CN110337125B - Workstation re-grouping method in 5G network - Google Patents
Workstation re-grouping method in 5G network Download PDFInfo
- Publication number
- CN110337125B CN110337125B CN201910328157.XA CN201910328157A CN110337125B CN 110337125 B CN110337125 B CN 110337125B CN 201910328157 A CN201910328157 A CN 201910328157A CN 110337125 B CN110337125 B CN 110337125B
- Authority
- CN
- China
- Prior art keywords
- hidden
- workstation
- workstations
- service
- network
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 27
- 230000005540 biological transmission Effects 0.000 claims abstract description 36
- 239000011159 matrix material Substances 0.000 claims abstract description 19
- 238000010295 mobile communication Methods 0.000 abstract description 2
- 238000004891 communication Methods 0.000 description 6
- 238000013459 approach Methods 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 230000007423 decrease Effects 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 101100172132 Mus musculus Eif3a gene Proteins 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000012804 iterative process Methods 0.000 description 1
- 230000006798 recombination Effects 0.000 description 1
- 238000005215 recombination Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/0294—Traffic management, e.g. flow control or congestion control forcing collision
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/06—Optimizing the usage of the radio link, e.g. header compression, information sizing, discarding information
- H04W28/065—Optimizing the usage of the radio link, e.g. header compression, information sizing, discarding information using assembly or disassembly of packets
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W74/00—Wireless channel access
- H04W74/08—Non-scheduled access, e.g. ALOHA
- H04W74/0808—Non-scheduled access, e.g. ALOHA using carrier sensing, e.g. carrier sense multiple access [CSMA]
- H04W74/0816—Non-scheduled access, e.g. ALOHA using carrier sensing, e.g. carrier sense multiple access [CSMA] with collision avoidance
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
- Small-Scale Networks (AREA)
Abstract
The invention belongs to the technical field of mobile communication, and particularly relates to a workstation re-grouping method in a 5G network, which comprises the steps of taking the PS-Poll frame transmission starting time of all workstations as a check index of hidden nodes, and detecting the hidden node relation in the network; after the access point obtains the PS-Poll frame transmission starting time of the work stations, determining the hidden node relation between the work stations and constructing a hidden relation matrix; the access point quantizes the expected service requirements reported by the workstation into different service levels, and constructs an expected service requirement table of the workstation; integrating an expected service demand table into a hidden node relation matrix to form a hidden service table which has comprehensive knowledge on the potential influence of hidden nodes; regrouping the workstations during each TBTT according to the detected hidden service table; the throughput of the STA regrouping method is improved by 40 percent compared with the throughput of the conventional random grouping method.
Description
Technical Field
The invention belongs to the technical field of mobile communication, and particularly relates to a method for regrouping workstations in a 5G network.
Background
With the rapid popularization of embedded devices, Internet of Things (IoT) communication is becoming the main communication mode for various emerging intelligent services including smart cities, smart meter reading, medical monitoring, agricultural monitoring, industrial automation, and the like. These new applications and services of scalable intelligent systems require a large number of intelligent devices (sensors, robots, controllers, etc.) to be connected together. For the application of the internet of things of large-scale terminal nodes, how to effectively connect a large number of terminals to the same Access Point (AP) is a key Point of research. An IEEE 802.11ah network is mainly composed of Stations (STAs) and APs. An 802.11ah AP can associate up to 8192 STAs within 1Km communication range, thereby forming a network that associates a large number of devices and covers a large area. In such large-scale networks, there may be a large number of hidden devices, resulting in serious collision problems, limiting system performance. In the case of a randomly deployed network, the probability that any two node devices are hidden from each other increases to 40%, and when the number of deployed node devices reaches 8000, the expected number of hidden node pairs will reach 1311836. Furthermore, the hidden node problem is more pronounced when the node device enters Power Save (PS) mode. Since most STAs in an 802.11ah network operate in Power-Save mode, STAs wake up and listen to the beacon sent by the AP at the same time and attempt to send a Power Save-Poll (PS-Poll) frame to request uplink transmission, which may result in multiple collisions. In order to minimize device collision, IEEE 802.11ah introduces a Restricted Access Window (RAW) mechanism based on Enhanced Distributed Channel Access (EDCA) with transmission Opportunity (TXOP) to implement a packet-based contention scheme. The AP divides the STAs into groups, allocates a RAW time slot for each group, and STAs belonging to the same group compete for channels in the allocated RAW time slots, and the STAs are only in an awake state in the allocated time slots and all sleep in the rest time slots. Previous studies have focused mainly on improving the performance of packet-based contention schemes, such as by adjusting the number of RAW slots or the RAW duration to obtain the best performance, but in these studies, it is assumed that the network is fully connected, i.e., there is no hidden node problem in the network, which means that the existing packet-based contention mechanism cannot effectively solve the hidden node problem, and no specific STA grouping scheme is specified in the IEEE 802.11ah standard, whereas the existing STA grouping method generally only randomly allocates STAs into different groups. This random assignment approach can lead to an increase in potential collisions within the group for STAs with high traffic demands.
Disclosure of Invention
The invention aims to overcome the technical defects, and provides a workstation recombination method in a 5G network by aiming at minimizing transmission conflict caused by hidden node problem under the control of Carrier Sense Multiple Access/conflict Avoidance (CSMA/CA) based on competition, which comprises the following steps:
s1, taking the energy-saving polling frame transmission starting time of all workstations as the check index of hidden nodes, and detecting the hidden node relation in the network;
s2, obtaining PS-Poll frame start transmission time t of the work station at the access pointiThen, determining hidden node relations among the workstations, and constructing a hidden relation matrix;
s3, the access point quantizes the expected service demands reported by the workstation into different service levels, and constructs an expected service demand table of the workstation;
s4, integrating the expected service requirement table into a hidden node relation matrix to form a hidden service table which has comprehensive knowledge on the potential influence of hidden nodes;
s5, the stations are regrouped according to the detected hidden traffic table during each Target Beacon Transmission Time (TBTT).
Further, detecting a hidden node relationship in the network includes: if tiTo limit the start time, t, of the first transmission of a PS-Poll frame by station i within the access window time slotjTo limit the start time of the first PS-Poll frame transmission by station j within the access window slot, when tiAnd tjWhen the absolute value of the difference is greater than TA, the workstation i and the workstation j are considered to be mutually hidden nodes, wherein TA is the maximum transmission delay between the same time slot STAs and is represented as TA tback-off+δ，tback-offRepresents the absolute difference between the backoff window first selected by station i and station j, and δ represents the propagation delay of the 802.11ah network.
Further, limiting the starting time t of the first PS-Poll frame transmission of the workstation i in the access window time slotiThe obtaining method comprises the following steps: explicit control frames are sent during other restricted access windows or best effort regions within the same beacon period.
Further, constructing the hidden relationship matrix includes: correlating the carrier sense of the workstation i with the workstation jijAs an element of the ith row and jth column in the hidden relationship matrix, where the carrier sense relationship k of workstation i and workstation jijExpressed as:
where TA is the maximum transmission delay between two stations in the same timeslot, and is denoted as TA ═ tback-off+δ，tback-offRepresents the absolute difference between the backoff window first selected by station i and station j, and δ represents the propagation delay of the 802.11ah network. When k isijWhen k is 0, it means that workstation i and workstation j can sense each otherij1, the workstation i and the workstation j are mutually hidden nodes.
Further, regrouping the workstations during each TBTT according to the detected hidden traffic table comprises:
s51, arranging the workstations in descending order according to the service levels of the workstations, and sequentially distributing the workstations with the highest service levels into empty groups until each group has one workstation;
s52, calculating hidden services brought to each group by the workstation with the highest service level in the rest workstations, and distributing the hidden services to the group with the least additional hidden service amount;
s53, if the work station has the same influence on a plurality of groups, a plurality of allocation selections can be carried out, a Viterbi-like algorithm is adopted, namely, the sequence of the work station is taken as an observation sequence, the sequence of the work station allocated to the group is taken as a state sequence, the size W of a Viterbi window is set, the first W work stations are selected from the work station sequence, the optimal path associated with the minimum additional hidden service is obtained through the Viterbi algorithm, and then the allocation of the work station is determined according to the optimal path;
s54, repeating the steps S51-S53 until all the workstations are allocated to the group.
The invention has the beneficial effects that:
1. the method comprises the steps that the service requirements of potential hidden node pairs and STAs in the network are obtained in the data transmission process, the frame structure of a protocol standard does not need to be changed, and the method can also be used for other competition-based wireless networks of Media Access Control (MAC) protocol support packets;
2. the hidden service table is introduced to minimize the potential hidden service in the network, the Viterbi algorithm is adopted to realize the re-grouping of the STA, and the throughput of the STA re-grouping method is improved by 40 percent compared with the throughput of the conventional random grouping method on the premise of ensuring the service quality and system fairness of equipment.
Drawings
FIG. 1 is a diagram illustrating a structure of a restricted access window according to the present invention;
FIG. 2 is a diagram illustrating an example of IEEE 802.11ah MAC layer data transmission employed in the present invention;
FIG. 3 is a flow chart of a method of the present invention;
fig. 4 is a simulation experiment result of the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a workstation regrouping method in a 5G network, as shown in FIG. 3, comprising the following steps:
s1, detecting the hidden node relation in the network by taking the PS-Poll frame transmission starting time of all the workstations as the check index of the hidden node;
s2, obtaining PS-Poll frame start transmission time t of the work station at the access pointiThen, determining hidden node relations among the workstations, and constructing a hidden relation matrix;
s3, the access point quantizes the expected service demands reported by the workstation into different service levels, and constructs an expected service demand table of the workstation;
s4, integrating the expected service requirement table into a hidden node relation matrix to form a hidden service table which has comprehensive knowledge on the potential influence of hidden nodes;
s5, regrouping the stations during each TBTT according to the detected hidden traffic table.
Wherein, during each TBTT, regrouping the workstations according to the detected hidden service table specifically comprises the following steps:
s51, arranging the workstations in descending order according to the service levels of the workstations, and sequentially distributing the workstations with the highest service levels into empty groups until each group has one workstation;
s52, calculating hidden services brought to each group by the workstation with the highest service level in the rest workstations, and distributing the hidden services to the group with the least additional hidden service amount;
s53, if the work station has the same influence on a plurality of groups, a plurality of allocation selections can be carried out, a Viterbi-like algorithm is adopted, namely, the sequence of the work station is taken as an observation sequence, the sequence of the work station allocated to the group is taken as a state sequence, the size W of a Viterbi window is set, the first W work stations are selected from the work station sequence, the optimal path associated with the minimum additional hidden service is obtained through the Viterbi algorithm, and then the allocation of the work station is determined according to the optimal path;
s54, repeating the steps S51-S53 until all the workstations are allocated to the group.
In this embodiment, consider an 802.11ah network with n stations associated with one AP in a circular AP coverage area of radius R, and all STAs powered by batteries. The workstations operate in a power-saving mode, are uniformly distributed in the coverage area of the AP, and are static or slow to move among the workstations.
As shown in fig. 1, the STAs are divided into 8 groups, each of which is allocated one RAW slot, and each RAW slot has the same duration. Assume that the IEEE 802.11ah network is mainly uplink communication, i.e., the STA transmits buffered data to the AP. The STA is awakened at the TBTT periodically to acquire the RAW scheduling information, if the STA has buffer data, the STA transmits PS-Poll frames to request uplink communication based on an EDCA mechanism in the allocated RAW time slot, and if not, the STA is in a dormant state until the TBTT of the next beacon interval. An example of IEEE 802.11ah MAC layer data transmission is shown in fig. 2. And when the AP successfully receives the PS-Poll frame, sending an ACK frame to the STA for response, and if the STA does not receive the ACK frame, retransmitting the PS-Poll frame until the maximum retransmission times is reached. And after receiving the ACK frame, the STA sends the buffer data to the AP and waits for the ACK frame sent by the AP to confirm.
The embodiment provides an STA regrouping method based on an IEEE 802.11ah network, which specifically includes the following steps:
acquiring a carrier monitoring relation between STAs by detecting the transmission starting time of a PS-Poll frame, and constructing a hidden node relation matrix; collecting the expected service requirements reported by STAs, quantizing the service requirements of the STAs into different service levels, and constructing an expected service requirement table of the STAs; integrating an expected service demand table into a hidden node relation matrix to form a hidden service table which has comprehensive knowledge on the potential influence of hidden nodes; the method comprises the steps of performing descending order on the STAs according to the service levels of the STAs, and sequentially distributing the STAs with the highest service levels to empty groups until no empty group exists; calculating hidden services brought to each group by the STA with the highest service level in the rest STAs, judging whether the STA has the same influence on a plurality of groups, if so, distributing the STA by adopting a Viterbi-like algorithm, otherwise, distributing the STA to the group with the least additional hidden service amount, judging whether all the STAs are completely distributed, if so, ending the process, otherwise, repeating the process of distributing the STA.
In the embodiment of the invention, t isiIs recorded as the starting time, k, of the first PS-Poll frame transmitted by STA i in RAW time slotijAnd carrying out carrier sense relationship between the STA i and the STA j. For ease of understanding, the acquisition effect and bit error rate problems of the wireless channel are ignored. Since the hidden node pair can only be detected in uplink transmission, the starting transmission time of the PS-Poll frame is used as the detection index of the hidden node. If the timing sequence of the first PS-Poll frame sent by STA i and STA j is repeatedAnd if so, judging that the STA i and the STA j are hidden node pairs. Let tiStarting time, k, of first transmission of PS-Poll frame for STA i in RAW slotijFor the carrier sense relationship between STA i and STA j, if k ij0 means STA i and STA j are mutually perceivable; k is a radical ofij1 means that STA i and STA j are hidden nodes to each other. Thus kijCan be expressed as:
where TA is the maximum transmission delay between STAs in the same timeslot, and is denoted as TA ═ tback-off+δ，tback-offRepresents the absolute difference between the backoff window first selected by station i and station j, and δ represents the propagation delay of the 802.11ah network.
The AP may obtain t by recording the timestamp of the start of the receiving STA i sending the PS-Poll frameiTherefore, a hidden node relationship is found between any two STAs, but the AP cannot acquire the timestamp from the PS-Poll frame with failed transmission, and cannot acquire the service requirements of the STA in uplink communication. Therefore, the STA needs to associate its AID, tiAnd the expected traffic demand is fed back to the AP. Two feedback modes are considered: the first way is to modify the PS-Poll frame structure in the 802.11ah standard; the second is to transmit explicit control frames in other RAWs or best effort regions within the same beacon period. For the first approach, it is necessary to add one for t in the PS-Poll frameiThe 8-byte field and the 2-byte field for traffic demands, the modified PS-Poll frame adds significant overhead in large scale networks, and the first approach also requires modification of the 802.11ah specification, so the second feedback approach is used in this chapter. Considering that the STA is static or moving slowly, the hidden node relationship in the network does not change, while the STA traffic demand is dynamic. Thus, the information is fed back to the AP by sending a display control frame in the previous beacon interval.
Obtaining STA t in each RAW time slot at APiThen according to kijDetermining concealment between STAs in RAW slotsAnd hiding the node relation and updating the hidden node relation matrix. All elements in the hidden node relation matrix are initially set to 0, and when the hidden node relation matrix is updated, if k is equal toijIf STA i and STA j are in a hidden relationship, the element (i, j) is set to 1; otherwise if kijWhen the element (i, j) is set to 0, it indicates that STA i and STA j can perceive each other. The hidden node matrix is symmetric, updating at the TBTT of each beacon interval until the hidden node relationship contains all the associated nodes of the AP.
In addition to hiding node information, the AP also collects the expected traffic demands fed back by the STAs. The AP quantizes the traffic demand of the STA to different traffic levels, and constructs an expected traffic demand table of the STA, as shown in table 1, where the larger the number is, the more the traffic demand of the STA is, the more buffer data needs to be transmitted.
Table 1 expected traffic demand table for STAs
In the internet of things network, the service requirement may also be based on the type of STA, and the AP matches it to a specific service level through the type of STA. If two STAs are hidden nodes from each other, they may cause collisions in attempting transmission. In order to minimize the impact of collisions, the active hidden nodes should be grouped into different groups and the hidden traffic within the group should be minimized according to the expected traffic demand table. And integrating the expected service demand table into the hidden node table to form a hidden service table with comprehensive knowledge of the potential influence of the hidden node.
The method comprises the steps that the STAs are regrouped according to a hidden service table, and a grouping algorithm mainly comprises a centralized dynamic programming algorithm and a distributed iterative updating algorithm, wherein the centralized dynamic programming algorithm has the main advantage that the maximum overall benefit can be obtained according to global information, but the algorithm complexity is generally high; the distributed iterative update algorithm has lower algorithm time complexity, but can only obtain the overall benefit of a suboptimal system, and may not be converged in the iterative process. Therefore, the invention adopts a centralized Viterbi-like algorithm to regroup the STAs according to the global information.
After the hidden node relationship matrix and the STA expected traffic demand table are collected, the STAs are regrouped during each TBTT according to the detected hidden node and expected traffic demand. The algorithm for STA regrouping is described as: firstly, performing descending order arrangement on the STA according to the service level of the STA, and sequentially dividing the STA with the highest service level into empty groups until each group has one STA; and then calculating hidden services brought to each group by the STA with the highest service level in the rest STAs, and distributing the hidden services to the group with the least additional hidden services, wherein if the STA has the same influence on a plurality of groups and can carry out various distribution selections, a Viterbi-like algorithm is adopted. The viterbi algorithm actually uses Dynamic Programming (DP) to solve the hidden markov model prediction problem, i.e. uses Dynamic Programming to solve the path with the maximum probability (the optimal path). The viterbi algorithm is described as: and sequentially calculating the maximum probability of each partial path when the state at the time T is i from the time T equal to 1 until the maximum probability of each path when the state at the time T is obtained. Then, the maximum probability according to the time T-T is the probability p of the optimal path*From the end point
At the beginning, the nodes are gradually obtained from back to front
Obtaining the optimal path
The method comprises the steps of taking a sequence of an STA as an observation sequence, taking a sequence of the STA distributed to a group as a state sequence, setting the size W of a Viterbi window, selecting the first W STAs from the STA sequence, obtaining an optimal path associated with the minimum additional hidden service through a Viterbi algorithm, and then determining the distribution of the STA according to the optimal path; finally all STAs are assigned to the group using the same method.
To further illustrate the effectiveness of the STA regrouping method, the throughput performance of the present invention is verified by simulation, and fig. 4 is a graph of the relationship between the number of STAs and the throughput in the Matlab 2014a environment. In an IEEE 802.11ah network environment, simulation parameters are set as follows: the AP transmission distance is 1Km, the average size of a data frame is 256bytes, the Orthogonal Frequency Division Multiplexing (OFDM) symbol duration is 40us, the basic rate is 650kbps, the PS-Poll frame size is 240us, the ACK size is 240us, the backoff slot duration is 52us, SIFS is 160us, DIFS is 264us, the maximum backoff number is 5, the minimum window number is 15, the number of slots of RAW is 8, the duration of RAW slots is 235ms, and the viterbi window size is 20. All STAs operate in power save mode and have data packets for uplink transmission. Neglecting the capture effect and bit error rate problem of the wireless channel. In a network, there are three types of STAs with different service requirements: s1, S2 and S2 in a ratio of 1:3: 6. Wherein, the service level of S1 is ten times higher than that of S2, and the service level of S2 is ten times higher than that of S3. The number of STAs under the coverage of the AP gradually increases from 100 to 1000, simulation results show that the smaller the number of STAs (less than 100), the smaller the difference in throughput between the STA re-grouping algorithm and the random grouping algorithm, which corresponds to the initial stage of the curve in the figure. Therefore, in a light-load network, the throughput of the STA re-grouping algorithm is not greatly different from that of the random grouping algorithm. As the number of STAs increases, the throughput of both algorithms decreases, but the throughput of the random grouping algorithm decreases more severely, which decreases by 48% at 1000 STAs. Due to the serious hidden node problem, collision and collision of the STAs occur during transmission, continuous collision occurs when the collision and collision is serious, the continuous collision time is very long, the reduction of the throughput and the energy efficiency performance is obvious, and the throughput performance is also reduced due to the collision and collision which are continuously increased among the non-hidden devices in the STA re-grouping algorithm. Therefore, the STA re-grouping algorithm can effectively improve the network throughput in a large-scale network; where the grey PS-Poll frame indicates already.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (3)
1. A method for regrouping workstations in a 5G network is characterized by comprising the following steps:
s1, using the energy-saving polling PS-Poll frame starting transmission time of all workstations as the check index of hidden nodes, detecting the hidden node relation in the network, i.e. if tiTo limit the start time, t, of the first transmission of a power save Poll PS-Poll frame by station i within an access window time slotjTo limit the start time of the first transmission of power save Poll PS-Poll frame by station j within the access window slot, when tiAnd tjWhen the absolute value of the difference is greater than TA, the workstation i and the workstation j are considered to be mutually hidden nodes, wherein TA is the maximum transmission time delay between two workstations in the same time slot and is represented as TA tback-off+δ，tback-offThe absolute difference value of the backoff window selected for the first time by the workstation i and the workstation j is shown, and delta represents the propagation delay of the 802.11ah network;
s2, obtaining the transmission start time t of the energy-saving polling PS-Poll frame of the work station at the access pointiThen, determining hidden node relations among the workstations, and constructing a hidden relation matrix;
s3, the access point quantizes the expected service demands reported by the workstation into different service levels, and constructs an expected service demand table of the workstation;
s4, integrating the expected service requirement table into a hidden node relation matrix to form a hidden service table which has comprehensive knowledge on the potential influence of hidden nodes;
s5, regrouping the stations according to the detected hidden traffic table during each target beacon transmission time TBTT, including:
s51, arranging the workstations in descending order according to the service levels of the workstations, and sequentially distributing the workstations with the highest service levels into empty groups until each group has one workstation;
s52, calculating hidden services brought to each group by the workstation with the highest service level in the rest workstations, and distributing the hidden services to the group with the least additional hidden service amount;
s53, if the work station has the same influence on a plurality of groups, a plurality of allocation selections can be carried out, a Viterbi-like algorithm is adopted, namely, the sequence of the work station is taken as an observation sequence, the sequence of the work station allocated to the group is taken as a state sequence, the size W of a Viterbi window is set, the first W work stations are selected from the work station sequence, the optimal path associated with the minimum additional hidden service is obtained through the Viterbi algorithm, and then the allocation of the work station is determined according to the optimal path;
s54, repeating the steps S51-S53 until all the workstations are allocated to the group.
2. The method of claim 1 wherein the start time t of the first transmission of power save Poll (PS-Poll) frame by station i in the access window slot is limitediThe obtaining method comprises the following steps: explicit control frames are sent during other restricted access windows or best effort regions within the same beacon period.
3. The method of claim 1, wherein constructing the hidden relationship matrix comprises: correlating the carrier sense of the workstation i with the workstation jijAs an element of the ith row and jth column in the hidden relationship matrix, where the carrier sense relationship k of workstation i and workstation jijExpressed as:
where TA is the maximum transmission delay between STAs in the same timeslot, and is denoted as TA ═ tback-off+δ，tback-offThe absolute difference value of the backoff window selected for the first time by the workstation i and the workstation j is shown, and delta represents the propagation delay of the 802.11ah network; when k isijWhen 0, the station i and the station i are representedj can be mutually sensed when k isij1, the workstation i and the workstation j are mutually hidden nodes.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910328157.XA CN110337125B (en) | 2019-04-23 | 2019-04-23 | Workstation re-grouping method in 5G network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910328157.XA CN110337125B (en) | 2019-04-23 | 2019-04-23 | Workstation re-grouping method in 5G network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110337125A CN110337125A (en) | 2019-10-15 |
| CN110337125B true CN110337125B (en) | 2022-04-05 |
Family
ID=68139757
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910328157.XA Active CN110337125B (en) | 2019-04-23 | 2019-04-23 | Workstation re-grouping method in 5G network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110337125B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113194424B (en) * | 2021-04-27 | 2023-09-12 | 大连理工大学 | RAW packet access method based on outage probability in industrial Internet of things |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1581831A (en) * | 2004-05-18 | 2005-02-16 | 中兴通讯股份有限公司 | Method for realizing group-turn accessing in wireless LAN |
| CN103298079A (en) * | 2012-02-23 | 2013-09-11 | 华为技术有限公司 | Data transmission method, access point and site |
| CN104365169A (en) * | 2012-06-27 | 2015-02-18 | Lg电子株式会社 | Method for indicating channel access type in wireless communication system, and apparatus therefor |
| CN105191474A (en) * | 2013-05-10 | 2015-12-23 | 株式会社Kt | Method for alleviating hidden node problem in WLAN system |
| WO2016006830A1 (en) * | 2014-07-08 | 2016-01-14 | 엘지전자 주식회사 | Method and apparatus for power save mode operation on basis of frame transmitted from another bss in wireless lan |
| CN106961696A (en) * | 2017-04-28 | 2017-07-18 | 扬州大学 | A kind of evitable group technology of WLAN concealed terminal |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9107229B2 (en) * | 2012-12-03 | 2015-08-11 | Nokia Technologies Oy | Method, apparatus, and computer program product for signaling for sectorized beam operation in wireless networks |
-
2019
- 2019-04-23 CN CN201910328157.XA patent/CN110337125B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1581831A (en) * | 2004-05-18 | 2005-02-16 | 中兴通讯股份有限公司 | Method for realizing group-turn accessing in wireless LAN |
| CN103298079A (en) * | 2012-02-23 | 2013-09-11 | 华为技术有限公司 | Data transmission method, access point and site |
| CN104365169A (en) * | 2012-06-27 | 2015-02-18 | Lg电子株式会社 | Method for indicating channel access type in wireless communication system, and apparatus therefor |
| CN105191474A (en) * | 2013-05-10 | 2015-12-23 | 株式会社Kt | Method for alleviating hidden node problem in WLAN system |
| WO2016006830A1 (en) * | 2014-07-08 | 2016-01-14 | 엘지전자 주식회사 | Method and apparatus for power save mode operation on basis of frame transmitted from another bss in wireless lan |
| CN106961696A (en) * | 2017-04-28 | 2017-07-18 | 扬州大学 | A kind of evitable group technology of WLAN concealed terminal |
Non-Patent Citations (3)
| Title |
|---|
| Intrusion detection system for PS-Poll DoS attack in 802.11 networks using real time discrete event system;Mayank Agarwal;《IEEE/CAA Journal of Automatica Sinica》;20161109;全文 * |
| Wi-Fi网络MAC协议跨层优化研究;谢忠林;《计算机集成制造系统》;20160415;全文 * |
| 吴广富 ; 邓天垠 ; 苏开荣 ; 李云.《计算机集成制造系统》.《电子与信息学报》.2018, * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110337125A (en) | 2019-10-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10356810B2 (en) | Device and method for controlling slot-based channel access in wireless LAN system, and slot-based channel access terminal in wireless LAN | |
| Zheng et al. | Performance analysis of group-synchronized DCF for dense IEEE 802.11 networks | |
| CN101668313B (en) | Wireless communication station, wireless communication terminal, wireless communication system and control method | |
| US9596648B2 (en) | Unified beacon format | |
| JP6696637B2 (en) | Channel access method and apparatus | |
| EP2938152B1 (en) | Backoff method and device in slot-type channel access of wireless lan system | |
| Zhou et al. | Advances in IEEE 802.11 ah standardization for machine-type communications in sub-1GHz WLAN | |
| US20150023236A1 (en) | Method by which stations operating in power save mode in wireless lan systems transmit and receive frames, and apparatus for supporting same | |
| US20050074025A1 (en) | Media Access Control Protocol for wireless sensor networks | |
| CN102883460A (en) | Service data transmitting method and system | |
| CN104202822A (en) | Channel access method, channel access system and stations | |
| CN109890085B (en) | Method for determining random access back-off parameters of priority-classified machine type communication | |
| CN102300257A (en) | Channel booking mechanism-based multi-channel multi-address access method in wireless ad hoc network | |
| CN103096439A (en) | Station scheduling method, data transmission method, access control station and station | |
| CN109819505B (en) | Method for adapting time slot of limited access window for optimizing network energy efficiency | |
| Gao et al. | A hybrid clustering-based MAC protocol for vehicular ad hoc networks | |
| Tseng et al. | Rotational listening strategy for IEEE 802.15. 4 wireless body networks | |
| CN110337125B (en) | Workstation re-grouping method in 5G network | |
| Ali et al. | Extending the operational range of UAV communication network using IEEE 802.11 ah | |
| CN109005065B (en) | Hidden node-perceptible clustering algorithm for large-scale D2D network | |
| CN108934081A (en) | A kind of wireless vehicle mounted network channel cut-in method | |
| CN113810870A (en) | Centralized meter reading communication method for LoRa ad hoc network | |
| CN113056010A (en) | Reserved time slot distribution method based on LoRa network | |
| CN102076105A (en) | Polling method for point-to-multipoint communication system | |
| Yu et al. | An adaptive radio resource management technique for APs in WLANs |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |