Channel activity detection method, device and medium based on nonlinear chirp spread spectrum signal

Abstract

The present invention discloses a channel activity detection method, device, and medium based on nonlinear chirp spread spectrum signals, comprising: designing a beacon based on a global channel occupancy matrix of gateway information and periodically sending it to nodes; designing a channel occupancy matrix based on historical channel access information of terminal nodes; combining the global channel occupancy matrix and the channel occupancy matrix at the nodes in a weighted summation manner to obtain a joint matrix of transmission channel information; designing an access control strategy based on a distributed frame interval mechanism and a random backoff mechanism at the nodes, utilizing the joint matrix to rationally select transmission parameters, and performing collision-free transmission of multi-node data. The present invention utilizes the combination of information between the gateway and the terminal nodes to effectively avoid node information collisions and save network energy consumption. The implementation method is simple and clear, and has practical value.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a channel activity detection method, device and medium based on nonlinear chirp spread spectrum signals. Background Art

[0002] With the widespread application of IoT technology in industrial monitoring, smart agriculture, smart grids, and other fields, wireless communication systems must achieve efficient channel access and resource management in environments with high node density and strong electromagnetic interference. Traditional linear chirp spread spectrum (CSS) technology is widely used in low-power wide area networks (LPWANs) due to its advantages in multipath interference resistance and high spectrum utilization. However, its practical application still faces the following key issues:

[0003] 1) Insufficient channel bit error rate and sensitivity

[0004] The spectral structure of linear chirp signals is fixed, and their ability to resist multipath interference depends on spread-spectrum gain. However, in complex electromagnetic environments (such as multipath reflection and Rayleigh fading), the time-frequency offset caused by signal superposition can significantly reduce the signal-to-noise ratio (SNR), leading to an increase in bit error rates. Traditional channel sensing methods based on energy detection or matched filtering have difficulty accurately distinguishing weak signals from noise, resulting in a high probability of channel misjudgment.

[0005] 2) Poor dynamic channel adaptability

[0006] Linear chirp signals have a fixed frequency modulation slope and cannot flexibly adapt to dynamic channel changes (such as rapid fading or multipath delay spread). In scenarios where multiple nodes share a channel, traditional methods require sacrificing detection time or increasing the sampling rate to improve accuracy, which conflicts with the low power requirements of IoT devices.

[0007] 3) Low efficiency of multi-node collaboration

[0008] Existing multi-node channel access protocols (such as ALOHA and CSMA) rely on single-point channel status perception and lack inter-node collaboration mechanisms, which leads to intensified channel contention and further deterioration of system throughput and reliability.

[0009] The innovation of this invention lies in the proposed method, device, and medium for channel activity detection based on nonlinear chirp spread spectrum signals. By introducing nonlinear frequency modulation (e.g., secondary frequency modulation) to expand the signal's time-frequency characteristics, this method significantly improves channel resolution and interference rejection, thereby reducing bit error rates and optimizing channel sensing efficiency. Furthermore, by integrating a distributed node collaboration mechanism, this method enables real-time sharing and joint detection of dynamic channel states, providing reliable communication support for high-density IoT networks. Summary of the Invention

[0010] This invention proposes a channel activity detection method, device, and medium based on nonlinear chirped spread spectrum signals. This method effectively reduces collision probability and saves device energy consumption. It utilizes the Distributed Interframe Spacing (DIFS) mechanism within the Distributed Coordination Function (DCF) and employs a fixed number of Channel Activity Detectors (CADs) to complete each DIFS time slot. To effectively meet the requirements of low collision and low energy consumption, this invention incorporates a terminal adaptive mechanism to dynamically select the appropriate channel / span frequency (CH / SF) combination for transmission. Furthermore, this invention proposes a method for analyzing the gateway's global view to minimize access collisions and energy consumption.

[0011] The object of the present invention is achieved through the following technical solutions:

[0012] A channel activity detection method based on nonlinear chirp spread spectrum signal comprises the following steps:

[0013] Step 1: At the gateway, a nonlinear chirp beacon with a global channel occupancy matrix is ​​defined. The node extracts the time-frequency features through matched filtering and periodically sends them to the network nodes.

[0014] Step 2: At the terminal node, the local channel occupancy matrix is ​​updated based on historical detection data. The cross-correlation of nonlinear chirps is used to correct the false detection probability and define a channel occupancy matrix that reflects the degree of channel / spreading factor congestion.

[0015] Step 3: At the terminal node, the global channel occupancy matrix and the channel occupancy matrix are combined using the element weighted sum method to obtain a joint matrix that fully reflects the transmission channel information;

[0016] In step 4, each node implements an access control strategy based on the distributed frame interval mechanism and designs a fixed number of channel activity detectors to complete the detection of each distributed frame interval mechanism time slot. Channel activity detection is performed in the distributed frame interval mechanism time slot. When the detection results are all idle, a backoff number is randomly generated and the random backoff mechanism phase is entered. In the random backoff mechanism phase, the channel availability is detected by the channel activity detector, and the backoff number is changed by decreasing it one by one. When the backoff number reaches 0, the node transmits data normally.

[0017] In step 5, for nodes applying for access at the same stage, the channel / spreading factor is adjusted according to the joint matrix obtained in step 3. Finally, according to step 4, the access control of multiple nodes is completed, and channel activity detection is finally realized.

[0018] Furthermore, in step 1, the global channel occupancy matrix is ​​a matrix of size = number of channels × number of spreading factors, where each matrix element represents the contention level under given channel / spreading factor conditions; the global channel occupancy matrix is ​​transmitted using time-sharing beacons through a predefined feedback channel, and the beacon needs to include the ID of the gateway sending the beacon to cope with the situation where a node receives overlapping coverage from two or more gateways.

[0019] Furthermore, in step 2, the channel occupancy matrix is ​​a matrix of size = number of channels × number of spreading factors, wherein each matrix element represents the historical utilization under given channel / spreading factor conditions; the channel occupancy matrix utilizes information of failed distributed inter-frame mechanisms and random back-off operations to achieve indirect channel detection; each node maintains historical information about the congestion levels of previously detected channel / spreading factor combinations; the channel occupancy matrix is ​​updated using a channel occupancy adaptive algorithm after each failed channel activity detection, wherein the channel occupancy adaptive algorithm determines a congestion status information dataset by collecting information from each failed channel activity detection, and adjusts and updates the congestion status information dataset in an appropriate proportion based on the proportion of the number of channel activity detections to the total number of detections.

[0020] Furthermore, in step 3, the process of combining the global channel occupancy matrix with the channel occupancy matrix adopts the weighted sum of the elements of the two matrices.

[0021] Furthermore, in step 4, for each node, when all channel activity detectors of a distributed frame interval mechanism time slot report that the channel is idle, a random backoff number is generated and the random backoff mechanism phase is entered; in the random backoff mechanism phase, the backoff number is reduced by 1 each time the channel activity detector of the node reports that the channel is idle; the node will continuously check the availability of the channel. If the channel is occupied, the node will reset to the distributed frame interval mechanism state. In this case, the node needs to wait for an idle channel again and resume the countdown of the backoff number; finally, when the backoff number is reduced to zero, the node starts to transmit data normally.

[0022] Furthermore, in step 5, while a node is performing step 4, another node senses that the channel is busy based on the joint matrix in step 3 and reselects a better channel / spreading factor channel. It continues the detection process according to step 4. If the detection is successful, it sends normally. Otherwise, it updates the joint matrix and selects again.

[0023] The present invention also provides a channel activity detection device based on nonlinear chirp spread spectrum signals, comprising one or more processors for implementing the above-mentioned channel activity detection method based on nonlinear chirp spread spectrum signals.

[0024] The present invention also provides a readable storage medium having a program stored thereon. When the program is executed by a processor, the channel activity detection method based on the nonlinear chirped spread spectrum signal as described above is implemented.

[0025] Compared with the prior art, the present invention has the following advantages:

[0026] 1. This invention effectively avoids channel conflicts by using a distributed interframe space (DIFS) mechanism and a random backoff (BO) mechanism, improving the packet reception rate (PRR) and network throughput. Compared to the traditional ALOHA protocol, it can maintain a PRR of up to 90% when communication demand increases, and achieve a 1.5x improvement in throughput.

[0027] 2. Based on the unique star network topology of nonlinear chirp spread spectrum signals, the present invention enables nodes and gateways to collaborate with each other. The gateways regularly broadcast global channel information, and the nodes combine local information to guide channel selection before transmission, further improving network performance and achieving more balanced channel load selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a flow chart of a channel activity detection method based on nonlinear chirp spread spectrum signals of the present invention.

[0029] Figure 2 The figure is a schematic structural diagram of a channel activity detection device based on nonlinear chirp spread spectrum signal according to the present invention.

[0030] Figure 3 It is a working principle diagram of a simulation example of the present invention. DETAILED DESCRIPTION

[0031] The technical solutions and effects of the present invention are further described in detail below with reference to the accompanying drawings.

[0032] Before introducing the channel activity detection method based on nonlinear chirped spread spectrum signals provided by the present invention, the concept of channel activity detection (CAD) is briefly introduced.

[0033] As a key technology in the Carrier Sense Multiple Access (CSMA) protocol, Channel Activity Detection (CAD) has long been a focus of academic research. Existing LoRa node chips all have CAD functionality. By monitoring signals for 2 to 3 symbol lengths and using coherent demodulation to determine whether they represent the current code and channel data, and thus whether the channel is occupied, CAD offers low power consumption and a low collision probability.

[0034] The above-mentioned channel activity detection method is commonly used in LoRa ad hoc or private networks. For networks that transmit nonlinear chirp signals, traditional methods often use ALOHA random access, which faces a series of challenges such as high collision probability and low transmission efficiency. To address these challenges, this paper proposes a channel activity detection method based on nonlinear chirp spread spectrum signals by coordinating the synchronous fusion of terminal node and gateway information, utilizing the Distributed Interframe Time (DIFS) mechanism and the Random Back-off (BO) mechanism. Please refer to the [Note: The original text is incomplete and should be omitted.] Figure 1 , the implementation steps of the present invention are as follows:

[0035] Step 1: At the gateway, a beacon based on the channel occupancy matrix Ψ of the entire channel utilization state is designed and periodically sent to network nodes.

[0036] Among them, the global channel occupancy matrix Ψ is of size N CH ×N SF A matrix where each matrix element Ψ CH,SF Indicates the contention level under given channel / spreading factor (CH / SF) conditions, N CH With N SF Represent the values ​​of CH and SF, respectively. The matrix Ψ reflects the current channel occupancy. Matrix Ψ uses time-sharing beacons transmitted over a predefined feedback channel. Given the lack of strict clock synchronization between nodes, clock drift may prevent nodes from properly receiving beacons. Therefore, the gateway needs to send multiple beacons consecutively to increase the probability of reception at the end node. The beacon must include the gateway ID to address situations where a node receives overlapping coverage from two or more gateways.

[0037] Step 2: At the terminal node, the local channel occupancy matrix Γ is updated based on the historical detection data, the cross-correlation of nonlinear chirp is used to correct the false detection probability, and a channel occupancy matrix Γ is defined to reflect the congestion level of the channel / spreading factor (CH / SF combination). The channel occupancy matrix Γ is a matrix of size N CH ×N SF A matrix where each element γ CH,SF represents the historical utilization under the given CH / SF conditions. The matrix Γ uses the information of the failed distributed frame interval mechanism and the random backoff operation to achieve indirect channel detection. Each node maintains the historical information about the congestion of the CH / SF combination detected in the past. The matrix Γ is replaced by Update, where α is the updated proportion of the node's congestion status information dataset, CAD busy CAD is the number of times the channel activity detects channel occupancy. total is the total number of detections. In order to ensure high correlation of the recently sensed channels, α is set to 0.85.

[0038] Step 3: At the terminal node, the global channel occupancy matrix Ψ is combined with the channel occupancy matrix Γ using the element-wise weighted sum method to obtain a joint matrix that fully reflects the transmission channel information. The joint matrix effectively utilizes the global view provided by the gateway while preserving the node's own historical characteristics.

[0039] For a node, there are CH / SFs that have not yet been detected for channel activity, and γ in the Γ matrix CH,SF Some elements of remain empty, failing to accurately reflect the channel state. Compensating for the local view at the node by using the gateway's global channel view effectively eliminates the empty elements of the Γ matrix. The merging of the Ψ and Γ matrices uses a weighted sum strategy, with elements in Γ weighted at 0.7 and elements in Ψ weighted at 0.3. This strategy better reflects the combined state of all CH / SFs in real time while preserving the node's historical information.

[0040] Step 4: Each node implements an access control strategy based on the Distributed Interframe Space (DIFS) mechanism and designs a fixed number of Channel Activity Detectors (CADs) to complete each DIFS time slot detection. CAD detection is performed in the DIFS time slot. If all detection results are idle, a random return number (N) is generated. BO value) and enters the random backoff mechanism phase (BO phase). In the BO phase, CAD is used to detect channel availability and change N BO The final value of N BO When it is 0, the node transmits data normally.

[0041] Among them, for a single terminal node, it is necessary to confirm the status of the CH / SF for each transmission, and it can only be transmitted when it is in the idle state. The confirmation process introduces the distributed interval frame space (DIFS) mechanism to control the node to wait for a period of time before transmitting data. If the channel is detected to be idle in the time slot of the distributed frame interval mechanism, the node will enter the transmission state, otherwise it will continue to wait. When all CADs of a time slot of a distributed frame interval mechanism are reported as idle, it enters the BO phase. In the random backoff mechanism phase, a random backoff value N is generated. BO , the value range is [4,64]. Each time the node CAD reports that the channel is idle, N BO The value is reduced by 1. The initial fallback value N of randomization BO The possibility of two or more frames colliding is reduced. The node will continuously check the availability of the channel. If the channel is occupied, the node will reset to the DIFS state. In this case, the node needs to wait for an idle channel again and resume the N BO The countdown. Finally, when N BO When it decreases to zero, the node starts transmitting data normally.

[0042] Step 5: For nodes applying for access in the same phase, adjust CH / SF according to the joint matrix λ obtained in step 3. Finally, according to step 4, complete the access control of multiple nodes and finally realize CAD detection.

[0043] Considering scenarios where multiple end nodes select the same CH / SF, while a single node is performing step 4, another node detects the channel status based on the channel information from step 3. If the channel status is determined to be busy, it reselects a better performing CH / SF in the merged matrix and continues the detection process according to step 4. If the detection is successful, transmission proceeds normally; otherwise, the merged matrix information is updated and the selection is repeated. From the node's perspective, the number of CADs required for each transmission and the associated time and energy consumption are reduced, thus avoiding channel collisions.

[0044] According to the above corresponding steps, the channel activity detection method based on the nonlinear chirp spread spectrum signal can be completed.

[0045] This invention utilizes a distributed interframe space (DIFS) mechanism and a random backoff (BO) mechanism to effectively resolve channel conflicts. Compared to the traditional ALOHA protocol, it improves the packet reception rate (PRR) and network throughput. Furthermore, this invention enables node-gateway collaboration. Gateways regularly broadcast global channel information, combined with local node information, to guide channel selection before transmission, further improving network performance and achieving more balanced channel load selection.

[0046] See also Figure 2 An embodiment of the present invention provides a channel activity detection device based on a nonlinear chirp spread spectrum signal, comprising one or more processors for implementing a channel activity detection method based on a nonlinear chirp spread spectrum signal in the above embodiment.

[0047] An embodiment of a channel activity detection device based on a nonlinear chirped spread spectrum signal of the present invention can be applied to any device with data processing capabilities, and the device with data processing capabilities can be a device or apparatus such as a computer. The device embodiment can be implemented through software, or through hardware or a combination of software and hardware. Taking software implementation as an example, as a device in a logical sense, it is formed by the processor of any device with data processing capabilities in which it is located reading the corresponding computer program instructions in the non-volatile memory into the internal memory for execution. From the hardware level, if Figure 2 As shown in FIG. 1 , a hardware structure diagram of a device having data processing capability in which a channel activity detection device based on nonlinear chirped spread spectrum signal of the present invention is located, except for Figure 2In addition to the processor, memory, network interface, and non-volatile memory shown, any device with data processing capabilities in the embodiment may also include other hardware according to the actual function of the device with data processing capabilities, which will not be described in detail.

[0048] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0049] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0050] An embodiment of the present invention further provides a readable storage medium having a program stored thereon. When the program is executed by a processor, the channel activity detection method based on nonlinear chirped spread spectrum signals in the above embodiment is implemented.

[0051] The readable storage medium may be an internal storage unit of any device with data processing capabilities described in any of the aforementioned embodiments, such as a hard disk or memory. The readable storage medium may also be an external storage device, such as a plug-in hard disk, a smart media card (SMC), an SD card, a flash card, etc. equipped on the device. Furthermore, the readable storage medium may also include both an internal storage unit and an external storage device of any device with data processing capabilities. The readable storage medium is used to store the computer program and other programs and data required by any device with data processing capabilities, and may also be used to temporarily store data that has been output or is to be output.

[0052] The terms used in one or more embodiments of this specification are for the purpose of describing specific embodiments only and are not intended to limit one or more embodiments of this specification. The singular forms "a," "an," "the," and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0053] It should be understood that although the terms first, second, third, etc. may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when..." or "when..." or "in response to determining."

[0054] The effect of the method proposed in the present invention is further described below with reference to a simulation example.

[0055] Simulation example:

[0056] like Figure 3 As shown, the channel detection process of two nodes and a gateway in the same network in the network topology is taken as an example to illustrate the marking.

[0057] (1) Node A opens the send window, informs the gateway of the need to send data, and configures a series of parameters such as CH / SF.

[0058] (2) The gateway receives the sending request from node A and sends its own global channel occupancy matrix Ψ and its number information to node A.

[0059] (3) Node A receives the information from the gateway, performs a weighted update on it and its own local channel occupancy matrix Γ, and reconfigures the parameters. In this example, CH=1, SF=7.

[0060] (4) Node A performs channel activity detection in the DIFS phase. When all CAD reports of a distributed frame interval mechanism time slot are idle, it enters the random backoff mechanism phase and generates a random backoff value N. BO , in this example, N BO =2.

[0061] (5) In the random backoff mechanism phase, each time CAD reports that the channel is idle, N BO The value is reduced by 1. Finally, when N BO When it decreases to zero, node A opens the transmission window and starts transmitting data to the gateway normally.

[0062] (6) Node B configured its parameters before receiving the gateway information (in this example, CH=1, SF=7). It then updated the parameters after receiving the gateway information. Since Node A selected CH=1, SF=7 before Node B, the selected channel is busy at this time. Therefore, Node B uses the channel information it received to reconfigure its parameters (in this example, CH=2, SF=7).

[0063] (7) Node B performs channel activity detection in the DIFS phase. When all CAD reports of a distributed frame interval mechanism time slot are idle, it enters the random backoff mechanism phase and generates a random backoff value N BO , in this example, N BO =3.

[0064] (8) During the random backoff phase, each time CAD reports that the channel is idle, N BO The value is reduced by 1. Finally, when N BO When it decreases to zero, node B opens the transmission window and starts transmitting data to the gateway normally.

[0065] The example process described above builds a topology on ns-3 and implements the entire process using a Python script. Experimental results show that, compared to the traditional ALOHA method, this method effectively reduces node collision probability, improves network throughput, and reduces node energy consumption.

[0066] The above description is only a preferred embodiment of the present invention. Although the present invention has been disclosed as a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can use the above disclosed methods and technical contents to make many possible changes and modifications to the technical solution of the present invention without departing from the scope of the technical solution of the present invention, or modify it into an equivalent embodiment with equivalent changes. Therefore, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of protection of the technical solution of the present invention.

Claims

1. A channel activity detection method based on nonlinear chirp spread spectrum signal, characterized in that: The following steps are involved: Step 1: At the gateway, a nonlinear chirp beacon with a global channel occupancy matrix is ​​defined. The node extracts the time-frequency features through matched filtering and periodically sends them to the network nodes. Step 2: At the terminal node, the local channel occupancy matrix is ​​updated based on historical detection data. The cross-correlation of nonlinear chirps is used to correct the false detection probability and define a channel occupancy matrix that reflects the degree of channel / spreading factor congestion. Step 3: At the terminal node, the global channel occupancy matrix and the channel occupancy matrix are combined using the element weighted sum method to obtain a joint matrix that fully reflects the transmission channel information; In step 4, each node implements an access control strategy based on the distributed frame interval mechanism and designs a fixed number of channel activity detectors to complete the detection of each distributed frame interval mechanism time slot. Channel activity detection is performed in the distributed frame interval mechanism time slot. When the detection results are all idle, a backoff number is randomly generated and the random backoff mechanism phase is entered. In the random backoff mechanism phase, the channel availability is detected by the channel activity detector, and the backoff number is changed by decreasing it one by one. When the backoff number reaches 0, the node transmits data normally. In step 5, for nodes applying for access at the same stage, the channel / spreading factor is adjusted according to the joint matrix obtained in step 3. Finally, according to step 4, the access control of multiple nodes is completed, and channel activity detection is finally realized.

2. The channel activity detection method based on nonlinear chirped spread spectrum signal according to claim 1, characterized in that: In step 1, the global channel occupancy matrix is ​​a matrix of size = number of channels × number of spreading factors, where each matrix element represents the contention level under given channel / spreading factor conditions; the global channel occupancy matrix is ​​transmitted using time-sharing beacons through a predefined feedback channel. The beacon needs to contain the ID of the gateway sending the beacon to deal with the situation where a node receives overlapping coverage from two or more gateways.

3. The channel activity detection method based on nonlinear chirped spread spectrum signal according to claim 1, characterized in that: In step 2, the channel occupancy matrix is ​​a matrix of size number of channels × number of spreading factors, where each matrix element represents the historical utilization under given channel / spreading factor conditions; The channel occupancy matrix uses the information of failed distributed inter-frame mechanisms and random back-off operations to achieve indirect channel detection; each node maintains historical information about the congestion level of the channel / spreading factor combinations detected in the past; The channel occupancy matrix is ​​updated using a channel occupancy adaptive algorithm after each failed channel activity detection. The channel occupancy adaptive algorithm collects information from each failed channel activity detection to determine the congestion status information dataset. The algorithm then adjusts and updates the congestion status information dataset in an appropriate proportion based on the proportion of channel activity detections to the total number of detections.

4. The channel activity detection method based on nonlinear chirped spread spectrum signal according to claim 1, characterized in that: In step 3, the global channel occupancy matrix is ​​combined with the channel occupancy matrix by taking the weighted sum of the elements of both matrices.

5. The channel activity detection method based on nonlinear chirped spread spectrum signal according to claim 1, characterized in that: In step 4, for each node, when all channel activity detectors of a distributed frame interval mechanism time slot report that the channel is idle, a random backoff number is generated and the random backoff mechanism phase is entered; in the random backoff mechanism phase, the backoff number is reduced by 1 each time the channel activity detector of the node reports that the channel is idle; the node continuously checks the availability of the channel. If the channel is occupied, the node resets to the distributed frame interval mechanism state. In this case, the node needs to wait for an idle channel again and resume the countdown of the backoff number; finally, when the backoff number is reduced to zero, the node starts to transmit data normally.

6. The channel activity detection method based on nonlinear chirped spread spectrum signal according to claim 1, characterized in that: In step 5, while a node is performing step 4, another node senses that the channel is busy based on the joint matrix in step 3. It will reselect a better channel / spreading factor channel and continue detection according to the process in step 4. If the detection is successful, it will send normally. Otherwise, it will update the joint matrix and select again.

7. A channel activity detection device based on nonlinear chirped spread spectrum signal, characterized in that: The system comprises one or more processors, configured to implement a channel activity detection method based on a nonlinear chirped spread spectrum signal according to any one of claims 1 to 6.

8. A readable storage medium, characterized in that: A program is stored thereon, and when the program is executed by a processor, a channel activity detection method based on a nonlinear chirped spread spectrum signal according to any one of claims 1 to 6 is implemented.

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