Dynamic clustering for radio coordination in a virtual network
US-2015311961-A1 · Oct 29, 2015 · US
US11432166B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11432166-B2 |
| Application number | US-201716636658-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 14, 2017 |
| Priority date | Aug 14, 2017 |
| Publication date | Aug 30, 2022 |
| Grant date | Aug 30, 2022 |
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The present invention refers to a method and apparatus and computer program for detecting communities in a radio access network with a plurality of vertices (C, BBU), wherein the method comprises calculating (S11) relationship strengths (31, 41) for network connections between the vertices (C, BBU) by executing a connection strength calculation process by analyzing performance factors, decisive for network performance including cell coverage overlap, signal strength, and inter-cell interference. The method further creates (S12) a network graph with nodes, representing the vertices (C,BBU) in the network and edges, representing the network connections based on the calculated relationship strengths (31, 41) and applies (S13) an extended iterative disjoint community detection algorithm for clustering nodes into communities, wherein in each iteration imposed one or more constraints for clustering cooperating nodes into the same community are analyzed (S14).
Opening claim text (preview).
The invention claimed is: 1. A method for detecting communities in a radio access network of a mobile telecom network with a plurality of vertices, the method comprising: calculating relationship strengths for network connections between the plurality of vertices by executing a connection strength calculation process by analyzing performance factors decisive for radio access network performance, wherein each vertex in the plurality of vertices represents an entity in a radio access network (RAN); creating a network graph, with nodes representing the vertices in the radio access network, and edges representing the network connections, based on the calculated relationship strengths; applying an extended iterative disjoint community detection algorithm for clustering nodes into communities, wherein in each iteration imposed, one or more different constraints for clustering nodes into the same community are analyzed; wherein the nodes are at least of a first type and a second type; wherein a node of the second type comprises or is connectable to multiple nodes of the first type, and wherein a node of the first type does not belong to multiple nodes of the second type; wherein the extended iterative disjoint community detection algorithm is firstly applied to nodes of the first type to provide an intermediate result with communities of nodes of the first type; and wherein the intermediate result serves as input for secondly applying the extended iterative disjoint community detection algorithm to the nodes of the second type; and clustering the nodes of the first and second type for which the constraints are fulfilled into communities of a first and second type, respectively. 2. The method of claim 1 , wherein the performance factors comprise: cell coverage overlap, signal strength, and/or inter-cell interference. 3. The method of claim 1 , further comprising providing the one or more constraints for clustering nodes into the same community. 4. The method of claim 1 , wherein the connection strength calculation process considers radio access network performance measures. 5. The method of claim 1 , wherein a connection strength calculation process for detecting baseband communities is based on analyzing a set of performance factors for achieving an optimal carrier aggregation network performance, the set comprising inter-frequency cell coverage overlap and signal quality, number of inter-frequency cell relationships, and/or physical cell distance. 6. The method of claim 5 , wherein detected baseband unit communities are used for coordination of the plurality of baseband units in order to improve radio access network performance by means of carrier aggregation and in order to mitigate inter-cell interference by applying uplink and/or down-link Coordinated Multi-Point features. 7. The method of claim 1 , wherein a connection strength calculation process for detecting cell communities is based on analyzing a set of performance factors for achieving an optimal radio access network performance with respect to coordinated multipoint and carrier aggregation techniques, the set comprising intra- and inter-frequency cell coverage overlap, signal strength and quality, and/or physical cell distance. 8. The method of claim 1 , wherein the one or more constraints for clustering cells as first type nodes in one baseband unit as a second type node, which serves as community, are provided and refer to capacity requirements of the respective baseband unit and comprise: a maximum and/or minimum number of cells per baseband unit; a maximum number of connected users per baseband unit; a maximum number of VoIP users per baseband unit; and/or a maximum number of scheduling entities and/or scheduling messages per baseband unit. 9. The method of claim 1 , wherein the one or more constraints for clustering cooperating baseband units as second type nodes in one community are provided and refer to capacity requirements of the respective community and comprise: a maximum and/or minimum number of baseband units per community. 10. The method of claim 1 , wherein detected cell communities are used to define baseband units in such a way that the network performance is improved by means carrier aggregation and in order to mitigate inter-cell interference by applying uplink and/or downlink Coordinated Multi-Point features for those baseband units. 11. The method of claim 1 wherein each vertex in the plurality of vertices represents a cell or a baseband unit (BBU). 12. A coordination apparatus for detecting communities in a radio access network of a mobile telecom network with a plurality of vertices, the coordination apparatus comprising: processing circuitry; memory containing instructions executable by the processing circuitry whereby the apparatus is operative to: calculate relationship strengths for network connections between the plurality of vertices by executing a connection strength calculation process by analyzing performance factors decisive for radio access network performance, wherein each vertex in the plurality of vertices represents an entity in a radio access network (RAN); create a network graph, with nodes representing the vertices in the network, and edges representing the network connections, based on the calculated relationship strengths; and apply an extended iterative disjoint community detection algorithm for clustering nodes into communities, wherein in each iteration imposed one or more different constraints for clustering cooperating nodes into the same community are analyzed; wherein the nodes are at least of a first type and a second type; wherein a node of the second type comprises or is connectable to multiple nodes of the first type, and wherein a node of the first type does not belong to multiple nodes of the second type; wherein the extended iterative disjoint community detection algorithm is firstly applied to nodes of the first type to provide an intermediate result with communities of nodes of the first type; and wherein the intermediate result serves as input for secondly applying the extended iterative disjoint community detection algorithm to the nodes of the second type; and clustering the nodes of the first and second type for which the constraints are fulfilled into communities of a first and second type, respectively. 13. A non-transitory computer readable recording medium storing a computer program product for controlling a coordination apparatus for detecting communities in a radio access network of a mobile telecom network with a plurality of vertices, the computer program product comprising program instructions which, when run on processing circuitry of the coordination apparatus, causes the coordination apparatus to: calculate relationship strengths for network connections between the plurality of vertices by executing a connection strength calculation process by analyzing performance factors decisive for radio access network performance, wherein each vertex in the plurality of vertices represents an entity in a radio access network (RAN); create a network graph, with nodes representing the vertices in the radio access network, and edges representing the network connections, based on the calculated relationship strengths; apply an extended iterative disjoint community detection algorithm for clustering nodes into communities, wherein in each iteration imposed one or more constraints for clustering nodes into the same community are analyzed; wherein the nodes are at least of a first type and a second type; wherein a node of the second type comprises or is connectable to multiple nodes of the first type, and wherein a node of the fir
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