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CN111065154B - Efficient energy-saving scheduling method applied to high-density WLAN - Google Patents

Efficient energy-saving scheduling method applied to high-density WLAN Download PDF

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CN111065154B
CN111065154B CN201911217884.5A CN201911217884A CN111065154B CN 111065154 B CN111065154 B CN 111065154B CN 201911217884 A CN201911217884 A CN 201911217884A CN 111065154 B CN111065154 B CN 111065154B
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CN111065154A (en
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陈清华
施郁文
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Wenzhou Polytechnic
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/02—Power saving arrangements
    • H04W52/0203—Power saving arrangements in the radio access network or backbone network of wireless communication networks
    • H04W52/0206—Power saving arrangements in the radio access network or backbone network of wireless communication networks in access points, e.g. base stations
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/02—Power saving arrangements
    • H04W52/0209—Power saving arrangements in terminal devices
    • H04W52/0212—Power saving arrangements in terminal devices managed by the network, e.g. network or access point is master and terminal is slave
    • H04W52/0216—Power saving arrangements in terminal devices managed by the network, e.g. network or access point is master and terminal is slave using a pre-established activity schedule, e.g. traffic indication frame
    • 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

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Abstract

The invention discloses a high-efficiency energy-saving scheduling method applied to a high-density WLAN, which is characterized by comprising the following steps that a station requesting dormancy sends TWT (target wakeup time) request frames to an AP (access point), the AP determines the optimal number of service stations in uplink random access according to network parameters, and determines the optimal LI (listen interval) and TBTT (target beacon frame transmission time) values of the station in different modes according to different network densities; when the network density is high, a knapsack decision-making mode is adopted to determine the value of the LI, and when the network density is low, the LI is adjusted to realize the optimal number of service sites; the AP returns the TBTT time parameter to each station through the TWT response frame; after receiving the response frame, the station enters a dormant state; and the station wakes up at a specified time to receive the beacon frame carrying the TWT service period information. The invention controls the number of stations waking up at the same time, reduces competition as much as possible on the premise of ensuring the throughput rate, and finally achieves the aim of improving the overall throughput rate and the energy efficiency of the terminal station.

Description

Efficient energy-saving scheduling method applied to high-density WLAN
Technical Field
The invention relates to the technical field of communication, in particular to an efficient energy-saving scheduling method applied to a high-density WLAN.
Background
A WLAN (wireless local area network) based on IEEE802.11 has a wide application range because it supports user mobility, has strong deployment flexibility, low maintenance cost, and strong scalability. With the improvement of network access requirements and the increase of demands, a large number of APs (access points) are deployed in public places such as airports, railway stations, large stadiums and the like, so that mobile users can conveniently access to a network anytime and anywhere and uninterruptedly. In the face of limited unlicensed spectrum resources, densely deployed (high-density) WLANs have a sharp decline in network performance due to their channel access contention mechanism and mutual interference. The AP is usually powered by a power supply, the position is basically fixed, and less research relates to AP energy saving. Wireless communication terminal devices are often powered by batteries carrying limited energy sources for mobility and portability. Therefore, how to guarantee the terminal device to operate for a longer time becomes a research focus. Typically, the end station can turn off the wireless transceiver into a sleep state to reduce power consumption, with longer sleep states and shorter times for transmission, resulting in more power savings for the device.
Aiming at a dense environment, a TWT (TargetWakeTime, target wake-up time) energy-saving mechanism is introduced into the next generation WLAN, a broadcast TWT mechanism is innovatively provided aiming at a multi-user transmission technology, and a terminal station which does not receive and transmit data in a short time enters a sleep state as much as possible to realize the energy saving of a mobile terminal. The broadcast TWT is preceded by a TBTT (targetbeacon transmission time) schedule, and the TWT service period is broadcast by controlling the TBTT time of each station.
The unequal number of stations waking up at the same time necessarily causes excessive contention in some beacon frame slots and waste of resources in some slots. However, in the next generation WLAN protocol draft, no explicit specification is made on the scheduling mechanism of when the sleeping demanded station wakes up, and instead, the scheduling mechanism is implemented by each wireless network interface hardware vendor.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an efficient energy-saving scheduling method applied to a high-density WLAN (wireless local area network) by combining an uplink multi-user simultaneous transmission mechanism.
In order to achieve the purpose, the invention provides the following technical scheme: an efficient energy-saving scheduling method applied to a high-density WLAN is characterized by comprising the following steps
Each station requesting dormancy sends a TWT (target wakeup time) request frame to the AP in sequence;
the AP calls a centralized scheduling process to determine LI (ListenInterva, interception interval) and TBTT (target beacon frame transmission time) values by combining network parameters and site density, and returns the TBTT moment of the awakening sleeping site to each site through a TWT response frame;
after receiving the TWT response frame, the station enters a dormant state and wakes up at the appointed TBTT moment to receive a beacon frame carrying TWT service period information;
when the station is dormant, the data sent to the station by the AP is stored in an AP buffer area;
when the station wakes up, the station may initiate a request to the AP to receive data stored in the AP buffer;
when the AP buffer zone overflows, the AP can send a request for reducing the interception interval to a larger station occupying the buffer zone;
for a station with small traffic, the AP may make a request to increase the listening interval to the station;
a deterministic channel access strategy is designed for the data transmission process of the TWT service period where the wake-up station is located.
As a further improvement of the invention, a GTSS (packet-based target wakeup time scheduling scheme) scheme is preset in the AP, and LI and the first TBTT value are obtained through the GTSS scheme to determine all TBTT time moments, wherein the GTSS scheme comprises
Determining the optimal number of service stations according to key backoff parameters in the uplink access process; determining stations in a TWT service period in different modes or adjusting station interception intervals LI to be optimal according to the station density in the network;
grouping according to the obtained final dormant station set and the corresponding interception interval value, classifying the corresponding stations into different groups, carrying out TBTT scheduling on the stations with the common interception interval attribute in the groups, and carrying out the equalization of the dislocation between the groups and the awakening stations through the drift of the initial index.
As a further improvement of the invention, the relationship between the overall throughput rate and the average number of active stations waking up in each beacon frame time is determined according to the station density in the network and the parameters in the backoff mechanism, including the minimum backoff window size, the maximum backoff window size, the backoff level, the number of available channel resources, the data transmission rate of the channel, the probability of successful backoff, and the probability of successful channel selection by the station.
As a further improvement of the invention, the step of acquiring TBTT value in the GTSS scheme comprises
Sequencing the given optimal listening intervals, classifying the given optimal listening intervals into different subsets according to different characteristics, and classifying the corresponding sites into corresponding subsets;
staggering TBTT of the stations, and controlling the number of awakening stations in each beacon frame time slot in the group;
the initial index of the list of timeslots for each beacon frame is randomly drifted.
As a further improvement of the invention, the relationship between the throughput rate and the optimal number of the waking stations is obtained according to the station density in the network and the parameters in the back-off mechanism, and the average number of the waking stations waking up in each beacon frame time in the transmission period is determined according to the relationship, so as to obtain the optimal listening interval LI.
As a further improvement of the invention, when the density of stations in the network is high, the optimal listening interval LI combination is obtained by deciding whether all the stations enter the sleep state, and when the density of the stations in the network is low, the difference value between the existing competition level and the optimal competition level is calculated, and the value of the listening interval LI of the stations is proportionally adjusted.
As a further improvement of the invention, the listening intervals are sorted, and according to different characteristics, the different characteristics included in different subsets are characterized in that each element in the same subset and other elements with smaller values in the subset are in a positive integer multiple relation.
As a further improvement of the invention, when the station wakes up, when the number of the active stations is less than or equal to the number of the available channel resources, a deterministic access mechanism is adopted, and the AP divides the TWT service period into a BSRP stage and a data transmission stage according to the number of the waking stations in the TBTT time; by means of a designed BSRP (polling) phase, the waking stations are polled for buffer status according to the number of available channels and access the channels by centralized determinism in the subsequent data transmission phase.
The invention has the advantages that the awakening interval of the station can be adjusted, the time for the station to connect with the AP is reduced, the energy consumption of the station is reduced by controlling the station to be in a dormant state, meanwhile, the channel allocation of the AP can be allocated to realize high-efficiency deterministic channel access, and the use efficiency of the channel can be improved while saving energy.
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FIG. 1 is a diagram illustrating the layout result of an embodiment of the present invention;
FIG. 2 is a diagram illustrating the grouping and results of intra-group grouping of the present invention;
FIG. 3 is a graph illustrating the drift results of the present invention;
FIG. 4 is a flow chart of algorithm 2 of the present invention;
FIG. 5 is a schematic diagram of a deterministic channel access procedure during a TWT service period in accordance with the present invention;
fig. 6 is a frame structure diagram of the improved TWT information element of the present invention.
Detailed Description
The invention will be further described in detail with reference to the following examples, which are given in the accompanying drawings.
Referring to fig. 1 to 6, the method for scheduling high-efficiency and energy-saving for high-density WLAN of this embodiment is characterized by comprising the following steps
Each station requesting dormancy sends a TWT (target wakeup time) request frame to the AP in sequence, the AP determines an LI (listening interval) and a TBTT (target beacon frame transmission time) value, and the station waking up the TBTT time through a TWT response frame and returns to each station;
after receiving the TWT response frame, the station enters a sleep state and wakes up at the appointed TBTT moment to receive a beacon frame carrying the TWT service period information;
when the station is dormant, the data sent to the station by the AP is stored in an AP buffer area;
when the station wakes up, the station may initiate a request to the AP to accept the data stored in the AP buffer;
when the AP buffer zone overflows, the AP can send a request for reducing the interception interval to a larger station occupying the buffer zone;
for a station with low traffic, the AP may make a request to increase the listening interval to the station.
In the scheme, before each station sleeps, a TWT request frame is sent to an AP, the AP determines an LI (inter-Integrated Circuit) and TBTT (tunnel boring time) value corresponding to the request frame after receiving the TWT request frame, and returns the TBTT time of waking up of the sleeping station to each station in a TWT response frame mode, and the station can enter a sleeping state after receiving the corresponding TWT response frame until the station sleeps to the corresponding TBTT time and then wakes up to communicate with the AP; during the sleep period of the station, the data sent to the station by the AP is firstly stored in the AP buffer area, and the data is temporarily stored, so that the required complete data can be conveniently transmitted at one time, and the waste of the channel due to the fact that the channel is occupied for a long time but only used for discontinuously transmitting the data is avoided; the station sends a request to the AP to receive the data of the AP buffer zone when the station wakes up, and the station can receive all the cached data at one time, so that the use efficiency of the channel can be improved, and the condition that the channel is occupied for a long time but only used for discontinuously transmitting the data is avoided. Wherein AP can real-time detection AP buffer's data storage state, if the AP buffer appears the data and overflows, AP can propose the request that reduces the interception interval to the great station that occupies AP buffer data this moment, and then shortens and listens the interval length, lets the interception frequency higher, and then avoids the AP buffer to overflow. On the contrary, if the AP buffer is not occupied for a long time, the AP sends a request for increasing the listening interval to the AP, thereby preventing the AP from waking up the station with a small data usage amount frequently. Therefore, the awakening interval of the station can be adjusted, the time for the station to connect with the AP is shortened, the energy consumption of the station is reduced by controlling the station to be in a dormant state, the channel allocation of the AP can be allocated, and the use efficiency of the channel can be improved while energy is saved.
As an embodiment of the optimization, a GTSS (packet-based target wakeup time scheduling scheme) scheme is preset in the AP, and LI and TBTT values are obtained through the GTSS scheme, where the GTSS scheme includes determining an optimal number of service stations and an optimal listening interval LI according to a station density in a network and parameters in a backoff mechanism;
and grouping the interception interval values, classifying the corresponding stations into different groups, scheduling the stations with the common interception interval attribute in the groups by TBTT, and carrying out the equalization of dislocation between the groups and the awakening stations by the drift of the initial index.
The obtained interception interval LI can be more suitable for the high-density WLAN by combining the station density and the backoff mechanism, and the energy-saving effect of the stations in the high-density WLAN can be controlled. The stations are grouped through different station interception interval values, the stations with the common interception interval attribute in the same group are scheduled by the TBTT, the stations in the same group have more efficient channel layout and energy-saving effect by the energy-saving scheduling scheme of the TBTT, and all the stations can perform efficient energy saving by combining the grouping effect.
Specifically, the relationship between the overall throughput rate and the average number of active stations waking up in each beacon frame time is determined according to the station density in the network and the parameters in the backoff mechanism, including the minimum backoff window size, the maximum backoff window size, the backoff level, the number of available channel resources, the probability of successful backoff calculated by the data transmission rate of the channel, and the probability of successful channel selection by the station.
The relationship between the throughput rate and the optimal number of awakening stations is obtained according to the parameters as follows:
formula 1
Figure BDA0002298856590000061
Formula 2
Figure BDA0002298856590000062
Formula 3
Figure BDA0002298856590000063
Formula 4
Figure BDA0002298856590000071
The number of the stations requesting dormancy is n, and is marked as a set S ═ SiI ═ 1, 2., n }, and the corresponding listen interval set is denoted as T ═ { T ═ T ·i1, 2.. times.n.the first TBTT value of the ith station is denoted as fi(i ∈ {1, 2.., n }), the specified TBTT time w of wake-upi＝fi+mi×ti(miIs an integer of 0 or more);
in the formulas 1 to 4, θ represents the throughput;
Figure BDA0002298856590000077
indicating the average number of awake stations in each beacon frame time during the transmission period. 1/tiIndicating the average frequency with which the station wakes up. From the above definitions, equation 5 can be obtained:
formula 5
Figure BDA0002298856590000072
Furthermore, TT、TDAnd TMRespectively representing the average time of transmitting a trigger frame (TriggerFrame), a data frame (DataFrame) and a Multi-ACK block (Multi-Block ACK); p is a radical of1Indicates the probability of success of backoff, b indicates the backoff level, OCWmin、OCWmaxRespectively, a minimum and a maximum backoff window size, W represents a minimum window value OCWmin+1；p2Representing the probability of a station successfully selecting a channel; m represents the number of available channel resources, and gamma represents the data transmission rate on one channel;
according to the obtained optimal number of sites served simultaneously
Figure BDA0002298856590000073
The specific method employed is determined. Apparently, p is1、p2And
Figure BDA0002298856590000075
in which p is1And p2、
Figure BDA0002298856590000074
And p2Are respectively inversely correlated and the three are positively correlated with the overall throughput rate in equation (2). Thus, given network parameters, the optimum can be determined
Figure BDA0002298856590000076
Calculating p1And p2To maximize the throughput rate theta.
The algorithm 1 gives the process of searching the optimal service site number, the input is the solving precision e of each network parameter and the throughput rate, and the output is
Figure BDA0002298856590000078
The optimal number of service sites is indicated. Searching for the optimum step by a descent method
Figure BDA0002298856590000079
To finally find the optimal throughput rate.
Obtaining p without solving1And p2In the case of (2), the function Cal _ θ is used to calculate the throughput rate. Under the condition of network parameters such as the number n of the given stations, the number m of the RUs which can be used for random access, the size of a backoff window and the like, p is continuously approximated2The throughput rate θ is obtained. The parameter e in the function is also used to constrain the solution accuracy.
Algorithm 1: algorithmic process to obtain optimal serving site data
Figure BDA0002298856590000081
Figure BDA0002298856590000091
When it is original
Figure BDA0002298856590000092
The following optimization problem is obtained, and the optimization problem is solved by reducing the interception interval value to obtain any station siCorresponding value t of optimized LIi′。
Formula 6Max theta (6)
w.r.tt1′，t2′，...，tn′
Figure BDA0002298856590000093
S′＝{si|ti′＝0，i＝1，2，...，n}； (6b)
ti′≤tj′，ifti≤tj； (6c)
i，j∈{1，2，…，n}. (6d)
Corresponding to the optimal throughput rate and the optimal number of service sites
Figure BDA0002298856590000107
There may be multiple combined solutions for the relevant station listen interval values. Constraints (6c) are proposed in view of the dormancy requirement values proposed by each site itself. It aims to make AP able to scale the interception interval value according to the sleep duration requirement first proposed by the station and finally obtain the corresponding optimal value
Figure BDA0002298856590000101
Value of
Figure BDA0002298856590000102
In particular, let s be arbitraryiOf the optimal LI value ti' is
Formula 7
Figure BDA0002298856590000103
Wherein the function R (·) represents rounding.
When it is original
Figure BDA0002298856590000104
The following optimization problem is obtained, and the site is put into a dormant state through a decision knapsack problem, so that the optimal throughput rate and energy efficiency are obtained.
Formula 8Max theta (8)
w.r.t a1，a2，...，an
Figure BDA0002298856590000105
S′＝{si|ai＝0，i＝1，2，...，n}； (8b)
ai∈{0，1}，i∈{1，2，…，n}. (8c)
Wherein a isi0 denotes site siWithout the need for accessTWT service period of scheduling, otherwise siAccording to tiWake up at intervals. The problem is a simple knapsack problem, and various existing methods are solved to obtain a global optimal solution, such as an exhaustive method, a Hungarian algorithm and the like. In order to save the whole actual energy consumption of the station and the calculated amount of the AP, the station with the minimum dormancy interval value is preferentially judged as refusing to enter the TWT service period until the optimal TWT service period is met
Figure BDA0002298856590000106
By heuristic, the algorithm complexity can be reduced below O (n).
And determining the optimal listening interval LI through the selection of the two schemes.
After LI has been allocated, a first TBTT value needs to be determined, a preferred embodiment is provided below:
the step of acquiring the TBTT value in the GTSS scheme comprises
Sequencing the given optimal listening intervals, classifying the given optimal listening intervals into different subsets according to different characteristics, and classifying the corresponding sites into corresponding subsets;
staggering TBTT of the stations, and controlling the number of awakening stations in each beacon frame time slot in the group;
the initial index of the list of timeslots for each beacon frame is randomly drifted.
In the above scheme, the listening intervals are firstly sequenced, so that subsequent classification grouping and division into different subsets are facilitated, and corresponding subset division is performed on the stations. The first TBTT of a station is then staggered in time to control the number of stations that wake up per beacon frame slot, thereby increasing the efficiency of use per channel. And finally, randomly shifting the initial index, thereby realizing the equalization of the dislocation between groups and the wake-up station.
Specifically, the method for determining the first TBTT is divided into the following three steps:
(1) step 1 (grouping): and according to different properties of the interception interval values, grouping the corresponding stations, and enabling the stations with the interception intervals having a positive integer multiple relation to enter the same group. The method comprises the steps of firstly sequencing the interception intervals, classifying the interception intervals into different subsets according to different characteristics, and finally classifying the sites into corresponding subsets.
Taking T ═ {8, 18, 9, 3, 3, 4, 2, 6, 12, 6, 9} as an example, the sorted listening interval result T is obtainedo＝{2，3，4，6，8，9，12，18}。ToFirst element 2 of (1) is first included in the newly generated subset sut1(ii) a Then ToIs 3, since it cannot be divided exactly by 2, falls under the new subset sut2(ii) a The 3 rd element is 4 since it can be SubT1All elements in (1) are divided equally, so 4 falls under the subset sut1In (1). By analogy, the subset division result of the listening interval is obtained as follows: SubT1＝{2，4，8}，SubT2{3, 6, 12} and SubT 39, 18. Finally, site subset partitioning is obtained: SubS1＝{s1，s6，s7}，SubT2＝{s4，s5，s8，s9，S10} and SubT3＝{s2，s3，s11}. The detailed procedure is as described in algorithm 2.
Algorithm 2 determines optimal segmentation subsets
Figure BDA0002298856590000111
Figure BDA0002298856590000121
Algorithm 3 determines the first TBTT time
Figure BDA0002298856590000122
Figure BDA0002298856590000131
(2) Step 2 (inner grouping): because the listening intervals of the stations in the group have a multiple relation, each TBTT of the stations can be staggered by setting a reasonable first TBTT value, and the aim of waking up the stations by each beacon frame time slot in the control group is achieved.
With an arbitrary subset SubT after segmentationkFor example, the TBTT determination process is as described in algorithm 3. In particular, with SubTkThe intra-packet grouping process is described by taking {2, 4, 4, 4, 4, 4, 8, 8, 16} as an example. As is clear from the results of the algorithm 3, the common multiple of all elements is the maximum element 16, and the list length is 16. First, SubTkIs allocated, and since the list is empty, a new list of length 16 is generated and occupies the first non-empty unit lst [1 ] of the list][1]. Meanwhile, the station will wake up at 3, 5, …, 15, etc. times, corresponding to lst [1 ]]Is marked as non-empty. Next, sites with LI of 4 were programmed to the corresponding locations: 2,6, 10, 14. By analogy, when the last list has no non-empty elements, a new list is generated. The final layout result of this example is shown in fig. 1.
(3) Step 3 (drift): step 2, starting from the 1 st vacant position for the initial indexes of all groups, the 1 st TBTT burst waking station number in each period is caused. A degree of equalization is achieved by random drift of the initial index of the last list.
After step 2, the maximum number of competing stations always appears in the first beacon frame slot during the transmission period. However, with proper orchestration, sites that have multiples of the listen interval or a common factor may not wake up at the same time at any time in the future. The results of the grouping and intra-group grouping are described in general by taking T ═ {3, 2, 2, 10, 9, 3, 2, 3, 3, 6} as an example, as shown in fig. 2. Easily derived maximum number of simultaneously awakened sites n max5, the minimum number of stations n that wake up simultaneouslymin2, so the maximum deviation ncvAnd the maximum number of competing stations always occurs in the first beacon frame slot, 3. Site s in the example of FIG. 22And s4The listening intervals have a multiple relationship and the maximum contention level can be reduced by drift of the initial index.
One of the drift results is shown in FIG. 3, with an updated maximum number of sites n 'waking at the same time by the drift of the initial index'maxUpdated minimum number of simultaneously awake stations n'min2, and a new deviation n'cv2. Obviously, the drift effectively reduces the overall maximum competition level and competition jitter between groups under the condition of keeping the competition level and the period in the groups unchanged, and the awakening number of the stations is more balanced. However, it is inefficient to traverse all possible or time-consuming algorithms (e.g., exhaustive, greedy) to find the optimal initial index value. Especially when the listening intervals are prime (worst case), drift does not produce any beneficial effect.
Since there are only free units in the last list of the lists in each group, drifting the initial index of non-empty units does not have any beneficial effect. Thus, the initial index of the last list in each group is shifted as a result. The determination of the initial index adopts a random process in consideration of time complexity and network real-time.
And after the station is awakened at each specific moment, determining whether a deterministic channel access strategy is adopted or not according to the number of usable channels and the number of simultaneously active stations. That is, when the number of active stations is less than or equal to m, a deterministic access mechanism, that is, a contention-free manner, is adopted to further obtain higher throughput and energy efficiency. In the deterministic access mechanism, the AP divides the TWT service period into a BSRP phase and a data transmission phase according to the number of stations that wake up in the TBTT time. By means of a designed BSRP (polling) phase, the awake stations are polled for buffer status according to the number of available channels, and in a subsequent data transmission phase, data is transmitted by means of a centralized deterministic access channel access policy, as shown in fig. 5, where TWT SP represents a TWT service period.
Meanwhile, the invention improves the TWT information frame structure, adds BSR Polling bit to determine the concrete kind of the broadcast TWT service period, wherein, the value 1 represents BSRP stage, namely BSRP TWT service period. When receiving the service period information of the BSRP, the station wakes up at a corresponding time point, and reports the buffer status, and the specific result is shown in fig. 6.
In summary, the method controls the number of stations waking up in each beacon frame slot by scheduling the first wake-up time and the listening interval to alleviate the contention and load imbalance problems. And providing an optimization method for optimizing the throughput rate and improving the energy efficiency, a specific sleep scheduling process and a channel access strategy for the number of wake-up stations and the backoff process. The method has better performance in the aspects of throughput rate, energy efficiency and packet loss rate. The scheme is also suitable for the periodic uplink transmission scene with terminal energy shortage and insensitive time delay.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may occur to those skilled in the art without departing from the principle of the invention, and are considered to be within the scope of the invention.

Claims (6)

1. A high-efficiency energy-saving method applied to high-density WLAN is characterized in that each station requesting to sleep sends a target wake-up time TWT request frame to an AP in sequence,
the AP determines a listening interval LI and a target beacon frame transmission time TBTT value, and returns the TBTT moment of the awakening of the sleeping station to each station through a target awakening time TWT response frame;
after receiving the TWT response frame, the station enters a sleep state and wakes up at the appointed TBTT moment to receive a beacon frame carrying the TWT service period information;
when the station is dormant, the data sent to the station by the AP is stored in an AP buffer area;
when the station wakes up, the station may initiate a request to the AP to receive data stored in the AP buffer;
when the station wakes up, when the number of active stations is less than or equal to the number of available channel resources, a deterministic access mechanism is adopted, and the AP divides a TWT service period into a BSRP stage and a data transmission stage according to the number of the awakened stations in the TBTT time; polling the state of a buffer area to a wake-up site according to the number of available channels in a designed BSRP polling stage, and accessing the channels in a centralized deterministic manner in a subsequent data transmission stage;
when the AP buffer zone overflows, the AP can send a request for reducing the interception interval to a larger station occupying the buffer zone;
for a station with small traffic, the AP may make a request to increase the listening interval to the station;
when the site density in the network is higher, obtaining an optimal interception interval LI combination by deciding whether all sites enter a dormant state or not;
when the density of the stations in the network is low, the difference value of the existing competition level and the optimal competition level is calculated, and the value of the listening interval LI of the stations is adjusted proportionally.
2. The method of claim 1, wherein a GTSS (packet-based target wakeup time scheduling) scheme is preset in the AP, and LI and the first TBTT value are obtained through the GTSS scheme to determine all TBTT moments, wherein the GTSS scheme comprises
Determining the optimal number of service stations according to key backoff parameters in the uplink access process; determining stations in a TWT service period in different modes or adjusting station interception intervals LI to be optimal according to the station density in the network;
grouping according to the obtained final dormant station set and the corresponding interception interval value, classifying the corresponding stations into different groups, carrying out TBTT scheduling on the stations with the common interception interval attribute in the groups, and carrying out the equalization of the dislocation between the groups and the awakening stations through the drift of the initial index.
3. The energy efficient method of claim 2, wherein the relationship between the overall throughput and the average number of active stations waking up in each beacon frame time is determined according to the station density in the network and the parameters of the backoff mechanism including the minimum backoff window size, the maximum backoff window size, the backoff level, the number of available channel resources, the data transmission rate of the channel, the probability of successful backoff, and the probability of successful channel selection by the station.
4. The energy efficient method of claim 2, wherein the step of obtaining the TBTT value in the GTSS scheme comprises
Sequencing the given optimal listening intervals, classifying the given optimal listening intervals into different subsets according to different characteristics, and classifying the corresponding sites into corresponding subsets;
staggering TBTT of the stations, and controlling the number of awakening stations in each beacon frame time slot in the group;
the initial index of the list of timeslots for each beacon frame is randomly drifted.
5. The method as claimed in claim 3, wherein the relationship between the throughput and the optimal number of waking stations is obtained according to the station density in the network and the parameters in the back-off mechanism, and the average number of waking stations waking up in each beacon frame time in the transmission period is determined according to the relationship, so as to obtain the optimal listening interval LI.
6. The method of claim 4, wherein the listening intervals are ordered according to different characteristics, and the different characteristics included in the different subsets are characterized by each element in the same subset being a positive integer multiple of other elements in the subset having smaller values.
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