Autonomous Self-Optimization of Coverage and Capacity in LTE Cellular Networks
Authors
Abstract
Self-organizing networks promise significant expenditure savings for operators when rolling out modern cellular network infrastructure, such as Long-Term Evolution (LTE) and LTE-Advanced systems. Savings in capital expenditures (CAPEX) and operational expenditures (OPEX) can be achieved in both the network deployment and network operation phase. Particularly, self-organized optimization of network coverage and network capacity is a key challenge to cope with the boost in mobile data traffic that is expected in the next years and to benefit from the growing market. We present a traffic-light related approach to autonomous self-optimization of tradeoff performance indicators in LTE multitier networks. Introducing a low-complexity interference approximation model, the related optimization problem is formulated as a mixed-integer linear program and is embedded into a self-organized network operation and optimization framework. Tuning site activity, transmission power, and antenna downtilt are parameters of eNodeBs and Home eNodeBs. The optimization procedure is carried out considering time-variant optimization parameters that are automatically adapted with respect to changes in the network. Simulation-based evaluation of representative case studies demonstrates applicability and the benefit potential of our overall concept.
BibTEX Reference Entry
@article{EnReXuMaZhZh13, author = {Alexander Engels and Michael Reyer and Xiang Xu and Rudolf Mathar and Jietao Zhang and Hongcheng Zhuang}, title = "Autonomous Self-Optimization of Coverage and Capacity in LTE Cellular Networks", pages = "1989-2004", journal = "Vehicular Technology, {IEEE} Transactions on", volume = "62", number = "5", doi = 10.1109/TVT.2013.2256441, month = Jun, year = 2013, hsb = hsb999910308392, }
Downloads
Download paper Download bibtex-file
© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.