A 6G distributed tri-polarization MIMO network parameter configuration method

Abstract

The application discloses a 6G distributed tri-polarization MIMO network parameter configuration method, and belongs to the technical field of wireless communication network optimization. The method unifies node deployment parameters, array structure parameters, tri-polarization port parameters and propagation mode parameters into the same candidate configuration and evaluation process; according to path loss, large-scale and small-scale propagation parameters, polarization impact, differential directional diagram response and near-far field propagation response, the overall network equivalent channel matrix corresponding to the candidate scheme is constructed; then, the candidate scheme is screened based on capacity, effective rank, condition number and received power, and a recommended network parameter configuration scheme is output. The method can coordinate the relationship between spatial deployment, polarization structure and propagation mode under the same framework, and improve the matching of the parameter configuration result and the actual propagation condition.

Description

Technical Field

[0001] This invention relates to the field of wireless communication and network optimization technology, and in particular to a parameter configuration method for a 6G distributed tri-polarized MIMO network. Specifically, it belongs to a parameter configuration method for the joint design of distributed multiple-input multiple-output networks, tri-polarized antenna arrays, and spatial channel evaluation. Background Technology

[0002] As sixth-generation mobile communication systems evolve towards higher spectral efficiency, wider-area cooperative coverage, ultra-large-scale connectivity, and high reliability with low latency, distributed multiple-input multiple-output (MIMO) networks are gradually becoming an important technological path to improve system capacity, coverage balance, and link stability. Compared with centralized arrays, distributed MIMO, by deploying multiple access nodes in different spatial locations, can achieve stronger macroscopic spatial diversity and path decorrelation capabilities, thereby improving edge user performance and overall system throughput in complex propagation environments.

[0003] Meanwhile, polarization dimension has become an important means to improve the performance of multi-antenna systems. Traditional single-polarized and dual-polarized antennas can provide a certain port expansion capability within a limited space, but their performance improvement is limited in scenarios with changes in user attitude, incident angle, enhanced multipath scattering, and high spatial correlation. Tri-polarized antennas, by setting three approximately orthogonal polarization ports at the same array location, can provide richer polarization response capabilities within a limited array aperture, and therefore have application potential in 6G multi-dimensional multiplexing and highly integrated array designs.

[0004] However, the performance gains of tri-polarized MIMO networks do not increase linearly with the number of ports. Their actual performance is influenced by a combination of factors, including the deployment location of distributed nodes, the number of nodes, array size, port orientation configuration, propagation environment, polarization coupling, pattern characteristics, and near-field or far-field propagation mode. For distributed networks, the decorrelation capability resulting from spatial location differences is intricately coupled with the polarization dimension gains from tri-polarized ports. Without a unified parameter configuration mechanism, it is difficult to reasonably coordinate distributed node parameters and tri-polarized array parameters under different deployment conditions, thus hindering the achievement of configuration results that balance capacity, effective rank, condition number, and received power.

[0005] In existing technologies, one type of approach primarily focuses on node deployment optimization or link performance analysis for single-polarization or dual-polarization distributed MIMO networks; the other type focuses more on tri-polarization channel modeling, polarization projection relationship construction, and performance evaluation. While these methods have studied distributed deployment or tri-polarization structures respectively, they typically lack a unified parameter configuration process for 6G distributed tri-polarization MIMO networks, making it difficult to establish a collaborative decision-making mechanism among node deployment, array structure, polarization mode, and propagation mode. Therefore, there is an urgent need to provide a parameter configuration method for 6G distributed tri-polarization MIMO networks, so as to output an adapted network parameter configuration scheme according to the target scenario and performance requirements. Summary of the Invention

[0006] The purpose of this invention is to provide a 6G distributed tripolar MIMO network parameter configuration method to solve the problem that the existing technology lacks a unified and coordinated configuration mechanism for distributed node deployment parameters, tripolar port parameters, array structure parameters, and propagation mode parameters, thereby enabling the output of network parameter configuration schemes adapted to different scenarios according to preset performance targets.

[0007] In this invention, the first The positions of the distributed nodes are denoted as follows: User location is recorded as , No. The propagation distance between a distributed node and a user is denoted as . , No. The path loss corresponding to each distributed node is denoted as . , No. The equivalent channel matrix corresponding to each distributed node is denoted as . The equivalent channel matrix of the overall distributed network is denoted as... Meanwhile, network performance metrics include channel capacity, effective rank, condition number, and received power. The final output of the optimal configuration includes the optimal number of nodes. Optimal node position The optimal array size parameters, optimal tripolar port direction parameters, and optimal propagation mode parameters.

[0008] In one embodiment, the method includes the following steps:

[0009] Step 200 is used to obtain the basic scenario parameters of the 6G distributed tri-polarization MIMO network to be configured. In this step, the obtained scenario parameters include at least the carrier frequency. speed of light User location Distributed base station candidate node locations Base station height User height Parameters include the candidate range for the number of nodes, the candidate range for the array size, the horizontal spacing between array elements, the vertical spacing between array elements, the polarization mode, the scene type, and the link status.

[0010] Among them, the The location of each distributed node It can be represented in three-dimensional coordinate form: User location It can be represented as: Step 200 completes the collection of basic input information required for network configuration, ensuring that subsequent node deployment, array construction, polarization response construction, and propagation mode determination are all based on a unified scenario.

[0011] Step 210, used according to the first Distributed node locations and user location Calculate the geometric relationship between the node and the user. In this step, at least the [number]th [node] is calculated. Two-dimensional distance between a node and a user and three-dimensional distance Among them, three-dimensional distance Used for path loss assessment, near-field and far-field propagation mode determination, and wavefront propagation relationship construction; two-dimensional distance. This step is used for deployment fairness comparison, scene-level geometric constraints, and relative position analysis between nodes. It clarifies the propagation geometry under different candidate node location configurations, providing input for subsequent path loss and channel response evaluation.

[0012] Step 220 is used to determine the network scenario type and link status based on system input or preset rules. In this step, the scenario type may include outdoor macrocell scenario, outdoor microcell scenario, indoor hotspot scenario, or other preset 6G propagation scenario; the link status may include line-of-sight link status and non-line-of-sight link status. Different scenario types and link statuses correspond to different path loss characteristics, large-scale statistical parameters, small-scale multipath distribution patterns, and polarization coupling characteristics.

[0013] Step 230 is used to determine the propagation mode parameters based on the relationship between the node array aperture and the propagation distance. In this step, for the first... For each distributed node, the corresponding array aperture is first determined based on its array size and element spacing. Then, the near-field and far-field determination thresholds are determined based on the relationship between the carrier wavelength and the array aperture. When the first The propagation distance between each node and the user Less than or equal to the threshold At that time, the first Each node adopts a near-field propagation mode; when Greater than the threshold At that time, the first Each node adopts a far-field propagation mode. Through step 230, the present invention separates the near-field and far-field propagation modes from the traditional background conditions and makes them explicit options in the parameter configuration process, thereby enabling subsequent candidate configurations to simultaneously adapt to large-aperture tri-polarized arrays and medium-short distance 6G link scenarios.

[0014] Step 300 involves constructing candidate configuration parameters for the distributed tripolar MIMO network based on the scenario parameters and propagation constraints obtained in steps 200 to 230. In this step, the candidate configuration parameters include at least the number of nodes. Node location The parameters include array size, horizontal element spacing, vertical element spacing, tri-polarization port direction vectors, and propagation mode parameters. By combining these parameters, multiple candidate network configuration schemes can be constructed to compare the performance differences of different configurations within a unified evaluation framework.

[0015] Unlike existing configuration schemes that only target node locations or array structures, this invention incorporates distributed deployment parameters and tri-polarized port parameters into the same candidate parameter space in step 300, thereby enabling the spatial dimension and polarization dimension to participate in network configuration collaboratively.

[0016] Step 310 is used to construct the parameters related to distributed node deployment. In this step, the node deployment parameters include at least the number of candidate nodes. and the position of each node By changing the number and spatial location of nodes, different distributed deployment structures can be formed. Different deployment structures will affect the macroscopic spatial diversity capability, the level of decorrelation between nodes, the total received power distribution, and the modal structure of the equivalent channel. Through step 310, the configuration space can simultaneously consider centralized deployment with few nodes, distributed deployment with many nodes, and the transitional form between the two, thereby avoiding limiting the system to a single architecture.

[0017] Step 320 is used to construct the array structure parameters corresponding to each distributed node. In this step, the array structure parameters include at least the first... Number of horizontal array elements of each node Vertical array elements Horizontal spacing of array elements Vertical spacing between array elements By combining different array sizes and element spacings, array structures with varying apertures, spatial resolutions, and wavefront sensitivities can be formed. The array structure parameters not only affect the first... The array gain and spatial resolution of each node also affect the near-field and far-field mode determination results, and therefore are considered important configuration objects rather than fixed design conditions in this invention.

[0018] Step 330 is used to construct the tri-polarization port configuration parameters. In this step, the... The direction vector of the tripolarized port of a distributed node can be denoted as: , and The three port direction vectors are preferably approximately orthogonal direction vectors, corresponding to the three physical ports in the tri-polarization array. Under different candidate configuration schemes, the port direction relationship, port orientation, and port arrangement can be different, thus forming different tri-polarization configuration modes. The core of this step is that the three ports are not simply regarded as completely equivalent ports, but their direction relationship is explicitly introduced as a configurable parameter, so that the response differences of different tri-polarization ports on the local polarization plane can be reflected in the subsequent channel response evaluation.

[0019] Step 340 is used to construct propagation and statistical constraint parameters that match the target scenario. In this step, the propagation and statistical constraint parameters include at least one or more of the following: Ricean factor, delay spread, departure angle spread, arrival angle spread, cluster number range, multipath power attenuation characteristics, and path loss constraints.

[0020] Step 400 is used to generate multiple candidate network configuration schemes based on the candidate configuration parameters constructed in step 300, and to evaluate the equivalent channel response of each candidate network configuration scheme. In this step, for each group of candidate node deployment parameters, array structure parameters, tri-polarization port parameters, and propagation mode parameters, a corresponding network configuration scheme is constructed, and the equivalent channel response under that scheme is calculated. For the first... A distributed node, whose equivalent channel matrix is ​​denoted as . The equivalent channel matrix of the entire network is denoted as .

[0021] Step 410 is used to calculate the first step based on scenario type, link status, propagation distance, and node deployment relationship. Path loss for each distributed node and large-scale propagation parameters. Path loss. Used to describe the The average attenuation level of the link from each node to the user, and the large-scale propagation parameters are used to describe statistical characteristics such as shadow fading, Ricean factor, delay spread, and angular spread. Different candidate node locations, different user locations, and different link states will all cause changes in path loss and large-scale propagation parameters, thereby affecting the overall performance of the corresponding candidate configuration schemes.

[0022] Step 420 is used to generate the multipath cluster structure and small-scale propagation parameters corresponding to the candidate configuration scheme based on the large-scale propagation parameters. In this step, the small-scale propagation parameters include at least cluster delay, cluster power, cluster center angle, intra-cluster ray direction parameters, and polarization coupling related parameters.

[0023] Step 430 is used to construct the polarization projection response of the tri-polarized port based on the relationship between the propagation path direction and the tri-polarized port direction vector. In this step, for each propagation path, the local polarization plane corresponding to the path is first determined, and then the polarization projection response is constructed based on the port direction vector. , and The corresponding port polarization response is constructed by projecting the relationship onto the local polarization plane. Since the local polarization planes are different for different propagation paths, the projection results of the same tri-polarized port will also be different on different paths.

[0024] Step 440 applies differentiated pattern weights to the different tri-polarized ports. In this step, different physical ports can have different pattern response characteristics. For example, at least two ports can have patch-type pattern responses, and the other port can have a probe-type pattern response. By applying different pattern weights to different ports, differences in main lobe shape, backsuppression, and spatial coverage characteristics can be distinguished. This approach does not simply treat the three ports in the tri-polarized array as three equivalent signal channels, but explicitly incorporates their physical radiation characteristics into the configuration evaluation process, making the final parameter configuration result closer to the actual array structure.

[0025] Step 450 is used to construct the corresponding propagation response based on the propagation mode determined in step 230. Since the phase difference and wavefront curvature characteristics between array elements differ in the near and far fields, different propagation modes significantly affect the equivalent channel structure corresponding to the candidate configuration scheme. In this step, when the... When the nth node adopts the far-field propagation mode, the propagation response is constructed according to the characteristics of the far-field plane wave; when the nth node adopts the far-field propagation mode, the propagation response is constructed according to the characteristics of the far-field plane wave; When each node adopts the near-field propagation mode, the propagation response is constructed according to the characteristics of near-field spherical waves.

[0026] Step 460 is used to synthesize path loss, large-scale propagation parameters, small-scale propagation parameters, tri-polarized port polarization projection response, radiation pattern response, and propagation mode response to generate the first... Equivalent channel matrix of each node Furthermore, the equivalent channel matrix of the overall network is constructed. .

[0027] Among them, the overall network equivalent channel matrix It is composed of sub-channel matrices of multiple distributed nodes, thus reflecting both the decorrelation capability brought by spatial distributed deployment and the polarization dimension benefits brought by the tripolar port.

[0028] Step 500 is used to determine the overall network equivalent channel matrix obtained in step 460. Calculate the performance metrics corresponding to the candidate network configuration schemes. Performance metrics should include at least channel capacity and effective rank. Condition number and received power One or more of the following: Channel capacity is used to characterize the transmission capability of the candidate configuration scheme; effective rank is used to characterize the spatial multiplexing capability and energy distribution balance of the candidate configuration scheme; condition number is used to characterize the channel stability and multi-stream transmission adaptability of the candidate configuration scheme; and received power is used to characterize the total link energy gain of the candidate configuration scheme.

[0029] Step 510 is used to calculate individual performance metrics for candidate configuration schemes. In this step, any one of the following metrics can be calculated based on the target requirements: channel capacity, effective rank, condition number, or received power, for single-target parameter configuration scenarios. For example, in scenarios pursuing high throughput, the capacity metric can be prioritized; in scenarios focusing on spatial multiplexing capabilities, the effective rank metric can be prioritized.

[0030] Step 520 combines multiple performance indicators to form a joint evaluation result. In this step, each indicator can collectively constitute a comprehensive performance characterization of the candidate configuration scheme. Compared to making configuration decisions based on only a single indicator, the joint evaluation of multiple indicators can more comprehensively reflect the overall performance of the distributed tripolar MIMO network in terms of transmission capacity, modal equalization, energy distribution, and stability.

[0031] Step 600 determines the optimal configuration of the target network based on the performance metrics obtained in step 500. In this step, all candidate configuration schemes can be compared, ranked, filtered, or optimized according to a preset objective function or preset constraints to obtain the optimal number of nodes. Optimal node position The optimal array structure parameters, optimal tripolar port direction parameters, and optimal propagation mode parameters.

[0032] Step 610 is used to filter the optimal configuration result according to a single objective rule. In this step, the optimal configuration result can be determined based on any one of the following rules: maximum capacity, maximum effective rank, minimum condition number, or maximum received power. For example, when the system prioritizes throughput improvement, maximum capacity can be used as the filtering criterion; when the system prioritizes link stability, minimum condition number can be used as the filtering criterion.

[0033] Step 620 is used to filter the optimal configuration results according to multi-objective joint rules. In this step, capacity, effective rank, condition number, and received power can be jointly evaluated, and candidate configurations can be sorted and filtered according to the comprehensive objectives. Compared with single-objective filtering, step 620 is more suitable for 6G distributed tripolar network configuration scenarios that require balancing multiple performance requirements.

[0034] Step 630 is used to determine the optimal result among candidate configuration schemes that meet preset constraints. In this step, a receive power threshold, a condition number threshold, a node number limit, an array size limit, or a propagation mode limit can be set first, and then the optimal result can be determined from the candidate configurations that meet the constraints.

[0035] Step 700 outputs the final network parameter configuration scheme. In this step, the output should include at least the optimal number of nodes. Optimal node position The optimal array size parameter, optimal element spacing parameter, optimal tri-polarization port direction parameter, optimal propagation mode parameter, and one or more of the corresponding performance results such as capacity, effective rank, condition number, and received power.

[0036] Beneficial effects

[0037] This invention integrates distributed node deployment parameters, array structure parameters, tri-polarization port parameters, and near-field and far-field propagation mode parameters into a single parameter configuration process, overcoming the problem of separation between spatial deployment optimization and polarization structure optimization in existing technologies.

[0038] This invention introduces tripolar port direction vectors and differentiated pattern responses, which can more accurately reflect the response differences of different tripolar ports under real propagation conditions, and improve the consistency between parameter configuration results and actual array structures.

[0039] This invention explicitly incorporates propagation mode parameters into the configuration process, making the same method applicable to both conventional far-field distributed MIMO scenarios and near-field tripolar MIMO scenarios with large aperture arrays and short-to-medium distance links, thereby expanding the applicability of the method.

[0040] The optimal configuration results output by this invention include the number of nodes, node locations, array parameters, port direction parameters, and propagation mode parameters. It has clear engineering feasibility and can serve the deployment planning and system design of 6G distributed tripolar MIMO networks. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the overall process of a 6G distributed tripolar MIMO network parameter configuration method according to the present invention.

[0042] Figure 2 This is a schematic diagram of the modeling of the differential orientation pattern of the three polarization ports in this invention.

[0043] Figure 3 This is a performance comparison chart showing the number of nodes K traversal in this embodiment of the invention.

[0044] Figure 4 This is a performance comparison diagram of differentiated and isomorphic radiation patterns in an embodiment of the present invention.

[0045] Figure 5 This is a performance comparison chart showing the switching between near-field mode and far-field mode in an embodiment of the present invention.

[0046] Figure 6 This is a graph showing the comprehensive score of candidate configurations and the output results of the final recommended configuration in an embodiment of the present invention. Detailed Implementation

[0047] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the following embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the present invention. Without departing from the concept of the present invention, those skilled in the art can adjust or replace the parameter forms, deployment methods, evaluation index weights, and candidate configuration generation methods, all of which should fall within the scope of protection of the present invention.

[0048] This invention proposes a 6G distributed tri-polarized MIMO network parameter configuration method, addressing the network deployment optimization problem in distributed multi-node, multi-polarized port, and near-far field hybrid propagation environments. It integrates node quantity parameters, node location parameters, array structure parameters, tri-polarized port parameters, and propagation mode parameters into a unified configuration process, and outputs recommended configuration results for the target scenario based on the constructed channel performance indicators. The overall process can be found in [link to relevant documentation]. Figure 1 .

[0049] Example 1

[0050] This embodiment illustrates the basic configuration process of the method of the present invention, namely, under the conditions of a given propagation scenario, array parameters and a set of candidate node numbers, channel construction, performance evaluation and recommendation output are performed on different candidate configurations.

[0051] Step 200 is used to obtain the basic scenario parameters of the 6G distributed tripolar MIMO network to be configured.

[0052] In this step, the basic input information required for network configuration is obtained. These basic scenario parameters include at least the carrier frequency. speed of light User location Distributed base station candidate node locations Base station height User height Candidate range for number of nodes, candidate range for array size, and horizontal spacing between array elements. Vertical spacing of array elements Parameters such as polarization mode, scene type, and link status. Among them, the first... The location of each distributed node It can be represented as: User location It can be represented as: Step 200 completes the unified collection of basic scenario information required for parameter configuration, ensuring that subsequent node deployment, array construction, port polarization response construction, and propagation mode determination are all based on the same scenario constraints.

[0053] Step 210, used according to the first Distributed node locations and user location Calculate the geometric relationship between the node and the user. In this step, calculate the first... Two-dimensional distance between a node and a user and three-dimensional distance Among them, three-dimensional distance It can be represented as: The geometric relationships obtained in step 210 are used for subsequent path loss assessment, near-field and far-field propagation mode determination, horizontal deployment constraint construction, and node relative position analysis. In a preferred embodiment, to reduce the impact of differences in propagation distances between different candidate nodes and users on the comparison results, equidistant deployment constraints can be imposed on the candidate nodes. If the target three-dimensional link distance is... The corresponding horizontal deployment radius can then be expressed as: Based on this radius, a set of candidate node positions that satisfy the equidistant condition can be constructed to highlight the impact of the number of nodes, array size, and polarization structure parameters on system performance during the comparison of candidate schemes.

[0054] Step 220 is used to determine the network scenario type and link status based on system input or preset rules. In this step, the network scenario type and link status are determined according to the target application environment. Scenario types may include outdoor macrocell scenarios, outdoor microcell scenarios, indoor hotspot scenarios, or other preset 6G propagation scenarios; link status may include line-of-sight link status and non-line-of-sight link status. Different scenario types and link statuses correspond to different path loss characteristics, large-scale statistical parameters, small-scale multipath distribution patterns, and polarization coupling characteristics.

[0055] Step 230 is used to determine the propagation mode parameters based on the relationship between the node array aperture and the propagation distance. In this step, for the first... Each distributed node determines the array aperture based on its array size and element spacing. Combined with carrier wavelength Determine the near-field and far-field discrimination thresholds In one embodiment, the determination threshold can be expressed as: When the first The propagation distance between each node and the user Less than or equal to the threshold When the propagation mode corresponding to the node is determined to be near-field mode; when Greater than the threshold When the propagation mode corresponding to the node is determined to be the far-field mode, step 230 of this invention uses the near-field mode and the far-field mode as explicit parameters in the candidate configuration process, rather than fixing them as background propagation assumptions. This allows subsequent candidate configuration schemes to be adapted to both large-aperture tri-polarized array scenarios and medium-short distance 6G link scenarios.

[0056] Step 300 involves constructing candidate configuration parameters for the distributed tripolar MIMO network based on the scene parameters and propagation constraints obtained in steps 200 to 230. In this step, a set of candidate configuration parameters to be compared is constructed based on the basic scene parameters, geometric relationships, and propagation mode determination results. The candidate configuration parameters include at least the number of nodes. Node location Array size parameters, horizontal spacing of array elements Vertical spacing of array elements The parameters include the tri-polarization port direction vector and propagation mode parameters. By combining these parameters, multiple candidate network configuration schemes are formed to compare the performance differences of different configuration methods under a unified evaluation framework. Compared with existing schemes that only optimize node locations or array structures locally, this invention incorporates both distributed deployment parameters and tri-polarization port parameters into the candidate parameter space in step 300, thereby achieving coordinated configuration of spatial and polarization dimensions.

[0057] Step 310 is used to construct the parameters related to distributed node deployment. In this step, the node deployment parameters include at least the number of candidate nodes. and the location of each node Different distributed deployment structures can be formed by changing the number and spatial location of nodes. Different deployment structures will affect spatial diversity capability, the degree of decorrelation between nodes, the total received power distribution, and the modal structure of the overall equivalent channel. Therefore, step 310 is used to simultaneously cover centralized deployment with few nodes, distributed deployment with many nodes, and transitional deployment forms between the two within the candidate parameter space, avoiding pre-limiting the network structure to a single architecture form. The array structure parameters not only affect the array gain and spatial resolution of the nodes, but also change the propagation mode determination result in step 230 through the array aperture. Therefore, in this invention, they are important parameters that need to be actively configured, rather than fixed design conditions.

[0058] Step 330 is used to construct the tri-polarization port configuration parameters. In this step, the... The three-polarized port direction vectors of each distributed node can be denoted as: , , The three port direction vectors are preferably approximately orthogonal direction vectors, corresponding to the three physical ports in the tri-polarization array. Under different candidate configuration schemes, the port direction relationship, port orientation, and port arrangement can be different, thus forming different tri-polarization configuration modes. The key to this step is to introduce the direction relationship of the tri-polarization ports as an explicit configurable parameter into the candidate parameter space, so that the response differences of different ports on the local polarization plane can be preserved in subsequent channel evaluation.

[0059] Step 340 is used to construct propagation and statistical constraint parameters that match the target scenario. In this step, the propagation and statistical constraint parameters include at least one or more of the following: Ricean factor, delay spread, departure angle spread, arrival angle spread, cluster number range, multipath power attenuation characteristics, and path loss constraints. Step 340 couples the geometry of the candidate configuration with the propagation statistics under the target scenario, ensuring that subsequent candidate scheme evaluations reflect not only the geometric differences of nodes and arrays, but also differences in propagation levels such as multipath distribution, angle spread, power attenuation, and polarization coupling.

[0060] Step 400 is used to generate multiple candidate network configuration schemes based on the candidate configuration parameters constructed in step 300, and to evaluate the equivalent channel response of each candidate network configuration scheme. In this step, for each group of candidate node deployment parameters, array structure parameters, tri-polarization port parameters, and propagation mode parameters, a corresponding network configuration scheme is constructed, and the equivalent channel response under that scheme is generated. For the first... A distributed node, whose equivalent channel matrix is ​​denoted as . The equivalent channel matrix of the entire network is denoted as .

[0061] Step 400 does not perform a posteriori analysis of a single fixed network structure, but rather constructs responses to different combinations of candidate parameter schemes in the candidate parameter space, thereby establishing the correspondence between "candidate parameters - equivalent channel - performance results".

[0062] Step 410 is used to calculate the first step based on scenario type, link status, propagation distance, and node deployment relationship. Path loss for each distributed node and large-scale propagation parameters. Path loss. Used to characterize the The average attenuation level of the link from each node to the user, and the large-scale propagation parameters are used to characterize statistical properties such as shadow fading, Ricean factor, delay spread, and angle spread. Since changes in the candidate node location, user location, and link state will all cause changes in path loss and statistical parameters, step 410 establishes discriminative average propagation constraints for different candidate configuration schemes.

[0063] Step 420 is used to generate the multipath cluster structure and small-scale propagation parameters corresponding to the candidate configuration scheme based on the large-scale propagation parameters. In this step, the small-scale propagation parameters include at least cluster delay, cluster power, cluster center angle, intra-cluster ray direction parameters, and polarization coupling related parameters.

[0064] Step 430 is used to construct the polarization projection response of the tri-polarized port based on the relationship between the propagation path direction and the tri-polarized port direction vector. In this step, for each propagation path, the local polarization plane corresponding to the path is first determined, and then the polarization projection response is constructed based on the port direction vector. , and The corresponding port polarization response is constructed by projecting the relationship onto the local polarization plane. Since the local polarization planes corresponding to different propagation paths are usually different, the projection results of the same tri-polarized port on different paths will also be different.

[0065] Step 440 applies differentiated pattern weighting to different tripolarized ports. In this step, different physical ports can correspond to different pattern response characteristics. For example, at least two ports adopt patch-type pattern responses, and the other port adopts a probe-type pattern response. In this example, the patch-type port is preferably a directional radiation element, with a concentrated main lobe, significant forward radiation, and weak backward radiation. For example, a single main lobe directional radiation model defined by the 3GPP standard can be used: Vertical plane attenuation:

[0066] （1）

[0067] Horizontal attenuation:

[0068] （2）

[0069] 3D pattern gain:

[0070] （3）

[0071] Linear amplitude conversion:

[0072] （4）

[0073] Probe-type ports preferably have different radiation pattern envelope characteristics than patch-type ports, exhibiting bimodal response, wide coverage, or significant energy concentration in a specific direction. Their linear amplitude gain... The calculation formula combination is: horizontal plane bimodal attenuation:

[0074] （5）

[0075] Vertical plane attenuation:

[0076] （6）

[0077] 3D pattern gain:

[0078] （7）

[0079] Considering the backward attenuation factor introduced by the backplate shading for:

[0080] （8）

[0081] Linear amplitude conversion:

[0082] （9）

[0083] The three ports are not identical in physical orientation and radiation characteristics, thus forming a tri-polarized heterogeneous port combination. This step constructs the tri-polarized antenna beamform as shown below. Figure 2 As shown.

[0084] Step 450 is used to construct the corresponding propagation response based on the propagation mode determined in step 230. Since near-field propagation and far-field propagation differ in wavefront curvature and inter-element phase difference construction methods, the different propagation modes will significantly affect the equivalent channel structure corresponding to the candidate scheme. In this step, when the... When the nth node adopts the far-field mode, the propagation response is constructed according to the characteristics of plane wave propagation; when the nth node adopts the far-field mode, the propagation response is constructed according to the characteristics of plane wave propagation; When each node adopts near-field mode, the propagation response is constructed according to the characteristics of spherical wave propagation.

[0085] In one implementation, if the first The receiving port and the first The propagation distance of a transmitter port along a certain propagation path is denoted as . Then the phase term in the near-field mode can be expressed as: In step 450, the propagation mode parameters are substantially incorporated into the candidate scheme equivalent response generation process. The near-field and far-field mode switching results corresponding to this step can be found in [reference needed]. Figure 5 .

[0086] Step 460 is used to synthesize path loss, large-scale propagation parameters, small-scale propagation parameters, tri-polarized port polarization projection response, radiation pattern response, and propagation mode response to generate the first... Equivalent channel matrix of each node Furthermore, the equivalent channel matrix of the overall network is constructed. Among them, the overall network equivalent channel matrix Composed of sub-channel matrices from multiple distributed nodes, it reflects both the spatial decorrelation capability brought about by distributed deployment and the polarization dimension gains introduced by the tri-polarized ports. Step 460 completes the mapping from the candidate parameter set to the overall network response structure.

[0087] Step 500 is used to calculate the performance indicators corresponding to the candidate network configuration schemes based on the overall network equivalent channel matrix obtained in step 460. In this step, the performance indicators include at least one or more of the following: channel capacity, effective rank, condition number, and received power. Channel capacity is used to characterize the transmission capability of the candidate scheme; effective rank is used to characterize spatial multiplexing capability and energy distribution balance; condition number is used to characterize channel stability and multi-stream transmission adaptability; and received power is used to characterize link energy gain.

[0088] Step 510 is used to calculate individual performance indicators for candidate configuration schemes. In this step, individual evaluation results based on capacity, effective rank, condition number, or received power can be generated according to the target requirements to suit single-target parameter configuration scenarios. For example, in a throughput-priority scenario, a capacity-oriented candidate scheme selection rule can be used; in a spatial reuse capability-priority scenario, an effective rank-oriented candidate scheme selection rule can be used.

[0089] Step 520 combines multiple performance indicators to form a joint evaluation result. In this step, the various performance indicators together constitute a comprehensive performance characterization of the candidate schemes. Compared to configuration decisions based on only a single performance indicator, multi-indicator joint evaluation can more comprehensively reflect the overall performance of distributed tripolar MIMO networks in terms of transmission capacity, modal equalization, stability, and energy gain. Using candidate configuration schemes with different numbers of nodes as comparison objects, the capacity, effective rank, condition number, and received power of each candidate scheme are statistically evaluated to obtain performance comparison results under different node counts, such as... Figure 3 As shown.

[0090] Step 600 determines the optimal configuration of the target network based on the performance metrics obtained in step 500. In this step, all candidate configuration schemes can be compared, ranked, filtered, or optimized according to a preset objective function or preset constraints to obtain the optimal number of nodes. Optimal node position The optimal array structure parameters, optimal tripolar port direction parameters, and optimal propagation mode parameters.

[0091] Step 610 is used to filter the optimal configuration result according to a single-objective rule. In this step, the optimal configuration result can be determined based on any one of the following rules: maximum capacity, maximum effective rank, minimum condition number, or maximum received power. This type of single-objective filtering method can be used when the system design objective has a clear single priority.

[0092] Step 620 is used to filter the optimal configuration result according to the multi-objective joint rule. The specific steps are the same as step 610.

[0093] Step 700 is used to output the final network parameter configuration scheme. In this step, the output results shall include at least one or more of the following performance results: optimal number of nodes, optimal node location, optimal array size parameter, optimal element spacing parameter, optimal tri-polarization port direction parameter, optimal propagation mode parameter, and corresponding capacity, effective rank, condition number, and received power.

[0094] Example 2

[0095] This embodiment is used to further illustrate the application of steps 440, 450 and 620 in the extended configuration scenario.

[0096] In this embodiment, by applying differentiated radiation pattern weights to different tripolar ports, the influence of port physical radiation differences on the candidate scheme response ranking after entering the configuration process is verified; at the same time, by evaluating candidate configurations for near-field and far-field modes respectively, the influence of propagation mode parameters independently participating in the configuration on the candidate scheme selection results is verified.

[0097] in, Figure 4 To illustrate: if different physical ports in a tripolar array are uniformly regarded as isomorphic pattern ports, the modal structure evaluation and stability evaluation of candidate schemes may deviate from the actual physical response; however, by distinguishing and modeling patch-type ports and probe-type ports, the comparison results of candidate schemes can be more consistent with the actual array radiation characteristics.

[0098] Figure 5This is to illustrate that when the array aperture increases or the link distance decreases, the equivalent channel structure and performance ranking of different candidate configurations may change after the propagation mode switches from far-field to near-field. Therefore, in scenarios adapted to large-aperture arrays or short-to-medium distance links, propagation mode parameters should be jointly evaluated along with the number of nodes, array structure, and tri-polarization port parameters.

[0099] Based on this, combined Figure 6 The comprehensive scoring results shown can be used to uniformly rank multiple candidate configuration schemes and output the final recommended network parameter scheme.

Claims

1. A method for configuring parameters in a 6G distributed tripolar MIMO network, characterized in that, include: Obtain basic scenario parameters for the network to be configured. These basic scenario parameters include at least carrier frequency, user location, candidate node locations of distributed base stations, candidate range of node quantity, candidate range of array size, horizontal spacing between array elements, vertical spacing between array elements, polarization mode, scenario type, and link status. Based on these basic scenario parameters, determine candidate configuration parameters. These candidate configuration parameters include at least node deployment parameters, array structure parameters, tri-polarization port parameters, and propagation mode parameters. Generate candidate network configuration schemes based on these candidate configuration parameters and construct the corresponding overall network equivalent channel matrix. Develop performance indicators corresponding to the candidate network configuration schemes based on the overall network equivalent channel matrix. Determine the optimal configuration result based on the performance indicators and output the final network parameter configuration scheme.

2. The method according to claim 1, characterized in that, The determination of the candidate configuration parameters includes combining the node number parameter, node spatial deployment parameter, array size parameter, tri-polarization port direction parameter, and propagation mode parameter into a unified candidate configuration set, so that the spatial deployment dimension, array structure dimension, polarization dimension, and propagation mode dimension jointly participate in the network parameter configuration.

3. The method according to claim 2, characterized in that, The propagation mode parameters are determined based on the relationship between the aperture of the distributed node array and the propagation distance from the node to the user, and are used as variable parameters in the candidate configuration set to participate in the generation of candidate network configuration schemes, so that the candidate network configuration schemes can be adapted to near-field propagation scenarios or far-field propagation scenarios.

4. The method according to claim 2, characterized in that, The array structure parameters include at least the number of horizontal array elements, the number of vertical array elements, the horizontal spacing between array elements, and the vertical spacing between array elements for each distributed node. Different array sizes and array element spacing combinations can form candidate array structures with different array apertures, different spatial resolutions, or different wavefront sensitivities.

5. The method according to claim 2, characterized in that, The three-polarization port parameters include three port direction vectors corresponding to each distributed node. These three port direction vectors are used to characterize the directional relationship between the three-polarization ports and participate in the subsequent equivalent channel response construction as polarization structure parameters in the candidate network configuration scheme.

6. The method according to claim 1, characterized in that, The construction of the corresponding overall network equivalent channel matrix includes constructing the polarization projection response of the three-polarized ports based on the relationship between the propagation path direction and the three port direction vectors, so that the differences in port response under different propagation path conditions are reflected in the equivalent channel response corresponding to the candidate network configuration scheme.

7. The method according to claim 1, characterized in that, The construction of the corresponding overall network equivalent channel matrix also includes applying differentiated pattern weighting to different tripolar ports. The differentiated pattern weighting includes at least patch pattern weighting or probe pattern weighting to distinguish the differences between different physical ports in terms of main lobe shape, backward suppression, or spatial coverage characteristics.

8. The method according to claim 1, characterized in that, The construction of the corresponding overall network equivalent channel matrix includes determining path loss and large-scale propagation parameters based on scenario type, link status, and node deployment relationship; generating multipath cluster structure and small-scale propagation parameters based on the large-scale propagation parameters; and combining polarization projection response, directional pattern response, and propagation mode response to generate the equivalent channel matrix of each distributed node and further construct the overall network equivalent channel matrix.

9. The method according to claim 1, characterized in that, The overall network equivalent channel matrix is ​​formed by combining the sub-channel matrices of multiple distributed nodes, so as to simultaneously reflect the spatial decorrelation characteristics brought about by the deployment of distributed nodes and the polarization dimension benefits brought about by the tripolar ports.

10. The method according to claim 1, characterized in that, The performance indicators include at least channel capacity, effective rank, condition number, or received power, and a single-objective evaluation result or a multi-indicator joint evaluation result is formed based on the performance indicators to compare, rank, or screen different candidate network configuration schemes.

11. The method according to claim 1, characterized in that, The optimal configuration result includes at least the optimal number of nodes, optimal node deployment parameters, optimal array structure parameters, optimal tripolar port parameters, or optimal propagation mode parameters, and the optimal configuration result is determined by single-target screening rules, multi-target joint screening rules, or screening rules that meet preset constraints.

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