CN117376986A - User load control method and communication system of mMTC network - Google Patents

User load control method and communication system of mMTC network Download PDF

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Publication number
CN117376986A
CN117376986A CN202311307843.1A CN202311307843A CN117376986A CN 117376986 A CN117376986 A CN 117376986A CN 202311307843 A CN202311307843 A CN 202311307843A CN 117376986 A CN117376986 A CN 117376986A
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user
probability
channel
load
sub
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蒋励菁
熊伟
张景
虞志刚
王静贤
张越
成俊峰
陆洲
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Electronic Science Research Institute Of China Electronics Technology Group Co ltd
Peoples Liberation Army Strategic Support Force Aerospace Engineering University
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Electronic Science Research Institute Of China Electronics Technology Group Co ltd
Peoples Liberation Army Strategic Support Force Aerospace Engineering University
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    • 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
    • H04W28/08—Load balancing or load distribution
    • H04W28/09—Management thereof
    • H04W28/0958—Management thereof based on metrics or performance parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
    • 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
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/241—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account channel quality metrics, e.g. SIR, SNR, CIR, Eb/lo

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Power Engineering (AREA)
  • Quality & Reliability (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The application discloses a user load control method and a communication system of an mMTC network, wherein the method comprises the following steps: calculating the successful transmission probability of the mMTC network system according to constraint conditions obtained by successful decoding analysis of a receiving end, thereby obtaining a system throughput expression; deriving a channel idle probability expression; calculating an optimal system load based on the system throughput expression; calculating the number of idle channels through a transmission frame; calculating the actual channel idle probability based on the idle channel number, the transmission time slot number contained in each frame and the sub-channel number; and estimating the real-time user load according to the actual idle channel probability, and broadcasting the estimated real-time user load update access probability to each user to complete load control. According to the method, the base station broadcasts the access probability to each user, the receiving end adopts serial interference elimination, and the system dynamically controls the load by adaptively adjusting the access probability of the user, so that the problem of congestion during large-scale access is solved.

Description

User load control method and communication system of mMTC network
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to a method for controlling a user load of an mctc network and a communications system.
Background
In order to realize ubiquitous connection of the internet of things in the future, an mMTC network is attracting attention in the academia and the industry. Unlike other systems, mctc networks serve a large number of low power consumption and low power users, and when many active users are concurrently requesting communications, the content-based uplink access protocols commonly used in the current LTE standards will experience frequent preamble collisions, resulting in severe access delays. In addition, the complicated four-step handshake process greatly increases signaling overhead, so that large-scale access in mass internet of things communication is more difficult.
A non-cooperative random access method with lower signaling overhead and shorter time delay can be used to solve the above problem, for example, a common non-cooperative random access method, i.e. the instant ALOHA (S-ALOHA) method is adopted, specifically, the time is divided into discrete time intervals, and each user randomly selects one time slot for transmission, and the present invention specifically considers multi-channel slotted ALOHA (MS-ALOHA) based on time slot ALOHA, so as to obtain higher system throughput. However, the conventional S-ALOHA random access mechanism is based on Orthogonal Multiple Access (OMA), which results in limited resource utilization when a large number of internet of things devices are accessed upstream.
To address this problem, non-orthogonal multiple access (NOMA) techniques are widely used for non-cooperative access mechanisms. And in particular power domain non-orthogonal multiple access (PD-NOMA), allows multiple users to communicate concurrently with different power levels on the same time/frequency resource block. At the receiving end, serial Interference Cancellation (SIC) is used to decode one by one from the user with the strongest signal power.
Theoretical analysis of system throughput is performed in "W.Yu, C.Foh, A.U.Quddus, W.Liu and R.Tafazolli" "" Throughput analysis and user barring design for uplink NOMA-enabled random access, "IEEE Trans.Wireless Commun., vol.20, no.10, pp.6298-6314, oct.2021," is assumed to always be satisfied. PD-NOMA based MS-ALOHA system, throughput per time slot is expressed as
Wherein q 0 ＝e -λ And q l ＝λe -λ The probability of no user selecting power level l and the probability of only one user selecting power level l on subchannel n are represented, respectively. However, the above equation only considers constraint one and two, ignoring constraint three regarding inter-user interference. In the case of low received signal-to-interference-and-noise ratio, the receiving end may not be able to decode successfully. That is, some cases of transmission failure are also included in the above equation, and thus the above equation can only be regarded as a theoretical upper limit value of throughput.
Based on this consideration, "J.Choi," On throughput bounds of NOMA-ALOHA, "IEEE Wireless Commun. Lett., vol.11, no.1, pp.165-168, jan.2022" takes into account the signal-to-interference-and-noise ratio, thereby deriving a more realistic throughput expression:
T lower ＝NLq 1 (q 0 +q 1 ) L-1
unlike the upper limits set forth in "W.Yu, C.Foh, A.U.Quddus, W.Liu and R.Tafazolli," Throughput analysis and user barring design for uplink NOMA-enabled random access, "IEEE Trans. Wireless Commun., vol.20, no.10, pp.6298-6314, oct.2021," the above equation takes into account the signal-to-interference and noise ratio problem, but only holds under the following conditions:
||U n || 0 ≥1
|u n,l |≤1,l∈{1,2,L,L}
wherein u is n,l Is U n And represents the number of users selecting power level l on subchannel n. U is U n || 0 Gtoreq.1 illustrates that at least one user is accommodated on subchannel n, |u n,l I.ltoreq.1, l.epsilon. {1,2, L } indicates that no power collision can occur on subchannel n.
That is, each power class has only two possible states, either idle or occupied by only one user. In this very special case, three constraints are satisfied, but some other important factors affecting throughput are ignored, which still results in a gap between the theoretical value and the simulation value, which can only be used as a lower throughput expression.
From the above, it can be seen that the congestion management method based on the above incomplete throughput analysis design necessarily has drawbacks.
Disclosure of Invention
The embodiment of the application provides a user load control method and a communication system of an mMTC network, which are based on MS-ALOHA of PD-NOMA, adopt power control of channel reciprocity, and enable a user to adjust transmitting power according to channel quality, so that receiving power of a receiving end can be accurately matched with a preset target power level, the receiving end is enabled to complete serial interference elimination decoding, user load is dynamically controlled through self-adaptive adjustment of access probability, and the problem of congestion during large-scale access is solved.
The embodiment of the application provides a user load control method of an mMTC network, which is used for a base station and a multi-user communication scene, wherein the mMTC network comprises N orthogonal sub-channels, each sub-channel for communication is preset with a plurality of receiving power grade values which are arranged according to a designated sequence, and each active user randomly selects one sub-channel to transmit at one power value in a transmission time slot, and the user load control method comprises the following steps:
before uplink transmission, the base station firstly broadcasts a beacon signal to complete uplink synchronization and informs active users of transmitting data packets in designated time slots;
in a transmission time slot, each active user randomly selects a sub-channel to transmit at a power value;
calculating the successful transmission probability of the mMTC network system according to the constraint condition determined by the successful decoding of the receiving end, thereby obtaining the system throughput;
calculating an optimal system load based on the system throughput under the condition of maximum system throughput;
calculating the number of idle channels through a transmission frame;
calculating the actual channel idle probability based on the idle channel number, the transmission time slot number contained in each frame and the sub-channel number;
and estimating real-time user load according to the calculated actual channel idle probability, and broadcasting the estimated real-time user load update access probability to each user so that each user accesses or delays accessing the mMTC network based on the access probability to complete load control.
Optionally, the constraint condition determined according to the successful decoding of the receiving end includes:
constraint condition one: in any sub-channel, any power level is selected by only one user;
constraint conditions II: at any sub-channel, successfully decoding a data packet at a higher power level than any power level;
constraint conditions three: and when any user decodes the data packet, the signal-to-interference-plus-noise ratio of the any user is not smaller than a preset SINR target threshold value.
Optionally, calculating the successful transmission probability of the mctc network system according to the constraint condition determined by the receiver capable of successfully decoding, thereby obtaining the system throughput includes:
in the case that the constraint one and the constraint two are simultaneously satisfied, the SINR value at the power level l is only related to the inter-user interference generated by the users of lower power level, so as to determine the sub-probability in the case that one user or no user selects the power level l+1;
calculating the successful transmission probability according to the sum of sub-probabilities in the case that one user exists or no user selects the power level l+1;
and calculating the throughput of the mMTC network based on the number of orthogonal sub-channels, the number of received power classes and the successful transmission probability.
Optionally, deriving the probability that the channel is idle satisfies:
wherein P is idle Represent the probability of channel idle, q 1 Represents the probability that the power class l is occupied by a user, q 0 Represents the probability that the power level L is not occupied by the user, λ represents the poisson distribution parameter, and L represents the number of preset received power levels per sub-channel for communication.
Optionally, based on the number of idle channels, the number of transmission slots contained in each frame and the number of sub-channels, calculating the actual channel idle probability satisfies:
wherein,indicating the actual channel idle probability, N indicating the number of orthogonal sub-channels, and t indicating the number of transmission slots per frame.
Optionally, estimating the real-time user load according to the calculated actual channel idle probability, and broadcasting to each user using the estimated real-time user load update access probability includes:
the updated access probability satisfies:
wherein lambda is * Indicating an optimal system load, and,representing real-time user load.
The embodiment of the application also provides an mMTC network communication system, which comprises a processor and a memory, wherein the memory is stored with a computer program, and the computer program realizes the steps of the user load control method of the mMTC network communication system when being executed by the processor.
The embodiments of the present application also provide a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of a user load control method of an mtc network communication system as described above.
According to the embodiment of the application, the MS-ALOHA based on PD-NOMA adopts power control of channel reciprocity, and a user adjusts the transmitting power according to the channel quality, so that the receiving power of a receiving end can be accurately matched with a preset target power level, the receiving end is prompted to complete serial interference elimination decoding, and the user load is dynamically adjusted by adaptively adjusting the access probability.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
fig. 1 is a system architecture example of MS-ALOHA of PD-NOMA of an embodiment of the present application;
fig. 2 is a basic flow example of a user load control method according to an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the application provides a user load control method of an mMTC network, which is used for a base station and a multi-user communication scene, in some specific applications, consider a single cell scene of one base station and a large number of users, and for uplink random access, as shown in fig. 1, the mMTC network comprises N orthogonal subchannels, each subchannel for communication is preset with a plurality of receiving power level values arranged according to a specified sequence, for example, in a system, each subchannel has L preset receiving power level values, and the power values are arranged according to a descending order
v 1 ＞v 2 ＞L＞v L ＞0
In order to transmit at a power value, each active user randomly selects a sub-channel for transmission, and the selected sub-channel and the transmitted power value form an NxL resource block.
During uplink transmission, the base station firstly broadcasts a beacon signal to complete uplink synchronization, and informs active users to transmit data packets in designated time slots. In the time division multiplexing mode, each user can estimate its own channel state based on the received beacon signal due to the reciprocity of the channel.
Each active user randomly selects one resource block during uplink access. Each subchannel is independent, and the base station side received signal through any subchannel n can be expressed as:
where K represents the number of active users selecting subchannel n for transmission, h n,k For the corresponding channel coefficient, p n,k For the transmission power of user k, the background noise is subject to z n :CN(0,N 0 ) Suppose that noise normalizes N 0 ＝1。
To match the preset received power at the base station side, the power class of each active user is set to v l Adjusting the transmit power according to the channel reciprocity, expressed as:
after assuming that the first k-1 data packets were successfully decoded and removed, the signal-to-interference-and-noise ratio of user k can be expressed as:
in accordance with the principles of PD-NOMA,i.e., reaching the SINR target threshold, may be successfully decoded.
The received power level may be expressed as:
the user load control method of the embodiment of the application is that the system input is N orthogonal sub-channels, each sub-channel has L preset receiving power class values, each time slot comprises continuous t transmission time slots, a current time frame j and an access probability p of a previous frame j-1 . As shown in fig. 2, the method comprises the following steps:
in step S201, before uplink transmission, the base station first broadcasts a beacon signal to complete uplink synchronization, and notifies an active user to transmit a data packet in a designated time slot.
In step S202, during the transmission time slot, each active user randomly selects a subchannel to transmit at a power value.
In step S203, the successful transmission probability of the mctc network system is calculated according to the constraint condition obtained by the successful decoding of the receiving end, thereby obtaining the throughput of the system.
In step S204, in the case where the system throughput is maximum, an optimal system load is calculated based on the system throughput. And calculating the optimal system load under the condition that the current time frame is 1 and the access probability is initialized to 1 based on the successful transmission probability.
In step S205, the number of idle channels is calculated through one transmission frame.
In step S206, the actual channel idle probability is calculated based on the number of idle channels, the number of transmission slots contained in each frame, and the number of sub-channels. Wherein the concept of channel idleness is: in this channel, at least one power level is not selected by the user before a power collision occurs or before successful decoding at the base station side, and the channel is called an idle channel. For example, assume that the active user pattern on subchannel n is U n ＝[1 0 1 3] T The base station side finds that v is successfully decoded 1 After the packet, no user selects the second power level, which is the case, even if occupied by some users, the subchannel n is still considered as a free channel in the embodiment of the present application.
In step S207, a real-time user load is estimated according to the calculated actual channel idle probability, and the estimated real-time user load is used to update the access probability to broadcast to each user, so that each user accesses or delays accessing the mctc network based on the access probability, and load control is completed.
According to the embodiment of the application, the MS-ALOHA based on PD-NOMA adopts power control of channel reciprocity, and a user adjusts the transmitting power according to the channel quality, so that the receiving power of a receiving end can be accurately matched with a preset target power level, the receiving end is prompted to complete serial interference elimination decoding, and the user load is dynamically adjusted by adaptively adjusting the access probability.
The constraint conditions determined according to the successful decoding of the receiving end in the embodiment of the application include:
constraint condition one: in either sub-channel either power level is selected by only one user, i.e. in sub-channel n power level l is selected by only user k.
Constraint conditions II: at any subchannel, a data packet at a higher power level than any of the power levels has been successfully decoded.
Constraint conditions three: and when any user decodes the data packet, the signal-to-interference-plus-noise ratio of the any user is not smaller than a preset SINR target threshold value. I.e. when decoding user k's packet, it is satisfied that
In subchannel n, a power collision occurs when more than one user selects the same power level. When a power collision occurs at power level l, all packets at this level cannot be decoded. That is, to ensure that user k's packet can be successfully decoded, constraint one indicates that no power collision is allowed.
The constraint condition II is used for ensuring that the data packet of the user can be successfully decoded, and the power conflict cannot occur at a higher power level.
The constraint three considers the influence of inter-user interference.
In the embodiment of the present application, it is assumed that the probability of transmitting a data packet at power level l obeys a poisson distribution with parameter λ by an active user selecting sub-channel n. On subchannel n, the probability that power class l is occupied by m users simultaneously isFurther, the load of each subchannel may be denoted as λl.
Before each random access, the eNodeB transmits an access probability p to all users along with the beacon signal. Each user can then access the system with probability p or defer access with probability 1-p. In the embodiment of the present application, it is assumed that the access probability p is kept unchanged during each frame, and updated at the beginning of the next frame. Each slot contains consecutive t transmission slots. That is, the eNodeB broadcasts the updated access probability p to all users per frame.
In the embodiment of the present application, calculating the successful transmission probability of the mctc network system according to the constraint condition determined by the receiver capable of successfully decoding, thereby obtaining the system throughput includes:
in case both the first constraint and the second constraint are fulfilled, the SINR value at power level l is only related to the inter-user interference generated by the users of lower power level to determine the sub-probability that one user or no user has selected power level l+1.
In the embodiment of the application, let the probability of meeting constraint one be q 1 The probability of meeting constraint two is (q 0 +q 1 ) l-1 . Consider further the case where constraint three is satisfied:
at power level l, it is assumed that C1 and C2 have been satisfied simultaneously, i.e., u l =1, and u i ≤1，1≤i≤l-1。
Based on the assumption of perfect SIC, the SINR value at power level l is only related to the inter-user interference generated by users of lower power level. Where the strongest interference comes from power level l +1. First, find out the maximum number of users with power level l+1 that the system can hold when ensuring that the power level l can be successfully decoded
Assuming that no user has selected power levels l+2 through L, based on the foregoing:
then:
thereby obtaining u l+1 Upper limit of (2):
considering the requirement of high reliability, assume that
Based on which u can be obtained l+1 =0 or u l+1 =1, i.e. the packet at power level l can only be successfully decoded if power level l+1 is selected at most by one user.
When u is l+1 When=0, only the interference from power class l+2 needs to be considered, because of the sum v l In contrast, the interference from power classes l+3 to L is negligible.
The method can obtain:
the rewriteable is:
is available in the form ofThere is->The corresponding probabilities are:
based onWhile satisfying constraint one and constraint two, and l+1 has no probability of user selection, i.e., u l+1 The probability of =0 can be expressed as:
similarly, the constraint I and the constraint II can be satisfied at the same time, and l+1 has only one probability of being selected by a user, namely u l+1 The probability when=1 can be expressed as:
P 2 ＝Pr(u i ≤1,u l ＝1,u l+1 ＝1)
＝(q 0 +q 1 ) l-1 q 1 q 1 (q 0 +q 1 (q 0 +q 1 (L)))
the probability of successful transmission is calculated from the sum of the sub-probabilities in the presence of one user or in the absence of a user selection of power level l +1.
Binding P 1 And P 2 The total probability is the probability of successful decoding completion of successful transmission when meeting the two-three constraint conditions, and the total probability of successful transmission is:
introducing an auxiliary parameter
And calculating the throughput of the mMTC network based on the number of orthogonal sub-channels, the number of received power classes and the successful transmission probability.
The overall system throughput can be expressed as:
in the case of maximum system throughput, an optimal system load is calculated based on the system throughput, and when l=2, the above equation is degraded into a throughput lower limit expression.
"W.Yu, C.Foh, A.U.Quddus, W.Liu and R.Tafazolli" "" Throughput analysis and user barring design for uplink NOMA-enabled random access, "IEEE Trans.Wireless Commun., vol.20, no.10, pp.6298-6314, oct.2021 gives the channel idle probability as:
whereas the concept of hollow in the embodiments of the present application is based on the decoding result, it can be expressed as:
wherein P is idle Represent the probability of channel idle, q 1 Represents the probability that the power class l is occupied by a user, q 0 Represents the probability that the power level L is not occupied by the user, λ represents the poisson distribution parameter, and L represents the number of preset received power levels per sub-channel for communication. The two formulas may prove equivalent.
In step S202, in the case where the system throughput is maximum, an optimal system load is calculated based on the system throughput. Specifically, when j=1, the access probability is initialized to p 0 =1, optimal system load λ * Refers to the load value at which the system throughput peaks. In the embodiment of the application, the system throughput is defined as the number of data packets which can be successfully decoded in each time slot on the base station side, and the optimal system load lambda can be obtained by deriving the throughput expression obtained in the previous step * 。
In some embodiments, the actual channel idle probability is calculated based on the number of idle channels, the number of transmission slots contained per frame, and the number of subchannels:
wherein,indicating the actual channel idle probability, N indicating the number of orthogonal sub-channels, and t indicating the number of transmission slots per frame.
In some embodiments, estimating real-time user load based on the calculated actual channel idle probabilities for broadcasting to users with the estimated real-time user load update access probabilities comprises:
the updated access probability satisfies:
wherein lambda is * Indicating an optimal system load, and,representing real-time user load.
Updating the access probability, broadcasting the access probability to all users, substituting the access probability into the calculation of the next frame, and completing the dynamic load control.
The embodiment of the application also provides an implementation case of the user load control method for the communication of the Internet of things, which comprises the following steps:
taking the power class l=3 as an example, the analysis is performed according to the following steps:
step one: the optimal user load is obtained by the throughput upper bound expression:
the derivative is obtained by:
to obtain the optimal load value lambda * I.e.Is available in the form of
9λ 3 +6λ 2 +2λe λ -4λ-2-e λ ＝0
Using Taylor expansion, e λ By usingInstead, the above formula may be converted into:
the simplification is as follows:
obtaining lambda * ＝0.5964。
Step two: estimating real-time user load by analyzing idle channel probability
After one transmission frame, the base station can calculate the number of idle subchannels. Thus, the actual idle channel probability per slot can be expressed as:
order theThe method can obtain:
further can be expressed as:
is rewritable as
The simplification can be obtained:
using the Taylor series expansion to approximate, the left side above can be expressed as:
likewise, the right side may be expressed as:
the items of the same class are combined,
from the above, a real-time user load estimate can be calculated
Step three: the access probability is calculated by comparing the optimal value of the user load with the estimated value.
The simulation result shows the effectiveness of the user load control method provided by the embodiment of the application, especially in the scene of a large number of concurrent user access systems.
The load management method provided by the embodiment of the application always approaches to an actual load value, and the throughput of the system steadily increases along with the increase of the load. When the load exceeds the optimal value, i.e. the system enters an overload state, the method provided by the invention starts to implement control so as to ensure that the receiving rate is close to the optimal load. Even if the user load increases gradually with time, the density of the data packet received by the base station side is still stable near the optimal load value. When the load management method provided by the invention is not used, the throughput cliff of the system is reduced due to the influence of serious conflict and interference among users. By adopting the method of the embodiment of the application, the throughput of the system can be stably close to the maximum value.
The embodiment of the application also provides a mass machine type communication system, which comprises a processor and a memory, wherein the memory stores a computer program, and the computer program realizes the steps of the user load control method for the communication of the Internet of things when being executed by the processor.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the steps of the user load control method of the internet of things communication when being executed by a processor.
It should be noted that, in the embodiments of the present disclosure, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing embodiment numbers of the present application are merely for describing, and do not represent advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), including several instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method described in the embodiments of the present application.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those of ordinary skill in the art without departing from the spirit of the present application and the scope of the protection of the claims, which fall within the protection of the present application.

Claims (8)

1. A user load control method for an mctc network, wherein the mctc network includes N orthogonal sub-channels, each sub-channel for communication is preset with a plurality of reception power class values arranged in a designated order, and each active user randomly selects one sub-channel for transmission at a power value in a transmission slot, the user load control method comprising the steps of:
before uplink transmission, the base station firstly broadcasts a beacon signal to complete uplink synchronization and informs active users of transmitting data packets in designated time slots;
in a transmission time slot, each active user randomly selects a sub-channel to transmit at a power value;
calculating the successful transmission probability of the mMTC network system according to the constraint condition determined by the successful decoding of the receiving end, thereby obtaining the system throughput;
calculating an optimal system load based on the system throughput under the condition of maximum system throughput;
calculating the number of idle channels through a transmission frame;
calculating the actual channel idle probability based on the idle channel number, the transmission time slot number contained in each frame and the sub-channel number;
and estimating real-time user load according to the calculated actual channel idle probability, and broadcasting the estimated real-time user load update access probability to each user so that each user accesses or delays accessing the mMTC network based on the access probability to complete load control.
2. The method for controlling a user load of an mctc network according to claim 1 wherein said successfully decoding said determined constraint according to said receiving end includes:
constraint condition one: in any sub-channel, any power level is selected by only one user;
constraint conditions II: at any sub-channel, successfully decoding a data packet at a higher power level than any power level;
constraint conditions three: and when any user decodes the data packet, the signal-to-interference-plus-noise ratio of the any user is not smaller than a preset SINR target threshold value.
3. The method for controlling a user load in mctc network communication according to claim 2 wherein calculating a successful transmission probability of said mctc network system based on a constraint condition determined by a receiver which can successfully decode said mctc network system, thereby obtaining a system throughput includes:
in the case that the constraint one and the constraint two are simultaneously satisfied, the SINR value at the power level l is only related to the inter-user interference generated by the users of lower power level, so as to determine the sub-probability in the case that one user or no user selects the power level l+1;
calculating the successful transmission probability according to the sum of sub-probabilities in the case that one user exists or no user selects the power level l+1;
and calculating the throughput of the mMTC network based on the number of orthogonal sub-channels, the number of received power classes and the successful transmission probability.
4. The method for controlling the user load of an mctc network according to claim 2 wherein deriving a channel idle probability satisfies:
wherein P is idle Represent the channel idle probability, q 1 Represents the probability that the power class l is occupied by a user, q 0 Represents the probability that the power level L is not occupied by the user, λ represents the poisson distribution parameter, and L represents the number of preset received power levels per sub-channel for communication.
5. The method for controlling the user load of an mctc network according to claim 4 wherein calculating an actual channel idle probability based on said number of idle channels, number of transmission slots contained in each frame, and number of subchannels satisfies:
wherein,indicating the actual channel idle probability, N indicating the number of orthogonal sub-channels, and t indicating the number of transmission slots per frame.
6. The method of controlling a user load of an mctc network according to claim 5 wherein estimating a real time user load based on the calculated actual channel idle probability, to update an access probability with the estimated real time user load for broadcasting to each user comprises:
the updated access probability satisfies:
wherein lambda is * Indicating an optimal system load, and,representing real-time user load.
7. A mass machine type communication system, comprising a processor and a memory, the memory having stored thereon a computer program which, when executed by the processor, implements the steps of the method for user load control of an emtc network according to any one of claims 1 to 6.
8. A computer readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, implements the steps of the method for controlling the user load of an emtc network according to any one of claims 1 to 6.
CN202311307843.1A 2023-10-10 2023-10-10 User load control method and communication system of mMTC network Pending CN117376986A (en)

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