CN115412189A - Multi-channel user access method - Google Patents
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Abstract
The application discloses a multi-channel user access method, which relates to the technical field of wireless access networks and comprises the following steps: the method comprises the following steps: the base station side receives the network access requests of all the users to be accessed to the network, estimates the current channel quality of each user according to the network access request message and calculates the signal-to-noise ratio; step two: the base station judges whether the sum of the required channel number of each user to be accessed is less than the current available channel number; if yes, executing the third step; otherwise, executing the step four; step three: distributing channel resources for all users to be accessed according to the number of channels required by the users, and executing the seventh step; step four: calculating the transmission rates of all users; step five: solving the problem P1 to obtain an optimal solution; step six: selecting users which can be accessed according to the result in the step five, and distributing the required channel resources for the users; step seven: and finishing the access process. The method and the device are convenient for improving the resource utilization rate of the existing user access method and obtaining higher network throughput.
Description
Technical Field
The invention relates to the technical field of wireless access networks, in particular to a multi-channel user access method.
Background
In a radio access network, a network device is composed of a base station device and a plurality of user devices. In such a network structure, a multi-channel bonding method is required for communication. Specifically, a plurality of channels are available for users in a base station, and before a user node performs communication, the base station node needs to select users that can be accessed according to a certain strategy and allocate corresponding access channels to the user node.
Conventional access mechanisms are generally divided into contention-based access and non-contention-based access. Contention-based access means that the base station does not know any information of the user equipment, and the user needs to establish a connection relationship with the base station by sending a preamble. And the base station continuously detects the lead code information sent by the user, generates response information and sends the response information to the user. In a non-contention access mechanism, a base station needs to acquire information of a user equipment to be accessed in advance, for example, a user's requirement for resources, a user's current channel quality, and the like. Based on the user information, the users that can be accessed are selected according to a certain policy. In the contention-based access mode, the access requests of the users have the possibility of conflict, and the access success rate of the users is relatively low. In addition, the base station does not master any information of the ue, and cannot perform efficient unified planning, which results in relatively low utilization rate of radio resources.
In the existing access network scenario, channel polling allocation, load balancing access, greedy strategy access, optimal signal-to-noise ratio access and the like are mainly applied access technical means. In the polling allocation method, the base station needs to sequentially poll all channels for the user nodes to be accessed. The mode enables each user to obtain the access opportunity with the same probability, and is an access method with better fairness. However, it does not take into account the differences in channel conditions of different users. The situation that users with extremely poor channel quality occupy channel transmission and users with good channel quality fail to access easily occurs. In addition, the polling access method does not consider the difference of the demands of different users on the transmission channel resources. When the number of users to be accessed is large, the situation that users with extremely poor channel quality occupy a large number of channel resources is easy to occur, so that the resource utilization rate is reduced, and the network throughput is reduced. By applying the strategy of load balancing access, the problem of unbalanced access of each base station user is solved, and the resource utilization efficiency is improved to a certain extent. However, since it only performs equalization on the number of access users and does not consider the difference of channel conditions of different users, it cannot obtain the optimal matching relationship between the base station resources and the users. In the greedy strategy, the base station selects a user with high transmission rate for access. And in the optimal signal-to-noise ratio access, the base station selects the user with the highest signal-to-noise ratio for access. The access technology based on the greedy strategy solves the problem of low network throughput to a certain extent, but only considers the transmission rate of users and does not consider the utilization efficiency of resources, so that the situation that a certain user occupies a large amount of wireless channel resources is easily generated. The optimal signal-to-noise ratio access is used as the simplest and most efficient access mechanism at the present stage, and higher resource utilization efficiency can be obtained. But the essence is still a greedy strategy based on the signal-to-noise ratio, so that the optimal matching relationship between the base station resources and the users cannot be obtained.
Based on this, we propose a multi-channel user access method.
Disclosure of Invention
The present invention aims to overcome the above problems in the prior art, and provides a multi-channel user access method, which improves the resource utilization rate of the existing user access method and obtains higher network throughput.
In order to achieve the technical purpose and achieve the technical effect, the invention is realized by the following technical scheme:
a multi-channel user access method aims at maximizing network throughput, and describes a multi-channel user access model as follows:
x(i)∈{0,1} (3)
the optimization goal of the optimization problem P1 is to maximize the throughput of the whole network in a scheduling period; r (i) represents the user transmission rate of user i; b (i) represents the number of channels required for transmission of user i; the limiting condition (2) indicates that the number of channels occupied by all the users with successful access cannot exceed the total number N of channel resources;
the method specifically comprises the following steps:
the method comprises the following steps: the base station side receives the network access requests of all the users to be accessed to the network, estimates the current channel quality of each user according to the network access request message, and calculates the signal to noise ratio SINR i ，i＝1，2，…，L；
Step two: the base station judges whether the sum of the required channel number of each user to be accessed is less than the current available channel number; if yes, executing the third step; otherwise, executing the step four;
step three: distributing channel resources for all users to be accessed according to the number of channels required by the users, and executing the seventh step;
step four: calculating transmission rates of all users
Where Δ B is the bandwidth of each channel;
step five: solving the problem P1 to obtain an optimal solution X = (X) 1 ,x 2 ,...,x L )；
Step six: selecting users which can be accessed according to the result in the step five, and distributing the required channel resources for the users;
step seven: and finishing the access process.
Preferably, in the fifth step, the problem P1 is defined as an L-level dynamic programming problem, and the state variable of the kth stage is s k Indicating the current residual channel resource number; the decision strategy variable is x k When user k gets a transmission opportunity, there is x k =1, otherwise x k =0; the recurrence relation is embodied as:
preferably, the dynamic programming algorithm for solving the optimization problem P1 is:
preferably, a variable x (i) e {0,1} is defined to indicate whether the user i successfully accesses in one scheduling period; when the access of the user i is successful, x (i) =1, otherwise, x (i) =0.
In summary, compared with the conventional access method, the present invention has the following advantages:
firstly, the difference of user channel quality and the difference of user transmission channel resource requirements are comprehensively considered, and the resource utilization rate is high.
Secondly, the access problem is embodied in a mathematical modeling mode, the optimal solution is obtained through a mathematical method, and the highest system throughput can be realized in the same scene.
In summary, in the present invention, from the perspective of optimizing and matching channel resources in a user and a base station, an access mechanism of the user is researched. And establishing a theoretical optimization model of user access under the multi-channel condition by taking the maximum system throughput as a target. Through theoretical analysis, the method of dynamic programming is adopted to solve the problem, and a corresponding access method is designed on the basis. Theoretical analysis proves that under the same condition, the result of the access method provided by the invention is the optimal solution, and the highest system throughput can be obtained.
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FIG. 1 is a schematic diagram of a system model of the present invention;
FIG. 2 is a flow chart of an access method according to the present invention;
FIG. 3 is a graph comparing the performance of the present invention.
Detailed Description
The present invention is described in further detail below with reference to FIGS. 1-3.
The embodiment provided by the invention comprises the following steps: a multi-channel user access method mainly aims at a wireless access network and a network scene taking a base station as a center. The idea is as follows: the central node uniformly distributes the channel resources on the channel according to the requirement of each user on the resources, the load condition of the base station and the wireless channel quality of the user. Through reasonable access planning, the optimal matching of the user and the channel resource is realized, the utilization efficiency of the channel resource is further improved, and the service data transmission capability of the system is enhanced.
Consider that there are L users to be accessed in an access network, and there are N channels available for users, as shown in fig. 1. Considering the situation that the number of users is large and the radio resources are limited, not all the users to be accessed can be accessed successfully within one scheduling period. Therefore, the variable x (i) ∈ {0,1} is defined to indicate whether user i successfully accesses within one scheduling period. When the access of the user i is successful, x (i) =1, otherwise, x (i) =0. With the goal of maximizing network throughput, we describe the multi-channel user access model as follows:
x(i)∈{0,1} (3)
the optimization goal of the optimization problem P1 is to maximize the throughput of the whole network in one scheduling period. R (i) represents the user transmission rate of user i; b (i) represents the number of channels required for user i transmission. The limiting condition (2) indicates that the number of channels occupied by all the users with successful access cannot exceed the total number N of channel resources; and as can be seen from the constraint (3), the optimization problem P1 is a 0-1 integer programming problem.
Based on the above analysis, the technical scheme of the invention comprises the following steps:
the method comprises the following steps: the base station side receives the network access requests of all the users to be accessed to the network, estimates the current channel quality of each user according to the network access request message, and calculates the signal to noise ratio SINR i ，i＝1，2，…，L。
Step two: the base station judges whether the sum of the required channel number of each user to be accessed is less than the current available channel number; if yes, executing the third step; otherwise, executing step four.
Step three: and step seven is executed according to the number of channels needed by the user to distribute the channel resources for all the users to be accessed.
Step four: calculating transmission rates of all users
Where Δ B is the bandwidth of each channel.
Step five: solving the problem P1 to obtain an optimal solution X = (X) 1 ,x 2 ,...,x L )。
Step six: and according to the result in the fifth step, selecting the users which can be accessed, and allocating the required channel resources for the users.
Step seven: and finishing the access process.
The above flow is shown in fig. 2.
In the fifth step, the optimization problem P1 needs to be solved, and a dynamic programming method is considered to solve the problem. The problem P1 is defined as an L-level dynamic programming problem with the k-th stage state variable being s k Indicating the current residual channel resource number; the decision strategy variable is x k When user k gets a transmission opportunity, there is x k =1, otherwise x k =0; the recurrence relation is embodied as:
based on the above analysis, the dynamic programming algorithm for summarizing the solution problem P1 is as follows:
dynamic programming algorithm for solving optimization problem P1 by algorithm 1
In algorithm 1, the input values are the number N of available channels, the number B (i) (i =1, 2.. Said., L) of channels required for each user transmission, and the user transmission rate R (i) (i =1, 2.. Said., L) for each user; the output being a function of state V k (ii) a And an optimal solution X.
In summary, in the present invention, the access problem of the multi-channel user is modeled as an optimized problem, and is solved by a dynamic programming method to obtain an optimal user access scheme. Therefore, the invention has the advantages of high utilization rate of wireless resources, good transmission performance and the like.
The specific implementation example is as follows:
the implementation steps of the present invention are further described. And compared with the conventional method.
Example 1:
assume that in the scenario shown in fig. 1, there are L =6 users to be accessed, and the base station channel capacity N =10. Wherein, the number of channels required by the user B = [2,1,3,4,2,3]. Transmission rate of user
Since B (i) and Δ B are constant values when calculating R (i), R (i) and signal-to-noise ratio SINR i In a one-to-one correspondence. For simplicity of description, the calculated transmission rate values R = [5,2.5,6,7,4.5,5.5] are given directly]。
(1) The access method of the invention comprises the following steps:
1: the base station side receives the network access requests of all the users to be accessed to the network, estimates the current channel quality of each user according to the network access request message and calculatesSINR (Signal to noise ratio) i ，i＝1，2，…，L。
2: the base station determines whether the sum of the required channel number of each user to be accessed is less than the current available channel number, and executes step four because 2+1+3+4+2+3=15 >.
3: the transmission rates R = [5,2.5,6,7,4.5,5.5] of all users are calculated.
4: substituting L, N, B and R to obtain a problem P1, and solving by using the algorithm 1 in the invention to obtain an optimal solution X = (1, 0, 1).
5: and selecting the user 1, the user 3, the user 5 and the user 6 for access, and allocating corresponding channel resources for the users.
By adopting the method, the throughput of the whole network is 5+6+4.5+5.5=21.
(2) And accessing by adopting a greedy algorithm, and performing comparative analysis, wherein the implementation strategy of the greedy algorithm is as follows: preferentially selecting a user with high transmission rate for access, comprising the following steps:
1: the base station side receives the network access requests of all the users to be accessed to the network, estimates the current channel quality of each user according to the network access request message, and calculates the signal to noise ratio SINR i ，i＝1，2，…，L。
2: the base station judges whether the sum of the required channel number of each user to be accessed is less than the current available channel number, and a subsequent greedy algorithm flow is performed because 2+1+3+4+2+3=15 >.
3: and sorting the users in a descending order according to the signal-to-noise ratio to obtain a user index sequence S = [4,3,6,1,5,2].
4: and sequentially selecting the user 4, the user 3 and the user 6 for access, and allocating corresponding channel resources for the users.
By adopting the method, the throughput of the whole network is 6+7+5.5=18.5.
(3) Comparing by adopting an access mode of the optimal signal-to-noise ratio, wherein the strategy for realizing the access of the optimal signal-to-noise ratio is as follows: preferentially selecting a user with high transmission signal-to-noise ratio for access, comprising the following steps:
1: the base station side receives all network access requests of the users to be accessed and generates the network access requestsEstimating the current channel quality of each user according to the network access request message, and calculating to obtain the signal-to-noise ratio SINR i ，i＝1，2，…，L。
2: the base station determines whether the sum of the required channel number of each user to be accessed is smaller than the current available channel number, and performs a subsequent optimal signal-to-noise ratio access process because 2+1+3+4+2+3=15 >/n.
3: and sorting the users in a descending order according to the signal-to-noise ratio to obtain a user index sequence S = [1,2,5,3,6,4].
4: and sequentially selecting the user 1, the user 2, the user 5 and the user 3 for access, and allocating corresponding channel resources for the users.
By adopting the method, the throughput of the whole network is 5+2.5+4.5+6=18.
Compared with the traditional greedy access and optimal signal-to-noise ratio access, the access method provided by the invention has obvious advantages in throughput performance.
Example 2:
suppose that in the scenario shown in fig. 1, there are L users to be accessed, and the base station has a channel capacity N. In order to avoid loss of generality, performance simulation is performed on the access method provided by the invention under the condition of different user numbers, and comparison with the traditional access method is performed. Wherein, the number B of channels needed by the user is randomly generated in the range [1,4], and the signal-to-noise ratio SINR is randomly generated in the range [1,7 ]. The specific simulation parameters are shown in the following table:
TABLE 1 simulation parameters Table
| Simulation parameter | Simulation value |
| Base station |
10/15 |
| Number of users | 1-10 |
| Number of channels required by user B | U[1，4] |
| User signal-to-noise ratio SINR | U[1，7] |
| Number of times of simulation | 100 |
Based on the above parameters, we obtained throughput performance as shown in fig. 3, which is the average of 100 simulation results.
From the comparison analysis, it can be known that the access method provided by the invention has obvious advantages in throughput performance compared with the traditional greedy access and optimal signal-to-noise ratio access.
The above are all preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby, so: all equivalent changes made according to the structure, shape and principle of the invention are covered by the protection scope of the invention.
Claims (4)
1. A multi-channel user access method is characterized in that: with the goal of maximizing network throughput, the multi-channel user access model is described as follows:
x(i)∈{0,1} (3)
the optimization goal of the optimization problem P1 is to maximize the throughput of the whole network in a scheduling period; r (i) represents the user transmission rate of user i; b (i) represents the number of channels required by user i to transmit; the limiting condition (2) indicates that the number of channels occupied by all the users with successful access cannot exceed the total number N of channel resources;
the method specifically comprises the following steps:
the method comprises the following steps: the base station side receives the network access requests of all the users to be accessed to the network, estimates the current channel quality of each user according to the network access request message, and calculates the signal to noise ratio SINR i ，i＝1，2，…，L；
Step two: the base station judges whether the sum of the required channel number of each user to be accessed is less than the current available channel number; if yes, executing the third step; otherwise, executing the step four;
step three: distributing channel resources for all users to be accessed according to the number of channels required by the users, and executing the seventh step;
step four: calculating transmission rates of all users
Where Δ B is the bandwidth of each channel;
step five: solving the problem P1 to obtain an optimal solution X = (X) 1 ,x 2 ,...,x L )；
Step six: selecting users which can be accessed according to the result in the step five, and distributing the required channel resources for the users;
step seven: and finishing the access process.
2. The multi-channel user access method of claim 1, wherein: in the fifth step, the problem P1 is defined as an L-level dynamic programming problem, and the state variable of the kth stage is s k Indicating the current residual channel resource number; the decision strategy variable is x k When user k gets a transmission opportunity, there is x k =1, otherwise x k =0; recursion relationThe method is characterized in that:
3. the multi-channel user access method of claim 2, wherein: the dynamic programming algorithm for solving the optimization problem P1 is as follows:
(1): initialization state function V k ＝0
(2)：for k＝1：L
(3)：for s k ＝1：N
(4)：if(s k ＜B(k))
(5)：V k (s k )＝V k-1 (s k )
(6)：else
(7)：if(V k-1 (s k )＞V k-1 (s k -B(k))+R(k))
(8)：V k (s k )＝V k-1 (s k )
(9)：else
(10)：V k (s k )＝V k-1 (s k -B(k))+R(k)
(11)：end if
(12)：end if
(13):end for
(14)：end for
(15)：k＝L，sk＝N
(16)：while(k>＝1)
(17)：if(V k (s k )＝＝V k-1 (s k ))
(18)：x k ＝0
(19)：else
(20)：x k ＝1，s k ＝s k -B(k)
(21)：end if
(22)：k＝k-1
(23)：end while
(24): output V k 、X＝(x 1 ,x 2 ,...,x L )。
4. The multi-channel user access method of claim 1, wherein: defining a variable x (i) epsilon {0,1} to represent whether the user i successfully accesses in a scheduling period; when the access of the user i is successful, x (i) =1, otherwise, x (i) =0.
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