This ebook is for it leaders who are ready to adopt a proactive approach to optimizing their networks and who want insights into the foundations necessary to prepare their networks for tomorrow. Solving such problems resourcefully is relevant for many fields of application and has direct impact in engineering, scientific and industrial areas. Pdf selfconfiguration and selfoptimization for lte networks. A distributed newton method for network optimization. In the shortterm, bestinclass network state metrics and kpis for continuous monitoring. The network optimization experience doing the math. Continuous and discrete models, athena scientific, 1998. In cellular communications technology, selfoptimization is a process in which the systems settings are autonomously and continuously adapted to the traffic profile and the network environment in terms of topology, propagation and interference. Distribution englished01 jae ho, lee customer training center 2. We believe that many other applications of convex optimization are still waiting to be discovered. Optimization mobility robustness optimization is a self optimization technique that.
Net ork mo dels ha v e three main adv an tages o v er linear programming. Convex optimization has also found wide application in combinatorial optimization and global optimization, where it is used to. Selfoptimization of low coverage and high interference in. Network applications sdn controller network operating system openflow figure 1. Heterogeneous twotier network with hybrid deployed small cells and macrocells is a promising solution for fifth generation 5g wireless networks. The aim with them is to reduce the total cost of ownership tco by having traditionally manual tasks like design, configuration, optimization, and operation. Lte son training, selforganizing networks son training course covers all aspects of a sonenabled system including technologies. This is an extensive book on network optimization theory and algorithms, and covers in addition to the simple linear models, problems involving nonlinear cost, multicommodity flows, and integer constraints. The book offers a multitechnology approach as it will consider the implications of the different. In this paper, we proposed a selforganizing capacity and coverage. The radio network design rnd is a nphard optimization problem which consists on the maximization of the coverage of a given area while minimizing the base station bs deployment. Pdf on wide area network optimization researchgate. The book explains principles, methodologies and techniques for optimizing network performance and reliability. The manual execution of configuration, maintenance, and optimization procedures produces tremendous costs and is therefore no.
Optimization of coverage in 5g selforganizing small cell. However, with the higher and higher spectrum band used in 5g, the coverage and capacity of indoor environment is not good enough for the users increasing demand. A distributed newton method for network optimization ali jadbabaie y, asuman ozdaglarz, and michael zargham abstractmost existing work uses dual decomposition and subgradient methods to solve network optimization problems in a distributed manner, which suffer from slow convergence rate properties. Maximizes the profit of the son operator taking into account the son operators budget critical issues. Network optimization is one of the key parts in the life cycle of mobile systems. Wireless network optimization by perronfrobenius theory. Most inventory applications do not include network optimization capabilities. Similarly, manual optimization processes or fault diagnosis and cure. The separation of data plane from control plane and centralizing the intelligence simpli.
The guide starts with a foundational chapter that teaches network fundamentals. Architecture of sdn the sdn is a layered architecture which separates the data plane from control plane. Shown here is one specific set of outcomes that demonstrate a. Selfoptimization of coverage and capacity based on a fuzzy neural network with cooperative reinforcement learning. Unique in that it focuses on formulation and case studies rather than solutions procedures covering applications for pure, generalized and integer networks, equivalent formulations plus successful techniques of network models. Network models in optimization and their applications in.
Together with selfplanning and selfhealing, selfoptimization is one of the key pillars of the selforganizing networks son management paradigm. In this paper, we present an overview of a perronfrobenius theoretic framework. Introduction to network optimization l1 shortest path problems l2 the maxflow problem l3 the mincost flow problem l4 auction algorithm for mincost flow l5 network flow arguments for bounding mixing times of markov chains l6 accelerated dual. Selfoptimization of antenna tilt in mobile networks. Selfoptimization algorithms can be located in oam or enb or both of them. On the one hand, open source software and creativecommons licensing. Wireless network optimization by perronfrobenius theory chee wei tan city university of hong kong abstracta basic question in wireless networking is how to optimize the wireless network resource allocation for utility maximization and interference management. Optimization techniques in wireless networks owl summary this project will apply optimization techniques in order to analyse and design wireless link communication and wireless network communication systems, and to improve capacity bounds for such systems. Network optimization is the technology required to consider the optimal flow of products throughout the supply chain and inherent cycle stock given the tradeoffs between a host of variables including transportation modes and facility locations.
Network optimization handbook your guide to a better network. Pdf selfoptimization of coverage and capacity based on a fuzzy. Pdf with the rapid growth of mobile communications, deployment and maintenance of cellular mobile networks are becoming more and more complex, time. For secondgeneration 2g mobile networks, a series of standardized procedures have been defined for wireless network planning and optimization, while for thirdgeneration 3g. 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.
White paper self optimizing networks from machine learning 2q 2017 2 closedloop automation systems requires hyperscale virtualized instrumentation to deliver the realtime, multivendor network state. Problems whose linear program w ould ha v e ro ws and 30,000 columns can b e solv ed in a matter of seconds. Network performance and optimization guide is an essential reference for systems performance, optimization and capacity planning. Self organizing networks as radio network planning and optimization are largely separated nowadays and this causes intrinsic shortcomings like the abstraction of access technologies for network planning. However there are some challenges associated with the introduction of selfoptimization of antenna tilt in real networks which are detailed bellow. An issue that is not discussed and can be seen as suitable for future work is the interaction of self. The concept of self organizing networks son has picked up only after the.
Pdf selfoptimization of coverage and capacity based on. Opex related to manual adjustment of a given parameter set associated with a use. The recent surge in the network modeling of complex systems has set the stage for a new era in the study of fundamental and applied aspects of optimization in collective behavior. Implementation of machine learning for autonomic capabilities in. The radio network design optimization problem springerlink. Use of selforganizing networks to optimize radio access. Network ran, and has not been a part of an end toend solution. Harnessing subscribercentric optimization for the next. Lte mobile optimization a definitive guide white paper. Optimization techniques in wireless networks owl summary. Self optimization of coverage and capacity, which allows. Keywords selforganizing networks machine learning energy saving. We apply for funding for hiring one researcher and two phd students to.
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