A 6G cell-free network construction method and system for coal mine intelligentization

Abstract

This application relates to a method and system for constructing a 6G non-cellular network for intelligent coal mines. The method includes: constructing a prototype non-cellular network for coal mines based on a centralized processing and distributed access architecture, and optimizing the multi-AP collaborative transmission and clock synchronization process across the entire network to obtain an optimized non-cellular network prototype; configuring the basic network architecture and scenario deployment sub-schemes corresponding to the target scenario based on the target scenario type and the optimized non-cellular network prototype to obtain a configuration result for the target scenario; and using the configuration result of the target scenario to perform communication coverage and service carrying in the target area of ​​the coal mine, obtaining a high-reliability, low-latency communication result across the entire area. This application can eliminate handover and uneven coverage, adapt to the entire scenario, achieve low-latency, high-reliability communication in the mine, and balance performance and cost.

Description

Technical Field

[0001] This application relates to the field of wireless communication technology, and in particular to a method and system for constructing a 6G non-cellular network for intelligent coal mines. Background Technology

[0002] With the evolution of wireless communication towards 6G and intelligent industrial networks, the construction of intelligent coal mines places higher demands on the transmission rate, latency reliability, coverage continuity, and anti-interference capabilities of communication systems. The complex underground environment of coal mines presents multiple adverse factors, including narrow and winding roadways, dense metal equipment, high-speed movement of coal mining machines, and dust and water mist scattering. These factors lead to severe multipath fading, shadowing, electromagnetic interference, and roadway waveguide effects in wireless signal propagation. These channel distortion phenomena directly restrict the communication quality and service stability of services such as inspection robots, remote control of coal mining machines, and sensor data feedback in intelligent coal mine networks.

[0003] In existing technologies, there are two main types of methods for constructing wireless communication networks in coal mines: The first type is the traditional cellular networking method, which builds a coverage model based on macro base stations, micro base stations, and remote radio units. It achieves regional coverage through cell division and handover mechanisms, and can provide stable access services in specific fixed scenarios. The deployment scheme is also relatively mature. The second type is the distributed coverage method, which achieves enhanced regional coverage through leaky cables, distributed antennas, or fiber optic extension. It can support continuous coverage and anti-interference transmission. However, traditional cellular networking relies on cell boundaries and hard handover mechanisms. Frequent handovers when mobile devices move at high speeds can lead to large latency fluctuations and high packet loss rates. Furthermore, its cell architecture is difficult to adapt to the special environment of coal mines with narrow tunnels and dense equipment. In addition, distributed coverage methods require a large amount of cabling and relay equipment, which significantly increases hardware costs and maintenance expenses. In scenarios where intelligent coal mines have high requirements for low latency, high reliability, and high mobility, the complexity of cabling and the problem of cascading faults will greatly reduce the real-time performance and reliability of the network. At the same time, it is designed for a single scenario and cannot be applied to the construction of full coverage in multiple areas such as underground tunnels, intelligent fully mechanized mining faces, and transportation trunk lines. It is difficult to support cross-regional device-level linkage and link-level testing, and it is also insufficiently adapted to special fading effects, resulting in a large deviation between the network coverage results and the actual channel characteristics of coal mines.

[0004] Therefore, it is necessary to improve one or more of the problems existing in the above-mentioned related technical solutions.

[0005] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this disclosure is to provide a method and system for constructing a 6G non-cellular network for intelligent coal mines, thereby overcoming, to at least some extent, one or more problems caused by the limitations and defects of related technologies.

[0007] Firstly, this application provides a method for constructing a 6G non-cellular network for intelligent coal mines, comprising: A prototype of a non-cellular network for coal mines was constructed based on a centralized processing and distributed access architecture. The collaborative transmission and clock synchronization process of multiple access points across the network were optimized to obtain an optimized non-cellular network prototype. The non-cellular network prototype includes a central processing unit and mine explosion-proof wireless access points. Based on the target scenario type and the optimized non-cellular network prototype, the basic network architecture and scenario deployment sub-scheme corresponding to the target scenario are configured to obtain the configuration result for the target scenario; the target scenario type includes underground roadway scenario, intelligent fully mechanized mining face scenario or transportation trunk line scenario, and the scenario deployment sub-scheme includes distance vector optimal deployment unit, service coverage maximization deployment unit and business perception energy efficiency deployment unit; Based on the configuration results of the target scenario, communication coverage and service carrying are carried out in the target area of ​​the coal mine, resulting in a highly reliable and low-latency communication result across the entire area.

[0008] In one possible implementation, the step of constructing a cellular-free network prototype for coal mines based on a centralized processing and distributed access architecture includes: The signals received by multiple distributed APs are superimposed and converged to the central processing unit to obtain a function of the coordinated received signal; Based on the functional representation of the cooperative received signal, a user cooperative cluster service model is constructed.

[0009] In one possible implementation, after the step of constructing the user cooperative cluster service model based on the functional representation of the cooperative received signal, the method further includes: The prototype of the coal mine non-cellular network is constructed by superimposing the cooperative cluster random process with the line-of-sight path power parameter; the prototype of the coal mine non-cellular network includes a high-reliability direct path transmission model and a non-line-of-sight scattering transmission model.

[0010] In one possible implementation, the function of the cooperatively received signal is: in, To coordinate signal reception, For the channel response of the nth AP, For the transmitted signal of the nth AP, For noise, This represents the total number of APs; The user collaboration cluster service model is as follows: in, For signals synthesized by cooperative clusters, This is the first in-phase orthogonal component. The imaginary unit, This is the second in-phase orthogonal component. The number of APs serving the first service. As the first magnitude weight, For carrier frequency, For time variables, This is the first initial phase. For the number of APs serving the second service, As the second magnitude weight, This is the second initial phase.

[0011] In one possible implementation, the step of superimposing and converging the received signals from multiple distributed APs to the central processing unit to obtain a function of the cooperative received signal includes: Set the equivalent frequency point and amplitude coefficient in the cooperatively received signal as deterministic variables, and set the phase as a random variable; or, The amplitude coefficient in the cooperatively received signal is set as a deterministic variable, and the equivalent frequency point and phase are set as random variables.

[0012] In one possible implementation, the step of optimizing the multi-AP collaborative transmission and clock synchronization process across the entire network to obtain an optimized non-cellular network prototype includes: The channel autocorrelation function of the non-cellular network is constructed using the user cooperative cluster service model. The channel autocorrelation function is truncated and synchronized to obtain the optimized AP equivalent frequency point and amplitude coefficient; Based on the optimized AP equivalent frequency point and amplitude coefficient, the optimized non-cellular network prototype is obtained.

[0013] In one possible implementation, the channel autocorrelation function of the cellular-free network is: in, The channel autocorrelation function, For signal power, It is a zeroth-order Bessel function of the first kind. For the maximum Doppler frequency shift, For time delay; The optimized AP equivalent frequency point is: in, The optimized AP equivalent frequency point, For the number of collaborative APs, For AP number; The optimized amplitude coefficient is: in, To optimize the amplitude coefficient, This represents the effective value of the signal.

[0014] In one possible implementation, the step of configuring the basic network architecture and scenario deployment sub-schemes corresponding to the target scenario based on the target scenario type and the optimized non-cellular network prototype, to obtain the configuration result for the target scenario, includes: When the target scenario type is an underground roadway scenario, the basic network architecture corresponding to the target scenario is configured as a distributed continuous coverage architecture, and the scenario deployment sub-scheme is configured as a distance vector optimal deployment unit and a service-aware energy efficiency deployment unit; wherein, the distributed continuous coverage architecture includes multiple distributed APs, and each AP corresponds to a roadway coverage area; When the target scenario type is an intelligent fully mechanized mining face scenario, the basic network architecture corresponding to the target scenario is configured as a dynamic collaborative cluster service architecture, and the service coverage maximization deployment unit of the scenario deployment sub-scheme is configured; wherein, the dynamic collaborative cluster service architecture is built based on multi-AP joint transceiver; When the target scenario type is a transportation trunk line scenario, the basic network architecture corresponding to the target scenario is configured as a distributed handover-free coverage architecture; wherein, the distributed handover-free coverage architecture includes multiple distributed APs, and each AP corresponds to a mobile coverage area.

[0015] In one possible implementation, the step of configuring the underlying network architecture corresponding to the target scenario as a distributed handover-free coverage architecture includes: If a line-of-sight link exists in the target scenario, the transmission model of the distributed handoverless coverage architecture is a highly reliable direct-path transmission model. If there is no line-of-sight link in the target scenario, the transmission model of the distributed handoverless coverage architecture is a non-line-of-sight scattering transmission model.

[0016] Secondly, this application provides a 6G non-cellular network construction system for intelligent coal mines, the system being used to execute the above-described method, the system comprising: The model building module is used to construct a prototype of a non-cellular network in a coal mine based on a centralized processing and distributed access architecture, and to optimize the multi-AP collaborative transmission and clock synchronization process of the entire network to obtain an optimized non-cellular network prototype; the non-cellular network prototype includes a central processing unit and mine explosion-proof wireless access points; The result configuration module is used to configure the basic network architecture and scenario deployment sub-scheme corresponding to the target scenario based on the target scenario type and the optimized non-cellular network prototype, and obtain the configuration result for the target scenario; the target scenario type includes underground roadway scenario, intelligent fully mechanized mining face scenario or transportation trunk line scenario, and the scenario deployment sub-scheme includes distance vector optimal deployment unit, service coverage maximization deployment unit and business perception energy efficiency deployment unit; The result implementation module is used to perform communication coverage and service carrying on the target area of ​​the coal mine based on the configuration results of the target scenario, so as to obtain a high-reliability and low-latency communication result across the entire area.

[0017] The technical solution provided in this application may include the following beneficial effects: This application presents a method and system for constructing a 6G non-cellular network for intelligent coal mines. It constructs and optimizes a non-cellular network prototype, including a central processing unit and mine-use explosion-proof wireless access points, based on a centralized processing and distributed access architecture. This eliminates traditional cellular boundaries and frequent handovers, improving coverage uniformity and transmission stability in complex underground environments. Furthermore, by dynamically configuring corresponding basic network architectures and scenario deployment sub-schemes according to target scenario types such as underground roadways, intelligent fully mechanized mining faces, and transportation trunk lines, it achieves refined coverage strategy adaptation and resource efficiency balance under different scenarios. Simultaneously, by utilizing the generated configuration results to perform communication coverage and service carrying in target areas of the coal mine, it obtains high-reliability, low-latency communication results across the entire area, solving the problems of redundancy, uneven coverage, and insufficient reliability in traditional methods, while balancing communication performance, deployment cost, and engineering feasibility.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0020] Figure 1 A flowchart illustrating a method for constructing a 6G non-cellular network for intelligent coal mines in an exemplary embodiment of this disclosure is shown. Figure 2 The diagram illustrates a centralized processing and distributed access architecture for the construction method of a 6G non-cellular network for intelligent coal mines in an exemplary embodiment of this disclosure. Figure 3 A detailed flowchart of step S100 of the method for constructing a 6G non-cellular network for intelligent coal mines in an exemplary embodiment of this disclosure is shown. Figure 4 This illustration shows a schematic diagram of a highly reliable direct-path transmission model for the construction method of 6G non-cellular network for intelligent coal mines in an exemplary embodiment of this disclosure. Figure 5 A detailed flowchart of step S200 of the method for constructing a 6G non-cellular network for intelligent coal mines in an exemplary embodiment of this disclosure is shown. Figure 6 This diagram illustrates the dynamic collaborative cluster service architecture of the 6G non-cellular network construction method for intelligent coal mines in an exemplary embodiment of this disclosure. Figure 7 This diagram illustrates the structure of a 6G non-cellular network construction system for intelligent coal mines in an exemplary embodiment of this disclosure. Detailed Implementation

[0021] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0022] This example implementation first provides a method for constructing a 6G non-cellular network for intelligent coal mines. This method can be applied to a terminal device, such as a mobile terminal like a mobile phone, desktop computer, personal digital assistant, laptop, tablet, or smartwatch. (Reference) Figure 1 As shown, the method may include the following steps: Step S100: Construct a prototype of a non-cellular network for coal mines based on a centralized processing and distributed access architecture, and optimize the multi-AP collaborative transmission and clock synchronization process of the entire network to obtain an optimized non-cellular network prototype; the non-cellular network prototype includes a central processing unit and mine explosion-proof wireless access points.

[0023] Step S200: Based on the target scenario type and the optimized non-cellular network prototype, configure the basic network architecture and scenario deployment sub-scheme corresponding to the target scenario to obtain the configuration result for the target scenario; the target scenario type includes underground roadway scenario, intelligent fully mechanized mining face scenario or transportation trunk line scenario, and the scenario deployment sub-scheme includes distance vector optimal deployment unit, service coverage maximization deployment unit and business perception energy efficiency deployment unit.

[0024] Step S300: Based on the configuration results of the target scenario, communication coverage and service carrying are performed on the target area of ​​the coal mine to obtain a high-reliability, low-latency communication result across the entire area.

[0025] The aforementioned method is adaptable to various typical and complex working conditions in coal mines, including underground roadways, intelligent fully mechanized mining faces, and transportation trunk lines. It leverages a non-cellular network architecture combining centralized processing and distributed access to overcome communication limitations caused by strong obstruction, multipath fading, electromechanical and electromagnetic interference, and rapid dynamic changes in mobile devices in underground coal mines. It effectively addresses the shortcomings of traditional cellular networks, such as frequent handovers, numerous coverage blind spots, redundant architecture, and insufficient transmission reliability. Through multi-AP collaborative transmission and timing clock synchronization optimization, coupled with scenario-specific network architectures and differentiated deployment sub-solutions, it achieves seamless continuous coverage across the entire coal mine and hard-switching-free transmission in mobile scenarios. While ensuring high-reliability and low-latency transmission performance, it balances network coverage quality, engineering deployment costs, and energy utilization efficiency, comprehensively supporting the stable operation of all services in coal mines, including intelligent remote equipment control, environmental sensing and data acquisition, high-definition video surveillance, and unmanned inspection robot operations.

[0026] Below, we will refer to Figures 2 to 6 The steps of the method described above in this example embodiment will be explained in more detail.

[0027] In step S100, a prototype of a non-cellular network for coal mines is constructed based on a centralized processing and distributed access architecture, and the multi-AP collaborative transmission and clock synchronization process of the entire network is optimized to obtain an optimized non-cellular network prototype; the non-cellular network prototype includes a central processing unit and a mine explosion-proof wireless access point.

[0028] It should be noted that, as Figure 2The diagram illustrates a centralized processing and distributed access architecture. This architecture adopts a 6G non-cellular dedicated networking paradigm for coal mines, combining centralized intelligent computing and distributed access. The core of the architecture consists of a top-level central processing unit and underground distributed mine-use explosion-proof wireless access points. The central processing unit is responsible for core functions such as network-wide computing power scheduling, joint signal processing, resource allocation, and unified network clock synchronization. Various mine-use explosion-proof wireless access points are distributed across underground roadways, intelligent fully mechanized mining faces, and transportation trunk lines, responsible for short-range wireless signal transmission and reception, on-site signal acquisition, and edge access. Unlike traditional cellular cell division models, all signals collected by distributed explosion-proof APs are converged to the central processing unit for centralized collaborative computation. Terminal devices do not have fixed cell affiliations and can rely on multiple surrounding APs to form dynamic collaborative coverage. At the same time, the architecture adapts to the engineering constraints of underground coal mine explosion-proof safety standards, confined space deployment, and low-power operation. It avoids the inherent defects of traditional cellular networks, such as hard cell handover, coverage blind spots, and architectural redundancy, from the bottom layer, providing a stable hardware architecture and networking foundation for subsequent multi-AP collaborative transmission modeling, channel autocorrelation function optimization, and collaborative cluster service model construction.

[0029] In one embodiment, such as Figure 3 As shown, step S100 may include the following sub-steps.

[0030] In step S110, the received signals from multiple distributed APs are superimposed and converged to the central processing unit to obtain a function of the cooperative received signal.

[0031] It should be noted that the method of superimposing the received signals of N distributed APs to obtain a random process function is an improvement on the traditional distributed antenna independent coverage model. This improvement can solve problems such as multi-AP cooperative interference, uneven coverage, and handover lag. The function of the cooperative received signal is used to describe the superimposed signal uploaded by multiple APs to the central processing unit in the network.

[0032] The function of the cooperatively received signal is: in, To coordinate signal reception, For the channel response of the nth AP, For the transmitted signal of the nth AP, For noise, This represents the total number of APs.

[0033] Furthermore, in step S110, the equivalent frequency point and amplitude coefficient in the cooperatively received signal can be set as deterministic variables, and the phase can be set as a random variable; or, the amplitude coefficient in the cooperatively received signal can be set as deterministic variables, and the equivalent frequency point and phase can be set as random variables.

[0034] It should be noted that by setting the parameters of the random process function as described above, it is possible to adapt to the differentiated needs of single-user remote control and multi-device concurrent access in coal mine scenarios, thereby meeting the communication requirements of different scenarios such as underground roadways, fully mechanized mining faces, and transportation trunk lines. Furthermore, the amplitude weighting coefficient, equivalent frequency point, and initial phase can all be set as random variables to adapt to high-density concurrent access scenarios. However, considering the limited number of APs deployed and space constraints in this application, this method is only an optional solution. For example, the equivalent frequency point and amplitude coefficient in the cooperative received signal can be set as deterministic variables, and the phase can be set as a random variable to adapt to the single-user cooperative cluster service model.

[0035] In step S120, a user cooperative cluster service model is constructed based on the functional representation of the cooperative received signal.

[0036] It should be noted that the aforementioned function for coordinated signal reception describes the composite form of terminal signals simultaneously received by all APs, superimposed and uploaded to the central processing unit. Based on this, when constructing the user cooperative cluster service model, the composite signal is decomposed into two orthogonal components, namely in-phase and orthogonal, corresponding to the contributions of two independent AP sets, respectively: The user collaboration cluster service model is as follows: in, For signals synthesized by cooperative clusters, This is the first in-phase orthogonal component. The imaginary unit, This is the second in-phase orthogonal component. The number of APs serving the first service. As the first magnitude weight, For carrier frequency, For time variables, This is the first initial phase. For the number of APs serving the second service, As the second magnitude weight, This is the first initial phase.

[0037] In this way, the original form of superimposed signals received by multiple APs is transformed into a collaborative cluster model centered on the user and jointly served by multiple APs, realizing the construction from physical layer signal synthesis to logical layer service model.

[0038] The specific process of constructing the user collaborative cluster service model is as follows: First, based on the collaborative reception signal function... The set of all access points (APs) serving the user is determined; subsequently, this set of APs is divided into two groups, corresponding to the in-phase components of the synthesized signal, respectively. Orthogonal components Next, magnitude weights are assigned to each group of APs. Equivalent frequency and initial phase Finally, the two components are superimposed to obtain a complex form of the cooperative cluster synthesis signal. This completes the model construction.

[0039] In step S130, the cooperative cluster random process is superimposed with the line-of-sight path power parameter to construct the prototype of the coal mine non-cellular network; the prototype of the coal mine non-cellular network includes a high-reliability direct path transmission model and a non-line-of-sight scattering transmission model.

[0040] It should be noted that the user collaboration cluster service model mentioned above... Essentially, it describes the random process of multi-AP joint transmission, i.e., the random process of cooperative clustering. When there is no direct path in the link, It is a stochastic process that follows a Rayleigh distribution, corresponding to a non-line-of-sight scattering transmission model; when a direct path exists in the link, a line-of-sight path power parameter needs to be superimposed on this stochastic process. This yields a Rice-distributed random process, namely: ;in, The power parameters are for the direct beam diameter. It is a stochastic process with multipath components. Therefore, the cooperative cluster stochastic process is the basic model, and the line-of-sight path power parameter is a key parameter used to superimpose on the basic model to construct a highly reliable transmission model containing direct paths.

[0041] like Figure 4 The diagram shows a highly reliable direct path transmission model. The difference between the line-of-sight transmission model and the scattering transmission model is that when a stable direct signal component exists in the link, the transmission model is a highly reliable line-of-sight model; otherwise, it is a non-line-of-sight scattering model. Since line-of-sight transmission has a direct path, the direct path power parameter can be superimposed on the random process of the cooperative cluster to achieve the construction of a highly stable transmission model without refactoring the core processing unit, thus saving hardware resources.

[0042] In step S140, the channel autocorrelation function of the non-cellular network is constructed through the user cooperative cluster service model.

[0043] It should be noted that, based on the aforementioned user cooperative cluster service model, the channel autocorrelation function of the cellular network can be obtained, which describes the correlation of cooperative cluster signals under different time delays and reflects the channel fading characteristics of multi-AP cooperative transmission. This application uses the superposition method to represent the autocorrelation function of the cellular network transmission channel, providing a theoretical basis for subsequent truncation optimization. The aforementioned cooperative transmission model, i.e., the user cooperative cluster service model, is a cellular transmission model centered on the user and jointly provided by multiple APs.

[0044] The channel autocorrelation function of the non-cellular network is: in, The channel autocorrelation function, For signal power, It is a zeroth-order Bessel function of the first kind. For the maximum Doppler frequency shift, For time delay.

[0045] In step S150, the channel autocorrelation function is truncated and synchronized to obtain the optimized AP equivalent frequency point and amplitude coefficient.

[0046] It should be noted that the truncation process can specifically be a finite-term optimal truncation of the Bessel function. By optimizing the equivalent frequency point and amplitude coefficient, the actual channel response gradually approaches the theoretical optimal value as the number of cooperative APs increases. This effectively improves the coverage uniformity and transmission stability in the complex environment of coal mines, and is suitable for the constraints of narrow underground spaces and explosion-proof low power consumption.

[0047] The optimized AP equivalent frequency point is: in, The optimized AP equivalent frequency point, For the number of collaborative APs, This is the AP number.

[0048] The optimized amplitude coefficient is: in, To optimize the amplitude coefficient, This represents the effective value of the signal.

[0049] In step S160, based on the optimized AP equivalent frequency point and amplitude coefficient, the optimized non-cellular network prototype is obtained.

[0050] It should be noted that, based on the optimized AP equivalent frequency point and amplitude coefficient, the operating frequency and transmit power of each AP in the cooperative cluster service model are adjusted so that the actual channel characteristics of multi-AP cooperative transmission approach the theoretical optimal value, thereby obtaining an optimized non-cellular network prototype with more uniform coverage, lower interference, and stronger mobility stability.

[0051] In step S200, based on the target scenario type and the optimized non-cellular network prototype, the basic network architecture and scenario deployment sub-scheme corresponding to the target scenario are configured to obtain the configuration result for the target scenario; the target scenario type includes underground roadway scenario, intelligent fully mechanized mining face scenario or transportation trunk line scenario, and the scenario deployment sub-scheme includes distance vector optimal deployment unit, service coverage maximization deployment unit and business perception energy efficiency deployment unit.

[0052] It should be noted that, since the non-cellular network prototype constructed in step S100 has the flexibility of centralized processing and distributed access, it can dynamically switch the basic network architecture and match the corresponding deployment strategy units according to the coverage requirements of different coal mine scenarios, thereby achieving a balance between full coverage and resource efficiency.

[0053] In one embodiment, such as Figure 5 As shown, step S200 may include the following sub-steps: In step S210, when the target scenario type is an underground roadway scenario, the basic network architecture corresponding to the target scenario is configured as a distributed continuous coverage architecture, and the scenario deployment sub-scheme is configured as a distance vector optimal deployment unit and a service-aware energy efficiency deployment unit; wherein, the distributed continuous coverage architecture includes multiple distributed APs, and each AP corresponds to a section of roadway coverage area.

[0054] It should be noted that in underground tunnel scenarios, to address signal distortion and blind spots caused by narrow tunnels, multiple branches, and metal obstructions, distance vector optimal deployment and service-aware energy-efficient deployment strategies are required. The distance vector optimal deployment unit establishes the optimal relationship between coverage distance and signal strength based on the tunnel geometry and equipment distribution, maximizing the average traversal capacity within the tunnel by optimizing AP locations. The service-aware energy-efficient deployment unit, based on historical traffic volume and real-time access density, enhances AP deployment in high-traffic areas and reduces the number of APs in sparsely trafficked areas, achieving precise matching of network resources and service demands, and reducing the pressure on underground power supply.

[0055] In step S220, when the target scenario type is an intelligent fully mechanized mining face scenario, the basic network architecture corresponding to the target scenario is configured as a dynamic collaborative cluster service architecture, and the service coverage maximization deployment unit of the scenario deployment sub-scheme is configured; wherein, the dynamic collaborative cluster service architecture is built based on multi-AP joint transceiver.

[0056] It should be noted that, as Figure 6The diagram illustrates a dynamic collaborative cluster service architecture. The longwall mining face contains numerous metal devices, mobile coal mining machines, and hydraulic supports, leading to frequent signal obstruction and drastic dynamic changes. The dynamic collaborative cluster service architecture employs a user-centric scheduling mechanism to generate an optimal set of service access points (APs), achieving seamless coverage during movement. During configuration, it adapts to the high-speed movement characteristics of coal mining machines and inspection robots, and sets the channel fading power spectrum to a Gaussian spectrum to accommodate multipath scattering and obstruction fading characteristics at the longwall mining face, thus resolving coverage interruption issues under dynamic obstruction.

[0057] In step S230, when the target scenario type is a transportation trunk line scenario, the basic network architecture corresponding to the target scenario is configured as a distributed handover-free coverage architecture; wherein, the distributed handover-free coverage architecture includes multiple distributed APs, and each AP corresponds to a mobile coverage area.

[0058] It should be noted that in the transportation trunk line scenario, the distributed handoverless coverage architecture adopts a linear series coverage structure, and the latency and power of each AP coverage section are independently adjustable to meet the long-distance continuous coverage requirements of alleyways and transportation trunk lines. Setting overlapping coverage sections between adjacent APs can more precisely simulate the smooth transition of coverage during movement.

[0059] Furthermore, the step of configuring the basic network architecture corresponding to the target scenario as a distributed handover-free coverage architecture includes: If a line-of-sight link exists in the target scenario, the transmission model of the distributed handoverless coverage architecture is a highly reliable direct-path transmission model. If there is no line-of-sight link in the target scenario, the transmission model of the distributed handoverless coverage architecture is a non-line-of-sight scattering transmission model.

[0060] In step S300, based on the configuration results of the target scenario, communication coverage and service carrying are performed on the target area of ​​the coal mine to obtain a high-reliability, low-latency communication result across the entire area.

[0061] It should be noted that, based on the basic network architecture and deployment sub-scheme, the coverage location, transmission power and cooperation relationship of each AP in the target scenario are determined, and a time-varying coverage sequence corresponding to each AP is generated; the coverage sequence is calibrated and cooperatively processed according to the location and power parameters to obtain the coverage signal of each AP; the cooperatively processed coverage signal and the terminal received signal are jointly processed to obtain the final global communication result.

[0062] For example, in underground roadway scenarios, continuous coverage of the entire roadway is achieved based on a distributed continuous coverage architecture, distance vector optimal deployment, and business-aware energy efficiency deployment; in intelligent fully mechanized mining face scenarios, seamless coverage of highly dynamic equipment is achieved based on a dynamic collaborative cluster service architecture and service coverage maximization deployment; and in transportation trunk line scenarios, long-distance mobile handover-free transmission is achieved based on a distributed handover-free coverage architecture.

[0063] Furthermore, this example embodiment also provides a 6G non-cellular network construction system for intelligent coal mines. (Reference) Figure 7 As shown, the system may include: The model building module is used to construct a prototype of a non-cellular network in a coal mine based on a centralized processing and distributed access architecture, and to optimize the multi-AP collaborative transmission and clock synchronization process of the entire network to obtain an optimized non-cellular network prototype; the non-cellular network prototype includes a central processing unit and mine explosion-proof wireless access points; The result configuration module is used to configure the basic network architecture and scenario deployment sub-scheme corresponding to the target scenario based on the target scenario type and the optimized non-cellular network prototype, and obtain the configuration result for the target scenario; the target scenario type includes underground roadway scenario, intelligent fully mechanized mining face scenario or transportation trunk line scenario, and the scenario deployment sub-scheme includes distance vector optimal deployment unit, service coverage maximization deployment unit and business perception energy efficiency deployment unit; The result implementation module is used to perform communication coverage and service carrying on the target area of ​​the coal mine based on the configuration results of the target scenario, so as to obtain a high-reliability and low-latency communication result across the entire area.

[0064] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

Claims

1. A method for constructing a 6G non-cellular network for intelligent coal mines, characterized in that, include: A prototype of a non-cellular network for coal mines was constructed based on a centralized processing and distributed access architecture. The collaborative transmission and clock synchronization process of multiple access points across the network was optimized to obtain an optimized non-cellular network prototype. The non-cellular network prototype includes a central processing unit and a mining explosion-proof wireless access point. Based on the target scenario type and the optimized non-cellular network prototype, the basic network architecture and scenario deployment sub-scheme corresponding to the target scenario are configured to obtain the configuration result for the target scenario; the target scenario type includes underground roadway scenario, intelligent fully mechanized mining face scenario or transportation trunk line scenario, and the scenario deployment sub-scheme includes distance vector optimal deployment unit, service coverage maximization deployment unit and business perception energy efficiency deployment unit; Based on the configuration results of the target scenario, communication coverage and service carrying are carried out in the target area of ​​the coal mine, resulting in a highly reliable and low-latency communication result across the entire area.

2. The method for constructing a 6G non-cellular network for intelligent coal mines according to claim 1, characterized in that, The steps for constructing a cellular-free network prototype for coal mines based on a centralized processing and distributed access architecture include: The signals received by multiple distributed APs are superimposed and converged to the central processing unit to obtain a function of the coordinated received signal; Based on the functional representation of the cooperative received signal, a user cooperative cluster service model is constructed.

3. The method for constructing a 6G non-cellular network for intelligent coal mines according to claim 2, characterized in that, After the step of constructing the user cooperative cluster service model based on the function representation of the cooperative received signal, the method further includes: The prototype of the coal mine non-cellular network is constructed by superimposing the cooperative cluster random process with the line-of-sight path power parameter; the prototype of the coal mine non-cellular network includes a high-reliability direct path transmission model and a non-line-of-sight scattering transmission model.

4. The method for constructing a 6G non-cellular network for intelligent coal mines according to claim 2, characterized in that, The function of the cooperative reception signal is: in, To coordinate signal reception, For the channel response of the nth AP, For the transmitted signal of the nth AP, For noise, This represents the total number of APs; The user collaboration cluster service model is as follows: in, For signals synthesized by cooperative clusters, This is the first in-phase orthogonal component. The imaginary unit, This is the second in-phase orthogonal component. The number of APs serving the first service. As the first magnitude weight, For carrier frequency, For time variables, This is the first initial phase. For the number of APs serving the second service, As the second magnitude weight, This is the second initial phase.

5. The method for constructing a 6G non-cellular network for intelligent coal mines according to claim 2, characterized in that, The step of superimposing and converging the received signals from multiple distributed APs to the central processing unit to obtain a function of the coordinated received signal includes: Set the equivalent frequency point and amplitude coefficient in the cooperatively received signal as deterministic variables, and set the phase as a random variable; or, The amplitude coefficient in the cooperatively received signal is set as a deterministic variable, and the equivalent frequency point and phase are set as random variables.

6. The method for constructing a 6G non-cellular network for intelligent coal mines according to claim 2, characterized in that, The steps for optimizing the multi-AP collaborative transmission and clock synchronization process across the entire network to obtain an optimized non-cellular network prototype include: The channel autocorrelation function of the non-cellular network is constructed using the user cooperative cluster service model. The channel autocorrelation function is truncated and synchronized to obtain the optimized AP equivalent frequency point and amplitude coefficient; Based on the optimized AP equivalent frequency point and amplitude coefficient, the optimized non-cellular network prototype is obtained.

7. The method for constructing a 6G non-cellular network for intelligent coal mines according to claim 6, characterized in that, The channel autocorrelation function of the non-cellular network is: in, The channel autocorrelation function, For signal power, It is a zeroth-order Bessel function of the first kind. For the maximum Doppler frequency shift, For time delay; The optimized AP equivalent frequency point is: in, The optimized AP equivalent frequency point, For the number of collaborative APs, For AP number; The optimized amplitude coefficient is: in, To optimize the amplitude coefficient, This represents the effective value of the signal.

8. The method for constructing a 6G non-cellular network for intelligent coal mines according to claim 1, characterized in that, The step of configuring the basic network architecture and scenario deployment sub-scheme corresponding to the target scenario based on the target scenario type and the optimized non-cellular network prototype, and obtaining the configuration result for the target scenario, includes: When the target scenario type is an underground roadway scenario, the basic network architecture corresponding to the target scenario is configured as a distributed continuous coverage architecture, and the scenario deployment sub-scheme is configured as a distance vector optimal deployment unit and a service-aware energy efficiency deployment unit; wherein, the distributed continuous coverage architecture includes multiple distributed APs, and each AP corresponds to a roadway coverage area; When the target scenario type is an intelligent fully mechanized mining face scenario, the basic network architecture corresponding to the target scenario is configured as a dynamic collaborative cluster service architecture, and the service coverage maximization deployment unit of the scenario deployment sub-scheme is configured; wherein, the dynamic collaborative cluster service architecture is built based on multi-AP joint transceiver; When the target scenario type is a transportation trunk line scenario, the basic network architecture corresponding to the target scenario is configured as a distributed handover-free coverage architecture; wherein, the distributed handover-free coverage architecture includes multiple distributed APs, and each AP corresponds to a mobile coverage area.

9. The method for constructing a 6G non-cellular network for intelligent coal mines according to claim 8, characterized in that, The steps for configuring the underlying network architecture corresponding to the target scenario as a distributed, handover-free coverage architecture include: If a line-of-sight link exists in the target scenario, the transmission model of the distributed handoverless coverage architecture is a highly reliable direct-path transmission model. If there is no line-of-sight link in the target scenario, the transmission model of the distributed handoverless coverage architecture is a non-line-of-sight scattering transmission model.

10. A 6G non-cellular network construction system for intelligent coal mines, characterized in that, The system is used to perform the method as described in any one of claims 1 to 9, the system comprising: The model building module is used to construct a prototype of a non-cellular network in a coal mine based on a centralized processing and distributed access architecture, and to optimize the multi-AP collaborative transmission and clock synchronization process of the entire network to obtain an optimized non-cellular network prototype; the non-cellular network prototype includes a central processing unit and mine explosion-proof wireless access points; The result configuration module is used to configure the basic network architecture and scenario deployment sub-scheme corresponding to the target scenario based on the target scenario type and the optimized non-cellular network prototype, and obtain the configuration result for the target scenario; the target scenario type includes underground roadway scenario, intelligent fully mechanized mining face scenario or transportation trunk line scenario, and the scenario deployment sub-scheme includes distance vector optimal deployment unit, service coverage maximization deployment unit and business perception energy efficiency deployment unit; The result implementation module is used to perform communication coverage and service carrying on the target area of ​​the coal mine based on the configuration results of the target scenario, so as to obtain a high-reliability and low-latency communication result across the entire area.

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