A state update method based on truncation automatic retransmission in cognitive relay Internet of Things

Abstract

A state update method based on truncated automatic retransmission in a cognitive relay Internet of Things includes transmission power control, data packet structure design, truncated automatic retransmission scheme design, iterative optimization of data packet length and retransmission times, and sending data packets for state update. The influence of outdated channel state information and short data packet characteristics on system state update is comprehensively considered, so that the model can more accurately characterize the state update process in the actual cognitive relay Internet of Things system. In terms of improving the system state update performance, on the one hand, the present invention utilizes cognitive Internet of Things relay and truncated automatic retransmission protocol to improve the coverage and transmission reliability of the system, and improves the utilization performance of spectrum resources; on the other hand, by analyzing the trade-off effect of the state update data packet length and the maximum allowed retransmission times on the system state update performance, the data packet length and the maximum allowed retransmission times are optimized to further improve the overall state update performance of the system.

Description

Technical Field

[0001] The present invention relates to the field of cognitive Internet of Things state update, and in particular to a state update method design based on truncation automatic retransmission in a cognitive relay Internet of Things. Background Art

[0002] With the continuous development of Internet of Things technology, the Internet of Things network has penetrated into all aspects of daily life and changed our production and lifestyle. On the one hand, the Internet of Things requires large-scale deployment of devices to provide convenient services, which leads to the need for the Internet of Things network to support massive node access. On the other hand, the Internet of Things also has higher requirements for service quality and requires more bandwidth to support the transmission of massive data. Therefore, the scarcity of spectrum resources has become an important bottleneck in the development of the Internet of Things. The development of cognitive radio technology provides a new idea for solving the problem of tight spectrum resources in the Internet of Things. The literature (F.Li, K.-Y.Lam, X.Li, Z.Sheng, J.Hua, and L.Wang, "Advances and Emerging Challenges in Cognitive Internet-of-Things," IEEE Trans.Ind.Informat., vol.16, no.8, pp.5489-5496, Aug.2020.) points out that the cognitive Internet of Things formed by applying it to the Internet of Things can greatly reduce the demand for dedicated spectrum resources.

[0003] In fact, there are two key differences between cognitive IoT and traditional spectrum sharing networks. The first difference is reflected in the traffic model. Traditional spectrum sharing technology is mainly developed for downlink long data packet communication. However, cognitive IoT is mainly based on uplink short data packet communication. The second difference is the data type. Many cognitive IoT applications use time-sensitive information to monitor and control the network. For example, in application areas such as smart agriculture, industrial control and sensor networks, it is very important to keep the time-critical information fresh. This invention is mainly aimed at such scenarios.

[0004] According to the above analysis, cognitive IoT devices need new architectures and metrics to measure their performance in short packet communication. Therefore, the short packet communication theory proposed by Polyanskiy et al. (Y.Polyanskiy, HVPoor, and S.Verdu, "Channelcoding rate in the finite blocklength regime," IEEE Trans.Inf.Theory, vol.56, no.5, pp.2307–2359, May 2010) can be used to more accurately characterize the packet error characteristics of communication between sensors and servers. Generally, when the length of the data packet transmitted in the network is less than 1000 channel uses, it can be considered as short packet communication. In addition, in order to better quantify the information freshness of the status update, the information age was proposed in the literature (SKKaul, RDYates, and M.Gruteser, "Real-time status: How often should one update?" in Proc.IEEE INFOCOM, Mar. 2012, pp.2731–2735.), which is defined as the difference between the current time and the time when the latest status data packet received by the receiver was generated. In addition, the literature (M. Costa, M. Codreanu, and A. Ephremides, "Age of Information with Packet Management," in Proc. IEEE Int. Symp. Information Theory (ISIT), 2014, pp. 1583-1587.) proposed using the peak information age to measure the maximum age, which has more practical value and impact on applications with age threshold restrictions.

[0005] However, the information age of short packet communication in cognitive relay IoT has not been well studied. On the one hand, due to the shortness of the monitored data packets, the system has a high probability of packet error, which further deteriorates the information freshness of the system's state update. In view of the small coverage and poor reliability of short packet communication in cognitive IoT, the relay and retransmission feedback protocol can be used in a targeted manner to solve the problem. The literature (D. Zheng, Y. Yang, L. Wei and B. Jiao, "Decode-and-Forward Short-Packet Relaying in the Internet of Things: Timely Status Updates," IEEE Trans. Wireless Commun., vol. 20, no. 12, pp. 8423-8437, Dec. 2021.) studied the state update performance of relay-assisted short packet communication under the retransmission protocol. We can further improve the performance by adopting the truncated automatic retransmission protocol. On the other hand, in actual cognitive IoT communication, it is difficult for the receiver side to obtain accurate channel state information in advance, especially compared with long packet communication, the pilot of short packet communication is comparable to the length of the state update packet, which cannot be ignored. At this time, it is unrealistic to allocate a long pilot to each data packet to accurately update the real-time channel state information. Due to feedback delay, when the actual transmission time arrives, it may happen that the instantaneous channel state information for the transmitter is actually outdated. To this end, we study the information age affected by outdated channel state information in cognitive relay IoT, and propose a method to iteratively optimize the state update packet length and the number of retransmissions based on the golden section method to further improve the state update performance of the system. Summary of the invention

[0006] The purpose of the present invention is to provide a more practical cognitive relay Internet of Things state update model, and proposes a state update method based on truncation and automatic retransmission in the cognitive relay Internet of Things to improve the system state update performance. The model comprehensively considers the impact of short data packet communication and the situation of outdated channel state information, and more accurately describes the process of system state update. The proposed method places the complex design work on the server side with strong computing power, and can adapt to the actual situation that the cognitive relay Internet of Things terminal has a simple structure and low computing power. On the secondary transmitter and relay side, it is only necessary to control the maximum transmission power through the perception information to protect the main network communication. On the server side, the server needs to use the golden section algorithm to iteratively optimize the length of the state update data packet and the number of truncation retransmissions to improve the system's state update performance.

[0007] A state update method based on truncation automatic retransmission in a cognitive relay Internet of Things comprises the following steps:

[0008] Step 1: Transmit power control: In the cognitive IoT in the Underlay mode, in order to ensure the communication service quality of the primary network, the transmit power of the secondary transmitter and relay needs to be limited within a threshold to reduce interference to the primary receiver. Specifically, before sending information, the secondary transmitter and relay need to sense the interference to the primary receiver and control the maximum transmit power within the tolerable interference threshold. If the interference exceeds the interference threshold, the transmitter must adjust its own transmit power in time to meet the communication service quality of the primary network;

[0009] Step 2: Data packet structure design: After the secondary transmitter determines the transmission power, the server calculates the information age of the received information and uses the one-dimensional golden section algorithm to optimize the status update data packet length of the secondary transmitter and reduce the average peak information age of the server;

[0010] Step 3: Design of truncated automatic retransmission scheme: Further, the server uses the two-dimensional golden section method based on the information age of the determined data packet length to optimize the maximum allowed retransmission times of the secondary transmitter and relay device in the truncated automatic retransmission scheme, thereby improving the system's state update performance.

[0011] Step 4: Iteratively optimize the packet length and retransmission times: The server iteratively optimizes the state update packet length and the maximum allowed retransmission times until the algorithm converges. After that, the server broadcasts the designed state update packet length and the maximum allowed retransmission times to the secondary transmitter and relay;

[0012] Step 5: Send data packets for status update: The secondary transmitter and relay send status update information to the server according to the truncation automatic repeat protocol. 1 and L 2 Indicates the maximum number of retransmissions allowed within two hops in the secondary network. In the first hop, the secondary transmitter sends a status update message to the relay. If the relay successfully receives the data packet, it will feedback the confirmation message. If 1 If the packet is still not received successfully after the first transmission, the packet is discarded and a new status update is waited for. In the second hop, the relay forwards the packet to the server using decoding and forwarding. When the packet is successfully decoded by the server, a confirmation feedback is sent to the secondary transmitter and the relay, and the transmission process ends. 2 If the packet is not successfully decoded during the secondary transmission, the secondary transmitter will discard the packet and wait for the newly generated update and repeat step 5.

[0013] Compared with the existing method for improving system status update performance, the present invention has the following advantages and significant effects:

[0014] The present invention utilizes cognitive Internet of Things relay and truncated automatic retransmission protocol to improve the coverage and transmission reliability of the system, and designs and optimizes the transmission packet length and retransmission times of the system, thereby improving the state update performance of the cognitive Internet of Things system. The system model is characterized as follows: Consider a cognitive relay Internet of Things system, in which the Internet of Things devices in the secondary network share the spectrum with the main network in an Underlay mode. Among them, the main network consists of a pair of main transmitters and a main receiver. The secondary network forwards the data packets sent by the secondary transmitter to a remote server (hereinafter referred to as the server) with the help of a relay to monitor the temperature, humidity, wind speed and other time-sensitive information of the sensor network. During the state update process, both hops use the truncated automatic retransmission protocol for transmission. If the receiving side still fails to successfully receive the data packet after the maximum number of retransmissions allowed, the packet is discarded and waits for the next packet to be transmitted.

[0015] The present invention considers a more practical communication model, comprehensively considering the short length of data packets in the cognitive relay Internet of Things and the outdated channel state information at the receiving end, so that the present model can more accurately characterize the state update process in the cognitive relay Internet of Things system. In addition, the present invention does not need to perform complex data packet control scheduling at the transmitting end, but only needs to adjust the simple state update data packet length and the maximum allowed number of retransmissions, while the more complex algorithm design work is placed on the server side with strong computing power, which makes the present invention suitable for cognitive relay Internet of Things networks with simple terminal structures and low computing power. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a system model diagram of the present invention.

[0017] Figure 2 It is a schematic diagram of the state update process of cognitive relay Internet of Things.

[0018] Figure 3 This is a graph showing the relationship between the average peak information age of the system and the length of the status update packet.

[0019] Figure 4 This is a graph showing the relationship between the average peak information age of the system and the maximum allowed number of retransmissions of the first and second hops.

[0020] Figure 5 It is a performance comparison chart of the proposed method and the exhaustive search method. DETAILED DESCRIPTION

[0021] The following is a further detailed description of the present invention in conjunction with the accompanying drawings. Figure 1As shown, a cognitive relay IoT system, the IoT devices in the secondary network adopt the Underlay mode to share the spectrum with the main network. Among them, the main network consists of a pair of main transmitters and main receivers, and the secondary network consists of secondary transmitters, relays and servers. The secondary transmitter sends randomly generated status update short data packets to the remote server with the help of relays, and the randomly generated status updates obey the Poisson distribution rate λ. During the data transmission process, the relay adopts a decoding and forwarding strategy to forward short data packets. Considering that there is inevitably a large packet error rate in the short data packet system, the secondary network adopts a truncated automatic retransmission scheme to transmit the status update data packet. The specific implementation process of the transmission method of the present invention is as follows:

[0022] Step 1: Transmit power control: In the cognitive relay IoT in the underlay mode, in order to ensure the communication service quality of the primary network, the transmit power of the secondary transmitter and the relay needs to be limited to a threshold to reduce interference to the primary receiver. In actual scenarios, it is difficult to obtain real-time channel state information for short data packet communication. Due to the feedback delay in the network, the secondary transmitter can only use outdated channel state information for encoding. The channel with outdated channel state information can be modeled as

[0023]

[0024] Where h is the actual channel coefficient, e is a complex Gaussian variable with the same variance as h and is uncorrelated with h, and ρ is Specifically, before the secondary transmitter sends information, it needs to sense the interference to the primary receiver and control the maximum transmission power within the tolerable interference threshold. Due to the outdated channel state information between the secondary transmitter and the interference link from the relay to the primary receiver, the interference power at the primary receiver may be higher than the tolerable interference threshold I Q Therefore, the secondary transmitter and relay use power control strategy to control the transmission power. S and P R The transmission power is expressed as

[0025]

[0026] Among them, κ 1 and κ 2 are the power control factors of the two-hop transmitters, and are the outdated channel coefficients from the secondary transmitter and the relay to the primary receiver, respectively, and P T is the maximum transmit power of the transmitter.

[0027] Assuming the channel obeys Rayleigh fading, in the first hop, the actual interference I at the primary receiver is 1 for

[0028]

[0029] Among them, h SP is the real-time channel coefficient from the secondary transmitter to the primary receiver;

[0030] Affected by outdated channel state information in the network, the primary network may be interrupted due to interference from the secondary network. The probability of interruption is defined as the actual interference at the primary receiver is higher than the interference power constraint I Q Therefore, the probability of interruption due to interference from the secondary transmitter is P I1 Expressed as

[0031]

[0032] in, is the channel h SP and Probability density function of the joint distribution of gains, x is the channel h SP Gain variable, y is the channel Gain variable. It can be expressed as

[0033]

[0034] Among them, Ω SP is the mean value of the channel gain from the secondary transmitter to the primary receiver. We can set the maximum tolerable interruption probability due to interference from the secondary transmitter to Substituting equation (6) into equation (5), we can numerically solve the first-hop power control factor κ 1 The value of the second hop power control factor κ can be obtained by the same logic. 2 ;

[0035] Step 2: Data packet structure design: Information age is used as a performance indicator of the state update system to analyze the freshness of the system data packets. Information age Δ(t) is defined as the difference between the current time t and the time U(t) when the latest state update data packet was successfully received by the receiver. Information age can be expressed as

[0036] Δ(t)=tU(t) (7)

[0037] The updating process of the system information age is as follows: Figure 2 As shown, assuming the maximum retransmission time L 1 =L 2 =2. Among them, S i Indicates the waiting time between the arrival of the last valid data packet and the generation of the next data packet. i is the time taken to complete the ith update, Z irepresents the departure time, which is the time interval between two consecutive valid data packets. The information age increases and decreases to That is, the time it takes to successfully receive the latest update package. In this status update system, we use the average peak information age to characterize the average freshness of the status information received at the base station. The peak information age is the peak value H before receiving the new update. i Then, the average peak information age can be given as

[0038]

[0039] where τ is the time limit and N(τ) is the number of packets received by the destination before τ time.

[0040] By calculation, in this system, the average peak information age can be expressed as

[0041]

[0042] Where λ is the state packet generation rate, n is the encoding length of the state update information, B is the system bandwidth, and θ 1 and θ 2 The average failure probability of status update packets sent to the first hop and the second hop respectively.

[0043] For a single-hop state update packet transmission, the probability of transmission failure can be expressed as

[0044]

[0045] Among them, D is the status update information, f γ (·) is the probability density function of the signal-to-interference-noise ratio at the receiving end. According to the system model, the received signal-to-interference-noise ratio of the first hop and the second hop is

[0046]

[0047] Among them, P S , P R and P P are the transmit powers of the secondary transmitter, relay and primary transmitter respectively, ρ SR and ρ SR are the correlation factors of the outdated channels from the secondary transmitter to the relay and from the relay to the server, and are the outdated channel coefficients from the secondary transmitter to the relay and from the relay to the server, respectively, and h PR and h PD are the channel coefficients from the main transmitter to the relay and the server, σ 2 is the noise power of the channel;

[0048] Substituting the probability density function of the Rayleigh fading channel gain into the solution, we can get the corresponding probability density function. Further, the average failure probability of the first and second hops of the secondary transmitter sending the status update data packet to the server is

[0049]

[0050] in, and are the probability density functions of the signal-to-noise ratio of the first hop and the second hop, respectively. Substituting equations (13) and (14) into equation (9), we can get the average peak information age at the server. Using the average peak information age, the server can design the state update packet length and the maximum allowed number of retransmissions to improve the overall state update performance of the system. The optimization problem can be expressed as

[0051]

[0052] stn min <n<n max (15b)

[0053] L 1 <L max (15c)

[0054] L 2 <L max (15d)

[0055] Among them, constraint (15b) is to adjust the state update information to the minimum encoding length n of the load information min and the maximum encoding length n of the payload information max Within , constraints (15c) and (15d) are to ensure the effectiveness of the system retransmission performance.

[0056] Due to the coupling of optimization parameters, we first split problems (15a), (15b), (15c), and (15d) into optimizing n and L 1 ,L 2 The subproblem of optimizing the length of the state update packet can be expressed as

[0057]

[0058] stn min <n<n max (16b)

[0059] The subproblem of optimizing the maximum number of retransmissions can be expressed as

[0060]

[0061] sL1 <L max (17b)

[0062] L 2 <L max (17c)

[0063] Considering the complexity of equation (9), this method uses the one-dimensional golden section method to solve the first sub-problem. This method can effectively avoid the work of differentiating the complex objective function. The specific solution steps of the algorithm are as follows:

[0064] Step 21: Set the maximum number of retransmissions to L 1 ,L 2 , the optimization problems in (16a) and (16b) are solved using the golden section algorithm, and we get

[0065] Step 22: Get the length of the data packet Rounding up, the optimal status update packet length is

[0066] After using the golden section method, the search range of the extreme point is continuously narrowed by comparing the function values ​​of the trial points. Compared with the one-dimensional global search, its complexity is about This method only requires calculating the function value and is convenient to use in this model.

[0067] Step 3: Design of truncated automatic retransmission scheme: Further, the server uses the two-dimensional golden section method based on the information age of the determined data packet length to optimize the maximum number of retransmissions allowed by the secondary transmitter and relay device in the truncated automatic retransmission scheme, thereby improving the performance of the system's state update. The specific solution steps of the algorithm are as follows:

[0068] Step 31: Given the state update packet length n obtained in step 2, use the two-dimensional golden section algorithm to solve the optimization problems in (17a), (17b), and (17c), and obtain

[0069] Step 32: Get the pilot length Round up to get the optimal maximum number of retransmissions allowed for the two hops.

[0070]

[0071] Step 4: Iteratively optimize the packet length and retransmission times: The server iteratively optimizes the state update packet length and the maximum allowed retransmission times until the algorithm converges. The specific solution steps of the algorithm are as follows:

[0072] Step 41: For the results obtained in step 3 Substitute the optimization problem in step 2 and solve it using the one-dimensional golden section algorithm to obtain n * .

[0073] Step 42: For n obtained in step 2 * Substitute the optimization problem in step 3 and solve it using the two-dimensional golden section algorithm to obtain

[0074] Step 43: Iterate in a loop until the algorithm converges or reaches the maximum number of iterations, and obtain the optimal state update packet length and the maximum allowed number of retransmissions.

[0075] Afterwards, the server broadcasts the designed status update data packet length and the maximum allowed number of retransmissions to the secondary transmitter and relay, and the secondary transmitter and relay transmit information according to the method designed by the server.

[0076] Step 5: Send data packets for status update: The secondary transmitter and relay send status update information to the server according to the truncation automatic repeat protocol. 1 and L 2 Indicates the maximum number of retransmissions allowed within two hops in the secondary network. In the first hop, the secondary transmitter sends a status update message to the relay. If the relay successfully receives the data packet, it will feedback the confirmation message. If 1 If the packet is still not received successfully after the first transmission, the packet is discarded and a new status update is waited for. In the second hop, the relay forwards the packet to the server using decoding and forwarding. When the packet is successfully decoded by the server, a confirmation feedback is sent to the secondary transmitter and the relay, and the transmission process ends. 2 If the packet is not successfully decoded during the secondary transmission, the secondary transmitter will discard the packet and wait for the newly generated update and repeat step 5.

[0077] The simulation parameters are set as follows: Considering the cognitive relay Internet of Things, the bandwidth B = 180kHz, the amount of information in each state packet D = 200nats, the state packet generation rate λ = 300packet / s, the state data packet length n = 300channel uses, and the lower and upper limits of the data packet length range are n respectively. min =100 channel uses and n max = 1000 channel uses. In addition, the transmission power of the secondary transmitter and the relay is P T =0.01W, channel power gain at reference distance χ 0 =-50.1473dB, the distance between each node is d=220m, the path loss factor is α=3.3 and the noise power spectral density is -174dBm / Hz.

[0078] Figure 3 and Figure 4 The average peak information age varies with the length of the state update packet and the maximum number of retransmissions allowed. The simulation points fit the theoretical curve, which shows the correctness of the theoretical analysis. We can see that Figure 3 In , as the packet length increases, the average peak information age of the system decreases first and then increases, which shows that there is an optimal packet length that minimizes the information age of the system. Figure 4 In , when the maximum allowed number of retransmissions is small, the packet waiting time caused by decoding errors becomes longer and the average peak information age becomes larger. However, as the number of retransmissions increases, the average peak information age decreases and reaches the best performance. As the maximum number of retransmissions increases, the performance decreases again.

[0079] Figure 5 The performance comparison between the proposed method and the exhaustive search algorithm. As can be seen from the figure, the proposed method can achieve almost the same performance as the exhaustive search algorithm. The exhaustive search algorithm traverses all valid states, calculates the value of the average peak information age, and finally obtains the optimal state update data packet length and the maximum allowed number of retransmissions. The exhaustive search method is a method that can obtain the optimal solution, but its complexity is very high. The proposed method greatly reduces the complexity of the algorithm by decoupling the original problem into two sub-problems and using the golden section to solve each sub-problem. As can be seen from the figure, by increasing the transmission power, the average peak information age of the system can be effectively reduced, and the state update performance of the system can be effectively improved. However, due to the performance limitations of the main network communication service, the power will be limited to a certain range, and finally the state update performance of the system will have a performance plateau.

[0080] The description of the above embodiment is relatively specific and detailed, but it only expresses a feasible implementation of the present invention and does not limit the scope of the patent of the present invention. It should be pointed out that researchers and engineers in this field can add some deformations or improvements on the basis of this embodiment within the framework of the present invention, but these are all within the scope of protection of the patent of the present invention, and the scope of protection of the patent of the present invention shall be subject to the attached claims.

Claims

1. A state update method based on truncation automatic retransmission in cognitive relay Internet of Things, Features The following steps are involved: Step 1: Transmit power control: In the cognitive IoT in the Underlay mode, the primary network consists of a pair of primary transmitters and a primary receiver, and the secondary network consists of secondary transmitters, relays, and servers. The transmit power of the secondary transmitters and relays needs to be limited within a threshold. Before sending information, the secondary transmitters and relays need to sense the interference to the primary receiver and control the maximum transmit power within the tolerable interference threshold. If the interference exceeds the interference threshold, the secondary transmitter must adjust its transmit power in time to meet the communication service quality of the primary network. The specific process is: In the cognitive relay IoT of the Underlay mode, short data packet communication is adopted, and the transmission power of the secondary transmitter and the relay needs to be limited within a threshold. In actual scenarios, it is difficult to obtain real-time channel state information in short data packet communication. Due to the feedback delay in the network, the secondary transmitter can only use outdated channel state information for encoding. The channel modeling of outdated channel state information is Where h is the actual channel coefficient, e is a complex Gaussian variable with the same variance as h and is uncorrelated with h, and ρ is The correlation factor between and h; Before the secondary transmitter sends information, it needs to sense the interference to the primary receiver and control the maximum transmission power within the tolerable interference threshold. Since the interference link between the secondary transmitter and the relay to the primary receiver has outdated channel state information, the interference power at the primary receiver may be higher than the tolerable interference threshold I Q Therefore, the secondary transmitter and relay use power control strategy to control the transmission power. S and P R The transmission power is expressed as Among them, κ 1 and κ 2 are the power control factors of the two-hop transmitters, and are the outdated channel coefficients from the secondary transmitter and the relay to the primary receiver, respectively, and P T is the maximum transmit power of the transmitter; Assuming the channel obeys Rayleigh fading, in the first hop, the actual interference I at the primary receiver is 1 for Among them, h SP is the real-time channel coefficient from the secondary transmitter to the primary receiver; Affected by outdated channel state information in the network, the primary network may be interrupted due to interference from the secondary network. The probability of interruption is defined as the actual interference at the primary receiver is higher than the interference power constraint I Q The probability of interruption due to interference from the secondary transmitter Expressed as Among them, among them, is the channel h SP and Probability density function of the joint distribution of gains, x is the channel h SP Gain variable, y is the channel Gain variables; Expressed as Among them, Ω SP is the average value of the channel gain from the secondary transmitter to the primary receiver; by setting the maximum tolerable interruption probability due to interference from the secondary transmitter Substituting equation (6) into equation (5), we can numerically solve the first-hop power control factor κ 1 The value of the second hop power control factor κ is obtained in the same way 2 ; Step 2: Data packet structure design: After the secondary transmitter determines the transmission power, the server calculates the information age of the received information and uses the one-dimensional golden section algorithm to optimize the status update data packet length of the secondary transmitter and reduce the average peak information age of the server; The specific process is: Information age is used as a performance indicator of the state update system to analyze the freshness of the data packet. Information age Δ(t) is defined as the difference between the current time t and the time U(t) when the latest state update data packet is successfully received by the receiver. Information age is expressed as Δ(t)=tU(t) (7) In the state update system, the average peak information age is used to characterize the average freshness of the state information received at the base station; the peak information age is the peak value H before receiving the new update. i , the average information age peak is Where τ is the time limit and N(τ) is the number of packets received by the destination before τ time; The average peak information age is expressed as Where λ is the state packet generation rate, θ 1 and θ 2 are the average failure probabilities of the status update packets sent to the first hop and the second hop, n is the encoding length of the status update information, B is the bandwidth of the system, and L 1 and L 2 Indicates the maximum number of retransmissions allowed within two hops in the secondary network; For a single-hop state update packet transmission, the probability of transmission failure is expressed as Among them, D is the status update information, f γ (·) is the probability density function of the signal-to-interference-noise ratio at the receiving end; the signal-to-interference-noise ratio of the first hop and the second hop is Among them, P S , P R and P P are the transmission powers of the secondary transmitter, relay and primary transmitter respectively, ρ SR and ρ SR are the correlation factors of the outdated channels from the secondary transmitter to the relay and from the relay to the server, and are the outdated channel coefficients from the secondary transmitter to the relay and from the relay to the server, respectively, and h PR and h PD are the channel coefficients from the main transmitter to the relay and the server, σ 2 is the noise power of the channel; Substitute the probability density function of the Rayleigh fading channel gain into the solution to obtain the corresponding probability density function; the average failure probability of the first and second hops of the secondary transmitter sending the status update data packet to the server is in, and are the probability density functions of the signal-to-interference-noise ratio received at the first hop and the second hop, respectively; Substituting equations (13) and (14) into equation (9), we can obtain the average peak information age at the server. Using the average peak information age, the server designs the state update packet length and the maximum allowed number of retransmissions to improve the overall state update performance of the system; The optimization problem is expressed as s.t.n min <n<n max (15b) L 1 <L max (15c) L 2 <L max (15d) Among them, constraint (15b) is to adjust the state update information to the minimum encoding length n of the load information min and the maximum encoding length n of the payload information max Within, constraints (15c) and (15d) are for the effectiveness of the system retransmission performance; Due to the coupling of optimization parameters, problems (15a), (15b), (15c), and (15d) are first split into optimizing n and L 1 ,L 2 The subproblem of optimizing the length of the state update packet is expressed as s.t.n min <n<n max (16b) The subproblem of optimizing the maximum number of retransmissions is expressed as s.t.L 1 <L max (17b) L 2 <L max (17c) The one-dimensional golden section method is used to solve the first sub-problem. The specific solution steps are as follows: Step 21: Set the maximum number of retransmissions to L 1 ,L 2 , the optimization problems in (16a) and (16b) are solved using the golden section algorithm to obtain the packet length Step 22: Get the length of the data packet Rounding up, the optimal status update packet length is Step 3: Design of truncated automatic retransmission scheme: The server uses the two-dimensional golden section method based on the information age of the determined data packet length to optimize the maximum allowed retransmission times of the secondary transmitter and relay device in the truncated automatic retransmission scheme, thereby improving the system's status update performance; The specific solution steps are as follows: Step 31: Given the state update packet length n obtained in step 2, use the two-dimensional golden section algorithm to solve the optimization problems in (17a), (17b), and (17c), and obtain Step 32: Get the pilot length Round up to get the optimal maximum number of retransmissions allowed for the two hops. Step 4: Iteratively optimize the packet length and retransmission times: The server iteratively optimizes the state update packet length and the maximum allowed retransmission times until the algorithm converges; the server broadcasts the designed state update packet length and the maximum allowed retransmission times to the secondary transmitter and relay; Step 5: Send data packets for status update: The secondary transmitter and the relay send status update information to the server according to the truncation automatic repeat protocol.

2. The state update method based on truncation automatic retransmission in the cognitive relay Internet of Things according to claim 1, Features Step 4 above: Iteratively optimize the packet length and the number of retransmissions: The server iteratively optimizes the state update packet length and the maximum allowed number of retransmissions until the algorithm converges; the specific solution steps are as follows: Step 41: For the results obtained in step 3 Substitute the optimization problem in step 2 and solve it using the one-dimensional golden section algorithm to obtain n * ; Step 42: For n obtained in step 2 * Substitute the optimization problem in step 3 and solve it using the two-dimensional golden section algorithm to obtain Step 43: loop iteration until the algorithm converges or reaches the maximum number of iterations, and obtain the optimal state update packet length and the maximum allowed number of retransmissions; Afterwards, the server broadcasts the designed status update data packet length and the maximum allowed number of retransmissions to the secondary transmitter and relay, and the secondary transmitter and relay transmit information according to the method designed by the server.

3. The state update method based on truncation automatic retransmission in the cognitive relay Internet of Things according to claim 2, Features In step 5 above, use L 1 and L 2 Indicates the maximum number of retransmissions allowed within two hops in the secondary network; in the first hop, the secondary transmitter sends a status update message to the relay. If the relay successfully receives the data packet, it will feedback the confirmation message. If in L 1 If the data packet is still not received successfully after the first transmission, the data packet is discarded and a new status update is waited for. In the second hop, the relay forwards the data packet to the server using the decoding forwarding method. When the data packet is successfully decoded by the server, a confirmation feedback is sent to the secondary transmitter and the relay, and the transmission process ends. If the data packet is received successfully in L 2 If the packet is not successfully decoded during the secondary transmission, the secondary transmitter will discard the packet and wait for the newly generated update and repeat step 5.

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