CN112566255B - Weighted Huffman tree, primary user bandwidth allocation method and secondary user channel sensing method - Google Patents

Abstract

The invention discloses a weighted Huffman tree, a main user channel allocation method and a secondary user channel sensing method. The weighted Huffman tree is characterized in that a weight attribute is added to all nodes and branches on the basis of the Huffman tree, an occupation state attribute is added to all branches, and the main user channel allocation and the secondary user channel perception are jointly optimized on the basis of the weighted Huffman tree. For the cognitive communication system in the interleaving type access mode, the method and the device can minimize the average sensing times of the secondary users under the constraint condition of given bandwidth loss, and improve the channel sensing efficiency of the secondary users.

Description

A Weighted Huffman Tree, Primary User Bandwidth Allocation Method and Secondary User Channel Sense know the way

technical field

The invention relates to the field of wireless network communication, in particular to a weighted Huffman tree, a bandwidth allocation method for primary users and a channel perception method for secondary users.

Background technique

With the rapid development of wireless communication technology, more and more wireless devices and applications are widely used, and people's demand for spectrum is increasing, which makes the available radio spectrum resources increasingly tight. The problem of spectrum scarcity has become an important issue in realizing wireless communication. The bottleneck of sustainable technological development. The United States Federal Communications Commission (FCC) has conducted a large number of investigations and studies on the use of frequency bands and found that due to the discontinuous use of spectrum by licensed users in time and space, the overall utilization efficiency of the allocated spectrum resources is only 15%-85%. %. In order to solve the problem of low spectrum utilization, Cognitive Radio (CR, Cognitive Radio) technology emerges as the times require, and has become a key technology for improving the utilization of wireless spectrum resources in the next generation network. In a cognitive wireless network, a user with a licensed spectrum is called a primary user (PU, primary user), and a user without a licensed spectrum is called a secondary user (SU, secondary user).

Spectrum sensing is a key technology in cognitive wireless networks. A secondary user (Secondary User, secondary user) needs to use a spectrum sensing algorithm to find spectrum gaps (white spaces) that are not used by a primary user (Primary User, primary user) in the currently available frequency band, and use these gaps to transmit data. Since each spectrum sensing operation takes time and energy, and the secondary user needs to suspend data transmission during the sensing process, reducing the sensing times of the secondary user as much as possible can effectively reduce energy consumption and improve the data throughput of the secondary user quantity.

In general, spectrum gaps appear randomly in the entire bandwidth range, and we take the average sensing times (ie, average sensing frequency) required by secondary users to obtain the spectrum occupancy status as an index to measure their spectrum sensing efficiency. Obviously, the higher the spectrum sensing efficiency is, the less energy is consumed, the more time is used for data transmission, and the higher the utilization rate of the entire spectrum is. Therefore, how to improve the efficiency of spectrum sensing is one of the important goals of cognitive wireless network communication performance optimization.

Existing methods for reducing the frequency of spectrum sensing and improving sensing efficiency mainly include: cooperative sensing, compressed sensing, machine learning sensing, etc. For example: Chinese patent CN103326797B proposes a cognitive network cooperative spectrum sensing method, in which multiple secondary users work together to perform energy detection on the spectrum and send the detection data to the control center, and then the control center combines the existing rights The value matrix and the threshold make a judgment on the activity of the current primary user. Cooperative sensing is mainly to cooperate among multiple secondary users to share the overall sensing task, thereby reducing the spectrum sensing workload of a single secondary user. However, the total spectrum sensing workload required for all frequency bands is not fundamentally reduced. Therefore, if the total number of sensing times required to obtain the spectrum occupancy status is taken as the index of spectrum sensing efficiency, cooperative sensing does not improve the overall sensing efficiency.

Patent CN103532645A proposes a new method of spectrum sensing with the help of compressed sensing technology, by reducing the sparsity between the column vectors of the observation matrix, reducing the correlation between the column vectors, and combining the adaptiveness of the observation matrix for overall optimization, Realize reducing the number of spectrum sensing times under the same receiving operation performance. However, this method is based on the assumption of sparse signals, and the reconstruction of sparse signals needs to consume a lot of computing resources, resulting in a long time for spectrum sensing.

Patent CN104135327B proposes a spectrum sensing method based on support vector machines, which models the spectrum sensing problem as a signal classification problem, selects the ratio of the maximum and minimum eigenvalues of the signal covariance matrix as the classification feature, and uses the support vector machine as a classifier. for spectrum sensing. But in actual use, how to choose an appropriate kernel function is a challenge.

According to the industry norms of cognitive radio, the access of secondary users to spectrum should avoid affecting the communication of primary users as much as possible. Due to the time-varying, diversity and difference of available spectrum in cognitive wireless network, there is a high risk of spectrum sensing. Due to the dynamics and complexity, simply relying on the secondary user's perception operation to obtain the spectrum occupancy status often leads to an overly complex algorithm. If there is cooperation between the primary user and the secondary user, on the premise of fully meeting the bandwidth requirements of the primary user, by optimizing the resource allocation strategy and giving some cooperation to the spectrum sensing of the secondary user, the spectrum sensing cost can be significantly reduced. Complexity, improve perception efficiency.

Common cooperation methods between primary users and secondary users are mainly based on spectrum leasing and spectrum sharing. The primary user has the ownership of the spectrum, so it can lease the unused spectrum to the secondary user according to its own situation; in return, the secondary user assists the primary user to transmit data. For example: Chinese patent CN102316465A proposes a spectrum game allocation method in a cognitive wireless network. The secondary user requests to lease the spectrum after detecting the idle spectrum. The spectrum management center receives the lease request information and detailed parameter information of the secondary user, and calls the game Algorithm to determine the primary user who provides spectrum for the secondary user. Patent CN104270768A proposes a spectrum sharing method based on the Stackelberg game in a cooperative cognitive wireless network, which uses a two-level Stark system in which the primary user is the leader and multiple non-cooperative cognitive sending users are the slaves. The Berg game model is introduced into spectrum sharing to improve the continuity of secondary user communication.

However, the above-mentioned spectrum leasing and sharing mechanism is mainly aimed at improving the overall utilization rate of the frequency band, and does not significantly improve the spectrum sensing efficiency of the secondary user; at the same time, the bandwidth demand of the primary user changes with time, how to meet this It remains a challenge to maximize the overall utilization of the spectrum while meeting this dynamically changing demand.

The present invention focuses on how to comprehensively consider the spectrum allocation strategy of the primary user and the spectrum sensing strategy of the secondary user, optimize the spectrum sensing efficiency of the secondary user and improve the overall utilization rate of the spectrum on the premise of fully meeting the spectrum requirements of the primary user.

Contents of the invention

In order to overcome the shortcomings and deficiencies of the prior art, the first object of the present invention is to provide a weighted Huffman tree (Weighted Huffman Tree);

The second object is to provide a channel division and allocation method for cognitive wireless communication based on weighted Huffman tree.

The third object is to provide a primary user channel allocation method based on weighted Huffman tree.

The fourth object is to provide a secondary user channel sensing method based on weighted Huffman tree.

First object of the present invention adopts following technical scheme:

The present invention proposes a weighted Huffman tree (Weighted Huffman tree), preferably, on the basis of the Huffman tree (Huffman Tree), a new weight attribute is added for all nodes and branches, and a new weight attribute is added for all branches Added an occupancy state property.

The newly added attributes meet the following conditions:

(a) The new attributes are independent of the original attributes of nodes and branches;

(b) The weight of the root node and each intermediate node is equal to the minimum value among the weights of its left and right child nodes;

(c) The branch weight of the root node and each intermediate node is equal to the absolute value of the difference between the weights of its left and right child nodes.

(d) The value of the newly added branch occupation state includes two states of "idle" and "occupied".

Further, the left and right branches of the node are used to distinguish the two states of "idle" and "occupied". Without loss of generality, in the present invention, the left branch of the node is used to represent the "idle" state of the channel, and the right branch of the node is used to represent the "occupied" state of the channel.

The second object of the present invention proposes a method for dividing and allocating cognitive wireless channels based on a weighted Huffman tree. Firstly, the available bandwidth resources of primary users (Primary User) and secondary users (Secondary User) are divided into a series of sub-channels ; Each channel is aggregated by a number of sub-channels; primary users and secondary users can use multiple channels to complete data transmission; the bandwidth of all sub-channels divided in the present invention are equal, equal to a fixed value.

Without loss of generality, the present invention discretizes the bandwidth requirement of the primary user in units of sub-channel bandwidth, and expresses the bandwidth requirement of the primary user by the number of required sub-channels.

The value of each bandwidth requirement is marked with a leaf node, the probability of occurrence of the value is marked as the probability of the leaf node, and the value of the bandwidth requirement is used as the weight of the leaf node.

Furthermore, the discretized primary user bandwidth demand is used as the weight attribute of a group of leaf nodes, and the Huffman tree is constructed on the group of leaf nodes based on its probability distribution. The construction process needs to ensure that the weight attributes of nodes and branches satisfy The described condition of claim 1, that is: the weight of the root node and each intermediate node is equal to the minimum value among its left and right child node weights; the branch weight of the root node and each intermediate node is equal to its left , the absolute value of the weight difference of the right child node.

The total number of leaf nodes is equal to the total number of all values after discretization of the bandwidth demand of primary users. The path from the root node to the leaf node represents the channel division and channel allocation scheme to achieve the bandwidth requirement; the number of branches contained in the path is equal to the total number of channels contained in the scheme; each branch corresponds to a channel, and the branch weight represents the bandwidth of the channel, and the occupied state of the branch represents whether the channel is used in the channel allocation scheme.

The path from the root node to any intermediate node represents part of the channel division and allocation scheme shared by all subordinate leaf nodes of the intermediate node, and the weight of the intermediate node represents the shared part provided by the main user. bandwidth.

The construction process of the weighted Huffman tree includes the following specific steps:

S1 assumes that the bandwidth requirement of the primary user is R. Without loss of generality, firstly, R is discretized, and the method is to discretize the value of R according to the sub-channel bandwidth d (round up), and obtain

S2 marks the value range of R _d as Q _r ＝{r ₀ ,r ₁ ,…,r _m-1 }, and the probability distribution P _r ＝{p ₀ ,p ₁ ,…,p _m-1 }, that is, P( R _d = _ri )=p _i (0≤i≤m-1), where P(•) is a probability function.

S3 establishes a node list L _v ={v ₀ ,v ₁ ,…,v _m-1 } according to Q _r and P _r , and sets two attributes for each node v _i (0≤i≤m-1) , the weight w(v _i )= _ri ∈Q _r and the probability P(v _i )=p _i ∈P _r , respectively expressed as the bandwidth requirement of _ri and the occurrence probability of _ri .

S4 creates a new node v.

S5 selects two nodes v _x and v _y with the lowest probability from the node list L _v , compares the weights of v _x and v _y , and determines the left and right child nodes according to the comparison result. Without loss of generality, in the present invention, a node with a smaller weight is used as a left child node, and a node with a larger weight is used as a right child node.

S6 calculates the sum of the probability of the left child node and the right child node as the probability of the new node v; uses the minimum value of the bandwidth of the left child node and the weight of the right child node as the weight of the new node v; The absolute value of the difference between the weights of the left and right child nodes is used as the weight of the left and right branches of the new node v.

S7 inserts a new node v into the list L _v , and removes two child nodes v _x and v _y from the node list L _v at the same time.

S8 checks the current number of elements in the node list L _v , if the number of elements is greater than 1, go to S4 to continue execution; otherwise, the construction process ends.

In the channel division and channel allocation method proposed by the present invention, the applicable channels of the method are frequency domain channels, space domain channels and combinations of the above channels.

The present invention proposes a primary user channel allocation method based on a weighted Huffman tree, and uses the following method to describe the primary user channel allocation mode: each primary user bandwidth requirement r _i (0≤i≤m-1), has a unique channel allocation scheme S _i corresponds to it; the overall channel allocation scheme constitutes the primary user channel allocation pattern S={S ₀ , S ₁ ,...,S _m-1 }. The channel allocation scheme S _i describes the leaf corresponding to r _i from the root node The complete path of a node; specifically, the channel allocation scheme S _i describes the branch sequence that makes up the path, and the channel allocation scheme S _i describes the occupancy state of each branch in the branch sequence and the bandwidth of the channel represented by the branch.

(0≤i≤m-1)，其中每一个加权位

(0≤j≤n-1)中的b_j标记了第(j+1)个信道的占用状态，b_j＝1代表第(j+1)个信道当前已被占用，b_j＝0则代表(j+1)个信道当前为空闲状态；权重w_j的值代表第(j+1)个信道的带宽。S_i的总带宽等于所有b_j值为1的所有信道的带宽之和，即

且w(S_i)＝r_i(0≤i≤m-1)。Without loss of generality, the present invention uses a weighted bit sequence to describe the channel allocation scheme S _i ,

(0≤i≤m-1), where each weighted bit

b _j in (0≤j≤n-1) marks the occupancy state of the (j+1)th channel, b _j =1 means that the (j+1)th channel is currently occupied, b _j =0 means It means that the (j+1) channel is currently idle; the value of the weight w _j represents the bandwidth of the (j+1)th channel. The total bandwidth of S _i is equal to the sum of the bandwidths of all channels with b _j value of 1, namely

And w(S _i )= _ri (0≤i≤m-1).

In the primary user channel allocation method proposed by the present invention, the steps of obtaining the primary user channel allocation mode are as follows: firstly, according to the bandwidth requirement of the primary user flow, select a leaf node with an equal weight, and then trace back to the root along the weighted Huffman tree node, and the path traversed represents the primary user channel allocation scheme that satisfies the bandwidth requirement. Further, the set of all primary user channel allocation schemes constitutes a primary user channel allocation pattern.

Specifically, the generation method of the channel allocation scheme S _i (0≤i≤m-1) includes the following steps:

S1 Let Q _r ={r ₀ , r ₁ ,…,r _m-1 }, w(·) is a function to obtain the weight of a node, w _b (·) is a function to obtain the weight of a branch of the node; let i ←0, j←0;

S2 selects the leaf node v in the weighted Huffman tree so that it satisfies w(v)= _ri ;

S3 traces back to the parent node v' of v along the weighted Huffman tree, and at the same time make j←j+1;

S4 Let w _j represent the branch weight, w _j ←w _b (v _k ). If v is the left branch of the parent node v', set b _j equal to 0; otherwise, set b _j equal to 1;

S5 If v' is the root node, set j←0, go to the next step; otherwise, go to S2 to continue execution;

(0≤i≤m-1)，结束。S6 If i<m-1, then i←i+1, turn to S2; otherwise, output the primary user bandwidth allocation mode {S ₀ , S ₁ ,...,S _m-1 }, where

(0≤i≤m-1), end.

In the primary user channel allocation method proposed by the present invention, the process of allocating channels for a given primary user bandwidth requirement _Rd according to the primary user channel allocation scheme S _i is: starting from the first weighted bit on the leftmost side of S _i , if the bit is zero, that is, b _n-(j+1) = 0 (0≤j≤n-1), indicating that the channel is not occupied by the primary user, then skip all w _{n-(j+ 1)} sub-channels; if b _n-(j+1) =1 indicates that the channel is occupied by the primary user, then allocate w _n-(j+1) sub-channels included in the channel to the primary user for data transmission.

The weighted Huffman tree-based secondary user channel state perception method proposed by the present invention is used to obtain the channel occupation state of the primary user, and select an idle channel for data transmission therefrom. Preferably, starting from the root node of the weighted Huffman tree, the occupancy state of the channel represented by the branch of the current node is perceived sequentially; if the state of the channel is "occupied", it indicates that the channel is being used by the main user , therefore, the secondary user needs to skip this channel, and select the right child node of the current node as the successor node, and continue to perceive the state of the next channel; if the state of the channel is "idle", mark the channel It is an idle channel and can be used by secondary users for data transmission. At this time, the left child node of the current node is selected as the successor node to continue the state perception of the next channel; when a leaf node is encountered, the perception process terminates .

Specifically, the channel sensing method of the secondary user includes the following steps:

S1 Let v point to the root node, j←0, w _b ( ) is a function to obtain the branch weight of the node; use c _j to represent the j+1th channel, and the left and right children of all leaf nodes Node is set to null value;

S2 The secondary user acquires the occupancy status of the jth channel c _j through perception. According to the foregoing description, it can be known that c _j includes w _b (v) sub-channels, and all sub-channels in the channel have the same occupancy state. Therefore, the secondary user can choose one of w _b (v) sub-channels as the sensing object;

S3 If the state of c _j is idle, it indicates that c _j is currently not occupied by the primary user, so allocate c _j to the secondary user for data transmission, and replace v with the left child node of v; otherwise, it indicates that c _j is currently being occupied by It is used by the primary user, so the channel needs to be skipped, and v is replaced by the right child node of v;

S4 judges whether v is empty, if not empty, go to S2 to continue execution; otherwise, terminate the program.

Beneficial effects of the present invention:

For a cognitive radio in an interweaving access mode, the present invention can minimize the average sensing times of secondary users under a given bandwidth loss constraint condition, thereby maximizing the channel sensing efficiency of secondary users.

The reason is that, from the construction process of the weighted Huffman tree, in addition to adding weight attributes and branch occupancy state attributes for nodes and branches, the weighted Huffman tree maintains the minimum average depth of the standard Huffman tree. excellent nature. Assuming that the secondary user has a large amount of data and needs to find all idle channels each time, the average number of times of sensing is equal to the average depth of the weighted Huffman tree, so the average number of times of sensing is the least.

By improving the spectrum sensing efficiency of the secondary user, the time and energy consumed in the spectrum sensing link can be reduced, and the transmission efficiency of the secondary user can be improved.

Description of drawings

FIG. 1 is a schematic diagram of the construction process of the weighted Huffman tree in this embodiment.

FIG. 2 is a schematic diagram of a weighted Huffman tree structure in this embodiment.

FIG. 3 is a list of channel occupancy states of the primary user in this embodiment.

Fig. 4 is a schematic diagram of the primary user channel allocation process and channel occupancy state when R _d = 2.

FIG. 5 is a schematic diagram of the steps for the secondary user to complete channel sensing according to the weighted Huffman tree when R _d =2.

FIG. 6 is a schematic diagram of a secondary user's channel sensing process for an actual channel when R _d =2.

Detailed ways

The present invention will be described in further detail below in conjunction with the embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto.

Example

The present invention includes the following operations, specifically: constructing a weighted Huffman tree, channel allocation for primary users, and channel perception for secondary users.

As shown in Figures 1-6, both the primary user and the secondary user in this embodiment are in multi-channel transmission mode, that is, traffic can be allocated to multiple channels, and data transmission can be completed in parallel using multiple channels; each channel It is formed by aggregation of sub-channels, and this aggregation is dynamic. The channel capacity is equal to the superposition of the sub-channel capacities.

Each leaf node represents the discretized value of the bandwidth requirement of a primary user's traffic, and the weight of the leaf node represents the bandwidth required to transmit the traffic; without loss of generality, the present invention sets the value as transmission The number of subchannels required by the primary user traffic.

The total number of leaf nodes is equal to the total number of all possible values of the primary user's bandwidth requirements; the path from the root node to the leaf node represents the channel division and channel allocation scheme to meet the bandwidth required by the traffic value.

The number of branches included in the path is equal to the total number of channels included in the scheme, each branch corresponds to a channel, the branch weight represents the bandwidth of the channel, and the occupied state of the branch represents whether the channel is used in the channel allocation scheme.

The path from the root node to any intermediate node represents part of the channel division and allocation scheme shared by all subordinate leaf nodes of the intermediate node, and the weight of the intermediate node represents the shared part provided by the main user. bandwidth.

(1) A construction method based on weighted Huffman tree, specifically:

不失一般性，设S1. Let R be the bandwidth requirement of the primary user, and W be the available frequency spectrum. Divide W into a series of equal-bandwidth sub-channels, and d is the sub-channel bandwidth. After rounding R to an integer in units of d, we get

Without loss of generality, let

R _d ∈ Q _R ＝{r ₀ ,r ₁ ,...,r ₁₅ }＝{0,1,...,15},

The details are shown in Table 1.

Table 1: Value range of primary user traffic.

The probability distribution corresponding to Q _R is P _R ={p ₀ ,p ₂ ,...,p ₁₅ }. The values of p _i (0≤i≤15) are shown in Table 2. Obviously, there are

Table 2: Probability distribution of primary user traffic values

S2. Set up a node list L _v ={v ₀ ,v ₂ ,...,v ₁₅ }, where the weight of each node satisfies: w _i = _ri (0≤i≤15), as shown in Table 3 .

Table 3: Probability and weight attributes of leaf nodes

S3. Create a new node.

S4. From the set L _v, the two values with the smallest probability are p ₂ =0.011 and p ₇ =0.012, and the weights corresponding to v ₂ and v ₇ are respectively w ₂ =2 and w ₇ =7. Since w ₂ <w ₇ , select node v ₂ as the left child node of the new node, and v ₇ as the right child node of the new node, so that the weight of the left child node is less than the weight of the right child node.

Compute the parameters of the new node:

1) The probability of a new node is p ₂ +p ₇ =0.011+0.012=0.023;,

2) The weight of the new node is min{w ₂ ,w ₇ }=w ₂ =2;

3) The branch weight of the new node is |w ₇ -w ₂ |=|7-2|=5.

Record the new node as v _(0.023,2) , and its subscript (0.023,2) marks the probability and weight of the node; the branch weight

S5. Insert the new node v _(0.023,2) into the list L _v , and remove v ₂ and v ₇ from L _v at the same time.

S6. Check that the number of elements in the current list L _v |L _v |=14>1, therefore, continue to create a new node.

Select the two values with the smallest probability in L _v at this time, which are respectively p ₄ =0.014 and p ₁₂ =0.015, and the weights corresponding to nodes v ₄ and v ₁₂ are respectively w ₄ =4 and w ₁₂ =12. Since w ₄ <w ₁₂ , select node v ₄ as the left child node of the new node, and v ₁₂ as the right child node of the new node, to ensure that the weight of the left child node is less than the weight of the right child node.

Calculate new node parameters:

1) The probability of a new node is p ₄ +p ₁₂ =0.014+0.015=0.029,

2) The weight of the new node is min{w ₄ ,w ₁₂ }=w ₄ =4,

3) The branch weight of the new node is |w ₁₂ -w ₄ |=12-4=8.

Record the new node as v _(0.029,4) , and its subscript (0.029, 4) marks the probability and weight of the node; the branch weight

S7. Insert a new node v _(0.029,4) into the list L _v , and remove v ₄ and v ₁₂ from L _v at the same time.

Continue to execute algorithms similar to S4-S5 and S6-S7 until the number of elements in the current list L _v |L _v |=1. The algorithm execution process is shown in Figure 1. After completing the above steps, the weighted Huffman tree shown in Figure 2 is obtained.

(0≤i≤m-1)，其中每一个加权位

(0≤j≤n-1)中的b_j标记信道的占用状态：b_j＝1代表信道当前已被占用，b_j＝0则代表信道当前为空闲状态；权重w_j的值代表第j个信道的带宽，S_i的总带宽等于所有b_j值为1的所有信道的带宽之和，即

且满足w(S_i)＝r_i.(2) A primary user bandwidth allocation method based on a weighted Huffman tree, including, for a given primary user bandwidth requirement r _i , assigning a group of channels to it, and the corresponding channel allocation scheme S _i uses a weighted bit sequence to describe,

(0≤i≤m-1), where each weighted bit

b _j in (0≤j≤n-1) marks the occupancy state of the channel: b _j =1 means that the channel is currently occupied, b _j =0 means that the channel is currently idle; the value of weight w _j represents the jth The bandwidth of channels, the total bandwidth of S _i is equal to the sum of the bandwidths of all channels with b _j value of 1, that is

And satisfy w(S _i )= _ri .

Obtain channel allocation mode based on primary user traffic

S1. It is known that R _d ∈ Q _r ={r ₀ ,r ₁ ,…,r ₁₅ }={0,1,…,15}, let i←0;

S2. Let j←0, select the leaf node whose weight is r _i from the weighted Huffman tree shown in Figure 2, denoted as v _j ;

S3. Obtain the parent node v _j ^p of v _j ;

S4. If v _j is the left branch of v _j ^p , then set b _j ←0, which means the channel is idle; otherwise, set b _j ←1, which means the channel is occupied.

S5. Let the weight w _j of b _j be equal to the branch weight of the parent node v _j ^p .

转S7；否则，j←j+1,转S2继续执行.S6. Determine whether v _j ^p is the root node. If yes, output

Go to S7; otherwise, j←j+1, go to S2 to continue execution.

S7. Make i←i+1, and judge whether there is i>15. If yes, output the distribution pattern table {S ₀ , S ₁ ,...,S ₁₅ }, and the algorithm ends. Otherwise, go to S2 to continue execution.

After the algorithm ends, the channel allocation pattern table shown in Figure 3 is obtained, which is used for channel allocation of the primary user.

(3) Primary user channel allocation

S1. Set the bandwidth requirement of the primary user as R, discretize it according to the minimum channel capacity d, and obtain

S2. In this embodiment, without loss of generality, taking R _d = 2 as an example, obviously, it satisfies 0≤R _d ≤15. From the primary user bandwidth allocation mode shown in Figure 3, retrieve the corresponding _Rd = 2 Allocation mode S _i =1 ¹ 0 ² 0 ¹³ 0 ¹² 1 ¹ 0 ⁵ , where the number in the upper left corner of 1 and 0 represents the channel bandwidth (that is, the number of sub-channels included in the channel).

S3. Make j←0, read the numbers of S _i =1 ¹ 0 ² 0 ¹³ 0 ¹² 1 ¹ 0 ⁵ sequentially from left to right; for j=0, since b ₅ =1, w ₅ =1, the main The user occupies the channel (the channel contains 1 subchannel, therefore, it is equivalent to the primary user starting from the 1st subchannel, crossing 1 subchannel, and the next channel starts from the 1st+1=2 subchannel), and still maintains the channel is idle.

S4. For j=1, let j←1, since b ₄ =0, w ₄ =2, then the primary user skips this channel (this channel contains 2 sub-channels, and the next channel starts from 1+2+1=4 sub-channels start to allocate);

S5. For j=2, since b ₃ =0w ₃ =13, the primary user skips the channel (this channel contains 13 sub-channels, therefore, it is equivalent to the primary user skipping 13 sub-channels, and the next channel starts from the first +2+13+1=17 sub-channels start to be allocated);

S6. For j=3, since b ₂ =0w ₂ =12, the primary user skips this channel (this channel contains 12 sub-channels, therefore, it is equivalent to the primary user skipping 12 sub-channels, and the next channel starts from 1+ 2+13+12+1=29 sub-channels start to allocate);

S7. For j=4, since b ₁ =0w ₁ =1, the primary user skips the channel (this channel contains 1 subchannel, therefore, it is equivalent to the primary user skipping 1 subchannel, and the next channel starts from 1+ 2+13+12+1+1=30 sub-channels start to allocate);

S8. For j=5, since b ₀ =1w ₀ =5, the primary user occupies the channel (this channel includes 5 sub-channels, therefore, it is equivalent to the primary user occupying 5 sub-channels).

So far, the analysis of the entire S _i =1 ¹ 0 ² 0 ¹³ 0 ¹² 1 ¹ 0 ⁵ is completed, and the bandwidth allocation of the primary user is completed. The allocated bandwidth capacity is 2 sub-channel bandwidths, which meets the current bandwidth requirement of the primary user R _d =2 . For the value of R _d equal to other integers within 0-15, according to the corresponding S _i , follow a similar process to allocate the bandwidth of the primary user.

When R _d =2, the spectrum occupancy status after the primary user bandwidth allocation is completed according to the weighted Huffman tree is shown in FIG. 4 .

(4) Secondary user channel sensing to obtain idle channels

From the root node of the weighted Huffman tree to the end of a leaf node, if the path passed through contains a branch with an occupancy state of 0, it means it is an idle channel, and a branch with an occupancy state of 1 means that the channel is already occupied; The bandwidth size is equal to the weight of the branch.

Taking R _d =2 as an example, the algorithm of secondary user channel sensing is described. Although the secondary user is not aware of the current spectrum resource occupancy status (as shown in Figure 4), the secondary user can estimate the statistical characteristics of the primary user's bandwidth demand based on the statistical characteristics of the primary user's traffic and the preset sub-channel bandwidth. characteristics, and construct a weighted Huffman tree according to the statistical characteristics. Without loss of generality, it is assumed that the secondary user and the primary user have the same weighted Huffman tree, so that the secondary user can gradually obtain the current channel occupancy status of the primary user through the channel sensing process according to the weighted Huffman tree. Its main steps are as follows:

S1. Starting from the root node of the current weighted Huffman tree, first confirm that the current node is not a leaf node, so detect the state of the first channel, the method is that the secondary user uses the channel sensing function to obtain the first channel of the first channel sub-channel states (because each channel contains at least one sub-channel), and the obtained occupancy state of the first sub-channel represents the state of the entire channel.

S2. According to the spectrum sensing result, since the current channel is in an occupied state, select the right branch of the current node in the weighted Huffman tree. The current branch weight is 1, so the secondary user needs to skip 1 sub-channel, and start the next round of detection from the 1st+1=2 sub-channel.

S3. According to the spectrum sensing result, since the current channel is in an idle state, select the left branch of the current node in the weighted Huffman tree. The current branch weight is 2, so the secondary user needs to skip 2 sub-channels, and start the next round of detection from the 1st+2+1=4th channel.

S4. According to the spectrum sensing result, since the current channel is in an idle state, select the left branch of the current node in the weighted Huffman tree, and reach the next node along the left branch. The current branch weight is 13, so the secondary user needs to skip 13 sub-channels, and start the next round of detection from the 1+2+13+1=17th channel.

S5. According to the spectrum sensing result, since the current channel is in an idle state, select the left branch of the current node in the weighted Huffman tree, and reach the next node along the left branch. The current branch weight is 12, so the secondary user needs to skip 12 sub-channels, and start the next round of detection from the 1+2+13+12+1=29th channel.

S6. According to the spectrum sensing result, since the current channel is in an occupied state, select the right branch of the current node in the weighted Huffman tree, and reach the next node along the right branch. The current branch weight is 1, so the secondary user needs to skip 1 sub-channel, and start the next round of detection from the 1+2+13+12+1+1=30th channel.

S7. According to the spectrum sensing result, since the current channel is in an idle state, select the left branch of the current node in the weighted Huffman tree, and reach the next node along the left branch. The current branch weight is 5, so the secondary user needs to skip 5 sub-channels.

S8. Since the current node is found to be a leaf node, the entire spectrum sensing process ends. During the entire sensing process, the secondary user sequentially discovers 4 idle channels containing 2, 13, 12, and 5 sub-channels respectively , so secondary users can use these 4 idle channels to transmit their own data.

The above-mentioned embodiment is a preferred embodiment of the present invention, but the embodiment of the present invention is not limited by the embodiment, and any other changes, modifications, substitutions and combinations made without departing from the spirit and principle of the present invention , simplification, all should be equivalent replacement methods, and are all included in the protection scope of the present invention.

Claims (8)

1. A cognitive radio channel dividing and distributing method based on a weighted Huffman tree is characterized in that the weighted Huffman tree is formed by adding a weight attribute to all nodes and branches and adding an occupation state attribute to all branches on the basis of the Huffman tree, and the added attributes meet the following conditions:

(a) The new attribute is independent of the original attributes of the nodes and the branches;

(b) The weight of the root node and each intermediate node is equal to the minimum value in the weights of the left sub-node and the right sub-node;

(c) The weights of the left branch and the right branch of the root node and each intermediate node are equal and are equal to the absolute value of the difference between the weights of the left sub-node and the right sub-node;

(d) The value of the newly added branch occupation state comprises an idle state and an occupation state, specifically, the idle state and the occupation state are distinguished by a left branch and a right branch respectively, the idle state of the channel is represented by the left branch, and the occupation state of the channel is represented by the right branch;

the method comprises the following steps:

firstly, dividing frequency spectrum resources available for a cognitive wireless communication system into a series of sub-channels; each channel is formed by aggregating a plurality of sub-channels; the primary user and the secondary user can use a plurality of channels to complete data transmission, and the divided sub-channels are assumed to have equal bandwidth;

on the basis, discretizing the specific bandwidth requirement of the master user aiming at the preset sub-channel bandwidth, and representing the discretized master user bandwidth requirement as the number of the occupied sub-channels by counting to obtain the probability distribution of the discretized master user bandwidth requirement;

then, the discretized main user bandwidth requirement is used as a weight attribute of the leaf node, the frequency of the bandwidth requirement is used as a probability attribute of the leaf node, and a weighted Huffman tree is constructed based on the probability distribution of the leaf node, namely: the probability of the root node and each intermediate node is equal to the sum of the probabilities of the left sub-node and the right sub-node; the weight of the root node and each intermediate node is equal to the minimum value of the weights of the left sub-node and the right sub-node; the left and right branch weights of the root node and each intermediate node are equal and both equal to the absolute value of the difference between the weights of its left and right child nodes.

2. The cognitive radio channel division and allocation method according to claim 1, wherein each leaf node of the obtained weighted huffman tree represents a specific primary user bandwidth requirement, and the weight of the leaf node represents the value of the primary user bandwidth requirement; the total number of the leaf nodes is equal to the total number of all possible specific values required by the bandwidth of the master user;

the path from the root node to the leaf node represents a channel division and channel allocation scheme corresponding to the bandwidth requirement of the primary user represented by the leaf node; the number of branches included in the path is equal to the total number of channels included in the channel division scheme, each branch in the path corresponds to a specific channel, the weight of the branch represents the bandwidth of the channel, and the occupation state of the branch represents whether the channel is used in the channel allocation scheme;

the path from the root node to any one intermediate node represents a partial channel division and allocation scheme shared by all subordinate leaf nodes of the intermediate node, and the weight of the intermediate node represents the bandwidth provided by the shared part for the primary user.

3. The cognitive radio channel division and allocation method according to claim 1, wherein the channels to which the method is applied include frequency domain channels, spatial domain channels and combinations thereof.

4. A method for allocating a primary user channel based on a weighted Huffman tree is characterized in that,

the weighted Huffman tree is characterized in that a weight attribute is added to all nodes and branches on the basis of the Huffman tree, an occupation state attribute is added to all branches, and the added attributes meet the following conditions:

(a) The new attribute is independent of the original attributes of the nodes and the branches;

(b) The weight of the root node and each intermediate node is equal to the minimum value of the weights of the left sub-node and the right sub-node;

(c) The weights of the left branch and the right branch of the root node and each intermediate node are equal and are equal to the absolute value of the difference between the weights of the left sub-node and the right sub-node;

(d) The value of the newly added branch occupation state comprises an idle state and an occupation state, specifically, the idle state and the occupation state are distinguished by a left branch and a right branch respectively, the idle state of the channel is represented by the left branch, and the occupation state of the channel is represented by the right branch;

the method comprises the following steps:

obtaining a channel allocation scheme of a master user under a given bandwidth requirement according to the weighted Huffman tree;

allocating channels for the master users according to the channel allocation scheme;

each given primary user bandwidth requirement has a unique channel allocation scheme corresponding to the bandwidth requirement; the channel allocation scheme describes a complete path from the root node to a leaf node corresponding to the bandwidth requirement; the method specifically includes a branch sequence forming the path, an occupation state of each branch included in the branch sequence and a bandwidth of a channel represented by the branch, and a set of all channel allocation schemes forms a primary user channel allocation mode.

5. The primary user channel allocation method according to claim 4, further characterized in that the method for obtaining the primary user channel allocation pattern is: and selecting leaf nodes with the same weight according to the bandwidth requirement of the main user, and then tracing the leaf nodes to the root node along the weighted Huffman tree, wherein the passed path represents a main user channel allocation scheme meeting the bandwidth requirement.

6. A primary user channel allocation method as in claim 4, further characterized by allocating a channel for a given primary user bandwidth requirement in accordance with a primary user channel allocation scheme, the primary user channel allocation scheme being represented by a weighted bit sequence comprising a plurality of weighted bits, each bit representing an occupancy state of the channel, the weight of a bit representing a bandwidth size of the channel;

the specific steps of channel allocation include: repeatedly executing the following steps from the leftmost first weighted bit to the rightmost last weighted bit of the weighted bit sequence corresponding to the given main user channel allocation scheme: if the value of the bit is 0, the channel is indicated to be occupied by a master user, and all sub-channels contained in the channel are skipped; if the value of the bit is 1, the channel is occupied by a primary user, and all sub-channels contained in the channel are allocated to the primary user for data transmission.

7. A secondary user channel sensing method based on weighted Huffman tree is used for obtaining the occupation state of a main user channel and selecting an idle channel from the occupation state for the data transmission of a secondary user, and is characterized in that:

the weighted Huffman tree is characterized in that a weight attribute is added to all nodes and branches on the basis of the Huffman tree, an occupation state attribute is added to all branches, and the added attributes meet the following conditions:

(a) The new attribute is independent of the original attributes of the nodes and the branches;

(b) The weight of the root node and each intermediate node is equal to the minimum value of the weights of the left sub-node and the right sub-node;

(c) The weights of the left branch and the right branch of the root node and each intermediate node are equal and are equal to the absolute value of the difference between the weights of the left sub-node and the right sub-node;

(d) The value of the newly added branch occupation state comprises an idle state and an occupation state, specifically, the idle state and the occupation state are distinguished by a left branch and a right branch respectively, the idle state of the channel is represented by the left branch, and the occupation state of the channel is represented by the right branch;

the method comprises the following steps:

sequentially sensing the occupation states of channels represented by branches of the current node from the root node of the weighted Huffman tree; if the state of the channel is 'occupied', the channel is indicated to be used by the primary user, therefore, the secondary user needs to skip all sub-channels contained in the channel, and selects the right sub-node of the current node as a subsequent node to continue the state perception of the next channel; if the channel state is idle, marking the channel as idle channel to enable the channel to be used by secondary users for data transmission, at the moment, selecting the left subnode of the current node as a subsequent node, and continuing the state perception of the next channel; the sensing process terminates when a leaf node is encountered.

8. The secondary user channel aware method of claim 7, further characterized by: the secondary user can perceive any one of the sub-channel states belonging to a given channel to know the occupancy state of the channel.

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