Information age minimization method and device for opportunistic channel access system

Abstract

The invention relates to the technical field of Internet of Things wireless communication, in particular to an information age minimization method and device for an opportunistic channel access system, the system comprises a base station and N Internet of Things devices, and the method comprises the following steps: each active device competes for a channel access right in a discrete time slot with a competition probability p; the winning device evaluates the channel gain and calculates the unloading rate, and decides whether to access according to the comparison with an unloading rate threshold r; the accessed equipment unloads data to the base station; the base station calculates the average information age in the observation period; and p and r optimized by a hierarchical iteration solving algorithm are fed back to each piece of Internet of Things equipment. Through joint optimization of two parameters and combination of an opportunity channel access mechanism, the defects that information freshness is insufficient and a non-convex problem is difficult to solve are overcome, the channel utilization efficiency is improved, and the method is suitable for a multi-device real-time data transmission scene.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) wireless communication technology, and in particular to a method and apparatus for minimizing information age in an opportunistic channel access system. Background Technology

[0002] In recent years, the Internet of Things (IoT) technology has developed rapidly, giving rise to a series of intelligent applications such as smart homes, connected vehicles, and smart industries. In these applications, multiple mobile devices need to transmit environmental sensing data (such as temperature, humidity, and equipment operating speed) to base stations via wireless links, and are extremely sensitive to end-to-end latency of the data. This is because the sensor data needs to be kept highly up-to-date to support real-time monitoring, decision-making, and automated control.

[0003] In traditional wireless communication systems, performance is typically measured using metrics such as latency and link throughput. However, these metrics cannot accurately depict the freshness of data from its generation to its reception by the base station. Therefore, information age has been proposed as a new performance metric: information age represents the time elapsed since the latest data held by the base station at a given moment was generated. A lower information age value indicates fresher data and is a core standard for measuring the effectiveness of real-time data.

[0004] To coordinate wireless access between multiple mobile devices and a base station, multiple access technologies are needed. Distributed multiple access technologies (such as ALOHA, sALOHA, and CSMA) are particularly attractive for IoT mobile devices with relatively simple structures. This is because they avoid the excessive signaling interactions that might occur between each mobile device in a centralized multiple access protocol, thus saving communication overhead, and allow each mobile device to access the base station by competing for exclusive use of the public wireless medium. However, common distributed multiple access technologies ignore the different channel conditions among multiple mobile devices. In fact, compared to the channel being utilized by mobile devices with good channel conditions, it results in a waste of spectrum opportunities when mobile devices with poor channel conditions preempt the channel. Granting such mobile devices exclusive use of the wireless medium is inefficient. To overcome this drawback, opportunistic channel access has emerged as an improved solution. In opportunistic channel access, a mobile device will only access the wireless medium when the channel gain between the mobile device that preempts the channel and the base station exceeds a certain threshold.

[0005] Existing research on information freshness related to multiple access problems mainly focuses on centralized multiple access or common distributed multiple access, neglecting opportunistic channel access. Furthermore, existing research on opportunistic channel access does not consider the minimization of information freshness, failing to meet the data freshness requirements of real-time IoT applications. Simultaneously, the problem of minimizing information age is inherently non-convex, making direct optimization of parameters such as device contention probability and offloading rate thresholds extremely difficult, lacking efficient solution schemes. Summary of the Invention

[0006] The purpose of this invention is to provide a method and apparatus for minimizing information age in an opportunistic channel access system, which solves the problems of insufficient information freshness and difficulty in solving optimization problems in the opportunistic channel access scenario in the prior art, and achieves the dual goals of minimizing average information age and improving channel utilization efficiency.

[0007] To achieve the above objectives, the present invention provides the following technical solution: According to one aspect of the present invention, a method for minimizing information age in an opportunistic channel access system is provided, 1. the system includes a base station and multiple Internet of Things (IoT) devices, the method comprising the following steps: S1: During the channel contention phase, the contention time of each round is divided into discrete time slots of equal length. In each time slot, each active IoT device continuously and independently competes for the channel access right with a competition probability p until a unique winner emerges. S2: The winning IoT device evaluates the channel state to obtain the instantaneous channel gain, uses the instantaneous channel gain to obtain the offloading rate with the base station, and makes an access decision based on the offloading rate and the offloading rate threshold r. S3: The winning IoT device accepts the channel access right and offloads the observation data to the base station; S4: After the base station receives all the observation data from the IoT devices, it calculates the information age within the observation period; S5: Construct an optimization problem that minimizes the average information age, optimize the competition probability p and the unloading rate threshold r through a hierarchical iterative solution algorithm, and update the optimized competition probability p and unloading rate threshold r to each IoT device.

[0008] According to one embodiment of the present invention, in step S1, when the nth round includes n active devices, the probability of a single device winning is: The feasible region of the competition probability p is (0,1). During the competition process, if zero or more devices send access requests, it is determined that no device can access or there is a conflict, and the competition will start again in the next time slot.

[0009] According to an embodiment of the present invention, in step S2, the instantaneous channel gain Rayleigh fading follows an independent and identically distributed distribution, and its probability density function is: ,in The distributed parameters are estimated using historical channel gain measurements; the offloading rate R is calculated based on Shannon's formula, expressed as: ,in, To unload power from the equipment, Let B be the noise power spectral density and B be the channel bandwidth.

[0010] According to an embodiment of the present invention, in step S2, the access decision determination rule includes: if the offloading rate The winning IoT device relinquishes its channel access right and returns to step S1; if The winning IoT device accepts the channel access right and proceeds to step S3; the probability of the IoT device accepting the channel access right is... The feasible region of r is , This is a predefined rate limit.

[0011] According to one embodiment of the present invention, in step S3, the time span for data unloading is... D represents the amount of data from a single observation. Let be the number of contention attempts for the first successful access to the channel in the nth round, following the parameter . The geometric distribution; the total time span of the nth round is determined by the unloading time. and competition time The composition, and the competition time, are expressed as: ,in, The time slot length, The number of time slots required for the k-th competition follows the parameter: , independent and identically distributed geometric random variables.

[0012] According to an embodiment of the present invention, in step S4, the calculation process of information age specifically includes: Total observation period duration: ; The sum of information for the nth round is: ,in ; The summation information age Q for a single observation period is: ; Obtain the average information age over a long period of time: ,in This indicates the expected operation.

[0013] According to an embodiment of the present invention, in step S5, the hierarchical iterative solution algorithm employs the Dinkelbach algorithm for outer-layer iteration, the BCD algorithm for middle-layer iteration, and the Polyblock algorithm for inner-layer optimization, specifically including: The Dinkelbach outer iteration transforms the fractional objective function into an equivalent linear objective function, and achieves iterative convergence by updating the parameter ξ. In the BCD mid-level iteration, the unloading rate threshold r is optimized by first fixing the contention probability p, and then the contention probability p is optimized by fixing the unloading rate threshold r. This process is repeated alternately until the convergence condition is met. Polyblock inner layer optimization transforms the non-convex subproblem into a monotonic optimization problem, solving for the optimal parameters of the competition probability p and the unloading rate threshold r by iteratively updating the point set.

[0014] According to one embodiment of the present invention, the convergence condition of the BCD iteration is: ; The convergence condition of the Dinkelbach iteration is: ;in To preset the convergence accuracy, , This indicates the expected operation.

[0015] According to one embodiment of the present invention, there are N Internet of Things (IoT) devices in the system. The N IoT devices observe the same object or area, and the observation content is different parts or different angles. The observation and data unloading are carried out in multiple rounds, and N rounds constitute an observation cycle. The device that has completed data unloading is inactive in subsequent rounds until the entire observation cycle ends.

[0016] On the other hand, the present invention also provides an information age minimization device for an opportunistic channel access system to implement the above-described method.

[0017] The device includes a contention module, a channel evaluation module, a data offloading module, and a parameter receiving module integrated into an IoT device, as well as a data receiving module, an information age calculation module, and a parameter optimization module integrated into a base station; wherein: The contention module is used to broadcast pilot signals with contention probability p in each time slot, participate in the contention for channel access rights, and receive feedback on the contention results; The channel evaluation module is used to evaluate the channel state after winning the right to use the channel to obtain the channel gain, calculate the offloading rate and compare it with the offloading rate threshold r to make an access decision. The data offloading module is used to transmit observation data to the base station after confirming access. The parameter receiving module is used to receive the optimized contention probability p and offloading rate threshold r sent by the base station and update the local parameters. The data receiving module is used to receive observation data transmitted by various IoT devices and record the data reception time. The information age calculation module is used to calculate the average information age of the system based on the observation period duration, the competition time of each round, and the unloading time. The parameter optimization module is used to construct an optimization problem that minimizes the average information age. It optimizes the competition probability p and the unloading rate threshold r through a hierarchical iterative solution algorithm and sends the optimization results to each IoT device.

[0018] This invention discloses a method and apparatus for minimizing information age in an opportunistic channel access system. By optimizing the device channel contention probability p and the offloading rate threshold r, combined with a hierarchical iterative solution algorithm, the average information age is minimized, while channel utilization efficiency is improved. The method is applicable to scenarios where multiple mobile devices transmit real-time sensing data to a base station, improving data freshness and channel utilization efficiency. Compared with existing technologies, the beneficial effects of this invention are: 1. Significantly improves data freshness. By jointly optimizing the contention probability p and offloading rate threshold r of IoT devices, the decrease in data freshness caused by IoT devices occupying the channel due to poor channel conditions can be effectively avoided. Compared with the existing ALOHA benchmark method (including unlimited retransmission, one-time limited retransmission, two-time limited retransmission, and no retransmission), the average information age is reduced by more than 50%; compared with the existing CSMA benchmark method, the average information age is reduced by more than 20%. Therefore, the method of this invention can better meet the data freshness requirements of real-time IoT applications.

[0019] 2. Significantly improved channel utilization efficiency. By combining opportunistic channel access mechanisms with parameter optimization strategies, spectrum resource waste is reduced, channel utilization efficiency is improved, and the shortcomings of traditional distributed multiple access technologies in ignoring differences in channel conditions are avoided.

[0020] 3. Achieved efficient solution to optimization problems. Addressing the non-convex nature of minimizing information age, a hierarchical iterative solution algorithm was designed. This algorithm decomposes complex non-convex problems into efficiently solvable subproblems. Compared to traditional exhaustive or global search methods, it significantly reduces computational complexity with minimal performance loss, making it suitable for resource-constrained IoT scenarios. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart of an information age minimization method for an opportunistic channel access system according to an embodiment of the present invention; Figure 2 This is a schematic diagram of an information age minimization device for an opportunistic channel access system according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the information age minimization process according to an embodiment of the present invention; Figure 4 This is a time slot diagram of the opportunistic channel access system according to an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the accumulation of information age within the observation period according to an embodiment of the present invention; Figure 6 The minimum average information age under different access methods in this embodiment of the invention and Comparison diagram. Detailed Implementation

[0022] To facilitate a clear description of the technical solutions in the embodiments of the present invention, the terms "first" and "second" are used to distinguish identical or similar items with essentially the same function and effect. For example, the first threshold and the second threshold are merely used to distinguish different thresholds and do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that the terms "first" and "second" are not necessarily different.

[0023] It should be noted that in this invention, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0024] In this invention, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one" or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, "at least one of a, b, or c" can represent: a, b, c, a combination of a and b, a combination of a and c, a combination of b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0025] like Figure 1 As shown, a flowchart of a method for minimizing information age in an opportunistic channel access system is presented. The method includes the following steps: S101: During the channel contention phase, the contention time of each round is divided into discrete time slots of equal length. In each time slot, each active IoT device continuously and independently competes for the channel access right with a contention probability p until a unique winner emerges. S102: The winning IoT device evaluates the channel state to obtain the instantaneous channel gain, uses the instantaneous channel gain to obtain the offloading rate with the base station, and makes an access decision based on the offloading rate and the offloading rate threshold r. S103: The winning IoT device accepts the channel access right and offloads the observation data to the base station; S104: After the base station receives all the observation data from the IoT devices, it calculates the information age within the observation period; S105: Construct an optimization problem that minimizes the average information age, optimize the competition probability p and the unloading rate threshold r through a hierarchical iterative solution algorithm, and update the optimized competition probability p and unloading rate threshold r to each IoT device.

[0026] like Figure 2 The diagram illustrates an information age minimization device for an opportunistic channel access system, comprising a base station and multiple IoT devices. This device implements the aforementioned method and includes a contention module, channel evaluation module, data offloading module, and parameter receiving module integrated into the IoT devices, and a data receiving module, information age calculation module, and parameter optimization module integrated into the base station; wherein: The contention module is used to broadcast pilot signals with contention probability p in each time slot, participate in the contention for channel access rights, and receive feedback on the contention results; The channel evaluation module is used to evaluate the channel state after winning the right to use the channel to obtain the channel gain, calculate the offloading rate and compare it with the offloading rate threshold r to make an access decision. The data offloading module is used to transmit observation data to the base station after confirming access. The parameter receiving module is used to receive the optimized contention probability p and offloading rate threshold r sent by the base station and update the local parameters. The data receiving module is used to receive observation data transmitted by various IoT devices and record the data reception time. The information age calculation module is used to calculate the average information age of the system based on the observation period duration, the competition time of each round, and the unloading time. The parameter optimization module is used to construct an optimization problem that minimizes the average information age. It optimizes the competition probability p and the unloading rate threshold r through a hierarchical iterative solution algorithm and sends the optimization results to each IoT device.

[0027] Assume an Internet of Things (IoT) system comprising one base station and N IoT devices. The N devices observe environmental sensing data and transmit the data to the base station via a shared wireless channel. In each observation period, the N devices compete for channel access rights in N rounds, with only one device winning and completing data offloading in each round.

[0028] These IoT devices form a collection The NSeveral IoT devices observe the same object or area, and this observation may be conducted on different parts or from different angles; then, the observation results are promptly offloaded back to the base station. Regarding observation offloading, all... N Each IoT node shares a bandwidth of B They use public channels to access the base station.

[0029] To ensure fair treatment of every IoT device and maintain the timeliness of observations, observation and data offloading are performed in multiple rounds according to... Figure 3 The process is as shown. In each round, only one IoT device gains exclusive access to the public channel for observation and data offloading. After completing the observation and data offloading, the winning IoT device remains inactive in subsequent rounds until all other IoT devices have offloaded their observation data to the base station. These rounds are labeled as rounds. and this N A cycle is defined as one observation period. At the end of an observation period, all of these... N All IoT devices are inactive, and another observation cycle will then begin. In one of the aforementioned cycles (let's say the [number]th cycle),... n In the wheel, there are n The IoT device has not yet offloaded its observation data to the base station, that is n An active IoT device will perform the following steps: Step 1: Divide the time range into time slots of equal length. In each time slot, this n A number of IoT devices with probability p Pilot broadcasts are used to compete for channel access until a single winner emerges. The following two scenarios will occur: Scenario 1: If just one device sends an access request, that device wins the right to use the channel.

[0030] Scenario 2: If there are zero or more device requests, it means there is no device access or a conflict, and the competition will resume in the next time slot.

[0031] In the first observation period, p takes its feasible region. In this setup, the probability of one device winning can be calculated. Specifically: (1) Step Two: The device that obtains channel access rights (i.e., the winner) performs channel state assessment, which is represented by channel gain or channel coefficient. The achievable offload rate R between the device and the base station is calculated using Shannon's formula. Comparing the offload rate R with the offload rate threshold r, the following two scenarios will occur: Scenario 1: At this point, the winning IoT device will relinquish its channel access right, and the system will return to step 1 to compete again.

[0032] Scenario 2: At this point, the IoT device will accept the channel access right and offload data to the base station.

[0033] Assume that the channel gain between each IoT device and the base station experiences independent and identically distributed Rayleigh fading. Furthermore, the channel gain of the winning IoT device also follows an independent and identically distributed pattern. Let represent the instantaneous channel gain between the IoT device that wins the i-th channel access right competition in the n-th round and the base station. It follows an exponential distribution, and its probability density function can be expressed as... ,in It is an indicator function. These are distribution parameters. About Since the channel gain from any IoT device to the base station follows the same distribution, it can be estimated by multiple historical measurements of these channel gains. .use The offload power of each IoT device is represented by... This represents the noise power spectral density. Then... It is the noise power on the base station side, and This is the signal-to-noise ratio (SNR) of the link between IoT devices and base stations. According to Shannon's formula, the maximum achievable link rate is: (2) As can be seen, if a device has poor channel conditions and a low link rate, it will delay data transmission throughout the entire system, thus increasing the data's information age. To limit the delay of data offloading, a threshold r is applied to the offloading rate, i.e., if... The winning IoT device will relinquish its channel access right. In this setup, the probability of accepting the channel access right can be calculated. : (3) To avoid wasting channel access opportunities, a predefined upper limit r is applied, denoted as r. Its feasible region is .like Figure 4 As shown, in the first observation period It can take any value within its feasible region. If the... The winning IoT device in this competition receives channel access rights and enters the data offloading phase. Assume that D Knights of data need to be offloaded from the winning IoT device to the base station. For a given round, such as round n, the start time and the end time of the observed offloading are defined as follows: and Then we can calculate the time span of the observed unloading (denoted as ). ): (4) It can be seen that the time span of one round (e.g., the nth round) is determined by the observed unloading time. Competition time for access rights (using) (This is represented as) the structure. Specifically, assuming that in the k-th competition of the n-th round, a winning IoT device needs to be selected and accept the channel access right, it requires... In a time slot, then It can be written as: (5) in It is an independent and identically distributed (i.e., i.i.d.) random variable, following a parameter of... The geometric distribution. And It is also a random variable that follows a geometric distribution, but with parameter . .

[0034] Step 3: Calculate the information age, update the channel contention probability p and the offloading rate threshold r, including the following sub-steps: Sub-step 31: After each observation period, the base station receives the latest data from all IoT devices and calculates the average information age at this time. .

[0035] Sub-step 32: Minimizing the average information age problem is a non-convex problem concerning the channel contention probability p and the offloading rate threshold r. Using the Dinkelbach and BCD methods, it is transformed into two non-convex subproblems that require iterative solutions. Each subproblem can then be transformed into a standard monotonic optimization problem.

[0036] Sub-step 33: Iteratively optimize p and r, return them to the IoT device, and return to the beginning of a new round of observations.

[0037] like Figure 5 As shown, after receiving information from IoT devices, the base station calculates the information age according to the definition above. According to the definition above, the time span C of an observation period can be expressed as: (6) Combination Figure 5 It can be seen that the total information age in the nth round is... It can be represented as: (7) At this point, the total information age over the entire observation period is Q: (8) To assess the average information age over a long period spanning multiple observation periods, a definition is provided. Let m be the cumulative information age of the m-th observation period. Let T be the number of observation periods contained within time T. Then, the average information age within time T can be expressed as: (9) when At that time, the average information age was expressed as: (10) To minimize average information freshness One objective is to optimize the competition probability p and the unloading rate threshold r, thus constructing the following optimization problem, namely Problem 1: (11) (12) (13) Because the objective function derived in equation (11) Since the expression is in fractional form, the Dinkelbach algorithm can be used to minimize the objective function. Specifically, the function F is defined as follows: (14) Therefore, problem 1 becomes problem 2: (15) Step 4: Use Dinkelbach iteration and the BCD algorithm to solve the non-convex optimization problem of minimizing the average information age with respect to the channel contention probability p and the offloading rate threshold r, to obtain new contention probabilities p and offloading rate threshold r. This includes the following sub-steps: Sub-step 41: Set initial parameters And initialize feasible solutions: .

[0038] calculate and ensure that it meets Set the outer iteration count. Convergence accuracy ,in This is the preset convergence accuracy.

[0039] Sub-step 42: If The initial solution of sub-step 41 is adopted; if Then the result of the previous iteration is used as the initial point: Set the middle-level iteration count. .

[0040] Sub-step 43: Fix ,optimization First, the critical point is obtained using the bisection method. Its purpose is to make Minimum speed. Then perform the following calculations: (16) (17) (18) (19) like Then take Proceed directly to sub-step 44 for Polyblock optimization. If... Then, Polyblock optimization needs to be performed on the following two intervals separately (i.e., sub-step 44 is applied): Interval 1 is Interval 2 is .

[0041] Sub-step 44: Define the initial point set Each point has two-dimensional elements. ,and Let the convergence threshold be set. .

[0042] Sub-step 45: For each Solve using the bisection method , making The following conditions must be met: (20) And order The optimal projection point index is then selected as follows: (twenty one) Then delete all points that satisfy the following conditions: (twenty two) If at this time Then select: (twenty three) Calculate the corresponding And generate two new points as follows: (twenty four) (25) Then add the two newly generated points to set B, and delete the original point. .

[0043] Repeat step 45 until... .

[0044] Sub-step 46: Output the final optimal projection point Calculate the corresponding optimal If there are multiple intervals, calculate them separately. and Take the smaller one as the optimal choice. .

[0045] Sub-step 47: Following the logic of sub-steps 43 to 46, and so on, fix the problem. Optimize p to obtain .

[0046] Sub-step 48: Based on the newly obtained and If the following conditions are met: (26) If BCD converges, proceed to sub-step 49; otherwise, let... Return to sub-step 43.

[0047] Sub-step 49: Update : (27) And order If the following conditions are met at this time: (28) The Dinkelbach algorithm then converges, and the final result is output: (29) In formula (29) and This refers to the probability of competition for IoT device usage in the next observation period. p With unloading rate threshold .

[0048] The system parameters for the simulation scenario are set as follows: The distance between the IoT device and the base station is 500 meters; the power spectral density of the noise is... Bandwidth is The carrier frequency is 4.8 GHz. Assume the instantaneous channel gain is caused by path loss. Rayleigh fading is determined by path loss. This can be calculated using the following formula (unit: dB). : (30) Where d is the distance between the transmitter and receiver, measured in kilometers. The frequency is in MHz. The average channel gain associated with Rayleigh fading is 1. The length of one time slot is... Milliseconds, and each observation The amount of data used by Knight. The above simulations were conducted on a desktop computer equipped with an Intel i9 12900K CPU running at 3.2 GHz. The information aging performance of the proposed method was compared with several benchmark methods that do not employ opportunistic channel access, including the sALOHA and CSMA protocols. Specifically, for the sALOHA protocol, the following methods need to be considered: (a) unrestricted retransmission method, (b) single-retransmission restricted method, (c) double-retransmission restricted method, and (d) no-retransmission method. Furthermore, for the CSMA protocol, the following method needs to be considered: (e) the CSMA method.

[0049] like Figure 6 As shown, the minimum average information age and its relationship under different access methods are given. Comparison diagram. The minimum average information age obtained by the method proposed in this invention and multiple benchmark methods is compared with... A comparison shows that the finite retransmission method outperforms the infinite retransmission method, or eliminates the need for retransmissions altogether. Furthermore, the average information age of the CSMA method increases with... The performance drops rapidly. However, neither the finite retransmission method nor the CSMA method can surpass the method proposed in this invention. Compared to the ALOHA benchmark method, the method of this invention can reduce the average AoI by more than 50%, and compared to the CSMA benchmark method, it can reduce the average AoI by more than 20%.

[0050] Although the invention has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings, disclosure, and other materials. In this specification, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple components. A single processor or other unit can implement several functions listed in the specification. While certain measures are described in different embodiments, this does not mean that these measures cannot be combined to produce good results.

[0051] Although the invention has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made therein without departing from the spirit and scope of the invention. Accordingly, this specification and drawings are merely illustrative of the invention and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the invention. Clearly, those skilled in the art can make various alterations and modifications to the invention without departing from its spirit and scope. Thus, if such modifications and modifications fall within the scope of the invention and its equivalents, the invention is also intended to include such modifications and modifications.

Claims

1. A method for minimizing information age in an opportunistic channel access system, characterized in that, The system includes a base station and multiple Internet of Things (IoT) devices, and the method includes the following steps: S1: During the channel contention phase, the contention time of each round is divided into discrete time slots of equal length. In each time slot, each active IoT device continuously and independently competes for the channel access right with a competition probability p until a unique winner emerges. S2: The winning IoT device evaluates the channel state to obtain the instantaneous channel gain, uses the instantaneous channel gain to obtain the offloading rate with the base station, and makes an access decision based on the offloading rate and the offloading rate threshold r. S3: The winning IoT device accepts the channel access right and offloads the observation data to the base station; S4: After the base station receives all the observation data from the IoT devices, it calculates the information age within the observation period; S5: Construct an optimization problem that minimizes the average information age, optimize the competition probability p and the unloading rate threshold r through a hierarchical iterative solution algorithm, and update the optimized competition probability p and unloading rate threshold r to each IoT device.

2. The method according to claim 1, characterized in that, In step S1, when the nth round includes n active devices, the probability of a single device winning is: The feasible region of the competition probability p is (0,1); During the competition, if zero or more devices send access requests, it is determined that no device can access or there is a conflict, and the competition will start again in the next time slot.

3. The method according to claim 2, characterized in that, In step S2, instantaneous channel gain Rayleigh fading follows an independent and identically distributed distribution, and its probability density function is: ,in These are distributed parameters, estimated using historical channel gain measurements; The unloading rate R is calculated based on Shannon's formula, and its expression is: ,in, To unload power from the equipment, Let B be the noise power spectral density and B be the channel bandwidth.

4. The method according to claim 3, characterized in that, In step S2, the rules for determining access include: If the unloading rate The winning IoT device relinquishes its channel access right and returns to step S1; like The winning IoT device accepts the channel access right and proceeds to step S3; The probability that an IoT device will accept channel access rights is The feasible region of r is , This is a predefined rate limit.

5. The method according to claim 4, characterized in that, In step S3, the time span for data unloading is D represents the amount of data from a single observation. Let be the number of contention attempts for the first successful access to the channel in the nth round, following the parameter . Geometric distribution; The total time span of the nth round is determined by the unloading time. and competition time The composition, and the competition time, are expressed as: ,in, The time slot length, The number of time slots required for the k-th competition follows the parameter: , independent and identically distributed geometric random variables.

6. The method according to claim 5, characterized in that, In step S4, the calculation process for the information age specifically includes: Total observation period duration: ; The sum of information for the nth round is: ,in ; The summation information age Q for a single observation period is: ; Obtain the average information age over a long period of time: ,in This indicates the expected operation.

7. The method according to claim 6, characterized in that, In step S5, the hierarchical iterative solution algorithm employs the Dinkelbach algorithm for outer-layer iteration, the BCD algorithm for middle-layer iteration, and the Polyblock algorithm for inner-layer optimization, specifically including: The Dinkelbach outer iteration transforms the fractional objective function into an equivalent linear objective function, and achieves iterative convergence by updating the parameter ξ. In the BCD mid-level iteration, the unloading rate threshold r is optimized by first fixing the contention probability p, and then the contention probability p is optimized by fixing the unloading rate threshold r. This process is repeated alternately until the convergence condition is met. Polyblock inner layer optimization transforms the non-convex subproblem into a monotonic optimization problem, solving for the optimal parameters of the competition probability p and the unloading rate threshold r by iteratively updating the point set.

8. The method according to claim 7, characterized in that, The convergence condition for BCD iteration is: ; The convergence condition of the Dinkelbach iteration is: ;in To preset the convergence accuracy, , This indicates the expected operation.

9. The method according to claim 1, characterized in that, The system contains N IoT devices, which observe the same object or area from different parts or angles. The observation and data unloading are carried out in multiple rounds, with N rounds constituting an observation cycle. Devices that have completed data unloading are inactive in subsequent rounds until the entire observation cycle ends.

10. An apparatus for minimizing information age in an opportunistic channel access system, for implementing the method according to any one of claims 1 to 9, characterized in that, The device includes a contention module, a channel evaluation module, a data offloading module, and a parameter receiving module integrated into an IoT device, as well as a data receiving module, an information age calculation module, and a parameter optimization module integrated into a base station; wherein: The contention module is used to broadcast pilot signals with contention probability p in each time slot, participate in the contention for channel access rights, and receive feedback on the contention results; The channel evaluation module is used to evaluate the channel state after winning the right to use the channel to obtain the channel gain, calculate the offloading rate and compare it with the offloading rate threshold r to make an access decision. The data offloading module is used to transmit observation data to the base station after confirming access. The parameter receiving module is used to receive the optimized contention probability p and offloading rate threshold r sent by the base station and update the local parameters. The data receiving module is used to receive observation data transmitted by various IoT devices and record the data reception time. The information age calculation module is used to calculate the average information age of the system based on the observation period duration, the competition time of each round, and the unloading time. The parameter optimization module is used to construct an optimization problem that minimizes the average information age. It optimizes the competition probability p and the unloading rate threshold r through a hierarchical iterative solution algorithm and sends the optimization results to each IoT device.

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