CN109890085B - Method for determining random access back-off parameters of priority-classified machine type communication - Google Patents
Method for determining random access back-off parameters of priority-classified machine type communication Download PDFInfo
- Publication number
- CN109890085B CN109890085B CN201910159265.9A CN201910159265A CN109890085B CN 109890085 B CN109890085 B CN 109890085B CN 201910159265 A CN201910159265 A CN 201910159265A CN 109890085 B CN109890085 B CN 109890085B
- Authority
- CN
- China
- Prior art keywords
- node
- random access
- nodes
- network
- parameters
- 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
Images
Classifications
-
- 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
A method for determining random access back-off parameters of prioritized machine-type communication comprises the following steps: step S1, a base station acquires the number, the type and the data packet sending rate of each node in a cell; step S2, calculating optimal random access back-off parameters according to the number and the type of the nodes and the data packet sending rate of each node, and broadcasting the back-off parameters of the next time slot of each node through a downlink broadcast channel; s3, a node needing to send data listens to a downlink broadcast channel, acquires a back-off parameter required by the node when the node is accessed randomly, and is accessed randomly through the back-off parameter; and S4, detecting the number of nodes in the network in real time by the base station, and circulating the steps S1-S3 when the number of the nodes changes. According to the method, the optimal random access back-off parameters can be calculated according to the types and the number of the nodes in the network, the arrival rate of the request data packet and other information, so that the priority requirements of different nodes are met, and the maximization of access throughput is realized.
Description
Technical Field
The invention belongs to the technical field of random access of the Internet of things, and particularly relates to a method for determining a random access back-off parameter of machine communication with different priorities.
Background
Machine communication is the most basic communication mode in the Internet of things era, and is mainly characterized in that seamless data exchange is independently carried out among a large number of equipment nodes without human interference. The application field of machine communication includes living aspects such as smart home, smart health, smart grid, industrial automation, etc. An important feature of machine communication is that the space is limited by high node density application, such as in factory production line, the number of nodes of the internet of things that each base station needs to serve may reach thousands or even tens of thousands, and when such a huge number of nodes need to be accessed randomly, serious congestion is likely to be caused. Moreover, the diversity of the nodes determines that the requirements of each node on network performance are different, such as a detector, an actuator, an alarm and the like, and if the nodes are treated the same, emergency information cannot be timely transmitted under special conditions, and huge losses may be caused. In such an environment, it is a critical issue how to ensure that a large number of nodes can successfully access in a short time and meet the different priority requirements of the various nodes.
At present, a lot of random access mechanisms based on priority aiming at improving random access efficiency or meeting different nodes are proposed by Y.Maraden et al, namely, when the random access process of a node encounters congestion, random access is not immediately carried out again, but is carried out after waiting for a period of time according to the congestion condition in a network, when the congestion condition is not serious, the waiting time is short, and when the congestion condition is serious, the waiting time is long, thereby achieving the purposes of dispersing congestion and improving the success probability of random access. S.Duan et al propose a dynamic ACB factor calculation method, when the node needs to access the network, a random number between 0 and 1 is firstly generated in the node and compared with ACB factors, if the random number is smaller than the ACB factors, the random access process can be immediately carried out, otherwise, the access is temporarily stopped, the ACB factors can be dynamically controlled by the base station, when the congestion in the network is not serious, the ACB factors can be properly amplified, and when the congestion in the network is serious, the base station can obtain small ACB factors, thereby controlling the number of the nodes carrying out random access and further reducing the probability of collision.
In addition, there are many methods for solving priority problems in machine communication, such as the method proposed by n.zangar et al, which divides nodes into multiple priorities, and when a data packet arrives at a node with a high priority, the base station temporarily stops the access of the node with a low priority to ensure the access performance of the node with a high priority. The method proposed by Vilgelm et al divides random access resources, namely, a high priority node and a low priority node use different resources for access, so that the access performance of the high priority node is ensured not to be affected by the access of the low priority node.
However, all the above methods only consider the access efficiency or the access with priority, and do not consider both at the same time, so there is still a need for a random access method that can maximize the network access performance and ensure different priorities for each node.
Disclosure of Invention
The invention aims to solve the technical problem of overcoming the defects of the prior art and providing a method for determining the random access back-off parameters of the machine communication with different priorities, which calculates the optimal back-off parameters of each group of nodes according to the types and the number of the nodes in a network and the arrival rate of request data packets, thereby meeting the priority requirements of different nodes and realizing the maximization of access throughput.
The invention provides a method for determining a random access back-off parameter of a priority-classified machine type communication, which comprises the following steps:
step S1, a base station acquires the number, the type and the data packet sending rate of each node in a cell;
step S2, calculating optimal random access back-off parameters according to the number and the type of the nodes and the data packet sending rate of each node, and broadcasting the back-off parameters of the next time slot of each node through a downlink broadcast channel;
s3, a node needing to send data listens to a downlink broadcast channel, acquires a back-off parameter required by the node when the node is accessed randomly, and is accessed randomly through the back-off parameter;
and S4, detecting the number of nodes in the network in real time by the base station, and circulating the steps S1-S3 when the number of the nodes changes.
In step S1, the base station records the number and types of nodes in the network and the arrival rate of the data packet of each node according to the condition that the node enters or leaves the network.
Further, in step S2, the calculation formula of the optimal random access backoff parameter is:
wherein M is the total node type in the network, n (i) I e { 1..m }, λ for the number of class i nodes (i) Data packet arrival rate gamma for i-th class node (i) The random access throughput for a desired class i node is a proportion of the total random access throughput of the network, where random access throughput is defined as the ratio of the total random access throughput to the total random access throughput of the networkDividing the number of successful random accesses in the time slot by the number of time slots, i.e. averaging the number of successful random accesses per time slot, and γ (1) +γ (2) +...+γ (M) ＝1；q *,(i) Optimal ACB factor, W, for class i node *,(i) For an optimal backoff window size.
Further, when the ACB factor of each type node is 1, the optimal backoff window size W *,(i) The method comprises the following steps:
when the back-off window size of each class node is 1, the optimal ACB factor q *,(i) The size is as follows:
further, in step S3, when the node initiates the random access request, the priority level of the node and the arrival rate of the request packet are reported at the same time, where the arrival rate of the request packet is the frequency of initiating the random access request.
Further, in step S4, when the node enters the network, a registration request is executed, that is, the node is registered in the network for network management, and when the node leaves the network, a detach process is executed, that is, the base station is notified to remove the information related to the node.
The invention can calculate the optimal random access back-off parameter according to the information of the types and the number of the nodes in the network, the arrival rate of the request data packet and the like, thereby meeting the priority requirements of different nodes and realizing the maximization of access throughput. In addition, the method does not need to adjust the optimal back-off parameter in each time slot, and only needs to adjust when the number of nodes in the network changes, thereby greatly reducing the calculation burden of the base station.
Drawings
FIG. 1 is a diagram of a machine communication network model of the present invention;
FIG. 2 is a schematic flow chart of the method of the present invention.
Fig. 3 is a flow chart of uplink random access implemented by the node of the present invention.
Detailed Description
Referring to fig. 1, the present embodiment provides a method for determining a random access backoff parameter for prioritized machine-based communication, which is applicable to a machine communication network scenario of "base station node+node", and the machine communication network scenario of this type has the following characteristics:
1. the nodes are various in variety, and the requirements of each node on the network are different.
2. The monitoring nodes are randomly distributed in the machine communication network, and can directly communicate with the base station nodes when the monitoring nodes exchange data, so that relay nodes are not needed.
3. The data volume of the monitoring node in a single uploading is smaller, and the time for the node to collect the data is regular.
4. The monitoring node is battery type equipment, the node energy is limited, and the base station has unlimited requirements on energy supply.
The method is as shown in fig. 2, and comprises the following steps:
step S1, a base station acquires the number, the type and the data packet sending rate of each node in a cell;
step S2, calculating optimal random access back-off parameters according to the number and the type of the nodes and the data packet sending rate of each node, and broadcasting the back-off parameters of the next time slot of each node through a downlink broadcast channel;
s3, a node needing to send data listens to a downlink broadcast channel, acquires a back-off parameter required by the node when the node is accessed randomly, and is accessed randomly through the back-off parameter;
and S4, detecting the number of nodes in the network in real time by the base station, and circulating the steps S1-S3 when the number of the nodes changes.
In step S1, when the node enters the network, a registration request is executed, that is, the node is registered in the network for network management, and when the node leaves the network (such as battery is used up, and the node is far away from the network), a detach process is executed, that is, the base station is notified to remove the information related to the node. Through the two processes, the base station can grasp the quantity information of each type of node in the network in real time.
In step S2, the base station records the number and types of nodes in the network and the arrival rate of the data packet of each node according to the condition that the nodes enter or leave the network, wherein M represents the total node type in the network, n (i) Represents the number of class i nodes, i e { 1..m }, λ (i) Indicating the packet arrival rate for the i-th class node. The optimal random access backoff parameter for each class of nodes should satisfy the following equation:
wherein gamma is (i) The random access throughput of the i-th node is defined as the ratio of the random access throughput of the expected i-th node to the total random access throughput of the network, wherein the random access throughput is defined as the random access times of successful access in a certain access time slot divided by the time slot number, namely the successful random access times of each time slot are averaged, and gamma (1) +γ (2) +...+γ (M) ＝1。q *,(i) And W is *,(i) The optimal ACB factor and the optimal backoff window size for the i-th class of nodes are represented, respectively.
When the ACB factor of each class of node is fixed to 1, the optimal backoff window size is:
when the rollback window of each class of nodes is fixed to be 1, the optimal ACB factor size is as follows:
referring to fig. 3, in the embodiment, a timing sequence of a random access application of a node is shown in the figure, a certain node first receives optimal backoff parameter information broadcasted by a base station when starting to operate, and then performs an ACB check when random access is needed, that is, generates a random number between 0 and 1 inside the node and compares the random number with an ACB factor, if the generated random number is smaller than the ACB factor, the random access can be immediately performed, and if the generated random number is larger than the ACB factor, the random access is temporarily stopped. After passing the ACB verification, the node performs a random access process and judges whether the access is successful, if the access is successful, data transmission can be performed on time-frequency resources allocated by the base station, if the access is failed, the ACB verification is performed again by waiting for a period of time at random according to the size of an optimal backoff window, specifically, if the size of the optimal backoff window is set to be W, the node randomly selects a number between 0 and W as waiting time (taking time slot as a unit), and performs the ACB verification process again after the waiting time.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the specific embodiments described above, and that the above specific embodiments and descriptions are provided for further illustration of the principles of the present invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as defined in the appended claims. The scope of the invention is defined by the claims and their equivalents.
Claims (4)
1. A method for determining random access back-off parameters of prioritized machine-type communication is characterized by comprising the following steps,
step S1, a base station acquires the number, the type and the data packet sending rate of each node in a cell;
step S2, calculating optimal random access back-off parameters according to the number and the type of the nodes and the data packet sending rate of each node, and broadcasting the back-off parameters of the next time slot of each node through a downlink broadcast channel;
s3, a node needing to send data listens to a downlink broadcast channel, acquires a back-off parameter required by the node when the node is accessed randomly, and is accessed randomly through the back-off parameter;
step S4, the base station detects the number of nodes in the network in real time, and the steps S1-S3 are circulated when the number of the nodes changes;
in the step S2, the calculation formula of the optimal random access backoff parameter is as follows:
wherein M is the total node type in the network, n (i) I e { 1..m }, λ for the number of class i nodes (i) Data packet arrival rate gamma for i-th class node (i) The random access throughput of the i-th node is defined as the ratio of the random access throughput of the expected i-th node to the total random access throughput of the network, wherein the random access throughput is defined as the random access times of successful access in a section of access time slot divided by the time slot number, namely the successful random access times of each time slot are averaged, and gamma (1) +γ (2) +...+γ (M) ＝1；q *,(i) Optimal ACB factor, W, for class i node *,(i) The optimal rollback window size for the i-th class node;
when ACB factor of each type node is 1, then the optimal rollback window size W *,(i) The method comprises the following steps:
when the rollback window size j of each class of nodes is 1, the optimal ACB factor q *,(i) The size is as follows:
2. the method according to claim 1, wherein in the step S1, the base station records the number and the type of nodes in the network and the arrival rate of the data packet of each node according to the condition that the node enters or leaves the network.
3. The method for determining the random access backoff parameter for prioritized machine-type communication according to claim 1, wherein in step S3, when the node initiates the random access request, the priority level of the node and the arrival rate of the request packet are reported at the same time, and the arrival rate of the request packet is the frequency of initiating the random access request.
4. The method according to claim 1, wherein in step S4, when the node enters the network, a registration request is performed, that is, the node is registered in the network for network management, and when the node leaves the network, a detach procedure is performed, that is, the base station is notified to remove information related to the node.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910159265.9A CN109890085B (en) | 2019-03-04 | 2019-03-04 | Method for determining random access back-off parameters of priority-classified machine type communication |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910159265.9A CN109890085B (en) | 2019-03-04 | 2019-03-04 | Method for determining random access back-off parameters of priority-classified machine type communication |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109890085A CN109890085A (en) | 2019-06-14 |
| CN109890085B true CN109890085B (en) | 2023-07-07 |
Family
ID=66930389
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910159265.9A Active CN109890085B (en) | 2019-03-04 | 2019-03-04 | Method for determining random access back-off parameters of priority-classified machine type communication |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109890085B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110602798B (en) * | 2019-09-20 | 2023-04-18 | 中山大学 | Distributed determination method for optimal parameters of LTE network machine communication random access |
| CN110691420A (en) * | 2019-09-30 | 2020-01-14 | 东南大学 | Novel Internet of things access mode based on anti-cheating random number |
| CN112769707B (en) * | 2019-11-04 | 2022-11-04 | 成都鼎桥通信技术有限公司 | Method, device and system for preventing congestion in Internet of things |
| CN113630901B (en) * | 2021-08-10 | 2023-08-11 | 南京工程学院 | Dynamic multi-priority self-adaptive back-off algorithm in heterogeneous wireless network |
| CN114143757B (en) * | 2022-02-08 | 2022-05-31 | 南京邮电大学 | Time delay guaranteed mass machine type communication access control method and system |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3606267B1 (en) * | 2017-03-22 | 2021-10-27 | LG Electronics Inc. | Method and device for adjusting random access backoff parameter |
| CN107040948B (en) * | 2017-06-13 | 2020-07-31 | 河北工业大学 | CSMA/CA optimization method based on priority |
| CN108307439B (en) * | 2017-08-17 | 2021-06-04 | 上海大学 | Self-adaptive back-off method under large number of multi-hop wireless nodes |
| CN108055702B (en) * | 2017-12-14 | 2020-12-04 | 威胜信息技术股份有限公司 | Self-adaptive back-off method based on time slot CSMA \ CA mode |
| CN108738161A (en) * | 2018-04-28 | 2018-11-02 | 南京邮电大学 | Accidental access method based on different delay demand device packets in a kind of machine type communication |
| CN108882301B (en) * | 2018-07-25 | 2020-07-28 | 西安交通大学 | Non-orthogonal random access method based on optimal power backoff in large-scale M2M network |
-
2019
- 2019-03-04 CN CN201910159265.9A patent/CN109890085B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN109890085A (en) | 2019-06-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109890085B (en) | Method for determining random access back-off parameters of priority-classified machine type communication | |
| Wei et al. | Modeling and analysis of random access channels with bursty arrivals in OFDMA wireless networks | |
| Ali et al. | Performance evaluation of heterogeneous IoT nodes with differentiated QoS in IEEE 802.11 ah RAW mechanism | |
| CN111294775B (en) | Resource allocation method based on H2H dynamic characteristics in large-scale MTC and H2H coexistence scene | |
| CN104853445B (en) | A kind of MAC protocol for wireless sensor networks based on broadcast message | |
| CN103582095B (en) | Based on the network medium of wireless sensor access scheduling method of Event triggered application | |
| Kai et al. | Energy-efficient sensor grouping for IEEE 802.11 ah networks with max-min fairness guarantees | |
| CN107094281B (en) | Access method and system for M2M equipment to access base station | |
| Chen et al. | Contention resolution in Wi-Fi 6-enabled Internet of Things based on deep learning | |
| CN110602798B (en) | Distributed determination method for optimal parameters of LTE network machine communication random access | |
| CN109819505B (en) | Method for adapting time slot of limited access window for optimizing network energy efficiency | |
| Wang et al. | Reliability optimization for channel resource allocation in multihop wireless network: A multigranularity deep reinforcement learning approach | |
| WO2020248102A1 (en) | Harq feedback method and apparatus, and readable storage medium | |
| CN111405678B (en) | CSMA-CA method based on virtual carrier sensing and priority scheduling | |
| Zhu et al. | A station regrouping method for contention based IEEE 802.11 ah wireless LAN | |
| CN105163394A (en) | Method for realizing service perception of SQ-MAC protocol for wireless sensor network | |
| Krishnamurthy et al. | Reservation-based protocol for monitoring applications using IEEE 802.15. 4 sensor networks | |
| Tao et al. | A novel congestion detection and avoidance algorithm for multiple class of traffic in sensor network | |
| CN110337125B (en) | Workstation re-grouping method in 5G network | |
| Vazquez‐Gallego et al. | Combining distributed queuing with energy harvesting to enable perpetual distributed data collection applications | |
| Zhai et al. | Large-Scale Micro-Power Sensors Access Scheme Based on Hybrid Mode in IoT Enabled Smart Grid | |
| CN110113720A (en) | Group based on ACB mechanism pages jamming control method | |
| Wang et al. | A hybrid MAC protocol for data transmission in Smart Grid | |
| Tang et al. | Energy efficient fuzzy time slot scheduling scheme for massive connections | |
| US11778663B1 (en) | Methods and systems for enabling communications from a station to an access point using a backoff counter and carrier sensing |
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 |