CN107911823B - Multi-channel anti-policy manipulated spectrum allocation method - Google Patents

Multi-channel anti-policy manipulated spectrum allocation method Download PDF

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CN107911823B
CN107911823B CN201710945302.XA CN201710945302A CN107911823B CN 107911823 B CN107911823 B CN 107911823B CN 201710945302 A CN201710945302 A CN 201710945302A CN 107911823 B CN107911823 B CN 107911823B
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CN107911823A (en
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董学文
杨晓宙
王永智
张涛
卢笛
张琛
李光夏
徐扬
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Xidian University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
    • H04W16/10—Dynamic resource partitioning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/391—Modelling the propagation channel

Abstract

The invention belongs to the technical field of cognitive radio, and discloses a multi-channel strategy-prevention operation spectrum allocation method, a computer program and a computer. The method fully considers the factors of the secondary user in spectrum allocation, such as flexible demand and flexible quotation function on a spectrum channel, signal-to-noise interference and the like, simultaneously considers the maximization of the spectrum utilization rate and the requirement of strategy manipulation prevention of the secondary user, and carries out detailed analysis and design on a spectrum auction mechanism. The method provided by the invention is easy to realize and convenient to expand, and is closer to practical application compared with the frequency spectrum auction method already provided; has higher distribution efficiency and fair effect.

Description

Multi-channel anti-policy manipulated spectrum allocation method
Technical Field
The invention belongs to the technical field of cognitive radio, and particularly relates to a multi-channel anti-policy operation spectrum allocation method, a computer program and a computer.
Background
In recent years, with the advent of software-defined radios (SDR) and the development of wireless communication devices, the spectrum shortage problem has become more and more severe. Traditional wireless spectrum allocation is statically allocated to users by governments according to purposes, so that wireless spectrum resources cannot be fully utilized, resource utilization rate is greatly reduced, and spectrum resources are greatly wasted. To meet the growing spectrum cravings for wireless devices, spectrum owners (primary users) are encouraged to lease licensed spectrum to unlicensed devices and users (secondary users), resulting in the emergence of the secondary market for wireless spectrum. Auction theory is considered a very popular tool for the allocation of wireless spectrum due to issues related to efficiency and fairness in the spectrum allocation process. A number of auction-based wireless spectrum allocation machines have been proposed in recent years; the utilization rate of the frequency spectrum is improved to a certain extent, but the strategy manipulation prevention and other relevant properties are not considered, and a plurality of defects exist, such as: both the Incentive Compatibility (IC) and personal compliance (IR) properties are not considered, and it has been proven theoretically and realistically that the auction process cannot be affected by market manipulation or the like without any guarantee. Most previous auction mechanisms focus only on IC and not on another property. In the aspect of realizing spectrum sharing, each secondary user is required to have the same quotation (the same channel) for the requested channel and the number of the applied channels is only single or continuous, so that the bidding of the users is not flexible enough, the actual demand of each requesting user on the spectrum cannot be expressed, and the fair flexibility of spectrum sharing is not well embodied.
In summary, the problems of the prior art are as follows: the existing wireless spectrum allocation mechanism based on auction has the defects that the bidding of users is not flexible enough, the actual demand of each requesting user on the spectrum cannot be expressed, and the fair flexibility of spectrum sharing is not well embodied.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a multi-channel anti-policy manipulated spectrum allocation method, a computer program and a computer.
The invention is realized in such a way that a multi-channel anti-strategy operation spectrum allocation method adopts an auction theory and mechanism, establishes an anti-strategy operation spectrum auction model which comprises a flexible channel request and carries out bidding corresponding to flexible real valuation, the model comprises three entities of a main user, an auctioneer and a secondary user, the secondary user submits bidding information (flexible channel requirement and flexible bidding) to the auctioneer, the auctioneer executes an auction strategy to allocate idle spectrum of the main user, the bidding relation among the secondary users is determined in the anti-strategy operation spectrum auction model, and spectrum auction is carried out through the bidding strategy. The design of the model finally realizes the reasonable distribution of the frequency spectrum according to the flexible requirements and flexible quotations of the secondary users, prevents strategic operation among the secondary users and ensures that the secondary users only adopt the optimal strategy according to the real quotation of the valuation.
Further, the multi-channel anti-policy spectrum manipulation allocation method comprises the following steps:
step one, pre-renting frequency band information is submitted, and resource information is collected and put into a frequency spectrum pool;
step two, the number of the frequency spectrums to be auctioned is defined as {1,2, …, C } according to the number of channels in the frequency spectrum pool;
step three, obtaining the actual cost p of each bidder i through the bidding information and the selection algorithm and the payment algorithmiNumber of channels a obtainediAnd obtaining the actual income of the bidder i:
Figure BDA0001431543550000021
step four, bidding is accompanied by position information, the signal to noise ratio is indirectly described by calculating the distance between each bidder, and all bidders are grouped;
step five, dividing each group into a plurality of virtual groups according to the channel requirements of bidders, and regarding the group gl，
Figure BDA0001431543550000022
Is a virtual group within the group:
Figure BDA0001431543550000023
where j indicates that all bidders contained in the virtual group must have bids for j channels, where
Figure BDA0001431543550000024
Denotes glMaximum number of demands for channels among bidders in the group:
Figure BDA0001431543550000031
didemand set D representing bidders i in a groupiThe medium maximum number of channel demands. Each virtual group
Figure BDA0001431543550000032
Is shown in the belonging group glA bidder set having bids on a jth channel;
and step six, selecting the virtual group.
And step seven, calculating the actual cost of each bidder.
Further, in step three, the set of all secondary users participating in bidding in the whole area, N ═ {1,2, …, N }; all secondary users need D channels at most, and the complete continuous channel requirement set D is {1,2, …, D }; all secondary users each have a set of demands for the channel
Figure BDA0001431543550000033
And corresponding valuation sets
Figure BDA0001431543550000034
Figure BDA0001431543550000035
The evaluation of the bidder i on the k channels is shown, and the evaluation set is added to the unit channel
Figure BDA0001431543550000036
Wherein:
Figure BDA0001431543550000037
l is the set of channel requirements DiThe number smaller than and closest to j, typically l equals 0 or j-1, again:
Figure BDA0001431543550000038
each secondary user carries out bidding according to the evaluation and then carries out bidding respectively
Figure BDA0001431543550000039
Figure BDA00014315435500000310
The bidding price of the bidder i on the k channels is shown, and the unit channel is added with a bidding price set
Figure BDA00014315435500000311
Wherein:
Figure BDA00014315435500000312
similar and valuation; of course:
Figure BDA00014315435500000313
further, in the fifth step, a virtual group bid is obtained for each virtual group, and each virtual group bid is the minimum bid in the virtual group multiplied by the number of bidders in the virtual group, and if there is no bidder in the virtual group, the bid is 0:
Figure BDA0001431543550000041
for virtual groups g belonging to the same grouplIf, if
Figure BDA0001431543550000042
Figure BDA0001431543550000045
Recalculation
Figure BDA0001431543550000043
Then updated
Figure BDA0001431543550000044
Further, the rule of the virtual group is selected in the sixth step:
1) for each bidding group, the virtual groups with small sequence numbers have higher priority than the virtual groups with large sequence numbers in the virtual groups in the group, and are preferentially selected;
2) for NDVGS, all virtual groups in the set are a whole, selected or not selected together;
3) in order to make the master user gain more profit, for any two virtual groups belonging to different groups, the virtual group with the larger price quoted by the virtual group has higher priority and is selected preferentially.
Further, the method for allocating the multi-channel anti-policy manipulated spectrum comprises the following steps:
(1) establishing m stacks S ═ S according to the number m of bidding groups1,s2,…,smThe stacking sequence of each stack is from a virtual group with a large sequence number to a virtual group with a small sequence number, the highest priority of the elements at the top of the stack is ensured, and the elements are selected preferentially;
(2) initializing a candidate virtual group set omega, wherein the set initially comprises all m stack top elements; selecting C virtual groups as objects of distributing channels;
(3) performing iteration selection, selecting a virtual group with the highest priority from the candidate set each time, judging the number of the remaining channels and the number of the virtual groups selected in each iteration for the NDVGS virtual group, if the number of the remaining channels is large, selecting the virtual groups as Winner, and putting the Winner set into the NDVGS virtual group; if the former is small, the virtual set is not selected as Winner;
(4) the last iteration of each iteration is to take the virtual group selected as Winner out of pop of the stack to which the virtual group belongs, take the new top element of the stack as the element in the candidate set, and carry out the next iteration until the channel is completely allocated or the candidate set is empty to obtain a Winner set W containing all virtual groups successful in bidding.
It is a further object of the present invention to provide a computer program for a method of allocation of a manipulated spectrum using said multi-channel anti-policy.
Another object of the present invention is to provide a computer having the computer program loaded thereon.
The method fully considers the factors of the secondary user in spectrum allocation, such as flexible demand and flexible quotation function on a spectrum channel, signal-to-noise interference and the like, simultaneously considers the maximization of the spectrum utilization rate and the requirement of strategy manipulation prevention of the secondary user, and carries out detailed analysis and design on a spectrum auction mechanism. In the prior auction mechanism, only the bidding of a single channel or a plurality of channels is considered, and the valuation of each channel required by bidders is the same, so that the design of the frequency spectrum auction is too simple and the consideration of practical factors is less; in the practical application, the demands of bidders on channels are flexible and various, and the corresponding valuations of the bidders are different. The method provided by the invention is easy to realize and convenient to expand, and is closer to practical application compared with the frequency spectrum auction method already provided; has higher distribution efficiency and fair effect.
Drawings
Fig. 1 is a flowchart of a method for allocating a multi-channel anti-policy manipulated spectrum according to an embodiment of the present invention.
Fig. 2 is a diagram of a spectrum sharing system model according to an embodiment of the present invention.
Fig. 3 is a block diagram of a system according to an embodiment of the present invention.
Fig. 4 is a flowchart of an implementation of a method for allocating a multi-channel anti-policy manipulated spectrum according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention integrates an auction model in economics, and adopts a spectrum sharing auction mechanism which can meet the flexible requirements of secondary users on channels and can meet the flexible estimation of bidding and prevent strategy manipulation. Through the mechanism, secondary users can bid for the frequency spectrum by submitting different requirements of the secondary users on the frequency spectrum and corresponding estimation functions, strategic operation of illegal users is prevented in the process, and a better frequency spectrum sharing mechanism is realized.
The following detailed description of the principles of the invention is provided in connection with the accompanying drawings.
As shown in fig. 1, the method for allocating a multi-channel anti-policy manipulated spectrum according to the embodiment of the present invention includes the following steps:
s101: establishing a spectrum sharing system auction model, and submitting idle spectrum to an Auctioneer (Auctioneer) by a master user and putting the idle spectrum into a spectrum pool for a secondary user to bid;
s102: all Bidders (Bidders) submit flexible channel demands (continuous or discontinuous channel demands) and the corresponding real estimates are used as bidding prices, and the auctioneers group the Bidders through a graph coloring algorithm (simulating SINR interference), and the Bidders in the same group can share the same channel. Dividing virtual groups in each group according to the demands of bidders and calculating the quotation of the virtual groups;
s103: designing a Winner selection algorithm, and allocating a channel to each virtual group in a Winner set; the Charging Method is designed to calculate the cost (Charge) of each virtual group and the Charge of each Bidder.
The application of the principles of the present invention will now be described in further detail with reference to the accompanying drawings.
The method for distributing the multi-channel anti-strategy manipulation frequency spectrum provided by the embodiment of the invention comprises the following steps:
(1) and establishing a system model, wherein entities comprise a main user with a spectrum renting requirement, an auctioneer controlling the whole auction process and a secondary user with a spectrum resource requirement. The master user submits the pre-rented frequency band information to an auctioneer, and the auctioneer collects and arranges the resource information and then puts the resource information into a frequency spectrum pool for the secondary user to bid.
(2) The main user submits the free frequency band information to an auctioneer, the auctioneer specifies the frequency spectrum number C to be auctioned according to the number of channels in the frequency spectrum pool {1,2, …, C }, and the frequency spectrum channel is different from the traditional object in that the frequency spectrum channel can be commonly used by several secondary users, provided that the secondary users can transmit and send signals under the enough signal-to-noise ratio (SINR).
(3) And (3) all secondary user sets N participating in bidding in the whole area are 1,2, …, N. All secondary users require a maximum of D channels, and the complete continuous channel requirement set D is {1,2, …, D }. All secondary users each have a set of demands for the channel
Figure BDA0001431543550000061
And corresponding valuation sets
Figure BDA0001431543550000062
Figure BDA0001431543550000063
The evaluation of the bidder i on the k channels is shown, and the evaluation set is added to the unit channel
Figure BDA0001431543550000064
Wherein
Figure BDA0001431543550000065
Where l is the set of channel requirements DiA number less than and closest to j, typically l equals 0 or j-1, due to the demand set DiThe elements in (1) are not necessarily consecutive, so l may be less than j-1. Also:
Figure BDA0001431543550000071
then each secondary user carries out bidding according to their valuation and bids are respectively bid
Figure BDA0001431543550000072
Figure BDA0001431543550000073
The bidding price of the bidder i on the k channels is shown, and the unit channel is added with a bidding price set
Figure BDA0001431543550000074
Figure BDA0001431543550000075
Wherein:
Figure BDA0001431543550000076
similar and valuation; of course:
Figure BDA0001431543550000077
through the bidding information, the auctioneer obtains the actual cost p of each bidder i by designing an effective selection algorithm and a payment algorithmiAnd the number of channels a that can be acquiredi. Thus, the actual profit of bidder i can be obtained:
Figure BDA0001431543550000078
the actual revenue is not necessarily maximized since the algorithm considers not only objective spectrum utilization but also flexible bidding requirements and bidding functions.
(4) In order to enable a single channel to be used by multiple users simultaneously and improve the utilization rate, the signal to noise ratio is considered, each user is additionally provided with own position information when competing for a bidding, and the signal to noise ratio is indirectly described by calculating the distance between each bidder, for example, the outdoor transmission range of IEEE 802.11n is about 250 meters, and the specified interference factor theta is 1.7, so that the same channel can be shared by two bidders as long as the distance between the two bidders is more than 425 meters. So that the auctioneer can group all bidders by this information (graph coloring algorithm).
(5) Through grouping, a plurality of secondary users in a group can share one channel, and each group also needs to be divided into a plurality of virtual groups according to the channel requirements of bidders because each secondary user can bid for a plurality of channel requirements during bidding, and for the group gl，
Figure BDA0001431543550000079
Is a virtual group within the group:
Figure BDA00014315435500000710
where j indicates that all bidders contained in the virtual group must have bids for j channels, where
Figure BDA0001431543550000081
Denotes glMaximum number of demands for channels among bidders in the group:
Figure BDA0001431543550000082
didemand set D representing bidders i in a groupiThe medium maximum number of channel demands. Each virtual group
Figure BDA0001431543550000083
Is shown in the belonging group glA set of bidders having bids on the jth channel. For later design choiceWhere a virtual group quote is required for each virtual group. In order to prevent policy manipulation, the bid price of each virtual group is the minimum bid in the virtual group multiplied by the number of bidders in the virtual group, and if no bidder is in the virtual group, the bid price is 0:
Figure BDA0001431543550000084
in the invention, the quotation of the original virtual group also needs to be specially processed, and the quotation of the original virtual group is specially processed for the virtual group g belonging to the same grouplIf, if
Figure BDA0001431543550000085
In this case (virtual group set of discontinuous demand, NDVGS for short), recalculation is required
Figure BDA0001431543550000086
Then updated
Figure BDA0001431543550000087
(6) The problem of spectrum auctioning after forming a virtual group becomes the process of selecting a wining virtual group, how to design a selection algorithm to select the virtual group, and if the virtual group is successfully bid, it means that all bidders in the virtual group commonly obtain a channel. In the prior auction mechanism, the channel requirement of each bidder is required to be continuous, so that all virtual groups formed in one group are regular, the sizes of the virtual groups are reduced in sequence, and the bids of the virtual groups are also reduced in sequence, so that the selection sequence of the virtual groups is ensured by designing a selection algorithm, and the fact that the first channel is obtained first is indicated that the second channel can be obtained. In the scheme, the bidders are considered to flexibly bid according to different requirements, so that the rules cannot be met, and the virtual groups in the same group are different in size, so that a selection algorithm needs to be redesigned. The auctioneer proposes three rules for selecting the virtual group: 1) for each bidding group, the virtual groups with small sequence numbers have higher priority than the virtual groups with large sequence numbers in the virtual groups in the group, and are preferentially selected; 2) for NDVGS, all virtual groups in the set are a whole and must be selected or unselected together; 3) in order to make the master user gain more profit, for any two virtual groups belonging to different groups, the virtual group with the larger price quoted by the virtual group has higher priority and is selected preferentially. It is emphasized that the first two rules are prerequisites for the third rule and must be considered first.
(7) The invention is a heuristic greedy selection algorithm to assign channels to virtual groups. Firstly, according to the number m of bidding groups, m stacks S ═ S are established1,s2,…,smAnd (4) each stack is pushed from a virtual group with a large sequence number to a virtual group with a small sequence number, so that the top element of the stack is guaranteed to have the highest priority and is selected preferentially. A candidate virtual group set Ω is initialized, which initially contains all m top-of-stack elements. The selection algorithm needs to select C virtual groups as objects for distributing channels, then iterative selection is carried out, a virtual group with the highest priority is selected from the candidate set each time, for NDVGS which are several virtual groups, the number of the residual channels and the number of the virtual groups selected in each iteration are judged, if the number of the residual channels is large, the virtual groups are all selected as Winner, and the Winner set is put in; if the former is small, these virtual groups are not selected as Winner. The last iteration is to take the virtual groups out of the stack pop, take the new top element as the element in the candidate set, and then perform the next iteration until the channel allocation is completed or the candidate set is empty. And finally obtaining a Winner set W containing all virtual groups successful in bidding.
(8) For successful bidders, the Charging Method is designed to calculate the charge of each virtual group, so as to obtain the respective charge of each bidder. For a virtual group
Figure BDA0001431543550000091
When it is not in the Winner set, its charge
Figure BDA0001431543550000092
All bidders in the virtual groupCharge of (2) is also 0. When the virtual group belongs to the Winner set, the index position index of the virtual group in the set is marked, then the group to which the virtual group belongs is deleted, all the virtual groups after the virtual group are deleted, then Winner selection is carried out again, W' is obtained, and then the smallest virtual group report value min _ value is selected as the virtual group from the index position index in the set to the last virtual group
Figure 1
The charge of (a) is calculated,
Figure BDA0001431543550000094
after the charge of all the virtual groups is obtained, for the channel obtained by the virtual group, the charge of the bidders in each virtual group is the average value of the charge of the virtual group. The total charge of each bidder is equal to the cumulative sum of the charges of all its acquired channels.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (4)

1. A multi-channel strategy-prevention operation spectrum allocation method is characterized in that an auction theory and mechanism are adopted in the multi-channel strategy-prevention operation spectrum allocation method, a strategy-prevention operation spectrum auction model which contains a flexible channel request and is used for bidding corresponding to a flexible real estimation value is established, a bidding relation among secondary users is determined in the strategy-prevention operation spectrum auction model, and spectrum auction is carried out through a bidding strategy;
the strategy manipulation prevention frequency spectrum auction model comprises three entities, namely a main user, an auctioneer and a secondary user, wherein the secondary user submits bidding information to the auctioneer, the auctioneer executes an auction strategy to allocate idle frequency spectrum of the main user, the bidding relation among the secondary users is determined in the strategy manipulation prevention frequency spectrum auction model, and frequency spectrum auction is carried out through the bidding strategy;
the multi-channel anti-policy manipulated spectrum allocation method comprises the following steps:
step one, pre-renting frequency band information is submitted, and resource information is collected and put into a frequency spectrum pool;
step two, the number of frequency spectrums C to be auctioned is specified according to the number of channels in the frequency spectrum pool, wherein the number of the frequency spectrums C is {1, 2.
Step three, obtaining the actual cost p of each bidder i through the bidding information and the selection algorithm and the payment algorithmiNumber of channels a obtainediAnd obtaining the actual income of the bidder i:
Figure FDA0003020063820000011
step four, bidding is accompanied by position information, and the signal to noise ratio is indirectly described by calculating the distance between each bidder; grouping the bidders by adopting a graph coloring algorithm;
step five, dividing each group into a plurality of virtual groups according to the channel requirements of bidders, and regarding the group gl，
Figure FDA0003020063820000012
Is a virtual group within the group:
Figure FDA0003020063820000013
where j indicates that all bidders contained in the virtual group must have bids for j channels, where
Figure FDA0003020063820000014
Denotes glMaximum number of demands for channels among bidders in the group:
Figure FDA0003020063820000015
didemand set D representing bidders i in a groupiMedium maximum channel requirement number; each virtualGroup of
Figure FDA0003020063820000016
Is shown in the belonging group glA bidder set having bids on a jth channel;
step six, selecting a virtual group;
step seven, calculating the actual cost p of each bidderi；
In the third step, all secondary user sets participating in bidding in the whole area are N ═ {1, 2.., N }; all secondary users require D channels at most, and a complete continuous channel requirement set D ═ 1, 2. All secondary users each have a set of demands for the channel
Figure FDA0003020063820000021
And corresponding valuation sets
Figure FDA0003020063820000022
Figure FDA0003020063820000023
The evaluation of the bidder i on the k channels is shown, and the evaluation set is added to the unit channel
Figure FDA0003020063820000024
Wherein:
Figure FDA0003020063820000025
l is the set of channel requirements DiThe number smaller than and closest to j, typically l equals 0 or j-1, again:
Figure FDA0003020063820000026
then each secondary user carries out bidding according to the valuation and carries out bidding respectively
Figure FDA0003020063820000027
Figure FDA0003020063820000028
The bidding price of the bidder i on the k channels is shown, and the unit channel is added with a bidding price set
Figure FDA0003020063820000029
Wherein:
Figure FDA00030200638200000210
Figure FDA00030200638200000211
in the fifth step, a virtual group bid is obtained for each virtual group, and the bid of each virtual group is the minimum bidding in the virtual group multiplied by the number of bidders in the virtual group, and if no bidder exists in the virtual group, the bid is 0:
Figure FDA00030200638200000212
for virtual groups belonging to the same group
Figure FDA00030200638200000213
If it is not
Figure FDA00030200638200000214
Combining and recalculating quotations for discrete channel requirements in the same group
Figure FDA00030200638200000215
Then updated
Figure FDA00030200638200000216
2. The method for multi-channel anti-policy spectrum allocation according to claim 1, wherein the virtual set of rules selected in step six:
1) for each bidding group, the virtual groups with small sequence numbers have higher priority than the virtual groups with large sequence numbers in the virtual groups in the group, and are preferentially selected;
2) for NDVGS, all virtual groups in the set are a whole, selected or not selected together;
3) for any two virtual groups belonging to different groups, the virtual group with the larger virtual group offer has a higher priority, and is preferentially selected.
3. The method for allocating multi-channel anti-policy steered spectrum according to claim 1, wherein the method for allocating multi-channel anti-policy steered spectrum comprises:
(1) establishing m stacks S ═ S according to the number m of bidding groups1，s2，...，smThe stacking sequence of each stack is from a virtual group with a large sequence number to a virtual group with a small sequence number, the highest priority of the elements at the top of the stack is ensured, and the elements are selected preferentially;
(2) initializing a candidate virtual group set omega, wherein the set initially comprises all m stack top elements; selecting C virtual groups as objects of distributing channels;
(3) performing iteration selection, selecting a virtual group with the highest priority from the candidate set each time, judging the number of the remaining channels and the number of the virtual groups selected in each iteration for the NDVGS virtual group, if the number of the remaining channels is large, selecting the virtual groups as Winner, and putting the Winner set into the NDVGS virtual group; if the former is small, the virtual set is not selected as Winner;
(4) the last step of each iteration is to take the virtual group selected as Winner out of pop of the stack to which the virtual group belongs, take the new top element of the stack as the element in the candidate set, and perform the next iteration until the channel is completely allocated or the candidate set is empty to obtain a Winner set W containing all virtual groups successful in bidding.
4. The method for allocating multi-channel anti-policy steered spectrum according to claim 1, wherein the method for allocating multi-channel anti-policy steered spectrum comprises: for successful bidders, the charge to be paid needs to be selected; calculating the charge of each virtual group by adopting a Charging Method to obtain the respective charge of each bidder; for a virtual group
Figure FDA0003020063820000031
When it is not in the Winner set, its charge
Figure FDA0003020063820000032
The charge of all bidders in the virtual group is also 0; when the virtual group belongs to the Winner set, marking the index position index of the virtual group in the set, deleting all the virtual groups including the virtual group and the virtual groups after the virtual group in the group to which the virtual group belongs, re-performing Winner selection to obtain W', and then starting from the index position index in the set to the last virtual group, selecting the minimum virtual group report value min _ value as the virtual group
Figure FDA0003020063820000041
The charge of (a) is calculated,
Figure FDA0003020063820000042
after the charge of all the virtual groups is obtained, for the channel obtained by the virtual group, the charge of the bidder in each virtual group is the average value of the charge of the virtual group; the total charge of each bidder is equal to the cumulative sum of the charges of all its acquired channels.
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