-end and the IRS reflecting surface, there are at least two modes: beam forming mode and beam steering mode. In the beam forming mode, step S30 specifically comprises: obtaining the wavelength; determining the phase shift matrix based on the second distance, the third distance and the wavelength. While in the beam steering mode, step S30 specifically comprises: obtaining the wavelength; determining the first direction vector of the path between the transmitting-end and the IRS reflecting surface, determining the second direction vector of the path between the receiving-end and the IRS reflecting surface; determining the first vector of each reflecting unit of the IRS reflecting surface; determining the phase shift matrix based on the wavelength, the first direction vector, the second direction vector and the first vector.

[0072] In some embodiments, the phase shift matrix j is a complex number. And specifically in the beam forming mode, r = 1, 2, …, R, m = 1, 2, …, M, n = 1, 2…N, d mrdenotes a second distance between the transmitting antenna element m and the IRS reflecting element r, d rn denotes a third distance between the receiving antenna element n and the IRS reflecting element r, and denotes a wavelength. In the beam steering mode, r takes 1, 2, …, R, and r is a first vector, is a second unit representation vector, is a first unit representation vector, and denotes a wavelength.

[0073] Step S40: determining the receiving signal of each receiving element of the receiving end based on the transmitting signal of each antenna element of the transmitting end, the transmitting power, the first channel gain, the second channel gain, the third channel gain, and each phase shift matrix.

[0074] Exemplarily, the channel model can be expressed as y represents the receiving signal, and s represents the transmitting signal, β sd denotes the first channel gain, and sr denotes the second channel gain, and rd denotes the third channel gain, and MN denotes a unit matrix with a size of MxN, and RM denotes a unit matrix with a size of RxM, and RN denotes a unit matrix with a size of RxN, and n represents a Gaussian additive white noise, σ 2 denotes a noise variance, and represents a phase shift matrix.

[0075] In order to better reflect the advantages of the IRS-assisted MIMO wireless communication channel modeling method of the present application, the system coverage and the path loss of the MIMO wireless communication channel without deploying the IRS and the MIMO wireless communication channel with deploying the IRS are analyzed and compared below.

[0076] System coverage of the MIMO wireless communication channel without deploying the IRS and the MIMO wireless communication channel with deploying the IRS:

[0077] For the MIMO wireless communication channel without deploying the IRS, the channel model is y represents the receiving signal, s represents the transmitting signal, p represents the transmitting power, and n represents a Gaussian additive white noise, β sd denotes the channel gain between the transmitting end and the receiving end, and MN denotes a unit matrix with a size of MxN. Further, the channel capacity expression of the MIMO wireless communication channel without deploying the IRS is: M is the number of antenna elements of the transmitting end, N is the number of antenna elements of the receiving end, p is the transmitting power, and σ represents the Gaussian noise variance.

[0078] For the MIMO wireless communication channel with IRS deployed, the channel model thereof can be obtained based on the above embodiment as The channel capacity expression thereof can be obtained as R is the number of reflecting elements, M is the number of antenna elements of the transmitting end, N is the number of antenna elements of the receiving end, H sd,mn represents the channel between the transmitting end antenna element m and the receiving end antenna element n, h sr,mrn represents the channel between the transmitting end antenna element m and the IRS reflecting element r, h rd,mrn represents the channel between the IRS reflecting element r and the receiving end antenna element n.

[0079] If the receiving end is required to reach a bit rate ξ, the required transmission power ε can be determined based on the channel capacity expression, p is the transmitting power, and σ 2 is the noise variance. The network coverage rate is determined by the formula P = Pr(C > ξ), P is the network coverage rate, Pr represents the probability density function, and C is the channel capacity. Further, the channel capacity expressions C R and C with and without IRS deployed are brought into the coverage rate formula to obtain

[0080] The coverage rate without IRS is

[0081] The coverage rate after deploying IRS is

[0082] wherein, β sd represents the first channel gain, β sr represents the second channel gain, β rd represents the third channel gain, and And

[0083] Further, the coverage rate expression for the scenario without IRS can be obtained by processing the coverage rate expression using the matrix matching method, and is P = Γ(k, ε / w) / Γ(k), wherein wherein R represents the total number of reflecting elements of the IRS reflecting surface. The coverage rate for the scenario with IRS deployed can be calculated as

[0084] For the scenario of IRS-assisted terahertz MIMO wireless communication, if f = 100 GHz, M = 2, N = 2, G T = 5 dB, G R = 5 dB, d sr = 100 m, d rd = 100 m, R = 256, the coverage rate of the MIMO wireless communication channel with and without the deployment of IRS at different bit rates is shown in FIG. 5. Figure 3 As can be seen from FIG. 5, the coverage rate of the MIMO wireless communication channel with the deployment of IRS is significantly improved compared with the MIMO wireless communication channel without the deployment of IRS. Figure 3

[0085] The path loss of the MIMO wireless communication channel without the deployment of IRS and the MIMO wireless communication channel with the deployment of IRS:

[0086] Based on the channel model, the expression of the received power and the path loss of the MIMO wireless communication channel assisted by IRS is derived from the Friis transmission formula as follows:

[0087]

[0088] wherein, represents the radiation pattern of the reflecting unit of the IRS reflecting surface, represents the radiation pattern of the transmitting end antenna unit, represents the radiation pattern of the receiving end antenna unit, represents the offset azimuth angle of the transmitting and receiving end and the central normal line of the IRS reflecting surface, b r,mn is a complex value representing the response generated by the control of the reflecting unit of the IRS reflecting surface; represents the phase shift generated on the propagation path after the signal transmitted by the transmitting end antenna unit m is reflected by the r th efficiency coefficient represents the efficiency of the reflecting unit in the actual situation and the insertion loss related to the generation of the phase shift, represents the incident power from the mth antenna unit of the transmitting end to the rth reflecting unit of the IRS reflecting surface, represents the reflected power from the rth reflecting unit of the IRS reflecting surface to the nth antenna unit of the receiving end. σ p = exp(-κ(f)(d SR +d RD )), the molecular absorption coefficient κ(f) is determined by f, which is the carrier frequency. The expression of is shown as follows:​

[0089] q0=0.285; G r represents the gain of the rth reflecting unit.

[0090] Further, according to the distance between the transceiver and the IRS, three modes can be selected to compare the path loss of the MIMO wireless communication channel based on the IRS assisted MIMO wireless communication channel of the application with the MIMO wireless communication channel without deploying the IRS. The selected mode can be: a general mode, a beamforming mode and a beam steering mode.

[0091] For the general mode, at this time, the IRS only acts as a normal reflecting surface, and the condition b r,mn =1, at this time, the expression of the path loss is:

[0092] θ r,mn is the phase shift from the mth antenna element of the transmitter to the nth antenna element of the receiver through the rth reflecting unit of the IRS reflecting surface.

[0093] For the beamforming mode: at this time, each element of the phase shift matrix then When the distance d between the transceiver and the IRS satisfies the far field condition , D represents the diagonal length of the IRS reflecting surface, and λ represents the wavelength. At this time, the distance difference between the transceiver and different units on the IRS can be ignored. The expression of the path loss in the far distance beamforming mode is: When the distance d between the transceiver and the IRS does not satisfy the far field condition, the distance difference between the transceiver and different units on the IRS needs to be considered. The expression of the path loss in the near distance beamforming mode is:

[0094] λ represents the wavelength, M represents the number of antenna elements of the transmitter, N represents the number of antenna elements of the receiver, R represents the number of reflecting units of the IRS reflecting surface, ε p represents the efficiency of the IRS reflecting unit, σ p represents the molecular absorption loss coefficient of the terahertz wave.

[0095] For the beam steering mode, the phase shift is set to minimize the path loss in the direction of the transceiver. At this time, each element of the phase shift matrix then then Substituting, the expression of the path loss in the beam steering mode is obtained as:

[0096]

[0097] And for the IRS-assisted terahertz MIMO wireless communication scenario, if f = 100 GHz, M = 2, N = 2, G T = 5 dB, G R = 5 dB, R = 256, the distance d sr and d rd between the IRS and the transceiver is changed, the change of the path loss under the far and near distances is obtained as shown in Figure 4 and Figure 5 , wherein, Figure 4 and Figure 5 The "source end" in and represents the "transmitting end".

[0098] In the above embodiment, the path loss formula of the three scenarios of the general mode, the beam steering and the beam forming is established in combination with the established model and the Friis transmission formula, and the influence of the distance between the transceiver and the IRS and the angle on the path loss can be easily obtained through the path loss expression in each scenario. In addition, based on the channel capacity formula, the closed-loop expression of the signal coverage rate, by comparing with the coverage rate without deploying the IRS, it is obtained that the coverage rate of the MIMO wireless communication channel deployed with the IRS has a better improvement effect relative to the coverage rate of the MIMO wireless communication channel without deploying the IRS.

[0099] It can be found through the above embodiment that the MIMO wireless communication channel modeling method based on IRS assistance disclosed in the embodiment of the present application is based on the intelligent metasurface theory assisted by the IRS, and a terahertz MIMO channel model under the assistance of the IRS is constructed. The model has universality, and by adjusting the distance between the transceiver, the offset angle and the number of antenna elements of the IRS surface and the like, different channel scenarios can be flexibly simulated, so that the coverage range of the channel model is improved. The MIMO wireless communication channel modeling method based on IRS assistance is not only suitable for the terahertz frequency band (100 GHz-10 THz), but also suitable for the millimeter wave and microwave frequency bands; the MIMO wireless communication channel based on IRS assistance under the terahertz frequency band includes a terahertz LOS MIMO (line of sight / direct path) channel and a terahertz NLOS MIMO (non-line of sight / non-direct path) channel. In addition to establishing a new link and eliminating interference, the IRS can also ensure secure communication between the transmitting end and the legitimate receiving end from the physical layer by adjusting the phase, amplitude and the like of the transmitting end signal. The IRS-assisted application in the multiple-input and multiple-output wireless communication channel improves the uplink reception gain.

[0100] Correspondingly, the application also discloses an IRS-assisted MIMO wireless communication channel modeling system, which comprises a processor and a memory, the memory stores computer instructions, and the processor is used for executing the computer instructions stored in the memory, and when the computer instructions are executed by the processor, the system implements the steps of the method according to any one of the above embodiments.

[0101] The modeling method and system disclosed by the application can describe the transmission channel of the blocked LoS path scene and the low signal quality scene at the edge of the base station coverage in a dense urban area based on the new three-dimensional channel model of the IRS in the terahertz band, and the model has universality and adaptability and can be used to simulate various IRS-assisted communication scenes.

[0102] In addition, the application also discloses a computer readable storage medium, which stores a computer program, and the program is executed by the processor to implement the steps of the method according to any one of the above embodiments.

[0103] Those skilled in the art should understand that the exemplary components, systems and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software or a combination of both. Whether the implementation is in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the application. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, etc. When implemented in software, the elements of the application are program or code segments used to perform the required tasks. The program or code segments can be stored in a machine readable medium or transmitted through a data signal carried in a carrier wave on a transmission medium or communication link. The "machine readable medium" can include any medium capable of storing or transmitting information. Examples of machine readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segments can be downloaded via a computer network such as the Internet, an intranet, etc.

[0104] It should also be noted that the exemplary embodiments mentioned in the application describe some methods or systems based on a series of steps or devices. However, the application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in an order different from the embodiments, or several steps can be performed simultaneously.

[0105] Features described and / or illustrated with respect to one implementation can be used in the same manner or in a similar manner in one or more other implementations and / or in combination with or in place of features of other implementations.

[0106] The above descriptions are merely some embodiments of the present application, but are not intended to limit the present application. The embodiments of the present application can be variously changed and / or modified by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall fall within the scope of the present application.

Claims

1. A method for modeling a terahertz MIMO wireless communication channel based on IRS assistance, characterized in that, The method comprises: acquiring a transmission power, first position information of each antenna unit of a transmission end, second position information of each antenna unit of a receiving end, and third position information of each reflecting unit of an IRS reflecting surface, calculating first distances between each antenna unit of the transmission end and each antenna unit of the receiving end, second distances between each antenna unit of the transmission end and each reflecting unit of the IRS reflecting surface, and third distances between each antenna unit of the receiving end and each reflecting unit of the IRS reflecting surface based on the first position information, the second position information, and the third position information; determining a first channel gain between the transmission end and the receiving end based on the first distances, determining a second channel gain between the transmission end and the IRS reflecting surface based on the second distances, and determining a third channel gain between the receiving end and the IRS reflecting surface based on the third distances; determining a phase shift matrix of signals received by each antenna unit of the receiving end on a propagation path; determining a received signal of each receiving unit of the receiving end based on a transmission signal of each antenna unit of the transmission end, the transmission power, the first channel gain, the second channel gain, the third channel gain, and the phase shift matrix; a calculation formula of the received signal of each receiving unit of the receiving end is: wherein represents a received signal, represents a transmitted signal, , , , represents a first channel gain, represents a second channel gain, represents a third channel gain, represents an identity matrix of size M x N, represents an identity matrix of size R x M, represents an identity matrix of size R x N, n represents a Gaussian additive white noise, represents a phase shift matrix, p is a transmission power; wherein there are at least two modes according to the distances of the transmission end and the IRS reflecting surface: a beamforming mode and a beam steering mode; in the beamforming mode, a wavelength is acquired, and the phase shift matrix is determined based on the second distances, the third distances, and the wavelength; in the beam steering mode, a wavelength is acquired, a first direction vector of a path between the transmission end and the IRS reflecting surface is determined, a second direction vector of a path between the receiving end and the IRS reflecting surface is determined, a first vector of each reflecting unit of the IRS reflecting surface is determined, and the phase shift matrix is determined based on the wavelength, the first direction vector, the second direction vector, and the first vector; wherein, in the beamforming mode, the phase shift matrix ; wherein, is a complex number, , r = 1, 2…R, denotes a second distance between the transmitting end antenna unit m and the IRS reflecting surface reflecting unit r, denotes a third distance between the receiving end antenna unit n and the IRS reflecting surface reflecting unit r, denotes a wavelength, m = 1, 2…M, n = 1, 2…N, R denotes the number of IRS reflecting surface reflecting units, M denotes the number of transmitting end antenna units, and N denotes the number of receiving end antenna units; in the beam steering mode, the phase shift matrix ; wherein, is a complex number, = , r = 1, 2…R, R denotes the number of IRS reflecting surface reflecting units, is a first vector, is a second unit representation vector, is a first unit representation vector, is a wavelength.​ 2. The method of claim 1, wherein: a calculation formula of the first channel gain is: ； a calculation formula of the second channel gain is: ； a calculation formula of the third channel gain is: ； wherein, is the transmit-end antenna gain, is the receive-end antenna gain, M is the number of antenna elements of the transmit-end, N is the number of antenna elements of the receive-end, R is the number of reflecting elements of the IRS reflecting surface, denotes the distance between the antenna element m of the transmit-end and the antenna element n of the receive-end, denotes the distance between the transmit-end antenna element m and the IRS reflecting surface reflecting element r, denotes the distance between the receive-end antenna element n and the IRS reflecting surface reflecting element r, r = 1, 2…R, m = 1, 2…M, n = 1, 2…N.

3. The IRS-aided terahertz MIMO wireless communication channel modeling method according to claim 2, wherein, , , = 1,2,... M, n = 1,2,... N; wherein, is the distance between the center position of the transmitting end and is the distance between the center position of the reflecting surface and is the distance between the center position of the receiving end and the center position of the IRS reflecting surface, is a second vector of the transmitting end antenna unit, is a third vector of the receiving end antenna unit, is a first vector of the IRS reflecting surface reflecting unit.

4. An IRS-aided terahertz MIMO wireless communication channel modeling system, the system comprising a processor and a memory, wherein, The memory stores computer instructions, and the processor is configured to execute the computer instructions stored in the memory, and when the computer instructions are executed by the processor, the system implements the steps of the method of any one of claims 1 to 3.

5. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the steps of the method of any one of claims 1 to 3.

Images