CN111313994B - Multi-user spectrum access method based on multi-arm gambling machine model under fairness principle - Google Patents
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Abstract
The invention discloses a multi-user spectrum access method based on a multi-arm gambling machine model under the fairness principle. The method comprises the following steps: firstly, aiming at a multi-user cognitive wireless network, establishing a channel perception and opportunity access model based on a multi-arm gambling machine model; then initializing the perception channel parameters of the secondary user; then each secondary user performs channel perception and updates channel statistical information on line; and finally, the secondary user performs channel access according to the channel sensing condition and judges whether the channel access conflicts or not, and after the channel access conflicts or not, the sensing process of the next time slot is restarted. The invention has the advantages of fairness, high efficiency and excellent performance, and can meet the wide and actual scene requirements.
Description
Technical Field
The invention relates to the technical field of wireless networks, in particular to a multi-user spectrum access method based on a multi-arm gambling machine model under the fairness principle.
Background
With the rapid increase of wireless communication service demand, the available spectrum resources are more and more scarce, and the contradiction of spectrum supply is increasingly prominent. On the other hand, the effective utilization rate of the authorized frequency band is very low, and the intermittent spectrum idling problem is serious. The cognitive radio access is considered as one of the main means capable of effectively relieving the spectrum tension problem by dynamically utilizing the spectrum gap to fill the gap of service requirement. Through the cognitive radio technology, the secondary user can sense the authorized spectrum in real time to identify the idle spectrum, and on the premise of not influencing the normal work of the primary user, the secondary user uses the sensed idle spectrum to perform opportunistic access to complete data transmission. In order to effectively use spectrum resources, secondary users need to design an efficient dynamic spectrum access method. Most of the existing technical schemes aim at the known situation of frequency spectrum information, but under the condition that the frequency spectrum information is unknown, an efficient secondary user perception access method is not available. For multi-user spectrum access under the condition that channel spectrum information is unknown, an efficient sensing and access method is not available.
In the case where conventional statistics are known, it is generally assumed that the secondary users know the idleness probability information of the licensed spectrum. In order to utilize the spectrum resources to the maximum extent and complete data transmission as much as possible, in each channel time slot, the secondary user selects the channel with the maximum idle probability information to perform spectrum sensing, and accesses all the channels which are sensed to be idle. In practical scenarios, such as an opportunistic access network, an unknown area, or a network with malicious interference, the secondary user usually cannot know the channel statistical information in advance, or needs to obtain the information through long-time spectrum sampling and data analysis. Therefore, the conventional channel sensing and access method with known channel statistics cannot be applied to the above scenario. Under the condition that the channel statistical information is unknown, the secondary user needs to measure the channel in real time through spectrum sensing, obtain the spectrum statistical information by using an online data analysis method, and dynamically access the spectrum. In the above-mentioned problem, the acquisition of the spectrum sensing and access method for the optimal user can be abstracted into a classical statistical model, namely, the Multi-arm gambling machine problem (MABP). Specifically, for accurate estimation of the optimal channel set, the secondary user needs to perform spectrum sensing for all channels for a sufficient time, accurately estimate channel statistical information by using measurement data, and distinguish the optimal channel from the suboptimal channel to realize dynamic channel optimal access. Since the channel statistical information can be accurately obtained only after a certain period of time, the secondary user can perceive or access a non-optimal channel in the spectrum sensing and opportunistic access processes, and the loss of revenue is inevitable.
In addition, in a practical network, the channel access fairness of multiple users is an important index for measuring the network performance. Fairness refers to that secondary users in a cognitive wireless network are regarded as peer-to-peer nodes, and all users share the same right for network access, so that in order to ensure the balance of user access efficiency, the difference of access performance among the users needs to be considered in the design of an access method, and the user benefits are achieved as average as possible. At present, the existing method related to the access of the multi-user cognitive radio network mainly provides a reasonable and efficient access strategy to avoid loss caused by perception and access of a plurality of secondary users to the same channel, so that the whole cognitive radio network can transmit as much information as possible in unit time, and no method considers the fairness principle among the secondary users.
In summary, the spectrum dynamic access method is designed on the basis of the optimal channel sensing access yield with known statistical information and on the premise of fairness among secondary users under the condition that the channel statistical information is unknown, so that the efficient balance between the multi-user transmission throughput and the fairness is realized, and the method has certain significance for improving the utilization rate of the authorized spectrum.
The current main channel sensing and access methods have the following disadvantages:
1) the actual scene is not considered enough: most of the existing sensing and access methods are proposed based on the condition that the channel statistical information is known, and cannot be applied to the condition that the channel statistical information is unknown;
2) the fairness of the user spectrum access is not considered: the existing methods are all provided with the aim of maximizing the throughput of multiple users, and the fairness problem among secondary users is not considered;
3) the hardware constraint is not considered enough: most of the existing work is based on the fact that the secondary users sense that the number of channels is the same as the number of access channels, but due to the fact that the mobile terminal is miniaturized and the secondary users are limited in energy, processing capacity and the like, the secondary users need to select partial channels to access from multiple sensed channels. In addition, the conventional work is based on that the secondary user can perfectly sense the channel state, and in an actual situation, due to noise, system errors and the like, certain errors exist in the sensing of the secondary user on the channel state.
Disclosure of Invention
The invention aims to provide a multi-user spectrum access method based on a multi-arm gambling machine model under the fairness principle of fairness, high efficiency and excellent performance.
The technical solution for realizing the purpose of the invention is as follows: a multi-user spectrum access method based on a multi-arm gambling machine model under the fairness principle comprises the following steps:
and 4, the secondary user performs channel access according to the channel sensing condition and judges whether the channel access conflicts or not, and after the channel access conflicts or not, the secondary user jumps to the step 3.
Further, the establishing of the multi-user channel sensing and opportunistic access model in step 1 is as follows:
step 1.1, setting U users in a cognitive network, wherein each user has a unique identification number, and the identification number corresponding to the user U is U, and the U belongs to {1, 2.., U }; n authorized channels are arranged in the network, a master user accesses the channels according to time slots, and the idle probability of the master user channels meets theta1＞θ2＞...＞θN(ii) a In a single time slot, a secondary user can simultaneously sense M channels, wherein U.M is less than N, and at most K sensing idle channels are accessed, and K is less than or equal to M; of secondary importanceThe user generates a label according to the self identification number in the time slot t, and the label is marked as Selu(t) determining a set of perceived channel indices, denoted as
According to the label sets of the channels, the secondary users select corresponding channels from all the sorted channel sets for perception; channel sensing is imperfect spectrum sensing, using PdAnd PfRespectively representing the detection probability and the false alarm probability of the channel;
step 1.2, uniformly modeling the perception access problem of the secondary user into an MABP problem.
Further, the initialization of the secondary user sensing channel parameters in step 2 is specifically as follows:
for time slot
The secondary user u follows { (l-1) M + 1: lM } the sequence of sensing all channels in turn, updating Tu(t)＝(Tu，l(t)，Tu，2(t)，...，Tu，N(t)) and Yu(t)＝(Yu，l(t)，Yu，2(t)，...，Yu，N(t)), and randomly selecting K idle channels for access;
wherein
Representing an upward rounding function, Tu(t) and Yu(T) represents a vector of length 1 XN, Tu，i(t) represents the number of time slots of the user u perceptual channel i before time slot t, Yu，i(t) represents the number of time slots before time slot t where user u perceives channel i as free.
Further, each secondary user in step 3 performs channel sensing and updates channel statistical information online, which is specifically as follows:
step 3.1, in time slot t, the secondary user u calculates all channel coefficients theta according to the expectation of the sample mean valueiIs estimated by
i ∈ {1, 2., N }, and the channel is indexed by index
Arranging in descending order to obtain channel set
Step 3.2, under time slot t, the secondary user u updates the corresponding label
Wherein mod is an arithmetic operator and represents a remainder obtained by integer division of two numbers; as shown in step 3.1, as time t increases, u + t-1 changes continuously, and the label Selu(t) also varies with time;
step 3.3, in time slot t, the secondary user u follows the label Selu(t) determining a set of perceptual channel indices at time slot t
Corresponding channel sets are
The secondary user u perceives the selected channel set and updates T according to the perception resultu(t) and Yu(t) and identifying a set of channels that are perceived to be idle
Further, in step 4, the secondary user performs channel access according to the channel sensing condition and determines whether a collision occurs, which is specifically as follows:
step 4.1, if set
If not, the secondary user u selects the set
Middle index
Largest size
Accessing a channel; otherwise, no channel is accessed; wherein
Representation collection
The number of middle elements, min {. cndot } represents the minimum element in the set;
and 4.2, finishing the sensing and opportunistic access processes in the time slot t by the secondary user, skipping to the step 3, and starting the sensing process of the next time slot t + 1.
Compared with the prior art, the invention has the remarkable advantages that: (1) based on the perception and opportunity access problems in the multi-user cognitive network under the condition that channel statistical information is unknown, the wide and actual scene requirements are met; (2) the secondary users sense the optimal channel set with the same probability, and the information quantity transmitted by the secondary users is the same in a long enough time; (3) based on the condition that the secondary users sense different numbers of the access channels and the condition that the secondary users do not need to perfectly sense the occupation condition of the channels, the problem that the secondary users sense the channel state wrongly due to noise, system errors and the like is solved, and the application scene is closer to reality; (4) the performance is superior, and the loss-of-return performance is O (ln t) when the time is limited and approaches infinity (t → ∞).
Drawings
Fig. 1 is a flow chart of a multi-user spectrum access method based on a dobby gambling machine model under the fairness principle of the invention.
Fig. 2 is a schematic flow chart of the secondary user spectrum dynamic access in the present invention.
FIG. 3 is a graph of normalized loss of revenue versus time for different U, N, K in an embodiment of the present invention.
FIG. 4 is a histogram of the average revenue over time for a time slot of a secondary user unit in accordance with an embodiment of the present invention.
Detailed Description
In a multi-user wireless cognitive network, based on a fairness principle between a classical MABP model and a secondary user, the invention provides an effective channel sensing and opportunity access method; the effectiveness of the method provided by the invention is verified through theoretical analysis and simulation.
For ease of understanding, some terms are explained below.
Fairness principle: the secondary users in the cognitive wireless network are regarded as peer-to-peer nodes, and all users share the same power for network access, so that the difference of access performance among the users is considered in the design of an access method to ensure the balance of user access efficiency, and the user benefits are realized as average as possible.
Imperfect main channel perception: in a practical cognitive network, due to the limitation of the receiving signal-to-noise ratio of the primary user channel, channel identification errors may exist in secondary user channel perception, and the situation is called as imperfect primary channel perception.
Perfect primary channel perception: the process of assuming that the secondary user does not have any error in channel perception is called perfect primary channel perception.
Opportunistic spectrum access: if the secondary user detects available spectrum, the secondary user may access the available spectrum without causing interference to the primary user.
MABP: multiple-arm gambling machines. Assuming that there are multiple booms, selecting any one will bring random gains; for the player, the instant profit generation process can be regarded as a black box and cannot be obtained from direct observation, but needs to learn, obtain the statistical characteristics of each horn and make a selection based on the statistical characteristics to ensure that the player can obtain the maximum profit.
And (3) detection probability: when the receiver input does have a signal, two decisions may be made due to interference background, etc.: "signal" or "no signal". When there is a signal, the probability of making a correct decision that "there is a signal" is called the detection probability.
False alarm probability: the probability that "no signal" is detected but "signal" is judged, or the probability that "signal" is judged as "no signal".
Collision: when multiple secondary users access the same channel, the transmission rate of the secondary users on the channel is zero. And as such the event is a collision.
sample mean value: the mean is the sum of all data in a set of data divided by the number of the set of data, and the sample mean is the mean of the sample data in the population.
It is desired that: the probability of each possible outcome in the trial is multiplied by the sum of its outcomes, which reflects the magnitude of the average value of the random variable.
the main users: users authorized to access the spectrum.
The secondary user: users that can access the spectrum without affecting the primary user.
mod: the arithmetic operator, representing the remainder of the division of two numbers, is, for example, mod (5, 2) resulting in a value of 1.
f (t) to O (ln t): indicates the existence of a constant c, such that for time t > t0There is a constant such that f (t) < cln t.
The invention is further described in detail below with reference to the drawings and the specific embodiments.
With reference to fig. 1, the method for multi-user spectrum access based on a dobby gambling machine model under the fairness principle of the invention comprises the following steps:
for practical problems, the problem is modeled using the MABP model. The MABP problem is first analyzed for similarities between secondary user perception and opportunistic access channels in cognitive wireless networks. Specifically, a plurality of arms in the MABP problem correspond to a master user channel in a cognitive wireless network; the statistical information of the horn is unknown, and the idle probability of the main channel in the corresponding cognitive radio network is unknown; the process that the player chooses to pull the horn and obtains the corresponding benefit is equivalent to the process that a secondary user in the cognitive radio network perceives the channel and accesses the channel; based on the observation information, the process of further estimating the horn profit by the player is equivalent to the process of estimating the statistical information of each channel by the secondary user in the cognitive radio network; the process of designing policies for maximum profit to players in the MABP is equivalent to designing perceptual access policies for secondary users in cognitive wireless networks. By combining the above analysis, the cognitive network opportunistic access problem has great similarity to the MABP problem, and the problem can be solved by establishing a proper mathematical model. In addition, since the secondary user can select the optimal partial idle channel from the multiple perceived channels for access, the secondary user faces both how to perceive the channels and how to access after perception; and because a plurality of users exist in the multi-user network, the MABP problem can be expanded and solved by extending the MABP problem to a multi-user scene.
Step 1.1: setting U secondary users in the cognitive network, wherein each secondary user has a unique identification number, and the identification number corresponding to the secondary user U is U, and the U belongs to {1, 2.. the., U }; n authorized channels are arranged in the network, a master user accesses the channels according to time slots, and the idle probability of the master user channels meets theta1＞θ2＞...＞θN(ii) a In a single time slot, the secondary user can simultaneously sense M channels, M is less than N, and at most, K sensing idle channels are accessed, and K isLess than or equal to M; for each secondary user u, there is a label in each time slot t, denoted Selu(t); according to the label, the secondary user has a set of perceived channel indices in each time slot, denoted as
According to the label index set of the channels, the secondary user selects the corresponding channel from the ordered channel set to sense; channel sensing as imperfect sensing channel, using PdAnd PfRespectively representing the detection probability and the false alarm probability of the channel;
step 1.2: the perceptual access problem of the secondary users is uniformly modeled as an MABP problem.
The perceived access of the secondary user can be divided into two processes: firstly, according to which method the channel is sensed; the second is how to select the optimal channel access among the perceived channels. For the first process, in order to consider fairness among secondary users, a reasonable perception method needs to be designed, so that the secondary users can perceive different channels with the same probability; by comprehensively considering the two processes, the problem can be uniformly modeled into an MABP problem for analysis and design of a spectrum access method.
each secondary user is simultaneously aware of all channels and has opportunistic access, in particular for time slots
And each secondary user u, according to the channel index { (l-1) M + 1: lM, sequentially sensing all channels, recording channel information in Tu(t)＝(Tu，l(t)，Tu，2(t)，...，Tu，N(t)) and Yu(t)＝(Yu，1(t)，Yu，2(t)，...，Yu，N(t)), and randomly selecting K idle channels for opportunistic access;
wherein
Direction of expressionUpper rounding function, Tu(t) and Yu(T) represents a vector of length 1 XN, Tu，i(t) represents the number of time slots of the user u perceptual channel i before time slot t, Yu，i(t) represents the number of time slots before time slot t where user u perceives channel i as free.
starting a cycle perception process, perceiving the channel by the secondary user according to a strategy, and the steps at the time slot t are as follows:
step 3.1: user u calculates all channel coefficients theta according to the expectation of sample meaniIs estimated by
And push the channel to
Obtaining a channel set after descending order arrangement
Step 3.2: in time slot t, the secondary user u updates its corresponding label
Wherein mod is an arithmetic operator and represents a remainder obtained by integer division of two numbers; as can be seen from step 3.1, as time t increases, u + t-1 changes constantly, with the mark Selu(t) also varies with time;
step 3.3: in time slot t, the secondary user u follows its label Selu(t) determining a set of perceptual channel indices at time slot t
The corresponding channel set is
The secondary user u perceives the selected channel set and updates T according to the perception resultu(t) and Yu(t) and identifying a set of channels that are perceived to be idle
At this point, the secondary user completes the channel sensing process.
And 4, the secondary user performs channel access according to the channel sensing condition and judges whether the channel access conflicts or not, and after the channel access conflicts or not, the secondary user jumps to the step 3, and the method specifically comprises the following steps:
step 4.1: if set
If not, the secondary user u selects
Middle index
Largest size
Accessing a channel; otherwise, no channel is accessed; wherein
Representation collection
The number of middle elements, min {. cndot } represents the minimum element in the set;
step 4.2: and the secondary user finishes the sensing process of the time slot t, jumps to the step 3 and starts the sensing process of the next time slot t + 1.
Analyzing the above sensing and opportunistic access processes, the scheme provided by the invention enables the channel set sensed and opportunistic accessed by the secondary users to change along with the increase of time, and the secondary users sense and access the optimal channel with the same probability.
Further, the method for performing the performance measurement of the opportunistic access method specifically includes the following steps:
when the channel information is known, the cognitive wireless network has the optimumChannel awareness and opportunistic access scheme of which the maximum gain U is obtained*(t) can be expressed as:
wherein
Set of channels, S, representing access by user u in time slot ji(j) Indicating the state of channel i in time slot j, Xi(j) Representing the state observed for channel i in time slot j,
representing the set of secondary user u perceptual channels in time slot j,
representing a set of all N primary user channels,
indicating a desire.
Compared with the situation of known channel information, the expected revenue value of the access method has certain loss when the statistical information is unknown, and can be calculated as follows:
wherein phiu(j) Indicating the access policy of user u in slot j,
the indication function is represented.
Further, the yield loss of the method provided by the invention is specifically as follows:
the yield loss brought by the method provided by the invention consists of two parts: the first part results from the secondary user not perceiving or accessing the optimal channel. In the classical MABP problem, the yield loss caused by sensing or access by a single secondary user without selecting an optimal channel satisfies o (ln t). Similarly, in a multi-user scenario, the gain loss due to sensing or access by each secondary user without selecting an optimal channel still satisfies o (ln t). The second part is derived from the collision of multiple secondary users sensing and opportunistic access to the channel. In each time slot, multiple secondary users may simultaneously perceive access to the same channel because the secondary users do not estimate the channel statistics accurately enough. In the classical MABP problem, the number of slots for which the secondary user estimates the channel statistics inaccurately satisfies o (ln t). Since the number of collisions occurring in each slot is limited, it can be concluded that the loss of revenue from collisions satisfies O (ln t). In summary, the secondary user performs the sensing and opportunistic access of the primary channel according to the method provided by the present invention, and the loss of revenue r (t) before the time slot t satisfies r (t) to o (ln t).
The multi-user frequency spectrum access method based on the multi-arm gambling machine model under the fairness principle has the following characteristics: (1) the actual scene consideration is sufficient. Most of the prior art provides a perception access strategy based on channel statistical information, and the invention considers the problems of perception and opportunity access in a multi-user cognitive network under the condition of unknown channel statistical information, thereby meeting the wide and actual scene requirements; (2) the method is specially designed for the multi-user fairness principle. Under the method provided by the invention, the secondary users sense the optimal channel set with the same probability, and the information quantity transmitted by the secondary users is the same in a long enough time; (3) the hardware constraint consideration is more comprehensive. The prior art work mostly considers the case where the secondary users perceive the same number of channels as the access channels, and assumes that the secondary users can perfectly perceive the occupancy of the channels. However, due to hardware reasons, in actual work, the secondary user may select to access a part of the optimal channels among the multiple perceived channels to save energy, and there is a certain error in perception of the channel state by the secondary user due to noise, system error and the like. The invention is based on the three problems, and the application scene is closer to the reality; (4) a multi-arm gambling machine statistical model is established, and the performance of the method is superior; under the proposed criteria of performance metric, the loss-of-revenue performance is O (ln t) when time is finite and approaches infinity (t → ∞).
Example 1
In a specific embodiment of the invention, in a multi-user cognitive wireless network, a secondary user simultaneously senses a plurality of channels in a single time slot and accesses an application scene of a part of channels, and statistical modeling is carried out on sensing and opportunistic access of the channels. By analysis, it can be known that the perceived access policy of the secondary user will have a loss of revenue with respect to time in the o (ln t) relationship, if the channel statistics are unknown. In order to make the yield loss and the spectrum access time have an o (ln t) logarithmic growth relationship, the spectrum opportunistic access method is modeled as an MABP model, and the model is analyzed and verified. By combining experimental results and theoretical analysis, the method provided by the invention can be obtained that the yield loss meets the convergence performance of O (ln t) when the finite time t and the time approach to infinity t → ∞.
In this scenario, consider a plurality of secondary users in the network, U is 2, 3, the number of primary user channels is N is 5, 7, the secondary users can access different channels, K is 1, 2. The normalized loss of revenue versus time curves for different parameters U, N, K were compared and the experimental results are shown in fig. 3. It can be seen that, when the number of secondary users and the number of channels in the cognitive network are fixed, the larger the number of user access channels is, the larger the normalized revenue loss is. This is because the larger the number of channels that the secondary user can access simultaneously, the larger the number of channels that the secondary user can access to the non-optimal channels, and therefore, the more revenue will be lost. In order to intuitively express the fairness principle, in this embodiment, N is 7, U is 3, M is 2, and K is 1, the average profit of each secondary user in a unit time slot is compared, and the experimental result is shown in fig. 4. As can be seen from the results in the figure, the average benefit in each secondary user unit time slot tends to be the same as time increases; it can be inferred that the secondary users receive the same benefit in a unit time slot as the time approaches infinity.
In summary, under the condition that channel statistical information is unknown, the method for channel sensing and opportunistic access is provided in the present invention, in view of the principle of fairness of secondary users, and for the condition that the secondary users in the multi-user cognitive wireless network do not perfectly sense multiple channels and access part of the channels. Specifically, for multi-user perception and opportunistic access, an MABP statistical model is established, and a partial perception and selective access process of a secondary user to an authorized channel is modeled; considering the fairness principle, the invention provides an effective method, which enables the channel perception set of the secondary user to change along with the increase of time, and can perceive and access the optimal channel with the same probability; analyzing the performance measurement standard of the method under the condition of unknown statistical information; theoretically, the loss of revenue can be distributed in O (ln t) when finite time t and time approach infinity t → ∞; the effectiveness of the method provided by the invention is proved through simulation verification.
Claims (1)
1. A multi-user spectrum access method based on a multi-arm gambling machine model under the fairness principle is characterized by comprising the following steps:
step 1, aiming at a multi-user cognitive wireless network, establishing a multi-user channel perception and opportunity access model based on a multi-arm gambling machine model;
step 2, initializing the perception channel parameters of the secondary user;
step 3, each secondary user performs channel perception and updates channel statistical information on line;
step 4, the secondary user accesses the channel according to the channel perception condition and judges whether the channel conflicts, and after the channel conflicts are judged, the secondary user jumps to the step 3;
the establishment of the multi-user channel perception and opportunity access model in the step 1 specifically comprises the following steps:
step 1.1, setting that U users exist in a cognitive network, each user has a unique identification number, the identification number corresponding to the user U is U, and the U belongs to {1, 2, …, U }; n authorized channels are arranged in the network, a master user accesses the channels according to time slots, and the idle probability of the master user channels meets theta1＞θ2＞…＞θN(ii) a In a single time slot, the secondary user can simultaneously sense M channels, and U.M < N, and access at most K sensing idle channelsChannel, K is less than or equal to M; the secondary user generates a label according to its own identification number in the time slot t, and the label is marked as Selu(t) determining a set of perceived channel indices, denoted as
According to the label sets of the channels, the secondary users select corresponding channels from all the sorted channel sets for perception; channel sensing is imperfect spectrum sensing, using PdAnd PfRespectively representing the detection probability and the false alarm probability of the channel;
step 1.2, uniformly modeling the perception access problem of the secondary user into an MABP problem;
initializing the secondary user perception channel parameters in the step 2 specifically as follows:
for time slot
The secondary user u follows { (t-1) M + 1: tM } sensing all channels in sequence, updating Tu(t)＝(Tu，1(t)，Tu，2(t)，...，Tu，N(t)) and Yu(t)＝(Yu，1(t)，Yu，2(t)，...，Yu，N(t)), and randomly selecting K idle channels for access;
wherein
Representing an upward rounding function, Tu(t) and Yu(T) represents a vector of length 1 XN, Tu，i(t) represents the number of time slots of the user u perceptual channel i before time slot t, Yu，i(t) represents the number of time slots before the time slot t when the user u perceives the channel i as idle;
each secondary user in step 3 performs channel sensing and updates channel statistical information online, which is as follows:
step 3.1, under the time slot t, the secondary user u calculates the idle probability theta of all channels according to the expectation of the sample mean valueiIs estimated by
And the channel is as index
Arranging in descending order to obtain channel set
Step 3.2, under time slot t, the secondary user u updates the corresponding label
Wherein mod is an arithmetic operator and represents a remainder obtained by integer division of two numbers; as shown in step 3.1, as time t increases, u + t-1 changes continuously, and the label Selu(t) also varies with time;
step 3.3, in time slot t, the secondary user u follows the label Selu(t) determining a set of perceptual channel indices at time slot t
Corresponding channel sets are
The secondary user u perceives the selected channel set and updates T according to the perception resultu(t) and Yu(t) and identifying a set of channels that are perceived to be idle
Step 4, the secondary user performs channel access according to the channel perception condition and judges whether conflict exists, specifically as follows:
step 4.1, if set
If not, the secondary user u selects the set
Middle index
Largest size
Accessing a channel; otherwise, no channel is accessed; wherein
Representation collection
The number of middle elements, min {. cndot } represents the minimum element in the set;
and 4.2, finishing the sensing and opportunistic access processes in the time slot t by the secondary user, skipping to the step 3, and starting the sensing process of the next time slot t + 1.
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