Advanced XL-MIMO design method and system for enhancing wireless augmented reality communication

Abstract

The invention provides an advanced XL-MIMO design method and system for enhancing wireless augmented reality communication. The advanced XL-MIMO design method comprises the steps of S1, selecting and designing a required frequency band and determining system parameters; s2, a centimetre wave frequency band centralized mMIMO system is designed according to the parameters, the system comprises a base station BS and a plurality of multi-user MUs, the base station adopts hybrid beam forming, and a zero-forcing equalization technology is used for digital beam forming; s3, designing a distributed XL-MIMO system under the millimeter wave and sub-terahertz frequency bands according to the parameters; s4, establishing a channel model, acquiring 3GPP and BUPT channel data, and verifying the accuracy of the data; s5, performing simulation in the UMi scene of the urban micro cell; and S6, according to the simulation result, obtaining the maximum achievable data rate in the augmented reality XR scene. According to the invention, smooth and immersive experience is ensured, and a more efficient and more stable communication effect is realized in the aspect of selecting proper architecture and frequency band.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to an advanced XL-MIMO design method and system for enhancing wireless extended reality communication. Background Art

[0002] Extended reality (XR) is an immersive technology that integrates the physical and virtual worlds. With the continuous development of XR technology, the market demand for communication technologies with higher throughput, lower latency and enhanced data processing capabilities has increased dramatically. The basic requirements of XR include high data rate, low latency and high reliability, which far exceed the capabilities that traditional communication systems can provide. Therefore, how to achieve efficient and stable communication has become the key to the application and development of wireless XR technology. In order to meet the high demand for wireless XR, a number of cutting-edge technologies have begun to attract the attention of researchers, especially reconfigurable smart surfaces, artificial intelligence, high-frequency millimeter wave communications, terahertz communications, and advanced antenna technologies, which are all important directions for improving the communication performance of wireless XR applications.

[0003] Among many technologies, Multiple Input Multiple Output (MIMO) technology is widely used. Due to its wide application in 4G and 5G wireless networks, it has become a basic technology for improving the performance of communication systems. MIMO technology improves the capacity, signal quality and anti-interference ability of wireless systems by using multiple antenna units at the transmitting and receiving ends. In particular, very large-scale multiple-input multiple-output (XL-MIMO) and massive multiple-input multiple-output (mMIMO) technologies have become key technologies to meet the needs of high-speed and high-capacity communications. XL-MIMO significantly improves communication capabilities and optimizes signal transmission paths through precise beamforming, which is crucial to providing high-quality XR experience.

[0004] XL-MIMO technology is based on the evolution of traditional MIMO technology. It mainly deploys a large number of antenna elements to significantly improve the performance of the communication system. The advantage of XL-MIMO is that it can achieve more accurate beamforming in large-scale arrays. By optimizing the signal transmission path, it can not only increase the communication capacity of the system, but also effectively reduce signal interference and multipath effects. Specifically, XL-MIMO can significantly increase the channel capacity of the system by increasing the scale of the antenna array, especially when facing the needs of wireless XR applications with high data rates, it can significantly improve the performance of the system. In the face of complex wireless environments, XL-MIMO can achieve precise signal orientation, significantly reduce interference and signal attenuation, and further improve the reliability and stability of the system through the configuration of its large-scale antenna array. Especially in the millimeter wave and terahertz frequency bands, due to the wide bandwidth of these frequency bands, they are suitable for supporting the high-speed data transmission needs of wireless XR, and XL-MIMO technology can provide better signal transmission efficiency in these high-frequency bands to meet the requirements of wireless XR applications for high-speed communication.

[0005] Although XL-MIMO technology has made some progress, there are still many unsolved technical challenges in how to fully utilize the potential of XL-MIMO for XR applications, especially in high-frequency bands (such as millimeter wave and sub-terahertz bands). For example, signal transmission and reception in complex non-line-of-sight (NLoS) environments. Under NLoS conditions, signal propagation is blocked by buildings, terrain and other obstacles, resulting in significant signal attenuation and multipath effects. Different frequency bands (such as centimeter wave, millimeter wave and sub-terahertz bands) have different propagation characteristics. How to design XL-MIMO array configurations that adapt to different frequency bands is a problem that needs to be solved in system design. In large-scale deployments, the scale and complexity of XL-MIMO arrays continue to increase. How to maintain the efficiency and scalability of the system and avoid system performance degradation due to excessive computational burden or high hardware complexity is another technical challenge. In addition, existing research on XL-MIMO support for wireless XR applications is still relatively small, especially in terms of how much data rate can be supported.

[0006] Definitions of Abbreviations and Key Terms:

[0007] XR Extended Reality

[0008] XL-MIMO Extremely Large Multiple-Input-Multiple-Output

[0009] mMIMO massive MIMO massive multiple input multiple output

[0010] 3GPP 3rd Generation Partnership Project

[0011] BUPT Beijing University of Posts and Telecommunications

[0012] UMi Urban Microcell

[0013] BS Base Station

[0014] MU Multi-User

[0015] ZF Zero Forcing

[0016] UPA Uniform Planar Array Uniform Planar Array

[0017] ISD Inter-Site Distance

[0018] CDF Cumulative Distribution Function

[0019] SNR Signal-to-Noise Ratio

[0020] LoS Line of Sight

[0021] NLoS Non-Line-of-Sight Summary of the invention

[0022] In view of the defects in the prior art, the present invention provides an advanced XL-MIMO design method and system for enhancing wireless extended reality communication.

[0023] According to the present invention, an advanced XL-MIMO design method and system for enhancing wireless extended reality communication is provided, which aims to fully explore the support capabilities of XL-MIMO for wireless XR applications in centimeter wave, millimeter wave and sub-terahertz bands by designing a multi-band advanced antenna system, thereby revealing the inherent principles of XL-MIMO and its potential in the field of wireless XR. The scheme is as follows:

[0024] In a first aspect, an advanced XL-MIMO design method for enhancing wireless extended reality communication is provided, the method comprising:

[0025] Step S1: Select the frequency band required for the design and determine the system parameters;

[0026] Step S2: designing a centimeter wave frequency band centralized mMIM0 system according to the parameters, the system comprising a base station BS and multiple multi-user MUs, wherein the base station adopts hybrid beamforming and uses zero-forcing equalization technology for digital beamforming;

[0027] Step S3: designing a distributed XL-MIMO system in millimeter wave and sub-terahertz frequency bands according to the parameters;

[0028] Step S4: Establish a channel model, obtain 3GPP and BUPT channel data and verify data accuracy;

[0029] Step S5: Perform simulation in the urban microcell UMi scenario;

[0030] Step S6: According to the simulation results, obtain the maximum achievable data rate in the extended reality XR scenario.

[0031] Preferably, the step S2 comprises: maintaining beam separation between users through sector division, the base station and user antennas both use UPA antennas, and the antenna spacing is half a wavelength.

[0032] Preferably, in step S2, maximizing the channel capacity is achieved by combining hybrid beamforming and zero-forcing equalization technology, including:

[0033] In a multi-user system, the zero-forcing equalization technology is used to prevent the signal received by the receiving end from being interfered by other user signals, that is, to eliminate the interference between users. The specific optimization process is calculated by W ZF , W ZF is the optimized beamforming matrix:

[0034] W ZF =(H T H) -1 H H

[0035] Among them, H H represents the conjugate transpose of the channel matrix; (H T H) -1 It is the pseudo-inverse of the channel matrix, ensuring that the receiving end can completely eliminate interference and achieve optimal data transmission effect;

[0036] Hybrid beamforming combines traditional digital beamforming and RF beamforming, allowing the system to be optimized in hardware and reduce the computational burden. The introduction of hybrid beamforming reduces hardware complexity and optimizes performance:

[0037] W HB =WRF W ZF

[0038] W RF represents the RF part beamforming matrix; W ZF Represents the baseband part beamforming matrix, which processes the baseband signal and further adjusts the beam.

[0039] Preferably, in step S3, a single-cell, single-user millimeter wave or sub-terahertz system utilizes four distributed XL-MIMO subarrays based on uniform planar arrays (UPA), and each subarray is located at a symmetrical edge of the cell.

[0040] Preferably, the step S5 comprises: performing simulation in a scenario of an urban micro cell UMi, using a circular cell, which complies with the cell spacing in the 3GPP standard;

[0041] In a multi-user centralized array system, thousands of random user position channel realizations are performed, where line-of-sight LoS and non-line-of-sight NLoS states between different arrays and users, different signal-to-noise ratio (SNR) values, and user antenna configurations are considered, covering all frequency bands.

[0042] In a second aspect, an advanced XL-MIMO design system for enhancing wireless extended reality communication is provided, the system comprising:

[0043] Module M1: Select the frequency band required for the design and determine the system parameters;

[0044] Module M2: Design a centimeter wave band centralized mMIM0 system according to the parameters. The system includes a base station BS and multiple multi-user MUs. The base station adopts hybrid beamforming and uses zero-forcing equalization technology for digital beamforming.

[0045] Module M3: Design of distributed XL-MIM0 system in millimeter wave and sub-terahertz frequency bands according to parameters;

[0046] Module M4: Establish channel model, obtain 3GPP and BUPT channel data and verify data accuracy;

[0047] Module M5: Simulation in the urban micro-cell UMi scenario;

[0048] Module M6: Based on the simulation results, obtain the maximum achievable data rate in the extended reality XR scenario.

[0049] Preferably, the module M2 includes: maintaining beam separation between users through sector division, base station and user antennas both use UPA antennas, and the antenna spacing is half a wavelength.

[0050] Preferably, in the module M2, the channel capacity is maximized by combining hybrid beamforming and zero-forcing equalization technology, including:

[0051] In a multi-user system, the zero-forcing equalization technology is used to prevent the signal received by the receiving end from being interfered by other user signals, that is, to eliminate the interference between users. The specific optimization process is calculated by W ZF , W ZF is the optimized beamforming matrix:

[0052] W ZF =(H T H) -1 H H

[0053] Among them, H H represents the conjugate transpose of the channel matrix; (H T H) -1 It is the pseudo-inverse of the channel matrix, ensuring that the receiving end can completely eliminate interference and achieve optimal data transmission effect;

[0054] Hybrid beamforming combines traditional digital beamforming and RF beamforming, allowing the system to be optimized in hardware and reduce the computational burden. The introduction of hybrid beamforming reduces hardware complexity and optimizes performance:

[0055] W HB =W RF W ZF

[0056] W RF represents the RF part beamforming matrix; W ZF Represents the baseband part beamforming matrix, which processes the baseband signal and further adjusts the beam.

[0057] Preferably, in the module M3, a single-cell, single-user millimeter wave or sub-terahertz system utilizes four distributed XL-MIMO subarrays based on uniform planar arrays (UPA), each subarray being located at a symmetrical edge of the cell.

[0058] Preferably, the module M5 comprises: simulation is performed in a scenario of urban microcell UMi, using circular cells, which conform to the cell spacing in the 3GPP standard;

[0059] In a multi-user centralized array system, thousands of channel realizations at random user locations are performed, taking into account the line-of-sight LoS and non-line-of-sight NLoS states between different arrays and users, different signal-to-noise ratio (SNR) values, and user antenna configurations. Thousands of channel realizations cover all frequency bands.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] The proposed system consistently exceeds the basic data rate requirements of wireless XR in all frequency bands, ensuring a smooth and immersive experience. It provides important insights into the design and optimization of advanced antenna systems for wireless XR, especially in selecting appropriate antenna architectures and wireless frequency bands to achieve more efficient and stable communication effects. At the same time, the data results of this solution also provide new theoretical support for future XR applications.

[0062] Other beneficial effects of the present invention will be explained in the specific implementation manner through the introduction of specific technical features and technical solutions. Through the introduction of these technical features and technical solutions, those skilled in the art should be able to understand the beneficial technical effects brought about by the technical features and technical solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0064] Figure 1a-1b They are respectively the centralized and distributed XL-MIMO antenna systems according to the embodiments of the present invention;

[0065] Figure 2 A flowchart of an advanced XL-MIMO design scheme for enhancing extended reality communication according to an embodiment of the present invention;

[0066] Figure 3 is the cumulative distribution function of the maximum achievable rate of 3.5GHz centralized mMIMO;

[0067] Figure 4 is the cumulative distribution function of the maximum achievable rate of 14GHz centralized mMIMO;

[0068] Figure 5 is the cumulative distribution function of the maximum achievable rate of 39GHz distributed XL-MIMO;

[0069] Figure 6 Cumulative distribution function of the maximum achievable rate of 132GHz distributed XL-MIMO. DETAILED DESCRIPTION

[0070] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0071] The embodiment of the present invention provides an advanced XL-MIM0 design method for enhancing wireless extended reality communication, such as Figure 1a-1b The centralized and distributed antenna systems with multiple frequency bands are designed, and the channel characteristics and performance in urban micro-scenes are compared. Through the channel generation platform data based on actual measurements and simulation verification, the antenna architecture and frequency selection are optimized, providing a theoretical basis and design guidance for the future application of mMIM0 and XL-MIM0 in 6G communication systems. Figure 2 As shown in the figure, this method designs an advanced multi-band centralized / distributed antenna system, combines the 3rd Generation Partnership Project (3GPP) standard channel model with the data generated by BUPT's real test platform simulation, and comprehensively studies the performance of XL-MIM0 in wireless XR applications, exploring its practical application potential of the maximum supportable data rate in multiple frequency bands, including:

[0072] Step S1: Select the frequency band required for the design and determine the system parameters.

[0073] Select appropriate frequency bands for system design, mainly including centimeter wave bands, millimeter wave bands and sub-terahertz bands. For the centimeter wave band, this band has wide coverage, strong penetration ability and low propagation loss, making it suitable for providing wide coverage for multiple users. Through centralized array design, it can ensure that the system can provide efficient and wide user coverage.

[0074] Step S2: design a centimeter wave frequency band centralized mMIM0 system according to the parameters, the system includes a base station (BS) and 10 multi-users (MUs), wherein the base station adopts hybrid beamforming and uses zero forcing equalization technology (ZF) for digital beamforming; the system covers a cell divided into 10 equal sectors, each sector accommodating one user.

[0075] The transmit antenna spacing is set to half a wavelength. It should be noted that the LoS and NLoS conditions between the base station and the user may change dynamically. Sector division is used to maintain appropriate beam separation between users to reduce interference and promote fairness. Both the base station and user antennas use UPA antennas with a half-wavelength spacing.

[0076] By combining hybrid beamforming and zero-forcing equalization technology, channel capacity is maximized, including:

[0077] In a multi-user system, the zero-forcing equalization technology is used to prevent the signal received by the receiving end from being interfered by other user signals, that is, to eliminate the interference between users. The specific optimization process is calculated by W ZF , W ZF is the optimized beamforming matrix:

[0078] W ZF=(H T H) -1 H H

[0079] Among them, H H represents the conjugate transpose of the channel matrix; (H T H) -1 It is the pseudo-inverse of the channel matrix, ensuring that the receiving end can completely eliminate interference and achieve optimal data transmission effect;

[0080] Hybrid beamforming combines traditional digital beamforming and RF beamforming, allowing the system to be optimized in hardware and reduce the computational burden. The introduction of hybrid beamforming reduces hardware complexity and optimizes performance:

[0081] W HB =W RF W ZF

[0082] W RF represents the RF part beamforming matrix; W ZF Represents the baseband part beamforming matrix, which processes the baseband signal and further adjusts the beam.

[0083] Step S3: Design a distributed XL-MIMO system in the millimeter wave and sub-terahertz frequency bands according to the parameters. Consider a single-cell, single-user millimeter wave or sub-terahertz system and utilize four distributed uniform planar array (UPA)-based XL-MIMO subarrays, each located at the symmetrical edge (upper, lower, left, and right) of the cell. This arrangement helps to enhance the comprehensive coverage of the cell range while maintaining cost-effectiveness.

[0084] In this system, the LoS and NLoS conditions between the distributed sub-arrays and users will vary, affecting the transmission and connectivity of the signals.

[0085] Step S4: Establish a channel model, obtain 3GPP and BUPT channel data and verify the data accuracy; that is, establish a channel model for the system and use 3GPP TR 38.901 Release 17 and BUPT channel models for simulation.

[0086] The 3GPP model focuses on standardization and performance and is applicable to a wide range of wireless communication scenarios, while the BUPT model has advantages in high-frequency transmission and urban environment modeling. The two channel models provide a solid theoretical basis and practical guidance for system performance evaluation.

[0087] Step S5: Simulate in an urban microcell (UMi) scenario; a circular cell with a radius of 200 meters is used, which complies with the cell spacing in the 3GPP standard. In a multi-user centralized array system, 1,000 random channel realizations were performed, considering line-of-sight (LoS) and non-line-of-sight (NLoS) states between different arrays and users. Different signal-to-noise ratio (SNR) values ​​and user antenna configurations were taken into account, and a total of 28,000 channel realizations were performed, covering all frequency bands. The LoS or NLoS state between the array and the user, different SNR values ​​and user antenna configurations all need to be taken into account, so a large number of experiments is more convincing.

[0088] Step S6: According to the simulation results, the maximum achievable data rate in the extended reality XR scenario is obtained. In the centralized system, each user is allocated four data streams and RF links, and a total of 40 RF links are allocated to all users. In the distributed system, each subarray is also allocated four data streams and RF links, with a total of 16 RF links.

[0089] When analyzing the beamforming architecture, hardware costs were not considered for the time being. Instead, the focus was on exploring the maximum achievable data rate in wireless XR scenarios, especially the performance at higher cost levels.

[0090] The present invention also provides an advanced XL-MIMO design system for enhancing wireless extended reality communication, which can be implemented by executing the process steps of the advanced XL-MIMO design method for enhancing wireless extended reality communication, that is, those skilled in the art can understand the advanced XL-MIMO design method for enhancing wireless extended reality communication as a preferred implementation of the advanced XL-MIMO design system for enhancing wireless extended reality communication. The system specifically includes:

[0091] Module M1: Select the frequency band required for the design and determine the system parameters.

[0092] Select appropriate frequency bands for system design, mainly including centimeter wave bands, millimeter wave bands and sub-terahertz bands. For the centimeter wave band, this band has wide coverage, strong penetration ability and low propagation loss, making it suitable for providing wide coverage for multiple users. Through centralized array design, it can ensure that the system can provide efficient and wide user coverage.

[0093] Module M2: A centimeter-wave frequency band centralized mMIM0 system is designed according to the parameters. The system includes a base station (BS) and 10 multi-users (MUs). The base station adopts hybrid beamforming and uses zero-forcing equalization technology (ZF) for digital beamforming. The system covers a cell divided into 10 equal sectors, and each sector accommodates one user.

[0094] The transmit antenna spacing is set to half a wavelength. It should be noted that the LoS and NLoS conditions between the base station and the user may change dynamically. Sector division is used to maintain appropriate beam separation between users to reduce interference and promote fairness. Both the base station and user antennas use UPA antennas with a half-wavelength spacing.

[0095] By combining hybrid beamforming and zero-forcing equalization technology, channel capacity is maximized, including:

[0096] In a multi-user system, the zero-forcing equalization technology is used to prevent the signal received by the receiving end from being interfered by other user signals, that is, to eliminate the interference between users. The specific optimization process is calculated by W ZF , W ZF is the optimized beamforming matrix:

[0097] W ZF =(H T H) -1 H H

[0098] Among them, H H represents the conjugate transpose of the channel matrix; (H T H) -1 It is the pseudo-inverse of the channel matrix, ensuring that the receiving end can completely eliminate interference and achieve optimal data transmission effect;

[0099] Hybrid beamforming combines traditional digital beamforming and RF beamforming, allowing the system to be optimized in hardware and reduce the computational burden. The introduction of hybrid beamforming reduces hardware complexity and optimizes performance:

[0100] W HB =W RF W ZF

[0101] W RF represents the RF part beamforming matrix; W ZF Represents the baseband part beamforming matrix, which processes the baseband signal and further adjusts the beam.

[0102] Module M3: Design of distributed XL-MIM0 systems in mmWave and THz bands according to parameters. Consider a single-cell, single-user mmWave or THz system and utilize four distributed XL-MIM0 subarrays based on uniform planar arrays (UPA), each located at the symmetrical edge of the cell. This arrangement helps to enhance the comprehensive coverage of the cell range while maintaining cost-effectiveness.

[0103] In this system, the LoS and NLoS conditions between the distributed sub-arrays and users will vary, affecting the transmission and connectivity of the signals.

[0104] Module M4: Establish a channel model, obtain 3GPP and BUPT channel data and verify data accuracy; that is, establish a channel model for the system and use 3GPP TR 38.901 Release 17 and BUPT channel models for simulation.

[0105] The 3GPP model focuses on standardization and performance and is applicable to a wide range of wireless communication scenarios, while the BUPT model has advantages in high-frequency transmission and urban environment modeling. The two channel models provide a solid theoretical basis and practical guidance for system performance evaluation.

[0106] Module M5: Simulation in an Urban Microcell (UMi) scenario; a circular cell with a radius of 200 meters is used, which complies with the cell spacing in the 3GPP standard. In a multi-user centralized array system, 1000 random channel realizations are performed, considering line-of-sight (LoS) and non-line-of-sight (NLoS) conditions between different arrays and users. Different signal-to-noise ratio (SNR) values ​​and user antenna configurations are taken into account, and a total of 28,000 channel realizations are performed, covering all frequency bands. LoS or NLoS conditions between arrays and users, different SNR values ​​and user antenna configurations need to be taken into account, so a large number of experiments is more convincing.

[0107] Module M6: Based on the simulation results, obtain the maximum achievable data rate in the extended reality XR scenario. In the centralized system, each user is assigned four data streams and RF links, and a total of 40 RF links are assigned to all users. In the distributed system, each subarray is also assigned four data streams and RF links, with a total of 16 RF links.

[0108] When analyzing the beamforming architecture, hardware costs were not considered for the time being. Instead, the focus was on exploring the maximum achievable data rate in wireless XR scenarios, especially the performance at higher cost levels.

[0109] Next, the present invention will be described in more detail.

[0110] The present invention provides an advanced XL-MIMO design method for enhancing wireless extended reality communication, evaluating the channel characteristics and actual performance of XL-MIMO technology in different frequency bands and urban micro-cell scenarios, and ensuring that the communication quality meets the requirements of wireless XR applications. Different from the simple channel model assumptions of most inventions, the sub-terahertz channel data and 3GPP channel data generated based on the measured channel platform are simulated and verified, and the antenna architecture is designed for multiple frequency bands, providing a theoretical basis and design guidance for the future application of mMIMO and XL-MIMO in 6G communication systems.

[0111] The method of the present invention aims at the challenge of high data rate requirements in wireless XR application scenarios. The design of the centralized system uses hybrid beamforming and cooperates with ZF to perform digital beamforming algorithm. The specific principles are as follows:

[0112] Channel capacity is an important indicator to measure the maximum data transmission rate of a communication system, and is defined as follows:

[0113]

[0114] Where: C is the channel capacity, in bps / H Z , H is N t ×N r The channel matrix represents the channel relationship between the transmitter and the receiver, P is the transmit power, and N0 is the noise power. The present invention combines hybrid beamforming and zero-forcing equalization technology to adopt the following strategy to maximize the channel capacity:

[0115] (1) Use zero-forcing equalization. In a multi-user system, signal interference will lead to a decrease in channel capacity. In order to eliminate this interference, we use the zero-forcing equalization method. The goal of zero-forcing equalization is to make the signal received by the receiver not interfered by other users' signals, that is, to eliminate the interference between users. The specific optimization process is to calculate W ZF , W ZF is the optimized beamforming matrix:

[0116] W ZF =(H T H) -1 H H

[0117] Among them, H H represents the conjugate transpose of the channel matrix, (H T H) -1 It is the pseudo-inverse of the channel matrix, ensuring that the receiving end can completely eliminate interference and achieve optimal data transmission effect.

[0118] (2) Hybrid beamforming combines traditional digital beamforming and RF beamforming, enabling the system to be optimized in hardware and reduce the computational burden. Introducing hybrid beamforming reduces hardware complexity and optimizes performance:

[0119] W HB =W RF W ZF

[0120] W RF represents the RF part beamforming matrix; W ZF Represents the baseband part beamforming matrix, which processes the baseband signal and further adjusts the beam.

[0121] Based on hybrid beamforming technology and combined with a zero-forcing equalization algorithm suitable for multi-user scenarios, it can reduce interference and improve transmission stability.

[0122] This solution takes into account the following characteristics of the channel performance in the urban micro-cell scenario:

[0123] (1) Multipath propagation: In urban environments, reflection, scattering, and shielding effects from buildings lead to a variety of signal propagation paths. The arrival time, power, and angle of each propagation path are different, and these factors together affect the received signal strength and quality. By deploying a large number of antenna arrays, XL-MIMO can effectively identify and utilize these multipath propagation signals, improving the system's transmission stability and data rate.

[0124] (2) LoS and NLoS propagation: The LoS path is mainly composed of unobstructed direct propagation, providing a relatively stable signal strength; while the NLoS path is blocked by buildings or other obstacles, resulting in reflection or scattering. This design explores the performance under NLoS conditions by optimizing beamforming and using hybrid beamforming technology.

[0125] (3) Frequency dependence: The channel characteristics of different frequency bands vary significantly. High frequency bands (such as millimeter waves and terahertz bands) are more sensitive to obstruction, and signal propagation is easily blocked, resulting in signal attenuation. Low frequency bands (such as centimeter waves) have stronger penetration and can better penetrate obstacles, ensuring signal stability and coverage. In the design, choosing the appropriate frequency band is crucial to system performance.

[0126] Based on the characteristic performance of the channel and considering the matched frequency band, the system model is built. The present invention simulates the sub-terahertz channel data generated based on the actual measurement platform and the 3GPP standard channel data to obtain reliable simulation results. This solution explores the potential data rate that wireless XR applications can support when the MIMO dimension is pushed to the limit. By comparing Figure 3 and Figure 4 It can be clearly seen that in low to medium rate areas, under LoS conditions, the direct transmission path leads to lower path loss, higher signal strength and better stability. Although LoS performs better in low rate areas, in NLoS conditions, due to the superposition effect of multipath signals, the performance of NLoS may surpass LoS, thereby improving transmission efficiency and data rate.

[0127] Secondly, in the NLoS case, the maximum achievable data rates in the 3.5GHz and 14GHz bands reach 7.1Gbps, 14.5Gbps, and 21.5Gbps, 35.2Gbps (at SNRs of 10dB and 20dB, respectively). This represents a significant improvement over the LoS state, primarily due to the significant structural reflection, refraction, and diffraction effects in the NLoS environment, which form strong multipath components. As the frequency band increases from 3.5GHz to 14GHz, the density of the antenna array increases, the beam directivity increases, and combined with the improvement in SNR, weak multipath signals that were previously masked by noise are more effectively identified and utilized. This progress brings the intersection of the LoS and NLoS capacity distribution function (CDF) curves forward, indicating the performance balance point. In both LoS and NLoS scenarios, the increase in data rates exceeds expectations, reaching more than twice the expected rate and at least 40% improvement, demonstrating the significant effectiveness of the system.

[0128] For higher frequencies, Figure 5 and Figure 6 Several relevant data results are shown: First, the maximum achievable data rates in the 39 GHz and 132 GHz bands are 80 Gbps and 200 Gbps, respectively. Second, under NLoS conditions, increasing the number of subarrays leads to an increase in data rate, and the CDF curve shifts to the right. In addition, when all subarrays are under NLoS conditions, the rate CDF curve narrows and moves to the right, indicating that the maximum achievable data rate for all users has been improved, resulting in better rate consistency for users. Possible reasons for these phenomena include:

[0129] (1) The high frequency band provides ultra-wide bandwidth and precise beamforming capabilities.

[0130] (2) Distributed XL-MIMO subarrays send signals in multiple directions and receive signals from different angles, naturally reducing the risk of complete signal blockage and increasing the chance of capturing an effective transmission path.

[0131] (3) As NLoS gradually becomes dominant, the combination of NLoS and distributed XL-MIMO improves system reliability and achievable data rate by increasing the channel rank and signal strength.

[0132] This scheme not only demonstrates the data indicators that support wireless XR communication technology, but also provides an important theoretical basis for future research. Based on the specific communication requirements in different wireless XR scenarios, researchers can explore how to optimize the number and size of antennas, select the most suitable antenna type (such as directional antenna or omnidirectional antenna), and arrange the antenna architecture reasonably to enhance signal coverage and quality. The focus of network infrastructure design is to strategically select frequency bands so that their propagation characteristics match the specific needs of urban and suburban environments. The 3.5GHz and 14GHz bands are well suited for widespread urban and suburban deployments due to their excellent penetration and wide coverage. These bands are the core of commercial mobile communications, and the performance of the system in real-world mobile networks can be effectively evaluated through multi-user testing. In contrast, the 39GHz and 132GHz bands are reserved for advanced wireless XR applications (such as fixed wireless access and specific industrial uses), providing insights into the best technical performance and potential under ideal conditions. In addition, our results help select the most suitable frequency bands based on network requirements and environmental factors. This will promote the improvement of infrastructure deployment strategies, including optimizing cell site layout to improve signal coverage and quality, especially in highly dense and demanding XR scenarios.

[0133] In addition, as a potential trend in the future, this proposal proposes the problems that future researchers may face.

[0134] (1) Characterizing near-field channels: XL-MIMO systems extend the near-field region and introduce spatial nonstationarity, complicating the accurate characterization of channel behavior. To date, only a few studies have investigated near-field channel measurements involving extremely large arrays. Therefore, effective channel measurement methods are needed to characterize near-field channels in the real world.

[0135] (2) Design low-cost and simple hardware: The complexity and high cost of XL-MIMO hardware require the development of innovative methods to design low-complexity transmitter architectures and stable hardware designs. Designing multiple subarrays may be a good solution. In addition, it is crucial to design compact and small XR headset antennas that meet data rate requirements without compromising performance.

[0136] (3) Computational and load challenges: The inherent high dimensionality of centralized and distributed XL-MIMO configurations poses huge computational and load challenges. Distributed learning may be a viable strategy to effectively manage these complexities.

[0137] The embodiments of the present invention provide an advanced XL-MIMO design method and system for enhancing wireless extended reality communications, and propose an advanced antenna system designed to meet the high-speed requirements of wireless XR, covering multiple frequency bands, using the 3GPP standard channel model and the BUPT sub-terahertz channel model, and analyzing the performance of the system in urban micro-cell scenarios under mixed line-of-sight and non-line-of-sight conditions, using hybrid beamforming and zero-forcing equalization methods. Numerical results show that the proposed system consistently exceeds the basic data rate requirements of wireless XR communications in all frequency bands, ensuring a smooth and immersive experience. The present invention provides important insights into the design of advanced antenna systems to support wireless XR communication rates, especially in terms of selecting appropriate architectures and frequency bands to achieve more efficient and stable communication effects.

[0138] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0139] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. An advanced XL-MIMO design method for enhancing wireless extended reality communications, characterized in that: include: Step S1: Select the frequency band required for the design and determine the system parameters; Step S2: designing a centimeter wave frequency band centralized mMIMO system according to the parameters, the system comprising a base station BS and a plurality of multi-user MUs, wherein the base station adopts hybrid beamforming and uses zero-forcing equalization technology for digital beamforming; Step S3: designing a distributed XL-MIMO system in millimeter wave and sub-terahertz frequency bands according to the parameters; Step S4: Establish a channel model, obtain 3GPP and BUPT channel data and verify data accuracy; Step S5: Perform simulation in the urban microcell UMi scenario; Step S6: According to the simulation results, obtain the maximum achievable data rate in the extended reality XR scenario.

2. The advanced XL-MIMO design method for enhancing wireless extended reality communication according to claim 1, characterized in that: The step S2 includes: maintaining beam separation between users through sector division, the base station and user antennas both use UPA antennas, and the antenna spacing is half a wavelength.

3. The advanced XL-MIMO design method for enhancing wireless extended reality communication according to claim 1, characterized in that: In step S2, the channel capacity is maximized by combining hybrid beamforming and zero-forcing equalization technology, including: In a multi-user system, the zero-forcing equalization technology is used to prevent the signal received by the receiving end from being interfered by other user signals, that is, to eliminate the interference between users. The specific optimization process is calculated by W ZF , W ZF is the optimized beamforming matrix: W ZF =(H T H) -1 H H Among them, H H represents the conjugate transpose of the channel matrix; (H T H) -1 It is the pseudo-inverse of the channel matrix, ensuring that the receiving end can completely eliminate interference and achieve optimal data transmission effect; Hybrid beamforming combines traditional digital beamforming and RF beamforming, allowing the system to be optimized in hardware and reduce the computational burden. The introduction of hybrid beamforming reduces hardware complexity and optimizes performance: IN HB =In RF IN ZF W RF represents the RF part beamforming matrix; W ZF Represents the baseband part beamforming matrix, which processes the baseband signal and further adjusts the beam.

4. The advanced XL-MIMO design method for enhancing wireless extended reality communication according to claim 1, characterized in that: In step S3, a single-cell, single-user millimeter wave or sub-terahertz system uses four distributed XL-MIMO sub-arrays based on uniform planar arrays (UPA), and each sub-array is located at a symmetrical edge of the cell.

5. The advanced XL-MIMO design method for enhancing wireless extended reality communication according to claim 1, characterized in that: The step S5 comprises: performing simulation in a scenario of an urban microcell UMi, using a circular cell, which complies with the cell spacing in the 3GPP standard; In a multi-user centralized array system, thousands of channel realizations at random user locations are performed, taking into account the line-of-sight LoS and non-line-of-sight NLoS states between different arrays and users, different signal-to-noise ratio (SNR) values, and user antenna configurations. Thousands of channel realizations cover all frequency bands.

6. An advanced XL-MIMO design system for enhanced wireless extended reality communications, characterized in that: include: Module M1: Select the frequency band required for the design and determine the system parameters; Module M2: Design a centimeter wave band centralized mMIMO system according to the parameters. The system includes a base station BS and multiple multi-user MUs. The base station adopts hybrid beamforming and uses zero-forcing equalization technology for digital beamforming. Module M3: Design of distributed XL-MIMO systems in millimeter wave and sub-terahertz frequency bands according to parameters; Module M4: Establish channel model, obtain 3GPP and BUPT channel data and verify data accuracy; Module M5: Simulation in the urban micro-cell UMi scenario; Module M6: Based on the simulation results, obtain the maximum achievable data rate in the extended reality XR scenario.

7. The advanced XL-MIMO design system for enhancing wireless extended reality communications according to claim 6, characterized in that The module M2 includes: maintaining beam separation between users through sector division, base station and user antennas both use UPA antennas, and the antenna spacing is half a wavelength.

8. The advanced XL-MIMO design system for enhancing wireless extended reality communications according to claim 6, characterized in that In the module M2, the channel capacity is maximized by combining hybrid beamforming and zero-forcing equalization technology, including: In a multi-user system, the zero-forcing equalization technology is used to prevent the signal received by the receiving end from being interfered by other user signals, that is, to eliminate the interference between users. The specific optimization process is calculated by W ZF , W ZF is the optimized beamforming matrix: W ZF =(H T H) -1 H H Among them, H H represents the conjugate transpose of the channel matrix; (H T H) -1 It is the pseudo-inverse of the channel matrix, ensuring that the receiving end can completely eliminate interference and achieve optimal data transmission effect; Hybrid beamforming combines traditional digital beamforming and RF beamforming, allowing the system to be optimized in hardware and reduce the computational burden. The introduction of hybrid beamforming reduces hardware complexity and optimizes performance: IN HB =In RF IN ZF W RF represents the RF part beamforming matrix; W ZF Represents the baseband part beamforming matrix, which processes the baseband signal and further adjusts the beam.

9. The advanced XL-MIMO design system for enhancing wireless extended reality communications according to claim 6, characterized in that In the module M3, a single-cell, single-user millimeter wave or sub-terahertz system utilizes four distributed XL-MIMO sub-arrays based on uniform planar arrays (UPA), each of which is located at a symmetrical edge of the cell.

10. The advanced XL-MIMO design system for enhancing wireless extended reality communications according to claim 6, characterized in that The module M5 includes: simulation in the urban microcell UMi scenario, using circular cells, in accordance with the cell spacing in the 3GPP standard; In a multi-user centralized array system, thousands of channel realizations at random user locations are performed, taking into account the line-of-sight LoS and non-line-of-sight NLoS states between different arrays and users, different signal-to-noise ratio (SNR) values, and user antenna configurations. Thousands of channel realizations cover all frequency bands.

Images