TW202121922A - Resource allocation method and data control center based on genetic algorithm - Google Patents

Abstract

The disclosure provides a resource allocation method and a data control center based on a genetic algorithm. The method includes: determining, at a t-th time point, whether a communication environment in which the plurality of secondary user devices are located is changed, wherein a plurality of transmission links exist between the secondary user devices; in response to determining that the communication environment at the t-th time point has changed, generating a candidate chromosome set corresponding to the t-th time point according to the historical candidate chromosome set; performing a multi-objective optimization algorithm on the candidate chromosome set to allocate an optimal power and an optimal band for each transmission link; controlling the secondary user device to communicate according to the optimal power and the optimal band corresponding to each transmission link.

Description

Resource allocation method and data control center based on genetic algorithm

The present invention relates to a communication resource allocation mechanism, and in particular to a resource allocation method and data control center based on genetic algorithm.

Please refer to FIG. 1, which is a schematic diagram of a conventional communication system architecture. As shown in FIG. 1, the communication system 100 includes a data control center 110, a primary user device 120, a primary base station 125, a secondary user device 130 and a secondary base station 135. In FIG. 1, the primary base station 125 (e.g., eNB) can allow the primary user device 120 (e.g., a general mobile phone) to implement communication functions based on a licensed spectrum, and the secondary base station 125 can be used for secondary users The device 130 is based on an unlicensed spectrum. Alternatively, the secondary user device 130 may also perform, for example, Bluetooth or other similar communication behaviors based on the unauthorized spectrum.

With the rise of Internet of Things (IoT) related industries in recent years, the demand for wireless transmission of IoT electronic devices has increased, which has also led to a lack of energy and spectrum resources for IoT. In order to make the use of the aforementioned resources more flexible, there is an IoT technology based on cognitive radio (cognitive radio, CR) in the prior art.

In the scenario of FIG. 1, the data control center 110 can learn which sub-channels (or frequency bands) are currently available from the data provided by the main user device 120 based on the concept of spectrum leasing, and can then use These resources are allocated to CR-based IoT devices (such as the devices in the dashed circle in Figure 1) for communication through certain resource allocation methods.

Among the related existing resource allocation methods, it can be roughly divided into the following methods: (1) Iterative calculation is used to find a balance point to solve; (2) The problem is transformed into a convex optimization problem (convex optimization problem) and related Algorithm solution. However, the above method is a single objective optimization, so it cannot solve the situation where multiple objective functions may contradict each other.

限制（

-constraint）方法。然而，此種作法所獲得之最佳解效能容易受

值所影響，故其效能並不穩定；(2) 利用多目標進化演算法求解，例如SPEA-II以及NSGA-II方法。然而，此類做法在運行過程中無法確保產生可行解，導致其收斂效能不佳。On the other hand, there are also documents discussing multi-objective optimization in the related prior art, and its practices can be divided into the following categories: (1) Convert the multi-objective optimization problem into a single-objective optimization problem, such as

limit(

-constraint) method. However, the best solution performance obtained by this approach is easily affected by

The performance is not stable due to the influence of the value; (2) Multi-objective evolutionary algorithms are used to solve the problem, such as SPEA-II and NSGA-II methods. However, such an approach cannot ensure that a feasible solution is produced during operation, resulting in poor convergence performance.

In addition, the related resource allocation method in the prior art only considers the static communication environment, so it is not suitable for the actual dynamic communication environment. Specifically, the prior art assumes that relevant system parameters (such as the number of available channels, etc.) do not change over time, but these system parameters should actually change over time. In other words, as long as the system parameters change, the prior art must recalculate to find the best solution at the moment, resulting in poor convergence efficiency.

In view of this, the present invention provides a resource allocation method and a data control center based on genetic algorithm, which can be used to solve the above technical problems.

The present invention provides a resource allocation method based on genetic algorithm, which is suitable for managing a data control center of multiple secondary user devices. The method includes: judging at the t-th time point whether a communication environment in which the multiple secondary user devices are located has changed, wherein there are multiple transmission links between the multiple secondary user devices, and t is A positive integer greater than 1; in response to determining that the communication environment at the t-th time point has changed, a candidate chromosome set corresponding to the t-th time point is generated based on at least one historical candidate chromosome set, wherein the candidate chromosome set includes a plurality of Candidate chromosomes, where each candidate chromosome includes a candidate energy and a candidate frequency band corresponding to each transmission link; a multi-objective optimization algorithm is performed on the set of candidate chromosomes to allocate an optimal energy and a maximum to each transmission link Optimal frequency band; controlling the multiple secondary user devices to communicate according to the optimal energy and optimal frequency band corresponding to each transmission link.

The invention provides a data control center that allocates resources based on genetic algorithm, which is used to manage multiple secondary user devices. The data control center includes a transceiver and a processor. The transceiver receives a plurality of data indicating a plurality of idle frequency bands from a plurality of main user devices. The processor is coupled to the receiver and is configured to: estimate, based on the plurality of data, a communication environment in which the plurality of primary user devices and the plurality of secondary user devices are located; determine the Whether the communication environment where the multiple secondary user devices are changed, wherein there are multiple transmission links between the multiple secondary user devices, and t is a positive integer greater than 1, reflecting the determination of the t-th time The communication environment of the point has changed, and a candidate chromosome set corresponding to the t-th time point is generated based on at least one historical candidate chromosome set, where the candidate chromosome set includes multiple candidate chromosomes, and each candidate chromosome includes a corresponding transmission link. Candidate energy sources and a candidate frequency band; perform a multi-objective optimization algorithm on the set of candidate chromosomes to allocate an optimal energy source and an optimal frequency band to each transmission link; control the multiple secondary user devices according to each transmission Link the corresponding best energy and best frequency band for communication.

In order to make the above-mentioned features and advantages of the present invention more comprehensible, the following specific embodiments are described in detail in conjunction with the accompanying drawings.

及資料流集合

。基於可用頻譜集合M(t)、傳輸鏈結集合

及資料流集合

，資料控制中心210可執行本發明提出的基於基因演算法的資源分配方法，以對次要用戶裝置230進行資源分配。在本發明的實施例中，資料控制中心210例如可用於對次要用戶裝置230分配能源及頻段等資源，藉以讓次要用戶裝置230可使用所分配的能源而在所分配的頻段上進行傳輸。Please refer to FIG. 2, which is a schematic diagram of a system according to an embodiment of the present invention. Roughly speaking, in this embodiment, at the t-th time point (t is a positive integer greater than or equal to 1), the main user device 220 can provide the data control center 210 with the measured available spectrum set M(t) . In an embodiment, the available spectrum set M(t) may include, for example, one or more idle sub-channels or frequency bands, and the total number thereof may be referred to as the number of available channels, but it may not be limited thereto. The secondary user device 230 (for example, a CR device) can be used to provide a transmission link set to the data control center 210

And data stream collection

. Based on the available spectrum set M(t), transmission link set

And data stream collection

, The data control center 210 can execute the resource allocation method based on the genetic algorithm proposed in the present invention to allocate resources to the secondary user device 230. In the embodiment of the present invention, the data control center 210 can be used, for example, to allocate resources such as energy and frequency bands to the secondary user device 230, so that the secondary user device 230 can use the allocated energy to transmit on the allocated frequency band. .

Please refer to FIG. 3, which is a schematic diagram of energy and spectrum allocation among secondary user devices according to an embodiment of the present invention. In the scenario shown in FIG. 3, it is assumed that there are 10 secondary user devices, which respectively correspond to nodes 1-10, and can communicate with each other after energy and frequency bands are allocated by the data control center 210 of the present invention.

代表由節點i傳輸信號至節點j所使用的能源，而

則代表由節點i傳輸信號至節點j所使用的頻段。此外，

代表傳輸資料流，而由圖3可看出，其中存在傳輸資料流

~

。基此，節點1~10可將以上資訊作為圖1中的傳輸鏈結集合

及資料流集合

而提供至資料控制中心210，但本發明可不限於此。另外，為便於說明，以下將節點i及節點j之間的傳輸鏈結以

代稱。In this embodiment,

Represents the energy used by node i to transmit signals to node j, and

It represents the frequency band used by node i to transmit signals to node j. In addition,

Represents the transmission data stream, and it can be seen from Figure 3 that there is a transmission data stream

~

. Based on this, nodes 1~10 can use the above information as the collection of transmission links in Figure 1.

And data stream collection

It is provided to the data control center 210, but the present invention is not limited to this. In addition, for the convenience of explanation, the transmission link between node i and node j is linked to

Pronoun.

的

及

。之後，本發明的方法可再對此染色體集合進行本發明提出的多目標最佳化演算法，以求得各傳輸鏈結

所對應的最佳資源分配解，亦即最佳能源及最佳頻段，藉以讓相應的節點（即，次要用戶裝置）可據以進行傳輸。Generally speaking, at each time point under consideration, the method of the present invention may first generate a chromosome set through a certain initialization operation, which may include multiple chromosomes, and each chromosome may include a link corresponding to each transmission link.

of

and

. After that, the method of the present invention can perform the multi-objective optimization algorithm proposed by the present invention on this chromosome set to obtain each transmission link

The corresponding best resource allocation solution, that is, the best energy and the best frequency band, allows the corresponding node (ie, the secondary user device) to transmit accordingly.

In the embodiment of the present invention, since the amount of historical data and communication environment corresponding to each time point may be different, the initialization operations related to each time point are also different, so that the generated chromosome set also has different patterns. The difference. Nevertheless, the same multi-objective optimization algorithm is used at each time point, and the details of the multi-objective optimization algorithm will be explained later.

對應的初始能源及初始頻段。之後，資料控制中心210可對初始染色體集合執行多目標最佳化演算法，以對各傳輸鏈結

分配初始最佳能源及初始最佳頻段。接著，資料控制中心210可控制次要用戶裝置依據各傳輸鏈結

對應的初始最佳能源及初始最佳頻段進行通訊。In the first embodiment, at the first time point (which can be understood as t equals 1), since there is no historical data, it is impossible to determine where the secondary user device (such as nodes 1~10 in Figure 2) is located. Whether the communication environment of the chromosome changes, the data control center 210 can randomly generate an initial chromosome set, where the initial chromosome set includes a plurality of randomly generated initial chromosomes, and each initial chromosome includes each transmission link

The corresponding initial energy and initial frequency band. After that, the data control center 210 can perform a multi-objective optimization algorithm on the initial set of chromosomes, so as to perform a multi-objective optimization algorithm on each transmission link.

Allocate the initial best energy and the initial best frequency band. Then, the data control center 210 can control the secondary user device according to each transmission link

Corresponding to the initial optimal energy and initial optimal frequency band for communication.

In order to facilitate the description of the details of the multi-objective optimization algorithm performed on the initial chromosome set at the first time point, the following description is supplemented with FIG. 4.

個迭代操作（

為一正整數）。Please refer to FIG. 4, which is a schematic diagram of the application scenario of the multi-objective optimization algorithm according to the first embodiment of the present invention. In this embodiment, the multi-objective optimization algorithm may include

Iterative operations (

Is a positive integer).

可包括多個初始染色體

~

，且各初始染色體

~

可包括對應於各傳輸鏈結

的初始能源及初始頻段。First of all, it can be seen from Figure 4 that the randomly generated initial set of chromosomes

Can include multiple initial chromosomes

~

, And each initial chromosome

~

Can include corresponding to each transmission link

The initial energy and initial frequency band.

為例，其可包括對應於傳輸鏈結

至

的初始頻段

~

及初始能源

至

，而初始頻段

~

及初始能源

至

個別皆為隨機產生。在一實施例中，各初始頻段例如是介於0及1之間的數值，而各初始能源例如是介於能源下限值（以

表示）及能源上限值（以

表示）之間的數值。基此，本領域具通常知識者應可理解其他初始染色體的結構所代表的意義，於此不另贅述。Initial chromosome

For example, it can include links corresponding to transmission links

to

Initial frequency band

~

And initial energy

to

, And the initial frequency band

~

And initial energy

to

Individuals are randomly generated. In one embodiment, each initial frequency band is, for example, a value between 0 and 1, and each initial energy is, for example, a lower limit of energy (in order to

Expressed) and the upper limit of energy (in

Indicates the value between). Based on this, those with ordinary knowledge in the field should be able to understand the meaning represented by the structure of other initial chromosomes, so I will not repeat them here.

In addition, in the embodiment of the present invention, the designer can set the initial number of chromosomes in the initial chromosome set to the required preset number according to requirements. Taking Figure 4 as an example, it is assumed that the initial chromosome set includes a total of 50 (ie, the preset number) initial chromosomes. In addition, for ease of understanding, the present invention assumes that the preset number of chromosomes in all mentioned sets is 50, but it is not used to limit the possible embodiments of the present invention.

）迭代操作中，資料控制中心210可對特定染色體集合採用比較選取法（tournament selection），以產生第一集合

。在不同的實施例中，若k為1，則上述特定染色體集合為初始染色體集合

，而若k不為1，則上述特定染色體集合可為第k-1個迭代操作所產生的結果，之後將作進一步說明。In this embodiment, in the kth (

) In the iterative operation, the data control center 210 may use a comparative selection method (tournament selection) on a specific chromosome set to generate the first set

. In different embodiments, if k is 1, the above-mentioned specific chromosome set is the initial chromosome set

, And if k is not 1, the above-mentioned specific chromosome set can be the result of the k-1th iterative operation, which will be further explained later.

包括多個第一染色體

~

。並且，各第一染色體

~

可包括對應於各傳輸鏈結

的第一能源及第一頻段。For ease of understanding, the details of the first (that is, k is 1) iterative operation will be described below. As shown in Figure 4, the first set

Include multiple first chromosomes

~

. And, each first chromosome

~

Can include corresponding to each transmission link

The first energy source and the first frequency band.

為例，其可包括對應於傳輸鏈結

至

的第一頻段

~

及第一能源

至

。基此，本領域具通常知識者應可理解其他第一染色體的結構所代表的意義，於此不另贅述。The first chromosome

For example, it can include links corresponding to transmission links

to

The first band

~

And first energy

to

. Based on this, a person with ordinary knowledge in the field should understand the meaning represented by the structure of other first chromosomes, which will not be repeated here.

~

係基於比較選取法而產生，以下針對比較選取法作進一步說明。在一實施例中，在取得初始染色體集合

作為上述特定染色體集合之後，資料控制中心210可依序執行以下步驟：(a)將第一集合

初始化為空集合；(b)隨機取出初始染色體集合

中的初始染色體

~

的其中之二者作為第一比較對象及第二比較對象；(c)將第一比較對象及第二比較對象的其中之一者加入第一集合

，以作為第一染色體之一；(d)重複步驟(b)及(c)，直至第一集合

中的第一染色體的數量達到預設數量（例如50）。As mentioned above, each first chromosome

~

It is based on the comparative selection method. The following is a further explanation for the comparative selection method. In one embodiment, after obtaining the initial set of chromosomes

After the above-mentioned specific chromosome set is set, the data control center 210 can sequentially perform the following steps: (a) Set the first set

Initialize to an empty set; (b) Take out the initial set of chromosomes randomly

Initial chromosome

~

Two of them are regarded as the first comparison object and the second comparison object; (c) one of the first comparison object and the second comparison object is added to the first set

, As one of the first chromosomes; (d) Repeat steps (b) and (c) until the first set

The number of first chromosomes in reaches the preset number (for example, 50).

，反之則可將第二比較對象加入第一集合

。In one embodiment, in the above step (c), the data control center 210 may determine the first crowded distance of the first comparison object and the second crowded distance of the second comparison object, where the first crowded distance is related to the first crowded distance. The energy usage rate, channel usage fairness, and spectrum usage rate of the comparison object, and the second congestion distance is related to the energy usage rate, channel usage fairness, and spectrum usage rate of the second comparison object. Afterwards, in response to determining that the first crowded distance is greater than the second crowded distance, the data control center 210 may add the first comparison object to the first set

, Otherwise you can add the second comparison object to the first set

.

，則第一比較對象的第一擁擠距離可表徵為：

，其中

為第一比較對象在初始染色體集合

中的前一個初始染色體，而

為第一比較對象在初始染色體集合

中的次一個初始染色體。並且，

、

、

個別為對應於能源使用率、通道使用公平性及頻譜使用率的多個參數，並可個別表徵如下：

；

；

； 其中，

為能源使用率運算子，

為通道使用公平性運算子，

為頻譜使用率運算子。In one embodiment, it is assumed that the first comparison object can be broadly characterized as

, Then the first crowded distance of the first comparison object can be characterized as:

,among them

The initial chromosome set for the first comparison object

The previous initial chromosome in

The initial chromosome set for the first comparison object

The next initial chromosome in. and,

,

,

Individually are multiple parameters corresponding to energy usage rate, channel usage fairness and spectrum usage rate, and can be individually characterized as follows:

；

；

; among them,

Is the energy usage rate operator,

Use fairness operators for the channel,

It is the spectrum utilization rate operator.

即為

對應的能源使用率，

為

對應的通道使用公平性，

為

對應的頻譜使用率。並且，

、

及

可分別計算如下：

；

；

； 其中

為傳輸鏈結

對應的傳輸速率，

為各傳輸鏈結

的平均傳輸速率，

為傳輸鏈結總數，

為傳輸鏈結所佔用的頻譜總數。In one embodiment,

That is

The corresponding energy usage rate,

for

The fairness of the corresponding channel usage,

for

Corresponding spectrum usage rate. and,

,

and

It can be calculated as follows:

；

；

; among them

Transmission link

Corresponding transmission rate,

For each transmission link

Average transmission rate,

Is the total number of transmission links,

It is the total number of spectrum occupied by the transmission link.

或

（即，最首或最末的初始染色體），則其相應的第一（或第二）擁擠距離可定義為無限大，但本發明可不限於此。Similarly, the second congestion distance of the second comparison object can also be obtained based on the above teachings, which will not be repeated here. In addition, if the first (or second) comparison object is the initial chromosome

or

(Ie, the first or last initial chromosome), the corresponding first (or second) crowding distance can be defined as infinite, but the present invention may not be limited to this.

中的第一染色體

~

之後，資料控制中心210可對第一集合

重複執行交叉（crossover）機制或變異（mutation）機制，以產生第二集合

，其中第二集合

可包括多個第二染色體

~

，且各第二染色體

~

包括對應於各傳輸鏈結

的第二能源及第二頻段。Obtain the first set according to the above teaching

The first chromosome in

~

After that, the data control center 210 can check the first set

Repeat the crossover mechanism or mutation mechanism to generate the second set

, Of which the second set

Can include multiple second chromosomes

~

, And each second chromosome

~

Including corresponding to each transmission link

The second energy and second frequency band.

為例，其可包括對應於傳輸鏈結

至

的第二頻段

~

及第二能源

至

。基此，本領域具通常知識者應可理解其他第二染色體的結構所代表的意義，於此不另贅述。Second chromosome

For example, it can include links corresponding to transmission links

to

Second band

~

And second energy

to

. Based on this, a person with ordinary knowledge in the field should understand the meaning represented by the structure of other second chromosomes, which will not be repeated here.

~

係基於交叉機制或變異機制而產生，以下針對交叉機制及變異機制作進一步說明。As mentioned above, each second chromosome

~

It is based on the crossover mechanism or mutation mechanism. The following is a further description of the crossover mechanism and mutation mechanism.

~

的其中之二作為第一成員染色體及第二成員染色體。之後，資料控制中心210可基於第一成員染色體及第二成員染色體產生第三成員染色體，並將第三成員作為第二染色體之一而新增至第二集合

。In the crossover mechanism, the data control center 210 can randomly obtain the first chromosome

~

Two of them are the first member chromosome and the second member chromosome. After that, the data control center 210 can generate a third member chromosome based on the first member chromosome and the second member chromosome, and add the third member as one of the second chromosomes to the second set

.

的第二能源可表徵為：

，其中

為第一成員染色體中對應於傳輸鏈結

的第一能源，

為第二成員染色體中對應於傳輸鏈結

的第一能源，

為一隨機變數，

為能源下限值。In one embodiment, the third member chromosome corresponds to the transmission link

The second energy can be characterized as:

,among them

Is the first member of the chromosome corresponding to the transmission link

The first energy,

Is the second member of the chromosome corresponding to the transmission link

The first energy,

Is a random variable,

It is the lower limit of energy.

的第二頻段表徵為

，且其係依據一隨機二元值而定。在一實施例中，若此隨機二元值為第一邏輯值（例如0），則

經定義為

，而若隨機二元值為第二邏輯值（例如1），則

經定義為

，其中

為第一成員染色體中對應於傳輸鏈結

的第一頻段，

為第二成員染色體中對應於傳輸鏈結

的第一頻段。簡言之，若隨機二元值為第一邏輯值，則

被設定為

，而若隨機二元值為第二邏輯值，則

被設定為

。In addition, the third member chromosome corresponds to the transmission link

The second frequency band is characterized as

, And it is based on a random binary value. In one embodiment, if the random binary value is the first logical value (for example, 0), then

Is defined as

, And if the random binary value is the second logical value (for example, 1), then

Is defined as

,among them

Is the first member of the chromosome corresponding to the transmission link

The first frequency band,

Is the second member of the chromosome corresponding to the transmission link

The first frequency band. In short, if the random binary value is the first logical value, then

Is set to

, And if the random binary value is the second logical value, then

Is set to

.

~

中的第四成員染色體，並隨機產生第五成員染色體。之後，資料控制中心210可基於第四成員染色體及第五成員染色體產生第六成員染色體，並將第六成員染色體作為第二染色體之一而新增至第二集合

。In addition, in the mutation mechanism, the data control center 210 can randomly obtain the first chromosome

~

The fourth member chromosome in, and the fifth member chromosome is randomly generated. After that, the data control center 210 can generate a sixth member chromosome based on the fourth member chromosome and the fifth member chromosome, and add the sixth member chromosome as one of the second chromosomes to the second set

.

的第二能源可表徵為：

，其中

為第四成員染色體中對應於傳輸鏈結

的第一能源，

為第五成員染色體中對應於傳輸鏈結

的第一能源，In one embodiment, the sixth member chromosome corresponds to the transmission link

The second energy can be characterized as:

,among them

Is the fourth member of the chromosome corresponding to the transmission link

The first energy,

Corresponding to the transmission link in the fifth member chromosome

The first energy,

個別的第二頻段為第四成員染色體中對應於前述傳輸鏈結

個別的第一頻段的混洗（shuffle）版本。In addition, the sixth member chromosome corresponds to multiple transmission links

The individual second frequency band corresponds to the aforementioned transmission link in the fourth member chromosome

Individual shuffle version of the first band.

的第一頻段

~

，且其個別對應的通道如圖5所示。在此情況下，資料控制中心210可從第一頻段

~

中隨機取出

個進行混洗，其中|

|為傳輸鏈結

的總數（即，9），

為地板函數。因此，資料控制中心210可從第一頻段

~

取出4個進行混洗，藉以產生第六成員染色體520中對應於各傳輸鏈結

的第二頻段。Please refer to FIG. 5, which is a schematic diagram of generating a shuffled version according to the first embodiment of the present invention. In this embodiment, it is assumed that the fourth member chromosome 510 has 9 transmission links

The first band

~

, And the corresponding channels are shown in Figure 5. In this case, the data control center 210 can use the first frequency band

~

Randomly taken out

Are shuffled, where |

|For the transmission link

The total number of (ie, 9),

Is the floor function. Therefore, the data control center 210 can use the first frequency band

~

Take out 4 and shuffle, so as to generate the sixth member chromosome 520 corresponding to each transmission link

The second frequency band.

執行上述交叉機制或變異機制，直至第二集合

中的第二染色體的總數達到預設數量（例如50），但本發明可不限於此。In one embodiment, the data control center 210 can repeat the first set

Perform the above crossover mechanism or mutation mechanism until the second set

The total number of second chromosomes in the chromosome reaches a preset number (for example, 50), but the present invention may not be limited to this.

（其包括第二染色體

~

）之後，資料控制中心210可依以下教示調整其中的一部分。Get the second set

(It includes the second chromosome

~

) Afterwards, the data control center 210 can adjust some of them according to the following teaching.

表示）適應性地調整第二集合

中的各第二染色體

~

。具體而言，資料控制中心210可取得第二染色體

~

的其中之一作為第一參考染色體，其中第一參考染色體包括對應於各傳輸鏈結

的多個第一參考能源及多個第一參考頻段。之後，資料控制中心210可計算第一參考染色體中的各第一參考頻段的傳輸品質（例如訊號雜訊干擾比（signal-to-interference-plus-noise ratio，SINR）。In one embodiment, the data control center 210 may limit the transmission quality based on

Means) adaptively adjust the second set

Each second chromosome

~

. Specifically, the data control center 210 can obtain the second chromosome

~

As the first reference chromosome, wherein the first reference chromosome includes the link corresponding to each transmission link

Multiple first reference energy sources and multiple first reference frequency bands. After that, the data control center 210 may calculate the transmission quality (for example, the signal-to-interference-plus-noise ratio (SINR) of each first reference frequency band in the first reference chromosome).

的第一參考頻段的傳輸品質可表徵如下：

，其中

為傳輸鏈結

對應的通道衰減值，

為雜訊，而

為傳輸鏈結

所遭遇的干擾。In one embodiment, corresponding to the transmission link

The transmission quality of the first reference frequency band can be characterized as follows:

,among them

Transmission link

Corresponding channel attenuation value,

For noise, and

Transmission link

The interference encountered.

。若是，則資料控制中心210可不調整第一參考染色體。After that, the data control center 210 can determine whether each of the first reference frequency bands in the first reference chromosome meets the transmission quality restriction. That is, the data control center 210 can determine whether the SINR of each first reference frequency band in the first reference chromosome is higher than

. If so, the data control center 210 may not adjust the first reference chromosome.

On the other hand, if any one of the first reference frequency bands in the first reference chromosome does not meet the transmission quality restriction, the data control center 210 can replace that one of the first reference frequency bands with another frequency band to adjust the first reference frequency band. The chromosome, where another frequency band has a lower load than that of the first reference frequency band.

~

，而其中共有4個頻段對應於通道1。在圖6中，假設頻段

未滿足傳輸品質限制，則資料控制中心210可相應地以另一頻段取代頻段

。在本實施例中，由於通道3僅對應於2個頻段，負載量較小，故資料控制中心210可將頻段

由對應於通道1改為對應於通道3。藉此，可產生調整後的第一參考染色體610a。Please refer to FIG. 6, which is a schematic diagram of adjusting the first reference chromosome according to the first embodiment of the present invention. In this embodiment, it is assumed that the first reference chromosome 610 includes the 9 frequency bands shown

~

, And there are 4 frequency bands corresponding to channel 1. In Figure 6, assuming the frequency band

If the transmission quality restriction is not met, the data control center 210 can replace the frequency band with another frequency band accordingly

. In this embodiment, since channel 3 only corresponds to 2 frequency bands and the load is small, the data control center 210 can change the frequency bands

Change from corresponding to channel 1 to corresponding to channel 3. In this way, the adjusted first reference chromosome 610a can be generated.

。Then, the data control center 210 can determine whether each of the first reference frequency bands in the adjusted first reference chromosome 610a meets the transmission quality restriction. If yes, the data control center 210 can use the adjusted first reference chromosome 610a as one of the adjusted second chromosomes and keep it in the second set

.

~

的其中之另一取代第一參考染色體610a。In another embodiment, if any one of the first reference frequency bands in the adjusted first reference chromosome 610a still does not meet the transmission quality restriction, the data control center 210 can use the second chromosome

~

The other of them replaces the first reference chromosome 610a.

In this embodiment, it is assumed that the first reference chromosome 610a is replaced with the first reference chromosome 620. After that, the data control center 210 may swap the first specific part of the first reference frequency band in the first reference chromosome 620 and the second specific part of the first reference frequency band one-to-one to adjust the first reference chromosome 620, where The first specific part corresponds to the first channel, the second specific part corresponds to the second channel, and the first specific part and the second specific part have the same number of channels.

中。In FIG. 6, the first specific part of the first reference chromosome 620 corresponds to channel 4 (the number of channels is 2), and the second specific part, for example, all corresponds to channel 6 (the number of channels is also 2). In this case, the data control center 210 can adjust the first specific part and the second specific part one-to-one to generate the adjusted first reference chromosome 620a. After that, the data control center 210 can use the adjusted first reference chromosome 620a as one of the adjusted second chromosomes and keep it in the second set

in.

（其包括第一染色體

~

）及調整後的第二集合

（其包括第二染色體

~

）之後，資料控制中心210可依以下教示淘汰其中的一部分，以產生對應於第1個（即，k為1）迭代操作的第三集合

。第三集合

包括多個第三染色體

~

，而各第三染色體

~

包括對應於各傳輸鏈結

的第三能源及第三頻段，如圖4所示。In one embodiment, after obtaining the first set

(It includes the first chromosome

~

) And the adjusted second set

(It includes the second chromosome

~

) Afterwards, the data control center 210 can eliminate some of them according to the following teaching to generate a third set corresponding to the first (ie, k is 1) iterative operation

. Third set

Including multiple third chromosomes

~

, And each third chromosome

~

Including corresponding to each transmission link

The third energy source and the third frequency band are shown in Figure 4.

為例，其可包括對應於傳輸鏈結

至

的第三頻段

~

及第三能源

至

。基此，本領域具通常知識者應可理解其他第三染色體的結構所代表的意義，於此不另贅述。Third chromosome

For example, it can include links corresponding to transmission links

to

Third frequency band

~

And third energy

to

. Based on this, those with ordinary knowledge in the field should be able to understand the meaning represented by the structure of other third chromosomes, which will not be repeated here.

~

及第二染色體

~

中的支配（dominated）染色體，並淘汰支配染色體。在不同的實施例中，資料控制中心210例如可基於一般取得支配解的方式來找出上述支配染色體，其細節於此不另贅述。In one embodiment, the elimination mechanism implemented by the data control center 210 is as follows. First, the data control center 210 can obtain the first chromosome

~

And the second chromosome

~

(Dominated) chromosomes in and eliminate the dominated chromosomes. In different embodiments, the data control center 210 can, for example, find the above-mentioned dominating chromosomes based on a general method of obtaining dominance solutions, and the details are not repeated here.

中的第三染色體。Then, the data control center 210 can determine whether the total number of eliminated first chromosomes and second chromosomes exceeds a preset number (for example, 50). If not, the data control center 210 can use the first chromosome and the second chromosome as the third set

The third chromosome in.

中的第三染色體

~

。On the other hand, if the total number of the eliminated first chromosome and second chromosome exceeds the preset number, the data control center 210 can use an archive update method to eliminate the first chromosome and the second chromosome with lower congestion. At least one of the distances, until the total number of remaining first chromosomes and second chromosomes does not exceed the preset number. In this embodiment, the manner of calculating the congestion distance can refer to the description in the previous embodiment, which will not be repeated here. After that, the data control center 210 can use the remaining first and second chromosomes as the third set

The third chromosome

~

.

而產生對應於多目標最佳化演算法中的第1個迭代操作的第三集合

。Based on the above teachings, those with ordinary knowledge in the field should be able to understand how the data control center 210 is based on the initial chromosome set at the first time point (ie, t is equal to 1)

And generate the third set corresponding to the first iterative operation in the multi-objective optimization algorithm

.

個迭代操作，因此在第k個（

）迭代操作時，資料控制中心210可重複執行以上教示的內容，藉以產生對應於第k個迭代操作的第三集合

。As mentioned earlier, the multi-objective optimization algorithm of the present invention includes

Iterative operation, so in the kth (

) During an iterative operation, the data control center 210 can repeatedly execute the content taught above, thereby generating a third set corresponding to the k-th iterative operation

.

作為所考慮的特定染色體集合。之後，資料控制中心210即可基於此特定染色體集合依序執行比較選取法、交叉機制、變異機制、調整及淘汰機制等，以產生對應於第k個迭代操作的第三集合

。基此，在到達迭代次數上限（即，

）時，所對應的第三集合可表徵為

。Specifically, at the kth time point, the data control center 210 may obtain the third set corresponding to the k-1th time point

As the specific set of chromosomes under consideration. After that, the data control center 210 can sequentially execute the comparison selection method, the crossover mechanism, the mutation mechanism, the adjustment and elimination mechanism, etc. based on the specific chromosome set to generate the third set corresponding to the k-th iterative operation.

. Based on this, after reaching the upper limit of the number of iterations (ie,

), the corresponding third set can be characterized as

.

之後，資料控制中心210可基於多個目標函數而以最佳選取（knee selection）法從

找出對應於第1個時間點的最佳初始染色體

。In one embodiment, in the first time point

After that, the data control center 210 can use the best selection (knee selection) method based on multiple objective functions to select

Find the best initial chromosome corresponding to the first time point

.

個迭代操作對應的第三集合

的第三染色體估計關聯於能源使用率目標函數、通道使用公平性目標函數及頻譜使用率目標函數的一最高能源使用率、一最佳通道使用公平性及一最高頻譜使用率。上述能源使用率目標函數、通道使用公平性目標函數及頻譜使用率目標函數可分別表徵如下：

；

；

， 受限於（subject to）：

；

。In one embodiment, the above-mentioned optimal selection method may include the following steps, for example. First, the data control center 210 can be based on the

The third set corresponding to one iterative operation

The third chromosome estimate of chromosome is related to a highest energy usage rate, a best channel usage fairness and a highest spectrum usage rate of the energy usage rate objective function, the channel usage fairness objective function, and the spectrum usage rate objective function. The above-mentioned energy utilization rate objective function, channel utilization fairness objective function, and spectrum utilization rate objective function can be characterized as follows:

；

；

, Subject to:

；

.

個迭代操作對應的第三集合

的第三染色體中找出最佳初始染色體

，其中最佳初始染色體

具有一最低參考差值。所述最低參考差值表徵為一第一差值、一第二差值及一第三差值的總和。上述第一差值為最佳初始染色體

對應的一能源使用率與最高能源使用率之間的差值，第二差值為最佳初始染色體

對應的一通道使用公平性與最佳通道使用公平性之間的差值，而第三差值為最佳初始染色體

對應的一頻譜使用率與最高頻譜使用率之間的差值。After that, the data control center 210 can be based on the highest energy usage rate, the best channel usage fairness, and the highest spectrum usage rate in the first

The third set corresponding to one iterative operation

Find the best initial chromosome in the third chromosome

, Of which the best initial chromosome

Has a lowest reference difference. The lowest reference difference is characterized as the sum of a first difference, a second difference, and a third difference. The first difference above is the best initial chromosome

Corresponding to the difference between the first energy usage rate and the highest energy usage rate, the second difference is the best initial chromosome

Corresponding to the difference between the fairness of the first channel and the fairness of the best channel, and the third difference is the best initial chromosome

Corresponding to the difference between a spectrum usage rate and the highest spectrum usage rate.

可表徵如下式：

=

，其中

、

及

分別表徵如下：

；

；

。In one embodiment, the optimal initial chromosome

It can be characterized as follows:

=

,among them

,

and

They are characterized as follows:

；

；

.

之後，資料控制中心210即可依據最佳初始染色體

中各傳輸鏈結

的初始能源及初始頻段設定各傳輸鏈結

的最佳能源及最佳頻段。The best initial chromosome

After that, the data control center 210 can use the best initial chromosome

Transmission links in

The initial energy and initial frequency band are set for each transmission link

The best energy and best frequency band.

的內容如圖4所示，則對於傳輸鏈結

而言，資料控制中心210可將傳輸鏈結

的最佳能源及最佳頻段分別設定為最佳初始染色體

中對應於傳輸鏈結

的初始能源

及初始頻段

。另外，對於傳輸鏈結

而言，資料控制中心210可將傳輸鏈結

的最佳能源及最佳頻段分別設定為最佳初始染色體

中對應於傳輸鏈結

的初始能源

及初始頻段

。Take Figure 4 as an example, assuming the best initial chromosome

The content of is shown in Figure 4, then for the transmission link

In other words, the data control center 210 can link the transmission

The best energy and the best frequency band are respectively set as the best initial chromosomes

Corresponds to the transmission link

Initial energy

And initial frequency band

. In addition, for the transmission link

In other words, the data control center 210 can link the transmission

The best energy and the best frequency band are respectively set as the best initial chromosomes

Corresponds to the transmission link

Initial energy

And initial frequency band

.

In this way, each secondary user device (such as nodes 1 to 10 in Figure 2) can communicate with the best energy usage, channel usage fairness, and spectrum usage at the first time point.

稱為最佳候選染色體。In the second embodiment, at other t-th time points (t in the second embodiment is a positive integer greater than 1), since there is historical data at the previous time point, it is also possible to determine the secondary user device (For example, nodes 1~10 in Fig. 2) Whether the communication environment is changed, so the present invention can adopt the initialization process different from the first embodiment to generate a set of chromosomes that can be used for multi-objective optimization algorithm ( Hereinafter referred to as the candidate chromosome set). In addition, to create a separation from the operation at the first time point, in the second embodiment,

Called the best candidate chromosome.

Please refer to FIG. 7, which is a flowchart of a resource allocation method based on a genetic algorithm according to a second embodiment of the present invention, which can be executed by the data control center 210 in FIG. 2.

First, in step S710, the data control center 210 may determine whether the communication environment of the secondary user device (for example, nodes 1-10 in FIG. 2) is changed at the t-th time point. In one embodiment, the data control center 210 may obtain the first available channel number corresponding to the communication environment at the t-th time point, and obtain the second available channel corresponding to the communication environment at the t-1 time point Quantity. After that, the data control center 210 can determine whether the first available channel number is the same as the second available channel number. If so, the data control center 210 can determine that the communication environment at the t-th time point has not changed, otherwise, it can determine that the communication environment at the t-th time point has changed. In short, as long as the number of available channels at the t-th time point is different from the number of available channels at the t-1th time point, the data control center 210 determines that the communication environment where the secondary user device is located has changed.

分配的歷史最佳能源及歷史最佳頻段，並據以設定各傳輸鏈結

的最佳能源及最佳頻段。簡言之，資料控制中心210可直接沿用第t-1個時間點的資源分配結果。亦即，資料控制中心210可將對應於第t個時間點的最佳候選染色體

設定為對應於第t-1個時間點的最佳候選染色體

，並將對應於第t個時間點的候選染色體集合

設定為

（即，將

的內容全數複製至候選染色體集合

中）。In an embodiment, if the communication environment at the t-th time point has not changed, the data control center 210 can obtain the previous data transfer link at the t-1 time point.

The best historical energy and the best historical frequency bands allocated, and the transmission links are set accordingly

The best energy and best frequency band. In short, the data control center 210 can directly use the resource allocation result at the t-1 time point. That is, the data control center 210 can assign the best candidate chromosome corresponding to the t-th time point

Set as the best candidate chromosome corresponding to the t-1 time point

, And set the candidate chromosomes corresponding to the t-th time point

set as

(I.e. will

All the contents of is copied to the set of candidate chromosomes

in).

，其中候選染色體集合

可包括多個候選染色體

~

。On the other hand, in step S720, in response to determining that the communication environment at the t-th time point has changed, the data control center 210 may generate a candidate chromosome set corresponding to the t-th time point based on the historical candidate chromosome set.

, Where the set of candidate chromosomes

Can include multiple candidate chromosomes

~

.

。在此情況下，資料控制中心210可將對應於第t個時間點的候選染色體集合

初始化為空集合。In an embodiment, the aforementioned set of historical candidate chromosomes includes a first set of historical candidate chromosomes corresponding to the t-1th time point

. In this case, the data control center 210 can set the candidate chromosomes corresponding to the t-th time point

Initialize to an empty collection.

，反之則可理解為歷史資料已足夠，故可採用預測方式建構候選染色體集合

。After that, the data control center 210 can determine whether t is greater than T, where T is a predetermined number of time points (for example, 10), and the concept can be understood as judging whether there is sufficient historical data at present. If not, it means that the historical data is not enough, so a semi-random method can be used to construct a set of candidate chromosomes

, On the contrary, it can be understood that the historical data is sufficient, so the set of candidate chromosomes can be constructed by the predictive method

.

。具體而言，資料控制中心210可取得對應於所述第t-1個時間點的第一歷史候選染色體集合

，其中第一歷史候選染色體集合

包括多個第一歷史候選染色體。之後，資料控制中心210可將第一歷史候選染色體中的一部分（例如一半）複製至候選染色體集合

中，以作為候選染色體的第一部分。另外，資料控制中心210還可隨機產生候選染色體的第二部分，以與候選染色體的第一部分協同建構對應於第t個時間點的候選染色體集合

。In one embodiment, if t is not greater than T, the data control center 210 can perform the above-mentioned semi-random method to construct a set of candidate chromosomes

. Specifically, the data control center 210 may obtain the first historical candidate chromosome set corresponding to the t-1 time point

, Where the first historical candidate chromosome set

Including multiple first historical candidate chromosomes. After that, the data control center 210 can copy a part (for example, half) of the first historical candidate chromosomes to the candidate chromosome set

, As the first part of the candidate chromosome. In addition, the data control center 210 can also randomly generate the second part of the candidate chromosome to construct a set of candidate chromosomes corresponding to the t-th time point in cooperation with the first part of the candidate chromosome

.

。在本實施例中，上述歷史候選染色體集合可更包括對應於第t-2個時間點的第二歷史候選染色體集合

。In another embodiment, if t is greater than T, the data control center 210 can perform the above prediction method to construct a set of candidate chromosomes

. In this embodiment, the aforementioned set of historical candidate chromosomes may further include a second set of historical candidate chromosomes corresponding to the t-2th time point

.

及第二歷史候選染色體集合

產生候選染色體的一第三部分。在一實施例中，候選染色體的第三部分可包括多個預測染色體，各預測染色體包括對應於傳輸鏈結

的

及

，其中

為對應於傳輸鏈結

的預測頻段，而

為對應於

的預測能源。After that, the data control center 210 may adaptively base on the first historical candidate chromosome set

And second historical candidate chromosome set

Generate a third part of the candidate chromosome. In an embodiment, the third part of the candidate chromosome may include a plurality of predicted chromosomes, and each predicted chromosome includes a link corresponding to the transmission link.

of

and

,among them

Corresponding to the transmission link

Predicted frequency bands, and

Corresponds to

Forecast energy.

的一第一自迴歸模型，並據以估計關聯於

的一第一質心，其中第一質心表徵為

。舉例而言，資料控制中心210可基於前幾個時間點的

來建構上述第一自迴歸模型，而其相關細節可參照習知與自迴歸模型相關的文獻，於此不另贅述。In an embodiment, the method for the data control center 210 to generate the above-mentioned third part may be as follows. First, the data control center 210 can construct an association with

Is a first autoregressive model, and is estimated to be related to

A first center of mass of, where the first center of mass is represented by

. For example, the data control center 210 can be based on the

To construct the above-mentioned first autoregressive model, and the related details can refer to the literature related to the conventional autoregressive model, which will not be repeated here.

，並依據第t-1個時間點的通訊環境將

映射為介於頻譜參考範圍（例如介於0及1之間）內的連續型變數。舉例而言，假設第t-1個時間點的通訊環境可表徵為相應的可用通道數量（可表示為|M(t -1)|），而

可屬於

。在此情況下，映射後的

可表徵為

，其為介於0及1之間的一連續型變數。After that, the data control center 210 can obtain

, And according to the communication environment at the t-1 time point

The mapping is a continuous variable within the spectrum reference range (for example, between 0 and 1). For example, suppose that the communication environment at the t-1 time point can be characterized as the corresponding number of available channels (which can be expressed as |M( t -1)|), and

May belong to

. In this case, the mapped

Can be characterized as

, Which is a continuous variable between 0 and 1.

）修正為一第一副本，其中第一副本表徵為

，且第一偏移值為

及

之間的第一歐氏距離。Then, the data control center 210 may change the above-mentioned continuous variable (ie,

) Amended as a first copy, where the first copy is represented by

, And the first offset value is

and

The first Euclidean distance between.

After that, the data control center 210 may calculate a first frequency band reference value based on the first centroid and the first copy, and determine whether the first frequency band reference value falls within the spectrum reference range (for example, between 0 and 1). In this embodiment, the first frequency band reference value can be characterized as the sum of the first centroid and the first copy.

定義為第一頻段參考值，反之則可將

定義為一第二頻段參考值。在一實施例中，第二頻段參考值可表徵為：

，其中

為落於頻譜參考範圍內的第一隨機值。In one embodiment, if the first frequency band reference value falls within the spectrum reference range (for example, between 0 and 1), the data control center 210 may change

Defined as the reference value of the first frequency band, and vice versa

Defined as a second frequency band reference value. In an embodiment, the second frequency band reference value may be characterized as:

,among them

Is the first random value that falls within the reference range of the spectrum.

的一第二自迴歸模型，並據以估計關聯於

的一第二質心，其中第二質心表徵為

。舉例而言，資料控制中心210可基於前幾個時間點的

來建構上述第二自迴歸模型，而其相關細節可參照習知與自迴歸模型相關的文獻，於此不另贅述。In addition, the data control center 210 can also construct an association with

A second autoregressive model of, and it is estimated to be related to

A second center of mass of, where the second center of mass is represented by

. For example, the data control center 210 can be based on the

To construct the above-mentioned second autoregressive model, and the related details can refer to the literature related to the conventional autoregressive model, which will not be repeated here.

，並基於一第二偏移值予以修正為一第二副本，其中第二副本表徵為

，且第二偏移值為

及

之間的一第二歐氏距離。After that, the data control center 210 can obtain

, And amended to a second copy based on a second offset value, where the second copy is characterized as

, And the second offset value is

and

A second Euclidean distance between.

及

之間）內。在本實施例中，第一能源參考值可表徵為第二質心及第二副本的總和。Then, the data control center 210 can calculate a first energy reference value based on the second center of mass and the second copy, and determine whether the first energy reference value falls within an energy reference range (for example, between

and

Between). In this embodiment, the first energy reference value can be characterized as the sum of the second center of mass and the second copy.

定義為第一能源參考值，反之則可將

定義為一第二能源參考值。在一實施例中，第二能源參考值可表徵為：

，其中

為落於能源參考範圍內的一第二隨機值。If the first energy reference value falls within the energy reference range, the data control center 210 may change

Defined as the first energy reference value, and vice versa

Defined as a second energy reference value. In an embodiment, the second energy reference value may be characterized as:

,among them

Is a second random value that falls within the energy reference range.

。After generating the third part of the candidate chromosome according to the above teachings, the data control center 210 can randomly generate a fourth part of the candidate chromosome to construct a set of candidate chromosomes corresponding to the t-th time point in cooperation with the third part of the candidate chromosome

.

之後，可理解為已完成在第t個時間點的初始化操作。因此，在步驟S730中，可對候選染色體集合執行多目標最佳化演算法，以對各傳輸鏈結

分配最佳能源及最佳頻段。Construct a set of candidate chromosomes corresponding to the t-th time point according to the above teaching

After that, it can be understood that the initialization operation at the t-th time point has been completed. Therefore, in step S730, a multi-objective optimization algorithm can be performed on the set of candidate chromosomes to perform the

Allocate the best energy and the best frequency band.

個迭代操作，

為正整數，且對候選染色體集合執行多目標最佳化演算法的步驟包括：在第k個迭代操作中，對特定染色體集合採用比較選取法，以產生第一集合（

）；對第一集合重複執行交叉機制或變異機制，以產生第二集合；基於傳輸品質限制適應性地調整第二集合中的各第二染色體；淘汰第一集合及第二集合中的第一染色體及第二染色體的一部分，以產生對應於第k個迭代操作的第三集合，其中若k為1，則特定染色體集合為候選染色體集合，若k不為1，則特定染色體集合為第k-1個迭代操作對應的第三集合；在產生第

個迭代操作對應的第三集合之後，基於多個目標函數而以最佳選取法從第

個迭代操作對應的第三集合找出最佳候選染色體

；依據最佳候選染色體

中各傳輸鏈結

的候選能源及候選頻段設定各傳輸鏈結

的最佳能源及最佳頻段。以上各步驟的細節可參照先前實施例中的說明，於此不另贅述。In this embodiment, the multi-objective optimization algorithm includes

Iterative operations,

Is a positive integer, and the steps of performing a multi-objective optimization algorithm on a set of candidate chromosomes include: in the k-th iterative operation, a comparative selection method is used for a specific set of chromosomes to generate the first set (

); Repeat the crossover mechanism or mutation mechanism for the first set to generate the second set; adaptively adjust each second chromosome in the second set based on transmission quality restrictions; eliminate the first set and the first set in the second set A part of the chromosome and the second chromosome to generate the third set corresponding to the k-th iterative operation. If k is 1, the specific chromosome set is the candidate chromosome set, and if k is not 1, the specific chromosome set is the k-th -1 The third set corresponding to the iterative operation;

After the third set corresponding to an iterative operation, based on multiple objective functions, the best selection method is used from the first

Find the best candidate chromosome

; According to the best candidate chromosome

Transmission links in

Candidate energy and candidate frequency bands to set each transmission link

The best energy and best frequency band. For the details of the above steps, please refer to the description in the previous embodiment, which will not be repeated here.

中各傳輸鏈結

的候選頻段可能為落於上述頻譜參考範圍內的連續型變數（例如先前揭示的

），故本發明的資料控制中心210可依據所述第t個時間點的通訊環境將各傳輸鏈結

的候選頻段轉換為離散數值。In addition, in one embodiment, since the best candidate chromosome

Transmission links in

Candidate frequency bands may be continuous variables that fall within the above-mentioned spectrum reference range (for example, the previously disclosed

), so the data control center 210 of the present invention can link each transmission link according to the communication environment at the t-th time point

The candidate frequency bands are converted into discrete values.

的候選頻段乘以第一可用通道數量，以產生對應於各傳輸鏈結

的參考頻段值。之後，資料控制中心210可將各傳輸鏈結

的參考頻段值無條件進位，以產生各傳輸鏈結

的離散數值。之後，資料控制中心210可將各傳輸鏈結

的最佳頻段設定為對應的離散數值。另外，資料控制中心210可將各傳輸鏈結

的最佳能源設定為對應的候選能源。For example, assuming that the communication environment at the t-th time point (corresponding to M( t )) corresponds to the number of first available channels (which can be expressed as |M( t )|), the data control center 210 may assign each transmission chain Knot

Multiply the number of candidate frequency bands by the first available channel number to generate a link corresponding to each transmission link

The reference frequency band value. After that, the data control center 210 can link each transmission link

The reference frequency band value is unconditionally carried to generate each transmission link

The discrete value of. After that, the data control center 210 can link each transmission link

The best frequency band is set to the corresponding discrete value. In addition, the data control center 210 can link each transmission link

The best energy is set as the corresponding candidate energy.

而執行，但在第t個時間點所執行的多目標最佳化演算法係基於對應於第t個時間點的候選染色體集合

而執行。In short, the content of the multi-objective optimization algorithm executed at the t-th time point is roughly the same as the multi-objective optimization algorithm executed at the first time point, except that the content of the multi-objective optimization algorithm executed at the first time point is roughly the same. The multi-objective optimization algorithm is based on the initial set of chromosomes

And execute, but the multi-objective optimization algorithm executed at the t-th time point is based on the set of candidate chromosomes corresponding to the t-th time point

And execute.

對應的最佳能源及最佳頻段進行通訊。After that, in step S740, the data control center 210 may control the plurality of secondary user devices (for example, nodes 1 to 10 in FIG. 2) according to each transmission link

Corresponding to the best energy and best frequency band for communication.

。在一些實施例中，若通訊環境已改變，本發明的方法還可基於先前的歷史候選染色體集合來產生當下時間點的候選染色體集合。相較於習知僅考慮靜態通訊環境的作法，本發明係將動態通訊環境納入考量，因而能找出更符合實際情況的最佳候選染色體。並且，由於本發明係基於多目標最佳化演算法找出最佳候選染色體，因而可讓各次要用戶裝置在第t個時間點（t大於1）時能夠以最佳的能源使用率、通道使用公平性及頻譜使用率進行通訊。It can be seen from the above that at other time points than the first time point, the resource allocation method based on the genetic algorithm proposed by the present invention can adopt different initialization operations in response to changes in the communication environment, and then generate accordingly Chromosome set candidate chromosome set that can be used for multi-objective optimization algorithm

. In some embodiments, if the communication environment has changed, the method of the present invention can also generate the candidate chromosome set at the current time point based on the previous historical candidate chromosome set. Compared with the conventional method that only considers the static communication environment, the present invention takes the dynamic communication environment into consideration, so that the best candidate chromosomes that are more in line with the actual situation can be found. In addition, because the present invention is based on a multi-objective optimization algorithm to find the best candidate chromosomes, each secondary user device can use the best energy usage rate at the t-th time point (t is greater than 1). Channel use fairness and spectrum utilization rate for communication.

Please refer to FIG. 8, which is a functional block diagram of a data control center according to an embodiment of the present invention. In this embodiment, the data control center 210 may include a transceiver 212 and a processor 214.

The transceiver 212 may include at least a transmitter circuit, a receiver circuit, an analog-to-digital (A/D) converter, a digital-to-analog (D/A) converter, Low noise amplifier (LNA), mixer, filter, matching circuit, transmission line, power amplifier (PA), one or more antenna units and local storage media components, but not limited to these , To provide wireless access to the data control center 210 in FIG. 8.

The above-mentioned receiver circuit may include functional units to perform operations such as low-noise amplification, impedance matching, frequency mixing, down-frequency conversion, filtering, and amplification. The above-mentioned transmitter circuit may include functional units to perform operations such as amplification, impedance matching, frequency mixing, up-frequency conversion, filtering, power amplification, and the like. The A/D converter or D/A converter is configured to convert the analog signal format to a digital signal format during the upstream signal processing, and to convert the digital signal format to the analog signal format during the downstream signal processing.

The processor 214 is coupled to the transceiver 212, and can be a general purpose processor, a special purpose processor, a traditional processor, a digital signal processor, multiple microprocessors, one or more combined digital signal processing Microprocessor, controller, microcontroller, Application Specific Integrated Circuit (ASIC), Field Programmable Gate Array (FPGA), any other type of integrated circuit , State machines, processors based on Advanced RISC Machine (ARM) and similar products.

In an embodiment of the present invention, the processor 214 can implement the resource allocation method based on the genetic algorithm proposed in the present invention by accessing software modules and program codes, and the related details can refer to the description in the previous embodiment. I will not repeat them here.

In summary, the resource allocation method and data control center based on genetic algorithm proposed by the present invention can first generate a chromosome set through a certain initialization process at each time point under consideration, and then perform the calculation of the chromosome set. The multi-objective optimization algorithm proposed by the invention is to obtain the optimal resource allocation solution corresponding to each transmission link, so that the corresponding node (ie, the secondary user device) can transmit accordingly.

In the first embodiment, at the first time point, since there is not yet any historical data, and it is impossible to determine whether the communication environment of the secondary user device has changed, the data control center of the present invention can randomly generate an initial chromosome set , And based on the multi-objective optimization algorithm to find the best initial chromosome.

In the second embodiment, at the t-th time point (t>1), the data control center of the present invention can determine the way to generate the candidate chromosome set based on whether the communication environment has changed and whether it has sufficient historical data (for example, Full copy, semi-random method, prediction method, etc.). After that, the data control center of the present invention can perform a multi-objective optimization algorithm on the generated candidate chromosome set to find the best candidate chromosome corresponding to the t-th time point.

In this way, considering the dynamic communication environment, the present invention allows each secondary user device to communicate with the best energy usage rate, channel usage fairness, and spectrum usage rate at each point in time. Moreover, since the multi-objective optimization algorithm of the present invention includes a crossover mechanism, a mutation mechanism, and an adjustment mechanism, it can ensure that a feasible solution is found, thereby improving the convergence performance.

Although the present invention has been disclosed in the above embodiments, it is not intended to limit the present invention. Anyone with ordinary knowledge in the relevant technical field can make some changes and modifications without departing from the spirit and scope of the present invention. The protection scope of the present invention shall be subject to those defined by the attached patent application scope.

:能源

:頻段

:染色體集合

:第一集合

:第二集合

、

:第三集合

~

、

~

、

~

、

~

、

:染色體 M(t ):可用頻譜集合

:傳輸鏈結集合

:資料流集合100: Communication system 110, 210: Data control center 120, 220: Primary user device 125: Primary base station 130, 230: Secondary user device 135: Secondary base station 1~10: Node 212: Transceiver 214: Processor 510, 520: member chromosomes 610, 610a, 620, 620a: reference chromosomes S710~S740: steps

:energy

: Frequency band

: Chromosome collection

: The first set

: The second set

,

: The third set

~

,

~

,

~

,

~

,

: Chromosome M( t ): available spectrum set

: Transmission link collection

: Data stream collection

Figure 1 is a schematic diagram of a conventional communication system architecture. Fig. 2 is a schematic diagram of a system according to an embodiment of the present invention. FIG. 3 is a schematic diagram of energy and spectrum allocation among secondary user devices according to an embodiment of the present invention. FIG. 4 is a schematic diagram of an application scenario of a multi-object optimization algorithm according to the first embodiment of the present invention. FIG. 5 is a schematic diagram of generating a shuffled version according to the first embodiment of the present invention. Fig. 6 is a schematic diagram of adjusting the first reference chromosome according to the first embodiment of the present invention. Fig. 7 is a flowchart of a resource allocation method based on a genetic algorithm according to a second embodiment of the present invention. Fig. 8 is a functional block diagram of a data control center according to an embodiment of the present invention.

S710~S740: steps

Claims (24)

A resource allocation method based on genetic algorithm, suitable for managing a data control center of multiple secondary user devices, the method includes: Determine at the t-th time point whether a communication environment in which the secondary user devices are located has changed, wherein there are multiple transmission links between the secondary user devices, and t is a positive integer greater than 1; In response to determining that the communication environment at the t-th time point has changed, a candidate chromosome set corresponding to the t-th time point is generated based on at least one historical candidate chromosome set, wherein the candidate chromosome set includes a plurality of candidate chromosomes, wherein Each candidate chromosome includes a candidate energy source and a candidate frequency band corresponding to each transmission link; Performing a multi-objective optimization algorithm on the candidate chromosome set to allocate an optimal energy source and an optimal frequency band to each transmission link; The secondary user devices are controlled to communicate according to the best energy and the best frequency band corresponding to each transmission link. The method according to item 1 of the scope of patent application, wherein the communication environment at the t-th time point is determined to be unchanged, and the method further includes: Obtain a historical best energy and a historical best frequency band previously allocated to each transmission link at the t-1th time point, and set the best energy and the best frequency band of each transmission link accordingly. As the method described in item 1 of the scope of patent application, it also includes: At the first time point, an initial chromosome set is randomly generated, where the initial chromosome set includes a plurality of randomly generated initial chromosomes, and each of the initial chromosomes includes an initial energy source and an initial frequency band corresponding to each transmission link; Performing the multi-objective optimization algorithm on the initial set of chromosomes to allocate an initial optimal energy source and an initial optimal frequency band to each transmission link; The secondary user devices are controlled to communicate according to the initial optimal energy and the initial optimal frequency band corresponding to each transmission link. The method according to item 1 of the scope of patent application, wherein the at least one historical candidate chromosome set includes a first historical candidate chromosome set corresponding to the t-1th time point, and the at least one historical candidate chromosome set corresponding to The steps of the candidate chromosome set at the t-th time point include: Initialize the set of candidate chromosomes corresponding to the t-th time point to an empty set; Judge whether t is greater than T, where T is a preset number of time points; In response to determining that t is not greater than T, obtain the first historical candidate chromosome set corresponding to the t-1th time point, wherein the first historical candidate chromosome set includes a plurality of first historical candidate chromosomes; Copy a part of the first historical candidate chromosomes to the set of candidate chromosomes to serve as the first part of the candidate chromosomes; A second part of the candidate chromosomes is randomly generated to construct the set of candidate chromosomes corresponding to the t-th time point in cooperation with the first part of the candidate chromosomes. The method according to item 4 of the scope of patent application, wherein the at least one historical candidate chromosome set further includes a second historical candidate chromosome set corresponding to the t-2th time point, and in response to the determination that t is greater than T, the Methods include: Adaptively generating a third part of the candidate chromosomes based on the first historical candidate chromosome set and the second historical candidate chromosome set; A fourth part of the candidate chromosomes is randomly generated to construct the set of candidate chromosomes in cooperation with the third part of the candidate chromosomes. For the method described in item 5 of the scope of patent application, the transmission link between the i-th secondary user device and the j-th secondary user device among the secondary user devices is characterized as

, The third part of the candidate chromosomes includes a plurality of predicted chromosomes, each of the predicted chromosomes includes corresponding to

of

and

,among them

Corresponds to

Of a prediction frequency band, and

Corresponds to

The step of generating the third part of the candidate chromosomes adaptively based on the first historical candidate chromosome set and the second historical candidate chromosome set includes: constructing an association with

Is a first autoregressive model, and is estimated to be related to

A first center of mass of, where the first center of mass is represented by

; Get

, And based on the communication environment at the t-1 time point

Is mapped to a continuous variable within a spectral reference range; the continuous variable is corrected into a first copy based on a first offset value, wherein the first copy is represented by

, And the first offset value is

and

Calculate a first frequency band reference value based on the first centroid and the first copy, and determine whether the first frequency band reference value falls within the spectrum reference range; if so, change

Defined as the reference value of the first frequency band, and vice versa

Defined as a reference value of the second frequency band;

A second autoregressive model of, and it is estimated to be related to

A second center of mass of, where the second center of mass is represented by

; Get

, And amended to a second copy based on a second offset value, where the second copy is characterized as

, And the second offset value is

and

Calculate a first energy reference value based on the second centroid and the second copy, and determine whether the first energy reference value falls within an energy reference range; if so, change

Defined as the first energy reference value, and vice versa

Defined as a second energy reference value. For the method described in item 6 of the scope of patent application, the second frequency band reference value is characterized as:

among them

Is a first random value within the reference range of the frequency spectrum; wherein the second energy reference value is characterized as:

among them

Is a second random value that falls within the energy reference range. The method described in item 1 of the scope of patent application, wherein the multi-objective optimization algorithm includes

Iterative operations,

Is a positive integer, and the steps of performing the multi-objective optimization algorithm on the candidate chromosome set include: In the k-th iterative operation, a comparative selection method is adopted for a specific chromosome set to generate a first set, where The first set includes a plurality of first chromosomes, each of the first chromosomes includes a first energy source and a first frequency band corresponding to each transmission link, and

; Repeating a crossover mechanism or a mutation mechanism on the first set to generate a second set, wherein the second set includes a plurality of second chromosomes, each of the second chromosomes includes a corresponding to each of the transmission link A second energy source and a second frequency band; adaptively adjust each second chromosome in the second set based on a transmission quality restriction; eliminate the first chromosomes and the first chromosomes in the first set and the second set A part of the second chromosome to generate a third set corresponding to the k-th iterative operation, wherein the third set includes a plurality of third chromosomes, and each of the third chromosomes includes a third corresponding to each of the transmission links. Energy and a third frequency band, where if k is 1, the specific chromosome set is the candidate chromosome set, and if k is not 1, the specific chromosome set is the third set corresponding to the k-1th iterative operation; In the production of

After the third set corresponding to an iterative operation, based on multiple objective functions, an optimal selection method is used from the first

The third set corresponding to an iterative operation finds a best candidate chromosome; according to the candidate energy and the candidate frequency band of each transmission link in the best candidate chromosome, the best energy and the best energy of each transmission link are set The best frequency band. The method according to item 8 of the scope of patent application, wherein the step of using the comparative selection method on the candidate chromosome set to generate the first set includes: (a) Initialize the first set to an empty set; (b) randomly taking out two of the candidate chromosomes in the candidate chromosome set as a first comparison object and a second comparison object; (c) adding one of the first comparison object and the second comparison object to the first set as one of the first chromosomes; (d) Repeat steps (b) and (c) until the number of the first chromosomes in the first set reaches a preset number. For the method described in item 9 of the scope of patent application, the step of adding one of the first comparison object and the second comparison object to the first set includes: Determine a first crowded distance of the first comparison object and a second crowded distance of the second comparison object; In response to determining that the first crowded distance is greater than the second crowded distance, the first comparison object is added to the first set, otherwise, the second comparison object is added to the first set. The method according to claim 10, wherein the first congestion distance is associated with an energy usage rate, a channel usage fairness, and a spectrum usage rate of the first comparison object. The method described in item 11 of the scope of patent application, wherein the first comparison object is characterized as

, And the first congestion distance is characterized as:

,among them

Is the previous candidate chromosome of the first comparison object in the set of candidate chromosomes, and

Is the next candidate chromosome of the first comparison object in the set of candidate chromosomes; where,

,

,

Individually are multiple parameters corresponding to the energy usage rate, the fairness of the channel usage, and the spectrum usage rate, and are individually characterized as follows:

；

；

; among them,

Represents the set of candidate chromosomes; where

Is the energy usage rate operator,

Use fairness operators for the channel,

It is the spectrum utilization rate operator. For the method described in item 8 of the scope of patent application, the transmission link between the i-th secondary user device and the j-th secondary user device among the secondary user devices is characterized as

, And the crossover mechanism includes: randomly obtaining a first member chromosome and a second member chromosome among the first chromosomes; generating a third member chromosome based on the first member chromosome and the second member chromosome, and combining the The third member is added to the second set as one of the second chromosomes; wherein, the chromosome of the third member corresponds to

The second energy is represented by:

,among them

Is the first member of the chromosome corresponding to

Of the first energy,

Is the second member of the chromosome corresponding to

Of the first energy,

( t,k ) is a random variable,

Is the lower limit of energy; among them, the third member of the chromosome corresponds to

The second frequency band is characterized as

, And it is determined based on a random binary value, where if the random binary value is the first logical value, then

Is defined as

, And if the random binary value is the second logical value, then

Is defined as

,among them

Is the first member of the chromosome corresponding to

Of this first frequency band,

Is the second member of the chromosome corresponding to

Of the first frequency band. For the method described in item 8 of the scope of patent application, the transmission link between the i-th secondary user device and the j-th secondary user device among the secondary user devices is characterized as

And the mutation mechanism includes: randomly obtaining a fourth member chromosome among the first chromosomes, and randomly generating a fifth member chromosome; generating a sixth member chromosome based on the fourth member chromosome and the fifth member chromosome, And add the sixth member chromosome as one of the second chromosomes to the second set; wherein, the sixth member chromosome corresponds to

The second energy is represented by:

,among them

Is the fourth member of the chromosome corresponding to

Of the first energy,

Corresponds to the fifth member of the chromosome

Of the first energy,

( t,k ) is a random variable,

Is the lower limit of energy; among them, the sixth member chromosome corresponds to multiple

The individual second frequency band is the fourth member chromosome corresponding to the

A shuffled version of the individual first frequency band. The method according to item 8 of the scope of patent application, wherein the step of adaptively adjusting each of the second chromosomes in the second set based on the transmission quality restriction includes: Acquiring one of the second chromosomes as a first reference chromosome, wherein the first reference chromosome includes a plurality of first reference energy sources and a plurality of first reference frequency bands corresponding to the transmission links; Determine whether each of the first reference frequency bands in the first reference chromosome all meets the transmission quality restriction; In response to determining that each of the first reference frequency bands in the first reference chromosome meets the transmission quality restriction, the first reference chromosome is not adjusted. For example, the method described in item 15 of the scope of patent application, wherein in response to determining that one of the first reference frequency bands does not meet the transmission quality restriction, the method further includes: Replacing the one of the first reference frequency bands with another frequency band to adjust the first reference chromosome, wherein the other frequency band has a lower load than the one of the first reference frequency bands; Determining whether each of the first reference frequency bands in the adjusted first reference chromosome meets the transmission quality restriction; In response to determining that each of the first reference frequency bands in the updated first reference chromosome meets the transmission quality restriction, the adjusted first reference chromosome is retained in the adjusted first reference chromosome as one of the adjusted second chromosomes In the second set. According to the method described in item 16 of the scope of the patent application, in response to determining that each of the first reference frequency bands in the updated first reference chromosome does not meet the transmission quality restriction, the method further includes: Replace the first reference chromosome with the other of the second chromosomes; Swap a first specific part of the first reference frequency bands in the first reference chromosome one-to-one with a second specific part of the first reference frequency bands to adjust the first reference chromosome, wherein the The first specific part corresponds to a first channel, the second specific part corresponds to a second channel, and the first specific part and the second specific part have the same number of channels; The adjusted first reference chromosome is retained in the second set as one of the adjusted second chromosomes. The method according to item 8 of the scope of patent application, wherein the step of eliminating the first chromosomes and the part of the second chromosomes in the first set and the second set includes: Obtain at least one match chromosome among the first chromosomes and the second chromosomes, and eliminate the at least one match chromosome; Determine whether a total number of the first chromosomes and the second chromosomes exceeds a predetermined number; In response to determining that the total number of the first chromosomes and the second chromosomes does not exceed the predetermined number, the first chromosomes and the second chromosomes are used as the third chromosomes in the third set. For example, the method described in item 18 of the scope of patent application, wherein in response to determining that the total number of the first chromosomes and the second chromosomes exceeds the predetermined number, the method further includes: A file library update method is used to eliminate at least one of the first chromosomes and the second chromosomes with a lower crowding distance, until the total number of the remaining first chromosomes and the second chromosomes does not exceed the predicted Set the number; The remaining first chromosomes and the second chromosomes are used as the third chromosomes in the third set. For the method described in item 8 of the scope of patent application, the objective functions include an energy usage objective function, a channel usage fairness objective function, and a spectrum usage objective function, and the objective function is based on the objective functions. The best selection method from the first

The step of finding the best candidate chromosome corresponding to the third set of iterative operations includes:

The third chromosome estimates of the third set corresponding to an iterative operation are associated with an energy usage objective function, a channel usage fairness objective function, and a highest energy usage rate and an optimal channel usage of the spectrum usage objective function Fairness and a highest spectrum usage rate; based on the highest energy usage rate, the fairness of the best channel usage and the highest spectrum usage rate in the first

Find the best candidate chromosome among the third chromosomes of the third set corresponding to one iterative operation, wherein the best candidate chromosome has a lowest reference difference, and the lowest reference difference is characterized as a first difference, The sum of a second difference and a third difference; wherein the first difference is the difference between an energy usage rate corresponding to the best candidate chromosome and the highest energy usage rate, and the second difference is The difference between a channel usage fairness corresponding to the best candidate chromosome and the best channel usage fairness, and the third difference is a spectrum usage rate corresponding to the best candidate chromosome and the highest spectrum usage rate The difference between. For the method described in item 8 of the scope of patent application, the candidate frequency band of each transmission link is a continuous variable falling within a spectrum reference range, and is based on the transmission link of each transmission link in the best candidate chromosome The steps for the candidate energy and the candidate frequency band to set the best energy and the best frequency band for each transmission link include: Converting the candidate frequency band of each transmission link into a discrete value according to the communication environment at the t-th time point; Setting the optimal frequency band of each transmission link to the corresponding discrete value; The optimal energy of each transmission link is set as the corresponding candidate energy. The method according to item 21 of the scope of patent application, wherein the communication environment at the t-th time point corresponds to a first number of available channels, and each transmission is performed according to the communication environment at the t-th time point. The steps of converting the linked candidate frequency band into the discrete value include: Multiplying the candidate frequency band of each transmission link by the first available channel number to generate a reference frequency band value corresponding to each transmission link; The reference frequency band value of each transmission link is unconditionally rounded to generate the discrete value of each transmission link. For the method described in item 1 of the scope of patent application, the step of judging whether the communication environment in which the secondary user devices are located at the t-th time point includes: Obtaining a first available channel quantity corresponding to the communication environment at the t-th time point; Obtain a second available channel quantity corresponding to the communication environment at the t-1 time point; In response to determining that the first available channel number is different from the second available channel number, it is determined that the communication environment at the t-th time point has changed, and vice versa, it is determined that the communication environment at the t-th time point has not changed. A data control center that allocates resources based on genetic algorithms for managing multiple secondary user devices, including: A transceiver, which receives a plurality of data indicating a plurality of idle frequency bands from a plurality of main user devices; A processor coupled to the transceiver and configured to: Estimate a communication environment in which the primary user devices and the secondary user devices are located based on the data; Determine at the t-th time point whether the communication environment in which the secondary user devices are located has changed, wherein there are multiple transmission links between the secondary user devices, and t is a positive integer greater than 1; In response to determining that the communication environment at the t-th time point has changed, a candidate chromosome set corresponding to the t-th time point is generated based on at least one historical candidate chromosome set, wherein the candidate chromosome set includes a plurality of candidate chromosomes, wherein Each candidate chromosome includes a candidate energy source and a candidate frequency band corresponding to each transmission link; Performing a multi-objective optimization algorithm on the candidate chromosome set to allocate an optimal energy source and an optimal frequency band to each transmission link; The secondary user devices are controlled to communicate according to the best energy and the best frequency band corresponding to each transmission link.

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