CN112235805B - Electric power wireless heterogeneous network service connection competition method and connection method - Google Patents
Electric power wireless heterogeneous network service connection competition method and connection method Download PDFInfo
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- CN112235805B CN112235805B CN202010864165.9A CN202010864165A CN112235805B CN 112235805 B CN112235805 B CN 112235805B CN 202010864165 A CN202010864165 A CN 202010864165A CN 112235805 B CN112235805 B CN 112235805B
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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
- H04W16/14—Spectrum sharing arrangements between different networks
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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
- H04W16/22—Traffic simulation tools or models
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
- H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality
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- 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
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- 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
Abstract
The invention discloses a power wireless heterogeneous network service connection competition method and a connection method, wherein a multi-commodity auction model is established aiming at the service connection problem of different terminals, and an objective function is used for searching the maximum bidding sum for a service group, so that the winning base station provides the maximum rate and the maximum sum for all services in the service group and is the base station which submits the bidding contained in the maximum bidding sum; constraint 1 specifies that for each base station c, it can win at most one traffic combination; constraint 2 specifies that each service in the service group has and can only be sold to one base station; constraint 3 specifies that the bids in the maximum bid sum must be greater than or equal to the WSP's valuation. The invention adopts the average throughput of the multi-round auction to be slightly larger than that of the single-round auction, thereby ensuring that the speed of the service maintains a higher level and effectively improving the throughput of the system.
Description
Technical Field
The invention belongs to the technical field of power Internet of things, and particularly relates to a power wireless heterogeneous network multi-mode terminal access technology.
Background
In recent years, the technology of the power internet of things is rapidly developed, and the intelligent processing technology is deeply applied to each link of power production. At present, intelligent monitoring equipment is widely applied to the Internet of things of electric power, and an intelligent instrument is used for realizing auxiliary supporting functions under different scenes, such as electric power meter reading, intelligent inspection and the like. However, these devices still have various problems in wireless access. Especially in an ultra-dense power collection wireless heterogeneous network, due to the factors of diversity of equipment, difference of wireless network channel transmission quality, overlapping of wireless network signals and the like, the monitoring equipment has more access choices, and reasonable choice is favorable for improving the throughput and the resource utilization rate of a system.
In the power internet of things, the application service of the intelligent monitoring instrument is more and more diversified and personalized. The current access selection scheme mainly adopts network performance indexes to select a network with the best comprehensive performance, but the scheme does not consider the service type and characteristics of the monitoring instrument, and is easy to generate an access scheme which is contrary to the actual requirement, and the situation has two main disadvantages: 1) The access delay of the monitoring equipment or the service cannot be guaranteed; 2) Resources such as wireless resources and energy consumption are easy to cause waste.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a connection competition method and a connection method for a power wireless heterogeneous network service, so that the service can obtain higher transmission rate, and the wireless resources of a base station are fully utilized.
In order to solve the technical problems, the invention adopts the following technical scheme:
a power wireless heterogeneous network service connection competition method is characterized in that in a service access selection scene in a power Internet of things scene, a multi-commodity auction model is established aiming at the service connection problem of different terminals, in the multi-commodity auction model, a Wireless Spectrum Provider (WSP) is a seller, a base station is a buyer, a service is a commodity, the WSP is used for conducting auction, and the service to be accessed is sold to the base station;
assuming that all access services in the network get an equal proportion of resources, if the number of services connected to base station c is N c Then, the ratio r of base station resources to be obtained by each access service is:
the speed of service is used as the standard for measuring the channel state, and the Shannon formula is used to map the speed of service as the function of SINR, if the proportion of the whole bandwidth W of the base station obtained by each access service is r, the speed TP of service m is m Comprises the following steps:
TP m ＝rW log 2 (1+r mc ) (2)
r mc SINR value for traffic m to base station c, defined as the sum of the noise power over signal power ratio received by the traffic from its access base station c and the interference power received from other base stations;
assuming that all base stations are deployed at the same frequency and the service model is full buffering, then:
grouping the services as commodities, and distributing a service group by adopting multi-commodity auction:
the WSP selects M services as a service group, and a buyer can bid on any service combination in the service group, and the service combination is recorded as x j ＝U 1 U 2 ……U M ，U m = 0,1 represents whether or not service m is in the combination, x j Represents the jth service combination, with a total of J =2 M -1 service combination;
base station c pairs service combination x j Valuation V of c (x j ) Defined as it can be provided for a service combination x j Average rate per service in (1):
wherein s is c For the number of services accessed in the base station c,
the total number of the services in the current service combination;
note base station c for service combination x j Bid of q c (x j ) Since the auction model is honest, the base station will submit bids, i.e. q, with its own valuation c (x j )＝V c (x j )，
Defining an valuation r of a WSP WSP (x j ) Comprises the following steps:
wherein the content of the first and second substances,
the average value of SINR of the service to the base station;
only the bids of which the price is more than or equal to the WSP estimation are reasonable bids, and all reasonable bids are based on bids above the SINR average value;
the WSP collects bids for the base stations and assigns different x' s j The bids are classified and unreasonable bids are filtered at the same time, and a bid combination G (x) is recorded on the assumption that K reasonable bids are provided j ) Comprises the following steps:
G(x j )＝[q c (x j )] 1×K (6)
a total of J G (x) j ) Matrix, let the corresponding indicator matrix delta (x) j ) Comprises the following steps:
δ(x j )＝[δ c (x j )] 1×K (7)
δ c (x j ) E {0,1} denotes base station c to x j Bidding q c (x j ) Let A = { j | delta = c (x j ) =1} represents the number of winning traffic combination;
the goals and constraints of the multi-commodity auction model are as follows:
∑ j∈A x j = (1, \8230;, 1) (M1) (8-2)
q c (x j )≥r WSP (x j ) (8-3)
The objective function (8) finds the maximum bidding sum for the service group, so that the winning base station provides the maximum rate sum for all services in the service group, and the winning base station is the base station of which the submitted bidding sum is contained in the maximum bidding sum;
the constraint (8-1) specifies that for each base station c it can win at most one traffic combination;
the constraint (8-2) specifies that each service in the service group has and can only be sold to one base station;
the constraint (8-3) specifies that the bids in the maximum bid sum must be greater than or equal to the WSP's valuation.
The invention also provides a multi-mode terminal service self-adaptive connection method in the power wireless heterogeneous network, the multi-commodity auction model is adopted for service connection, and the service multi-commodity auction process comprises the following steps:
step S11: service group formation: the WSP forms a service group according to the geographic position of the service, and executes an auction for each service;
step S12: auction preparation: measuring SINR of each service to all base stations and obtaining a composite access point set C m Designing an SINR threshold V in Only SINR is greater than or equal to V in The corresponding base station can enter the alternative set C of the service m Then the service will perform signaling interaction with the base stations in the set;
step S13: and (3) starting auction: first, all base stations submit a bid q to the WSP based on information obtained from the service c (x j ) The WSP then processes the collected bids, classifies the bids by service combination and based on their valuations r WSP (x j ) Unreasonable bidding is filtered, and finally the WSP solves the multi-commodity auction model under the condition that constraint conditions are met, and the maximum bidding sum is searched for the service group;
step S14: and (4) follow-up work: the WSP accesses the services in the service group to a winning base station, and simultaneously records evaluation of the services as a standard for later evaluation of whether the channel state is poor;
step S15: the next auction: and after all the services in the last auction group are accessed to the base station, ending the auction, starting the next auction, selecting a new group of services by the WSP for arranging access, re-measuring the parameters of the services, and ending the whole multi-commodity auction when all the services are sold.
Preferably, the WSP selects 3 services to be accessed that are adjacent in geographical location to form a service group.
Preferably, the step of finding the maximum bid sum is as follows:
step S13.1:
step S13.2: from one of G (x) j ) At the beginning of the process, the user can start,
step S13.3: submit bid Q (x) j ) Is Q -1 (x j ) Remove other bids from the base station, record as G/Q -1 (x j )，Q G/c (x j ) Indicating that base station c has been removed from the bid, G (x) j ) Maximum bid in (b);
step S13.4: repeating the steps S13.2 and S13.3 before all the services in the service group are distributed;
step S13.5: summing all of the above maximum bids to obtain a bid sum W, enumerating all bid sums, and obtaining a maximum bid sum therein, since starting from different service combinations will result in different bid sums.
Preferably, when each round of auction is finished, the service records the WSP evaluation as a lower limit rate for measuring the channel state after access, and when the service rate is lower than the WSP evaluation, it indicates that the access base station can not provide the rate above the average value based on SINR for the service, at this moment, the WSP arranges a single product forward auction for the service, only reallocates the access base station for the service,
the business single commodity auction process comprises the following steps:
step S21: rate detection and assessment: the service detects the speed of the WSP once every t seconds, and when the speed is lower than the WSP estimation updated by the last auction, the service sends a re-auction request to the WSP;
step S22: auction preparation: the WSP receives the service request, informs the service of auction preparation after confirming that no errors exist, measures SINR of all base stations and screens out an access point set C m Then the service and the alternative base station carry out signaling interaction, and the alternative base station obtains service information;
step S23: and (3) starting auction: the base station submits the bidding for the service, the WSP collects the bidding of all the base stations and filters unreasonable bidding, the WSP seeks the maximum bidding sum for the service group according to the formula under the condition of satisfying the constraint condition, and the base station submitting the maximum bidding sum in the maximum bidding sum is the winning base station;
step S24: and (4) subsequent work: the WSP accesses the service with the poor channel state into a new winning base station, and the service updates the WSP valuation recorded by the last auction into the WSP valuation of the current auction.
Preferably, the follow-up work of step S24 further includes the WSP settling base station rewards based on the base station revenue.
Preferably, the specific steps of the WSP for settling the base station rewards according to the base station revenues are as follows:
step S24.1: if the service combination won by the winning base station c is j, the winning base station c wins a cross price p c (x j ) Comprises the following steps: p is a radical of c (x j )＝max{r WSP (x j ),V(c)-∑ u≠c ∑ h≠j δ u ′(x h )q u (x h )}，
Wherein
For maximum sum of bids when winning base station c is not engaged in bidding u≠c ∑ h≠j δ u ′(x h )q u (x h ) The sum of the current maximum bid and the bids of other base stations;
step S24.2: for the special case when M =1 and J =1, the bargain price p c Comprises the following steps: p is a radical of c ＝max{r WSP ,max∑ u≠c q u Where max sigma u≠c q u A maximum bid when winning base station c is not engaged in bidding;
step S24.3: since the VCG mechanism is an extension of the next highest auction, its bid price p is for winning base station c c (x j ) Less than its winning bid q c (x j ) I.e. r WSP (x j )≤p c (x j )≤q c (x j )；
Step S24.4: effectiveness obtained by winning base station c due to winning service combination j Z c (x j )＝V c (x j )-p c (x j ) Is not obtainedThe utility of the base station for service access is 0, and the utility Z obtained by the WSP due to selling the service combination j WSP (x j )＝p c (x j )-r WSP (x j )；
Step S24.5: to encourage base stations to participate in bidding, when a service is updated to access a base station, the WSP will award money to the base station that previously served the service, the money award being proportional to the base station gain, which is defined as:
where a (n) is an increasing function of the detection round n,
is the number of services in service combination j, t c The time for the base station c to service the service.
In the invention, the heterogeneous characteristics of services in the power Internet of things are considered, and a multi-commodity auction model is established aiming at the connection problem of different services; then, strategies for initial access and switching of the service are designed based on the auction model, and the method has the following beneficial effects:
when the service is initially accessed, the access right of the service is distributed by adopting multi-commodity forward auction, and the service obtains higher transmission rate through competition among base stations.
After the service obtains its own initial access, the channel state of the service may be deteriorated due to the time-varying nature of the channel, and at this time, the initial access base station of the service cannot continue to provide a higher level rate for the service, so that the radio resource of the base station is not fully utilized. Therefore, a lower limit for the traffic rate is designed, and when the traffic rate falls below the lower limit, the auction is rescheduled for the traffic to switch to the base station that can provide the higher rate.
The multi-round auction is adopted, so that the service rate is reduced to a lower level and the opportunity of re-access exists, therefore, the average throughput of the service adopting the multi-round auction is slightly larger than that of a single-round auction, the service rate is ensured to maintain a higher level, and the throughput of the system is effectively improved.
The multi-commodity auction model adopts a VCG (Vickrey Clarke Groves, VCG) price mechanism, and the WSP pays a monetary reward to a winning base station according to the utility of the base station in the auction so as to encourage the base station to participate in bidding.
The following embodiments are provided to explain the present invention and its advantages.
Drawings
The invention is further described with reference to the accompanying drawings and the detailed description below:
fig. 1 is a scene diagram of service access selection in a power internet of things scene.
Fig. 2 is a flow chart of a business multi-item auction.
Figure 3 is a flow diagram of a single item auction process.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be apparent that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a view of a service access selection scenario in a power internet of things scenario, in order to make allocation of resources more flexible, the present invention groups different services as commodities, and allocates one service group by using multi-commodity auction. The access rights of different services are distributed by multi-commodity forward auction, and the services obtain higher transmission rate through competition among base stations.
The invention has set up the model of multi-commodity auction to the business connection problem of different monitoring instruments, wireless Spectrum Provider (WSP) is the seller in the multi-commodity auction, the base station is the buyer, the business is the commodity; the WSP hosts the auction and sells the service to be accessed to the base station. Each monitoring device can issue a plurality of services, each intelligent detection device has a plurality of access modes, and the WSP serving as a manager can provide corresponding wireless resources. In addition, the multi-commodity auction model employs a VCG (VCG) price mechanism to which the WSP will pay monetary rewards based on the utility that the winning base station is gaining in the auction, to encourage the base station to participate in bidding.
Assuming that all access services in the network get an equal proportion of resources, if the number of services connected to base station c is N c Then, the ratio r of base station resources to be obtained by each access service is:
if the number of access services of a certain base station is too large, the proportion of wireless resources which can be provided for the service to be accessed by the certain base station is reduced, and the service to be accessed is more favored by other alternative base stations which can provide more wireless resources. In addition, the base station strives to obtain service access as much as possible in order to maximize its own value, even though it may not necessarily provide sufficient radio resources for these access services. The present invention coordinates this interest relationship between the base station and the business by introducing a multi-commodity auction model.
The invention adopts the speed of the service as the standard for measuring the channel state, and adopts the Shannon formula to map the speed of the service as the function of the signal to interference plus noise ratio (SINR). If the ratio of the total bandwidth W of the base station obtained by each access service is r, the rate TP of the service m m Comprises the following steps:
TP m ＝rW log 2 (1+r mc ) (2)
r mc is the SINR value of the traffic m to base station c, defined as the sum of the noise power over signal power ratio received by the traffic from its access base station c and the interference power received from other base stations.
Assuming that all base stations are deployed at the same frequency, and the service model is Full buffer:
in the connection model of the business, the invention adopts a multi-commodity auction model, and in order to ensure that the allocation of resources is more flexible, the invention groups the businesses as commodities and allocates a business group by adopting multi-commodity auction. The buyer (base station) can bid for any number of services in the service group according to the quantity of wireless resources owned by the buyer, so that the seller (WSP) can obtain more reasonable bids higher than the self-valuation.
The WSP selects M services as a service group, and the buyer can bid on any service combination in the service group. Record service combination as x j ＝U 1 U 2 ……U M ，U m = {0,1} represents whether or not traffic m is in the combination, x j Represents the jth service combination, with a total of J =2 M -1 service combination.
Base station c pairs service combination x j Valuation V of c (x j ) Defined as it can be provided for a service combination x j Average rate per service.
Wherein r is mc SINR value, s, for service m to base station c c For the number of services accessed in the base station c,
the total number of services in the current service combination.
Note base station c pairs service combination x j Bid of q c (x j ). Because of the honesty of the auction model, the base station will submit bids, i.e., q, at its own valuation c (x j )＝V c (x j ) I.e., the bid submitted by the base station is the average rate it can offer for each service in the service combination.
Defining an valuation r of a WSP WSP (x j ) Comprises the following steps:
wherein
Is the average SINR of the traffic to the base station. Only bids greater than or equal to the WSP estimate are fair bids, all of which are based on bids above the SINR average.
The WSP collects bids for the base stations and assigns different x' s j Bids are categorized while unreasonable bids are filtered.
Assuming that there are K reasonable bids, the combination of bids G (x) j ) Comprises the following steps:
G(x j )＝[q c (x j )] 1×K (6)
a total of J G (x) j ) Matrix, let the corresponding indicator matrix delta (x) j ) Comprises the following steps:
δ(x j )＝[δ c (x j )] 1×K (7)
δ c (x j ) E {0,1} represents base station c to x j Bidding q c (x j ) The win-loss is realized. Let A = { j | δ c (x j ) =1 represents the number of winning traffic combinations.
Based on the above notation and definitions, the goals and constraints of the multi-commodity auction model are as follows:
∑ j∈A x j = (1, \8230;, 1) (M1) (8-2)
q c (x j )≥r WSP (x j ) (8-3)
An objective function (8) finds the maximum bid sum for the service group, maximizing the rate sum provided by the winning base station for all services in the service group. The winning base station is the base station for which the bid submitted is included in the maximum bid sum.
The constraint (8-1) states that for each base station c it can win at most one traffic combination. Since the optimal resource allocation strategy for each base station is unique. The constraint (8-2) specifies that each service in the service set has and can only be sold to one base station. The constraint (8-3) specifies that the bids in the maximum bid sum must be greater than or equal to the WSP's valuation.
A self-adaptive switching method for a multi-mode terminal in a power wireless heterogeneous network mainly comprises two parts: 1) A service connection policy; 2) And (4) switching strategies of the service.
In the connection strategy, in order to filter base stations with lower SINR and improve the SINR average value, the invention designs an SINR threshold V in the service connection strategy in . The service measures the SINR value of the service to all base stations before each auction, and only the SINR is more than or equal to V in The corresponding base station can enter the alternative set C of the service m And submitting the bidding for the service. SINR average of traffic
Is based on C m All base stations in (1). In the multi-commodity auction model, the WSP divides the services to be accessed into a plurality of groups, and the number of each group of services and the grouping mode influence the result and complexity of the auction. If M services are sold to the base station as a group, the base station bidding combination of services will have a value of 2 M -1 possibility. The more the number of services in each group, the more flexibly the base station can bid for the services in the group according to the own wireless resources, thereby leading to better resource allocation. However, the number of services in each group is not too large, on one hand, the number is too large to evaluate the advantages of different bidding combinations, and on the other hand, the base station cannot carry too much services due to lack of sufficient power. In the present invention, only the case of M =3 is considered due to the limitation of computational complexity. In addition, because the base station bids on the rate at which it can provide the service, the topology of the intra-group service does not greatly affect the outcome of the auctionIn the invention, services adjacent to the geographical position are selected to form a group.
Referring to fig. 2, the main steps of the connection policy of the service are as follows:
step 1: the WSP selects 3 services to be accessed with adjacent geographic positions to form a service group, and carries out auction for each group of services respectively.
Step 2: preparing before auction, WSP informs corresponding service in service group, the service measures SINR value of all base stations and obtains C m (SINR≥V in ) Then service m will be associated with C m The base stations in (1) perform signaling interaction (including service ID, channel status, etc.).
And step 3: first, all base stations submit a bid q to the WSP based on information obtained from the service c (x j ). Since the VCG mechanism adopted by the multi-item auction is a Sealed (Sealed) auction mechanism, all base stations do not know the bids of other base stations, and once all base stations submit bids, the auction is ended. The WSP then processes the collected bids, classifies them by business portfolio and based on their r WSP (x j ) Filtering unreasonable bidding; and finally, the WSP solves the multi-commodity auction model under the condition of meeting the constraint condition, seeks the maximum bidding sum for the service group, and the steps of seeking the maximum bidding sum are as follows:
step 3.1:
step 3.2: from one of G (x) j ) At the beginning of the process, the user can start,
step 3.3: submit bid Q (x) j ) Is Q -1 (x j ) Remove other bids from the base station, record as G/Q -1 (x j )，Q G/c (x j ) Indicating that base station c has been removed from the bid, G (x) j ) Maximum bid in (1);
step 3.4: repeating the steps 3.2 and 3.3 before all the services in the service group are distributed;
step 3.5: all the maximum bids are summed to obtain a bid sum W. Since starting from different service combinations will result in different bid sums, all bid sums are enumerated and the maximum bid sum is obtained.
And 4, step 4: the WSP arranges follow-up work, accesses the services in the service group to the winning base station, and records the evaluation of the services by the WSP at the moment as a standard for evaluating whether the channel state is poor or not later.
And 5: as the WSP schedules access for a service group, the group of services begins to occupy a portion of its resources accessing the base station, and the base station bids for subsequent services accordingly. After all the services in the last auction group are accessed to the base station, the auction is ended, the next auction is started, the WSP selects a new group of services to arrange access for the new group of services, and the services measure the parameters again. The entire multi-item auction ends when all of the services have been sold.
The definition of WSP valuation mentioned above is based on SINR averages, and only bids greater than WSP valuation are fair bids to ensure that the winning base station in this auction can provide traffic at rates above SINR averages. However, as the number of the access services increases, the proportion of resources obtained by the service previously accessed to the base station decreases, so that the rate provided by the base station for the previous service also decreases correspondingly; in addition, due to the time-varying nature of the channel, the channel state of the service may be deteriorated, which inevitably results in the reduction of the service rate; although the winning base station can provide the service with a rate based on the SINR average above a certain auction is completed, there is no guarantee that the winning base station can always provide the service with a rate greater than the WSP valuation.
Therefore, at the end of each round of auction, the service records the WSP valuation as the lower limit rate for measuring the channel state after access. When the traffic rate is lower than the WSP estimate, it means that its access station has no way to continue providing the traffic with a rate above the SINR average. The service of issuing the re-auction request is often single coming because the channel state is poor to occur and random. The WSP arranges a single product forward auction for the service and only reallocates its access base station for the service. This single-commodity auction model can be considered as a special case of the multi-commodity auction model when M = 1.
Referring to fig. 3, the main steps of the single item auction process are as follows:
step 1: the service detects its rate every t seconds, and when it is lower than the updated WSP valuation of the last auction, the service sends a re-auction request to the WSP.
And 2, step: and the WSP receives the service request, and informs the service of auction preparation after confirming that no error exists. The service measures its SINR value to all base stations again and screens out C m Then the service and the alternative base station carry out signaling interaction, and the alternative base station obtains service information.
And 3, step 3: the base station submits bids for the service, and the WSP collects all base station bids and filters unreasonable bids. Since the commodity is a single service at this time, M =1 and J =1, the matrix of equation (3-6) has only one, i.e., G (1). The WSP finds the maximum bid sum for the service group according to equation (3-8) under the constraint condition that is satisfied, i.e., the maximum value in G (1), and the base station submitting the maximum bid in G (1) is the winning base station.
And 5: the WSP accesses the service with the poor channel state into a new winning base station, and the service updates the WSP valuation recorded by the last auction into the WSP valuation of the current auction. Meanwhile, the WSP settles the base station reward according to the base station income and comprises the following specific steps:
step 5.1 the multi-commodity auction model adopts VCG price mechanism, if the service combination won by the winning base station c is j, the winning base station becomes a transaction price p c (x j ) Comprises the following steps: p is a radical of c (x j )＝max{r WSP (x j ),V(c)-∑ u≠c ∑ h≠j δ u ′(x h )q u (x h ) In which the first part
For maximum sum bid when winning base station c is not engaged in bidding, second part Σ u≠c ∑ h≠j δ u ′(x h )q u (x h ) The current maximum bid is summed with the bids of the other base stations (i.e., the winning base station c is not included).
Step 5.2 for the special case when M =1 and J =1, the bargain price p is c Comprises the following steps: p is a radical of formula c ＝max{r WSP ,max∑ u≠c q u Where max sigma u≠c q u The winning base station c is the maximum bid when it is not participating in the bid (and is also the second highest bid when it is participating in the bid).
Step 5.3 since the VCG mechanism is an extension of the next highest auction, its bid price p is for winning base station c c (x j ) Less than its winning bid q c (x j ) I.e. r WSP (x j )≤p c (x j )≤q c (x j )。
Step 5.4: z the effectiveness obtained by the winning base station c due to winning the service combination j c (x j )＝V c (x j )-p c (x j ) The utility of the base station which does not obtain service access is 0. Utility Z obtained by WSP due to selling business combination j WSP (x j )＝p c (x j )-r WSP (x j )
Step 5.5: to encourage base station participation in bidding, the WSP will, upon a service update accessing the base station, award a monetary reward to the base station that previously served the service, the monetary reward being proportional to the base station revenue. Defining the base station gains as:
and a (n) is an increasing function of the detection turn n, and because the channel state is poor when the service sends a re-access request each time, the bid submitted by the alternative base station to the service at this moment is possibly lower than the bid submitted at the last auction, the effectiveness of the base station after re-auction is lower, and the base station does not have power to participate in the re-auction. Thus, the present invention introduces a (n) to encourage base stations to participate in subsequent rounds of auctions.
Is the number of services in service combination j, t c The time for the base station c to service the service.
In conclusion, the invention adopts the multi-commodity forward auction to distribute the access right of the service, and the service obtains higher transmission rate through the competition among the base stations. After a service obtains its initial access, the channel state of the service may deteriorate due to the time-varying nature of the channel, and at this time, the initial access base station of the service cannot continue to provide a higher level rate for the service, so that the radio resources of the base station are not fully utilized. Therefore, the present invention contemplates a lower limit on the traffic rate, and when the traffic rate falls below the lower limit, the auction is rescheduled for the traffic to switch to the base station that can provide the higher rate.
The multi-round auction is adopted, so that the service rate can be reduced to a lower level and the opportunity of re-accessing is available, therefore, the average throughput of the service adopting the multi-round auction is slightly larger than that of the single-round auction, the service rate is guaranteed to maintain a higher level, and the throughput of the system is effectively improved.
The multi-commodity auction model employs a VCG (VCG) price mechanism to which the WSP will pay monetary rewards based on the utility that the winning base station achieves in the auction, to encourage the base station to participate in bidding.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that the invention is not limited thereto, and may be embodied in other forms without departing from the spirit or essential characteristics thereof. Any modification which does not depart from the functional and structural principles of the present invention is intended to be included within the scope of the claims.
Claims (1)
1. A multi-mode terminal service self-adaptive connection method in a power wireless heterogeneous network is characterized in that in a service access selection scene in a power wireless internet of things scene, a multi-commodity auction model is established aiming at the service connection problem of different terminals, in the multi-commodity auction model, a Wireless Spectrum Provider (WSP) is a seller, a base station is a buyer, a service is a commodity, and the WSP conducts auction and sells the service to be accessed to the base station;
assuming that all access services in the network get an equal proportion of resources, if the number of services connected to base station c is N c Then, the ratio r of base station resources to be obtained by each access service is:
the speed of service is used as the standard for measuring the channel state, and the Shannon formula is used to map the speed of service to the function of signal-to-interference-and-noise ratio (SINR), if the proportion of the whole bandwidth W of the base station obtained by each access service is r, the speed TP of service m is m Comprises the following steps:
TP m ＝rW log 2 (1+r mc ) (2)
r mc an SINR value for traffic m to base station c, defined as the sum of the noise power over signal power received by the traffic from its access base station c and the interference power received from other base stations;
assuming that all base stations are deployed at the same frequency and the service model is full buffering, then:
grouping the services as commodities, and distributing a service group by adopting multi-commodity auction:
the WSP selects M services as a service group, and a buyer can bid on any service combination in the service group and records the service combination as x j ＝U 1 U 2 ……U M ，U m = 0,1 represents whether or not service m is in the combination, x j Represents the jth service combination, with a total of J =2 M -1 service combination;
base station c pairs service combination x j Valuation V of c (x j ) Defined as it can be provided for a service combination x j Average rate per service in (1):
wherein s is c For the number of services accessed in the base station c,
the total number of the services in the current service combination;
note base station c pairs service combination x j Bid of q c (x j ) Since the auction model is honest, the base station will submit bids, i.e. q, with its own valuation c (x j )＝V c (x j )，
Defining an valuation r of a WSP WSP (x j ) Comprises the following steps:
wherein the content of the first and second substances,
the SINR average value of the service to the base station is obtained;
only the bids of which the price is more than or equal to the WSP estimation are reasonable bids, and all reasonable bids are based on bids above the SINR average value;
the WSP collects bids for the base stations and assigns different x' s j The bids are classified and unreasonable bids are filtered at the same time, and a bid combination G (x) is recorded on the assumption that K reasonable bids are provided j ) Comprises the following steps:
G(x j )＝[q c (x j )] 1×K (6)
a total of J G (x) j ) Matrix, let the corresponding indicator matrix delta (x) j ) Comprises the following steps:
δ(x j )＝[δ c (x j )] 1×K (7)
δ c (x j ) E {0,1} represents base station c to x j Bidding q c (x j ) Let A = { j | delta = c (x j ) =1} the number of winning traffic combination;
the goals and constraints of the multi-item auction model are as follows:
∑ j∈A x j = (1, \8230;, 1) (M1) (8-2)
q c (x j )≥r WSP (x j ) (8-3)
The objective function (8) finds the maximum bidding sum for the service group, so that the winning base station provides the maximum rate sum for all services in the service group, and the winning base station is the base station of which the submitted bidding sum is contained in the maximum bidding sum;
the constraint (8-1) states that for each base station c it can win at most one traffic combination;
the constraint (8-2) specifies that each service in the service group has and can only be sold to one base station;
the constraint (8-3) specifies that bids in the maximum bid sum must be greater than or equal to the WSP's valuation;
the method is characterized in that: the multi-commodity auction model is adopted for service connection, and the service multi-commodity auction process comprises the following steps:
step S11: service group formation: the WSP forms a service group according to the geographic position of the service, and executes an auction for each service;
step S12: auction preparation: measuring SINR of each service to all base stations and obtaining a composite access point set C m Designing an SINR threshold V in Only SINR is greater than or equal to V in The corresponding base station can enter the alternative set C of the service m Then the service will perform signaling interaction with the base stations in the set;
step S13: and (3) starting auction: first, all base stations submit a bid q to the WSP based on information obtained from the service c (x j ) The WSP then processes the collected bids, classifies the bids by service combination and based on their valuations r WSP (x j ) Unreasonable bidding is filtered, and finally the WSP solves the multi-commodity auction model under the condition that constraint conditions are met, and the maximum bidding sum is searched for the service group;
step S14: and (4) follow-up work: the WSP accesses the services in the service group to a winning base station, and simultaneously records evaluation of the services as a standard for later evaluation of whether the channel state is poor;
step S15: the next auction: after all the services in the last auction group are accessed to the base station, the auction is ended, the next auction is started, the WSP selects a new group of services to arrange access for the WSP, the services measure parameters again, and the whole multi-commodity auction is ended when all the services are sold;
the WSP selects 3 services to be accessed which are adjacent to each other in geographic position to form a service group, and the steps of searching the maximum bid sum are as follows:
step S13.1: g = { G (x) 1 )...G(x j )...G(x J )}
Classify and filter unreasonable bids [ q ] c (x j )] C×J ；
Step S13.2: from a certain G (x) j ) At the start of the process,
step S13.3: submit bid Q (x) j ) Is Q -1 (x j ) Remove other bids from the base station, record as G/Q -1 (x j )，Q G/c (x j ) Indicating that base station c is removed from bidding, G (x) j ) Maximum bid in (1);
step S13.4: repeating the steps S13.2 and S13.3 before all the services in the service group are distributed;
step S13.5: summing all the maximum bids to obtain a bid sum W, listing all bid sums and obtaining a maximum bid sum thereof, since different bid sums will result from different service combinations;
when each round of auction is finished, the service records WSP valuation as a lower limit rate for measuring the channel state after access, when the service rate is lower than the WSP valuation, the access base station can not provide the rate above the average value based on the SINR for the service, at the moment, the WSP arranges single commodity forward auction for the service, only reallocates the access base station for the service,
the business single-commodity auction process comprises the following steps:
step S21: rate detection and assessment: the service detects the speed of the WSP once every t seconds, and when the speed is lower than the WSP estimation updated by the last auction, the service sends a re-auction request to the WSP;
step S22: auction preparation: the WSP receives the service request, informs the service of auction preparation after confirming that no errors exist, measures SINR of all base stations and screens out an access point set C m Then the service and the alternative base station carry out signaling interaction, and the alternative base station obtains service information;
step S23: and (3) starting auction: the base station submits the bidding for the service, the WSP collects the bidding of all the base stations and filters unreasonable bidding, the WSP seeks the maximum bidding sum for the service group according to the formula under the condition of satisfying the constraint condition, and the base station submitting the maximum bidding sum in the maximum bidding sum is the winning base station;
step S24: and (4) follow-up work: the WSP accesses the service with the poor channel state into a new winning base station, and the service updates the WSP valuation recorded by the last auction into the WSP valuation of the auction;
the subsequent work of step S24 also includes the WSP settling the base station rewards according to the base station profits;
the specific steps of the WSP for settling the base station rewards according to the base station profits are as follows:
step S24.1: if the service combination won by the winning base station c is j, the winning base station c wins a cross price p c (x j ) Comprises the following steps: p is a radical of c (x j )＝max{r WSP (x j ),V(c)-∑ u≠c ∑ h≠j δ u ′(x h )q u (x h )}，
Wherein
For maximum sum of bids when winning base station c is not engaged in bidding u≠c ∑ h≠j δ u ′(x h )q u (x h ) For the current maximum bid and the sum of bids of other base stations;
step S24.2: for the special case when M =1 and J =1, the bargain price p c Comprises the following steps: p is a radical of formula c ＝max{r WSP ,max∑ u≠c q u Where max sigma u≠c q u A maximum bid when winning base station c is not engaged in bidding;
step S24.3: since the VCG mechanism is an extension of the next highest auction, its bid price p is for winning base station c c (x j ) Less than its winning bid q c (x j ) I.e. r WSP (x j )≤p c (x j )≤q c (x j )；
Step S24.4: z the effectiveness obtained by the winning base station c due to winning the service combination j c (x j )＝V c (x j )-p c (x j ) The utility of the base station that does not get service access is 0, the utility Z that WSP gets due to selling service combination j WSP (x j )＝p c (x j )-r WSP (x j )；
Step S24.5: to encourage base stations to participate in bidding, when a service is updated to access a base station, the WSP will award money to the base station that previously served the service, the money award being proportional to the base station gain, which is defined as:
where a (n) is an increasing function of the detection round n,
is the number of services in service combination j, t c The time for the base station c to service the service.
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