CN109005589B - Method and equipment for spectrum resource allocation - Google Patents

Method and equipment for spectrum resource allocation Download PDF

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CN109005589B
CN109005589B CN201810717388.5A CN201810717388A CN109005589B CN 109005589 B CN109005589 B CN 109005589B CN 201810717388 A CN201810717388 A CN 201810717388A CN 109005589 B CN109005589 B CN 109005589B
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CN109005589A (en
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韩韧
高阳
杨晖
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University of Shanghai for Science and Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The method comprises the steps of determining a primary network and a secondary network corresponding to the primary network in a wireless network; determining the SINR of a primary user working on the channel and the SINR of a secondary user working on the same channel according to the information of the current main network allocable channel; determining power consumption efficiency corresponding to the secondary network according to the current transmitting power of a transmitter in the secondary link and the maximum transmitting power of the transmitter, and determining the total data rate of the wireless network according to the SINR of the primary user and the SINR of the secondary user; and optimizing the power consumption efficiency and the total data rate based on a multi-target spectrum and power combined distribution model of the artificial immune system, and distributing spectrum resources according to an optimization result. Therefore, the optimization of the cognitive wireless network performance is realized, and good network performance is obtained.

Description

Method and equipment for spectrum resource allocation
Technical Field
The present application relates to the field of communication networks, and in particular, to a method and a device for spectrum resource allocation.
Background
The cognitive radio technology can allocate available spectrum resources to users to achieve efficient utilization of the spectrum resources, and therefore the spectrum allocation technology is an important component of cognitive radio. The spectrum allocation technology can allocate the current available frequency band to the users according to the number of the users needing to access the network and the service requirements of the users, and enables the cognitive users to share the spectrum resources in a reasonable and fair way on the premise of not causing excessive interference to authorized users. Since spectrum allocation can directly affect network performance indexes, cognitive radio generally acquires a suitable spectrum allocation scheme according to the performance requirements of users. However, performance indexes in the network are mutually restricted, and simply optimizing one performance index may reduce performance in other aspects. Users also seek to optimize not only one performance, but often wish to consider the balance of multiple performances.
Disclosure of Invention
An object of the present application is to provide a method and an apparatus for spectrum resource allocation, which solve the current problem of singly optimizing a certain network performance and the problem of difficult search of an optimal solution by the current optimization algorithm.
According to an aspect of the present application, there is provided a method for spectrum resource allocation, the method comprising:
determining a main network and a secondary network corresponding to the main network in a wireless network, wherein the main network comprises information of all main links of a main user and information of an allocable channel of the current main network, and the secondary network comprises information of all secondary links of a secondary user and information of the allocable channel of the corresponding main network;
determining the SINR of a primary user working on the channel and the SINR of a secondary user working on the same channel according to the information of the current main network allocable channel;
determining power consumption efficiency corresponding to the secondary network according to the current transmitting power of a transmitter in the secondary link and the maximum transmitting power of the transmitter, and determining the total data rate of the wireless network according to the SINR of the primary user and the SINR of the secondary user;
and optimizing the power consumption efficiency and the total data rate based on a multi-target spectrum and power combined distribution model of the artificial immune system, and distributing spectrum resources according to an optimization result.
Further, determining the SINR of the primary user working on the channel and the SINR of the secondary user working on the same channel according to the information of the currently available channel of the primary network, including:
determining the expected receiving power of a main user when the main link works on the channel according to the information of the current main network allocable channel;
determining the SINR of a primary user working on the channel according to the expected receiving power;
and determining the SINR of the secondary user according to the interference of the primary link working on the channel to the secondary link on the same channel and the interference of all the secondary links working on the channel to the current link.
Further, determining an expected received power of a primary user when the primary link operates on the channel according to the information of the current primary network allocable channel comprises:
determining a transmitter and a receiving master user of the master link according to the information of the current master network allocable channel;
calculating the path loss from the transmitter of the main link to the receiving main user;
and determining the expected receiving power of a main user when the main link works in the channel according to the path loss and the transmitting power of the transmitter.
Further, determining the total data rate of the wireless network according to the SINR of the primary user and the SINR of the secondary user includes:
and determining the total data rate of the wireless network according to the SINR of the primary user, the SINR of the secondary user and the bandwidth of the shared channel of the primary link.
Further, the spectrum resource allocation according to the optimization result includes:
determining an SINR threshold of a main link of the main user and an SINR threshold of a secondary link of the secondary user according to an optimization result and the transmission performance requirement of the user in the wireless network;
and performing spectrum resource allocation according to the SINR threshold of the primary link and the SINR threshold of the secondary link.
Further, the multi-target spectrum and power joint allocation model of the artificial immune system comprises:
encoding a target frequency spectrum in the artificial immune system to generate an initial antibody population in an action region, and determining a dominant antibody population according to an iteration algebra and the initial antibody population;
and circularly executing the following steps until the termination condition is met:
determining dominant antibodies in the dominant antibody population, and putting the dominant antibodies into a temporary dominant population to select a dominant population;
judging whether a termination condition is met, if not, increasing the iteration algebra by 1, selecting an active population from the dominant population, and if so, stopping searching;
cloning the movable population to obtain a cloned population, and recombining and hyper-differentiating the cloned population to obtain a new population;
updating the dominant antibody population according to the new population and the dominant population.
Further, placing the dominant antibodies into a temporary dominant population to select a dominant population, comprising:
judging whether the size of the temporary dominant population is smaller than N, if so, taking the temporary dominant population as a dominant population, wherein N is the size of the initial antibody population;
if not, calculating the crowding distance of all individuals in the temporary dominant population, sorting the individuals in a descending order according to the crowding distance, and selecting the population determined by the first N individuals as the dominant population.
Further, selecting an active population from the dominant population, comprising:
judging whether the size of the dominant population is smaller than N A If yes, the dominant population is used as an active population, wherein N is A Is the maximum size of the active population;
if not, calculating the crowding distance of all individuals in the dominant population, sorting the individuals in a descending order according to the crowding distance, and selecting the top N A The individual defined population is used as the active population.
According to yet another aspect of the present application, there is also provided a computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to implement the method as described above.
According to another aspect of the present application, there is also provided an apparatus for spectrum resource allocation, the apparatus comprising:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method as previously described.
Compared with the prior art, the method and the device have the advantages that the main network and the corresponding secondary networks in the wireless network are determined, wherein the main network comprises information of all main links of a main user and information of the current main network allocable channels, and the secondary networks comprise information of all secondary links of a secondary user and information of the corresponding main network allocable channels; determining the SINR of a primary user working on the channel and the SINR of a secondary user working on the same channel according to the information of the current main network allocable channel; determining power consumption efficiency corresponding to the secondary network according to the current transmitting power of a transmitter in the secondary link and the maximum transmitting power of the transmitter, and determining the total data rate of the wireless network according to the SINR of the primary user and the SINR of the secondary user; and optimizing the power consumption efficiency and the total data rate based on a multi-target spectrum and power combined distribution model of an artificial immune system, and distributing spectrum resources according to an optimization result. Therefore, on the premise of simultaneously considering spectrum allocation and power control, two performance indexes of network throughput and power consumption efficiency are used as targets to perform modeling solution, and a multi-objective optimization problem is constructed. And an effective heuristic algorithm is used for solving, and a multi-resource and multi-target distribution algorithm is provided based on an artificial immune system. And constructing the frequency spectrum and power distribution scheme of the network into an antibody in an immune system during solving, and obtaining an optimal solution set through iterative operation. The optimization of the cognitive wireless network performance is realized, and good network performance is obtained.
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Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:
fig. 1 illustrates a flow diagram of a method for spectrum resource allocation provided in accordance with an aspect of the present application;
FIG. 2 shows a schematic diagram of a cognitive wireless network model including several communication links in an embodiment of the present application;
FIG. 3 shows a schematic structural diagram of antibody encoding in one embodiment of the present application;
FIG. 4 is a flow diagram illustrating a multi-objective spectrum and power joint assignment model of an artificial immune system according to an embodiment of the present application.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The present application is described in further detail below with reference to the attached figures.
In a typical configuration of the present application, the terminal, the device serving the network, and the trusted party each include one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
Fig. 1 shows a flowchart of a method for spectrum resource allocation according to an aspect of the present application, the method comprising: step S11 to step S14, wherein,
in step S11, a primary network and a secondary network corresponding to the primary network in the wireless network are determined, wherein the primary network includes information of all primary links of a primary user and information of an allocable channel of the current primary network, and the secondary network includes information of all secondary links of a secondary user and information of an allocable channel of the corresponding primary network; in an embodiment of the present application, as shown in fig. 2, which is a schematic diagram of a cognitive radio network model including a plurality of communication links, a communication Link in a network in which a Primary user serves as a receiving end is called a Primary Link (Primary Link), a communication Link in which a Secondary user serves as a receiving end is called a Secondary Link (Secondary Link), and they coexist in an area. All primary users in the network are served by respective transmitters and their locations are fixed, while in the secondary link, one transmitter serves only one secondary user and is randomly distributed in the area. In fig. 2, the main link 1 operates at m 1 There are secondary links 1 and 2 with which data is transmitted on the same channel. Thus, the main link receiver
Figure BDA0001717863310000061
At the receiving transmitter->
Figure BDA0001717863310000062
At the same time as the signal, a secondary link transmitter is received>
Figure BDA0001717863310000063
And &>
Figure BDA0001717863310000064
Of the signal of (1). Similarly, the secondary link receiver->
Figure BDA0001717863310000065
And &>
Figure BDA0001717863310000066
When receiving the signal of each transmitter, the receiver is not only interfered by the transmitter of the other party, but also is received by the receiver-link transmitter->
Figure BDA0001717863310000067
The interference of (2). Considering that a primary user network and a cognitive wireless network exist in a mixed mode, the whole network is divided into a communication network containing primary users and a communication network containing secondary users, which are respectively marked as a primary network (v) and a secondary network (u), and sets M, PL and SL are defined, wherein M is a set of available channels of the current network, and PL and SL respectively represent a set of all primary links in the primary network and a set of all secondary links in the secondary network.
Next, in step S12, determining the SINR of the primary user working on the channel and the SINR of the secondary user working on the same channel according to the information of the current primary network assignable channel; in the current network model, the transmission performance of the primary and secondary links is affected by the transmit power of all users in the current frequency band, the primary link is interfered by the secondary link in the same frequency band during transmission, and conversely, the secondary link is also affected by the primary link in the same frequency band and is also interfered by other secondary links in the same frequency band. Therefore, in order to ensure the overall performance of the network, the transmission quality of all links in the network needs to be evaluated, and in the wireless network, the SINR is used for measuring the quality of the received signal. In the method, the SINR of the primary user working on the channel m is calculated firstly, and then the SINR of the secondary user is calculated, so that when a network carries out spectrum allocation and power control, normal communication of the primary user is guaranteed, and interference among the secondary users working on the same channel is guaranteed to be as low as possible. Wherein the SINR is a signal to interference plus noise ratio.
Subsequently, in step S13, determining power consumption efficiency corresponding to the secondary network according to the current transmission power of the transmitter in the secondary link and the maximum transmission power of the transmitter, and determining a total data rate of the wireless network according to the SINR of the primary user and the SINR of the secondary user; in an embodiment of the present application, a spectrum access manner of Underlay is adopted, and a secondary user can access an authorized frequency band being used by a primary user. And the interference of the secondary user to the primary user is within a tolerable range of the primary user. At this time, the transmission power of the secondary link is a main cause of network interference. In order to obtain balanced optimization among multiple network performances, the power consumption efficiency corresponding to the secondary network and the total data rate of the network can be calculated, so that the performance indexes can be optimized in the subsequent process, and therefore the communication performance of the secondary user can be guaranteed while serious interference to the primary user is avoided. In a wireless communication network, power control can not only reduce interference among network users, but also save power consumption of network equipment, and provide guarantee for continuous operation of the equipment. In the embodiment of the application, the secondary link transmitter is assumed to be capable of adjusting the transmission power of the secondary link transmitter downwards on the basis of the maximum power of the secondary link transmitter. The power efficiency is the ratio of the power saved on the basis of the maximum power to the maximum power. As shown in the following equation:
Figure BDA0001717863310000071
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0001717863310000072
represents the current transmit power of the transmitter in the secondary link sl, <' >>
Figure BDA0001717863310000073
Representing the maximum transmit power of the transmitter.
It is understood that in the embodiment of the present application, the throughput is defined as the total Data Rate (Data Rate) of the entire network, i.e., the sum of the Data rates obtained by all the primary links and the secondary links.
Finally, in step S14, the power consumption efficiency and the total data rate are optimized based on a multi-target spectrum and power joint allocation model of the artificial immune system, and spectrum resources are allocated according to an optimization result. Here, the spectrum resource allocation includes allocation of spectrum and power, and an increase in the transmission power of the secondary link reduces the power consumption efficiency of the network, but does not necessarily increase the capacity of the network, because the interference of the network is more serious as the power is increased. Therefore, the power consumption efficiency and the network capacity are two conflicting targets, are suitable for optimization by using a multi-target optimization method, and can be defined as a multi-target optimization problem, the defined multi-target optimization problem is complex, a large amount of calculation cost needs to be consumed when searching for a spectrum and power allocation scheme, and the spectrum and power allocation scheme needs to be given quickly and efficiently according to the current environment and performance requirements. An optimized solution is obtained through the multi-target frequency spectrum and power combined distribution model based on the artificial immune system.
In an embodiment of the present application, in step S12, an expected received power of a primary user when the primary link operates on the channel is determined according to information of the current primary network allocable channel; determining the SINR of a primary user working on the channel according to the expected receiving power; and determining the SINR of the secondary user according to the interference of the primary link working on the channel to the secondary link on the same channel and the interference of all the secondary links working on the channel to the current link. Further, the expected receiving power of a primary user when the primary link works on the channel is determined according to the information of the current primary network allocable channel, and the expected receiving power is determined by the following method: determining a transmitter and a receiving master user of the master link according to the information of the current master network allocable channel; determining a transmitter and a receiving master user of the master link according to the information of the current master network allocable channel; calculating the path loss from the transmitter of the main link to the receiving main user; and determining the expected receiving power of the main user when the main link works in the channel according to the path loss and the sending power of the transmitter.
Here, when the primary link pl operates on channel m, the expected received power of the primary user:
Figure BDA0001717863310000081
wherein
Figure BDA0001717863310000082
And &>
Figure BDA0001717863310000083
Represents a transmitter and a receiving user, respectively, of a main link pl, and &>
Figure BDA0001717863310000084
Representing the transmit power of the transmitter. />
Figure BDA0001717863310000085
Then it indicates that it is asserted from the transmitter>
Figure BDA0001717863310000086
To its receiving user->
Figure BDA0001717863310000087
Path loss of (2):
Figure BDA0001717863310000088
wherein k and a are a path loss constant and a path loss exponent, respectively,
Figure BDA0001717863310000089
then it indicates slave->
Figure BDA00017178633100000810
To/>
Figure BDA00017178633100000811
The distance of (c).
In the present embodiment, it is assumed that all the main links in the current area operate on different communication channels. In calculating the received power of the undesired signal, in addition to the thermal noise of the receiving device, only the sum of the interference of all secondary link transmitters operating on channel m to the primary user needs to be considered:
Figure BDA0001717863310000091
/>
where I (m) denotes that the secondary link sl operates on channel m.
Determining the SINR of the primary user working on the channel m as follows according to the expected receiving power of the primary user and the sum of the interference of all secondary link transmitters working on the channel m to the primary user:
Figure BDA0001717863310000092
here, the constant No. indicates the thermal noise of the device. It is understood that in this formula
Figure BDA0001717863310000093
Determines the master user->
Figure BDA0001717863310000094
The strength of the signal that can be received. And->
Figure BDA0001717863310000095
Then a total disturbance to which the user is subjected is defined, wherein>
Figure BDA0001717863310000096
Representing the sum of the interference to it from all secondary links using the same channel as the user.
When the network performs spectrum allocation and power control, it is necessary to ensure normal communication of the primary user and also to ensure as low interference as possible between secondary users operating on the same channel. The SINRs of all secondary users need to be taken into account. When calculating the SINR of the secondary user, all signals of the primary link and the secondary link operating in the same channel are interference to the current user, and need to be considered separately. First, consider the interference caused by the primary link pl on the secondary link sl working on channel m at the same time:
Figure BDA0001717863310000097
similarly, the interference caused by all other secondary links operating on channel m to the current secondary link can be defined as:
Figure BDA0001717863310000098
since the expected signal received power of this secondary user can be defined as:
Figure BDA0001717863310000099
the SINR of the user can be obtained by the following formula:
Figure BDA00017178633100000910
in summary, in the case that the primary and secondary users exist in the network at the same time, the spectrum allocation and the power control have a great influence on the performance of the network. Therefore, in order to ensure the overall performance of the network, the goals that the network needs to achieve need to be set according to the network requirements.
In an embodiment of the present application, the total data rate of the wireless network may be determined according to the SINR of the primary user, the SINR of the secondary user, and the bandwidth of the shared channel of the primary link. Here, throughput is defined as the total data rate of the entire network, i.e., the sum of the data rates obtained by all primary and secondary links. The total data rate may depend on the bandwidth of the primary and secondary link shared channels and the current communication environment, such as fading, interference, etc. The data rate formulas of the primary and secondary links are as follows:
C pl ＝Wlog 2 (1+SINR pl (m))
C sl ＝Wlog 2 (1+SINR sl (m))
wherein, C pl And C sl Representing the data rate size of the primary link pl and the secondary link sl, respectively. W denotes the bandwidth of the shared channel, and in the embodiment of the present application, the bandwidth of all the channels participating in allocation is the same.
Through the above calculation, the total data rate of the network is obtained as follows:
Figure BDA0001717863310000101
/>
in practical applications, the increase of the transmission power of the secondary link will reduce the power consumption efficiency of the network, but will certainly increase the capacity of the network, and the interference of the network is more serious with the increase of the power. Therefore, the power consumption efficiency and the capacity are two conflicting targets, and are suitable for optimization by using a multi-objective optimization method, and the power consumption efficiency and the network capacity can be defined as the following multi-objective optimization problem:
Max f 1
Max f 2
s.t.
SINR pl (m)≥β pl ,pl∈PL
SINR sl (m)≥β sl ,sl∈SL
interference caused by environmental noise or other radio transmissions can reduce the SINR of the receiver and affect network communication stability, and therefore, in order to guarantee the service quality of the user, the SINR is generally required to be greater than a certain threshold. Therefore, the constraint condition of the communication link on SINR, beta, is added in the multi-objective optimization problem pl And beta sl Respectively representing SINR thresholds for primary link pl and secondary link sl. When spectrum resource allocation is carried out according to the optimization result, determining the SINR threshold value of the main link of the main user and the SINR threshold value of the secondary link of the secondary user according to the optimization result; and performing spectrum resource allocation according to the SINR threshold of the primary link and the SINR threshold of the secondary link.
In an embodiment of the present application, an improved non-inferior neighborhood immune algorithm (NNIA) is selected to solve the above multi-objective optimization problem, where the improved non-inferior neighborhood immune algorithm is applicable to a multi-objective spectrum and power joint allocation model of the artificial immune system, and when the power consumption efficiency and the total data rate are optimized based on the multi-objective spectrum and power joint allocation model of the artificial immune system, the following steps are specifically performed: coding a target frequency spectrum in the artificial immune system to generate an initial antibody population in an action area, and determining a dominant antibody population according to an iterative algebra and the initial antibody population; and circularly executing the following steps until the termination condition is met:
determining dominant antibodies in the dominant antibody population, and putting the dominant antibodies into a temporary dominant population to select a dominant population; judging whether a termination condition is met, if not, increasing the iteration algebra by 1, selecting an active population from the dominant population, and if so, stopping searching; cloning the active population to obtain a cloned population, and recombining and hyper-transforming the cloned population to obtain a new population; updating the dominant antibody population according to the new population and the dominant population.
In an embodiment of the present application, it is first necessary to encode the antibody in the immune algorithm, the encoding structure is shown in fig. 3, and when encoding the channel allocation scheme, a vector C is defined i Expressed as: c i ＝(c 1 ,c 2 ,…,c SL ) Wherein c is i Belongs to M and represents a channel number distributed and obtained by a secondary link i, and the value range of i is [1, | SL-]Is an integer of (1). In addition, power allocation is also needed while considering secondary link channel allocation. In the same way, a vector P is defined i ＝(p 1 ,p 2 ,…,p |SL| ) Wherein p is i Indicating transmitters in secondary link i
Figure BDA0001717863310000111
The value range of i is also [1, | SL | ]]Is an integer of (1).
In a preferred embodiment of the present application, as shown in fig. 4, the specific steps are as follows:
s1: performing initialization of antibody population, and randomly generating initial antibody population B with size N in the action region according to the encoding mode shown in FIG. 2 0 Order dominant antibody population D 0 =0, active population A 0 =0 and clonal population C 0 =0; let iteration algebra t =0 at the same time.
S2: updating the dominant antibody population, wherein the dominant antibody is placed into a temporary dominant population to select the dominant population, specifically: judging whether the size of the temporary dominant population is smaller than N, if so, judging whether the size of the temporary dominant population is smaller than NThe temporary dominant population is used as a dominant population, wherein N is the size of the initial antibody population; if not, calculating the crowding distance of all individuals in the temporary dominant population, sorting the individuals in a descending order according to the crowding distance, and selecting the population determined by the first N individuals as the dominant population. Determination of antibody population B t And putting all dominant antibodies into the temporary dominant population DT t+1 In, if DT t+1 Is smaller than N, order D t+1 ＝DT t+1 . Otherwise, calculating DT t+1 The crowding distances of all individuals in the system are sorted from large to small according to the crowding distance values, and the first N individuals are selected to form D t+1 。
S3: end condition if t ≧ G max If yes, stopping searching; otherwise, t = t +1.
S4: selecting non-dominated neighbors, wherein the non-dominated individuals are dominant individuals, selecting is carried out through the neighbors, an active population is selected from the dominant population, and specifically, whether the size of the dominant population is smaller than N or not is judged A If yes, the dominant population is used as an active population, wherein N is A Is the maximum size of the active population; if not, calculating the crowding distance of all individuals in the dominant population, sorting the individuals in a descending order according to the crowding distance, and selecting the top N A The individual defined population is used as the active population. Here, if D is t Is smaller than the maximum size N of the active population A Let A t ＝D t (ii) a Otherwise, calculate D t The crowding distances of all individuals in the tree are sorted in descending order according to the crowding distance value, and the top N is selected A Individual formed active population A t . The selection procedure here tends to have dominant antibodies with high crowding distances, and the implementation of the dominant population as the outer population in the present example implements the elite retention strategy. And after the selected individuals are subjected to operations such as later cloning, recombination, mutation and the like, namely heuristic search is carried out, more solutions in a sparse area can be obtained.
S5: proportional cloning, for A t Performing proportional cloning operation, and obtaining clone speciesGroup C t . Proportional clones will replicate more times for individuals with larger crowding distance values, so that sparsely distributed areas of individuals on the Pareto (Pareto) front will have more opportunities to be searched.
S6: recombination and hypermutation, on clonal population C t Recombination and hypervariability are carried out to give a new population C' t To avoid the problem of falling into a locally optimal solution.
S7: antibody populations were pooled by combination of C' t And D t Obtaining the dominant population B t Then, go to step S2.
When the number of dominant antibodies exceeds the upper limit of the number of the specified population and the size of the dominant population is larger than the maximum size of the active population, it is necessary to select the dominant antibodies by the crowding distance, reduce the size of the population, and select the active antibodies.
In the embodiment of the application, when selecting individuals, a small number of non-dominant individuals with large crowding distance tend to be selected as active antibodies in the algorithm, then excellent individuals are replicated through proportional cloning to form a clonal population, and through the adopted recombination and mutation operations, the search of sparse areas in the current Pareto (Pareto) frontier is strengthened, so that the solution of the solution set is uniformly spread to the whole Pareto frontier.
According to the method, on the premise of simultaneously considering spectrum allocation and power control, two performance indexes of network throughput and power consumption efficiency are used as targets to perform modeling solution, and a multi-target optimization problem based on a Pareto optimal concept is constructed. And to guarantee the most basic transmission quality per link, constraints on SINR are added to them. Because the complexity of the problem is high, an effective heuristic algorithm needs to be used for solving, and then a multi-resource multi-target allocation algorithm is provided based on an artificial immune system. And constructing the frequency spectrum and power distribution scheme of the network into an antibody in an immune system during solving, and obtaining an optimal solution set through iterative operation.
Furthermore, according to yet another aspect of the present application, there is provided a computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to implement the method as described above.
In an embodiment of the present application, according to another aspect of the present application, there is also provided an apparatus for spectrum resource allocation, the apparatus including:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method as previously described.
For example, the computer readable instructions, when executed, cause the one or more processors to:
determining a main network and a secondary network corresponding to the main network in a wireless network, wherein the main network comprises information of all main links of a main user and information of an allocable channel of the current main network, and the secondary network comprises information of all secondary links of a secondary user and information of the allocable channel of the corresponding main network;
determining the SINR of a primary user working on the channel and the SINR of a secondary user working on the same channel according to the information of the current main network allocable channel;
determining power consumption efficiency corresponding to the secondary network according to the current transmitting power of a transmitter in the secondary link and the maximum transmitting power of the transmitter, and determining the total data rate of the wireless network according to the SINR of the primary user and the SINR of the secondary user;
and optimizing the power consumption efficiency and the total data rate based on a multi-target spectrum and power combined distribution model of the artificial immune system, and distributing spectrum resources according to an optimization result.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the steps or functions described above. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Further, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
Additionally, some portions of the present application may be applied as a computer program product, such as computer program instructions, which, when executed by a computer, may invoke or provide the method and/or solution according to the present application through the operation of the computer. Program instructions which invoke the methods of the present application may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium and/or stored within a working memory of a computer device operating in accordance with the program instructions. An embodiment according to the present application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a solution according to the aforementioned embodiments of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.

Claims (8)

1. A method for spectrum resource allocation, wherein the method comprises:
determining a main network and a secondary network corresponding to the main network in a wireless network, wherein the main network comprises information of all main links of a main user and information of an allocable channel of the current main network, and the secondary network comprises information of all secondary links of a secondary user and information of the allocable channel of the corresponding main network;
determining the SINR of a primary user working on the channel and the SINR of a secondary user working on the same channel according to the information of the current main network allocable channel;
determining power consumption efficiency corresponding to the secondary network according to the current transmitting power of a transmitter in the secondary link and the maximum transmitting power of the transmitter, and determining the total data rate of the wireless network according to the SINR of the primary user and the SINR of the secondary user;
optimizing the power consumption efficiency and the total data rate based on a multi-target spectrum and power combined distribution model of an artificial immune system, and distributing spectrum resources according to an optimization result;
the multi-target spectrum and power joint distribution model of the artificial immune system comprises the following steps:
encoding a target frequency spectrum in the artificial immune system to generate an initial antibody population in an action region, and determining a dominant antibody population according to an iteration algebra and the initial antibody population;
and circularly executing the following steps until the termination condition is met:
determining dominant antibodies in the dominant antibody population, and putting the dominant antibodies into a temporary dominant population to select a dominant population;
judging whether a termination condition is met, if not, increasing the iteration algebra by 1, selecting an active population from the dominant population, and if so, stopping searching;
cloning the active population to obtain a cloned population, and recombining and hyper-transforming the cloned population to obtain a new population;
updating the dominant antibody population according to the new population and the dominant population;
the method for allocating the spectrum resources according to the optimization result comprises the following steps:
determining an SINR threshold of a main link of the main user and an SINR threshold of a secondary link of the secondary user according to an optimization result and the transmission performance requirement of the user in the wireless network;
and performing spectrum resource allocation according to the SINR threshold of the primary link and the SINR threshold of the secondary link.
2. The method of claim 1, wherein determining the SINR of a primary user operating on the channel and the SINR of a secondary user operating on the same channel based on information about the current primary network allocable channel comprises:
determining the expected receiving power of a main user when the main link works on the channel according to the information of the current main network allocable channel;
determining the SINR of a primary user working on the channel according to the expected receiving power;
and determining the SINR of the secondary user according to the interference of the primary link working on the channel to the secondary link on the same channel and the interference of all the secondary links working on the channel to the current link.
3. A method according to claim 2, wherein determining an expected receive power of a primary user with the primary link operating on the channel based on information of the current primary network allocable channel comprises:
determining a transmitter and a receiving master user of the master link according to the information of the current master network allocable channel;
calculating the path loss from the transmitter of the main link to the receiving main user;
and determining the expected receiving power of a main user when the main link works in the channel according to the path loss and the transmitting power of the transmitter.
4. The method of claim 1, wherein determining the total data rate of the wireless network as a function of the SINR of the primary user and the SINR of the secondary user comprises:
and determining the total data rate of the wireless network according to the SINR of the primary user, the SINR of the secondary user and the bandwidth of the shared channel of the primary link.
5. The method of claim 1, wherein placing the dominant antibodies into a temporary dominant population to select a dominant population comprises:
judging whether the size of the temporary dominant population is smaller than N, if so, taking the temporary dominant population as a dominant population, wherein N is the size of the initial antibody population;
if not, calculating the crowding distance of all individuals in the temporary dominant population, sorting the individuals in a descending order according to the crowding distance, and selecting the population determined by the first N individuals as the dominant population.
6. The method of claim 1, wherein selecting an active population from the dominant population comprises:
judging whether the size of the dominant population is smaller than NA, if so, taking the dominant population as an active population, wherein the NA is the maximum size of the active population;
if not, calculating the crowding distances of all individuals in the dominant population, sorting the individuals in a descending order according to the crowding distances, and selecting the population determined by the first NA individuals as an activity population.
7. A computer readable medium having computer readable instructions stored thereon which are executable by a processor to implement the method of any one of claims 1 to 6.
8. An apparatus for spectrum resource allocation, wherein the apparatus comprises:
one or more processors; and
a memory having computer-readable instructions stored thereon that, when executed, cause the processor to perform the operations of the method of any of claims 1 to 6.
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