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System and Method for enhancing self optimizing functions of a network Disclosure Number: IPCOM000241147D
Publication Date: 2015-Mar-31
Document File: 4 page(s) / 38K

Publishing Venue

The Prior Art Database


This paper describes an improved system and method for enhancing self-optimizing functions of a network. The enhancement is achieved by feeding a reliable estimation of the future demand derived from collective call information located in the corporate mail servers. This optimizes the current self-optimizing algorithms which purely depends on the historical load pattern and real-time load changes. The self-optimizing function results can be improved if the realistic future demand is considered along with the historic and real time load information.

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System and Method for enhancing self optimizing functions of a network

Back Ground

    Currently Self-Optimizing networks are employed as a major functional area of Self-Organizing Network (SON) concept in mobile communication technology. SON is an automation technology designed to make the planning, configuration, management, optimization and healing of mobile radio access networks simpler and faster. It is considered to be a necessity in future mobile networks and operations due to the increased cost pressure. The main drivers are essentially to reduce CAPEX and OPEX, which would otherwise increase dramatically due to increased number of network parameters that has to be monitored and set, the rapidly increasing numbers of base stations in the network and parallel operation of 2G, 3G and Evolved Packet Core (EPC) infrastructures. The three major functional areas of SON are self-configuration, self-optimization and self-healing.

    As the networks become complex day by day, it is necessary to ensure that networks adapt automatically to ensure optimal network utilization as well as its performance. SON self-optimization functions are aiming at maintaining network quality and performance with a minimum of manual intervention from the operator. Self-optimization functions monitors and analyzes performance data and automatically triggers optimization action on affected network element(s) when necessary. This significantly reduces manual interventions and replaces them with automatic adjustments keeping the network optimized at all times. Self-optimizing SON functions make it possible to introduce new automatic processes that are too fast, and/or too complex to be implemented manually.

    Every base station contains hundreds of configuration parameters that control various aspects of the cell site. Current deployment of self-optimization concept is to determine and alter these various configuration parameters to change network behavior, based on observations of both the base station itself, and measurements at the mobile station or handset. One of the first SON features establishes neighbor relations automatically, while others optimize random access

parameters or mobility robustness in terms of handover oscillations. A very illustrative use case is the automatic switch-off of a percent of base stations during the night hours. The neighboring base station would then re-configure their parameters in order to keep the entire area covered by signal. In case of a sudden growth in connectivity demand for any reason, the "sleeping" base stations "wake up" almost instantaneously. This mechanism leads to significant energy savings for operators.

    In mobile communication networks, there are number of areas where self-optimization of the network is undertaken. Few of those areas are to ensure mobility robustness optimization, mobility load balancing and traffic steering, energy saving, coverage and capacity optimization and random access channel optimiza...