An adaptive short code allocation method for power sensing information based on information age

Abstract

A method for adaptive short code allocation of power sensing information based on information age is first constructed by N Power information sensing nodes and K The power Internet of Things perception and transmission model composed of 3 base stations is constructed, and the decoding error probability of the receiving end is determined based on the channel noise between the power information perception nodes in the model. Then, according to the decoding error probability of the receiving end, the information age model constructed with the minimum average information age as the optimization target and the information code length of the power information perception node as the optimization variable is solved to obtain the optimal allocation scheme of the information code length. The present invention can provide the optimal information code length allocation scheme in real time, improve the reliability of the perception information, and reduce the delay of the perception information.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a method for adaptively allocating short codes of power sensing information based on information age. Background Art

[0002] Communication technology is crucial in the power Internet of Things. It can promote the enabling of smart grid technology at many levels, provide the power grid with rich IoT big data and device connection and communication capabilities, and promote the all-round development of power grid business in terms of refined management, business scope expansion, operational efficiency improvement, and intelligence level. However, the power Internet of Things perception information is usually heterogeneous, and the transmission environment of perception information is complex and changeable. Therefore, it is necessary to explore adaptive power perception information transmission methods. The length of the perception information data packet has an important impact on its transmission efficiency, reliability and other indicators. For different power perception information, the data packet length needs to be adaptively adjusted to meet its transmission requirements.

[0003] At present, most studies are designed based on the wireless code length in the Shannon domain, but in order to meet the requirements of ultra-reliable and low latency, the size of the transmitted information is often small. At the same time, the information age can better represent the freshness of the information than the latency, so it is of profound significance to study the power-aware information adaptive short code allocation method based on the information age. Summary of the invention

[0004] The purpose of the present invention is to provide an adaptive short code allocation method for power sensing information based on information age, which can effectively improve the reliability of power sensing information and reduce the delay of power sensing information in order to solve the above problems in the prior art.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows:

[0006] A method for adaptively allocating short codes of power sensing information based on information age comprises the following steps in sequence:

[0007] Step A: construct a power Internet of Things perception and transmission model consisting of N power information perception nodes and K base stations, and determine the decoding error probability of the receiving end based on the channel noise between the power information perception nodes in the model;

[0008] Step B: According to the decoding error probability of the receiving end, the information age model constructed with the minimum average information age as the optimization target and the information code length of the power information sensing node as the optimization variable is solved to obtain the optimal allocation plan of the information code length.

[0009] In step B, the information age model is:

[0010]

[0011] In the above formula, is the average information age, m i is the number of symbols that the i-th power information sensing node encodes the power information, i.e., the information code length, λ is the power information generation speed, ε is the decoding error probability at the receiving end, T s is the transmission time of each symbol, and M is the total number of symbols transmitted.

[0012] The information age model is constructed based on the finite code length theory and the traditional ARQ retransmission protocol, where:

[0013] The finite code length theory includes: the probability of information transmission error is the probability of decoding error;

[0014] The traditional ARQ retransmission protocol includes: when a data packet fails to be transmitted, the transmitting end will keep retransmitting the data packet until the transmission is successful.

[0015] In step A, the decoding error probability of the receiving end is calculated according to the following formula:

[0016]

[0017]

[0018] In the above formula, Q(x) is the right tail function of the standard normal distribution, γ is the signal-to-noise ratio at the receiving end, r is the coding rate, and m is the number of symbols for power information coding, i.e., the information code length.

[0019] The step B uses the CVX convex optimization tool to solve the information age model.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] The invention discloses an adaptive short code allocation method for power perception information based on information age. The method first constructs a power Internet of Things perception and transmission model composed of N power information perception nodes and K base stations, and determines the decoding error probability of the receiving end based on the channel noise between the power information perception nodes in the model. Then, according to the decoding error probability of the receiving end, the constructed information age model with the minimum average information age as the optimization target and the information code length of the power information perception node as the optimization variable is solved to obtain the optimal allocation scheme of the information code length. The method is based on the information age model that comprehensively considers the finite code length theory and the traditional ARQ retransmission protocol, minimizes the average information age of the system information by optimizing the allocation of the information code length, effectively improves the reliability of the power perception information, reduces the delay of the power perception information, and realizes the low-delay transmission of the perception information in the power Internet of Things. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1It is a structural diagram of the power Internet of Things perception and transmission model in the present invention.

[0023] Figure 2 Graph showing the relationship between the average information age of power sensing information and the information arrival rate in Example 1.

[0024] Figure 1 The arrow lines in represent the power sensing information transmission. DETAILED DESCRIPTION

[0025] The present invention is further described in detail below in conjunction with specific implementations and drawings.

[0026] The present invention provides an adaptive short code allocation method for power perception information based on information age, which can realize low-latency transmission of perception information in the power Internet of Things, and minimize the average information age of perception information by optimizing the code length of each information. At the same time, considering the reliability requirements, the present invention considers the retransmission scheme, which can effectively improve the reliability of perception information.

[0027] Embodiment 1:

[0028] A method for adaptively allocating short codes for power sensing information based on information age is performed in the following steps:

[0029] 1. Build Figure 1 The power Internet of Things perception and transmission model shown in the figure consists of N power information perception nodes and K base stations. i (i=1,2,···,N) sends the sensed power information to the base station to realize the sensed information transmission.

[0030] 2. Detect the channel noise between each power information sensing node, and determine the decoding error probability ε of the receiving end based on the channel noise:

[0031]

[0032]

[0033] In the above formula, Q(x) is the right tail function of the standard normal distribution, γ is the signal-to-noise ratio at the receiving end, r is the coding rate, and m is the number of symbols for power information coding, i.e., the information code length.

[0034] 3. Construct an information age model with the minimum average information age as the optimization target and the information code length of the power information perception node as the optimization variable. The model is:

[0035]

[0036] In the above formula, is the average information age, mi is the number of symbols that the i-th power information sensing node encodes the power information, i.e., the information code length, λ is the power information generation speed, ε is the decoding error probability at the receiving end, T s is the transmission time of each symbol, and M is the total number of symbols transmitted.

[0037] in, The process of determining the expression of is as follows:

[0038] Information age measures the freshness of power information and can be expressed as Δ=tU(t), where U(t) is the time when the information is generated and t is the current time. The power information sensing node randomly generates sensing information. Let the time interval for sensing information generation be X, the time for sensing information to wait for transmission be W, the transmission time of sensing information be S, and the residence time of sensing information be T. Then the average information age of sensing information is for:

[0039]

[0040] In the above formula, E[·] is the expected formula.

[0041] If the power information sensing node S i Encode D bits of information into m i symbols, and transmit these symbol information to the base station. The transmission time of each symbol is T s In order to meet the reliability requirements, the traditional ARQ retransmission protocol is considered in the transmission process of the perceived power information, that is, the data packet with decoding errors will be retransmitted until the decoding is successful. If the perceived information needs to be transmitted b times, that is, the number of retransmissions is b-1 times, then the time for each perceived information transmission is S = bT s m i .

[0042] Assuming that the generation interval of power information is a Poisson process, the probability density function of the information generation process can be expressed as:

[0043] f X (x) = λe -λx

[0044] In the above formula, λ is the power information generation speed.

[0045] The probability p of successful transmission of power sensing information t It can be expressed as:

[0046] p t =Pr{B=b}=ε b-1 (1-ε)

[0047] In the above formula, Pr{B=b} represents the probability of transmission times B=b, b=1,2,3···, ε is the decoding error probability at the receiving end. According to the finite code length theory, the probability of information transmission error is the probability of decoding error.

[0048] The probability of power sensing information transmission time is:

[0049]

[0050] The transmission time of the sensing information can be expressed as:

[0051]

[0052] In the above formula, δ(x) is the Dirac function.

[0053] According to the above formula, we can deduce The expression is:

[0054]

[0055] 4. Use the CVX convex optimization tool to solve the constructed information age model and obtain the optimal allocation plan for the information code length.

[0056] Based on the optimal information code length obtained in Example 1, the following is obtained through simulation: Figure 2 The relationship curve between the average information age and the information arrival rate is shown in the figure. It can be seen from the figure that the average information age decreases first and then increases with the increase of the information arrival rate, and the average information age has a minimum value. This is because when the information arrival rate is very small, the time to wait for a new information to arrive is very long. When the information arrival rate is very high, the transmitted information needs to wait for a while before being transmitted, which will lead to a large average information age.

Claims

1. A method for adaptively allocating short codes for power sensing information based on information age, characterized in that: The method comprises the following steps in sequence: Step A: construct a power Internet of Things perception and transmission model consisting of N power information perception nodes and K base stations, and determine the decoding error probability of the receiving end based on the channel noise between the power information perception nodes in the model, wherein the decoding error probability of the receiving end is calculated according to the following formula: In the above formula, ε is the decoding error probability at the receiving end, Q(x) is the right tail function of the standard normal distribution, γ is the signal-to-noise ratio at the receiving end, r is the coding rate, and m is the number of symbols encoded in the power information, i.e., the information code length; Step B: according to the decoding error probability of the receiving end, the information age model constructed with the minimum average information age as the optimization target and the information code length of the power information sensing node as the optimization variable is solved to obtain the optimal allocation scheme of the information code length, wherein the information age model is: In the above formula, is the average information age, m i is the number of symbols that the i-th power information sensing node encodes the power information, i.e., the information code length, λ is the power information generation rate, ε is the decoding error probability at the receiving end, T s is the transmission time of each symbol, and M is the total number of symbols transmitted.

2. According to claim 1, a method for adaptively allocating short codes for power sensing information based on information age, characterized in that: The information age model is constructed based on the finite code length theory and the traditional ARQ retransmission protocol, where: The finite code length theory includes: the probability of information transmission error is the probability of decoding error; The traditional ARQ retransmission protocol includes: when a data packet fails to be transmitted, the transmitting end will keep retransmitting the data packet until the transmission is successful.

3. According to claim 1, a method for adaptively allocating short codes for power sensing information based on information age, characterized in that: The step B uses the CVX convex optimization tool to solve the information age model.

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