CN112165716B - Wireless network information age optimization scheduling method supporting retransmission - Google Patents

Wireless network information age optimization scheduling method supporting retransmission Download PDF

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CN112165716B
CN112165716B CN202011051055.7A CN202011051055A CN112165716B CN 112165716 B CN112165716 B CN 112165716B CN 202011051055 A CN202011051055 A CN 202011051055A CN 112165716 B CN112165716 B CN 112165716B
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time slot
loss
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CN112165716A (en
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王恒
李霄哲
余蕾
王平
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Chongqing University of Post and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0446—Resources in time domain, e.g. slots or frames
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention relates to a wireless network information age optimization scheduling method supporting retransmission, and belongs to the technical field of wireless network communication. The method is used for optimizing the network information age by adopting a time slot link scheduling mode in consideration of a data retransmission mechanism aiming at an uplink wireless communication network in which a plurality of nodes transmit data to a base station. And aiming at the scene of scheduling decision pre-static configuration, an information age optimization static scheduling method based on the minimum system expectation decision loss is adopted. Aiming at a scene that a scheduling decision can be dynamically configured along with time slots, a time slot-by-time information age optimization dynamic scheduling method based on the minimized dynamic expectation decision loss is adopted by utilizing the change characteristic of one-step expectation decision loss of nodes. The invention improves the reliability of wireless data transmission and improves the timeliness of network information transmission by adopting data retransmission and average information age optimization.

Description

Wireless network information age optimization scheduling method supporting retransmission
Technical Field
The invention belongs to the technical field of wireless network communication, and relates to a wireless network information age optimization scheduling method supporting retransmission.
Background
With the rapid development of wireless network technology, many real-time service scenarios are applied to the wireless network technology, which puts requirements on the timeliness of data transmission in the wireless network. For example, in real-time service scenarios such as vehicle-mounted communication and smart home, both communication parties are required to transmit data as soon as possible, so that the system can process data quickly. The Age of Information (AoI) is an index for measuring the timeliness of data transmission, and has important application in the field of wireless network communication. It represents the time interval from the generation time of the data newly received by the receiving end to the current time, and describes the freshness of the data currently received by the receiving end. The time slot scheduling is used for planning the information transmission sequence of two communication parties in a wireless network, and the timeliness of data transmission in the network can be effectively improved by optimizing the average information age of the network through the time slot scheduling method, so that the time slot scheduling method is an important means for improving the timeliness of network data transmission.
Meanwhile, considering that channel transmission in a wireless network is unreliable, the problem of packet loss is often generated in the data transmission process of the wireless network, and the packet loss not only causes waste of network communication resources, but also reduces the timeliness of data transmission in the network. The data retransmission is a simple and efficient technology for improving the reliability of network data transmission, and by retransmitting the result of the transmission failure in the last time slot, the packet loss problem can be relieved, and the timeliness of the data transmission can be improved to a certain extent. Therefore, how to consider the data retransmission mechanism and optimize the average information age of the network simultaneously makes the network capable of maintaining higher data transmission timeliness while improving reliability, and becomes an important challenge.
Aiming at the problem, the invention provides a wireless network information age optimization scheduling method supporting retransmission, which comprises a static scheduling method and a dynamic scheduling method, and improves the timeliness and reliability of network information transmission.
Disclosure of Invention
In view of this, the present invention provides a wireless network information age optimization scheduling method supporting retransmission, and simultaneously considers a data retransmission mechanism and an optimized network information age, and provides a corresponding static scheduling method and a corresponding dynamic scheduling method for two scenarios, namely, a scheduling decision static configuration in advance and a scheduling decision dynamic configuration at a time slot, so as to improve timeliness and reliability of network information transmission.
In order to achieve the purpose, the invention provides the following technical scheme:
a wireless network information age optimization scheduling method supporting retransmission optimizes the network information age by adopting a time slot link scheduling mode in consideration of a data retransmission mechanism aiming at an uplink wireless communication network in which a plurality of nodes transmit data to a base station. Specifically, the method specifically comprises the following steps:
s1: according to the information age updating characteristics of the nodes in the time slot network, one-step loss of the nodes is established, and then the one-step loss of each node in the system is summed to obtain the expected one-step loss of the system;
s2: aiming at two scenes that scheduling decision is statically configured in advance and scheduling decision can be dynamically configured at any time slot, a corresponding static scheduling method and a corresponding dynamic scheduling method are respectively adopted;
the static scheduling method comprises the steps of establishing system expectation decision loss by fusing the maximum retransmission times of nodes and the system expectation one-step loss, and obtaining a static scheduling table which is configured in advance under a current frame by adopting a minimization strategy;
the dynamic scheduling method calculates the expected scheduling success rate by utilizing the channel transmission success rate and the maximum retransmission times of the node, establishes the dynamic expected decision loss under the current time slot by combining the expected one-step loss of the system, and corrects the dynamic expected decision loss by considering the size between the maximum retransmission times of the node and the residual time slot of the current frame; and generating a scheduling decision of the current time slot according to the scheduling result of the upper time slot and the dynamic expectation decision loss strategy of the minimum system.
Further, in step S1, obtaining the expected further loss of the system specifically includes the following steps:
s11: assuming that there is one base station and M nodes in the wireless network, the nodes update to generate new data at the beginning of each frame and send to the base station in one frame, using symbol B to represent the base station and symbol uiRepresents an arbitrary node; and the frame length in the network is T, k is a frame label, T is a time slot label, and (k, T) identifies any time slot in the network;
Figure BDA0002709569880000021
represents an arbitrary node uiThe information age under the current time slot, and any node u in the time slot network according to the success and failure of the time slot scheduling resultiThe information age updating characteristic of (1), the expression is as follows:
Figure BDA0002709569880000022
wherein the content of the first and second substances,
Figure BDA0002709569880000023
represents an arbitrary node uiThe scheduling result in the time slot (k, t) has the value range of 0,1{,
Figure BDA0002709569880000024
indicates that the scheduling was successful, and
Figure BDA0002709569880000025
indicating that the scheduling fails;
Figure BDA0002709569880000026
represents an arbitrary node uiThe information age after the scheduling fails is updated, and t +1 represents any node uiUpdating the information age result after the scheduling is successful;
s12: according to the arbitrary node u obtained in the step S11iThe information age updating characteristic of (1) and establishing any node uiOne-step loss, the expression is as follows:
Figure BDA0002709569880000027
wherein the content of the first and second substances,
Figure BDA0002709569880000028
represents an arbitrary node uiThe loss is influenced by the scheduling result in the current time slot and the information age in the current time slot, and represents the information age loss caused by selecting and updating the current node for scheduling;
s13: for any node u in step S12iAnd performing expected calculation and linear summation on the one-step loss to obtain the expected one-step loss of the system, wherein the expression is as follows:
Figure BDA0002709569880000031
wherein, E [ Ck(t)]The expected loss of the system, which represents the expected loss brought by any time slot scheduling in the wireless network, is influenced by the information age of each node under the current time slot and the scheduling decision.
Further, in step S13, the specific calculation formula of the expected one-step loss of the system is:
Figure BDA0002709569880000032
Figure BDA00027095698800000311
Figure BDA0002709569880000034
wherein the content of the first and second substances,
Figure BDA0002709569880000035
representing a node uiThe scheduling decision result in time slot (k, t),
Figure BDA0002709569880000036
indicating that the node is selected as a scheduling decision in the current time slot, and
Figure BDA0002709569880000037
then it is indicated as not selected; p is a radical ofiIs node uiThe success rate of channel transmission between the base station B and the base station B is influenced by the channel quality; the constraint condition (1) is single-channel constraint and indicates that at most one user can be scheduled in the same time slot; constraint (2) is a scheduling constraint that is determined to indicate that the user node is only selected and not selected. The above expression gives the expected one-step loss of the system without considering the retransmission mechanism, and the expected one-step loss of the system is influenced by the number of nodes, the information age of each node, the transmission success rate of each node and the time slot scheduling decision by observing the above expression. Considering that the number of nodes is not changed, the influence of the number M of users can be ignored by regarding M as a system constant. Thus, the relationship among the information age of each node, the channel transmission success rate and the time slot scheduling decision is established.
Further, in step S2, the static scheduling method is considered in combination with a pre-arranged fixed retransmission mechanism, and corrects the system expected further loss by using the fixed retransmission characteristic thereof and using the maximum retransmission times of the node as a parameter variable, and establishes a system expected decision loss expression as a scheduling decision basis. And then, generating a static time slot scheduling table under the current frame by adopting a minimum system expectation decision loss strategy. The method specifically comprises the following steps:
s211: in the current frame k initial time slot, the base station updates the information age of each node in the current time slot according to the scheduling result of the previous frame
Figure BDA0002709569880000038
And establishes a scheduling set Uk(ii) a Then, by using the fixed retransmission characteristic of the pre-arranged fixed retransmission mechanism, the maximum retransmission times is used as one of the factors influencing the scheduling decision, and the relationship between the maximum retransmission times and the system expected one-step loss is established by combining the system expected one-step loss as follows:
Figure BDA0002709569880000039
wherein the content of the first and second substances,
Figure BDA00027095698800000310
for scheduling node uiRepresenting scheduling node u in response to expected decision lossiThe resulting age loss of desired information;
Figure BDA0002709569880000041
representing node uiWhether or not the time slot (k, t) is selected,
Figure BDA0002709569880000042
representing node uiMaximum number of transmissions, P, owned under frame kiRepresenting a node uiThe probability of successful scheduling at least once in the maximum retransmission time range is determined by formula
Figure BDA0002709569880000043
Is given in which piIs node uiThe channel transmission success rate of (1);
s212: based on step S211, for M network nodes, a system expected decision loss expression is established as follows:
Figure BDA0002709569880000044
wherein, E [ Co ]k(t)]The system expects a decision loss, which means the age loss of the network expectation information caused by scheduling any node;
s213: based on the system expected decision loss of step S212, a formalized expression for the strategy for minimizing the system expected decision loss is established as follows:
Figure BDA0002709569880000045
Figure BDA0002709569880000048
Figure BDA0002709569880000047
the constraint condition (1) is single-channel constraint and indicates that at most one user can be scheduled in the same time slot; the constraint condition (2) is to determine scheduling constraint, and represents that the user node is only selected or not selected; obtaining a node with minimum age loss of the network expectation information under the current time slot by adopting a minimum expectation decision loss strategy, wherein the node is an optimal scheduling decision under the current time slot;
s214: establishing a static scheduling table S under a current frame kkAnd traversing the node scheduling set U based on the minimum system expectation decision loss strategy obtained in the step S213kObtaining the node u with the minimum decision loss expected by the system under the current time slot (k, t)iNode uiAdding information such as corresponding scheduling time slot and maximum retransmission times into scheduling table SkInternal;
S215：updating node scheduling set UkDeleting the nodes added into the scheduling table; repeating step S214 until all time slots under the current frame k are used up or the scheduling set UkIs empty;
s216: obtaining a static scheduling table S under a current frame kkAnd scheduling according to the scheduling table.
Further, in step S2, the dynamic scheduling method utilizes the characteristic that the one-step expected decision loss of a node changes with time slot, and constructs a dynamic expected decision loss expression by calculating the expected scheduling success rate of each node from the current time slot and fusing the one-step expected decision loss of the system. And on the basis, the maximum retransmission times of the nodes and the size between the residual time slots of the current frame are considered and corrected. And finally, establishing different processing flows according to the scheduling result of the previous time slot and the minimization strategy so as to obtain the scheduling decision result under the current time slot. The method specifically comprises the following steps:
s221: if the current time slot is the initial time slot, directly entering step S222; otherwise, judging whether the current time slot needs to retransmit the upper time slot scheduling decision result according to the upper time slot scheduling result; if the condition "the scheduling of the last time slot fails and the maximum retransmission times is not reached" is satisfied, retransmitting the scheduling decision node of the last time slot, and proceeding to step S228, otherwise, proceeding to step S222;
s222: by calculating the expected scheduling decision probability of each node from the current time slot and combining the expected one-step loss of the system, the relationship between the retransmission times and the expected one-step loss of the system is established as follows:
Figure BDA0002709569880000051
wherein the content of the first and second substances,
Figure BDA0002709569880000052
is node uiRepresents the loss of node u in time slot (k, t)iExpected information age loss brought to the system as scheduling decision loss; the loss is caused byThe main reason for the age increase of the system information is that according to the geometric growth change characteristic of the age of the node information, the effect of making the average information age of the whole network smaller can be achieved by minimizing the dynamic expectation decision loss at each step;
s223: based on step S222, for M network nodes, a formal expression of the system dynamic expectation decision loss is established as follows:
Figure BDA0002709569880000053
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0002709569880000054
representing a node uiWhether or not the time slot (k, t) is selected,
Figure BDA0002709569880000055
node uiMaximum number of transmissions, P, owned in time slot (k, t)iRepresenting a node uiIn that
Figure BDA0002709569880000056
The probability of success at least once in a secondary transmission is given by the formula
Figure BDA0002709569880000057
To obtain wherein piIs node uiThe channel transmission success rate of (1); p (Y ═ r) represents the probability of the event "transmission was successful in the r-th transmission slot", and is represented by the formula P (Y ═ r) ═ Pi·(1-pi)r-1Giving out; f. of(i)(t) represents the frame edge effect, which means that the remaining time slot of the current frame is less than the maximum retransmission times of all the nodes to be scheduled in the node scheduling set, and is represented by the formula
Figure BDA0002709569880000058
Giving out;
s224: based on step S223, a minimum dynamic expectation decision loss strategy is obtained, and the expression is as follows:
Figure BDA0002709569880000059
Figure BDA00027095698800000512
Figure BDA00027095698800000511
where the system expects a decision loss E Cnk(t)]Given by step S4.3; the constraint condition (1) is single-channel constraint, which means that at most one user can be scheduled in the same time slot; the constraint condition (2) is to determine scheduling constraint, and represents that the user node is only selected or not selected;
s225: based on the policy of minimizing the dynamic expectation decision loss obtained in step S224, the node u that minimizes the dynamic expectation decision loss of the ordering system at the current time slot (k, t) is calculatedi；
S226: judging whether the node obtained in the step S225 is scheduled, if so, switching to a step S227; if not, go to step S228;
s227: base station updating scheduling node set UkRemoving the scheduled nodes from the node scheduling set, and turning to step S225;
s228: taking the node as a scheduling decision result of the current time slot to perform scheduling;
s229: and repeating the steps S221-S228 until the end of the current frame is reached, ending the frame time slot scheduling process, and entering the next frame.
The invention has the beneficial effects that:
(1) the invention simultaneously considers the data retransmission mechanism and the optimized network information age, combines the characteristics of different retransmission mechanisms, and optimizes the network information age by adopting a time slot scheduling mode, so that the network can maintain good reliability, reduce the average information age and improve the timeliness of information transmission.
(2) The invention considers two scheduling scenes of scheduling decision pre-static configuration and scheduling decision dynamic configuration at any time slot, provides a corresponding static scheduling method and a corresponding dynamic scheduling method by combining the data retransmission characteristics under different scheduling scenes, and meets the requirements on the timeliness of information transmission under different scheduling scenes.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention may be realized and attained by the means of the instrumentalities and combinations particularly pointed out hereinafter.
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For the purposes of promoting a better understanding of the objects, aspects and advantages of the invention, reference will now be made to the following detailed description taken in conjunction with the accompanying drawings in which:
FIG. 1 is a schematic diagram of network communication between a base station and a node according to the present invention;
FIG. 2 is a flow chart of the information age optimization static scheduling method of the present invention based on minimizing the system's expected decision loss;
fig. 3 is a flowchart of an information age optimization dynamic scheduling method based on minimizing dynamic expectation decision loss according to the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention in a schematic way, and the features in the following embodiments and examples may be combined with each other without conflict.
Referring to FIGS. 1-3, FIG. 1 is a schematic diagram of communication between a node and a base station, such asIn the illustrated wireless network, shown in fig. 1, a plurality of nodes transmit data to a base station, and the nodes generate status update data only at the beginning of a frame and transmit to the base station within one frame. Note node uiChannel transmission success rate with base station is piAnd according to the information age definition, the interval between the generation time of the data packet received by the receiving end most recently and the current time. The information age updating formula under the time slot model is established as follows:
Figure BDA0002709569880000071
wherein, the wireless network is supposed to adopt frame-by-frame scheduling, and the frame length is T; k is a frame label, t is a time slot label, and (k, t) uniquely identifies any time slot in the network;
Figure BDA0002709569880000072
represents an arbitrary node uiThe scheduling result at time slot (k, t) satisfies the following relation:
Figure BDA0002709569880000073
wherein the content of the first and second substances,
Figure BDA0002709569880000074
represents an arbitrary node uiThe information age under the current time slot, and any node u according to the success and failure of the updating resultiThe information age of the next slot can be represented by two results:
Figure BDA0002709569880000075
represents an arbitrary node uiThe updating result after the scheduling fails, and t +1 represents the node uiAnd updating results after the scheduling is successful.
According to the above formula, the node one-step loss can be preliminarily established, and the loss is influenced by the scheduling result of the node in the time slot (k, t), and can be expressed as the following formula:
Figure BDA0002709569880000076
definition of
Figure BDA0002709569880000077
Representing node u for scheduling decision of node in time slot (k, t)iWhether the current time slot is scheduled or not is evaluated as
Figure BDA0002709569880000078
Establishing
Figure BDA0002709569880000079
And
Figure BDA00027095698800000710
the relationship is as follows:
Figure BDA00027095698800000711
the expected one-step loss of the system can be obtained by combining the formulas (3) and (4):
Figure BDA00027095698800000712
in the above formula, E [ C ]k(t)]And representing the expected loss of the system in one step, wherein the one-step loss is formed by superposition of the expected losses of the nodes and represents the expected loss caused by arbitrary decision of the system in the time slot (k, t). Observing that the formula is influenced by the information age of the node and the scheduling decision of the current time slot, the current scheduling decision, namely the node with the maximum information age value, can be obtained by minimizing the expected one-step loss.
Then, the maximum retransmission times are introduced, and the above formula is corrected. Aiming at two scenes that scheduling decision is statically configured in advance and scheduling decision can be dynamically configured at any time slot, the invention respectively provides a corresponding static scheduling method and a corresponding dynamic scheduling method.
1) Combining time slot networks for static scheduling methodsThe information age updating characteristic of the middle node and the fixed retransmission characteristic of the pre-arranged fixed retransmission mechanism define the maximum retransmission times of the user in the frame k
Figure BDA0002709569880000081
The probability of an event "at least one successful transmission in all transmission slots" is known as follows:
Figure BDA0002709569880000082
in the above formula, piFor the node transmission success rate, the node expected decision loss is established based on the above formula under the condition that retransmission can be established as follows:
Figure BDA0002709569880000083
the loss represents the node uiThe expected loss of the current scheduling decision, which is the expected loss of the system, corresponds to both successful scheduling and failed scheduling, and can be given by the above formula.
And superposing the expected decision losses of all nodes to obtain the expected decision loss of the system, wherein the expected decision loss represents the expected loss caused by the system selecting any node as the current time slot scheduling, and is represented by the following formula:
Figure BDA0002709569880000084
according to the formulas (2) and (3), the following constraints exist:
Figure BDA0002709569880000085
on the basis of obtaining the formal expression of the system expectation decision loss, establishing a static scheduling empty table S under the current frame kkThe table indicates the node scheduling order within frame k. System expectation decision through repetition minimizationAnd losing to obtain a node scheduling sequence, and inserting the node scheduling sequence into the scheduling table to form a final static scheduling table.
2) Aiming at a dynamic scheduling method, according to a scheduling result of a previous time slot, a current scheduling decision is divided into three conditions, wherein in the first condition, the scheduling of the previous time slot fails, the maximum retransmission times are not reached, and the current scheduling decision of the time slot is kept the same as that of the previous time slot; in the second case, the scheduling of the previous time slot fails, but the maximum retransmission times is reached, and the scheduling decision of the current time slot should be dynamically generated; in the third situation, the scheduling of the previous time slot is successful, and the scheduling decision of the current time slot should be dynamically generated.
For dynamic retransmission, based on equation (5), the node expected decision loss is established as follows:
Figure BDA0002709569880000091
establishing the system expected decision loss based on equation (10) as follows:
Figure BDA0002709569880000092
in the formula (I), the compound is shown in the specification,
Figure BDA0002709569880000093
representing a node uiWhether or not the time slot (k, t) is selected,
Figure BDA0002709569880000094
node uiMaximum number of transmissions, P, owned in time slot (k, t)iRepresenting a node uiIn that
Figure BDA0002709569880000095
The probability of success at least once in the secondary transmission is given by the formula
Figure BDA0002709569880000096
To obtain wherein piIs node uiThe channel transmission success rate. P (Y ═ r) denotesThe probability of successful transmission of r transmission time slots is represented by the formula P (Y ═ r) ═ Pi·(1-pi)r-1It is given. f. of(i)(t) represents the frame edge effect, expressed by the formula
Figure BDA0002709569880000097
Giving out;
and judging whether the current time slot needs to be retransmitted or not according to the scheduling result of the last time slot. If the last time slot scheduling fails and the maximum retransmission times are not reached, the current time slot scheduling decision strategy is kept the same as the last time slot; if the previous time slot scheduling fails and the maximum retransmission times are reached, the current time slot scheduling decision should be dynamically generated; if the last time slot is successfully scheduled, the current time slot scheduling decision should be dynamically generated.
Example (b):
FIG. 2 is a flowchart of a method for optimizing static scheduling based on information age that minimizes system expected decision loss according to the present invention. The embodiment provides an implementation example for a static scheduling method, which specifically includes the following steps:
c1: the frame scheduling process begins.
C2: and the base station and the node are interacted to acquire the network parameter information.
C3: and the base station updates the information age information of each node according to the scheduling result of the previous frame.
C4: the base station establishes one-step loss of each node according to the obtained information
Figure BDA0002709569880000098
C5: and obtaining a formal expression of the expected one-step loss of the system according to the one-step loss of the nodes.
C6-C7: and according to a retransmission mechanism, correcting the loss of one step expected by the system to obtain a formalized expression of the decision loss expected by the system.
C8: and generating a static scheduling empty table under the current frame.
C9-C11: and repeatedly calculating to obtain nodes which minimize the expected decision loss of the system, sequentially entering the nodes into a table, and simultaneously establishing a mapping relation between the time slots and the node scheduling sequence according to the maximum retransmission times.
C12: and generating a static scheduling table under the current frame.
C13: and scheduling according to the static scheduling table in sequence.
C14: the frame scheduling process ends.
Fig. 3 is a flowchart of an information age optimization method based on minimizing dynamic expectation decision loss according to the present invention. As shown in fig. 3, an implementation example of the dynamic scheduling method in this embodiment specifically includes the following steps:
c1: the frame scheduling process begins.
C2: and the base station and the node interact to acquire network parameter information.
C3: and the base station updates the information age of each node according to the scheduling result of the previous frame.
C4: and judging the scheduling result of the upper time slot, if the scheduling of the upper time slot fails and the maximum retransmission times is not reached, switching to the step C5, otherwise, switching to the step C8.
C5: and retransmitting the scheduling decision of the previous time slot, and enabling the time slot t to be t + 1.
C6: and judging whether the frame end is reached, if so, switching to C7, and if not, switching to C3.
C7: and the frame time slot scheduling is finished.
C8: and establishing one-step loss of each node of the network, and obtaining a system expected one-step loss expression according to the one-step loss of the nodes.
C9-C12: and introducing the maximum retransmission times, and establishing a system dynamic expectation decision loss expression.
C13: minimizing the dynamic expectation decision loss expression to obtain the node u minimizing the dynamic expectation decision loss of the current systemi。
C14: judging node uiIf it has already been scheduled, go to C15 if it is, and go to C16 if it is not.
C15: the scheduled node is removed from the node schedule set and the new schedule set is updated.
C16: selecting the node uiReturning as the current time slot scheduling decision, let t be t +1, and go to C6.
Finally, the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all of them should be covered by the claims of the present invention.

Claims (4)

1. A wireless network information age optimization scheduling method supporting retransmission is characterized in that a static scheduling method based on minimum system expectation decision loss is adopted for a scene of scheduling decision pre-static configuration, and specifically comprises the following steps:
s1: according to the information age updating characteristics of the nodes in the time slot network, one-step loss of the nodes is established, and then the one-step loss of each node in the system is summed to obtain the expected one-step loss of the system; the method specifically comprises the following steps:
s11: assuming that there is one base station and M nodes in the wireless network, the nodes update to generate new data at the beginning of each frame and send to the base station in one frame, using symbol B to represent the base station and symbol uiRepresents an arbitrary node; and the frame length in the network is T, k is a frame label, T is a time slot label, and (k, T) identifies any time slot in the network;
Figure FDA0003672412850000011
represents an arbitrary node uiThe information age under the current time slot, and any node u in the time slot network according to the success and failure of the time slot scheduling resultiThe information age updating characteristic of (1), the expression is as follows:
Figure FDA0003672412850000012
wherein the content of the first and second substances,
Figure FDA0003672412850000013
means at willNode uiThe scheduling result under the time slot (k, t) has the value range of {0, 1},
Figure FDA0003672412850000014
indicates that the scheduling was successful, and
Figure FDA0003672412850000015
indicating that the scheduling fails;
Figure FDA0003672412850000016
represents an arbitrary node uiThe information age updating result after the scheduling fails, and t +1 represents any node uiUpdating the information age after the scheduling is successful;
s12: according to the arbitrary node u obtained in the step S11iThe information age updating characteristic of (1) and establishing any node uiOne-step loss, the expression is as follows:
Figure FDA0003672412850000017
wherein the content of the first and second substances,
Figure FDA0003672412850000018
represents an arbitrary node uiThe one-step loss under the time slot (k, t) represents the age loss of information caused by selecting and updating the current node for scheduling;
s13: for any node u in step S12iAnd performing expected calculation and linear summation on the one-step loss to obtain the expected one-step loss of the system, wherein the expression is as follows:
Figure FDA0003672412850000019
wherein, E [ Ck(t)]The expected loss of the system, which represents the expected loss brought by any time slot scheduling in the wireless network, is influenced by the information age and scheduling of each node under the current time slotImpact of the decision;
the specific formula for calculating the expected one-step loss of the system is as follows:
Figure FDA0003672412850000021
Figure FDA0003672412850000022
Figure FDA0003672412850000023
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003672412850000024
representing a node uiThe scheduling decision result in time slot (k, t),
Figure FDA0003672412850000025
indicating that the node is selected as a scheduling decision in the current time slot, and
Figure FDA00036724128500000213
then it is indicated as not selected; p is a radical ofiIs node uiThe channel transmission success rate with the base station B; the constraint condition (1) is single-channel constraint, which means that at most one user can be scheduled in the same time slot; the constraint condition (2) is to determine scheduling constraint, and represents that the user node is only selected or not selected;
s2: and establishing system expectation decision loss by fusing the maximum retransmission times of the nodes and the system expectation one-step loss, and obtaining a pre-configured static scheduling table under the current frame by adopting a minimization strategy.
2. The method for optimizing scheduling of wireless network information age supporting retransmission according to claim 1, wherein in step S2, the static scheduling method specifically includes the following steps:
s211: at the initial time slot of the current frame k, the base station updates the information age of each node under the current time slot according to the scheduling result of the previous frame
Figure FDA0003672412850000026
And establishes a scheduling set Uk(ii) a Then, by using the fixed retransmission characteristic of the pre-arranged fixed retransmission mechanism, the maximum retransmission times is used as one of the factors influencing the scheduling decision, and the relationship between the maximum retransmission times and the system expected one-step loss is established by combining the system expected one-step loss as follows:
Figure FDA0003672412850000027
wherein the content of the first and second substances,
Figure FDA0003672412850000028
for scheduling node uiRepresenting scheduling node u in response to expected decision lossiThe resulting age loss of desired information;
Figure FDA0003672412850000029
representing a node uiWhether or not the time slot (k, t) is selected,
Figure FDA00036724128500000210
representing a node uiMaximum number of transmissions, P, owned under frame kiRepresenting a node uiThe probability of successful scheduling at least once in the maximum retransmission time range is determined by formula
Figure FDA00036724128500000211
Is given in which piIs node uiThe channel transmission success rate of (1);
s212: based on step S211, for M network nodes, a system expected decision loss expression is established as follows:
Figure FDA00036724128500000212
wherein, E [ Co ]k(t)]The system expects a decision loss, which means the age loss of the network expectation information caused by scheduling any node;
s213: based on the system expected decision loss of step S212, a formalized expression for the strategy for minimizing the system expected decision loss is established as follows:
Figure FDA0003672412850000031
Figure FDA0003672412850000032
Figure FDA0003672412850000033
the constraint condition (1) is single-channel constraint and indicates that at most one user can be scheduled in the same time slot; the constraint condition (2) is to determine scheduling constraint, and represents that the user node is only selected or not selected; obtaining a node with minimum age loss of the network expectation information under the current time slot by adopting a minimum expectation decision loss strategy, wherein the node is an optimal scheduling decision under the current time slot;
s214: establishing a static scheduling table S under a current frame kkAnd traversing the node scheduling set U based on the minimum system expectation decision loss strategy obtained in the step S213kObtaining the node u with the minimum decision loss expected by the system under the current time slot (k, t)iNode uiAdding information such as corresponding scheduling time slot and maximum retransmission times into scheduling table SkInner;
s215: updating node scheduling set UkNode to be added to scheduleDeleting; repeating step S214 until all time slots under the current frame k are used up or the scheduling set UkIs empty;
s216: obtaining a static scheduling table S under a current frame kkAnd scheduling according to the scheduling table.
3. A wireless network information age optimization scheduling method supporting retransmission is characterized in that a dynamic scheduling method based on minimized dynamic expectation decision loss is adopted slot by slot aiming at a scene that scheduling decisions can be dynamically configured along with slots, and the method specifically comprises the following steps:
s1: according to the information age updating characteristics of the nodes in the time slot network, one-step loss of the nodes is established, and then the one-step loss of each node in the system is summed to obtain the expected one-step loss of the system; the method specifically comprises the following steps:
s11: assuming that there is one base station and M nodes in the wireless network, the nodes update to generate new data at the beginning of each frame and send to the base station in one frame, using symbol B to represent the base station and symbol uiRepresents an arbitrary node; and the frame length in the network is T, k is a frame label, T is a time slot label, and (k, T) identifies any time slot in the network;
Figure FDA0003672412850000034
represents an arbitrary node uiThe information age under the current time slot, and any node u in the time slot network according to the success and failure of the time slot scheduling resultiThe information age updating characteristic of (1), the expression is as follows:
Figure FDA0003672412850000035
wherein the content of the first and second substances,
Figure FDA0003672412850000036
represents an arbitrary node uiThe scheduling result under the time slot (k, t) has the value range of {0, 1},
Figure FDA0003672412850000037
indicates that the scheduling was successful, and
Figure FDA0003672412850000038
indicating that the scheduling fails;
Figure FDA0003672412850000039
represents an arbitrary node uiThe information age updating result after the scheduling fails, and t +1 represents any node uiUpdating the information age result after the scheduling is successful;
s12: according to the arbitrary node u obtained in the step S11iThe information age updating characteristic of (1) and establishing any node uiOne-step loss, the expression is as follows:
Figure FDA0003672412850000041
wherein the content of the first and second substances,
Figure FDA0003672412850000042
represents an arbitrary node uiThe one-step loss under the time slot (k, t) represents the age loss of information caused by selecting and updating the current node for scheduling;
s13: for any node u in step S12iAnd performing expected calculation and linear summation on the one-step loss to obtain the expected one-step loss of the system, wherein the expression is as follows:
Figure FDA0003672412850000043
wherein, E [ Ck(t)]One-step loss is expected for a system, and the expected loss brought by any time slot scheduling in a wireless network is influenced by the information age of each node under the current time slot and a scheduling decision;
the specific calculation formula of the system expected one-step loss is as follows:
Figure FDA0003672412850000044
Figure FDA0003672412850000045
Figure FDA0003672412850000046
wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003672412850000047
representing a node uiThe scheduling decision result in time slot (k, t),
Figure FDA0003672412850000048
indicating that the node is selected as a scheduling decision in the current time slot, and
Figure FDA0003672412850000049
then it is indicated as not selected; p is a radical of formulaiIs node uiThe channel transmission success rate with the base station B; the constraint condition (1) is single-channel constraint, which means that at most one user can be scheduled in the same time slot; the constraint condition (2) is to determine scheduling constraint, and represents that the user node is only selected or not selected;
s2: calculating to obtain an expected scheduling success rate by utilizing the channel transmission success rate and the maximum retransmission times of the node, establishing a dynamic expected decision loss under the current time slot by combining the expected one-step loss of the system, and correcting the dynamic expected decision loss by considering the size between the maximum retransmission times of the node and the remaining time slot of the current frame; and generating a scheduling decision of the current time slot according to the scheduling result of the upper time slot and the strategy of minimizing the system dynamic expectation decision loss.
4. The method for optimizing and scheduling the age of wireless network information supporting retransmission according to claim 3, wherein in step S2, the dynamic scheduling method specifically includes the following steps:
s221: if the current time slot is the initial time slot, directly entering step S222; otherwise, judging whether the current time slot needs to retransmit the upper time slot scheduling decision result according to the upper time slot scheduling result; if the condition "the scheduling of the last time slot fails and the maximum retransmission times is not reached" is satisfied, retransmitting the scheduling decision node of the last time slot, and proceeding to step S228, otherwise, proceeding to step S222;
s222: by calculating the expected scheduling decision probability of each node from the current time slot and combining the expected one-step loss of the system, the relationship between the retransmission times and the expected one-step loss of the system is established as follows:
Figure FDA0003672412850000051
wherein the content of the first and second substances,
Figure FDA0003672412850000052
is node uiRepresents the loss of node u in time slot (k, t)iExpected information age loss brought to the system as scheduling decision loss;
s223: based on step S222, for M network nodes, a formal expression of the system dynamic expectation decision loss is established as follows:
Figure FDA0003672412850000053
wherein the content of the first and second substances,
Figure FDA0003672412850000054
representing a node uiWhether or not the time slot (k, t) is selected,
Figure FDA0003672412850000055
representing nodesuiMaximum number of transmissions, P, owned in time slot (k, t)iRepresenting a node uiIn that
Figure FDA0003672412850000056
The probability of success at least once in the secondary transmission is given by the formula
Figure FDA0003672412850000057
To obtain wherein piIs node uiThe channel transmission success rate of (1); p (Y ═ r) represents the probability of the event "transmission was successful in the r-th transmission slot", and is represented by the formula P (Y ═ r) ═ Pi·(1-pi)r-1Giving out; f. of(i)(t) represents the frame edge effect, which means that the remaining time slot of the current frame is less than the maximum retransmission times of all the nodes to be scheduled in the node scheduling set, and is represented by the formula
Figure FDA0003672412850000058
Giving out;
s224: based on step S223, a minimum dynamic expectation decision loss strategy is obtained, and the expression is as follows:
Figure FDA0003672412850000059
Figure FDA00036724128500000510
Figure FDA00036724128500000511
where the system expects a decision loss E Cnk(t)]Given by step S4.3; the constraint condition (1) is single-channel constraint, which means that at most one user can be scheduled in the same time slot; the constraint condition (2) is to determine scheduling constraint, and represents that the user node is only selected or not selected;
s225: based on the policy of minimizing the dynamic expectation decision loss obtained in step S224, the node u that minimizes the dynamic expectation decision loss of the ordering system at the current time slot (k, t) is calculatedi；
S226: judging whether the node obtained in the step S225 is scheduled, if so, switching to a step S227; if not, go to step S228;
s227: base station updating scheduling node set UkRemoving the nodes which are scheduled from the node scheduling set, and turning to the step S225;
s228: taking the node as a scheduling decision result of the current time slot to perform scheduling;
s229: and repeating the steps S221-S228 until the end of the current frame is reached, ending the frame time slot scheduling process, and entering the next frame.
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