METHOD FOR JOINT AND COORDINATED LOAD BALANCING AND COVERAGE AND CAPACITY OPTIMIZATION IN CELLULAR COMMUNICATION NETWORKS

• US 20150189533A1
• Filed: 08/26/2013
• Published: 07/02/2015
• Est. Priority Date: 08/24/2012
• Status: Active Grant

• Current Assignee: Actix GmbH
• Original Assignee: Actix GmbH, Technische Universitã¤T Dresden
• Inventors: Voigt, Jens, Fehske, Albrecht, Isheden, Christian, Klessig, Henrik
• Granted Patent: US 9,775,068 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H04W 16/18 Network planning tools
• CPC Class Codes: H04W 24/02 Arrangements for optimising operational condition
• CPC Class Codes: H04W 28/021 in wireless networks with changing topologies, e.g. ad-hoc networks self-organizing networks H04W84/18
• CPC Class Codes: H04W 28/0226 based on location or mobility handoff or reselection H04W36/00; mobile application services making use of the location of users or terminals H04W4/02

Abstract

The present invention relates to a method for optimizing a real cellular, wireless communication network that combines mobility load balancing (MLB) with coverage and capacity optimization (CCO) in a joint and coordinated optimization. An optimal set of physical base station parameters is determined by performing an iterative direct search. The iterative direct search comprises a partitioning strategy to jointly determine an optimal partition of the served area and an associated optimal load of each of the plurality of base stations for a current set of physical base station parameters for each direct search iteration; said partitioning strategy using an updated value of the received power of the pilot or reference signal for each the plurality of user locations associated with the current set of physical base station parameters for each direct search iteration.

Claims

1. A method for optimizing a real cellular, wireless communication network comprising a plurality of base stations and having a network configuration comprising a plurality of radio cells, the plurality of radio cells serving a served area;

each of the plurality of radio cells covering a cell area which is further sub-divided into user locations, said network being defined by network parameters, the method comprising;

providing a model of said cellular, wireless communication network having an original model network configuration;

providing, for each of said user locations, a value of a received power of a pilot or reference signal and a traffic demand;

optimizing said model network configuration by performing an iterative direct search to determine an optimal set of physical base station parameters;

wherein the iterative direct search comprises;

a partitioning strategy to jointly determine an optimal partition of the served area and an associated optimal load of each of the plurality of base stations for a current set of physical base station parameters for each direct search iteration;

said partitioning strategy using an updated value of the received power of the pilot or reference signal for each the plurality of user locations associated with the current set of physical base station parameters for each direct search iteration;

and

using said optimized model network configuration to configure said real cellular, wireless communication network.

2. The method of claim 1, wherein the partitioning strategy comprises:

computing a signal-to-interference-and-noise ratio coverage using the optimal partition of the served area and associated optimal load for each of the plurality of base stations and the updated value of the received power of the pilot or reference signal for each of the plurality of user locations for each direct search iteration.

3. The method of claim 1, wherein the partitioning strategy comprises:

computing a reference signal received power coverage using the optimal partition of the served area and associated optimal load for each of the plurality of base stations and the updated value of the received power of the pilot or reference signal for each of the plurality of user locations for each direct search iteration.

4. The method of claim 1, wherein the partitioning strategy comprises:

minimizing a function of loads for each of the plurality of base stations.

5. The method of claim 4, wherein the partitioning strategy comprises:

explicitly considering an interdependency between an inter-base station interference and the load of a base station.

6. The method of claim 4, wherein the partitioning strategy comprises:

setting cell load values for each of the plurality of base stations to one minus an arbitrarily positive constant; and

iteratively searching for a fix point of the load of each of the plurality of base stations by computing a data rate for each of the plurality of base stations by considering a mean interference power,

computing cell areas for each of the plurality of base stations using the given degree of load balancing; and

updating the load for each of the plurality of base stations by computing a ratio of a measured base station average resource utilization and the data rate for each of the plurality of base stations and applying an exponential averaging with a forgetting factor for each fix point iteration.

7. The method of claim 4, wherein the iterative direct search comprises:

constraining the load of each of the plurality of base stations to a defined supremum such that the load is below the defined supremum and/or

constraining the load of each of the plurality of base stations to a defined infinum such that the load is above the defined infinum and/or

constraining the received power of the pilot or reference signal of each of the plurality of base stations such that the received power is above a defined threshold at least in a defined part of the serving area and/or

constraining a signal-to-interference-and-noise ratio of the pilot or reference signal of each of the plurality of base stations such that the signal-to-interference-and noise ratio is above a defined threshold at least in a defined part of the serving area.

8. The method of claim 1, wherein using said optimized model network configuration to configure said real cellular, wireless communication network comprises:

transforming the optimal partition of the served area into a power offset for each of the plurality of base stations; and

adding the power offset to the transmit power of the pilot or reference signal of each of the plurality of base stations.

9. The method of claim 1, wherein the load of a base station is defined as the sum over all user locations in the base station'"'"'s served area of the ratio of traffic demand and data rate per user location, wherein estimating the data rate per user location comprises considering a measured or estimated signal-to-interference and noise ratio at the user location.

10. The method of claim 1, wherein the iterative direct search comprises:

performing the partitioning strategy for each of the plurality of base stations in an order of descending loads.

11. The method of claim 7, the method comprising:

giving out a signal when no optimal partition fulfilling all imposed constraints could be found, said signal being indicative of a specific constraint that could not be fulfilled.

12. The method of claim 1, wherein optimizing said model network configuration comprises:

setting and maintaining a degree of load balancing and/or the set of physical base station parameters as constant.

13. The method of claim 1, the method comprising:

weighting, for each of said user locations, the traffic demand with a linear factor.

14. The method of claim 1, wherein providing, for each of said user locations, a traffic demand comprises:

obtaining said traffic demand by geolocation techniques and traffic statistics.

15. The method of claim 8, wherein transforming the optimal partition of the served area into a power offset for each of the plurality of base stations comprises:

determining a power offset for a base station that is specific to a neighboring base station by minimizing an integrated overlap area between cell borders.