CN102843691B - Femtocell network spectrum distributing method based on tabu search - Google Patents
Femtocell network spectrum distributing method based on tabu search Download PDFInfo
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Abstract
The invention provides a femtocell network spectrum distributing method based on a tabu search. The femtocell network spectrum distributing method mainly solves the problems that the conventional femtocell network spectrum distributing method has a poor distributing effect. The method comprises the following steps of: (1) drawing a femtocell network interference drawing, and randomly distributing the node into a node group so as to obtain an initial solution and an adaptive value thereof; (2) determining whether the adaptive value of the initial solution is 0, if so, accomplishing the distribution, if not so, generating current solution and the current optimal solution; and (3) generating the neighbourhood of current solution; (4) carrying out the non-tabu optimal solution in the neighbourhood or the optimal solution meeting the flouting rule, so as to obtain a new solution to replace the current solution; and (5) replacing the current optimal solution through the current solution, wherein if the adaptive value of the current optimal solution is 0, the spectrum distributing program can be obtained, if not, returning to step (3). With adoption of the femtocell network spectrum distributing method, a greater spectrum distributing program can be obtained when the femtocell network is in dense distribution; and the method can be suitable for achieving hybrid networking of a macro cell and the femtocell.
Description
Technical field
The invention belongs to wireless communication technology field, particularly fly the spectrum allocation may of cellular network, can be used for macrocellular and fly honeycomb mixed networking.
Background technology
Along with the develop rapidly of the communication technology, the requirement of people to transport service speed and quality is also more and more higher.In order at intra-area communication, Cellular Networks is used to cover whole region.The macrocellular covering radius that the Cellular Networks networking initial stage occurs is larger, be difficult to meet the requirement of user to signal quality and speed, but because the voice communication of 50% and the data communication of 70% all occur in indoor, so occurred flying honeycomb, it effectively can solve indoor voice-and-data business.Macrocellular with fly in honeycomb mixed networking, when flying the intensive covering of honeycomb, signal interference problem is particularly serious, and frequency spectrum resource is relatively deficient again, how effectively to avoid the interference flown in cellular network, and the utilance improving frequency spectrum just becomes the focus of expert and scholar's research.
Macrocellular is mainly divided into three kinds with the spectral band flying honeycomb mixed networking FMOS: the special spectral band of macrocellular, flies cell-specific spectral band, the recycling spectral band of FMOS.Macrocellular and the macrocellular flown in honeycomb mixed networking use the special spectral band of macrocellular; Fly honeycomb be divided into be positioned at interference sensitizing range ISA fly honeycomb and be positioned at non-interference sensitizing range NISA fly honeycomb, the honeycomb use that flies being positioned at interference sensitizing range ISA flies cell-specific spectral band, and the honeycomb that flies being positioned at non-interference sensitizing range NISA uses the recycling spectral band of FMOS.Fly cellular network spectrum allocation may problem, exactly the recycling spectral band of FMOS is distributed, thus reduce the frequency spectrum resource flying cellular network and take, improve the utilance of the recycling spectral band of FMOS, avoid the same layer interference flown between cellular network.
Existingly fly cellular network frequency spectrum distributing method mainly based on the method for graph theory, cellular network will be flown and convert graph coloring model to, then the Dsatur algorithm solving map colouring problem is utilized, obtain the spectrum allocation may result flying cellular network, although this method used time is less, but when flying cellular network density and being large, spectrum allocation may effect is poor, cause frequency spectrum resource utilization rate not high.
Summary of the invention
The object of the invention is to the deficiency for above-mentioned prior art, propose a kind ofly to fly cellular network spectral method based on TABU search, with reduce fly cellular network density large time, required frequency spectrum resource, thus improve the utilance of frequency spectrum resource, avoid the same layer interference flown between cellular network.
To achieve these goals, technical scheme of the present invention comprises the steps:
(1) by macrocellular with fly the honeycomb node that flies of non-interference sensitizing range in honeycomb mixed networking and represent, connect the node flown corresponding to honeycomb of interference mutually with limit, obtain interference figure H={N, V, E}, wherein N is node number, and V is the set of node, V={1,2, ..., N}, E are the set on limit;
(2) nodes all in interference figure H are randomized into K node set, obtain the initial solution S flying cellular network spectrum allocation may problem
0={ V
1, V
2..., V
k, wherein V
1, V
2..., V
krepresent node set 1,2 respectively ..., K;
(3) the adaptive value f (S of initial solution is solved
0)=∑ δ
uv, wherein
U, v represent two nodes mutually disturbed, V
lrepresent node set l, 1≤l≤K, as two node u mutually disturbed, v belongs to node set V
ltime, δ
uv=1, otherwise δ
uv=0, f (S
0) represent initial solution S
0the interference summation of middle existence;
(4) the adaptive value f (S of initial solution is judged
0) whether be 0, if f is (S
0)=0, then S
0={ V
1, V
2..., V
kfor flying cellular network spectrum allocation may result, K is required spectrum number; Otherwise, generate current solution S=S
0={ V
1, V
2..., V
kand current optimal solution S
best=S
0={ V
1, V
2..., V
k, then current solution adaptive value f (S)=f (S
0), current optimal solution adaptive value f (S
best)=f (S
0);
(5) by current solution S={V
1, V
2..., V
kinterior joint set V
iin node c, from node set V
imove to node set V
j, be designated as action (c, V
i, V
j), wherein c is and node set V
iin certain node exist interference a node, 1≤i≤K, 1≤j≤K, i ≠ j with current solution S everything, form current solution S neighborhood neigh;
(6) in the neighborhood neigh of current solution S, select the action (c, the V that make current solution adaptive value f (S) decline maximum
i, V
j)
min;
(7) action (c, the V that select in (6) is judged
i, V
j)
minwhether in taboo list, if not in taboo list, this action (c, V are performed to current solution S
i, V
j)
min, generate new explanation S '; Otherwise, judge this action (c, V
i, V
j)
minwhether meet and despise rule, if meet, this action (c, V are performed to current solution S
i, V
j)
minif do not meet, then in neighborhood neigh, delete this action, jump (6);
(8) action (c, the V that will perform in step (7)
i, V
j)
minadd taboo list, and Tabu Length is set for it, relatively new explanation S ' adaptive value f (S ') and the size of current solution adaptive value f (S), if f (S ') <f (S), then replace current solution S with new explanation S ', i.e. S=S ', current solution S adaptive value is replaced, i.e. f (S)=f (S ') by new explanation S ' adaptive value, otherwise, in neighborhood neigh, delete this action, jump (6);
(9) more current solution adaptive value f (S) and current optimal solution adaptive value f (S
best) between size, if f (S) <f (S
best), then replace current optimal solution S with current solution S
best, i.e. S
best=S, replaces current optimal solution adaptive value f (S with current solution adaptive value f (S)
best), i.e. f (S
best)=f (S), otherwise, perform step (10);
(10) current optimal solution adaptive value f (S is judged
best) whether be 0, if f is (S
best)=0, exports and flies cellular network spectrum allocation schemes S
bestwith required spectrum number K, otherwise, rebound step (2).
The present invention has the following advantages compared with prior art:
1, because the present invention adopts taboo strategy to the action performed, can effectively avoid roundabout search, jump out the restriction that existing graph coloring algorithm is easily absorbed in local optimum, therefore, it is possible to search globally optimal solution in neighborhood, obtain good spectrum allocation schemes;
2, because the present invention searches for optimal solution in the neighborhood of current solution, can effectively reduce the time complexity solving challenge, therefore be conducive to solving fly cellular network density large time spectrum allocation may problem, thus effectively improve the availability of frequency spectrum, save frequency spectrum resource.
Accompanying drawing explanation
Fig. 1 is FB(flow block) of the present invention;
Fig. 2 is the interference figure flying cellular network in the embodiment of the present invention;
Fig. 3 is the interference figure flying cellular network 1 in l-G simulation test of the present invention;
Fig. 4 is the interference figure flying cellular network 2 in l-G simulation test of the present invention;
Fig. 5 is the interference figure flying cellular network 3 in l-G simulation test of the present invention.
Embodiment
With reference to accompanying drawing 1, specific implementation step of the present invention is described below:
Step 1. by macrocellular with fly the honeycomb that flies of non-interference sensitizing range in honeycomb mixed networking and represent with node, connects the node flown corresponding to honeycomb mutually disturbed with limit, obtains interference figure H.
Embodiments of the invention are selected macrocellular and fly the cellular network that specifically flies of non-interference sensitizing range in honeycomb mixed networking to carry out spectrum allocation may, fly honeycomb node and represent, be designated as 1,2 ..., 11, the node 1 and 2,1 and 4,1 and 7,1 and 9 flown corresponding to honeycomb of interference is mutually connected with limit, 2 and 3,2 and 6,2 and 8,3 and 5,3 and 7,3 and 10,4 and 5,4 and 6,4 and 10,5 and 8,5 and 9,6 and 11,7 and 11,8 and 11,9 and 11,10 and 11, draw interference figure, as shown in Figure 2.
Nodes all in interference figure H are randomized into K node set by step 2., obtain the initial solution S flying cellular network spectrum allocation may problem
0={ V
1, V
2..., V
k, wherein V
1, V
2..., V
krepresent node set 1,2 respectively ..., K.
In the present embodiment, by the node 1,2 in Fig. 2 ..., 11 are randomized into 4 node set, obtain initial solution S
0={ V
1, V
2, V
3, V
4, wherein V
1={ 1,7,9}, V
2={ 2,6,11}, V
3={ 3}, V
4={ 4,5,8,10}.
Step 3. solves initial solution S
0adaptive value f (S
0)=∑ δ
uv, wherein
U, v represent two nodes mutually disturbed, V
lrepresent initial solution S
0={ V
1, V
2..., V
kin node set l, 1≤l≤K, as the node u of two mutual interference, v belongs to node set V
ltime, δ
uv=1, otherwise δ
uv=0, f (S
0) represent initial solution S
0the interference summation of middle existence.
In the present embodiment, obtain according to above-mentioned formulae discovery, initial solution S
0adaptive value f (S
0)=7.
Step 4. judges the adaptive value f (S of initial solution
0) whether be 0, if f is (S
0)=0, then S
0={ V
1, V
2..., V
kfor flying cellular network spectrum allocation may result, K is required spectrum number; Otherwise, generate current solution S=S
0={ V
1, V
2..., V
kand current optimal solution S
best=S
0={ V
1, V
2..., V
k, then current solution adaptive value f (S)=f (S
0), current optimal solution adaptive value f (S
best)=f (S
0).
In the present embodiment, initial solution S
0adaptive value f (S
0) be not 0, generate current solution S=S
0={ V
1, V
2, V
3, V
4and current optimal solution S
best=S
0={ V
1, V
2, V
3, V
4, then current solution adaptive value f (S)=f (S
0)=7, current optimal solution adaptive value f (S
best)=f (S
0)=7.
Step 5. is by current solution S={V
1, V
2..., V
kinterior joint set V
iin node c, from node set V
imove to node set V
j, be designated as action (c, V
i, V
j), wherein c is and node set V
iin certain node exist interference a node, 1≤i≤K, 1≤j≤K, i ≠ j, with current solution S everything, form current solution S neighborhood neigh.
In the present embodiment, learn according to above-mentioned steps, the neighborhood neigh of current solution S is (1, 1, 2), (1, 1, 3), (1, 1, 4), (2, 2, 1), (2, 2, 3), (2, 2, 4), (3, 4, 1), (3, 4, 2), (3, 4, 3), (4, 4, 1), (4, 4, 2), (4, 4, 3), (5, 2, 1), (5, 2, 3), (5, 2, 4), (6, 1, 2), (6, 1, 3), (6, 1, 4), (7, 4, 1), (7, 4, 2), (7, 4, 3), (8, 1, 2), (8, 1, 3), (8, 1, 4), (9, 4, 1), (9, 4, 2), (9, 4, 3), (10, 2, 1), (10, 2, 3), (10, 2, 4).
Step 6. is selected to make current solution adaptive value f (S) change maximum action (c, V in the neighborhood neigh of current solution S
i, V
j)
min.
In the present embodiment, in the neighborhood neigh of current solution S, action (1,1,3) is selected.
The action (c, the V that select in step 7. determining step 6
i, V
j)
minwhether in taboo list, if not in taboo list, this action (c, V are performed to current solution S
i, V
j)
min, generate new explanation S '; Otherwise, judge this action (c, V
i, V
j)
minwhether meet and despise rule, if meet, this action (c, V are performed to current solution S
i, V
j)
minif do not meet, then in neighborhood neigh, delete this action, return step 6; Taboo list, being forbid by all the table that the action performed is formed, is empty time initial.
Despise rule, refer to and S action (c, V are performed to current solution
i, V
j)
minrear generation new explanation S ', if new explanation adaptive value f (S ') is less than current solution adaptive value f (S), regardless of action (c, V
i, V
j)
minwhether in taboo list, all perform an action (c, V
i, V
j)
min.
In the present embodiment, because the action (1,1,3) selected in step 6 is not in taboo list, this action (1,1,3) is performed to current solution S, generate new explanation S ', S '={ V
1, V
2, V
3, V
4, wherein V
1={ 7,9}, V
2={ 2,6,11}, V
3={ 1,3}, V
4={ 4,5,8,10}.
Action (c, V that step 8. will perform in step 7
i, V
j)
minadd taboo list, and Tabu Length tl is set for it, relatively new explanation S ' adaptive value f (S ') and the size of current solution adaptive value f (S), if f (S ') <f (S), then replace current solution S with new explanation S ', i.e. S=S ', current solution S adaptive value is replaced, i.e. f (S)=f (S ') by new explanation S ' adaptive value, otherwise, in neighborhood neigh, delete this action, return step 6.Tabu Length, refers to action (c, V
i, V
j)
minbe prohibited perform number of times.
In the present embodiment, the action (1,1 will performed in step 7,3) add taboo list, and arrange Tabu Length tl=5 for it, new explanation S ' adaptive value f (S ')=5 is less than current solution adaptive value f (S)=7, current solution S, i.e. S=S '={ V is replaced with new explanation S '
1, V
2, V
3, V
4, wherein V
1={ 7,9}, V
2={ 2,6,11}, V
3={ 1,3}, V
4={ 4,5,8,10} replaces current solution S adaptive value by new explanation S ' adaptive value, f (S)=f (S ')=5.
Step 9. more current solution adaptive value f (S) and current optimal solution adaptive value f (S
best) between size, if f (S) <f (S
best), then replace current optimal solution S with current solution S
best, i.e. S
best=S, replaces current optimal solution adaptive value f (S with current solution adaptive value f (S)
best), i.e. f (S
best)=f (S), otherwise, perform step 10.
In the present embodiment, current solution adaptive value f (S)=5 is less than current optimal solution adaptive value f (S
best)=7, replace current optimal solution S with current solution S
best, i.e. S
best=S={V
1, V
2, V
3, V
4, wherein V
1={ 7,9}, V
2={ 2,6,11}, V
3={ 1,3}, V
4={ 4,5,8,10}.
Step 10. judges current optimal solution adaptive value f (S
best) whether be 0, if f is (S
best)=0, exports and flies cellular network spectrum allocation schemes S
bestwith required spectrum number K, otherwise, return step 2.
In the present embodiment, current optimal solution adaptive value f (S
best)=5, obtain f (S after returning step 2 repetitive cycling 3 times
best)=0, exports and flies cellular network spectrum allocation schemes S
best={ V
1, V
2, V
3, V
4, wherein V
1={ 4,7,9}, V
2={ 2,5,11}, V
3={ 1,3,6}, V
4={ 8,10}, required spectrum number K=4.
Effect of the present invention can be further illustrated by following experiment:
1. simulated conditions:
Be core 22.4GHZ at CPU, the system of internal memory 2G, WINDOWS XP uses VC++6.0 to emulate.
2. emulate content:
Choose three groups and different specifically fly cellular network as experimental subjects, the interference figure flying cellular network 1,2,3 is respectively shown in Fig. 3, Fig. 4, Fig. 5, obtain these three kinds by the method proposed in the present invention and fly spectrum number required for cellular network and allocation result, and logging program running time, as shown in the table:
Spectrum number needed for table 1 three group network and allocation result and running time
As can be seen from Table 1, what the present invention is based on tabu search algorithm flies cellular network frequency spectrum distributing method, efficiently solves and flies cellular network spectrum allocation may problem, decrease the spectrum number flown needed for cellular network, improve the availability of frequency spectrum, effectively inhibit the same layer interference flown between honeycomb.
Above-mentioned execution mode is only an example of the present invention, does not form any limitation of the invention, such as, can also carry out spectrum allocation may to the network comprising varying number and fly honeycomb by the inventive method.
Claims (4)
1. fly a cellular network frequency spectrum distributing method based on TABU search, comprise the steps:
(1) by macrocellular with fly the honeycomb node that flies of non-interference sensitizing range in honeycomb mixed networking and represent, connect the node flown corresponding to honeycomb of interference mutually with limit, obtain interference figure H={N, V, E}, wherein N is node number, and V is the set of node, V={1,2, ..., N}, E are the set on limit;
(2) nodes all in interference figure H are randomized into K node set, obtain the initial solution S flying cellular network spectrum allocation may problem
0={ V
1, V
2..., V
k, wherein V
1, V
2..., V
krepresent node set 1,2 respectively ..., K;
(3) the adaptive value f (S of initial solution is solved
0)=Σ δ
uv, wherein
u, v represent two nodes mutually disturbed,
represent node set
, 1≤
≤ K, as two node u mutually disturbed, v belongs to node set
time, δ
uv=1, otherwise δ
uv=0, f (S
0) represent initial solution S
0the interference summation of middle existence;
(4) the adaptive value f (S of initial solution is judged
0) whether be 0, if f is (S
0)=0, then S
0={ V
1, V
2..., V
kfor flying cellular network spectrum allocation may result, K is required spectrum number; Otherwise, generate current solution S=S
0={ V
1, V
2..., V
kand current optimal solution S
best=S
0={ V
1, V
2..., V
k, then current solution adaptive value f (S)=f (S
0), current optimal solution adaptive value f (S
best)=f (S
0);
(5) by current solution S={V
1, V
2..., V
kinterior joint set V
iin node c, from node set V
imove to node set V
j, be designated as action (c, V
i, V
j), wherein c is and node set V
iin certain node exist interference a node, 1≤i≤K, 1≤j≤K, i ≠ j, with current solution S everything, form current solution S neighborhood neigh;
(6) in the neighborhood neigh of current solution S, select the action (c, the V that make current solution adaptive value f (S) decline maximum
i, V
j)
min;
(7) action (c, the V that select in (6) is judged
i, V
j)
minwhether in taboo list, if not in taboo list, this action (c, V are performed to current solution S
i, V
j)
min, generate new explanation S '; Otherwise, judge this action (c, V
i, V
j)
minwhether meet and despise rule, if meet, this action (c, V are performed to current solution S
i, V
j)
minif do not meet, then in neighborhood neigh, delete this action, leapfrog rapid (6),
Describedly despise rule, refer to and S action (c, V are performed to current solution
i, V
j)
minrear generation new explanation S ', if new explanation adaptive value f (S ') is less than current solution adaptive value f (S), regardless of action (c, V
i, V
j)
minwhether in taboo list, all perform an action (c, V
i, V
j)
min;
(8) action (c, the V that will perform in step (7)
i, V
j)
minadd taboo list, and Tabu Length is set for this action, relatively new explanation S ' adaptive value f (S ') and the size of current solution adaptive value f (S), if f (S ') < f (S), then replace current solution S with new explanation S ', i.e. S=S ', current solution S adaptive value is replaced, i.e. f (S)=f (S ') by new explanation S ' adaptive value, otherwise, this action is deleted, leapfrog rapid (6) in neighborhood neigh;
(9) more current solution adaptive value f (S) and current optimal solution adaptive value f (S
best) between size, if f (S) < f (S
best), then replace current optimal solution S with current solution S
best, i.e. S
best=S, replaces current optimal solution adaptive value f (S with current solution adaptive value f (S)
best), i.e. f (S
best)=f (S), otherwise, perform step (10);
(10) current optimal solution adaptive value f (S is judged
best) whether be 0, if f is (S
best)=0, exports and flies cellular network spectrum allocation schemes S
bestwith required spectrum number K, otherwise, rebound step (2).
2. method according to claim 1, the taboo list in wherein said step (4) forbids by all the table that the action performed is formed.
3. method according to claim 1, wherein said step (7) despise rule, refer to and current solution performed an action (c, V
i, V
j)
minrear generation new explanation, if new explanation adaptive value f (S ') is less than current solution adaptive value f (S), regardless of action (c, V
i, V
j)
minwhether in taboo list, all perform an action (c, V
i, V
j)
min.
4. method according to claim 1, the Tabu Length of wherein said step (8), refers to action (c, V
i, V
j)
minbe prohibited perform number of times.
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| US7660651B2 (en) * | 2002-08-22 | 2010-02-09 | United Parcel Service Of America, Inc. | Core area territory planning for optimizing driver familiarity and route flexibility |
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| CN101459589A (en) * | 2007-12-14 | 2009-06-17 | 华为技术有限公司 | Method and device for distributing network resource |
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| An Improved Tabu Search Algorithm for the Fixed-Spectrum Frequency-Assignment Problem;Roberto Montemanni et al.;《IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY》;20030531;第891-201页 * |
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