CN113630906B - Method and device for compensating interruption of wireless self-organizing network - Google Patents
Method and device for compensating interruption of wireless self-organizing network Download PDFInfo
- Publication number
- CN113630906B CN113630906B CN202111005837.1A CN202111005837A CN113630906B CN 113630906 B CN113630906 B CN 113630906B CN 202111005837 A CN202111005837 A CN 202111005837A CN 113630906 B CN113630906 B CN 113630906B
- Authority
- CN
- China
- Prior art keywords
- particles
- base station
- user
- determining
- particle
- 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.)
- Active
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W76/00—Connection management
- H04W76/10—Connection setup
- H04W76/19—Connection re-establishment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/004—Artificial life, i.e. computing arrangements simulating life
- G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
-
- 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
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0802—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using antenna selection
- H04B7/0831—Compensation of the diversity switching process for non-uniform properties or faulty operations of the switches used in the diversity switching process
-
- 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
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/084—Equal gain combining, only phase adjustments
-
- 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
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/0842—Weighted combining
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
-
- 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention provides a wireless self-organizing network interruption compensation method and a device, wherein the method comprises the following steps: after any cell is interrupted, determining the allocation schemes of a plurality of different base station service user terminals according to a plurality of allocation modes of reallocating all user terminals in a target area to each base station for service and a plurality of allocation modes of each base station for antenna downtilt angle, antenna azimuth angle and power of the served user terminals; an allocation scheme that maximizes the weighted transmission rates of all user terminals is determined from among a plurality of different allocation schemes as a compensated allocation scheme. The method adjusts key parameters affecting user service quality and base station efficacy more flexibly than single parameter adjustment. The user transmission rate is used for measuring the optimization effect, so that the change caused by optimization can be truly reflected, important services can be preferentially met, and the service requirements of high-priority users can be met as much as possible under the condition that the user density is high or more base stations are interrupted.
Description
Technical Field
The present invention relates to the field of wireless communications, and in particular, to a method and apparatus for wireless ad hoc network outage compensation.
Background
With the development of 5G networks, future networks will develop from providing communication services between people and people only to providing connections between people and objects and thus provide more diversified informationized services, so that more strict requirements are put forward on network management and self-optimization, and 5G networks must have wider perceptibility and self-optimization capability, so as to improve reliability and intelligence of the networks, improve spectral efficiency, improve network perception of users, reduce probability of network occurrence, improve intelligent and automatic degree of network operation and maintenance, and realize fault self-diagnosis and self-optimization.
The self-organizing network is a network operation and maintenance strategy proposed by 3GPP and mainly comprises three functions of self-configuration, self-healing and self-optimization. The self-configuration function mainly comprises self-configuration of the base station and self-management in the running process, and can realize automatic management of the base station in the whole working period of the base station, including creation of the base station, automatic test, automatic IP address acquisition, automatic configuration related parameters, neighbor cell planning and the like. The self-configuration function greatly reduces the artificial operation and maintenance cost and reduces the cost of network infrastructure construction. The autonomous recovery function mainly processes network element faults in a network, and the function monitors equipment in the network in real time, when fault warning occurs, firstly analyzes fault information, then automatically or manually executes solving measures, and reports the fault information after the fault processing is finished so as to enable a system to learn, namely fault backup and the like. The self-optimizing function mainly refers to optimizing network performance by self-adaptively adjusting parameters in network equipment and the like, and the wireless network is optimized mainly by two kinds of parameter optimization and mechanical optimization, and the self-optimizing function of the self-organizing network comprises a plurality of technologies.
The cell outage compensation method in the wireless self-organizing network is mostly realized based on a single parameter at present and mainly comprises two kinds of optimization configuration and mechanical optimization of network parameters. The optimization of network parameters includes downlink transmission power and channel, etc., the mechanical optimization includes downtilt angle and azimuth angle of antenna, etc., and the interruption compensation is realized by adjusting some parameters of neighbor cells of the interruption cell. However, most schemes only consider a certain point, so that the applicability is not strong, and a good optimization effect cannot be achieved in a network environment with complex and various networks in the future. In addition, for the user dense area, if the network compensation can not meet the normal requirements of all users, the current method can not dynamically adjust the power distribution and the mechanical parameters according to the characteristics of the service, so that the important service requirements can be guaranteed preferentially.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a wireless self-organizing network interruption compensation method and device.
The invention provides a wireless self-organizing network interruption compensation method, which comprises the following steps: after any cell in the target area is interrupted, determining the allocation schemes of a plurality of different base stations for serving the user terminals according to a plurality of allocation modes of reallocating all the user terminals in the target area to each base station in the target area for serving and a plurality of allocation modes of each base station for antenna downtilt angle, antenna azimuth angle and served user terminal power; and determining an allocation scheme which maximizes the weighted transmission rate of all the user terminals from the allocation schemes of the plurality of different base stations serving the user terminals as a compensated allocation scheme.
According to an embodiment of the present invention, the method for compensating interruption of a wireless ad hoc network further includes, as a compensated allocation scheme, determining an allocation scheme that maximizes a weighted transmission rate of all user terminals from among allocation schemes in which the plurality of different base stations serve the user terminals: determining the signal to noise ratio between the base station and the user according to the channel gain between the user and the base station, the downlink transmission power provided by the base station for the user and the total transmission power of the base station; and determining the transmission rate of the user according to the signal-to-noise ratio.
According to the method for compensating interruption of wireless self-organizing network, before determining the signal to noise ratio between the base station and the user according to the channel gain between the user and the base station, the downlink transmission power provided by the base station for the user and the total transmission power of the base station, the method further comprises: respectively determining a horizontal antenna gain and a vertical antenna gain according to a horizontal azimuth angle and a vertical azimuth angle between a user and a base station; determining the total antenna gain between the base station and the user according to the horizontal antenna gain and the vertical antenna gain; and determining the channel gain between the user and the base station according to the total antenna gain and the user equipment gain.
According to an embodiment of the present invention, the method for compensating interruption of a wireless ad hoc network further includes, as a compensated allocation scheme, determining an allocation scheme that maximizes a weighted transmission rate of all user terminals from among allocation schemes in which the plurality of different base stations serve the user terminals: determining a coverage radius of each base station; for any two base stations m and n, determining the communication relation between the base stations according to the following formula:
determining that the sum of the communication numbers among all the base stations in any allocation scheme is larger than a preset threshold value;
wherein d m,n For the distance of base stations m and n, r m 、r m The coverage radii of base stations m and n, respectively.
According to an embodiment of the present invention, the method for compensating interruption of a wireless ad hoc network determines an allocation scheme with the largest weighted transmission rate of all user terminals from allocation schemes of the plurality of different base station service user terminals, and includes: taking each allocation scheme as one particle of a particle swarm algorithm, and initializing the value, the particle position and the particle speed of each particle; calculating the fitness of each particle by taking the weighted transmission rate of the user as a fitness function, and updating the historical optimal position and the global optimal position of each particle; dividing the particles into advanced particles and common particles according to the fitness, and updating the common particles and the advanced particles; if the adaptability of the position after the updating of the advanced particles is lower than that of the position before the updating, rolling back to the position before the updating, generating a chaotic point sequence based on the current position in a chaotic mapping mode, and selecting the point with the highest adaptability as a new position until the updating of all the particles is completed; repeating the calculation of the fitness of each particle, updating the historical optimal position and the global optimal position of each particle, and updating the common particles and the advanced particles until the iterative process of updating all the particles is completed until the preset iterative times are reached; and selecting particles with the largest fitness function value as a compensated distribution scheme.
According to one embodiment of the invention, the method for compensating interruption of wireless self-organizing network updates common particles and advanced particles comprises the following steps: determining an inertia factor according to the fitness function and the historical optimal position; and updating the common particles and the advanced particles according to the inertia factors, the historical optimal positions and the global optimal positions.
According to an embodiment of the invention, the method for compensating the interruption of the wireless self-organizing network generates a chaotic point sequence based on the current position by adopting a chaotic mapping mode, and comprises the following steps: according to the particles at the current position, tent mapping is carried out, three dimensional parameters of downward inclination angle setting, azimuth angle setting and power distribution of a user of each particle antenna are mapped to a 0-1 interval according to the following formula:
after M times of iteration, a chaotic sequence is obtained
Updating each dimension parameter in the particles k according to the following formula;
wherein [ a ] l ,b l ]For the value range of each dimension parameter, x kl A first dimension parameter representing a kth particle.
The invention also provides a wireless self-organizing network interruption compensation device, which comprises: the distribution module is used for determining distribution schemes of a plurality of different base station service user terminals according to a plurality of distribution modes of service from all user terminals in the target area to each base station in the target area after any cell in the target area is interrupted and a plurality of distribution modes of each base station for antenna downward inclination angle, antenna azimuth angle and power of the served user terminals; and the processing module is used for determining an allocation scheme which maximizes the weighted transmission rate of all the user terminals from the allocation schemes of the plurality of different base station service user terminals, and taking the allocation scheme as a compensated allocation scheme.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the wireless self-organizing network interrupt compensation method are realized by the processor when the program is executed.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the wireless ad hoc network outage compensation method according to any one of the above.
The wireless self-organizing network interruption compensation method and the device provided by the invention comprehensively consider the wireless parameter optimization and the mechanical parameter optimization, adapt to various application scenes, adjust key parameters affecting the service quality of users and the efficacy of the base station, and are more flexible than single parameter adjustment. The user transmission rate is used for measuring the optimization effect, the change caused by optimization can be truly reflected, the service of the user is classified, the important service can be preferentially met, and the service requirement of the user with high priority can be met as much as possible under the condition that the user density is high or more base stations are interrupted.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a wireless ad hoc network outage compensation method provided by the present invention;
fig. 2 is a schematic structural diagram of a wireless ad hoc network interrupt compensating device according to the present invention;
fig. 3 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The wireless ad hoc network outage compensation method and apparatus of the present invention are described below with reference to fig. 1-3. Fig. 1 is a flow chart of a wireless ad hoc network outage compensation method provided by the present invention, and as shown in fig. 1, the present invention provides a wireless ad hoc network outage compensation method, including:
101. after any cell in the target area is interrupted, determining the allocation schemes of a plurality of different base stations for serving the user terminals according to a plurality of allocation modes of reallocating all the user terminals in the target area to each base station in the target area for serving and a plurality of allocation modes of each base station for antenna downtilt angle, antenna azimuth angle and served user terminal power.
When the wireless self-organizing network interruption compensation model is established, key factors affecting the service quality of users need to be considered, including the downlink transmission power provided by a base station to the users and the direction angle and the downward inclination angle of an antenna.
There are several cells in a certain area, where a certain cell is interrupted. Assuming that the number of base stations in a target area cell is M, the number of users in the target area cell is N, the base station has two states, and is interrupted or normally operated, and the State of the base station is assumed to be State i The base station state takes the value of:
Users of an outage need to allocate new base stations, and users of an unbroken cell may also need to tune to new base stations to free up resources.
Using the symbol S ij The state of any user j served by the base station i is represented as follows:
thereby corresponding to the service distribution result of the new user and the base station.
Based on the allocation result, the antenna downtilt angle and azimuth angle of each base station are adjusted, and the power of the allocation user of the base station is allocated to obtain different allocation schemes.
102. And determining an allocation scheme which maximizes the weighted transmission rate of all the user terminals from the allocation schemes of the plurality of different base stations serving the user terminals as a compensated allocation scheme.
The optimization objective of the method is to maximize the weighted transmission rate of all users, assuming three priority user groups, N respectively 1 ，N 2 ，N 3 The corresponding weights are alpha respectively 1 ，α 2 ，α 3 The optimization function is:
wherein, the liquid crystal display device comprises a liquid crystal display device,and C j3 The transmission rates of the user groups with different priorities are respectively.
In a preferred embodiment, the objective function may include some or all of the following constraints:
1)indicating that the total number of service relationships is equal to the total number of users for all base stations and users in the area;
2)Meaning that for a certain user, it can only be served by one base station at the same time;
3)meaning that for a certain user, the obtained transmission power is necessarily equal to or greater than its minimum received power;
4)if a certain base station is in a normal working state at this time, the state value is necessarily equal to 1, no matter whether the base station is connected with a certain user or not, the state value is necessarily equal to or greater than the connection relation value, if the base station is in an interruption state at this time, the base station cannot be connected with any user, the state value is 0, and the service relation value is also necessarily 0;
5)meaning that for any base station, the sum of all the power that can be provided to the user must be less than or equal to the maximum power of that base station, where P i MAX Indicating the maximum downlink power of the base station;
6)meaning that the signal to noise ratio must be equal to or greater than a given value ω for a certain base station and user.
And solving the maximization of the objective function to obtain the compensated optimal allocation scheme.
The wireless self-organizing network interruption compensation method provided by the invention comprehensively considers the wireless parameter optimization and the mechanical parameter optimization, adapts to various application scenes, adjusts key parameters affecting the service quality of users and the efficacy of the base station, and is more flexible than single parameter adjustment. The user transmission rate is used for measuring the optimization effect, the change caused by optimization can be truly reflected, the service of the user is classified, the important service can be preferentially met, and the service requirement of the user with high priority can be met as much as possible under the condition that the user density is high or more base stations are interrupted.
In one embodiment, the determining an allocation scheme for maximizing the weighted transmission rate of all the user terminals from the allocation schemes of the plurality of different base stations serving the user terminals, as the compensated allocation scheme, further includes: determining the signal to noise ratio between the base station and the user according to the channel gain between the user and the base station, the downlink transmission power provided by the base station for the user and the total transmission power of the base station; and determining the transmission rate of the user according to the signal-to-noise ratio.
After obtaining the channel gain between the user and the base station, the signal to noise ratio between the base station i and the user j can be calculated, and the calculation formula is as follows:
wherein P is i j Representing the downlink transmission power provided by base station i for user j, S ij The communication relationship between the two is represented,representing the channel gain between the two, P k The calculation formula of the transmission power of a certain base station is as follows:
the formula indicates that the transmit power of a certain base station is equal to the sum of the downlink transmit power received by all users served by it.
State k Indicating the operating state of the base station, N 0 Is constant and represents the spectrum density of the additive Gaussian white noise, and the meaning of the formula is as follows: the signal to noise ratio between a certain base station i and a user j is equal to the value obtained by multiplying the effective power received by the user by the gain and dividing the effective power transmitted by all other base stations by the Gaussian white noise.
The transmission rate can be obtained after the signal-to-noise ratio is obtained
Wherein B is the channel bandwidth.
In one embodiment, before determining the signal-to-noise ratio between the base station and the user according to the channel gain between the user and the base station, the downlink transmission power provided by the base station for the user, and the total transmission power of the base station, the method further comprises: respectively determining a horizontal antenna gain and a vertical antenna gain according to a horizontal azimuth angle and a vertical azimuth angle between a user and a base station; determining the total antenna gain between the base station and the user according to the horizontal antenna gain and the vertical antenna gain; and determining the channel gain between the user and the base station according to the total antenna gain and the user equipment gain.
Key factors affecting coverage of a base station include downtilt angle and azimuth angle of an antenna, where downtilt angle of an antenna isAt this time, the vertical azimuth between base station i and user j is assumed to be +.>The calculation formula is:
base station i and useHorizontal azimuth between user j isThe calculation formula of the horizontal antenna gain is as follows:
wherein delta 3dB Representing horizontal half-power lobe width, G m Is constant.
Vertical azimuth between base station i and user j isThe calculation formula of the vertical antenna gain is as follows:
Wherein, xi e And SLA (service level agreement) v Are all constant and zeta 3dB Is the vertical half power lobe width.
Obtaining horizontal azimuth angle between base station i and user jAnd vertical azimuth +.>Thereafter, the total antenna gain between base station i and user j can be calculated>The calculation formula is as follows:
obtaining total antenna gainThe channel gain between base station i and user j can then be calculated>The calculation formula is as follows:
wherein G is user Indicating the gain of the user equipment,representing the path loss between base station i and user j, wherein +.>The calculation formula of (2) is as follows:
wherein f c Representing carrier frequency and epsilon represents extra loss.
In one embodiment, the determining, from the allocation schemes of the plurality of different base stations serving the user terminals, an allocation scheme with the largest weighted transmission rate of all the user terminals, as a compensated allocation scheme, further includes: determining a coverage radius of each base station; for any two base stations m and n, determining the communication relation between the base stations according to the following formula:
determining that the sum of the communication numbers among all the base stations in any allocation scheme is larger than a preset threshold value;
wherein d m,n For the distance of base stations m and n, r m 、r m The coverage radii of base stations m and n, respectively.
That is, there must be enough (a preset number of) base stations overlapped by the coverage area.
For each base station, there is its coverage radius, and the calculation formula is:
wherein d i Representing the furthest served user distance obtained by the path loss formula, the coverage radius of the base station is equal to the smaller of the furthest corresponding horizontal distance of its served object and the tan value of the base station height divided by its downtilt. After the coverage radius of each base station is obtained, the communication relationship between any two base stations can be evaluated as shown in formula (13).
Accordingly, the following constraints can be added when solving equation (3):
i.e. it means that the number of connections between all base stations needs to be larger than a given value η.
According to the embodiment of the invention, the sum of the communication numbers among all the base stations in any allocation scheme is determined to be larger than the preset threshold value, so that more resources among the base stations can be ensured to perform network compensation, and the compensation effect is improved.
In one embodiment, the determining, from the allocation schemes of the plurality of different base stations serving the user terminals, the allocation scheme with the largest weighted transmission rate of all the users as the compensated allocation scheme includes: taking each allocation scheme as one particle of a particle swarm algorithm, and initializing the value, the particle position and the particle speed of each particle; calculating the fitness of each particle by taking the weighted transmission rate of the user as a fitness function, and updating the historical optimal position and the global optimal position of each particle; dividing the particles into advanced particles and common particles according to the fitness, and updating the common particles and the advanced particles; if the adaptability of the new position of the advanced particle is lower than that of the position before updating, rolling back to the position before updating, generating a chaotic point sequence based on the current position in a chaotic mapping mode, and selecting the point with the highest adaptability as the new position until updating of all particles is completed; repeating the calculation of the fitness of each particle, updating the historical optimal position and the global optimal position of each particle, and updating the common particles and the advanced particles until the iterative process of updating all the particles is completed until the preset iterative times are reached; and selecting particles with the largest fitness function value as a compensated distribution scheme.
The particle swarm algorithm belongs to one of evolutionary algorithms, and is characterized in that from random solutions, optimal solutions are searched for through iteration, the quality of the solutions is evaluated by adopting fitness, the operations of crossing and mutation are removed compared with a genetic algorithm, global optimal is searched for through searching the currently searched optimal values, and the algorithm is high in accuracy and high in convergence speed.
The invention adopts an improved particle swarm optimization algorithm based on chaotic mapping to implement interrupt compensation. In order to avoid the algorithm from being trapped in local optimum, the invention introduces chaotic mapping in particle position updating. Chaos refers to a motion state with randomness obtained by a deterministic equation, a variable with the chaos state is called a chaos variable, the variable has randomness, ergodic property and regularity, and the characteristic of the chaos variable is utilized to optimize searching, avoid local optimization and improve the global searching capability of an algorithm.
In the algorithm iteration process, the particles are divided into two types according to the fitness value, wherein one type is advanced particles, and the other type is common particles. The advanced particles are particles with a certain value of fitness or small change amplitude (such as change amplitude smaller than a preset threshold value or change amplitude smaller than a preset proportion) in iteration, the positions and the speeds of the common particles are updated in a conventional mode, the positions of the advanced particles are updated by a conventional method, if the fitness value of the new position is not higher than that of the current position, the original coordinates are returned, a chaotic mapping mode is adopted to generate a chaotic point sequence to be selected, and the point with the highest fitness is selected as the new coordinates, and the speed of the chaotic point is not changed. The advanced particles search the optimal solution in the local range by a chaotic mapping method, and in the iterative process, the two types of particles are mutually converted and jointly evolve.
According to the above idea, the algorithm first initializes a population of particles, which contains a set of random solutions in the format X i ＝(x 1 ,x 2 ,...x K ) Each solution x in the set of random solutions i Is a scheme showing the power allocation and configuration of downtilt and azimuth angles of all base stations to users, assuming K e K, for scheme x k In terms of the content, the content indicated is:
when each base station allocates power, it is necessary to ensure that:
1) The sum of the power allocated by the single base station cannot be greater than P i MAX 。
2) The power allocated for each user must be guaranteed to be greater than or equal to the gain multiplied by
3) Each base station has a status code State i Indicating the working state of the base station, maintaining a service list, indicating the number of the user served by the base station, wherein 1 indicates that the corresponding user is served by the base station i, and 0 indicates that the user is not served by the base station i, and ensuring that all the users are served in the processes of initializing solution sets and each iteration.
4) Each user can only be served by one base station, so if a certain user has been assigned to a certain base station, no other base station can provide service to that user anymore.
5) If the status code of a certain base station is 0, the downtilt angle, azimuth angle and service list of the base station are all empty.
6) For any base station user pair, its signal to noise ratio must be greater than a given value ω.
7) The coverage radius of the base station can be calculated by the service list and the downtilt angle of the base station, and the adjacency relation between the base station and the adjacent base station can be evaluated, wherein the number of adjacency relations must be larger than a given value eta.
The above conditions need to be met all the time during the initialization of the solution set and the iteration process. For each particle, given its initial velocity, V i ＝(v 1 ,v 2 ,...v K ) Wherein v is k Representation of particle x k In terms of its speed of movement, which is in the same form as the particle, is shown below:
each particle has a fitness determined by the objective function and is able to know the best position pbest found so far, and the position x now located k In addition to this, all particles share position information, so that the best position gbest found by all particles in the whole population so far can be known, and the particles determine their next actions by their own experience and the best experience in the population.
v k ＝ω*v k +c 1 ×rand()×(pbest k -x k )+c 2 ×rand()×(gbest-x k ) (17)
The above is an updated formula for particle velocity, where ω v k Indicating the extent to which the speed in the next step affects with the speed of the last state, w is an inertia factor.
In one embodiment, the updating of the normal particles and the advanced particles includes: determining an inertia factor according to the fitness function and the optimal positions found by all particles; and updating the common particles and the advanced particles according to the inertia factors, the optimal positions found by all particles and the optimal positions found by history.
The invention adopts an improved particle swarm optimization algorithm based on self-adaptive weight and chaotic mapping to implement interrupt compensation, and in the speed updating, the weight w adopted by the traditional particle swarm algorithm is a fixed value and lacks variation.
In the present invention, the inertia factor w is defined as:
where gbest represents the maximum of the current global fitness. fit k Indicating the fitness of the particle k, the calculation formula is:
Wherein C is j I.e. the transmission rate in the model part, alpha being the weight.
In the conventional particle swarm algorithm, c1 and c2 are fixed values, and represent the influence degrees of the speed by the maximum value searched by the algorithm and the global maximum value respectively, if the speed is too large in the initial stage c2 of the algorithm, the algorithm tends to the global optimal position too early, so that a local optimal solution is caused, and if the speed is too large in the later stage c1 of the algorithm, the algorithm is difficult to converge, so that the initial bias of c1 is gradually reduced, and the initial bias of c2 is gradually reduced and gradually increased in the whole iterative process of the algorithm.
c 1 ×rand()×(pbest k -x k ) A vector pointing from the current point to the best point considered by the particle itself for self-aware term, whereincur represents the current iteration number, total represents the given total iteration number, and with iteration numberAn increase in the number, c 1 And will be continuously reduced.
c 2 ×rand()×(gbest k -x k ) For the group cognitive term, a vector pointing from the current point to the best point in the group reflects the collaborative cooperation and knowledge sharing among particles, whereinAs the number of iterations increases, c 2 Will increase accordingly.
After the velocity of the particle at this iteration is obtained, the position of the particle can be updated as follows:
in summary, the steps of the present algorithm can be obtained as follows:
1) Initializing various parameters including total iteration times total, iteration times M of chaotic mapping, population scale K, and giving an initial population and initial speed.
2) The fitness of each particle was calculated.
3) The historical best position pbest of each particle, and the global best position gbest are updated.
4) The method comprises the steps of dividing particles into two types according to fitness, namely normal particles and advanced particles, wherein the normal particles update speed and position, the advanced particles try to update the position through a normal particle mode, if the new position fitness is lower than the current position, rolling back to the original position, generating a chaotic point sequence based on the current position in a chaotic mapping mode, selecting the point with the highest fitness as the new position, and keeping the speed unchanged. In this way the whole population of particles is updated.
5) If the current iteration times cur > v, ending the algorithm, and outputting the optimal scheme, otherwise, returning to the step 2). The following table shows:
the interruption compensation method of the wireless self-organizing network adopts the interruption compensation method of the improved particle swarm algorithm based on self-adaptive weight and chaotic mapping: the current optimal allocation scheme is found through a heuristic method, the algorithm is prevented from sinking into local optimal through a self-adaptive weight and chaotic mapping method, and the optimization effect is guaranteed.
In one embodiment, the generating the chaotic point list based on the current position by adopting the chaotic mapping method includes: according to the particles at the current position, tent mapping is carried out, three dimensional parameters of downward inclination angle setting, azimuth angle setting and power distribution of a user of each particle antenna are mapped to a 0-1 interval according to the following formula:
after M times of iteration, a chaotic sequence is obtained
Updating each dimension parameter in the particles k according to the following formula;
wherein [ a ] l ,b l ]For the value range of each dimension parameter, x kl A first dimension parameter representing a kth particle.
The chaotic mapping mode adopted by the embodiment of the invention is Tent mapping, and the formula is as follows:
according to the Tent mapping, the chaotic point column of the particle k can be obtained through the following steps:
1) The particles x are expressed according to formula (21) k The third dimension is an allocation scheme, and the mapping method is the same.
The variables are mapped into the interval of 0 to 1 by the above formula.
2) Using equation (21) to convert cx kl Iterating M times to obtain a chaotic sequence
3) Each dimension in particle k is updated as per equation (22).
4) Particle x can be obtained by chaotic sequence k The chaotic point column after being mapped by the Tent needs to be noted that because of the constraint relation, the points which do not accord with the constraint need to be screened and deleted after the mapping:
The wireless self-organizing network interruption compensating device provided by the invention is described below, and the wireless self-organizing network interruption compensating device and the wireless self-organizing network interruption compensating method described above can be correspondingly referred to each other.
Fig. 2 is a schematic structural diagram of a wireless ad hoc network outage compensation device according to the present invention, as shown in fig. 2, the wireless ad hoc network outage compensation device includes: an allocation module 201 and a processing module 202. The allocation module 201 is configured to determine allocation schemes of a plurality of different base station service ues according to a plurality of allocation modes of reallocating all ues in a target area to each base station in the target area for service after any cell in the target area is interrupted, and a plurality of allocation modes of each base station for antenna downtilt angle, antenna azimuth angle and power of served ues; the processing module 202 is configured to determine, from the allocation schemes of the plurality of different base stations serving the user terminals, an allocation scheme that maximizes the weighted transmission rates of all the user terminals, as a compensated allocation scheme.
In an embodiment of the apparatus, the processing module 202 is further configured to determine, from the allocation schemes of the plurality of different base stations serving the user terminals, an allocation scheme that maximizes the weighted transmission rates of all the user terminals, as a compensated allocation scheme, before: determining the signal to noise ratio between the base station and the user according to the channel gain between the base station and the user, the downlink transmission power provided by the base station for the user and the total transmission power of the base station; and determining the transmission rate of the user according to the signal-to-noise ratio.
In an embodiment of the apparatus, the processing module 202 is further configured to, before determining the signal-to-noise ratio between the base station and the user, according to the channel gain between the base station and the user, the downlink transmission power provided by the base station for the user, and the total transmit power of the base station: respectively determining a horizontal antenna gain and a vertical antenna gain according to a horizontal azimuth angle and a vertical azimuth angle between a user and a base station; determining the total antenna gain between the base station and the user according to the horizontal antenna gain and the vertical antenna gain; and determining the channel gain between the user and the base station according to the total antenna gain and the user equipment gain.
In an embodiment of the apparatus, the processing module 202 is further configured to determine, from the allocation schemes of the plurality of different base stations serving the user terminals, an allocation scheme that maximizes the weighted transmission rates of all the user terminals, as a compensated allocation scheme, before: determining a coverage radius of each base station; for any two base stations m and n, determining the communication relation between the base stations according to the following formula:
determining that the sum of the communication numbers among all the base stations in any allocation scheme is larger than a preset threshold value;
wherein d m,n For the distance of base stations m and n, r m 、r m The coverage radii of base stations m and n, respectively.
In one apparatus embodiment, the processing module 202 is further to: taking each allocation scheme as one particle of a particle swarm algorithm, and initializing the value, the particle position and the particle speed of each particle; calculating the fitness of each particle by taking the weighted transmission rate of the user as a fitness function, and updating the historical optimal position and the global optimal position of each particle; dividing the particles into advanced particles and common particles according to the fitness, and updating the common particles and the advanced particles; if the adaptability of the position after the updating of the advanced particles is lower than that of the position before the updating, rolling back to the position before the updating, generating a chaotic point sequence based on the current position in a chaotic mapping mode, and selecting the point with the highest adaptability as a new position until the updating of all the particles is completed; repeating the calculation of the fitness of each particle, updating the historical optimal position and the global optimal position of each particle, and updating the common particles and the advanced particles until the iterative process of updating all the particles is completed until the preset iterative times are reached; and selecting particles with the largest fitness function value as a compensated distribution scheme.
In one apparatus embodiment, the processing module 202 is further to: determining an inertia factor according to the fitness function and the historical optimal position; and updating the common particles and the advanced particles according to the inertia factors, the historical optimal positions and the global optimal positions.
In one apparatus embodiment, the processing module 202 is further to: according to the particles in the current position, tent mapping is carried out, three dimensional parameters are distributed to the antenna downtilt angle, the azimuth angle and the power of a user in each particle, and the three dimensional parameters are mapped to a 0-1 interval according to the following formula:
after M times of iteration, a chaotic sequence is obtained
Updating each dimension parameter in the particles k according to the following formula;
wherein [ a ] l ,b l ]For the value range of each dimension parameter, x kl A first dimension parameter representing a kth particle.
The embodiment of the device provided by the embodiment of the present invention is for implementing the above embodiments of the method, and specific flow and details refer to the above embodiments of the method, which are not repeated herein.
The wireless self-organizing network interruption compensation device provided by the embodiment of the invention comprehensively considers the wireless parameter optimization and the mechanical parameter optimization, adapts to various application scenes, adjusts key parameters affecting the service quality of users and the efficacy of the base station, and is more flexible than single parameter adjustment. The user transmission rate is used for measuring the optimization effect, the change caused by optimization can be truly reflected, the service of the user is classified, the important service can be preferentially met, and the service requirement of the user with high priority can be met as much as possible under the condition that the user density is high or more base stations are interrupted.
Fig. 3 is a schematic structural diagram of an electronic device provided by the present invention, and as shown in fig. 3, the electronic device may include: processor 301, communication interface (Communications Interface) 302, memory (memory) 303 and communication bus 304, wherein processor 301, communication interface 302, memory 303 accomplish the communication between each other through communication bus 304. The processor 301 may invoke logic instructions in the memory 303 to perform a wireless ad hoc network interrupt compensation method comprising: after any cell in the target area is interrupted, determining the allocation schemes of a plurality of different base stations for serving the user terminals according to a plurality of allocation modes of reallocating all the user terminals in the target area to each base station in the target area for serving and a plurality of allocation modes of each base station for antenna downtilt angle, antenna azimuth angle and served user terminal power; and determining an allocation scheme which maximizes the weighted transmission rate of all the user terminals from the plurality of different allocation schemes as a compensated allocation scheme.
Further, the logic instructions in the memory 303 may be implemented in the form of software functional units and stored in a computer readable storage medium when sold or used as a stand alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the wireless ad hoc network interrupt compensation method provided by the above methods, the method comprising: after any cell in the target area is interrupted, determining the allocation schemes of a plurality of different base stations for serving the user terminals according to a plurality of allocation modes of reallocating all the user terminals in the target area to each base station in the target area for serving and a plurality of allocation modes of each base station for antenna downtilt angle, antenna azimuth angle and served user terminal power; and determining an allocation scheme which maximizes the weighted transmission rate of all the user terminals from the allocation schemes of the plurality of different base stations serving the user terminals as a compensated allocation scheme.
In still another aspect, the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, is implemented to perform the wireless ad hoc network outage compensation method provided by the above embodiments, the method comprising: after any cell in the target area is interrupted, determining the allocation schemes of a plurality of different base stations for serving the user terminals according to a plurality of allocation modes of reallocating all the user terminals in the target area to each base station in the target area for serving and a plurality of allocation modes of each base station for antenna downtilt angle, antenna azimuth angle and served user terminal power; and determining an allocation scheme which maximizes the weighted transmission rate of all the user terminals from the allocation schemes of the plurality of different base stations serving the user terminals as a compensated allocation scheme.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A wireless ad hoc network outage compensation method, comprising:
after any cell in the target area is interrupted, determining the allocation schemes of a plurality of different base stations for serving the user terminals according to a plurality of allocation modes of reallocating all the user terminals in the target area to each base station in the target area for serving and a plurality of allocation modes of each base station for antenna downtilt angle, antenna azimuth angle and served user terminal power;
determining an allocation scheme for maximizing the weighted transmission rate of all the user terminals from the allocation schemes of the plurality of different base station service user terminals as a compensated allocation scheme;
The determining, from the allocation schemes of the plurality of different base stations serving the user terminals, an allocation scheme that maximizes the weighted transmission rates of all the user terminals, as a compensated allocation scheme, further includes:
determining a coverage radius of each base station;
for any two base stations m and n, determining the communication relation between the base stations according to the following formula:
；
determining that the sum of the communication numbers among all the base stations in any allocation scheme is larger than a preset threshold value;
wherein, the liquid crystal display device comprises a liquid crystal display device,for the distance of base stations m and n, +.>、/>The coverage radii of base stations m and n, respectively;
the determining, from the allocation schemes of the plurality of different base stations serving the user terminals, an allocation scheme that maximizes the weighted transmission rates of all the user terminals, as a compensated allocation scheme, includes:
taking each allocation scheme as one particle of a particle swarm algorithm, and initializing the value, the particle position and the particle speed of each particle;
calculating the fitness of each particle by taking the weighted transmission rate of the user as a fitness function, and updating the historical optimal position and the global optimal position of each particle;
dividing the particles into advanced particles and common particles according to the fitness, and updating the common particles and the advanced particles; the advanced particles are particles in which the adaptation degree does not change any more when reaching a target value in iteration, or particles with the change amplitude smaller than a preset threshold value after reaching the target value, or particles with the change amplitude smaller than a preset proportion after reaching the target value;
If the adaptability of the position after the updating of the advanced particles is lower than that of the position before the updating, rolling back to the position before the updating, generating a chaotic point sequence based on the current position in a chaotic mapping mode, and selecting the point with the highest adaptability as a new position until the updating of all the particles is completed;
repeating the calculation of the fitness of each particle, updating the historical optimal position and the global optimal position of each particle, and updating the common particles and the advanced particles until the iterative process of updating all the particles is completed until the preset iterative times are reached;
and selecting particles with the largest fitness function value as a compensated distribution scheme.
2. The wireless ad hoc network outage compensation method according to claim 1, wherein said determining an allocation scheme that maximizes weighted transmission rates of all user terminals from among the allocation schemes of the plurality of different base station serving user terminals, as a compensated allocation scheme, further comprises:
determining the signal to noise ratio between the base station and the user according to the channel gain between the base station and the user, the downlink transmission power provided by the base station for the user and the total transmission power of the base station;
and determining the transmission rate of the user according to the signal-to-noise ratio.
3. The wireless self-organizing network outage compensation method according to claim 2, wherein before determining the signal-to-noise ratio between the base station and the user based on the channel gain between the base station and the user, the downlink transmission power provided by the base station to the user, and the total transmission power of the base station, further comprising:
respectively determining a horizontal antenna gain and a vertical antenna gain according to a horizontal azimuth angle and a vertical azimuth angle between a user and a base station;
determining the total antenna gain between the base station and the user according to the horizontal antenna gain and the vertical antenna gain;
and determining the channel gain between the user and the base station according to the total antenna gain and the user equipment gain.
4. The wireless ad hoc network outage compensation method according to claim 1, wherein said updating the normal particles and the advanced particles comprises:
determining an inertia factor according to the fitness function and the historical optimal position;
and updating the common particles and the advanced particles according to the inertia factors, the historical optimal positions and the global optimal positions.
5. The method for compensating for interruption of wireless ad hoc network according to claim 1, wherein said generating a chaotic point train based on a current position by means of chaotic mapping comprises:
According to the particles in the current position, tent mapping is carried out, three dimensional parameters are distributed to the antenna downtilt angle, the azimuth angle and the power of a user in each particle, and the three dimensional parameters are mapped to a 0-1 interval according to the following formula:
；
after M times of iteration, a chaotic sequence is obtained；
And updating each dimension parameter in the particle k according to the following formula:
；
wherein, the liquid crystal display device comprises a liquid crystal display device,for the value range of each dimension parameter, +.>The +.>And (5) dimension parameters.
6. A wireless ad hoc network outage compensation device, comprising:
the distribution module is used for determining distribution schemes of a plurality of different base station service user terminals according to a plurality of distribution modes of service from all user terminals in the target area to each base station in the target area after any cell in the target area is interrupted and a plurality of distribution modes of each base station for antenna downward inclination angle, antenna azimuth angle and power of the served user terminals;
a processing module, configured to determine, from among the allocation schemes of the plurality of different base station service user terminals, an allocation scheme that maximizes weighted transmission rates of all user terminals, as a compensated allocation scheme;
the determining, from the allocation schemes of the plurality of different base stations serving the user terminals, an allocation scheme that maximizes the weighted transmission rates of all the user terminals, as a compensated allocation scheme, further includes:
Determining a coverage radius of each base station;
for any two base stations m and n, determining the communication relation between the base stations according to the following formula:
；
determining that the sum of the communication numbers among all the base stations in any allocation scheme is larger than a preset threshold value;
wherein, the liquid crystal display device comprises a liquid crystal display device,for the distance of base stations m and n, +.>、/>The coverage radii of base stations m and n, respectively;
the determining, from the allocation schemes of the plurality of different base stations serving the user terminals, an allocation scheme that maximizes the weighted transmission rates of all the user terminals, as a compensated allocation scheme, includes:
taking each allocation scheme as one particle of a particle swarm algorithm, and initializing the value, the particle position and the particle speed of each particle;
calculating the fitness of each particle by taking the weighted transmission rate of the user as a fitness function, and updating the historical optimal position and the global optimal position of each particle;
dividing the particles into advanced particles and common particles according to the fitness, and updating the common particles and the advanced particles; the advanced particles are particles in which the adaptation degree does not change any more when reaching a target value in iteration, or particles with the change amplitude smaller than a preset threshold value after reaching the target value, or particles with the change amplitude smaller than a preset proportion after reaching the target value;
If the adaptability of the position after the updating of the advanced particles is lower than that of the position before the updating, rolling back to the position before the updating, generating a chaotic point sequence based on the current position in a chaotic mapping mode, and selecting the point with the highest adaptability as a new position until the updating of all the particles is completed;
repeating the calculation of the fitness of each particle, updating the historical optimal position and the global optimal position of each particle, and updating the common particles and the advanced particles until the iterative process of updating all the particles is completed until the preset iterative times are reached;
and selecting particles with the largest fitness function value as a compensated distribution scheme.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the wireless ad hoc network interrupt compensation method of any one of claims 1 to 5 when the program is executed by the processor.
8. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the wireless ad hoc network outage compensation method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111005837.1A CN113630906B (en) | 2021-08-30 | 2021-08-30 | Method and device for compensating interruption of wireless self-organizing network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111005837.1A CN113630906B (en) | 2021-08-30 | 2021-08-30 | Method and device for compensating interruption of wireless self-organizing network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113630906A CN113630906A (en) | 2021-11-09 |
| CN113630906B true CN113630906B (en) | 2023-07-18 |
Family
ID=78388408
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111005837.1A Active CN113630906B (en) | 2021-08-30 | 2021-08-30 | Method and device for compensating interruption of wireless self-organizing network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113630906B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102843709A (en) * | 2012-05-30 | 2012-12-26 | 北京邮电大学 | Interruption compensation method and device for SON (self-organized network) systems |
| CN103269494A (en) * | 2013-04-24 | 2013-08-28 | 北京邮电大学 | Method and system for interruption compensating in wireless access network cell |
| EP2770772A1 (en) * | 2013-02-26 | 2014-08-27 | Alcatel Lucent | Cell failure compensation method and network node |
| WO2016029442A1 (en) * | 2014-08-29 | 2016-03-03 | 华为技术有限公司 | Data transmission method and device |
| EP3018860A1 (en) * | 2014-11-06 | 2016-05-11 | Telefonaktiebolaget LM Ericsson (publ) | Outage compensation in a cellular network |
| CN105813097A (en) * | 2016-05-09 | 2016-07-27 | 东南大学 | Interruption compensation method for cell in mobile communication network |
-
2021
- 2021-08-30 CN CN202111005837.1A patent/CN113630906B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102843709A (en) * | 2012-05-30 | 2012-12-26 | 北京邮电大学 | Interruption compensation method and device for SON (self-organized network) systems |
| EP2770772A1 (en) * | 2013-02-26 | 2014-08-27 | Alcatel Lucent | Cell failure compensation method and network node |
| CN103269494A (en) * | 2013-04-24 | 2013-08-28 | 北京邮电大学 | Method and system for interruption compensating in wireless access network cell |
| WO2016029442A1 (en) * | 2014-08-29 | 2016-03-03 | 华为技术有限公司 | Data transmission method and device |
| EP3018860A1 (en) * | 2014-11-06 | 2016-05-11 | Telefonaktiebolaget LM Ericsson (publ) | Outage compensation in a cellular network |
| CN105813097A (en) * | 2016-05-09 | 2016-07-27 | 东南大学 | Interruption compensation method for cell in mobile communication network |
Non-Patent Citations (2)
| Title |
|---|
| 基于功率和倾角联合优化的小区中断补偿机制;李文;尹梦君;喻鹏;项楠;;电子与信息学报(05);全文 * |
| 基于天线下倾角优化的小区中断补偿机制;乔彬;;电信网技术(07);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113630906A (en) | 2021-11-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109947545B (en) | Task unloading and migration decision method based on user mobility | |
| CN109729528B (en) | D2D resource allocation method based on multi-agent deep reinforcement learning | |
| CN111372314A (en) | Task unloading method and task unloading device based on mobile edge computing scene | |
| WO2020125454A1 (en) | Information processing method, system and apparatus | |
| CN107949025B (en) | Network selection method based on non-cooperative game | |
| US20210326695A1 (en) | Method and apparatus employing distributed sensing and deep learning for dynamic spectrum access and spectrum sharing | |
| US20040077354A1 (en) | Systems and methods for managing wireless communications using link space information | |
| CN113873434B (en) | Communication network hotspot area capacity enhancement oriented multi-aerial base station deployment method | |
| CN108075975B (en) | Method and system for determining route transmission path in Internet of things environment | |
| WO2020048594A1 (en) | Procedure for optimization of self-organizing network | |
| CN105101248A (en) | Device for controlling change of working state of cell and method thereof | |
| CN111628855A (en) | Industrial 5G dynamic multi-priority multi-access method based on deep reinforcement learning | |
| Balevi et al. | A clustering algorithm that maximizes throughput in 5G heterogeneous F-RAN networks | |
| EP2578016A2 (en) | Dynamic channel and transmission rate selection | |
| CN104378772B (en) | Towards the small base station deployment method of the amorphous covering of cell in a kind of cellular network | |
| CN109362093B (en) | Resource optimization method for maximizing total throughput of network function virtualization | |
| CN114698128A (en) | Anti-interference channel selection method and system for cognitive satellite-ground network | |
| WO2021188726A1 (en) | Method and system for enhancing signal qualities within a wi-fi network using an adaptive - software defined network (a-sdn) | |
| Guo et al. | A deep reinforcement learning based mechanism for cell outage compensation in massive IoT environments | |
| Zhao et al. | Power control for D2D communication using multi-agent reinforcement learning | |
| CN113630906B (en) | Method and device for compensating interruption of wireless self-organizing network | |
| Ma et al. | Socially aware distributed caching in device-to-device communication networks | |
| Gong et al. | Distributed DRL-based resource allocation for multicast D2D communications | |
| Khuntia et al. | An actor-critic reinforcement learning for device-to-device communication underlaying cellular network | |
| CN114173421B (en) | LoRa logic channel based on deep reinforcement learning and power distribution method |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |