Environmental semantic perception assisted orthogonal time-frequency space channel estimation system and method
By extracting information about communication equipment and scatterers from environmental semantic-aware base stations, a low-overhead pilot structure is designed, which solves the problems of spectrum resource waste and high computational complexity in orthogonal time-frequency spatial modulation, and achieves efficient channel estimation and resource decoupling.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-02
- Publication Date
- 2026-03-27
AI Technical Summary
In existing technologies, orthogonal time-frequency spatial modulation technology relies on precise channel state information in high-mobility communication scenarios, resulting in wasted spectrum resources and high computational complexity. At the same time, there is severe competition for sensing and communication resources, which cannot meet the fine-grained requirements of physical layer channel estimation.
By acquiring environmental images through environmental semantic perception base stations, the location and movement characteristics of communication access points, user equipment, and scatterers are extracted. A low-overhead pilot structure is designed for channel estimation. User equipment performs orthogonal time-frequency spatial demodulation and estimates channel coefficients, thereby achieving independent decoupling of sensing and communication resources and low-complexity channel estimation.
It significantly reduces pilot overhead, improves spectrum efficiency, eliminates resource contention, reduces computational complexity, and enables fine-grained physical layer channel estimation.
Smart Images
Figure CN121750409A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application belongs to the technical field of wireless communication, and particularly relates to an environment semantic perception assisted orthogonal time frequency space channel estimation system and method. BACKGROUND
[0002] In a high mobility communication scenario, the orthogonal time frequency space (OTFS) modulation technology can effectively combat the double selective channel fading, but its performance is severely dependent on accurate channel state information. The traditional channel estimation method relies on inserting a large number of pilot symbols in the time-frequency domain and setting a guard interval around it, as shown in FIG. 1, which leads to a significant waste of spectrum resources and reduces the spectral efficiency of the system. Figure 1
[0003] To reduce the pilot overhead, perception assisted communication technology is proposed, such as obtaining environmental information through wireless perception means such as radar to assist channel inference. However, such methods have inherent limitations: the perception function usually shares spectrum and power resources with the communication link, which itself introduces new resource competition.
[0004] Further, as an emerging research direction, environment semantic assisted communication attempts to infer channel characteristics by extracting higher layer environmental features (such as object position, shape). However, the current public scheme is mostly focused on network layer or application layer resource management and optimization, such as semantic based handover decision or traffic prediction. For the core requirement of physical layer channel estimation, the existing technology lacks effective means to directly convert environmental semantic information into accurate channel parameters (such as delay, Doppler shift and channel coefficients), and cannot meet the strict requirements of fine-grained channel information for physical layer symbol detection.
[0005] Therefore, there is an urgent need in the art for an innovative solution that can overcome the above-mentioned deficiencies, which can significantly improve the spectral efficiency, avoid resource competition with traditional communication links, and achieve low complexity fine-grained physical layer channel estimation. SUMMARY
[0006] The embodiments of the present application propose an environment semantic perception assisted orthogonal time frequency space channel estimation system and method, aiming to solve the problems of severe loss of spectral efficiency, resource competition between perception and communication, high computational complexity, and lack of fine-grained physical layer channel estimation in the prior art.
[0007] The first aspect of the embodiments of the present application provides an environment semantic perception assisted orthogonal time frequency space channel estimation system, comprising an environment semantic perception base station, a communication access point and a user equipment, wherein: The environmental semantic awareness base station is used to collect environmental images, process the images to extract environmental semantic information, and broadcast the environmental semantic information through a broadcast channel. The environmental semantic information includes at least the location and movement characteristics of the communication access point, the user equipment, and the scattering object. The communication access point is used to receive the environmental semantic information, determine the channel's time delay parameters and Doppler frequency shift parameters based on the environmental semantic information, generate a low-overhead pilot structure based on the time delay parameters and Doppler frequency shift parameters, and use the low-overhead pilot structure to perform orthogonal time-frequency spatial modulation to transmit signals. The low-overhead pilot structure is implemented by setting guard intervals only at time delay-Doppler grid points that may be subject to interference, as determined by the time delay parameters and Doppler frequency shift parameters. The user equipment is configured to obtain the environmental semantic information by listening to the broadcast channel, receive the signal and perform orthogonal time-frequency spatial demodulation, and estimate the channel coefficient by performing point-by-point division between the received pilot signal and the known transmitted pilot signal based on the time delay-Doppler grid point positions determined by the environmental semantic information.
[0008] In some embodiments of this application, the environmental semantic awareness base station processes the image to extract environmental semantic information including: The image is used to perform target recognition to identify the communication access point, the user equipment, and the scattering object, and to obtain their position and movement characteristics.
[0009] In some embodiments of this application, the communication access point determines the channel's delay parameters and Doppler frequency shift parameters based on the environmental semantic information, including: For line-of-sight links, according to the formula and Calculate, where, , representing the distance of the LOS link between the communication access point and the user equipment at time index n. and These represent the estimated positions of the communication access point and the user equipment at time index n, respectively, where c represents the speed of light. It is the relative speed between the communication access point and the user equipment at time index n. f is the angle between the direction of the connection between the communication access point and the user equipment and the speed direction. c It is the carrier frequency; For non-line-of-sight links, according to the formula and Calculate, where, It is the segment number of the p-th path. It is the length of the i-th segment of the p-th path. It is the relative velocity of the i-th segment. It is the angle between the direction of the i-th segment and the direction of the velocity.
[0010] In some embodiments of this application, the user equipment performs a point-by-point division operation between the received pilot signal and the known transmitted pilot signal to estimate the channel coefficients, including: The channel coefficients are estimated using the following formula: , in, , For the number of paths, These represent the Doppler and time delay taps estimated based on environmental semantics, respectively.
[0011] In some embodiments of this application, the environmental semantic awareness base station periodically collects and processes environmental images to continuously update the environmental semantic information; The communication access point dynamically adjusts the design of the low-overhead pilot structure based on the received updated environmental semantic information; The user equipment adaptively performs channel estimation at the corresponding delay-Doppler grid point locations based on the acquired updated environmental semantic information.
[0012] A second aspect of this application provides an environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method, executed by a communication access point, comprising: Acquire environmental semantic information, which includes the position and movement characteristics of transmitters, receivers and scatterers in the communication link; Based on the environmental semantic information, the channel's time delay parameters and Doppler frequency shift parameters are determined. Based on the time delay parameters and Doppler frequency shift parameters, a low-overhead pilot structure is designed, wherein a protection interval is set only at the time delay-Doppler grid points that may be subject to interference, as determined by the time delay parameters and Doppler frequency shift parameters. The low-overhead pilot structure is used to construct the transmission signal, which is then transmitted after orthogonal time-frequency spatial modulation.
[0013] In some embodiments of this application, the design of the low-overhead pilot structure based on the time delay parameter and the Doppler frequency shift parameter includes: Place the pilot symbols in the coordinates of the time-delay-Doppler grid. Place; After passing through the channel, the pilot symbols will be mapped to grid point locations. ,in ; The grid point positions that may interfere with the shifted pilot symbols. Set as a protection interval, where , This represents the number of paths.
[0014] In some embodiments of this application, determining the channel's time delay parameters and Doppler frequency shift parameters based on the environmental semantic information includes: Based on the location information in the environmental semantic information, the transmission distance of each communication path between the communication access point and the user equipment is calculated, and the time delay parameter is obtained based on the speed of light. The communication path includes line-of-sight path and non-line-of-sight scattering path. Based on the mobility characteristic information in the environmental semantic information, the relative velocity is calculated and combined with the carrier frequency to obtain the Doppler frequency shift parameter.
[0015] A third aspect of this application provides an environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method, executed by a user equipment, comprising: Obtain environmental semantic information, which is used to determine the channel's time delay parameters and Doppler frequency shift parameters; The parameters are determined based on the environmental semantic information; Receive signals from a communication access point, the signals being generated using a low-overhead pilot structure designed based on the time delay parameters and the Doppler frequency shift parameters and modulated by orthogonal time-frequency space; The received signal is subjected to orthogonal time-frequency spatial demodulation, and at the time-delay-Doppler grid point positions determined by the time delay parameter and the Doppler frequency shift parameter, the demodulated received pilot signal is divided point by point with the locally known transmitted pilot signal to estimate the channel coefficient.
[0016] In some embodiments of this application, obtaining environmental semantic information includes: By monitoring the broadcast channel of the environmental semantic awareness base station, the environmental semantic information or the time delay parameters and Doppler frequency shift parameters determined based on it can be obtained.
[0017] In summary, the environmental semantic awareness-assisted orthogonal time-frequency spatial channel estimation system and method provided in the embodiments of this application predict channel changes using environmental semantic information through the communication access point (AP), and accordingly construct a low-overhead pilot structure that sets guard intervals only at key interference points. This design replaces the traditional coarse protection mode with a precise protection mechanism, achieving significant compression of pilot overhead and maximization of spectrum resource utilization, thereby fundamentally solving the problem of spectrum efficiency loss caused by guard interval overload. By introducing an independent environmental semantic awareness base station (ESSBS) and constructing a collaborative system with the communication access point (AP) and user equipment (UE), this... The system architecture enables visual perception to operate independently of communication functions on the physical link, fundamentally decoupling perception and communication resources and completely eliminating resource competition between the two. At the user equipment (UE) end, by utilizing prior channel parameters determined by semantic information, direct point division of the received pilot and local pilot is performed at known delay-Doppler grid points. This method simplifies the traditionally complex search process into a single-step operation, significantly reducing computational complexity. Finally, by integrating the visual recognition of ESSBS, the parameter calculation and pilot design of the AP, and the direct point division estimation capability of the UE, an end-to-end mapping from environmental semantic features to physical layer channel parameters is established. This integration enables a direct correlation between semantic information and fine-grained parameters such as channel delay, Doppler shift, and channel coefficients, overcoming the technical challenge that existing semantic-assisted communication cannot meet the fine-grained requirements of physical layer symbol detection. Attached Figure Description
[0018] The features and advantages of this application will become clearer with reference to the accompanying drawings, which are illustrative and should not be construed as limiting the application in any way. In the drawings: Figure 1 This is a schematic diagram of a traditional pilot embedding scheme; Figure 2 This is a schematic diagram of the environmental semantic awareness-assisted orthogonal time-frequency spatial channel estimation system to which this application applies; Figure 3 This is a flowchart illustrating an environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method according to some embodiments of this application; Figure 4 This is the target identification result in one embodiment of this application; Figure 5 This is the semantic-assisted pilot design scheme applicable to this application; Figure 6 This is a flowchart illustrating an environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method according to some embodiments of this application; Figure 7 This is a performance comparison chart of pilot overhead between low-overhead semantic-assisted pilot structures and traditional pilot structures; Figure 8 This is a comparison chart of the receiving end computation and processing overhead between the environment semantic-assisted OTFS communication channel estimation scheme and the traditional scheme. Detailed Implementation
[0019] In the following detailed description, numerous specific details of this application are illustrated by example to provide a thorough understanding of the relevant disclosure. However, it will be apparent to those skilled in the art that this application can be practiced without these details. It should be understood that the terms “system,” “apparatus,” “unit,” and / or “module” used in this application are one way of distinguishing different parts, elements, sections, or components at different levels in a sequential arrangement. However, these terms may be replaced with other expressions if other expressions can achieve the same purpose.
[0020] It should be understood that when a device, unit, or module is referred to as being "on," "connected to," or "coupled to" another device, unit, or module, it may be directly connected to or coupled to or communicate with other devices, units, or modules, or there may be intermediate devices, units, or modules present, unless the context explicitly indicates otherwise. For example, the term "and / or" as used herein includes any one and all combinations of one or more of the relevant listed items.
[0021] The terminology used in this application is for the purpose of describing specific embodiments only and is not intended to limit the scope of this application. As shown in the specification and claims of this application, unless the context clearly indicates otherwise, words such as "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate that explicitly identified features, integrals, steps, operations, elements, and / or components are included, and such expressions do not constitute an exclusive list, and other features, integrals, steps, operations, elements, and / or components may also be included.
[0022] Referring to the following description and accompanying drawings, these and other features and characteristics, operating methods, functions of related structural elements, combinations of parts, and economics of manufacture of this application can be better understood, wherein the description and drawings form part of the specification. However, it is clearly understood that the drawings are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. It is understood that the drawings are not drawn to scale.
[0023] Various structural diagrams are used in this application to illustrate various variations of the embodiments according to this application. It should be understood that the preceding or following structures are not intended to limit this application. The scope of protection of this application is determined by the claims.
[0024] As described in the background section, traditional methods mitigate the biselective fading problem by increasing pilot overhead and guard intervals, but this results in a loss of spectral efficiency. Their pilot configuration schemes (such as...) Figure 1 The drawback of the pilot overhead (as shown) is its large overhead, which wastes resources and contradicts the goal of achieving high-speed communication. To reduce pilot overhead, sensing-assisted communication has gradually become a promising solution. However, most existing sensing-assisted methods still focus on wireless sensing itself. Improving sensing resolution consumes bandwidth and power, and wireless sensing and communication often share the same frequency band, which greatly limits the potential for improving communication performance. Environmental semantic-assisted communication, as an emerging research direction, aims to overcome the above limitations. However, most existing research is limited to studying the application of environmental semantics within a single basic communication function. This type of research still has significant shortcomings in meeting the fine-grained requirements of the physical layer for symbol detection. The key challenge lies in how to directly extract detailed small-scale channel information from semantic data.
[0025] Figure 1 This is a traditional pilot setup scheme used for channel estimation. The pilot setup scheme describes the arrangement of pilot symbols, data symbols, and guard intervals in an OTFS (Orthogonal Time-Frequency Space) frame. An OTFS frame is a two-dimensional time-delay-Doppler grid containing M×N grid points, with a time delay dimension of M and a Doppler dimension of N. Figure 1 The OTFS frame contains a pilot symbol denoted as p. Ng guard symbols represented as 0 and MN-Ng-1 data symbols represented as d This symbol structure allows the receiver to classify received symbols into two categories: pilot and guard symbols used for channel estimation, and symbols used for data detection. Guard symbols prevent interference between pilot and data symbols. For pilot symbols, coordinates can be selected. satisfy At any position, where and These represent the maximum time delay and the Doppler value, respectively. Figure 1 The pilot configuration scheme shown requires a large number of guard intervals to avoid interference between pilot symbols and data symbols. However, these guard intervals cannot carry information, resulting in a significant waste of resources.
[0026] To address the aforementioned shortcomings, this application proposes a novel technical solution. Its core idea lies in the fact that an Environment Semantic Aware Base Station (ESSBS) can acquire environmental visual semantic features. The receiver (AP) utilizes the relative motion relationships between the transceiver and environmental scattering objects to estimate the channel delay and Doppler information. Simultaneously, combined with the innovative pilot design proposed in this application, direct point division between the received pilot and the local pilot at known delay-Doppler grid points yields the estimated channel coefficients, thereby achieving low-overhead, high-precision channel estimation.
[0027] The implementation of this application is based on Figure 2 The system model shown. (As shown) Figure 2 As shown, in a vehicular communication scenario involving an access point (AP) and a highly mobile user equipment (UE), the communication link comprises S scatterers forming a wireless channel. An Environmental Semantic Aware Base Station (ESSBS) is deployed on a tower and equipped with a downward-facing high-resolution camera, which periodically captures images covering the area surrounding the AP, UE, and scatterers to continuously perceive the surrounding environment. The ESSBS can process these images to derive semantic information, including the location and mobility characteristics of the AP, UE, and scatterers. The extracted semantic information is then transmitted to the AP via the backhaul link and broadcast to nearby communication participants (including potential UEs) through a shared broadcast channel.
[0028] This application is used for channel estimation in the OTFS system.
[0029] Considering the case with integer time delay and integer Doppler shift, the OTFS system has a finite number of taps on both the time delay and Doppler shift axes, with the time delay ranging from... Doppler range is in and These are the maximum time delay and Doppler shift across all channel paths, respectively. The channel can be sparsely represented as: , Where P is the number of communication channel paths, These are the channel coefficients, time delay, and Doppler shift of the p-th path, respectively. It is the Dirac function. (Using...) and Let represent the time delay and Doppler tap of the p-th path. Then, the relationship between the tap position and the time delay and Doppler frequency shift can be expressed as: , , Where M represents the number of symbols, N represents the number of subcarriers, and T represents the symbol period. The subcarrier spacing.
[0030] Then, the received symbol can be represented. and sending symbols The relationship between (representing the (k, l)th element of the sent OTFS frame): .
[0031] Therefore, channel estimation for OTFS includes three parts: time delay, Doppler offset, and channel tap coefficients.
[0032] The following section, with reference to the accompanying drawings, will explain in detail how this application achieves the estimation of the above three parameters. Figure 3 This is a flowchart illustrating an environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method according to some embodiments of this application. In some embodiments, the environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method is composed of... Figure 2 The aforementioned communication access point execution specifically includes the following steps: S310, Obtain environmental semantic information, which includes the position and movement characteristics of the transmitter, receiver and scatterer in the communication link.
[0033] In some embodiments of this application, the ESSBS periodically captures images covering the area surrounding the AP, UE, and scattering objects using a high-resolution camera. Semantic information, including the location and mobility characteristics of the AP, UE, and scattering objects, can be derived by processing these images. The ESSBS then transmits this semantic information to the AP via a backhaul link and broadcasts it to nearby communication participants (including potential UEs) through a shared broadcast channel.
[0034] Figure 4 This is the target recognition result in one embodiment of this application. Figure 4 In this diagram, Tx represents the transmitter identification result, Sca represents the scatterer identification result, and Rx represents the receiver identification result. Based on the relative distance and its variation in adjacent time slots, the relative time delay and relative velocity between AP and UE, AP and scatterer, and scatterer and UE can be calculated.
[0035] S320, based on the environmental semantic information, determine the channel's time delay parameters and Doppler frequency shift parameters, and design a low-overhead pilot structure based on the time delay parameters and Doppler frequency shift parameters, wherein a protection interval is set only at the time delay-Doppler grid points that may be subject to interference, as determined by the time delay parameters and the Doppler frequency shift parameters.
[0036] In some embodiments of this application, the AP first determines the time delay parameter and Doppler frequency shift parameter based on the location and movement characteristics in the environmental semantic information. Specifically: For line-of-sight (LOS) links, ——Formula 1 in, , representing the distance of the LOS link between the communication access point and the user equipment at time index n. and These represent the estimated positions of the communication access point and the user equipment at time index n, respectively, where c represents the speed of light. It is the relative speed between the communication access point and the user equipment at time index n. f is the angle between the direction of the connection between the communication access point and the user equipment and the speed direction. c It is the carrier frequency.
[0037] For non-line-of-sight (NLOS) links, ——Formula 2 in, It is the segment number of the p-th path. It is the length of the i-th segment of the p-th path. It is the relative velocity of the i-th segment. The angle between the direction of the i-th segment and the direction of the velocity.
[0038] Subsequently, based on the aforementioned time delay parameters and Doppler frequency shift parameters, a pilot structure design is performed to address the channel sparsity characteristics in the time delay Doppler domain. The specific scheme is as follows: Figure 5 As shown. Pilot symbols can be placed at any grid point in a two-dimensional time-delay-Doppler domain grid, with coordinates represented as follows. After passing through the channel, the pilot symbols will be shifted to the grid points. ,in To prevent interference from data symbols, guard intervals are placed at grid point locations where interference could occur to known pilot shift points. These locations are denoted as... ,in Finally, the data symbols are placed in the remaining positions. This forms... Figure 5 The semantic-assisted pilot design scheme is shown.
[0039] S330, a transmission signal is constructed using the low-overhead pilot structure and then transmitted after orthogonal time-frequency spatial modulation. Figure 6 This is a flowchart illustrating an environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method according to some embodiments of this application. In some embodiments, the environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method is composed of... Figure 2 The user equipment execution specifically includes the following steps: S610, Obtain environmental semantic information, which is used to determine the channel's time delay parameters and Doppler frequency shift parameters.
[0040] As previously mentioned, the ESSBS broadcasts the semantic information to nearby communication participants via a shared broadcast channel. The UE can obtain the semantic information by listening to the ESSBS's broadcast channel.
[0041] S620, Based on the environmental semantic information, determine the parameters. To achieve channel estimation, the user equipment (UE) first needs to obtain the channel's delay parameters and Doppler shift parameters. In the embodiments provided in this application, the UE can obtain these parameters through the following two paths.
[0042] Path 1: Parameters are calculated by the UE itself.
[0043] After obtaining environmental semantic information (such as location and mobility characteristics), the UE can calculate channel parameters locally based on this information. In this path, the UE's calculation method is similar to that on the access point (AP) side, as detailed in S320.
[0044] Path 2: Receive parameters directly from the environmental semantic perception base station Furthermore, to improve processing efficiency and reduce the computational burden on the UE, the delay parameters and Doppler shift parameters can also be calculated by the Environmental Semantic Aware Base Station (ESSBS) and directly provided to the UE. Specifically, after extracting environmental semantic information, the ESSBS can calculate the channel parameters based on this information, and then send the calculated parameters to the UE through a shared broadcast channel. The UE can directly obtain the parameters by listening to this broadcast channel without performing local calculations.
[0045] After obtaining the parameters through any of the above paths, the UE can perform subsequent channel estimation operations.
[0046] S630, receiving a signal from a communication access point, the signal being generated using a low-overhead pilot structure designed based on the time delay parameter and the Doppler frequency shift parameter and modulated by orthogonal time-frequency space; S640, the received signal is subjected to orthogonal time-frequency spatial demodulation, and at the time delay-Doppler grid point positions determined by the time delay parameter and the Doppler frequency shift parameter, the demodulated received pilot signal is divided point by point with the locally known transmitted pilot signal to estimate the channel coefficient.
[0047] The UE can directly estimate the channel coefficients at the delay-Doppler grid point locations obtained from the semantic awareness results using the following formula.
[0048] ——Formula 3 in , These represent the Doppler and time delay taps estimated based on environmental semantics, respectively.
[0049] According to Formula 3, the UE can obtain the channel coefficients by dividing the received pilot and the known transmitted pilot point by point based on the designed pilot. This avoids the search process and reduces the signal processing complexity at the receiver.
[0050] One embodiment of this application compares the performance of the low-overhead semantic-assisted pilot structure with that of a traditional pilot structure. Figure 7 This is a performance comparison chart of pilot overhead. Figure 7 As can be seen, the low-overhead semantic auxiliary pilot structure designed for the OTFS system in this application significantly reduces pilot overhead compared to traditional pilot structures. Taking the case of multipath number P=13 as an example, the pilot overhead is reduced from more than 8% in the traditional scheme to less than 1%, and its pilot overhead does not increase with the increase of movement speed.
[0051] Another embodiment of this application compares the environmental semantic-assisted OTFS communication channel estimation scheme proposed in this application with the receiving end computation and processing overhead of traditional schemes. Figure 8 This is a comparison chart of the computational processing overhead at the receiving end. Figure 8 It is evident that the proposed environment semantic-assisted OTFS communication channel estimation scheme significantly reduces the receiving end computational processing overhead compared to traditional schemes. Figure 8 In this method, the computational processing overhead is reduced by nearly two orders of magnitude compared to traditional methods.
[0052] In summary, the environmental semantic awareness-assisted orthogonal time-frequency spatial channel estimation system and method provided in the embodiments of this application predict channel changes using environmental semantic information through the communication access point (AP), and accordingly construct a low-overhead pilot structure that sets guard intervals only at key interference points. This design replaces the traditional coarse protection mode with a precise protection mechanism, achieving significant compression of pilot overhead and maximization of spectrum resource utilization, thereby fundamentally solving the problem of spectrum efficiency loss caused by guard interval overload. By introducing an independent environmental semantic awareness base station (ESSBS) and constructing a collaborative system with the communication access point (AP) and user equipment (UE), this... The system architecture enables visual perception to operate independently of communication functions on the physical link, fundamentally decoupling perception and communication resources and completely eliminating resource competition between the two. At the user equipment (UE) end, by utilizing prior channel parameters determined by semantic information, direct point division of the received pilot and local pilot is performed at known delay-Doppler grid points. This method simplifies the traditionally complex search process into a single-step operation, significantly reducing computational complexity. Finally, by integrating the visual recognition of ESSBS, the parameter calculation and pilot design of the AP, and the direct point division estimation capability of the UE, an end-to-end mapping from environmental semantic features to physical layer channel parameters is established. This integration enables a direct correlation between semantic information and fine-grained parameters such as channel delay, Doppler shift, and channel coefficients, overcoming the technical challenge that existing semantic-assisted communication cannot meet the fine-grained requirements of physical layer symbol detection.
[0053] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the devices and modules described above can be referred to the corresponding descriptions in the foregoing device embodiments, and will not be repeated here.
[0054] Although the subject matter described herein is provided in the general context of execution on a computer system in conjunction with an operating system and applications, those skilled in the art will recognize that other implementations can also be executed in conjunction with other types of program modules. Generally, program modules include routines, programs, components, data structures, and other types of structures that perform specific tasks or implement specific abstract data types. Those skilled in the art will understand that the subject matter described herein can be practiced using other computer system configurations, including handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframes, etc., and can also be used in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules may reside on both local and remote memory storage devices.
[0055] Those skilled in the art will recognize that the units and method steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0056] It should be understood that the specific embodiments described above are merely illustrative or explanatory of the principles of this application and do not constitute a limitation thereof. Therefore, any modifications, equivalent substitutions, improvements, etc., made without departing from the spirit and scope of this application should be included within the protection scope of this application. Furthermore, the appended claims are intended to cover all variations and modifications falling within the scope and boundaries of the appended claims, or equivalent forms of such scope and boundaries.
Claims
1. An environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation system, characterized in that, This includes environmental semantic-aware base stations, communication access points, and user equipment, among which: The environmental semantic awareness base station is used to collect environmental images, process the images to extract environmental semantic information, and broadcast the environmental semantic information through a broadcast channel. The environmental semantic information includes at least the location and movement characteristics of the communication access point, the user equipment, and the scattering object. The communication access point is used to receive the environmental semantic information, determine the channel's time delay parameters and Doppler frequency shift parameters based on the environmental semantic information, generate a low-overhead pilot structure based on the time delay parameters and Doppler frequency shift parameters, and use the low-overhead pilot structure to perform orthogonal time-frequency spatial modulation to transmit signals. The low-overhead pilot structure is implemented by setting guard intervals only at time delay-Doppler grid points that may be subject to interference, as determined by the time delay parameters and Doppler frequency shift parameters. The user equipment is configured to obtain the environmental semantic information by listening to the broadcast channel, receive the signal and perform orthogonal time-frequency spatial demodulation, and estimate the channel coefficient by performing point-by-point division between the received pilot signal and the known transmitted pilot signal based on the time delay-Doppler grid point positions determined by the environmental semantic information.
2. The system according to claim 1, characterized in that, The environmental semantic awareness base station processes the image to extract environmental semantic information, including: The image is used to perform target recognition to identify the communication access point, the user equipment, and the scattering object, and to obtain their position and movement characteristics.
3. The system according to claim 1, characterized in that, The communication access point determines the channel's time delay parameters and Doppler frequency shift parameters based on the environmental semantic information, including: For line-of-sight links, according to the formula and Calculate, where, , representing the distance of the LOS link between the communication access point and the user equipment at time index n. and These represent the estimated positions of the communication access point and the user equipment at time index n, respectively, where c represents the speed of light. It is the relative speed between the communication access point and the user equipment at time index n. f is the angle between the direction of the connection between the communication access point and the user equipment and the speed direction. c It is the carrier frequency; For non-line-of-sight links, according to the formula and Calculate, where, It is the segment number of the p-th path. It is the length of the i-th segment of the p-th path. It is the relative velocity of the i-th segment. It is the angle between the direction of the i-th segment and the direction of the velocity.
4. The system according to claim 1, characterized in that, The user equipment performs a point-by-point division operation between the received pilot signal and the known transmitted pilot signal to estimate the channel coefficients, including: The channel coefficients are estimated using the following formula: ， in, , For the number of paths, These represent the Doppler and time delay taps estimated based on environmental semantics, respectively.
5. The system according to claim 1, characterized in that: The environmental semantic awareness base station periodically collects and processes environmental images to continuously update the environmental semantic information; The communication access point dynamically adjusts the design of the low-overhead pilot structure based on the received updated environmental semantic information; The user equipment adaptively performs channel estimation at the corresponding delay-Doppler grid point locations based on the acquired updated environmental semantic information.
6. An environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method, executed by a communication access point, characterized in that, include: Acquire environmental semantic information, which includes the position and movement characteristics of transmitters, receivers and scatterers in the communication link; Based on the environmental semantic information, the channel's time delay parameters and Doppler frequency shift parameters are determined. Based on the time delay parameters and Doppler frequency shift parameters, a low-overhead pilot structure is designed, wherein a protection interval is set only at the time delay-Doppler grid points that may be subject to interference, as determined by the time delay parameters and Doppler frequency shift parameters. The low-overhead pilot structure is used to construct the transmission signal, which is then transmitted after orthogonal time-frequency spatial modulation.
7. The method according to claim 6, characterized in that, The design of the low-overhead pilot structure based on the time delay parameter and Doppler frequency shift parameter includes: Place the pilot symbols in the coordinates of the time-delay-Doppler grid. Place; After passing through the channel, the pilot symbols will be mapped to grid point locations. ,in ; The grid point positions that may interfere with the shifted pilot symbols. Set as a protection interval, where , This represents the number of paths.
8. The method according to claim 6, characterized in that, The determination of the channel's time delay parameters and Doppler frequency shift parameters based on the environmental semantic information includes: Based on the location information in the environmental semantic information, the transmission distance of each communication path between the communication access point and the user equipment is calculated, and the time delay parameter is obtained based on the speed of light. The communication path includes line-of-sight path and non-line-of-sight scattering path. Based on the mobility characteristic information in the environmental semantic information, the relative velocity is calculated and combined with the carrier frequency to obtain the Doppler frequency shift parameter.
9. An environment semantic awareness-assisted orthogonal time-frequency spatial channel estimation method, executed by a user equipment, characterized in that, include: Obtain environmental semantic information, which is used to determine the channel's time delay parameters and Doppler frequency shift parameters; The parameters are determined based on the environmental semantic information; Receive signals from a communication access point, the signals being generated using a low-overhead pilot structure designed based on the time delay parameters and the Doppler frequency shift parameters and modulated by orthogonal time-frequency space; The received signal is subjected to orthogonal time-frequency spatial demodulation, and at the time-delay-Doppler grid point positions determined by the time delay parameter and the Doppler frequency shift parameter, the demodulated received pilot signal is divided point by point with the locally known transmitted pilot signal to estimate the channel coefficient.
10. The method according to claim 9, characterized in that, The acquisition of environmental semantic information includes: By monitoring the broadcast channel of the environmental semantic awareness base station, the environmental semantic information or the time delay parameters and Doppler frequency shift parameters determined based on it can be obtained.