CN109526042A - A kind of network access point selection method of the LWA system based on OWMAD - Google Patents
A kind of network access point selection method of the LWA system based on OWMAD Download PDFInfo
- Publication number
- CN109526042A CN109526042A CN201910064571.4A CN201910064571A CN109526042A CN 109526042 A CN109526042 A CN 109526042A CN 201910064571 A CN201910064571 A CN 201910064571A CN 109526042 A CN109526042 A CN 109526042A
- Authority
- CN
- China
- Prior art keywords
- access point
- network
- network access
- attribute
- value
- 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.)
- Granted
Links
- 238000010187 selection method Methods 0.000 title claims abstract description 8
- 239000011159 matrix material Substances 0.000 claims abstract description 37
- 238000000034 method Methods 0.000 claims abstract description 25
- 238000012545 processing Methods 0.000 claims abstract description 6
- 238000005259 measurement Methods 0.000 claims description 3
- 238000001228 spectrum Methods 0.000 abstract description 5
- 238000010295 mobile communication Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 5
- 230000005540 biological transmission Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 238000000060 site-specific infrared dichroism spectroscopy Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000015556 catabolic process Effects 0.000 description 2
- 230000001413 cellular effect Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000006731 degradation reaction Methods 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 238000013468 resource allocation Methods 0.000 description 2
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W48/00—Access restriction; Network selection; Access point selection
- H04W48/16—Discovering, processing access restriction or access information
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/318—Received signal strength
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
- H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W48/00—Access restriction; Network selection; Access point selection
- H04W48/20—Selecting an access point
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Computer Security & Cryptography (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The network access point selection method for the LWA system based on OWMAD that the present invention relates to a kind of, belongs to mobile communication field.Method includes the following steps: S1: in network access point selection cycle, the information that network-side is fed back according to UE first obtains alternative eNBs set in current network access point selection cycleGather with APsS2: the alternative subset of network access point is measured respectivelyWithThe attribute value of property set forms the decision matrix A of attribute valueN×M, and standardization processing is carried out to it, obtain decision Standard Process RN×M；S3: the attribute optimal weights vector ω of current network access point is calculated+；S4: the weighted value vector f of each network access point is calculated+；S5: being ranked up weighted value, acquires the smallest network access point b of weighted value*, and execute access point connection.The present invention can be improved the availability of frequency spectrum of LWA system, mitigate the load of eNB, guarantee the QoS demand of UE, simplify access point selection course.
Description
Technical Field
The invention belongs to the field of mobile communication, and relates to a network access point selection technology of an LWA system in a heterogeneous network.
Background
In recent years, with the explosive increase of mobile data traffic and types, higher demands are made on network system capacity and data rate. To meet the mobile traffic increase of nearly 1000 times in the next 10 years, the fifth generation mobile communication (5G) becomes a research hotspot in academia and industry. With the aim of improving mobile data rate and network system capacity, many new technologies and solutions, such as massive MIMO, millimeter wave communication, dense cellular heterogeneous network, etc., have recently emerged. In existing heterogeneous networks (hetnets), IEEE 802.11 Wireless Local Area Networks (WLANs) have the advantages of rich bandwidth resources and large low-cost deployments in cities, making WLAN networks an attractive solution to complement LTE networks. By deploying a large number of low-transmission-power APs in a hot spot area or an area with high service pressure, part of data transmitted by the LTE network is transmitted to a User Equipment (UE) through the WLAN network, thereby improving the system capacity of the entire network.
The heterogeneous network has become a key network evolution path, and the mutual fusion of the networks has also become a big trend, and the lwa (lte WLAN aggregation) system plays an important role in improving the system spectrum efficiency and energy efficiency, and increasing the network system capacity and data transmission rate. The basic idea of the LWA system is to utilize the AP deployment of the existing WLAN network to transmit a part of data to be transmitted from the eNB to the UE through the WLAN network, and to improve the spectrum reuse rate of the network by using the advantages of the deployment density and number of the WLAN APs, thereby improving the overall performance of the network. Unlike the conventional LTE system, the LWA system has the following advantages: firstly, a large number of APs are densely deployed in a network system, especially in hot spot areas or areas with large service load, LWA not only can solve the problem of coverage blind areas existing in the traditional cellular network, improve the coverage of the network, but also can realize seamless connection between a base station and UE and load balance of the network, and improve the capacity of the network system; secondly, in the LWA system, although the coverage area of the AP is small, the transmission distance from the transmitting end (AP) to the receiving end (UE) is short, so that the communication quality of the UE is improved, and meanwhile, the transmitting power of the WLAN AP is small, the deployment is flexible, and the cost is low, thereby reducing the cost of the whole system. As described above, the LWA system shows a good application prospect. However, in the LWA system, as the number of currently deployed APs is increased, the distance between AP stations is decreased, and a new series of technical difficulties and challenges are brought. First, in the LWA system, due to the large and dense deployment of the eNB and the AP, especially the large number of APs, and the performance of each access point is different, how to efficiently select the optimal access point in the access point selection of the LWA system is a very necessary and practical problem. Secondly, in the LWA system, offloading and offloading is not a single choice for traffic transmission in a certain network, and the capacity and performance of each network base station need to be considered before resource allocation, and if the allocation number is not limited, it is very likely to cause disadvantages such as performance degradation and capacity degradation for a certain network, so resource allocation needs to consider how to efficiently allocate resources to improve the throughput and performance of the system without damaging the performance of the two existing networks.
In an actual LTE network system, the number of UEs requesting services varies with time, and when the number of UEs requesting services in the network is large, the eNB load is too heavy, and the system performance is degraded. At this time, if the LTE network eNB cannot effectively reduce its load, and a large number of new users are forced to access the network because the performance of the current network access point is unknown, the congestion probability of the system is increased, the network performance is deteriorated, and the system throughput is reduced. Therefore, an LWA system network access point selection technology is provided, which can effectively reduce the eNB load, reduce the congestion probability, and increase the system throughput on the premise of ensuring that the user obtains sufficient qos (quality of service) stability. The selection of the network access point mainly comprises three processes: (1) an access point discovery process; (2) an access point selection process; (3) and (5) access point access process. In the LWA system network access point selection, an eNB of an LTE network and an AP of a WLAN network are mainly selected, such as a single network access point or both network access points are selected.
In the heterogeneous network LWA system, the main problems and technical challenges faced by the network access point selection technology include:
(1) the network access point selects the best-performing access point access design. The existing methods include access point selection based on maximum RRSI (received Signal Strength indicator), access point selection based on maximum SINR (Signal to Interference noise ratio), and the like.
(2) How to quickly and efficiently collect attribute values of an attribute set selected by each network access point.
(3) How to reduce the latency of access point selection.
Disclosure of Invention
In view of this, the present invention is directed to provide a network access point selection method for an LWA system based on OWMAD (Optimal weighted-attribute determination), which simplifies a UE measurement calculation process and reduces feedback information amount between a UE and a base station, for the case that an LTE network eNB load is too large due to access of a large number of users and an LTE network access point cannot guarantee a user QoS requirement.
In order to achieve the purpose, the invention provides the following technical scheme:
a network access point selection method of an LWA system based on an OWMAD includes the steps of selecting a to-be-selected subset of network access points through RSSI and setting a multi-attribute decision set: access capacity, RSSI, time delay; then the AP and the eNB feed back the attribute value and the time delay value of the capacity to the network end, the UE feeds back the RSSI to the network end, and a decision matrix is generated for the attribute values of different networks; secondly, simply and quickly calculating the weighted value of each eNB and each AP according to the decision matrix and the optimal weight vector; and finally, performing an access strategy by using the selected weighted minimum value. In order to enable the UE to select the access point with the best performance for connection, the method obtains the optimal weight vector of the access point by constructing the Lagrangian function. The method specifically comprises the following steps:
s1: in the network access point selection period, the network end firstly obtains the eNBs set which can be selected in the current network access point selection period according to the information fed back by the UEAnd APs Collection
S2: separately measuring alternative subsets of network access pointsAndattribute values of the attribute set, and decision matrix A for forming attribute valuesN×MAnd carrying out standardization processing on the matrix R to obtain a decision standardization matrix RN×M；
S3: calculating an attribute optimal weight vector omega of the current network access point+；
S4: based on step S3, a weight vector f for each network access point is calculated+；
S5: based on step S4, the weighted value f is added+Sorting to obtain the network access point b with the minimum weighted value*And performs access point connection.
Further, the step S1 specifically includes: in the network access point selection period, the network end firstly obtains the eNBs set which can be selected in the current network access point selection period according to the information fed back by the UEAnd APs CollectionAnd respectively satisfy:
wherein,representing a set of eNBsA certain eNB biThe RSRP value of the LTE network received by UE k when serving the UE,the minimum value of the LTE network which the UE k allows to receive is within the coverage range of the LTE network;representing a set of APsIn a certain AP bjThe RSRP value of the WLAN network received by UE k when serving the UE,UE k is allowed to receive the LTE network minimum value for WLAN network coverage.
Further, the step S2 specifically includes the following steps:
s21: the rows of the decision matrix correspond to the network access points, the columns are determined by the attribute values of the attribute sets of the network access points, and the attribute sets are composed of three attributes of access capacity, RSSI and time delay, specifically:
wherein, aijAn attribute value representing a jth attribute of an ith access point;
s22: unified measurement, namely carrying out standardization processing on the decision matrix to obtain a decision standardized matrix as follows:
wherein,represents the decision matrix AN×MMaximum value in j-th column;represents the decision matrix AN×MThe minimum value in the j-th column.
Further, the step S3 specifically includes the following steps:
s31: defining an objective functionWherein ω isjA weight value representing a jth attribute in the set of attributes;
s32, constructing Lagrangian function L (omega, ξ) for access point weighted value, and obtaining optimal weight vector
Further, the step S4 specifically includes: using the optimal weight vector omega+And obtaining a weighted value vector of each network access point with the decision matrix:
f+＝[f1,f2,…,fN]T＝RN×M*ω+
wherein f isiIndicating a performance weighting value for the ith network access point.
Further, in step S5, the weighted values are sorted to obtain the network access point with the best performance:
the invention has the beneficial effects that: the invention not only can effectively lighten the load of the eNB of the LTE network, but also can effectively shorten the data delay. Compared with the traditional scheme of selecting the access point with the maximum RSSI or the access point with the maximum SINR, the method and the device can improve the spectrum utilization rate of the LWA system, reduce the load of the eNB and ensure the QoS requirement of the UE. Meanwhile, the information feedback quantity of UEs and eNBs brought by a network access point mechanism is greatly reduced, and the access point selection process is simplified.
Drawings
In order to make the object, technical scheme and beneficial effect of the invention more clear, the invention provides the following drawings for explanation:
FIG. 1 is a diagram illustrating access point selection initialization based on signal strength;
FIG. 2 is a schematic diagram of an access point selection attribute set;
FIG. 3 is a timing diagram of network access point selection;
fig. 4 is a flowchart of an OWMAD-based access point selection algorithm.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The invention relates to a network access point selection method of an LWA system based on an OWMAD, which comprises 9 initial conditions and 6 main steps:
initial condition 1: assuming that each UE is equipped with a single antenna, the eNB and the AP are connected through an Xw interface and may transfer information including UE location, mobility of the UE, load, and the like. A central controller (which may be referred to as a network end for short) exists in the network system, and is specifically responsible for collecting relevant information reported by the UE and access capacity information and delay information of the AP and eNB, and performing a network access point selection operation. The eNB, the AP and the network end are connected in a double mode, and the eNB, the AP and the network end are connected in pairs.
Initial condition 2: consider a heterogeneous network LWA system that employs network access point selection. In the network system, in a macro cell coverage area, wherein the macro cell occupies a low frequency band (<2.5GHz) to provide a wide coverage area and a position tracking function of UE, APs are deployed in the macro cell coverage area, and APs occupy a high frequency band (>5.0GHz) to provide stable high-speed data transmission and improve network system capacity by using a large amount of idle frequency spectrum of a WLAN network. In order for the macro cell to maintain a wide coverage and UE tracking and feedback information, APs will feedback information according to the system requirements.
Initial condition 3: since the positions of the eNBs are generally fixed in the actual network, the channel gains between the eNBs can be considered to be kept constant or have small fluctuation amplitude, and the positions of the APs are also fixed, and the channel gains between the APs can be considered to be kept constant or have small fluctuation amplitude. It can be further appreciated that for a UE, once the enb and APs are deployed, most of the decision matrix of the access point attribute values can be considered to be associated with the UE. Therefore, after the network topology structure is determined, the attribute values of the eNBs and the APs in the LWA system can be measured off-line in advance, a decision matrix is formed, and the decision matrix is stored in the network.
Initial condition 4:
access point selection initialization: the UE in the network is dual-link UE, and the UE is simultaneously connected with the eNB, the AP and the network terminal. The UE periodically moves to the network in the process of network activityThe terminal reports the RSSI of the service eNB and the AP and the corresponding eNBID and the AP SSID once, if a single eNB and a single AP are met, the reporting process does not need to be executed, and if a single eNB and a plurality of APs are met, only the RSSI of the AP and the corresponding AP SSID need to be uploaded. During a certain access point selection period (fig. 1 is a diagram illustrating the access point selection initialization signal strength), different RSRP thresholds are designed for two networks for UE kAndcomparing RSSI values of LTE networksSelecting a candidate set available for access point selection by an LTE network eNBComparing the RSSI values of the WLAN networkSelecting candidate sets of WLAN network APs available for access point selection
Initial condition 5:
definition of a decision matrix: the set of network attributes (fig. 2 is a schematic diagram of the set of access point selection attributes), which mainly refers to access capacity, delay, and RSSI, is defined. For a single UE k in the LWA system, RSSI of the LTE network and the WLAN network needs to be collected and fed back to the network, and meanwhile, the access points eNBs and APs need to collect the capacity of the current access point and the attribute value of the delay, and feed back information to the network. Suppose that the LTE network has NLeNB, WLAN network has NWThere are M AP and both networks consider the attribute set. Constructing a decision matrix for attribute values of an LTE networkConstructing decision matrix for attribute value of WLAN network
Initial condition 6:
calculation of decision matrix normalization: because the performance of the access points of each network is different, the attribute values in the attribute set are also different, and in order to facilitate subsequent calculation, normalization processing needs to be performed on each attribute. Column vector A of decision matrix for eNBs of LTE networkl＝[a1l,a2l,…,aMl]TNormalizing the column vector elements to a normalized matrix using the following equation (3)Column vector a ═ a of decision matrix for APs of WLAN network1p,a2p,…,aMp]TNormalizing the column vector elements to a normalized matrix using the following equation (4)
Initial condition 7:
determining the optimal weight: for the attribute, the attribute weight can well reflect the variation degree of the attribute in the attribute set, and has a decisive influence on the performance of each access point, so the weight value should be carefully considered. For corresponding to the attribute values, the optimal weight is obtained by using a decision matrix and an objective function, wherein the performance objective function g of each access point+In order to obtain the weight value construction Lagrangian function L (omega, ξ), a weight optimal solution is obtained
Initial condition 8:
determining an optimal scheme: in the network access point selection scheme, for access points of different networks, considering different attribute values, an optimal weight vector omega is obtained by utilizing an objective function+Obtaining weighted values by utilizing the optimal weighted values and the access point performance, sequencing the weighted values, selecting the access point represented by the weighted minimum value as the best access point of the current network performance, and determining the best access point of the LTE network as the best access pointThe best access point for a WLAN network is
Initial condition 9: it is assumed that the attribute values of the attribute set of the network access point have been measured in advance and saved to the network side. Further assume that the UE in the network is a dual-link UE, that is, the UE establishes a connection with the eNB, the AP and the network simultaneously. In the process of network activity, the UE periodically reports the RSSI of the serving eNB and the AP and the corresponding eNB ID and the corresponding AP SSID to the network end, if a single eNB and a single AP are encountered, the reporting process is not required to be executed, and if a single eNB and a plurality of APs are encountered, only the RSSI of the AP and the corresponding AP SSID are required to be uploaded. The specific reporting information feedback timing sequence is shown in fig. 3.
On the basis of the above initial conditions, as shown in fig. 4, the network access point selection method of the present invention is implemented by the following steps:
the method comprises the following steps: in the network access point selection period, the network end firstly obtains the eNBs set which must be selected in the current access point selection period according to the information fed back by the UEAnd APs CollectionAnd satisfy formula (17):
wherein,representing a set of eNBsA certain eNB biThe RSRP value of the LTE network received by UE k when serving the UE,the minimum value of the LTE network which the UE k allows to receive is within the coverage range of the LTE network;representing a set of APsIn a certain AP bjThe RSRP value of the WLAN network received by UE k when serving the UE,the minimum value of the LTE network which the UE k allows to receive in the coverage range of the WLAN network; at the same time, acquiring alternative eNBs setAnd APs Collection
Step two: separately measuring alternative subsets of network access pointsAndthe attribute value of the attribute set is used for generating a decision matrix A of the current attribute value by using the formulas (1) and (2)N×MNormalizing the column vector of the decision matrix by using the formulas (3) and (4) to obtain a decision normalized matrix RN×M。
Step three: calculating the attribute optimal weight vector omega of the current network access point by using the formulas (18) and (19)+. (assuming that the kth UE performs selection, since the access point selection processes of the two networks are the same, it is uniformly written as a general formula, that is, N in the general formula can represent NLAnd may represent NW)。
Wherein r isijRepresents the normalized value of the attribute value, and L (ω, ξ) represents the lagrange function.
Step four: the current UE all-area candidates are calculated by equations (20) and (21)Weighted values for each network access point in the subset, and in particular, by superimposing optimal attribute weightsAnd a normalized matrix RN×MTo calculate the weighted value of each access point in the current network.
f+＝[f1,f2,…,fN]T＝RN×M*ω+(21)
Step five: and for the network access point selection with the best performance, based on the fourth step, the network access point selection is judged in a manner of sorting the weighted values, and specifically, in all the candidate subsets, the access point with the best performance is selected by using the formula (22) for subsequent access.
Step six: and finally, carrying out an access point selection period at the kth UE, and executing access point connection operation according to the obtained network access point with the best performance, namely the minimum weight. In particular, for LTE networks, in the setThe access point with the smallest weighted value is selectedConnecting; for WLAN networks, in the setThe access point with the smallest weighted value is selectedThe connection is made.
Finally, it is noted that the above-mentioned preferred embodiments illustrate rather than limit the invention, and that, although the invention has been described in detail with reference to the above-mentioned preferred embodiments, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the invention as defined by the appended claims.
Claims (6)
1. A network access point selection method of an LWA system based on an OWMAD is characterized by comprising the following steps:
s1: in the network access point selection period, the network end firstly obtains the eNBs set which can be selected in the current network access point selection period according to the information fed back by the UEAnd APs Collection
S2: separately measuring alternative subsets of network access pointsAndattribute values of the attribute set, and decision matrix A for forming attribute valuesN×MAnd carrying out standardization processing on the matrix R to obtain a decision standardization matrix RN×M；
S3: calculating an attribute optimal weight vector omega of the current network access point+；
S4: based on step S3, a weight vector f for each network access point is calculated+；
S5: based on step S4, the weighted values are sorted to obtain the network access point b with the smallest weighted value*And performs access point connection.
2. The method for selecting a network access point of an LWA system based on OWMAD according to claim 1, wherein the step S1 specifically includes: in the network access point selection period, the network end firstly obtains the eNBs set which can be selected in the current network access point selection period according to the information fed back by the UEAnd APs CollectionAnd respectively satisfy:
wherein,representing a set of eNBsA certain eNB biThe RSRP value of the LTE network received by UE k when serving the UE,the minimum value of the LTE network which the UE k allows to receive is within the coverage range of the LTE network;representing a set of APsCertain APb injThe RSRP value of the WLAN network received by UE k when serving the UE,UE k is allowed to receive the LTE network minimum value for WLAN network coverage.
3. The method for selecting the network access point of the LWA system based on the OWMAD according to claim 2, wherein the step S2 specifically includes the following steps:
s21: the method comprises the following steps that the attribute values of the attribute sets of the network access points corresponding to the rows and the columns of the decision matrix, and the three attributes of access capacity, RSSI and time delay form an attribute set, and specifically the method comprises the following steps:
wherein, aijAn attribute value representing a jth attribute of an ith access point;
s22: unified measurement, namely carrying out standardization processing on the decision matrix to obtain a decision standardized matrix as follows:
wherein,represents the decision matrix AN×MMaximum value in j-th column;represents the decision matrix AN×MThe minimum value in the j-th column.
4. The method for selecting the network access point of the LWA system based on the OWMAD according to claim 3, wherein the step S3 specifically includes the following steps:
s31: defining an objective functionWherein ω isjA weight value representing a jth attribute in the set of attributes;
s32, constructing a Lagrangian function L (omega, ξ) for the target function, and obtaining an optimal weight vector
5. The method for selecting the network access point of the LWA system based on the OWMAD according to claim 4, wherein the step S4 specifically includes: using optimal weightsWeight vector omega+And obtaining a weighted value vector of each network access point with the decision matrix:
f+＝[f1,f2,…,fN]T＝RN×M*ω+
wherein f isiIndicating a performance weighting value for the ith network access point.
6. The method as claimed in claim 5, wherein in step S5, the ranking of the performance weighted values of the aps results in the network ap with the best performance:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910064571.4A CN109526042B (en) | 2019-01-23 | 2019-01-23 | Network access point selection method of LWA system based on OWMAD |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910064571.4A CN109526042B (en) | 2019-01-23 | 2019-01-23 | Network access point selection method of LWA system based on OWMAD |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109526042A true CN109526042A (en) | 2019-03-26 |
| CN109526042B CN109526042B (en) | 2021-02-02 |
Family
ID=65799365
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910064571.4A Active CN109526042B (en) | 2019-01-23 | 2019-01-23 | Network access point selection method of LWA system based on OWMAD |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109526042B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111083724A (en) * | 2019-12-26 | 2020-04-28 | 重庆邮电大学 | OCWG-TOPSIS-based user association method in fog computing network |
| CN111093239A (en) * | 2019-12-16 | 2020-05-01 | 运易通科技有限公司 | Communication device for logistics intelligent door lock |
| CN111818620A (en) * | 2020-06-05 | 2020-10-23 | 袁建涛 | Network selection method and system for multi-mode terminal |
| CN112566223A (en) * | 2020-12-01 | 2021-03-26 | 江苏科技大学 | WLAN access point selection method based on multi-attribute weighting |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102113359A (en) * | 2008-07-31 | 2011-06-29 | 高通股份有限公司 | Resource partitioning in heterogeneous access point networks |
| CN106131921A (en) * | 2016-07-19 | 2016-11-16 | 南京理工大学 | The access point system of selection of heterogeneous network |
| EP3213594A1 (en) * | 2015-02-05 | 2017-09-06 | MediaTek Inc. | Network selection and data aggregation with lte-wlan aggregation |
| CN108293266A (en) * | 2015-11-27 | 2018-07-17 | 华为技术有限公司 | network node and its method |
| US20180295572A1 (en) * | 2017-04-07 | 2018-10-11 | Qualcomm Incorporated | Wireless local area network (wlan) selection for long term evolution (lte) - wlan aggregation (lwa) |
-
2019
- 2019-01-23 CN CN201910064571.4A patent/CN109526042B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102113359A (en) * | 2008-07-31 | 2011-06-29 | 高通股份有限公司 | Resource partitioning in heterogeneous access point networks |
| EP3213594A1 (en) * | 2015-02-05 | 2017-09-06 | MediaTek Inc. | Network selection and data aggregation with lte-wlan aggregation |
| CN108293266A (en) * | 2015-11-27 | 2018-07-17 | 华为技术有限公司 | network node and its method |
| CN106131921A (en) * | 2016-07-19 | 2016-11-16 | 南京理工大学 | The access point system of selection of heterogeneous network |
| US20180295572A1 (en) * | 2017-04-07 | 2018-10-11 | Qualcomm Incorporated | Wireless local area network (wlan) selection for long term evolution (lte) - wlan aggregation (lwa) |
Non-Patent Citations (1)
| Title |
|---|
| 徐浪，申滨，周晓勇，金纯: "LWA关键技术分析", 《计算机工程与应用》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111093239A (en) * | 2019-12-16 | 2020-05-01 | 运易通科技有限公司 | Communication device for logistics intelligent door lock |
| CN111083724A (en) * | 2019-12-26 | 2020-04-28 | 重庆邮电大学 | OCWG-TOPSIS-based user association method in fog computing network |
| CN111083724B (en) * | 2019-12-26 | 2022-02-11 | 重庆邮电大学 | OCWG-TOPSIS-based user association method in fog computing network |
| CN111818620A (en) * | 2020-06-05 | 2020-10-23 | 袁建涛 | Network selection method and system for multi-mode terminal |
| CN111818620B (en) * | 2020-06-05 | 2022-04-01 | 袁建涛 | Network selection method and system for multi-mode terminal |
| CN112566223A (en) * | 2020-12-01 | 2021-03-26 | 江苏科技大学 | WLAN access point selection method based on multi-attribute weighting |
| CN112566223B (en) * | 2020-12-01 | 2022-11-15 | 江苏科技大学 | WLAN access point selection method based on multi-attribute weighting |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109526042B (en) | 2021-02-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109526042B (en) | Network access point selection method of LWA system based on OWMAD | |
| EP4344287A1 (en) | Optimizing a cellular network using machine learning | |
| Al Sibahee et al. | Efficient extreme gradient boosting based algorithm for QoS optimization in inter-radio access technology handoffs | |
| CN105898757B (en) | A kind of frequency spectrum resource allocation method in wireless backhaul link isomery Internet of Things | |
| CN104584616A (en) | Method for joint and coordinated load balancing and coverage and capacity optimization in cellular communication networks | |
| CN103703814A (en) | Beamforming for cell edge capacity improvement in a heterogeneous network | |
| JP6570620B2 (en) | Multi-cell beam forming method and apparatus | |
| US20230209467A1 (en) | Communication method and apparatus | |
| US10833736B2 (en) | Hybrid beamforming method for beam-based cooperative transmission, and apparatus for the same | |
| Wang et al. | QoS-aware cell association in 5G heterogeneous networks with massive MIMO | |
| CN103220688A (en) | Moving-load balancing method based on efficacy function in LTE (long term evolution) self-organized network | |
| CN107708157A (en) | Intensive small cell network resource allocation methods based on efficiency | |
| CN106792893A (en) | Isomery cellular network cut-in method based on maximal received power | |
| CN106028371B (en) | The dynamic TDD configuration method of serial interference between a kind of reduction microcell cluster | |
| CN104618934B (en) | A kind of global optimization relay node selecting method based on throughput prediction | |
| CN103517309B (en) | A kind of cell interrupt compensation method explored based on the behavior of asymptotic greed | |
| CN110430584B (en) | Uplink multi-beam initial access method for non-active users in millimeter wave network | |
| Liya et al. | A MADM-based handover management in software defined 5G network | |
| Peng et al. | Macro-controlled beam database-based beamforming protocol for LTE-WiGig aggregation in millimeter-wave heterogeneous networks | |
| Radwan et al. | Towards Cell-Free Networking: Analytical Study of Ultra-Dense On-Demand Small Cell Deployment for Internet of Things | |
| CN107071911B (en) | Virtual cell carrier allocation method based on maximum SNR | |
| Zhang et al. | Congestion-aware user-centric cooperative base station selection in ultra-dense networks | |
| Li et al. | A speed-aware joint handover approach for clusters of D2D devices | |
| Sun et al. | Data driven smart load balancing in wireless networks | |
| US20240008018A1 (en) | Method, Apparatus and Computer Program for Machine Learning-Assisted Beams Coordinated Scheduling in 5G and Beyond |
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 |