A time slot ALOHA adaptive access method based on information age

Abstract

The application provides a time slot ALOHA adaptive access method which allows age gain threshold and sending probability to dynamically change with time slots under a multi-packet receiving mechanism. The method gives an initial age gain distribution, and performs the following steps in each time slot: each time slot initial access point sets sending probability and age gain threshold according to the estimated age gain distribution, aiming at maximizing current time slot AoI reduction expectation value; users whose real-time age gain is greater than or equal to the set threshold in each time slot access the channel with the set sending probability, if the number of simultaneously transmitted users in the time slot is less than or equal to the packet acceptance capacity γ of the receiving end, the transmission is successful, otherwise all fail; the access point at the end of each time slot records the observed information of the number of simultaneously transmitted users in the time slot; and the access point at the end of each time slot estimates the age gain distribution at the beginning of the next time slot based on the Bayesian updating theory according to the age gain distribution estimated at the beginning of the time slot, the observed information in the time slot and data arrival probability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless network communication, in particular to a time slot ALOHA adaptive access method based on information age. BACKGROUND

[0002] With the continuous development of communication technology, the number of terminals of Internet of Things is increasing, and the real-time requirement of transmission is becoming more and more strict. In the Internet of Things scenario, terminal users need to send data updates to the access point in real time so that they can make decisions in time according to the received information. As an important performance indicator for characterizing the freshness of the information received by the receiver, the optimization of information age (Age of Information, AoI) has become a research hotspot. Due to the mutual interference between users, the priority ranking of different users through age information can achieve better system information age performance. However, previous research lacks exploration of how to design an age-based adaptive random access method under the physical layer multiple-packet reception (MPR) mechanism. In the single-packet reception mechanism, the design of access parameters in the AAT method proposed by Chen et al. is based on the optimization of throughput rate rather than information age, so there is a large optimization space in the information age performance. Therefore, it is of great significance to set reasonable time-varying access parameters under the MPR mechanism to adapt to the dynamically changing interference environment in the system. SUMMARY

[0003] The present application aims to provide a time slot ALOHA adaptive access method based on information age, which can provide excellent system mean AoI performance under the MPR mechanism. The technical solution for realizing the purpose of the present application is as follows: after a given age gain initial distribution is given, the following steps are performed in each time slot:

[0004] Step 1: The initial AP of each time slot sets the transmission probability and age gain threshold according to the estimated age gain distribution, with the goal of maximizing the expected value of the current time slot AoI reduction;

[0005] Step 2: Users with real-time age gain greater than or equal to the set threshold in each time slot access the channel with the set transmission probability, and if the number of users transmitting simultaneously in the time slot is less than or equal to the packet acceptance capability γ of the AP, the transmission is successful, otherwise all fail;

[0006] Step 3: The AP records the observed information of the number of simultaneous transmission users at the end of each time slot;

[0007] Step 4: The AP estimates the age gain distribution at the beginning of the next time slot based on the Bayesian update theory according to the estimated age gain distribution at the beginning of the time slot, the observed information in the time slot, and the data arrival probability.

[0008] Compared with the prior art, the significant advantages of this invention are: this invention considers the data non-saturation model and MPR mechanism, and can achieve excellent system mean AoI performance under different parameters with low complexity. Attached Figure Description

[0009] Figure 1 This is a schematic diagram illustrating an application scenario of the present invention;

[0010] Figure 2 This is a flowchart of the time-slot ALOHA adaptive access method of the present invention;

[0011] Figures 3-4 This is a graph showing the system mean AoI curve of the slotted ALOHA adaptive access method of the present invention under different data arrival probabilities and MPR capabilities. Detailed Implementation

[0012] This invention focuses on an uplink scenario consisting of N (N≥2) users with the same priority and one access point. In this scenario, the time axis is divided into equal-length time slots k∈{1,2,...,K}, and each user and AP can accurately locate the boundaries of the time slots. Assume any user... At the initial time of each time slot k, a data packet is generated independently with probability λ, and each user retains only the most recently generated data packet. The real-time AoI of user i locally and at the AP for any time slot k are respectively... and And set initial values If user i generates a new data packet at the initial time of time slot k, then update Otherwise update like Figure 1 As shown, assume that the N users transmit data to the AP through a shared channel, and the AP's data packet receiving capacity is 1 ≤ γ ≤ N, meaning that all data packets are successfully transmitted when the number of packets transmitted simultaneously in each time slot is less than or equal to γ; otherwise, all transmissions fail. Assume that at the end of any time slot, the AP sends transmission feedback for that time slot to each user through an error-free and delay-free control channel. Define the real-time age gain of user i in any time slot k as... Let f be the probability that the real-time AoI of any user terminal in the system estimated by the AP at the initial time slot k is x and the real-time AoI of the AP terminal is y. k (x,y),x≥0,y≥1,y≥x.

[0013] Figure 2 This is a flowchart illustrating the time-slotted ALOHA adaptive access method of the present invention. Figure 2 As shown, a time-slot ALOHA adaptive access method based on information age is described. The method, after providing an initial age gain distribution, performs the following steps in each time slot:

[0014] Step 1: The AP at the beginning of time slot k sets the transmission probability and the age gain threshold according to the estimated age gain distribution:

[0015] Step 1-1: Calculate the probability that the real-time age gain of any user in the system estimated by the AP at the beginning of time slot k is g:

[0016] Step 1-2: Set the age gain threshold of time slot k as follows:

[0017]

[0018] Step 1-3: Set the transmission probability of time slot k as follows:

[0019]

[0020] where the parameter z is solved by the following fixed point iteration:

[0021]

[0022] The iteration initial value z(0) takes any real number in [1, γ].

[0023] Step 2: The users in time slot k that meet the threshold condition access the channel according to the transmission probability: the set of users that meet the threshold condition Any user in the set transmits a data packet with probability p k , and the real-time AoI of the AP end of any successful transmission user j will become while the real-time AoI of the AP end of the remaining users will increase by 1.

[0024] Step 3: The AP records the observed information of the number of simultaneous transmission users in time slot k: the channel state observed by the AP in time slot k is denoted as c k , and is defined as follows:

[0025]

[0026] where r k represents the number of users transmitting in time slot k.

[0027] Step 4: The AP estimates the age gain distribution at the beginning of the next time slot based on the Bayesian update theory according to the age gain distribution estimated at the beginning of the time slot, the observed information in the time slot, and the data arrival probability:

[0028] Step 4-1: Calculate the probability π k that any user in the system meets the threshold condition estimated by the AP at the beginning of time slot k:

[0029]

[0030] Step 4-2: Based on observation information c k Calculate the minimum number of users n that satisfy the threshold condition. min :

[0031]

[0032] Step 4-3: Calculate the observed information c when the number of users satisfying the threshold condition is n. k conditional probability η c,n :

[0033]

[0034] Step 4-4: Calculate the conditional probability β of the following condition at the initial time slot k+1: given that the real-time AoI of any user terminal is x′, the real-time AoI of the AP is y′, and the channel state is c. x,y,c,x′,y′ Based on whether the real-time age gain of any user i reaches the threshold, and whether user i successfully transmits data packets within time slot k, β x,y,c,x′,y′ The calculation can be divided into the following four cases: (1) when Furthermore, user i successfully transmitted the data packet in time slot k, i.e., y′-x′<Γ. k x∈{x′+1,0},y=x′+1:

[0035] β x,y,c,x′,y′ =0. (8)

[0036] (2) When Furthermore, user i failed to transmit a data packet in time slot k, i.e., y′-x′<Γ. k x∈{x′+1,0},y=y′+1:

[0037]

[0038] (3) When Furthermore, user i successfully transmitted the data packet in time slot k, i.e., y′-x′≥Γ. k x∈{x′+1,0},y=x′+1:

[0039]

[0040] (4) When Furthermore, user i failed to transmit a data packet in time slot k, i.e., y′-x′≥Γ. k x∈{x′+1,0},y=y′+1:

[0041]

[0042] where 1(·) is an indicator function.

[0043] Step 4-5: update f k+1 (x,y) as follows:

[0044]

[0045] The method is implemented by using MATLAB software, the number of devices in the network is set to N=100, and the simulation time is K=100000 time slots.

[0046] Figures 3-4 Under the premise that the remaining parameters remain unchanged, the data arrival probability λ and the MPR capability γ are changed in turn, and the results show that the method has excellent system mean AoI performance under each parameter, thereby verifying the effectiveness of the method.

Claims

1. A time-slotted ALOHA adaptive access method based on the Age of Information (AoI), the scenario contains N users with the same priority and 1 Access Point (AP), characterized in that, The application divides a time axis into equal length time slots k∈{1, 2,..., K}, and each user can be accurately positioned to the boundary of the time slot; it is assumed that any user A data packet is generated at the initial moment of each time slot k with a probability λ, each user sends the newly generated data packet to the AP through a shared channel, and the data packet receiving capacity of the AP end is 1≤γ≤N, that is, when the number of data packets sent simultaneously in each time slot is less than or equal to γ, all are successful, otherwise all fail; the real-time AoI of any time slot k user i at the local and the AP end is marked as And And the initial value is set as If the user i generates a new data packet at the initial moment of the time slot k, then Otherwise The real-time age gain of any time slot k user i is defined as The probability that the AP estimates the real-time AoI of any user end in the system to be x and the real-time AoI of the AP end to be y at the initial moment of any time slot k is marked as f k (x, y), x≥0, y≥1, y≥x, after the initial distribution of the given age gain is given, the following steps are executed in each time slot: Step 1: Each time slot initial AP sets the transmission probability and age gain threshold according to the estimated age gain distribution, aiming to maximize the expected value of the current time slot AoI reduction; the transmission probability p of any time slot k k and the setting method of the age gain threshold Γ k are as follows: Step 1-1: Calculate the probability that the real-time age gain of any user in the system estimated by the AP at the initial time of time slot k is equal to g Steps 1-2: Set the age gain threshold for timeslot k as follows: Steps 1-3: Set the transmission probability for timeslot k as follows: where the parameter z is solved by the following fixed-point iteration: The iteration initial value z(0) takes any real number in [1, γ]; where j ∈ {0, 1, …, γ-1} represents the number of users whose real-time age gain is greater than or equal to the set threshold within the time slot k; Step 2: Users whose real-time age gain in each time slot is greater than or equal to the set threshold value access the channel with a set transmission probability, if the number of simultaneous transmissions in the time slot is less than or equal to the packet acceptance capacity γ of the AP end, the transmission is successful, otherwise all fail; the specific process of user access to the channel in any time slot k is: any user in the user set that meets the threshold condition accesses the channel with a probability p k of transmitting a data packet, and at the same time, the real-time AoI of any successful transmission user j at the AP end will become and the real-time AoI of the remaining users at the AP end will increase by 1. Step 3: Each AP records the observed information of the number of simultaneously transmitting users in the time slot; the specific process of recording the observed information of the number of simultaneously transmitting users in the time slot k by any AP is as follows: marking the channel state c that the AP can observe in the time slot k as c k and is defined as follows: where r k denotes the number of users transmitting within time slot k; Step 4: Each AP at the end of a time slot estimates the age gain distribution at the beginning of the next time slot based on the age gain distribution estimated at the beginning of the time slot, the observation information in the time slot and the data arrival probability based on the Bayesian updating theory. Any AP at the end of a time slot estimates the age gain distribution at the beginning of the next time slot based on the age gain distribution estimated at the beginning of the time slot, the observation information in the time slot and the data arrival probability based on the Bayesian updating theory. k+1 (x, y) x≥0,y≥1,y≥x The specific process is as follows: Step 4-1: Calculate the probability π that any user in the system satisfies the threshold condition at the initial time of time slot k as estimated by AP k : Step 4-2: Based on observation information c k Calculate the minimum number of users n that satisfy the threshold condition min : Step 4-3: Calculate the observation information c when the number of users satisfying the threshold condition is n k η c,n : Step 4-4: Calculate the conditional probability β that at the initial moment of time slot k+1, the real-time AoI of any user end is x, the real-time AoI of AP end is y, and the channel state is c, given that at the initial moment of time slot k, the real-time AoI of any user end is x', the real-time AoI of AP end is y', and the channel state is c x,y,c,x′,y′ Step 4-4-1: Calculate the conditional probability β that at the initial moment of time slot k+1, the real-time AoI of any user end is x, the real-time AoI of AP end is y, and the channel state is c, given that at the initial moment of time slot k, the real-time AoI of any user end is x', the real-time AoI of AP end is y', and the channel state is c, and the real-time AoI gain of any user i does not reach the threshold value, and the user i does not successfully transmit a data packet in time slot k x,y,c,x′,y′ Step 4-4-2: Calculate the conditional probability β that at the initial moment of time slot k+1, the real-time AoI of any user end is x, the real-time AoI of AP end is y, and the channel state is c, given that at the initial moment of (1) when and user i has successfully transmitted a data packet at time slot k, i.e., y'-x' < Γ k , x e {x' + 1, 0}, y = x' + 1: β x,y,c,x′,y′ ＝0； (8) (2) when and user i has not successfully transmitted a data packet at time slot k, i.e., y'-x' < Γ k x e {x' + 1, 0}, y = y' + 1: (3) when and user i successfully transmitted a packet at time slot k, i.e., y'-x'≥Γ k x e {x' + 1, 0}, y = x' + 1: (4) when and user i has not successfully transmitted a packet at time slot k, i.e., y'-x' ≥ Γ k x e {x' + 1, 0}, y = y' + 1: where 1(·) is the indicator function; Step 4-5: Update f k+1 (x, y) as follows:

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