Efficient Cell Planning Method by Considering Initial Conditions

This paper focuses on cell planning method and optimal Access Point (AP) location. Cell planning can reduce the adjacent channel interference and minimize the number of AP. So an efficient cell planning method can save cost and time of systems setup. We introduce some methods, compare one another and suggest an efficient method. Existing method is considering a variety of objective functions. So their complexity makes it difficult to design wireless systems. The new method which will be suggested in this paper considering a special condition reduces a lot of calculation quantity

Оптимальная модернизация мобильных систем связи

The key aspects of optimal modernization of mobile communication systems are analyzed. The problem is shown to be reduced to the basic problem of optimal planning of such systems.Проанализированы ключевые аспекты оптимальной модернизации мобильных систем связи. Показано, что рассматриваемая проблема сводится к основной проблеме оптимального планирования упомянутых систем

Cell Planning for Wireless Local Area Network and Optimal Antenna Location

This paper focuses on cell planning method and optimal Access Point (AP) location. Cell planning can reduce the adjacent channel interference and minimize the number of AP. We introduce some methods and compare one another and suggest an efficient method. Existing method considering objective functions is very complex. The new method considers a special condition - indoor environment. So this reduces a lot of calculation quantity. Next, topic is optimal antenna location. When AP is set up, generally AP is attached to the wall. At this time, constructive and destructive effects happen because service providers choose a omni-directional antenna to save cost. This paper will show optimal antenna location to avoid destructive effect

Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach

Communication infrastructure planning is a critical design task that typically requires handling complex concepts on networking aimed at optimizing performance and resources, thus demanding high analytical and problem-solving skills to engineers. To reduce this gap, this paper describes an optimization algorithm—based on evolutionary strategy—created as an aid for decision-making prior to the real deployment of wireless LANs. The developed algorithm allows automating the design process, traditionally handmade by network technicians, in order to save time and cost by improving the WLAN arrangement. To this end, we implemented a multiobjective genetic algorithm (MOGA) with the purpose of meeting two simultaneous design objectives, namely, to minimize the number of APs while maximizing the coverage signal over a whole planning area. Such approach provides efficient and scalable solutions closer to the best network design, so that we integrated the developed algorithm into an engineering tool with the goal of modelling the behavior of WLANs in ICT infrastructures. Called WiFiSim, it allows the investigation of various complex issues concerning the design of IEEE 802.11-based WLANs, thereby facilitating design of the study and design and optimal deployment of wireless LANs through complete modelling software. As a result, we comparatively evaluated three target applications considering small, medium, and large scenarios with a previous approach developed, a monoobjective genetic algorithm

Self-Organizing Networks use cases in commercial deployments

These measurements can be obtained from different sources, but these sources are either expensive or not applicable to any network. To solve this problem, this thesis proposes a method that uses information available in any network so that the calibration of predictive maps is converted into universal without losing accuracy with respect to current methods. Furthermore, the complexity of today's networks makes them prone to failure. To save costs, operators employ network self-healing techniques so that networks are able to self-diagnose and even self-fix when possible. Among the various failures that can occur in mobile communication networks, a common case is the existence of sectors whose radiated signal has been exchanged. This issue appears during the network roll-out when engineers accidentally cross feeders of several antennas. Currently, manual methodology is used to identify this problem. Therefore, this thesis presents an automatic system to detect these cases. Finally, special attention has been paid to the computational efficiency of the algorithms developed in this thesis since they have finally been integrated into commercial tools.Ince their origins, mobile communication networks have undergone major changes imposed by the need for networks to adapt to user demand. To do this, networks have had to increase in complexity. In turn, complexity has made networks increasingly difficult to design and maintain. To mitigate the impact of network complexity, the concept of self-organizing networks (SON) emerged. Self-organized networks aim at reducing the complexity in the design and maintenance of mobile communication networks by automating processes. Thus, three major blocks in the automation of networks are identified: self-configuration, self-optimization and self-healing. This thesis contributes to the state of the art of self-organized networks through the identification and subsequent resolution of a problem in each of the three blocks into which they are divided. With the advent of 5G networks and the speeds they promise to deliver to users, new use cases have emerged. One of these use cases is known as Fixed Wireless Access. In this type of network, the last mile of fiber is replaced by broadband radio access of mobile technologies. Until now, regarding self-configuration, greenfield design methodologies for wireless networks based on mobile communication technologies are based on the premise that users have mobility characteristics. However, in fixed wireless access networks, the antennas of the users are in fixed locations. Therefore, this thesis proposes a novel methodology for finding the optimal locations were to deploy network equipment as well as the configuration of their radio parameters in Fixed Wireless Access networks. Regarding self-optimization of networks, current algorithms make use of signal maps of the cells in the network so that the changes that these maps would experience after modifying any network parameter can be estimated. In order to obtain these maps, operators use predictive models calibrated through real network measurements

Multi-objective site selection and analysis for GSM cellular network planning

Although considerable effort has been placed on developing techniques and algo rithms to create feasible cell plans, much less effort has been placed on understanding the relationship between variables and objectives. The purpose of this thesis is to improve the body of knowledge aimed at understanding the trade-offs and tensions in the selection of transmission sites and in the configuration of macro-cells for GSM and related FDMA wireless systems. The work begins by using an abstract 2-dimensional (2D) model for area coverage. A multiple objective optimisation framework is de veloped to optimise the sequential placement and configuration of downlink wireless cells. This is deployed using a range of evolutionary algorithms whose performance is compared. The framework is further tuned via a decoding mechanisms using the best performing evolutionary algorithm. The relationship between primary variables in the 2D model is analysed in detail. To improve realism, the thesis additionally addresses complexities relating to planning in 3-dimensional (3D) environments. A detailed open source static model is developed and the optimisation framework is extended to accommodate the additional model complexities and choices in algorithm design are compared. Finally, sensitivity analysis is performed to determine the relationship between objectives in the 3D model and benchmark solutions are provided