CN104640185A - Cell dormancy energy-saving method based on base station cooperation - Google Patents
Cell dormancy energy-saving method based on base station cooperation Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0203—Power saving arrangements in the radio access network or backbone network of wireless communication networks
- H04W52/0206—Power saving arrangements in the radio access network or backbone network of wireless communication networks in access points, e.g. base stations
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
- H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
- H04W52/243—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account interferences
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention discloses a cell dormancy energy-saving method based on base station cooperation. The method comprises the following steps: performing a network energy-saving target decomposition method based on dynamic planning, a cell dynamic clustering low-complexity method under a mode of CoMP-JT (coordinated multi-point joint transmission) as well as a CoMP cell power and OFDM (orthogonal frequency division multiplexing) carrier distribution optimizing method under interference conditions. The cell dormancy energy-saving method can sufficiently utilize high spectrum efficiency and relatively low same frequency interference caused by a base station cooperation technology while realizing cell dormancy energy saving, and further improves a network energy-saving effect. Besides, the low-complexity algorithm disclosed by the invention is very suitable for performing large-scale application in a true network.
Description
Technical Field
The invention relates to a cell dormancy energy-saving method based on base station cooperation, relates to the energy-saving problem of an LTE (Long Term evolution) network, and belongs to the technical field of networks in wireless communication networks.
Background
Dormant low-load cells have become a widely accepted energy-saving method for cellular networks when the network is idle. However, in the currently deployed wireless cellular network, after a low-load cell is dormant, the neighboring cells usually need to increase the transmission power to increase the coverage area to serve the users in the dormant cell, which results in a reduction in the overall energy saving effect of the network. To address this deficiency, some studies indicate that applying a Coordinated Multi-point (CoMP) technique between adjacent cells of the dormant cell can reduce an increased value of transmission power of the adjacent cells, thereby improving a network energy saving level.
The coordinated multipoint technology was adopted by the LTE Release 10 standard of the third Generation Partnership Project (3 GPP) in 2010, and is currently considered as an important component of LTE-Advanced, which is regarded as an effective means for interference coordination and spectral efficiency improvement. In the aspect of eNB energy consumption which is most concerned by network energy saving, an eNB (evolved Node b) energy consumption model participating in coordinated multipoint transmission will include newly added signal processing energy consumption and data return energy consumption between base stations. Based on such energy consumption models, several CoMP-based energy saving studies are conducted. The research shows that: compared with non-cooperative systems, systems employing CoMP have an improvement in both energy consumption and Energy Consumption Ratings (ECR). Among the energy efficiency performances of different CoMP coordination modes, the jt (joint transmission) mode has the best energy efficiency. Besides mode selection, Clustering (Clustering) method of CoMP is also a research focus. Because for different user parameters and base station load conditions, there is a corresponding optimal CoMP cluster size to achieve maximization of energy efficiency.
At present, in the energy-saving application aspect of a specific network, the prior art provides an eNB transmit power and spectrum subcarrier joint optimization method considering constraints such as user qos (quality of service), cooperative base station load upper limit, spectrum resources and the like. However, most of these methods are based on static eNB cooperative clusters, and there are limitations on the selection manner of cluster member cells and the cluster size, which are not favorable for large-scale use in practical network energy saving applications. On the other hand, once the dynamic CoMP clustering method is adopted, an additional solution to an integer optimization problem with a cluster member cell configuration preference is required, and the solution of the problem generally requires the use of a greedy search tool, so that the complexity of the original optimization problem is greatly increased, and a great challenge is brought to the implementation of the existing network. It is therefore desirable to design new low complexity methods.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an energy-saving optimization method suitable for an actual network environment by researching the application of coordinated multi-point transmission (CoMP) in cell dormancy energy saving. The method is based on a network energy-saving optimization problem of inter-cell cooperation and including constraint conditions such as inter-cell interference, user service quality, base station load and the like, and a Dynamic Programming method (Dynamic Programming) is adopted to divide the network combination optimization problem into a plurality of independent cell dormancy stages (stages) according to the principle of the Dynamic Programming method. For each stage, the composition of the optimal cooperative cell cluster is solved, and then a heuristic method is used for iteration to optimize the transmitting power and subcarrier configuration of each cooperative cell, so that the overall complexity of the method is reduced. Simulation results show that the method has the advantages of low complexity and convenience in distributed deployment, and is very suitable for energy-saving application of actual networks.
The invention provides a cell dormancy energy-saving method based on base station cooperation, which comprises the following steps: 1) decomposing a network energy-saving target; 2) dynamic composition of a coordinated cell cluster; 3) allocating power and OFDM subcarriers of the members of the cooperative cell cluster; in order to obtain the maximum energy-saving effect, the last two steps are carried out in an iteration mode.
The step 1) is realized by a network energy-saving target decomposition method based on a dynamic programming method, and is characterized in that: decomposing the energy-saving target of the network level into a series of independent cell dormancy stages with a front-back relation on the time sequence; each stage focuses on dynamically establishing a coordinated cell cluster CoMP cluster around a target dormant cell and pursuing the energy-saving effect maximization of the coordinated cell cluster.
Preferably, the coordinated cell cluster with the maximum energy-saving effect is selected according to the cell service load condition of the starting coordinated time point and the user rate requirement.
The step 2) can be realized by any one of three low-complexity cooperative cell cluster combination optimization methods; the method specifically comprises the following steps: searching the service load of a target dormant cell user on all alternative cooperative cell cluster combinations, and selecting one cooperative cell cluster combination with the minimum service load increase as an optimal cooperative cell cluster combination; calculating and summing SINR values of users in the target dormant cell and each adjacent cell, arranging the SINR values according to the high and low sequence, and selecting the L cell with the highest value as an optimal cooperative cell cluster combination, wherein L is the cooperative cell cluster combination size; and thirdly, calculating and summing the load increase values of the user in the target dormant cell and each adjacent cell, arranging the load increase values according to the high and low sequence, and selecting the L cell with the lowest value as the preferred cooperative cell cluster combination.
The step 3) is realized by a cooperative cell power and OFDM subcarrier allocation optimization method under an interference condition; the method is based on parameters such as user position, speed requirement, cooperative cell transmitting power, channel conditions and the like, and by designing a power iteration stepping value, the optimal cell transmitting power is searched by iteration from the initial cell transmitting power.
The method comprises the following specific steps: in each iteration period, calculating the quantity requirements of OFDM subcarriers of each user after the change of the power iteration step values, and averagely distributing the requirements on each cell of the cooperative cell cluster combination; if the subcarrier requirements exceed the upper limit of the number of subcarriers which can be provided by the cell, the iteration is stopped, otherwise, the power iteration is continued.
The methods of the above steps will be described in detail below.
1 network energy-saving target decomposition method based on dynamic programming method
The standard dynamic programming method variables comprise states, decisions, state transfer functions, overhead per stage and the like. Assume the state of phase i is S(k)Then the state of the next stage is:
S(k+1)＝I(k)(S(k),U(k)) (1)
wherein I(k)、U(k)Respectively representing the state transition function and the decision applied at phase i.
In the invention, if the whole energy saving of the network is regarded as a set of a series of cell dormancy events with time sequence, the network state after the k cell dormancy is recorded asWhereinRepresenting a cluster C containing cooperating cells surrounding the cell T to be closedTOf participating cells, V(k)Representing a list of cells that have been switched off at that time, LBS,b (k)Representing the traffic load, P, of each celltx,i (k)Representing the transmit power of cell i. Let U be { U ═ U(1),U(2),U(3),...U(k)The decision of further cell dormancy and the allocation of user power and frequency resources is taken on the basis of the network state after the 1 st, 2 nd, 3 th cell dormancy. The network status can be set by S after the k +1 th cell dormancy(k+1)To describe. Therefore, the original network optimization problem can be decomposed into a series of cell dormancy sub-stages taking the minimum energy consumption of the cooperative cell cluster as an objective function according to a single cell dormancy event.
The energy consumption optimization objective function of each stage is as follows:
wherein P isclusterRepresenting participation in collaborationL cell energy consumptions P of cell clusterBS,iAnd (4) summing. The constraints for achieving this energy consumption optimization goal are:
(S1) satisfying the rate requirement of each user;
(S2) being less than the cell load upper limit and the base station transmit power upper limit;
(S3) the number of cells participating in the cooperative cell cluster is a positive integer;
according to the idea of the dynamic planning method, the solution of the overall network energy-saving optimization problem can be finally obtained from the solution set of the sub-phases. In the method, the construction and the solution of the sub-stages are carried out successively and iteratively according to time sequence, and when any one of the following two conditions is met, the construction of a new sub-stage is stopped:
(S4) the solution of the sub-phase does not contribute to the reduction of the overall energy consumption of the network;
(S5) under a given cooperative cell cluster size limit, a new cooperative cell cluster cannot be constructed because the cell load reaches an upper limit;
low-complexity cooperative cell cluster combination optimization method in 2 CoMP-JT (joint transmission) mode
The method is based on a CoMP-JT (joint transmission) working mode. After the target dormant cell T is assumed to be dormant, its users are served by the cooperative cell cluster, and the traffic load brought by the users is averagely allocated to each participating cell of the cooperative cell cluster. In order to avoid the load of the cells participating in the cooperation from exceeding the respective upper limit, when planning the (k + 1) th cell dormancy, the cell with the lowest load in the current (namely, the phase k) network is selected as a target dormant cell T(k+1)The load is as follows:
whereinRepresenting that the target sleeping cell belongs to the network M and is still in operation. After the target dormant cell of the stage k +1 is determined, the next step is to select a cooperative cell cluster combination participating in CoMP-JT (joint transmission) from the adjacent cellsSolving cooperative cell cluster combination for optimizing network energy-saving effectA plurality of factors such as user QoS, service load of each cell base station, and the like need to be considered comprehensively. This is similar to a multi-dimensional knapsack problem, and at present there is not a good solution except for the poor search method, but the computation complexity of the poor search method is relatively high.
In order to reduce the computational complexity, the invention provides three low-complexity cooperative cell cluster combination optimization methods. The three methods are respectively based on three information dimensions of a network, a cell and a user to screen clustering cells, and the number of dynamic clustering cells and the QoS requirement of the user are considered.
A) CLS method (Cluster Load Search Based Cluster Scheme)
The CLS method is a load searching method based on a cooperative cell cluster. In the k +1 th cell dormancy decision, the CLS is based on the network state parameter S after the k cell dormancy(k)After the target cell is predicted to be dormant, all users of the target cell give alternative cooperative cell cluster combinationsSum of the resulting load increase valuesSorting the load increment values of the alternative cooperation cell cluster combinations, and selecting the cooperation cell cluster combination with the minimum load increment value as the cooperation cell cluster combination
B) Sum-SINR method (User Sum SINR Based Clustering Scheme)
The sum-SINR method sums the SINR between the user in the target dormant cell and the neighbor eNB (S/N ratio) (S/N-SINR)SINR, Signal to Interference plus Noise Ratio) value θi (k+1)And further according to theta for the adjacent regioni (k+1)And (6) sorting. Selecting thetai (k+1)Largest sizeThe cells constitute an optimal cooperative cell cluster combination.
WhereinRepresenting a target sleeping cell T(k+1)User u in (1) receivesSINR of cell i signal.
C) Sum-LOAD method (Cell Sum LOAD Based Clustering Scheme)
sum-LOAD method sums up LOAD sigma brought to neighbor cell by user in target dormant celli (k+1)And further according to sigma for adjacent regionsi (k+1)Sorting to select sigmai (k+1)Minimum sizeThe cells constitute an optimal cooperative cell cluster combination.
Wherein,representing a target sleeping cell T(k+1)Load, N, on cell i caused by user u in (1)w，iRepresenting the upper load capacity limit of cell i.
3 power and OFDM subcarrier allocation optimization method
According to the clustering result of the cooperative cell cluster combination optimization method, the invention provides a heuristic method based on cell power iteration.
Wherein, Δ is a preset power iteration step value, and can be set according to the needs of an operator and an actual scene.
Compared with the prior art, the invention has the following beneficial effects: the invention decomposes the network energy-saving problem into a series of cell dormancy sub-stages by using a dynamic planning idea, and provides three low-complexity optimized clustering methods for cell clustering calculation in the sub-stages. In consideration of the complexity of cell transmitting power optimization in an interference scene, the invention also provides a heuristic method, which solves the transmitting power optimization value of the member cell of the cooperative cell cluster through iterative optimization so as to further reduce the complexity and improve the overall energy-saving effect of the network.
The network energy-saving strategy based on the invention has the following advantages:
1. the invention reduces the complexity of cluster calculation of the cooperative cell by providing three improved methods. The method can be applied to different network use scenes, and has higher flexibility compared with a static clustering method;
2. compared with the energy-saving optimization method proposed by the research literature in the field, the transmission power iterative optimization method of the CoMP-JT (joint transmission) participating cell provided by the invention has the advantages that the calculation complexity is greatly reduced;
3. the network decomposition idea based on dynamic programming can be further popularized to the step of decomposing a large network into a plurality of sub-networks so as to implement an energy-saving optimization strategy in parallel, and has better expansibility;
drawings
Fig. 1 is a schematic diagram of a network.
Fig. 2 is a schematic diagram of CoMP-JT (joint transmission) according to the present invention.
Detailed Description
The following further describes an implementation method of the cell dormancy energy-saving method based on base station cooperation, with reference to the accompanying drawings:
1) when the (k + 1) th cell shutdown is performed (k is 0, 1,2 …), the current phase state S is referred to(k)A wireless network transmission and service load model, which calculates the service load condition and network energy consumption condition of each cell in the selected target network (see figure 1);
2) sorting all cells according to service load, screening out target closing cell T with lowest service load(k+1)(see FIG. 2);
3) according to the preset cooperative cell cluster rulerCun restrictionConstructing a cooperative cell cluster C by any one of the three low-complexity dynamic clustering methods provided by the inventionT(see FIG. 2);
4) according to the power and OFDM subcarrier allocation optimization method provided by the invention, the participating C is subjected toTThe cell power and the sub-carrier are subjected to iterative optimization, and the result is recorded as
5) According to S(k+1)And S(k)Calculating the overall energy consumption of the network, and repeating the steps 1) to 5 if iteration continuation conditions (S4) and (S5) are met); and if the iteration continuing condition is not met, terminating the iteration.
Claims (6)
1. A cell dormancy energy-saving method based on base station cooperation comprises the following steps: 1) decomposing a network energy-saving target; 2) dynamic composition of a coordinated cell cluster; 3) allocating power and OFDM subcarriers of the members of the cooperative cell cluster; in order to obtain the maximum energy-saving effect, the last two steps are carried out in an iteration mode.
2. The energy-saving method for dormancy of cells based on cooperation of base stations as claimed in claim 1, wherein the step 1) is implemented by a network energy-saving goal decomposition method based on a dynamic programming method, characterized in that: decomposing the energy-saving target of the network level into a series of independent cell dormancy stages with a front-back relation on the time sequence; each stage focuses on dynamically establishing a coordinated cell cluster CoMP cluster around a target dormant cell and pursuing the energy-saving effect maximization of the coordinated cell cluster.
3. The base station cooperation-based cell dormancy energy-saving method of claim 2, wherein: and preferably selecting the cooperative cell cluster with the maximum energy-saving effect according to the cell service load condition of the starting cooperative time point and the user rate requirement.
4. The method for saving energy in cell dormancy based on base station cooperation according to claim 1, wherein the step 2) can be implemented by any one of three methods of optimizing the combination of cooperative cell clusters with low complexity; the method specifically comprises the following steps: searching the service load of a target dormant cell user on all alternative cooperative cell cluster combinations, and selecting one cooperative cell cluster combination with the minimum service load increase as an optimal cooperative cell cluster combination; calculating and summing SINR values of users in the target dormant cell and each adjacent cell, arranging the SINR values according to the high and low sequence, and selecting the L cell with the highest value as an optimal cooperative cell cluster combination, wherein L is the cooperative cell cluster combination size; and thirdly, calculating and summing the load increase values of the user in the target dormant cell and each adjacent cell, arranging the load increase values according to the high and low sequence, and selecting the L cell with the lowest value as the preferred cooperative cell cluster combination.
5. The base station cooperation-based cell dormancy energy-saving method according to claim 1, wherein the step 3) is implemented by a cooperative cell power and OFDM subcarrier allocation optimization method under an interference condition; the method is based on parameters such as user position, speed requirement, cooperative cell transmitting power, channel conditions and the like, and by designing a power iteration stepping value, the optimal cell transmitting power is searched by iteration from the initial cell transmitting power.
6. The base station cooperation-based cell dormancy energy-saving method according to claim 1, wherein the method for optimizing the power and OFDM subcarrier allocation of the cooperative cell under the interference condition comprises the following specific steps: in each iteration period, calculating the quantity requirements of OFDM subcarriers of each user after the change of the power iteration step values, and averagely distributing the requirements on each cell of the cooperative cell cluster combination; if the subcarrier requirements exceed the upper limit of the number of subcarriers which can be provided by the cell, the iteration is stopped, otherwise, the power iteration is continued.
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| CN104883725A (en) * | 2015-06-19 | 2015-09-02 | 东南大学 | Method for network energy conservation based on station actual load in long-term evolution network |
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| CN106304232B (en) * | 2016-08-08 | 2019-09-24 | 北京邮电大学 | A kind of communication means and device of base station dormancy |
| CN110506432A (en) * | 2017-03-31 | 2019-11-26 | 华为技术有限公司 | A kind of cooperation cell determines method and the network equipment |
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| CN109286425A (en) * | 2018-05-23 | 2019-01-29 | 中国科学院上海微系统与信息技术研究所 | The multipoint cooperative dynamic clustering method and system of combined optimization energy efficiency and load balancing |
| CN110858983A (en) * | 2018-08-22 | 2020-03-03 | 中国移动通信集团山东有限公司 | Energy-saving control method and device for base station |
| CN117202331A (en) * | 2023-10-23 | 2023-12-08 | 哈尔滨智汇信息科技有限公司 | Remote control method and system for intelligent dormancy of 5G base station |
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