CN114884593A

CN114884593A - Anti-interference media access method and device for star topology network and electronic equipment

Info

Publication number: CN114884593A
Application number: CN202210209341.4A
Authority: CN
Inventors: 雍安睿; 邱昕; 柴旭荣; 李大朋
Original assignee: Institute of Microelectronics of CAS
Current assignee: Institute of Microelectronics of CAS
Priority date: 2022-03-04
Filing date: 2022-03-04
Publication date: 2022-08-09

Abstract

The invention discloses an anti-interference media access method and device for a star topology network and electronic equipment, and relates to the technical field of wireless communication. The method comprises the following steps: controlling a plurality of users to determine a target channel corresponding to each user based on a reinforcement learning channel selection algorithm in each access gap; monitoring the target channel, and retreating a plurality of signals corresponding to the target channel based on preset retreat duration under the condition that the interference signal is not detected to obtain a plurality of signals with different durations reaching the target channel; and updating the neural network parameters in the reinforcement learning channel selection algorithm based on the data corresponding to the completion of the signal transmission, completing the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed, and determining the access mode corresponding to the user, so that the throughput rate of the system can be improved, and the star topology network has the anti-interference capability.

Description

Anti-interference media access method and device for star topology network and electronic equipment

Technical Field

The invention relates to the technical field of wireless communication, in particular to an anti-interference media access method and device for a star topology network and electronic equipment.

Background

In the field of wireless communication technology, malicious interference signals and other network signals that may actually interfere with the network may hinder data transmission of legitimate users. Due to the openness of electromagnetic waves as transmission media in wireless communication, interference equipment can easily apply interference signals on one side of a receiver of a legal user, and the communication process of the legal user is damaged in a mode of reducing the signal-to-interference-and-noise ratio of the receiver. In some special situations, such as private network construction and emergency communication, the presence of interference signals becomes very common due to the lack of illegal device supervision and punishment. In particular, a network structure in which electromagnetic resources are coordinated and allocated by a central node, such as a star topology network, becomes extremely vulnerable in the above situations (e.g., a private LTE, NR network).

With the continuous improvement of the requirement of the legal user on the reliable transmission of the information, the reliable transmission of the information is ensured and the communication requirement is met, so that higher and stricter requirements are provided for the anti-interference capability of communication equipment, a system and a network. The traditional anti-interference method such as frequency hopping communication can effectively avoid the condition that the information transmission of the whole network is damaged when some channels are interfered by continuously and frequently changing communication channels between data pairs. However, the frequency hopping communication method is less studied in the star topology network. In the IEEE 802.15.4e protocol, a time slot Channel hopping protocol tsch (time slotted Channel hopping) for industrial internet of things is defined, wherein a link layer scheduling mechanism is defined, that is, all nodes perform data transmission on their allowed time frequency resources in a manner of one scheduling table. By matching with a centralized network manager provided by WirelessHART, a centralized resource scheduling method can be provided for the star topology network, and the problems of fading and interference in a wireless environment can be solved. However, in a scenario where the environment changes greatly (the interference signal changes frequently) and the scheduling needs to be reconfigured frequently, the performance may be degraded, and further research is needed.

In other anti-interference communication researches on star topology Networks, namely, in "correlation Learning for interference obtaining Reactive Jammers in Wireless Networks" (dead rank bar a, Kaddoum g.etc. IEEE Transactions on Communications,2021), a deceptive anti-interference method is adopted, and aiming at a directional interference signal which interferes with a signal with the maximum power of an interference machine side, a control center node deliberately designates a disguised channel to be interfered by configuring the transmission power of a common node in the network, and deceptive interference exerts interference on the channel, while other legal users can finish normal communication in a safe channel without being influenced.

The method can obtain better packet receiving performance than the known method under the interference mode of interfering the user with the maximum transmitting power. However, this method has a narrow application range and limited kinds of interference that can be resisted, so that the stability and reliability of the anti-interference method are low.

Disclosure of Invention

The invention aims to provide a novel anti-interference media access method, a novel anti-interference media access device and a novel anti-interference media access electronic device for solving the problem that the existing anti-interference method is limited in the interference resistance in the face of severe change, so that the network throughput rate is low.

In a first aspect, the present invention provides an anti-interference media access method for a star topology network, which is applied to a star topology network that adopts a frequency division multiplexing mode and has a central node and a plurality of users connected to the central node, and the method includes:

controlling a plurality of users to determine a target channel corresponding to each user based on a reinforcement learning channel selection algorithm in each access gap;

monitoring the target channel, and controlling to finish the transmission work of the target channel under the condition of detecting an interference signal;

monitoring the target channel, and retreating a plurality of signals corresponding to the target channel based on preset retreat duration under the condition that the interference signal is not detected to obtain a plurality of signals with different durations reaching the target channel;

transmitting an access request data packet formed based on a plurality of signals in a preset direction, receiving an access request response data packet, and determining whether all the users acquire the current time-frequency resource access qualification;

for the user obtaining the current time-frequency resource access qualification, initiating data transmission under the condition that the user receives the access request response data packet corresponding to the user, and determining that the signal transmission corresponding to the user is finished under the condition of receiving a data receiving receipt;

and updating the neural network parameters in the reinforcement learning channel selection algorithm based on the data corresponding to the completion of the signal transmission, completing the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed, and determining the access mode corresponding to the user.

Under the condition of adopting the technical scheme, a plurality of users can be controlled to determine a target channel corresponding to each user based on a channel selection algorithm of reinforcement learning in each access gap; monitoring the target channel, and controlling to finish the transmission work of the target channel under the condition of detecting an interference signal; monitoring the target channel, and retreating a plurality of signals corresponding to the target channel based on preset retreat duration under the condition that the interference signal is not detected to obtain a plurality of signals with different durations reaching the target channel; transmitting an access request data packet formed based on a plurality of signals in a preset direction, receiving an access request response data packet, and determining whether all the users acquire the current time-frequency resource access qualification; for the user obtaining the current time-frequency resource access qualification, initiating data transmission under the condition that the user receives the access request response data packet corresponding to the user, and determining that the signal transmission corresponding to the user is finished under the condition of receiving a data receiving receipt; the neural network parameters in the reinforcement learning channel selection algorithm are updated based on the data corresponding to the completion of the signal transmission, the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed is completed, the access mode corresponding to the user is determined, so that the network architecture using the star topology has the capacity of resisting partial random interference on the channel, a legal user can perform data transmission under the condition of malicious interference by using the star topology network, interference signals changed by a Markov random process on each channel can be resisted, the throughput rate of the system can be improved, and the star topology network has certain anti-interference capacity.

In a possible implementation manner, after the forming an access request data packet based on a plurality of the signals for transmission in a preset direction, receiving an access request response data packet, and determining whether all the users obtain current time-frequency resource access qualification, the method further includes:

determining that the signal transmission corresponding to the user fails under the condition that the user does not receive the access request response data packet completely corresponding to the user or does not receive the data receiving receipt;

and updating the neural network parameters in the reinforcement learning channel selection algorithm based on the data corresponding to the signal transmission failure, completing the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed, and determining the access mode corresponding to the user.

In a possible implementation manner, the listening to the target channel, and performing back-off on a plurality of signals corresponding to the target channel based on a preset back-off duration to obtain a plurality of signals with different durations reaching the target channel when the interfering signal is not detected includes:

monitoring the target channel, and randomly selecting a value as a backoff factor from a backoff index set under the condition that the interference signal is not detected;

determining the preset backoff duration based on the backoff factor;

and performing backoff on the plurality of signals corresponding to the target channel based on the preset backoff duration to obtain a plurality of signals with different durations reaching the target channel.

In a possible implementation manner, the transmitting of the access request packet formed based on a plurality of signals in a preset direction includes:

forming the access request packet including a cyclic prefix, a preamble sequence and a guard interval based on a plurality of the signals;

and transmitting the access request data packet in a preset direction.

In a possible implementation manner, the preset direction includes an uplink direction or a downlink direction.

In a second aspect, the present invention further provides an anti-interference media access device for a star topology network, which is applied to a star topology network that adopts a frequency division multiplexing mode and has a central node and a plurality of users connected to the central node, and the device includes:

a first determining module, configured to control, in each access gap, a plurality of the users to determine, based on a reinforcement learning channel selection algorithm, a target channel corresponding to each of the users;

the control module is used for monitoring the target channel and controlling to end the transmission work of the target channel under the condition of detecting an interference signal;

a backoff module, configured to monitor the target channel, and backoff, based on a preset backoff duration, a plurality of signals corresponding to the target channel to obtain a plurality of signals with different durations of reaching the target channel when the interference signal is not detected;

a second determining module, configured to perform transmission in a preset direction on an access request data packet formed based on the multiple signals, receive an access request response data packet, and determine whether all the users obtain a current time-frequency resource access qualification;

a third determining module, configured to initiate data transmission for a user obtaining the access qualification of the current time-frequency resource when the user receives the access request response data packet corresponding to the user's own integrity, and determine that signal transmission corresponding to the user is completed when a data reception receipt is received;

and the first updating module is used for updating the neural network parameters in the reinforcement learning channel selection algorithm based on the data corresponding to the completion of the signal transmission, completing the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed, and determining the access mode corresponding to the user.

In one possible implementation, the apparatus further includes:

a fourth determining module, configured to determine that signal transmission corresponding to the user fails when the user does not receive the access request response packet corresponding to the user completely or does not receive the data reception receipt;

and the second updating module is used for updating the neural network parameters in the reinforcement learning channel selection algorithm based on the data corresponding to the signal transmission failure, completing the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed, and determining the access mode corresponding to the user.

In one possible implementation, the backoff module includes:

the monitoring submodule is used for monitoring the target channel, and randomly selecting a value as a backoff factor from the backoff index set under the condition that the interference signal is not detected;

the determining submodule is used for determining the preset backoff duration based on the backoff factor;

and the back-off submodule is used for carrying out back-off on a plurality of signals corresponding to the target channel based on the preset back-off duration to obtain a plurality of signals with different durations reaching the target channel.

In one possible implementation manner, the second determining module includes:

a forming sub-module for forming the access request packet including a cyclic prefix, a preamble sequence and a guard interval based on a plurality of the signals;

the transmission submodule is used for transmitting the access request data packet in a preset direction;

the preset direction includes an uplink direction or a downlink direction.

The beneficial effects of the anti-interference media access apparatus for a star topology network provided in the second aspect are the same as the beneficial effects of the anti-interference media access method for a star topology network described in the first aspect or any possible implementation manner of the first aspect, and are not described herein again.

In a third aspect, the present invention also provides an electronic device, including: one or more processors; and one or more machine readable media having instructions stored thereon, which when executed by the one or more processors, cause the electronic device to perform the anti-interference media access method for a star topology network described in any of the possible implementations of the first aspect.

The beneficial effect of the electronic device provided in the third aspect is the same as that of the anti-interference media access method for the star topology network described in the second aspect or any possible implementation manner of the second aspect, and details are not repeated here.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and not to limit the invention. In the drawings:

fig. 1 shows a flowchart of an anti-interference media access method for a star topology network according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a star topology network according to an embodiment of the present disclosure;

fig. 3 is a schematic diagram illustrating time-frequency resources used for legal user data transmission according to an embodiment of the present application;

fig. 4 is a schematic diagram illustrating an overall working time axis of an uplink access algorithm according to an embodiment of the present application;

FIG. 5 is a schematic diagram illustrating a neural network structure used by each legitimate user according to an embodiment of the present disclosure;

fig. 6 is a schematic flowchart illustrating another anti-interference media access method for a star topology network according to an embodiment of the present application;

fig. 7 is a schematic diagram illustrating a method for constructing a broadcast paging packet according to an embodiment of the present application;

fig. 8 is a schematic diagram illustrating an overall operation time axis of a downlink access algorithm according to an embodiment of the present application;

fig. 9 shows an uplink average user throughput simulation curve provided in an embodiment of the present application;

fig. 10 shows a simulation curve of downlink average user throughput provided in an embodiment of the present application;

fig. 11 shows a schematic structural diagram of an anti-interference media access device for a star-topology network according to an embodiment of the present application;

fig. 12 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present invention;

fig. 13 is a schematic structural diagram of a chip according to an embodiment of the present invention.

Detailed Description

In order to facilitate clear description of technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish the same items or similar items having substantially the same functions and actions. For example, the first threshold and the second threshold are only used for distinguishing different thresholds, and the sequence order of the thresholds is not limited. Those skilled in the art will appreciate that the terms "first," "second," and the like do not denote any order or importance, but rather the terms "first," "second," and the like do not denote any order or importance.

It is to be understood that the terms "exemplary" or "such as" are used herein to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

In the present invention, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of the singular or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, a and b combination, a and c combination, b and c combination, or a, b and c combination, wherein a, b and c can be single or multiple.

Fig. 1 shows a schematic flow chart of an anti-interference media access method for a star topology network provided in an embodiment of the present application, and is applied to a star topology network that has a central node and a plurality of users respectively connected to the central node in a frequency division multiplexing manner, where as shown in fig. 1, the anti-interference media access method for the star topology network includes:

step 101: and controlling a plurality of users to determine a target channel corresponding to each user based on a reinforced learning channel selection algorithm in each access gap.

By using a reinforcement learning method in the field of artificial intelligence, a media Access layer algorithm based on the reinforcement learning method and suitable for a star topology network shown in fig. 2 is designed by utilizing the characteristics of the reinforcement learning method that the reinforcement learning method can interact with the environment and the decision level of a deployment unit is continuously improved, that is, an anti-interference media Access method of the star topology network is provided, fig. 2 shows a schematic diagram of the star topology network provided by the embodiment of the present application, as shown in fig. 2, the star topology network can include a central node (Access Point, AP)01 and K legal users 02 which are respectively in communication connection with the central node 01, and N jammers 03 also exist in the network.

In the present application, the star topology network uses frequency division multiplexing multiple access (FDMA) to respectively complete data transmission in the uplink and downlink directions in two different frequency bands. And in the process of transmitting data in uplink or downlink single direction, the available channel is used for data transmission in different time periods. In one data transmission, each legal user has one or more time frequency resource blocks shown in fig. 3 as time frequency resources for contention access, and fig. 3 shows a schematic diagram of time frequency resources used for data transmission of the legal user provided in the embodiment of the present application, where as shown in fig. 3, the horizontal axis represents time and the vertical axis represents channel numbers.

It should be noted that, in the dynamic spectrum access mechanism (the uplink dynamic spectrum access mechanism and the downlink dynamic spectrum access mechanism) in the preset direction described in the present application, it is assumed that the local originating transmission time of each legitimate user can be consistent with the start position of the time block of the central node by configuring a high-precision clock for each node and using an extra control channel.

In this application, without loss of generality, the uplink bandwidth of the system is assumed to be W _UP ＝W _UP-0 Channels are artificially divided into N _UP Are independent and have a bandwidth of

Set of subchannels { CH _i ^UP In which i ∈ {1, 2., N } _UP -1,N _UP }。

And setting the number of the time slots of the continuous work of the system as T (namely the total work duration as T), and formulating an access mode to the channel by optimizing an objective function of each legal user. Defining an objective function for each legal user as:

wherein r is _n (t') represents a return function of the nth legal user on the kth channel in the t-th time slot (successful data transmission is 1, unsuccessful data transmission is 0, and data uplink transmission by other users is 0.15). Wherein k is in the range of {1,2 _UP -1,N _UP }。

In each Access gap, a central node (Access Point, AP) may be responsible for exchanging control information with all K users in the network, and each legitimate user may deploy a set of dynamic spectrum Access methods, and an algorithm obtains the usage right of each time-frequency resource block through competition with other users, and the user obtaining the usage right performs data transmission in the remaining time on the time-frequency resource block.

Optionally, a plurality of the users may be controlled to select a channel from a set of channels {1, 2., N ] based on a reinforcement learning channel selection algorithm in each access slot _UP -1,N _UP Selecting a channel, that is, determining a target channel corresponding to each user.

Step 102: and monitoring the target channel, and controlling to finish the transmission work of the target channel under the condition of detecting the interference signal.

In the present application, the target channel may be monitored, and a if an interfering signal is detected _t'ij When 1, then control SU _i And ending the transmission work of the target channel, namely giving up the channel transmission opportunity.

Step 103: and monitoring the target channel, and retreating a plurality of signals corresponding to the target channel based on preset retreat duration under the condition that the interference signal is not detected, so as to obtain a plurality of signals with different durations reaching the target channel.

In the present application, the target channel may be monitored, and no interfering signal is detectedIn the case of (A) _t'ij 0, in the set of backoff indices {0,1,2 _max Randomly selecting a value as a backoff factor; determining the preset backoff duration based on the backoff factor; and carrying out backoff on a plurality of signals corresponding to the target channel based on the preset backoff duration to obtain a plurality of signals with different durations reaching the target channel.

Wherein the preset backoff duration is t _backoff ＝t _{bf_base} *2 ^λ Backoff may be performed based on the preset backoff duration, where t _{bf_base} Is the basic backoff duration.

Step 104: and transmitting an access request data packet formed based on a plurality of signals in a preset direction, receiving an access request response data packet, and determining whether all the users acquire the current time-frequency resource access qualification.

In the present application, after the preset backoff duration is over, the access request data packet including a cyclic prefix, a preamble sequence, and a guard interval is formed based on the plurality of signals; and transmitting the access request data packet in a preset direction.

Specifically, when the preset direction is an uplink direction, after the preset back-off duration is over, a preamble may be randomly selected from the preamble set ψ to form an uplink Access Request packet ar (Access Request) for uplink transmission, and an Access Request Reply (ARR) data packet issued by the central node within a specific RA window time is waited for to confirm whether all users obtain the current time-frequency resource Access qualification.

It should be noted that the uplink access request packet is also an access request data packet in the present application, and includes a cyclic prefix, a preamble sequence, and a guard interval.

In the application, the system uses OFDM frequency multiplexing mode to transmit data, therefore, the cyclic prefix CP part is adopted to resist the multi-path effect, then, the Zadoff-Chu sequence is adopted to construct the leader sequence used for distinguishing each user in the competitive access stage, wherein, the ZC sequence has ideal periodic autocorrelation and good cross correlation, when the number of the access users is lessAnd the probability of being allocated to the same ZC sequence is very low, so that the AP can uniquely identify the user identity according to the ZC sequence. At a specified root index q (root index q) and cyclic shift length

In this case, ZC sequence generation may be performed using the following formula:

after the leader sequence, a guard interval is reserved to enable the AP to carry out user detection, and the user serial number (according to the arrival sequence of the AR packet) of the current time-frequency resource is determined.

Step 105: and for the user obtaining the current time-frequency resource access qualification, initiating data transmission under the condition that the user receives the access request response data packet completely corresponding to the user, and determining that the signal transmission corresponding to the user is finished under the condition of receiving a data receiving receipt.

In the application, if a legal user receives an ARR packet completely belonging to the legal user, the data transmission is initiated, a data receiving receipt (ACK) issued by a CAP is waited, and when the data receiving receipt is received, an O is generated _tij And determining that the signal transmission corresponding to the user is finished.

Step 106: and updating the neural network parameters in the reinforcement learning channel selection algorithm based on the data corresponding to the completion of the signal transmission, completing the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed, and determining the access mode corresponding to the user.

In the application, the optimization of the objective function in the self reinforcement learning algorithm can be independently updated according to the local spectrum sensing and the channel access result (data corresponding to signal transmission completion), and the next round of training is carried out until the network stops running.

In this application, fig. 4 shows a schematic diagram of an overall working time axis of an uplink access algorithm provided in an embodiment of the present application, and with reference to fig. 4, a specific embodiment flow of the anti-interference media access method for a star topology network of the present application is as follows:

step (a), in a time slot, all legal users independently carry out channel selection algorithm based on reinforcement learning to determine channels and carry out local illegal user detection, namely carry out interference signal detection;

step (b), when no illegal interference signal is detected, that is, no occupied channel is detected, corresponding to O _t'ij Randomly selecting a backoff factor to perform backoff, and transmitting an uplink request data packet when the backoff time is over, wherein the backoff time is t from the sensing end time _sense Start of timing, t _sense +t _backof The time is the time when all the latest allowed legal user uplink request packets reach the AP under the condition of the specified network user number (K);

step (c) at t _ARR In a time period, the AP sequentially issues an access permission packet (from ARR1 to ARRK) of each user for each user AP, and an ARR data packet of each user comprises user identifications (1 to K) corresponding to the lead codes and corresponding user access permission (0 or 1) which are spliced;

step (d), obtaining the user of the current time frequency resource using authority at t _date Carrying out uplink data transmission in a time period;

step (e) at t _date At the time of the time period ending, the AP sends a receipt ACK (1) or receives no NACK (0) according to whether complete data information is received or not;

and (f) updating the neural network parameters in the reinforcement learning algorithm.

Note that, in the present application, the basic random backoff duration (t) is _{bf_base} ) Maximum backoff index (λ) _max ) The length of the cyclic prefix, the length of the preamble sequence code, the length of the guard interval in the uplink request data packet, the length of the random backoff window in the overall working time axis legend, and the time maintenance length of the access response data packet can be determined according to the end-to-end requirements of the actual system, the coverage range and the frequency band of the network planned deploymentAnd (4) specifically limiting.

The channel selection method based on reinforcement learning may include an uplink channel selection method based on reinforcement learning and a downlink channel selection method based on reinforcement learning, and the uplink channel selection method based on reinforcement learning is mainly introduced below, specifically, reinforcement learning elements that may define each legitimate user in each time slot include:

01. action (action, a) _t ) The 1 × N one-hot vector may indicate which channel the legitimate user selects for access;

02. observation (O) _t ) The tuple may represent an action vector at the previous time, a channel occupation result perceived by a valid user at the current time slot (0 indicates unoccupied, and 1 indicates occupied), and whether the valid user receives the RAK and the ACK packet (0 indicates not receiving the RAK, 1 indicates receiving the RAK and receiving the ACK packet, and 2 indicates receiving the RAR but not allowing the access, and other users perform data uplink);

03. reward (Reward, R) _t ) It means that the successfully transmitted data is 1, the unsuccessfully transmitted data is 0, and the data uplink is 0.15 when other legal users are authorized to perform data uplink;

04. and (3) exploring strategies: selecting the action with the maximum Q value according to the probability of 1-epsilon, and selecting the action randomly according to the probability;

05. the network parameter optimization method comprises the following steps: an Adam optimization method;

06. fig. 5 is a schematic diagram illustrating a neural network structure used by each legitimate user according to an embodiment of the present disclosure, and includes, as shown in fig. 5, an input layer, a fully-connected layer, a recurrent neural network layer, a fully-connected layer, and an output layer.

Each legitimate user can improve his own decision level by interacting with the environment to collect observations in a way that maximizes the objective function (long-term cumulative discount return). Since legitimate users have no prior knowledge of channel availability (i.e., the interfering signal generation method), we can use the Model-free based Q-learning derivation method in reinforcement learning to directly fit each state-action function Q (s, a) representing "in each state, perform an action to obtain a value" through a sample. Since Q (s, a) rises exponentially as the dimensionality of the number of channels and the number of actions increases, it becomes difficult to store Q values in a table manner, and therefore, the algorithm can adopt a deep-loop neural network DRQN to fit a state-action function. The loss function of the network is as follows, wherein: s ', a' represent the system state and legal user action choices for the next exercise, respectively:

L(w)＝E)[(r+Υ*max _a' Q(s',a',w)-Q(s,a,w)) ² ]；

and the network optimizes the network parameter w by a gradient descent method and determines the access mode corresponding to the user. The reinforcement learning algorithm can be applied to wireless media access of the star topology network, and the functions of detecting and deciding the occupied condition of an interference signal channel are sent back in the media access process.

In summary, the anti-interference media access method for the star topology network provided by the embodiment of the present application can control a plurality of users to determine a target channel corresponding to each user based on a channel selection algorithm of reinforcement learning in each access gap; monitoring the target channel, and controlling to finish the transmission work of the target channel under the condition of detecting an interference signal; monitoring the target channel, and retreating a plurality of signals corresponding to the target channel based on preset retreat duration under the condition that the interference signal is not detected to obtain a plurality of signals with different durations reaching the target channel; transmitting an access request data packet formed based on a plurality of signals in a preset direction, receiving an access request response data packet, and determining whether all the users acquire the current time-frequency resource access qualification; for the user obtaining the current time-frequency resource access qualification, initiating data transmission under the condition that the user receives the access request response data packet corresponding to the user, and determining that the signal transmission corresponding to the user is finished under the condition of receiving a data receiving receipt; the neural network parameters in the reinforcement learning channel selection algorithm are updated based on the data corresponding to the completion of the signal transmission, the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed is completed, the access mode corresponding to the user is determined, so that the network architecture using the star topology has the capacity of resisting partial random interference on the channel, a legal user can perform data transmission under the condition of malicious interference by using the star topology network, interference signals changed by a Markov random process on each channel can be resisted, the throughput rate of the system can be improved, and the star topology network has certain anti-interference capacity.

Fig. 6 is a schematic flowchart of another anti-interference media access method for a star topology network provided in an embodiment of the present application, and is applied to a star topology network that has a central node and a plurality of users respectively connected to the central node in a frequency division multiplexing manner, where as shown in fig. 6, the anti-interference media access method for the star topology network includes:

step 201: and controlling a plurality of users to determine a target channel corresponding to each user based on a channel selection algorithm of reinforcement learning in each access gap.

By using a reinforcement learning method in the field of artificial intelligence, a media Access layer algorithm based on the reinforcement learning method and suitable for a star topology network shown in fig. 2 is designed by utilizing the characteristics of the reinforcement learning method that the reinforcement learning method can interact with the environment and the decision level of a deployment unit is continuously improved, that is, an anti-interference media Access method of the star topology network is provided, fig. 2 shows a schematic diagram of the star topology network provided by the embodiment of the present application, as shown in fig. 2, the star topology network can include a central node (Access Point, AP)01 and K legal users which are in communication connection with the central node 01, and N malicious interference machines 03 also exist in the network.

In the present application, the star topology network uses frequency division multiplexing multiple access (FDMA) to respectively complete data transmission in the uplink and downlink directions in two different frequency bands. And in the process of transmitting data in the uplink or downlink single direction, the available channel is used for data transmission in different time periods. In one data transmission of each legal user, the time-frequency resource for contention access is one or more time-frequency resource blocks as shown in fig. 3, and fig. 3 shows a schematic diagram of the time-frequency resource used for data transmission of the legal user according to the embodiment of the present application, where as shown in fig. 3, the horizontal axis represents time and the vertical axis represents channel number.

In this application, without loss of generality, the uplink bandwidth of the system is assumed to be W _DW ＝W _DW-0 Channels are artificially divided into N _DW Are independent and have a bandwidth of

wherein r is _n (t') represents a return function of the nth legal user on the kth channel in the t-th time slot (successful data transmission is 1, unsuccessful data transmission is 0, and data uplink transmission by other users is 0.15). Wherein k is in the range of {1,2 _DW -1,N _DW }。

Step 202: and monitoring the target channel, and controlling to finish the transmission work of the target channel under the condition of detecting the interference signal.

In the present application, the target channel may be monitored, and in case of detection of an interfering signal, a _t'ij When 1, then control SU _i And ending the transmission work of the target channel, namely giving up the channel transmission opportunity.

Step 203: and monitoring the target channel, and retreating a plurality of signals corresponding to the target channel based on preset retreat duration under the condition that the interference signal is not detected, so as to obtain a plurality of signals with different durations reaching the target channel.

In the present application, a target channel may be monitored, and a may be performed when no interfering signal is detected _t'ij 0, in the set of backoff indices {0,1,2 _max Randomly selecting a value as a backoff factor; determining the preset backoff duration based on the backoff factor; and carrying out backoff on a plurality of signals corresponding to the target channel based on the preset backoff duration to obtain a plurality of signals with different durations reaching the target channel.

Step 204: and transmitting an access request data packet formed based on a plurality of signals in a preset direction, receiving an access request response data packet, and determining whether all the users acquire the current time-frequency resource access qualification.

In the application, the system uses OFDM frequency multiplexing mode to transmit data, therefore, the cyclic prefix CP part is adopted to resist the multipath effect, then, the Zadoff-Chu sequence is adopted to construct the leader sequence for distinguishing each user in the competitive access stage, wherein, the ZC sequence has ideal periodic autocorrelation and good cross correlation, when the number of the access users is less, the probability of distributing the same ZC sequence is very low, therefore, the AP can uniquely identify the user identity according to the ZC sequence. At a specified root index q (root index q) and cyclic shift length

Step 205: and for the user obtaining the current time-frequency resource access qualification, initiating data transmission under the condition that the user receives the access request response data packet completely corresponding to the user, and determining that the signal transmission corresponding to the user is finished under the condition of receiving a data receiving receipt.

Step 206: and updating the neural network parameters in the reinforcement learning channel selection algorithm based on the data corresponding to the completion of the signal transmission, completing the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed, and determining the access mode corresponding to the user.

step (c) at t _ARR In the time period, the AP sequentially issues the AP for each userThe access permission packets (from ARR1 to ARRK) of the users, and the ARR data packet of each user is formed by splicing user identifications (1 to K) corresponding to the lead codes and corresponding user access permission (0 or 1);

Note that, in the present application, the basic random backoff duration (t) is _{bf_base} ) Maximum backoff index (λ) _max ) The length of the cyclic prefix, the length of the preamble sequence code, and the length of the guard interval in the uplink request packet, as well as the length of the random backoff window and the time maintenance length of the access response packet in the overall working time axis legend, may all be determined jointly according to the end-to-end requirement of the actual system, the coverage range to be deployed by the network, the frequency band, and other requirements, and the specific values thereof are not specifically limited in the embodiments of the present application.

06. fig. 5 is a schematic diagram illustrating a neural network structure used by each legitimate user according to an embodiment of the present disclosure, and includes, as shown in fig. 5, an input layer, a fully-connected layer, a recurrent neural network layer, a fully-connected layer, and an output layer. It should be noted that, the number of neurons and activation functions in each layer are not limited in the embodiments of the present application, and may be specifically adjusted according to an actual application scenario.

L(w)＝E)[(r+Υ*max _a' Q(s',a',w)-Q(s,a,w)) ² ]；

Step 207: and determining that the signal transmission corresponding to the user fails under the condition that the user does not receive the access request response data packet completely corresponding to the user or the data receiving receipt.

In the present application, when the user does not receive an ARR packet or performs data transmission but does not receive ACK, O is generated _tij ＝0。

Step 208: and updating the neural network parameters in the reinforcement learning channel selection algorithm based on the data corresponding to the signal transmission failure, completing the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed, and determining the access mode corresponding to the user.

In the present application, for the preset direction being the downlink direction, corresponding to the uplink direction, without loss of generality, it is assumed that the uplink bandwidth of the system is W _DW ＝W _DW-0 Channels are artificially divided into N _DW Are independent and have a bandwidth of

Set of subchannels { CH _i ^DW In which i ∈ {1, 2., N } _DW -1,N _DW }。

For the dynamic spectrum access method in the downlink direction, the method can comprise the following sub-steps:

substep S1: firstly, channel availability detection is carried out on each local channel through the AP, and an idle channel is selected to form a channel set phi supporting data issuing.

Substep S2: the control AP broadcasts paging packets (IB) on all locally available channel sets phi to measure whether all legitimate users to be paged support downlink data transmission.

Substep S3: the legal user can select the channel set {1, 2., N ] according to the downlink channel selection algorithm based on reinforcement learning _DW -1,N _DW Selecting one channel j, keeping monitoring on the channel, waiting for paging data packet IB issued by AP, if IB data packet is successfully received in specified time, determining that current channel is available, A _tij Otherwise an interfering signal is considered to be present, a _tij ＝0。

Substep S4: if A _tij When 0 or IB paging user does not include itself, SU is controlled _i Ending the transmission of the target channel, i.e. giving up the transmission opportunity of the current channel, and generating O _tij ＝0，R _t Otherwise, performing the following substeps:

sub-step F1: in the set of backoff indices {0,1, 2.,. lambda.,) _max Randomly selecting a value as a backoff factor, and carrying out time length t _backoff ＝t _{bf_base} *2 ^λ And carrying out backoff.

Sub-step F2: and after the backoff duration is finished, randomly selecting a lead code from the lead code set to form an uplink confirmation packet and perform uplink transmission, and waiting for downlink data transmission after the AP confirmation.

Sub-step F3: performing AP downlink data transmission, A _tij The legal user 1 continuously receives data, and if a data packet is received and the destination of the data packet is self, O is generated _tij ＝1，R _t Replying ACK to the AP as 1; otherwise, O is generated _tij Observation of 2, R _t Award 0.15 and discard the packet.

Sub-step F4: and updating the intelligent agent parameters (W) in the reinforcement learning algorithm, and performing the next round of training until the network stops running.

Fig. 7 shows a schematic diagram of a method for constructing a broadcast paging packet according to an embodiment of the present application, and as shown in fig. 7, an AP broadcasts a paging packet IB, where the paging packet is 1 vector of 1 × N, each bit indicates whether a corresponding user has a data packet to be transmitted by an AP downlink data, 0 indicates that downlink data exists, and 1 indicates that no downlink data is transmitted. The user may look up the paging indicator at a fixed location in the broadcast paging packet at a fixed location with the index number (1-N) of the sequence number in the network.

Optionally, the AP pages on each channel, and only the legitimate users that arrive at the AP side first and are in the downlink paging set are allowed to access in response.

Fig. 8 shows a schematic diagram of an overall working time axis of a downlink access algorithm provided in an embodiment of the present application, and as shown in fig. 8, a specific embodiment of the overall downlink algorithm may include:

step P1: in a time slot, all legal users independently perform channel selection algorithm based on reinforcement learning to determine a channel and receive signals, and wait for the AP to issue a paging broadcast packet; and meanwhile, the AP detects all the channels and counts the channel set supporting downlink transmission.

Step P2: the AP broadcasts paging packets on all locally available channel sets. Meanwhile, all users receive IB packets on the respective selected channels, and know that the maximum receiving time t is reached _sense +t _{IB_recv} 。

Step P3: the IB packet detects a user paging the IB packet by the AP, a backoff factor is randomly selected for backoff, when the backoff time is over, the uplink acknowledgement packet is sent, and the maximum time when the AP side receives the uplink acknowledgement packet of the user is as follows: t is t _sense +t _{IB_recv} +t _backoff And then the AP does not receive the uplink data packet of the user any more and directly starts to transmit downlink data.

Step P4: and the AP initiates downlink data transmission to the first user replying the uplink acknowledgement packet on each channel, and all users receive data on respective channels.

Step P5: at t _date Can be determined by each user according toIf the complete data packet directed to the AP is not received, the AP receives an ACK (1) or receives no NACK (0).

Step P6: and each user updates the neural network parameters in the reinforcement learning algorithm.

For example, for the downlink channel selection method based on reinforcement learning, the reinforcement learning elements that can be defined for each legitimate user in each timeslot include:

01. action (action, a) _t )，1×N _DW The one-hot vector of (2) can indicate which channel a legal user selects to listen and receive data;

02. observation (O) _t ) Tuple, which may represent the last moment of the action vector, the observation A of whether the current legitimate user received the IB packet or not _tij Whether the current legal user receives the AP issued data packet with the target of the current legal user is observed O _tij ；

The structure of the neural network used in the downlink process is the same as that of the uplink process, and the neural network parameters are optimized by reducing the loss function by the gradient descent method, so that the legal user strategy is improved.

In the application, the legal users in the network can resist interference to carry out the uplink and downlink transmission flow of data transmission, the network overall deployment method and the matched uplink and downlink process access request packet construction method. The network architecture using the star topology has the capability of resisting partial random interference on channels, a legal user can transmit data under the condition that malicious interference signals exist in the star topology network, and compared with a specific interference mode, the system can resist the interference signals changing in the Markov random process on each channel.

Compared with the common resource distribution type star topology network without introducing an anti-interference method, the system throughput rate can be improved, so that the star topology network has certain anti-interference capability, the number of channels is set to be 8, the number of users is set to be 8, and Markov-compliant transfer matrices are applied to channels 1-5

Applying a Markov-compliant transfer matrix to channels No. 6-8

Compared with the common star topology network which is respectively distributed by 1-8 users and transmitted at a fixed frequency in the uplink and downlink directions, the interference of the method is characterized in that under the condition that the effective data transmission time of the method is less than that of the common star topology network, when the uplink and downlink discount factors are 65% and 70% respectively, the maximum data rate of each channel is 400kbits/s and each time slot is 0.5, 20 times of simulation are carried out, 2500 time slots are simulated each time, figure 9 shows an uplink average user throughput simulation curve provided by the embodiment of the method, figure 10 shows a downlink average user throughput simulation curve provided by the embodiment of the method, as can be known from figures 9 and 10, when the algorithm converges, the throughput in the uplink and downlink directions is improved on each user compared with that of the common star topology network, which shows that the algorithm provides the capability of resisting the interference, meanwhile, the transmission time of the access algorithm designed by the application is limited by specific physical layer parameters, the average throughput is limited after stabilization, the optimization time is carried out on the physical layer, and the average throughput can be further improved after the effective transmission time is prolonged.

Fig. 11 shows a schematic structural diagram of an anti-interference media access apparatus for a star topology network provided in an embodiment of the present application, which is applied to a star topology network that adopts a frequency division multiplexing manner and has a central node and a plurality of users respectively connected to the central node, and as shown in fig. 11, the apparatus 300 includes:

a first determining module 301, configured to control, in each access gap, a plurality of the users to determine a target channel corresponding to each of the users based on a reinforcement learning channel selection algorithm;

a control module 302, configured to monitor the target channel, and control to end transmission of the target channel when an interference signal is detected;

a backoff module 303, configured to monitor the target channel, and backoff, based on a preset backoff duration, a plurality of signals corresponding to the target channel to obtain a plurality of signals with different durations of reaching the target channel when the interference signal is not detected;

a second determining module 304, configured to perform transmission in a preset direction on an access request data packet formed based on a plurality of signals, receive an access request response data packet, and determine whether all the users obtain a current time-frequency resource access qualification;

a third determining module 305, configured to initiate data transmission for a user obtaining the access qualification of the current time-frequency resource when the user receives the access request response data packet corresponding to the user, and determine that signal transmission corresponding to the user is completed when receiving a data reception receipt;

a first updating module 306, configured to update a neural network parameter in the reinforcement learning channel selection algorithm based on data corresponding to the completion of signal transmission, complete optimization of an objective function in the channel selection algorithm of the user correspondingly accessed, and determine an access mode corresponding to the user.

Optionally, the apparatus further comprises:

Optionally, the backoff module includes:

Optionally, the second determining module includes:

the preset direction comprises an uplink direction or a downlink direction.

The anti-interference media access device for the star topology network, provided by the embodiment of the application, can control a plurality of users to determine a target channel corresponding to each user based on a channel selection algorithm of reinforcement learning in each access interval; monitoring the target channel, and controlling to finish the transmission work of the target channel under the condition of detecting an interference signal; monitoring the target channel, and retreating a plurality of signals corresponding to the target channel based on preset retreat duration under the condition that the interference signal is not detected to obtain a plurality of signals with different durations reaching the target channel; transmitting an access request data packet formed based on a plurality of signals in a preset direction, receiving an access request response data packet, and determining whether all the users acquire the current time-frequency resource access qualification; for the user obtaining the current time-frequency resource access qualification, initiating data transmission under the condition that the user receives the access request response data packet corresponding to the user, and determining that the signal transmission corresponding to the user is finished under the condition of receiving a data receiving receipt; the neural network parameters in the reinforcement learning channel selection algorithm are updated based on the data corresponding to the completion of the signal transmission, the optimization of the objective function in the channel selection algorithm of the user correspondingly accessed is completed, the access mode corresponding to the user is determined, so that the network architecture using the star topology has the capacity of resisting partial random interference on the channel, a legal user can perform data transmission under the condition of malicious interference by using the star topology network, interference signals changed by a Markov random process on each channel can be resisted, the throughput rate of the system can be improved, and the star topology network has certain anti-interference capacity.

The anti-interference media access device for the star topology network provided by the invention can realize the anti-interference media access method for the star topology network as shown in any one of fig. 1 to fig. 10, and is not repeated here to avoid repetition.

The electronic device in the embodiment of the present invention may be a device, or may be a component, an integrated circuit, or a chip in a terminal. The device can be mobile electronic equipment or non-mobile electronic equipment. By way of example, the mobile electronic device may be a mobile phone, a tablet computer, a notebook computer, a palm top computer, a vehicle-mounted electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a Personal Digital Assistant (PDA), and the like, and the non-mobile electronic device may be a server, a Network Attached Storage (NAS), a Personal Computer (PC), a Television (TV), a teller machine or a self-service machine, and the like, and the embodiment of the present invention is not particularly limited.

The electronic device in the embodiment of the present invention may be an apparatus having an operating system. The operating system may be an Android (Android) operating system, an ios operating system, or other possible operating systems, and embodiments of the present invention are not limited in particular.

Fig. 12 is a schematic diagram illustrating a hardware structure of an electronic device according to an embodiment of the present invention. As shown in fig. 12, the electronic device 400 includes a processor 410.

As shown in fig. 12, the processor 410 may be a general processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more ics for controlling the execution of programs according to the present invention.

As shown in fig. 12, the electronic device 400 may further include a communication line 440. Communication link 440 may include a path for transmitting information between the aforementioned components.

Optionally, as shown in fig. 12, the electronic device may further include a communication interface 420. The communication interface 420 may be one or more. Communication interface 420 may use any transceiver or the like for communicating with other devices or a communication network.

Optionally, as shown in fig. 12, the electronic device may further include a memory 430. The memory 430 is used to store computer-executable instructions for performing aspects of the present invention and is controlled for execution by the processor. The processor is used for executing the computer execution instructions stored in the memory, thereby realizing the method provided by the embodiment of the invention.

As shown in fig. 12, the memory 430 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a Random Access Memory (RAM) or other types of dynamic storage devices that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 430 may be separate and coupled to the processor 410 via a communication link 440. The memory 430 may also be integrated with the processor 410.

Optionally, the computer-executable instructions in the embodiment of the present invention may also be referred to as application program codes, which is not specifically limited in this embodiment of the present invention.

In particular implementations, as one embodiment, processor 410 may include one or more CPUs, such as CPU0 and CPU1 in fig. 12, as shown in fig. 12.

In a specific implementation, as an embodiment, as shown in fig. 12, the terminal device may include a plurality of processors, such as the first processor 4101 and the second processor 4102 in fig. 12. Each of these processors may be a single core processor or a multi-core processor.

Fig. 13 is a schematic structural diagram of a chip according to an embodiment of the present invention. As shown in fig. 13, the chip 500 includes one or more than two (including two) processors 410.

Optionally, as shown in fig. 13, the chip further includes a communication interface 420 and a memory 430, and the memory 430 may include a read-only memory and a random access memory and provide operating instructions and data to the processor. The portion of memory may also include non-volatile random access memory (NVRAM).

In some embodiments, as shown in FIG. 13, memory 430 stores elements, execution modules or data structures, or a subset thereof, or an expanded set thereof.

In the embodiment of the present invention, as shown in fig. 13, by calling an operation instruction stored in the memory (the operation instruction may be stored in the operating system), a corresponding operation is performed.

As shown in fig. 13, the processor 410 controls the processing operation of any one of the terminal devices, and the processor 410 may also be referred to as a Central Processing Unit (CPU).

As shown in fig. 13, memory 430 may include both read-only memory and random access memory, and provides instructions and data to the processor. A portion of the memory 430 may also include NVRAM. For example, in applications where the memory, communication interface, and memory are coupled together by a bus system that may include a power bus, a control bus, a status signal bus, etc., in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 540 in FIG. 13.

As shown in fig. 13, the method disclosed in the above embodiment of the present invention can be applied to a processor, or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The processor may be a general purpose processor, a Digital Signal Processor (DSP), an ASIC, an FPGA (field-programmable gate array) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

In one aspect, a computer-readable storage medium is provided, in which instructions are stored, and when executed, the instructions implement the functions performed by the terminal device in the above embodiments.

In one aspect, a chip is provided, where the chip is applied in a terminal device, and the chip includes at least one processor and a communication interface, where the communication interface is coupled to the at least one processor, and the processor is configured to execute instructions to implement the functions performed by the anti-interference media access method for a star-topology network in the foregoing embodiments.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the procedures or functions described in the embodiments of the present invention are performed in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, a terminal, a user device, or other programmable apparatus. The computer program or instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer program or instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire or wirelessly. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that integrates one or more available media. The usable medium may be a magnetic medium, such as a floppy disk, a hard disk, a magnetic tape; or optical media such as Digital Video Disks (DVDs); it may also be a semiconductor medium, such as a Solid State Drive (SSD).

While the invention has been described in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a review of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the word "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

While the invention has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the invention. Accordingly, the specification and figures are merely exemplary of the invention as defined in the appended claims and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the invention. It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims

1. An anti-interference media access method for a star topology network is characterized in that the method is applied to the star topology network which adopts a frequency division multiplexing mode and is provided with a central node and a plurality of users connected with the central node respectively, and the method comprises the following steps:

for the user obtaining the current time-frequency resource access qualification, under the condition that the user receives the access request response data packet corresponding to the user, initiating data transmission, and under the condition that a data receiving receipt is received, determining that the signal transmission corresponding to the user is completed;

2. The method of claim 1, wherein after the forming an access request packet based on a plurality of the signals for transmission in a predetermined direction, receiving an access request response packet, and determining whether all the users are eligible for current time-frequency resource access, the method further comprises:

3. The method according to claim 1, wherein the listening to the target channel and, if the interfering signal is not detected, performing back-off on a plurality of signals corresponding to the target channel based on a preset back-off duration to obtain a plurality of signals with different durations reaching the target channel comprises:

determining the preset backoff duration based on the backoff factor;

and carrying out backoff on a plurality of signals corresponding to the target channel based on the preset backoff duration to obtain a plurality of signals with different durations reaching the target channel.

4. The method of claim 1, wherein the transmitting the access request packet formed based on the plurality of signals in the predetermined direction comprises:

and transmitting the access request data packet in a preset direction.

5. The method of claim 1, wherein the predetermined direction comprises an uplink direction or a downlink direction.

6. An anti-interference media access device of a star topology network is applied to a star topology network which adopts a frequency division multiplexing mode and is provided with a central node and a plurality of users connected with the central node respectively, and the device comprises:

7. The apparatus of claim 6, further comprising:

8. The apparatus of claim 6, wherein the back-off module comprises:

9. The apparatus of claim 6, wherein the second determining module comprises:

the preset direction comprises an uplink direction or a downlink direction.

10. An electronic device, comprising: one or more processors; and one or more machine readable media having instructions stored thereon that, when executed by the one or more processors, cause the electronic device to perform the method of star topology network interference rejection medium access of any of claims 1 to 5.