CN106900064A - Minimize the LTE downlink resource scheduling methods of compression losses - Google Patents
Minimize the LTE downlink resource scheduling methods of compression losses Download PDFInfo
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- H04W72/00—Local resource management
- H04W72/12—Wireless traffic scheduling
- H04W72/1263—Mapping of traffic onto schedule, e.g. scheduled allocation or multiplexing of flows
- H04W72/1273—Mapping of traffic onto schedule, e.g. scheduled allocation or multiplexing of flows of downlink data flows
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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
- H04W72/53—Allocation or scheduling criteria for wireless resources based on regulatory allocation policies
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- H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract
The present invention proposes a kind of LTE downlink resource scheduling methods for minimizing compression losses, mainly solves the problems, such as that prior art does not combine consideration Resource Block compression in scheduling of resource.Its scheme is：1. couple user is numbered and expands to identical with resource block number；2. the transition probability of initialization algorithm；3. all Resource Block to the assigning process of user are completed；4. current maximum handling capacity and optimal distributing scheme are updated；5. pair algorithm carries out the transition probability renewal based on optimal distributing scheme；6. pair algorithm is iterated the iterations until reaching maximum, then the Customs Assigned Number after extension is mapped back into initial number of users, obtains optimal distributing scheme.The present invention both ensure that user fairness in sub-band channel quality distribution, and the compression efficiency of Resource Block is improve again, the raising of handling capacity be ensure that to greatest extent, the multi-subscriber dispatching that can be used in long evolving system.
Description
Technical field
The invention belongs to wireless communication technology field, more particularly to a kind of descending dynamic resource allocation methods of LTE can be used for
The resource requirements for access of multi-subscriber dispatching in long evolving system LTE.
Background technology
For radio communication, Radio Resource, such as frequency spectrum, time slot are all very valuable.How the availability of frequency spectrum is improved,
As the technical problem that people pay special attention to.Radio Resource is competed between many users so that allocation strategy needs to consider user
Fairness, enabling each user to as far as possible justice obtain scheduling while, it is necessary to take into account the handling capacity of system.
And the factor of decision systems handling capacity includes：Transmission power, running time-frequency resource, channel quality, and resource allocation algorithm, Yong Hugong
Levelling then depends on descending scheduling algorithm.Resource allocation policy how is selected to meet raising system while user fairness
Handling capacity is the problem that the distribution of LTE downlink resources is studied all the time.
In LTE scheduling downlink resource algorithms, LTE standard regulation in each time slot scheduling TTI, is distributed to same
All Resource Block RB of user must use identical modulating-coding strategy MCS, therefore when a user is assigned to different channels
, it is necessary to use suitable compression function during the RB of quality, it is ensured that in the range of the bit error rate, the corresponding channel qualities of different RB are referred to
Show that CQI is mapped as a CQI, so that for user selects a suitable MCS, but compression can bring the loss of modulation levels,
In turn result in the loss of throughput of system.
Early stage is it has been suggested that cross some classical dispatching algorithms.As polling algorithm and maximum throughput quantity algorithm, these are classical
Dispatching algorithm due to simple, expense is small, thus is widely used, but when being related to subband CQI and distributing, algorithm is in resource
The compression of Resource Block is not accounted for during distribution, is had the disadvantage that,
Wherein：
Polling algorithm, is most fair algorithm for user, and be sequentially allocated Resource Block to different users by it, but
It is that user is exchanged for sacrificial system handling capacity and Resource Block compression efficiency due to not accounting for channel quality and Resource Block compression
Absolute fair algorithm.
Maximum throughput quantity algorithm, is that all Resource Block in each TTI are distributed on into the best user of channel quality, but
Due to distribution when do not account for Resource Block compression, algorithmic dispatching may cause after terminating certain user compress after CQI occur compared with
The decline of big degree, makes the CQI after the good user's compression of channel quality be in one than relatively low level, brings throughput of system
Loss, also, the algorithm may result in the uneven problem of resource allocation, and the good user of channel quality occur can be assigned to more
Multiple resource, the situation that the edge customer of bad channel quality cannot be dispatched.
The content of the invention
It is an object of the invention to the defect for overcoming above-mentioned prior art to exist, a kind of minimum compression losses is proposed
LTE scheduling downlink resource algorithms, with the loss that joint consideration Resource Block compression strap is come simultaneously during resource allocation, and
In the case of considering user fairness, maximum system throughput.
The technical proposal of the invention is realized in this way：
One, know-whies
Minimum compression losses LTE downlink resource scheduling methods proposed by the present invention are pre-assigned to use by by Resource Block
Family, calculates compression losses and records, then according to the information for recording come the method for salary distribution of continuous adjustresources block to user, so that
It is the resource allocation methods of user's selection minimal compression loss on the premise of user fairness is ensured.Its implementation can use
Some heuritic approaches are realized, such as simulated annealing, ant group algorithm etc., and the present invention is realized with ant group algorithm as case.
Two, implementations
Included according to above-mentioned principle implementation of the invention as follows：
(1) determine the number of Resource Block to be allocated and user to be allocated, and user's number to be allocated is extended to and resource
The number of block is identical；
(2) pheromone concentration of initialization algorithm：τk,n=0.1, wherein k represents user, and n represents Resource Block；
(3) according to pheromone concentration τk,nDetermine Resource Block to the transition probability p of userk,n；
(4) for any one Resource Block, according to transition probability pk,n, calculate the distributing user of current resource block；
(5) judge whether Resource Block is assigned, if so, then performing (6), otherwise, move to next unassigned
Resource Block, return to step (4)；
(6) throughput of system that current allocation result is obtained is calculated, judges whether this handling capacity handles up more than current system
The maximum of amount, if so, the maximum for then updating current system handling capacity is the handling capacity of the current method of salary distribution, and will be current
Allocative decision otherwise, does not update as the optimal allocative decision of current system；
(7) according to the pheromones of current system optimal allocative decision more new algorithm；
(8) whether the algebraically of evaluation algorithm operation reaches maximum algebraically, if so, then performing step (9), otherwise, runs generation
Number Jia 1, return to step (4)；
(9) the maximum handling capacity of system and current optimal distributing scheme are drawn, step (10) is performed；
(10) user for extending (1) is remapped back user to be allocated according to one-to-one mode, by same user
Optimal distributing scheme be combined superposition, obtain final allocative decision.
The present invention compared with prior art, with advantages below：
The present invention considers the compression of Resource Block when being related to subband CQI to distribute during resource allocation, can be more excellent
The compression efficiency that Resource Block is given each user, Resource Block is improve changed, compared to using for conventional method, by resource point
The parallel procedure that consideration compression is combined in distribution is changed to the series process with compression, so as to reduce the compression losses of Resource Block,
And the fairness of resource allocation is considered, when there is edge customer, the situation that edge customer cannot be dispatched is eliminated, and
Handling capacity maintains a level higher.
Brief description of the drawings
Fig. 1 realizes flow chart for conventional allocation method；
Fig. 2 realizes flow chart for of the invention；
Fig. 3 is the present invention and traditional maximum throughput quantity algorithm and the handling capacity comparative result figure of polling algorithm.
Fig. 4 is the resource block assignments comparative result figure of the present invention and traditional maximum throughput quantity algorithm.
Specific embodiment
The embodiment of the present invention and effect are described in further detail below in conjunction with accompanying drawing.
Assuming that number of resource blocks is N in system, total number of users is M, the speed that each user obtains within each dispatching cycle
It is RkK=1,2 ..., M, it is assumed that base station can obtain the value of the channel condition information CQI of user terminal, and root by feedback channel
It is dynamically each user resource allocation block according to the value of feedback.
Define ρk,nThe occupancy situation of Resource Block is represented, works as ρk,nWhen=1, represent that Resource Block n is taken by user k, work as ρk,n=
Represent that Resource Block n is not taken by user k when 0.
Define ck,nThe bit number that user M is distributed on Resource Block n is represented, the handling capacity that T represents system is defined, by money
The dynamically distributes of source block maximize the total throughout T of system, are with formulation：
Formula<1>Represent the handling capacity of system acquisition, formula<2>Represent that each Resource Block can only distribute to a user,
Formula<3>Represent the speed of each user.
However, above-mentioned allocation rule be according to channel quality distribute Resource Block, it is contemplated that edge effect be possible to because
Bad channel quality and distribute less than Resource Block, it is necessary to add following limitation：
Formula<4>Represent for each user, be at least assigned to 1 Resource Block, cannot be adjusted so as to avoid
The situation of degree.
Referring to Figures 1 and 2, conventional method first carries out resource allocation in scheduling downlink resource, then carries out resource compression
Process, distribution and compression are serial.
Of the invention is that in scheduling downlink resource, the process of distribution considers Resource Block compression while combining, constantly
It is iterated according to compression information before, until being optimal allocative decision, resource allocation and compression are parallel.
Reference picture 2, the present invention is with ant group algorithm as case, and implementation step is as follows：
Step 1：Determine the number of Resource Block to be allocated and user to be allocated, and user's number to be allocated is extended.
Number according to request user determines the number of user to be allocated, and the idling-resource block according to system determines to be allocated
Resource Block number, it is assumed that user's number to be allocated be M, Resource Block number to be allocated be N, M<=N；
After determining Resource Block to be allocated and user's number to be allocated, by user's number to be allocated be extended to it is to be allocated
Resource Block number is identical.
Assuming that Customs Assigned Number is u before extension, then it is extended as follows：
| Customs Assigned Number before extension | Customs Assigned Number after extension |
| u | M·X+u |
Wherein, u ∈ { 1,2 ..., M },
S.t. MX+u ＜=N X ∈ { 0,1,2 ... },
For example, number of users is 4 before extension, Resource Block quantity to be allocated is 25, then the Customs Assigned Number result after extending is：
| The Customs Assigned Number of extension | Customs Assigned Number after extension |
| 1 | 1,5,9,13,17,21,25 |
| 2 | 2,6,10,14,18,22 |
| 3 | 3,7,11,15,19,23 |
| 4 | 4,8,12,16,20,24 |
Step 2：Initialization ant group algorithm pheromone concentration.
The pheromones τ in ant group algorithmk,nThe phase of the bit number that representative is obtained n-th resource block assignments to user k
Hope, this example initialization information element concentration is：τk,n=0.1.
Step 3：Determine the transition probability of each moved further of ant.
Ant in moving process, if based on may decision-making from Resource Block to be allocated move to one it is unassigned
User, then it represents that give this user by this resource block assignments to be allocated, this possible decision-making is referred to as in ant moving process
Transition probability pk,n, it is defined as follows：
Wherein, ηk,nRepresent that user k is to determine the parameter that pheromones are followed the trail of in the mapping CQI, α of n-th Resource Block, β is for certainly
Surely the parameter of information, Tabu are soundd outkThe user that expression is not selected by ant k.
Step 4：Calculate distributing user of the ant in current resource block.
M ant is placed on the position of any cost block at random, for any one ant, according to transition probability pk,n,
Calculate that method calculates distributing user of the ant in current resource block using roulette.Comprise the following steps that：
4a) the random decimal a generated between 0 to 1；
4b) according to pheromone concentration, using transition probability pk,nFormula calculates the transfer that each unallocated user is selected
Probability；
4c) by 4b) transition probability that obtains is overlapped, until the probability sum being superimposed is more than a, reselection last
The user being applied is the distributing user of current resource block.
Step 5：Judge whether Resource Block is assigned, if being assigned, into step 6, otherwise, return to step 4.
Step 6：Calculate the throughput of system that current ant allocation result is obtained.
6a) resource allocation result according to current ant obtains the resource allocation table of each user；
The downstream rate of each user 6b) is calculated according to resource allocation table：
6b1) the corresponding different channels matter of Resource Block for being distributed each user according to the mapping EESM methods based on index
Amount CQI value is equivalent to a modulating-coding grade MCS value；
MCS value 6b2) according to mapping and the number of Resource Block, by looking into the bit table of LTE standard, obtain each user
Downstream rate；
The speed of each user 6c) is added the handling capacity of the system that obtains.
Step 7：Judge whether the ant of current algebraically has all been already engaged in the process of resource allocation, if it is, performing
8, otherwise, the ant number that will participate in resource allocation plus 1, return to step 4.
Step 8：The pheromones of ant colony are updated according to the optimal allocative decision of current system.
8a) define the pheromones increment Delta τ of ant group algorithmk,nIt is as follows：
In formula, L represents the maximum throughput of the current system that current ant colony finds；Q is that pheromones are put in a cycle
The number put, (k, n) is represented and is given k-th user by n-th resource block assignments；
The pheromones of ant colony 8b) are updated according to equation below：
τk,n=(1- ρ) τk,n+Δτk,n,
In formula, the dissipation value that parameter ρ representative information element is followed the trail of.
Step 9：Judge whether ant group algorithm terminates, if it is, the result run according to algorithm, show that system is maximum and gulp down
The amount of telling and current optimal distributing scheme, perform step 10；Otherwise, operation algebraically adds 1, return to step 4.
Step 10：The user of 1 extension is remapped back user to be allocated according to one-to-one mode, i.e., will first be extended
Customs Assigned Number afterwards obtains remainder result to number of users remainder；Judge whether remainder result is 0 again, if 0, then after mapping
Customs Assigned Number be number of users M, otherwise, Customs Assigned Number after mapping is the result of remainder, obtains final allocation result.
For convenience of explanation, it is assumed that resource block number to be allocated is 10, number of users to be allocated is 4, it is assumed that preliminary distribution
Result is as follows：
Allocation result after then finally having mapped is：
| User | 1 | 2 | 3 | 4 |
| Resource Block | 6,3,7 | 5,9,8 | 2,10 | 1,4 |
Effect of the invention can be further illustrated by emulation：
1. simulated conditions
In simulating scenes, system bandwidth is 20M, and corresponding Resource Block RB numbers are 100, and user's number is 4, is used
The method of salary distribution of LTE standard type0, is allocated by minimum particle size of Resource Block group RBG, according to LTE standard agreement, 4 moneys
Source block is a Resource Block group.
2. emulation content and result
Emulation 1, the feedback channel quality CQI for setting the 4th user is respectively less than 5, and the user is set into edge customer, other
The channel quality of user preferably, uses inventive algorithm, polling algorithm, maximum signal-to-noise ratio algorithm to carry out under above-mentioned simulated conditions
Downlink resource is distributed, and the handling capacity result such as Fig. 3 for obtaining, wherein abscissa represents different algorithms, and ordinate represents system
Handling capacity.
Available from Fig. 3, the handling capacity that the algorithm used in the present invention is obtained is little compared to maximum throughput quantity algorithm difference,
But the significantly larger than handling capacity of polling algorithm.
Emulation 2, is still set to edge customer, with inventive algorithm and most under above-mentioned simulated conditions by the 4th user
Big signal-to-noise ratio (SNR) Algorithm carries out downlink resource distribution, and the resource block assignments result such as Fig. 3 for obtaining, wherein abscissa represents different calculations
Method, ordinate represents the Resource Block number that each user gets.
Available from Fig. 4, edge customer does not get Resource Block under maximum throughput quantity algorithm, and uses in the present invention
Algorithm under but assigned to Resource Block, algorithm of the invention can ensure the fairness of user compared to maximum throughput quantity algorithm.
The above, the only present invention preferably specific embodiment, but protection scope of the present invention is not limited thereto,
Any one skilled in the art the invention discloses technical scope in, the change that can readily occur in or replace
Change, should all be included within the scope of the present invention.Therefore, protection scope of the present invention should be with the protection of claims
Scope is defined.
Claims (5)
1. it is a kind of minimize compression losses LTE downlink resource scheduling methods, including：
(1) determine the number of Resource Block to be allocated and user to be allocated, and user's number to be allocated is extended to and Resource Block
Number is identical；
(2) pheromone concentration of initialization algorithm：τk,n=0.1, wherein k represents user, and n represents Resource Block；
(3) according to pheromone concentration τk,nDetermine Resource Block to the transition probability p of userk,n；
(4) for any one Resource Block, according to transition probability pk,n, calculate the distributing user of current resource block；
(5) judge whether Resource Block is assigned, if so, then performing (6), otherwise, move to next unassigned resource
Block, return to step (4)；
(6) throughput of system that current allocation result is obtained is calculated, judges this handling capacity whether more than current system handling capacity
Maximum, if so, the maximum for then updating current system handling capacity is the handling capacity of the current method of salary distribution, and by current distribution
Scheme otherwise, does not update as the optimal allocative decision of current system；
(7) according to the pheromones of current system optimal allocative decision more new algorithm；
(8) whether the algebraically of evaluation algorithm operation reaches maximum algebraically, if so, then performing step (9), otherwise, operation algebraically adds
1, return to step (4)；
(9) the maximum handling capacity of system and current optimal distributing scheme are drawn, step (10) is performed；
(10) user for extending (1) is remapped back user to be allocated according to one-to-one mode, by same user most
Excellent allocative decision is combined superposition, obtains final allocative decision.
2. method according to claim 1, wherein according to pheromone concentration τ in step (3)k,nDetermine each moved further
Transition probability pk,n, determine as follows：
Wherein, ηk,nRepresent that user k is to determine the parameter that pheromones are followed the trail of in the mapping CQI, α of n-th Resource Block, β is tried for decision
Make inquiries about the parameter of breath, TabukUnassigned user is represented, this formula is used for carrying out the predistribution of resource.
3. method according to claim 1, it is characterised in that the system that current allocation result obtains is calculated in step (6) and is gulped down
The amount of telling, is carried out as follows：
The resource allocation table of each user 6a) is obtained according to current resource allocation result；
The downstream rate of each user 6b) is calculated according to resource allocation table, is concretely comprised the following steps：
6b1) the corresponding different CQI values of Resource Block for being distributed each user according to index mapping EESM methods are equivalent to one
MCS value；
MCS value and the number of Resource Block 6b2) according to mapping obtains the speed of the user；
The speed of each user 6c) is added the handling capacity of the system that obtains.
4. method according to claim 1, it is characterised in that the distribution optimal according to current system described in step (7)
The pheromones of scheme more new algorithm, are carried out by equation below：
τk,n=(1- ρ) τk,n+Δτk,n,
In formula, the dissipation value that parameter ρ representative information element is followed the trail of；Δτk,nThe pheromones of the algorithm of best allocative decision are found in expression,
It is defined as follows：
If (k, n) is combined inside optimum allocation path
In formula, L represents the maximum throughput of the current system having now been found that；Q is the number that pheromones are placed in a cycle,
It can strengthen the effect of pheromones tracking, in allocation algorithm, for the optimal compression scheme of more new resources.
5. method according to claim 1, the user that will be extended wherein in step (10) is according to one-to-one mode weight
New mappings return user to be allocated, are, to number of users M remainders, to obtain remainder result by Customs Assigned Number U, if remainder result is 0,
Customs Assigned Number after then mapping is number of users M, and otherwise, the Customs Assigned Number after mapping is the result of remainder.
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Application publication date: 20170627 |