CN109152060A - Transmitter channel allocation model and method in short wave downlink communication - Google Patents
Transmitter channel allocation model and method in short wave downlink communication Download PDFInfo
- Publication number
- CN109152060A CN109152060A CN201811128742.7A CN201811128742A CN109152060A CN 109152060 A CN109152060 A CN 109152060A CN 201811128742 A CN201811128742 A CN 201811128742A CN 109152060 A CN109152060 A CN 109152060A
- Authority
- CN
- China
- Prior art keywords
- transmitter
- channel
- user
- strategy
- probability
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000004891 communication Methods 0.000 title claims abstract description 126
- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000005381 potential energy Methods 0.000 claims abstract description 10
- 238000005516 engineering process Methods 0.000 claims abstract description 6
- 230000006870 function Effects 0.000 claims description 30
- 230000005540 biological transmission Effects 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 7
- 238000013507 mapping Methods 0.000 claims description 6
- 230000010354 integration Effects 0.000 claims description 5
- 238000005457 optimization Methods 0.000 claims description 4
- 230000009286 beneficial effect Effects 0.000 claims description 3
- 210000004209 hair Anatomy 0.000 claims description 3
- 230000004044 response Effects 0.000 claims description 3
- 238000013179 statistical model Methods 0.000 abstract 1
- 238000004422 calculation algorithm Methods 0.000 description 10
- 238000011160 research Methods 0.000 description 5
- 238000001228 spectrum Methods 0.000 description 5
- 230000001186 cumulative effect Effects 0.000 description 4
- 238000000354 decomposition reaction Methods 0.000 description 4
- 238000013468 resource allocation Methods 0.000 description 3
- 230000006641 stabilisation Effects 0.000 description 3
- 238000011105 stabilization Methods 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005315 distribution function Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 241000208340 Araliaceae Species 0.000 description 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000001934 delay Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 235000008434 ginseng Nutrition 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 238000006116 polymerization reaction Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/53—Allocation or scheduling criteria for wireless resources based on regulatory allocation policies
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/022—Site diversity; Macro-diversity
- H04B7/024—Co-operative use of antennas of several sites, e.g. in co-ordinated multipoint or co-operative multiple-input multiple-output [MIMO] systems
-
- 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
- H04W72/543—Allocation or scheduling criteria for wireless resources based on quality criteria based on requested quality, e.g. QoS
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Quality & Reliability (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention discloses a transmitter channel allocation model and a method in short wave downlink communication. The model is as follows: the probability statistical model and the downlink channel diversity technology are combined to construct a corresponding user communication probability model, and the system communication probability is optimized by adjusting the downlink transmitter channel allocation strategy. The method comprises the following steps: the problem of large decision space is decomposed into two sub-problems of channel matching and transmitter allocation; aiming at the problem of channel matching, a many-to-one matching game model is constructed, and stable transmitter-channel matching under the expected communication probability of a maximized system is calculated; aiming at the problem of transmitter distribution, a potential energy game model is constructed, and an optimal distribution strategy under the communication probability of a maximization system is calculated to obtain the optimal distribution strategy; and finally, calculating the communication probability of the system. The invention solves the problem of large decision space in short-wave communication and ensures the reliability of short-wave user communication.
Description
Technical field
The invention belongs to wireless communication technology field, the transmitter channel in especially a kind of shortwave downlink communication distributes mould
Type and method.
Background technique
Short wave communication has many advantages, such as that maintenance cost is low, equipment is simple, networking is convenient, has in future development huge
Potentiality.However, the disadvantages of short wave channel propagation quality is unstable, serious interference, limited frequency resource, limits short wave communication
Development.For shortwave downlink transmission process, in order to improve communication reliability, often by the way of channel diversity.With shortwave
User increases to increase with business demand, because shortwave spectrum resource is limited, how efficiently to distribute short wave channel resource becomes more next
It is more important.For channel resource allocation problem, there are many researchs under mobile network's scene.It is proposed that carrier wave polymerization (ginseng
Examine document, Yuanhui Zhang, Chunrong Kan, Kun Xu, et al, " Distributed carrier
aggregation in small cell networks:a game-theoretic approach,"Ksii
Transactions on Internet & Information Systems, vol.9, no.12,2015.) cut-in method,
Improve spectrum utilization efficiency.However, the research at present about short wave channel resource allocation is less, existing short wave channel research is big
Part is all to be concerned with how to select reasonable channel from the unstable short wave channel of propagation quality.
At present about in the research of short wave channel, having research work (bibliography, Bernard.Lacaze, " Modeling
the HF channel with Gaussian random delays,"Signal processing,vol.64,no.2,
Pp.215-220,1998.) short wave channel is modeled using gaussian random delay.There are correlative study (bibliography, Zhiqiang
Qin, Jinlong Wang, Jin Chen et al, " Opportunistic channel access with repetition
time diversity and switching cost:a block multi-armed bandit approach,"
Wireless Networks, vol.24, no.5, pp.1683-1697,2018.) by multi-arm Slot Machine thought be applied to link setup letter
In road selection.But because shortwave user is less before, downlink diversity channel resource is sufficient, current rare people divides shortwave downlink
Collection technology and channel resource allocation, which are optimized integration, to be studied, often using mode is empirically evenly distributed at random, so frequently
The utilization rate of spectrum resource is lower, is not able to satisfy growing frequency spectrum resource demand.
Summary of the invention
The purpose of the present invention is to provide the transmitter channel distribution models and method in a kind of shortwave downlink communication, short
Towards business demand under wave downlink transfer scene, reliable downlink diversity strategy is obtained by optimization system communication probability.
The technical solution for realizing the aim of the invention is as follows: the transmitter channel in a kind of shortwave downlink communication distributes mould
Type, the model portray shortwave system communication probability as follows: in shortwave system descending transmitting scene, using channel diversity
Technology guarantees the reliability of short wave communication;Short wave channel diversity refers to that platform is sent out to user on the different channels with multiple transmitters
Identical signal is sent, received multiple signal integrations are improved reception stability by user;For arbitrary user, success communication
Probability by the availability of diversity channel, user's communication requirement probability and occupy same channel transmitter probability of interference determine;
By adjusting downstream transmitter channel assignment strategy, the maximized target of the total communication probability of system is realized.
A kind of transmitter channel distribution method in shortwave downlink communication, comprising the following steps:
Step 1, by shortwave down channel diversity optimization problem, transmitter-channel matched and transmitter diversity point are decomposed into
With two sub-problems;
Step 2, by transmitter-channel matched problem, it is modeled as many-one matching game, matching both sides are all transmitters
And available channel;
Step 3, each transmitter defines transmitter each according to the availability of available channel and the business demand of all users
Expectation communication probability on available channel, and respectively obtain the matching preference list of transmitter and available channel;
Step 4, stable transmitter-channel matched strategy under maximization system expectation communication probability is calculated;
Step 5, under stable transmitter-channel matched strategy, by transmitter diversity assignment problem, it is rich to be modeled as potential energy
Model is played chess, the participant of game is all users with mission requirements in shortwave system;
Step 6, each user constructs the transmitter diversity strategy of oneself, introduces the mutually beneficial betting model in space part, according to being
It is no to select identical transmitter that other users are divided into neighbours and non-neighbor user, and define local communication probability utility function;
Step 7, the optimal distribution strategy maximized under system communication probability is calculated, optimal distribution strategy is obtained.
Further, transmitter-channel matched problem is modeled as many-one matching game, specifically such as described in step 2
Under:
Betting model G1Is defined as:
WhereinFor set of available channels,For collection of transmitters;Preference relation >mAnd >fThe respectively letter of transmitter m
The transmitter preference relation of road preference relation and channel f;
One many-one matching u is one from setTo setMapping and two preference relation >m
And >f, wherein mapping relations refer to that a transmitter only takes up a channel, and a channel can be occupied by multiple transmitters:
1) for each channelAnd | μ (f) | ∈ 1,2 ..., qc};
2) for each transmitterAnd | μ (f) |=1;
3) f ∈ μ (m) is and if only if m ∈ μ (f);
μ (f) refers to the subset of the transmitter using channel f, μ (m) be by the subset of the transmitter m short wave channel accessed,
QuotaIt is that each channel can be with the maximum number of matched transmitter.
Further, each transmitter described in step 3 is according to the availability of available channel and the business demand of all users,
Expectation communication probability of the transmitter on each available channel is defined, and respectively obtains the matching preference column of transmitter and available channel
Table, specific as follows:
Consider the communication probability of entire shortwave system, and uses rmIndicate that expectation communication of the transmitter m on a certain channel is general
Rate:
Wherein fmFor the available channel of transmitter m;Indicate transmitter m in channel fmSend data to user n's
Channel is available,Indicate that channel is unavailable;Indicate transmitter m in channel fmSend data to channel when user n
Usable probability;pnIndicate the communication requirement of user n;
For two available channel f1mAnd f2m, the preference of each transmitter m are as follows:
For two transmitter m in available transmission machine1And m2, the preference of each channel f are as follows:
Further, stable transmitter-channel matched under calculating maximization system expectation communication probability described in step 4
Strategy, specific as follows:
Step 4.1, initialization: each transmitter and each channel obtain matching preference list, and calculate matching round;
Step 4.2, matching: the channel for not matching transmitter highest priority into oneself preference list sends request, and
The channel is deleted from preference list;Each channel is according to oneself quota and preference list, from request list and current
With selecting best transmitter in transmitter;
Step 4.3, convergence: circulation step 4.2 is sky, matching process until all transmitter matchings or preference list
Terminate, obtains stable transmitter-channel matched strategy.
Further, described in step 5 under stable transmitter-channel matched strategy, transmitter diversity distribution is asked
Topic, is modeled as potential energy betting model, specific as follows:
The betting model is defined as:
WhereinFor user's set;A2nFor the transmitter strategy set of user n selection;u2nFor user
Communication probability utility function set.
Further, definition local communication probability utility function described in step 6, specific as follows:
The local communication probability utility function u2 of each user nn(mn,m-n) are as follows:
Wherein mn,m-nThe transmitter strategy for respectively indicating the selection of user's n channel diversity and all users in addition to user n
Transmitter strategy set, JnIt is that the user of identical transmitter has been selected to gather with user n,It is JnIn all users selection
Transmitter strategy;
WhereinIt is the communication probability of user k, is defined as:
Wherein R (m, f, n) is the communication probability of link m-f-n, is defined as:
Wherein δm,f,n=1 expression transmitter m sends data to user n i.e. link m-f-n by channel f), δm,f,n=0 table
Show that link m-f-n is disabled;θm,f,nIndicate channel usable probability of the transmitter m when channel f is sent to user n;ImChoosing
User's set of transmitter m is selected;pkIndicate user's communication requirement probability;IfIndicate the collection of transmitters of all selection channel f;
Transmitter decision function f (θm,f,n,θm1,f,n) be defined as
JnIt is to have selected identical transmitter with user n and the user that user n is interfered may have been gathered, is defined as:
Wherein mnWith m 'nIt respectively indicates user n currently and prepares the transmitter strategy of selection.
Further, calculating described in step 7 maximizes the optimal distribution strategy under system communication probability, obtains most optimal sorting
It is specific as follows with strategy:
Step 7.1, initialization: each user randomly chooses transmitter diversity strategy, and the number of iterations is arranged;
Step 7.2, detection: one user of random selection operates, and selects the neighbor user of the user, and calculate the use
The local communication probability utility function value of all possible allocation strategies in family, can bring optimal partial communication probability according to probability selection
The allocation strategy of utility function;
According to (7) formula, the communication probability of whole system is obtained are as follows:
Optimal distribution strategy P2 are as follows:
P2:
Step 7.3, convergence: circulation step 7.2, user updates transmitter allocation strategy, until the distribution plan of all users
It slightly selects convergence or reaches the number of iterations of setting, detection study terminates, and obtains down channel diversity strategy;
Further, circulation step 7.2 described in step 7.3, user updates transmitter allocation strategy, specific as follows:
The transmitter selection strategy m before other users repetition in addition to user ni(k+1)=mi(k), the use for choosing
Family n calculates local communication probability utility function of the user n under all possible transmitter selection strategies first, in accordance with formula (6),
Current best transmitter strategy is obtained according to best response principle
Then user decides whether to receive according to formula (14)Wherein receive and the probability of refusal is respectivelyAnd mn(k+1)=mn(k), the transmitter strategy P of oneself is updated:
Wherein, β is learning parameter,Assume that n selects optimum transmitter strategyUtility function afterwards, u2 (mn
(k)) user n selection transmitter strategy m when being kth time iterationn(k) utility function after.
Compared with prior art, the present invention its remarkable advantage is: (1) having fully considered short wave channel availability and business
Demand combines probability statistics model and downlink diversity technique, constructs shortwave system communication probability, describes more accurately
True Shortwave Communication System scene;(2) the huge problem of decision space is decomposed into two sub-problems, by transmitter-channel
With being configured to matching game and transmitter assignment problem is configured to potential energy game, it was demonstrated that the presence of stable matching and Nash Equilibrium
Property, decomposition of the theories integration (3) by problem is provided for the design of algorithm, so that shortwave downlink diversity policy calculation restrains
Faster, computing cost is reduced, extensive shortwave system is suitable for.
Detailed description of the invention
Fig. 1 is that multichannel Shortwave Communication System is shown in transmitter channel distribution model in shortwave downlink communication of the present invention
It is intended to.
Fig. 2 is the schematic block diagram of the transmitter channel deversity scheme in shortwave downlink communication of the present invention.
Fig. 3 is the system communication probability pair of model method and optimal policy in the number of iterations increase in the embodiment of the present invention
Than figure.
Fig. 4 is the cumulative probability distribution that 1 algorithm of subproblem restrains number under different transmitters number in present example
Figure.
Fig. 5 is the cumulative probability distribution map that 2 algorithm of subproblem restrains number under different user number in present example.
Specific embodiment
Fig. 1 show Shortwave Communication System downlink diversity transmission schematic diagram.In Fig. 1, different users possesses different
Communication requirement, and different short wave channels are different for the availability of different user.The multiple transmitters of system distribution give each user,
By increasing the reliability for sending channel quantity to improve transmission.Assuming that user's n diversity strategy is { (m1,f1),(m2,f2),(m3,
f3), then the communication probability that the user is properly received channel over multiple channels is 1- (1-R (m1,f1,n))(1-R(m2,f2,
n))(1-R(m3,f3, n)), which shows that the user diversity number of channel is more, and it is higher to communicate the process.Pass through diversity channel plan
It slightly selects, realizes system communication maximization target under the premise of meeting communication requirement.
Transmitter channel distribution model in a kind of shortwave downlink communication of the present invention, is portrayed as follows: in shortwave system descending
In transmitting scene, guarantee the reliability of short wave communication using channel diversity technology.Short wave channel diversity refers to platform with multiple hairs
It penetrates machine and sends identical signal to user on the different channels, received multiple signal integrations are improved reception stability by user.
For arbitrary user, the probability of success communication by the availability of diversity channel, user's communication requirement probability and is occupied identical
The transmitter probability of interference of channel determines;By adjusting downstream transmitter channel assignment strategy, the total communication probability of system is realized most
The target changed greatly.
Transmitter channel deversity scheme in conjunction with Fig. 2, in shortwave downlink communication of the present invention, comprising the following steps:
Step 1, by shortwave down channel diversity optimization problem, transmitter-channel matched and transmitter diversity point are decomposed into
With two sub-problems;
Step 2, by transmitter-channel matched problem, it is modeled as many-one matching game, matching both sides are all transmitters
And available channel;
Step 3, each transmitter defines transmitter each according to the availability of available channel and the business demand of all users
Expectation communication probability on available channel, and respectively obtain the matching preference list of transmitter and available channel;
Step 4, stable transmitter-channel matched under maximization system expectation communication probability is calculated, specific as follows:
Step 4.1, initialization: each transmitter and each channel obtain matching preference list, and calculate matching round;
Step 4.2, matching: the channel for not matching transmitter highest priority into oneself preference list sends request, and
The channel is deleted from preference list;Each channel is according to oneself quota and preference list, from request list and current
With selecting best transmitter in transmitter;
Step 4.3, convergence: circulation step 4.2 is sky, matching process until all transmitter matchings or preference list
Terminate, obtains stable transmitter-channel matched strategy;
Step 5, under stable transmitter-channel matched strategy, by transmitter diversity assignment problem, it is rich to be modeled as potential energy
Model is played chess, the participant of game is all users with mission requirements in shortwave system;
Step 6, each user constructs the transmitter diversity strategy of oneself, introduces the mutually beneficial betting model in space part, according to being
It is no to select identical transmitter that other users are divided into neighbours and non-neighbor user, and define local communication probability utility function;
Step 7, the optimal distribution strategy maximized under system communication probability is calculated, obtains optimal distribution strategy, specifically such as
Under:
Step 7.1, initialization: each user randomly chooses transmitter diversity strategy, and the number of iterations is arranged;
Step 7.2, detection: one user of random selection operates, and selects the neighbor user of the user, and calculate the use
The local communication probability utility function value of all possible allocation strategies in family, can bring optimal partial communication probability according to probability selection
The allocation strategy of utility function;
Step 7.3, convergence: setting is restrained or reached to circulation step 7.2 until the allocation strategy selection of all users
The number of iterations, detection study terminate, and obtain down channel diversity strategy.
Specific implementation of the invention is as follows:
One, shortwave down channel diversity PROBLEM DECOMPOSITION described in step 1 is two sub-problems, specific as follows:
A Shortwave Communication System is considered, wherein having N number of user, M transmitter, F available channel and k diversity letter
Road.By analytical calculation, all possible strategy size isFor one include 12 transmitters, 6 users,
The shortwave system that 10 short wave channels and diversity number are 3, possible strategy number are 1.1338e+26.As it can be seen that the decision of the problem
Space is very huge, therefore is the low subproblem of two complexities by former PROBLEM DECOMPOSITION: transmitter-channel matched and transmitter point
Collection distribution.
Two, short-wave transmitter-channel matched problem is modeled as many-one matching game, the betting model described in step 2
Is defined as:
WhereinFor set of available channels,For collection of transmitters;Preference relation >mAnd >fThe respectively letter of transmitter m
The transmitter preference relation of road preference relation and channel f;
One many-one matching u is one from setTo setMapping and two preference relation >m
And >f, wherein mapping relations refer to that a transmitter only takes up a channel, and a channel can be occupied by multiple transmitters:
1) for each channelAnd | μ (f) | ∈ 1,2 ..., qc};
2) for each transmitterAnd | μ (f) |=1;
3) f ∈ μ (m) is and if only if m ∈ μ (f).
μ (f) refers to the subset of the transmitter using channel f, μ (m) be by the subset of the transmitter m short wave channel accessed,
Quota be each channel can with the maximum number of matched transmitter, byIt indicates.
Three, expectation communication probability of the transmitter on each available channel is defined described in step 3, and respectively obtains transmitter
It is specific as follows with the matching preference list of available channel:
Consider the communication probability of entire shortwave system, and uses rmIndicate that expectation communication of the transmitter m on a certain channel is general
Rate:
Wherein fmFor the available channel of transmitter m;Indicate transmitter m in channel fmSend data to user n's
Channel is available,Indicate that channel is unavailable;Indicate transmitter m in channel fmSend data to channel when user n
Usable probability;pnIndicate the communication requirement of user n;
For two available channel f1mAnd f2m, the preference of each transmitter m are as follows:
For two transmitter m in available transmission machine1And m2, the preference of each channel f are as follows:
Four, stabilization transmitter-channel matched under maximization system expectation communication probability is calculated, specific as follows:
Ideal transmitter-channel matched strategy P1 are as follows:
P1:
Five, described in step 5 in the case where stablizing transmitter-channel matched strategy, transmitter diversity assignment problem is modeled as gesture
Energy betting model, the betting model is defined as:
G2={ N, { A2n}n∈N,{u2n}n∈N} (6)
WhereinFor user's set;A2nFor the transmitter strategy set of user n selection;u2nFor user
Communication probability utility function set.
Further, definition local communication probability utility function described in step 6, specific as follows:
The local communication probability utility function of each user n are as follows:
Wherein mn,m-nThe transmitter strategy for respectively indicating the selection of user's n channel diversity and all users in addition to user n
Transmitter strategy set, JnIt is that the user of identical transmitter has been selected to gather with user n,It is JnIn all users selection
Transmitter strategy.
WhereinIt is the communication probability of user k, is defined as:
Wherein R (m, f, n) is the communication probability of link m-f-n, is defined as:
Wherein δm,f,n=1 expression transmitter m sends data to user n (link m-f-n), δ by channel fm,f,n=0 table
Show that link m-f-n is disabled;θm,f,nIndicate channel usable probability of the transmitter m when channel f is sent to user n;ImChoosing
User's set of transmitter m is selected;pkIndicate user's communication requirement probability;IfIndicate the collection of transmitters of all selection channel f;
Transmitter decision function f (θm,f,n,θm1,f,n) be defined as
Six, calculating described in step 7 maximizes the optimal distribution strategy under system communication probability, obtains optimum allocation plan
Slightly, specific as follows:
According to (7) formula, the communication probability of whole system is obtained are as follows:
Optimal distribution strategy P2 are as follows:
P2:
Seven, update user iterative emission machine allocation strategy described in step 7.2, specific as follows:
The transmitter selection strategy m before other users repetition in addition to user ni(k+1)=mi(k), the use for choosing
Family n calculates local communication probability utility function of the user n under all possible transmitter selection strategies first, in accordance with formula (6),
Current best transmitter strategy is obtained according to best response principle
Then user decides whether to receive according to formula (15)Wherein receive and the probability of refusal is respectivelyAnd mn(k+1)=mn(k), the transmitter strategy of oneself is updated:
Wherein, β is learning parameter,Assume that n selects optimum transmitter strategyUtility function afterwards, u2 (mn
(k)) user n selection transmitter strategy m when being kth time iterationn(k) utility function after.
For the mentioned matching algorithm of subproblem 1, can prove to obtain stable matching;The game mould constructed for subproblem 2
Type can prove that it, for potential energy game, at least has a Nash Equilibrium Solution.And the limited improved property of potential energy game is utilized,
The algorithm Solving Nash Equilibrium for meeting the property can be designed.
Embodiment 1
A specific embodiment of the invention is described below: system emulation uses Matlab software, and parameter setting does not influence
It is general;N number of user and several platforms are randomly dispersed in the network scenarios of a 500km × 500km, wherein each transmitter
Transmission power be identical;The usable probability θ of channelm,f,nWith user's communication requirement pnIt is known that and subscriber channel diversity number
It is fixed;Learning coefficient β is changed according to actual utility value, and is increased as the number of iterations increases so that result gradually from
Learn detection process and is biased to convergence;Shown simulation result is average value after 300 emulation.
Consider the shortwave downlink deversity scheme, for example above-mentioned specific implementation process of concrete operations, until transmitter distributes
Policy selection convergence or the number of iterations for reaching setting, user carry out diversity according to the result of step 7 in specific implementation process
Signal transmission.
Analysis of simulation result:
Fig. 3 be in the scene of 4 transmitters, 3 available channels and 3 users using mentioned method and optimal policy with
The number of iterations increases system communication probability situation of change.It can be seen that as the number of iterations increases, the system communication probability of mentioned method
It is continuously increased, finally converges to a stabilization result, final result is optimal 90% or more of the communication probability under strategy, can
See, the down channel diversity strategy that mentioned algorithm obtains is reliably, to meet user's communication requirement.
Fig. 4 gives the convergence number of cumulative distribution function and 1 algorithm of subproblem under 40 available channel scenes
Between relationship.As it can be seen that the matching algorithm can obtain stable matching, and convergent iterations number is no more than 30.Fig. 5 gives
Pass between the convergence number of 2 algorithm of cumulative distribution function and subproblem under 12 transmitters and 10 available channels
System, it is seen that mentioned method can achieve preferable system communication probability, and convergence rate is very fast.
To sum up, the shortwave down channel diversity betting model and allocation algorithm proposed by the present invention based on probability statistics, fills
Divide and consider the unreliable feature of Shortwave Communication System channel and the huge problem of decision space, constructs user's communication probability model, and will
PROBLEM DECOMPOSITION is two low complex degree subproblems, solve using matching game and potential energy Game Characteristics having obtained stabilization
Reliable downlink diversity strategy, improves spectrum utilization efficiency.By comparing with the optimal diversity strategy based on exhaustive method, imitate
It is true the result shows that mentioned method gained system communication probability be optimal 90% or more, meet customer service demand, and method
Convergence rate is very fast, is suitable for extensive Shortwave Communication System.
Claims (9)
1. the transmitter channel distribution model in a kind of shortwave downlink communication, which is characterized in that the model is to shortwave system communication
Probability is portrayed as follows: in shortwave system descending transmitting scene, guarantee short wave communication using channel diversity technology can
By property;Short wave channel diversity refers to that platform sends identical signal to user on the different channels with multiple transmitters, and user will receive
Multiple signal integrations improve reception stability;For arbitrary user, the probability of success communication by diversity channel can
Expenditure, user's communication requirement probability and the transmitter probability of interference decision for occupying same channel;By adjusting downstream transmitter letter
Road allocation strategy realizes the maximized target of the total communication probability of system.
2. the transmitter channel distribution method in a kind of shortwave downlink communication, which comprises the following steps:
Step 1, by shortwave down channel diversity optimization problem, transmitter-channel matched and transmitter diversity distribution two are decomposed into
A subproblem;
Step 2, by transmitter-channel matched problem, it is modeled as many-one matching game, matching both sides are all transmitters and can
Use channel;
Step 3, each transmitter defines transmitter each available according to the availability of available channel and the business demand of all users
Expectation communication probability on channel, and respectively obtain the matching preference list of transmitter and available channel;
Step 4, stable transmitter-channel matched strategy under maximization system expectation communication probability is calculated;
Step 5, under stable transmitter-channel matched strategy, by transmitter diversity assignment problem, it is modeled as potential energy game mould
Type, the participant of game are all users with mission requirements in shortwave system;
Step 6, each user constructs the transmitter diversity strategy of oneself, the mutually beneficial betting model in space part is introduced, according to whether choosing
It selects identical transmitter and other users is divided into neighbours and non-neighbor user, and define local communication probability utility function;
Step 7, the optimal distribution strategy maximized under system communication probability is calculated, optimal distribution strategy is obtained.
3. the transmitter channel distribution method in shortwave downlink communication according to claim 2, which is characterized in that step 2
It is described that transmitter-channel matched problem is modeled as many-one matching game, specific as follows:
Betting model G1Is defined as:
WhereinFor set of available channels,For collection of transmitters;Preference relationWithThe channel of respectively transmitter m is inclined
The transmitter preference relation of good relationship and channel f;
One many-one matching u is one from setTo setMapping and two preference relationsWith
Wherein mapping relations refer to that a transmitter only takes up a channel, and a channel can be occupied by multiple transmitters:
1) for each channelAnd | μ (f) | ∈ 1,2 ..., qc};
2) for each transmitterAnd | μ (f) |=1;
3) f ∈ μ (m) is and if only if m ∈ μ (f);
μ (f) refers to the subset of the transmitter using channel f, and μ (m) is by the subset of the transmitter m short wave channel accessed, quotaIt is that each channel can be with the maximum number of matched transmitter.
4. according to the transmitter channel distribution method in shortwave downlink communication as claimed in claim 2, which is characterized in that step 3 institute
Each transmitter stated defines transmitter on each available channel according to the availability of available channel and the business demand of all users
Expectation communication probability, and respectively obtain the matching preference list of transmitter and available channel, it is specific as follows:
Consider the communication probability of entire shortwave system, and uses rmIndicate expectation communication probability of the transmitter m on a certain channel:
Wherein fmFor the available channel of transmitter m;Indicate transmitter m in channel fmSend data to the channel of user n
It can use,Indicate that channel is unavailable;Indicate transmitter m in channel fmChannel when sending data to user n is available
Probability;pnIndicate the communication requirement of user n;
For two available channel f1mAnd f2m, the preference of each transmitter m are as follows:
For two transmitter m in available transmission machine1And m2, the preference of each channel f are as follows:
5. according to the transmitter channel distribution method in shortwave downlink communication as claimed in claim 2, which is characterized in that step 4 institute
Stable transmitter-channel matched the strategy calculated under maximization system expectation communication probability is stated, specific as follows:
Step 4.1, initialization: each transmitter and each channel obtain matching preference list, and calculate matching round;
Step 4.2, matching: the channel for not matching transmitter highest priority into oneself preference list sends request, and should
Channel is deleted from preference list;Each channel is sent out according to oneself quota and preference list from request list and current matching
It penetrates in machine and selects best transmitter;
Step 4.3, convergence: circulation step 4.2 is sky, matching process knot until all transmitter matchings or preference list
Beam obtains stable transmitter-channel matched strategy.
6. according to the transmitter channel distribution method in shortwave downlink communication as claimed in claim 2, which is characterized in that step 5 institute
State under stable transmitter-channel matched strategy, by transmitter diversity assignment problem, be modeled as potential energy betting model, have
Body is as follows:
The betting model is defined as:
WhereinFor user's set;A2nFor the transmitter strategy set of user n selection;u2nFor user's communication
Probability utility function set.
7. according to the transmitter channel distribution method in shortwave downlink communication as claimed in claim 2, which is characterized in that step 6 institute
The definition local communication probability utility function stated, specific as follows:
The local communication probability utility function u2 of each user nn(mn,m-n) are as follows:
Wherein mn,m-nRespectively indicate the transmitter strategy of user's n channel diversity selection and the hair of all users in addition to user n
Penetrate machine strategy set, JnIt is that the user of identical transmitter has been selected to gather with user n,It is JnIn all users selection hair
Penetrate machine strategy;
WhereinIt is the communication probability of user k, is defined as:
Wherein R (m, f, n) is the communication probability of link m-f-n, is defined as:
Wherein δm,f,n=1 expression transmitter m sends data to user n i.e. link m-f-n by channel f), δm,f,n=0 indicates chain
Road m-f-n is disabled;θm,f,nIndicate channel usable probability of the transmitter m when channel f is sent to user n;ImIt selects
The user of transmitter m gathers;pkIndicate user's communication requirement probability;IfIndicate the collection of transmitters of all selection channel f;Transmitting
Machine decision function f (θm,f,n,θm1,f,n) be defined as
JnIt is to have selected identical transmitter with user n and the user that user n is interfered may have been gathered, is defined as:
Wherein mnWith m 'nIt respectively indicates user n currently and prepares the transmitter strategy of selection.
8. according to the transmitter channel distribution method in shortwave downlink communication as claimed in claim 7, which is characterized in that step 7 institute
The calculating stated maximizes the optimal distribution strategy under system communication probability, obtains optimal distribution strategy, specific as follows:
Step 7.1, initialization: each user randomly chooses transmitter diversity strategy, and the number of iterations is arranged;
Step 7.2, detection: one user of random selection operates, and selects the neighbor user of the user, and calculate the user institute
It is possible that the local communication probability utility function value of allocation strategy, can bring optimal partial communication probability effectiveness according to probability selection
The allocation strategy of function;
According to (7) formula, the communication probability of whole system is obtained are as follows:
Optimal distribution strategy P2 are as follows:
Step 7.3, convergence: circulation step 7.2, user update transmitter allocation strategy, until the allocation strategy of all users selects
It selects convergence or reaches the number of iterations of setting, detection study terminates, and obtains down channel diversity strategy.
9. according to the transmitter channel distribution method in shortwave downlink communication according to any one of claims 8, which is characterized in that step 7.3
The circulation step 7.2, user updates transmitter allocation strategy, specific as follows:
The transmitter selection strategy m before other users repetition in addition to user ni(k+1)=mi(k), for the user n chosen,
Local communication probability utility function of the user n under all possible transmitter selection strategies is calculated first, in accordance with formula (6), according to
Best response principle obtains current best transmitter strategy
Then user decides whether to receive according to formula (14)Wherein receive and the probability of refusal is respectively
And mn(k+1)=mn(k), the transmitter strategy P of oneself is updated:
Wherein, β is learning parameter,Assume that n selects optimum transmitter strategyUtility function afterwards, u2 (mn(k))
User n selection transmitter strategy m when being kth time iterationn(k) utility function after.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811128742.7A CN109152060A (en) | 2018-09-26 | 2018-09-26 | Transmitter channel allocation model and method in short wave downlink communication |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811128742.7A CN109152060A (en) | 2018-09-26 | 2018-09-26 | Transmitter channel allocation model and method in short wave downlink communication |
Publications (1)
Publication Number | Publication Date |
---|---|
CN109152060A true CN109152060A (en) | 2019-01-04 |
Family
ID=64812710
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201811128742.7A Withdrawn CN109152060A (en) | 2018-09-26 | 2018-09-26 | Transmitter channel allocation model and method in short wave downlink communication |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109152060A (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110071752A (en) * | 2019-03-07 | 2019-07-30 | 中国人民解放军陆军工程大学 | Short wave multi-station fusion receiving low fault tolerance rapid combination method |
CN114217638A (en) * | 2021-12-15 | 2022-03-22 | 中国人民解放军66389部队88分队 | Dynamic deployment method for information acquisition of mobile station under task driving |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070060080A1 (en) * | 2005-09-09 | 2007-03-15 | Daisuke Nishimura | Receiver |
CN101425822A (en) * | 2008-12-03 | 2009-05-06 | 中兴通讯股份有限公司 | Frequency hopping method for supporting multiuser multiplexing single time slot |
CN102013910A (en) * | 2010-11-17 | 2011-04-13 | 中国人民解放军理工大学 | Short-wave multi-antenna signal enhancement receiving method |
CN104796181A (en) * | 2015-03-27 | 2015-07-22 | 中国人民解放军61469部队 | Short-wave double-antenna digital communication system and automatic receiving verification method for the same |
CN106102132A (en) * | 2016-06-12 | 2016-11-09 | 广州海格通信集团股份有限公司 | A kind of short-wave intelligent frequency-selecting and the shortwave networking implementation method of diversity |
-
2018
- 2018-09-26 CN CN201811128742.7A patent/CN109152060A/en not_active Withdrawn
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070060080A1 (en) * | 2005-09-09 | 2007-03-15 | Daisuke Nishimura | Receiver |
CN101425822A (en) * | 2008-12-03 | 2009-05-06 | 中兴通讯股份有限公司 | Frequency hopping method for supporting multiuser multiplexing single time slot |
CN102013910A (en) * | 2010-11-17 | 2011-04-13 | 中国人民解放军理工大学 | Short-wave multi-antenna signal enhancement receiving method |
CN104796181A (en) * | 2015-03-27 | 2015-07-22 | 中国人民解放军61469部队 | Short-wave double-antenna digital communication system and automatic receiving verification method for the same |
CN106102132A (en) * | 2016-06-12 | 2016-11-09 | 广州海格通信集团股份有限公司 | A kind of short-wave intelligent frequency-selecting and the shortwave networking implementation method of diversity |
Non-Patent Citations (1)
Title |
---|
WEN LI等: "Exploring channel diversity in HF communication systems: A matching-potential game approach", 《CHINA COMMUNICATIONS 》 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110071752A (en) * | 2019-03-07 | 2019-07-30 | 中国人民解放军陆军工程大学 | Short wave multi-station fusion receiving low fault tolerance rapid combination method |
CN114217638A (en) * | 2021-12-15 | 2022-03-22 | 中国人民解放军66389部队88分队 | Dynamic deployment method for information acquisition of mobile station under task driving |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Yoshida et al. | MAB-based client selection for federated learning with uncertain resources in mobile networks | |
CN109194763B (en) | Caching method based on small base station self-organizing cooperation in ultra-dense network | |
CN105873214B (en) | A kind of resource allocation methods of the D2D communication system based on genetic algorithm | |
CN106454700B (en) | D2D communication content distribution method based on social network | |
CN102769917B (en) | Combinational iteration optimization-based resource allocation method for device-to-device system | |
CN108391317A (en) | The resource allocation methods and system that D2D is communicated in a kind of cellular network | |
CN106792451A (en) | A kind of D2D communication resource optimization methods based on Multiple-population Genetic Algorithm | |
CN109905864A (en) | A kind of cross-layer Resource Allocation Formula towards electric power Internet of Things | |
CN104254130A (en) | Method, device and system for allocating D2D (Device-to-Device) user link and cellular user shared resources | |
CN108924934A (en) | Heterogeneous network interference management method based on multi dimensional resource distribution | |
CN108848045A (en) | D2D Communication Jamming management method based on joint interference alignment and power optimization | |
CN104507153B (en) | Small cell power control method under OFDMA | |
CN109152060A (en) | Transmitter channel allocation model and method in short wave downlink communication | |
CN111669759A (en) | Dynamic multi-channel cooperative sensing method based on deep Q network | |
CN109039494A (en) | A kind of 5G resource assignment method of communication system based on improvement harmonic search algorithm | |
Luo et al. | Performance analysis of non-ideal wireless PBFT networks with mmWave and terahertz signals | |
CN108809470B (en) | Clustering algorithm in ultra-dense cellular network | |
CN112954806B (en) | Chord graph coloring-based joint interference alignment and resource allocation method in heterogeneous network | |
CN110519728A (en) | A kind of vehicle-carrying communication resource allocation methods and device | |
CN106792480A (en) | D2D communication resource distribution algorithms based on cellular network | |
CN110139281A (en) | A method of the full duplex D2D sub-clustering resource allocation based on K-means | |
CN106793122B (en) | Method for safely allocating each bit minimized wireless resources of heterogeneous network | |
Dahrouj et al. | Coordinated scheduling for wireless backhaul networks with soft frequency reuse | |
Gkonis et al. | A New Subcarrier Allocation Strategy for MIMO‐OFDMA Multicellular Networks Based on Cooperative Interference Mitigation | |
Maaz et al. | Joint user association, power control and scheduling in multi-cell 5G networks |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
WW01 | Invention patent application withdrawn after publication | ||
WW01 | Invention patent application withdrawn after publication |
Application publication date: 20190104 |