87 research outputs found
Development of Base Transceiver Station Selection Algorithm for Collocation Arrangement
Placement of base transceiver station (BTSs) by different operators on a particular site as collocation site, so as to save cost and reduce the number of people who are at risk of radiation in BTSs located places as compared to each operator having different BTSs is the new trend in Nigeria telecommunication industries development. Collocation of base stations is much safer when compared to scattered base station telecommunication operators because of the radiations. Although the International Commission on Non-Ionizing Radiation Protection (ICNIRP) viewed that the presently existing scientific verification that prolonged contact with low frequency magnetic fields is more often than not connected with an increased danger of childhood leukaemia is too frail to form the basis for exposure guidelines. This work includes the study, analysis and proposal of a collocation scheme based on collected data of the number of BTS already sited in University of Ilorin, Ilorin, Nigeria as a case study. A drive test conducted with Transmission Environmental Monitoring System (TEMS) equipment was carried out on the existing BTSs, and a linear algorithm optimization program based on the spectral link efficiency of each BTS was developed, the output of this site optimization gives the selected number of base station sites to be used for the collocation arrangement, and the BTSs site with the best spectral link efficiency are selected in accordance with the output of the site optimization for the collocation.http://dx.doi.org/10.4314/njt.v34i3.1
Modelos de enfriamiento en recocido simulado
Se realiza una recopilación de los modelos de enfriamiento más utilizados en el algoritmo de recocido simulado. Se muestra una comparación del rendimiento de los modelos en el contexto del problema combinatorio de particionamiento de datos cuantitativos. Además, se propone un modelo empírico alternativo para acelerar el modelo geométrico, el cual es el más comúnmente utilizado en la práctica
A Genetic Algorithm with Location Intelligence Method for Energy Optimization in 5G Wireless Networks
The exponential growth in data traffic due to the modernization of smart devices has resulted in the need for a high-capacity wireless network in the future. To successfully deploy 5G network, it must be capable of handling the growth in the data traffic. The increasing amount of traffic volume puts excessive stress on the important factors of the resource allocation methods such as scalability and throughput. In this paper, we define a network planning as an optimization problem with the decision variables such as transmission power and transmitter (BS) location in 5G networks. The decision variables lent themselves to interesting implementation using several heuristic approaches, such as differential evolution (DE) algorithm and Real-coded Genetic Algorithm (RGA). The key contribution of this paper is that we modified RGA-based method to find the optimal configuration of BSs not only by just offering an optimal coverage of underutilized BSs but also by optimizing the amounts of power consumption. A comparison is also carried out to evaluate the performance of the conventional approach of DE and standard RGA with our modified RGA approach. The experimental results showed that our modified RGA can find the optimal configuration of 5G/LTE network planning problems, which is better performed than DE and standard RGA
Self-optimization of pilot power in enterprise femtocells using multi objective heuristic
Deployment of a large number of femtocells to jointly provide coverage in an enterprise environment raises critical challenges especially in future self-organizing networks which rely on plug-and-play techniques for configuration. This paper proposes a multi-objective heuristic based on a genetic algorithm for a centralized self-optimizing network containing a group of UMTS femtocells. In order to optimize the network coverage in terms of handled load, coverage gaps, and overlaps, the algorithm provides a dynamic update of the downlink pilot powers of the deployed femtocells. The results demonstrate that the algorithm can effectively optimize the coverage based on the current statistics of the global traffic distribution and the levels of interference between neighboring femtocells. The algorithm was also compared with the fixed pilot power scheme. The results show over fifty percent reduction in pilot power pollution and a significant enhancement in network performance. Finally, for a given traffic distribution, the solution quality and the efficiency of the described algorithm were evaluated by comparing the results generated by an exhaustive search with the same pilot power configuration
Acoustic Sensor Planning for Gunshot Location in National Parks: A Pareto Front Approach
In this paper, we propose a solution for gunshot location in national parks. In Spain there are agencies such as SEPRONA that fight against poaching with considerable success. The DiANa project, which is endorsed by Cabaneros National Park and the SEPRONA service, proposes a system to automatically detect and locate gunshots. This work presents its technical aspects related to network design and planning. The system consists of a network of acoustic sensors that locate gunshots by hyperbolic multi-lateration estimation. The differences in sound time arrivals allow the computation of a low error estimator of gunshot location. The accuracy of this method depends on tight sensor clock synchronization, which an ad-hoc time synchronization protocol provides. On the other hand, since the areas under surveillance are wide, and electric power is scarce, it is necessary to maximize detection coverage and minimize system cost at the same time. Therefore, sensor network planning has two targets, i.e., coverage and cost. We model planning as an unconstrained problem with two objective functions. We determine a set of candidate solutions of interest by combining a derivative-free descent method we have recently proposed with a Pareto front approach. The results are clearly superior to random seeding in a realistic simulation scenario
Metaheurísticas aplicadas a la optimización de cobertura de señales de radio frecuencia con un modelo de propagación adaptable
Desde el surgimiento de las comunicaciones inalámbricas la selección de un conjunto de puntos geográficos que permitan una cobertura óptima de una señal ha sido una tarea crítica. El costo de los equipamientos para brindar el servicio con la calidad adecuada es elevado, por lo tanto minimizar su cantidad es fundamental. A este problema se lo denomina diseño de la red de radio (RND) [1]. Los métodos analíticos fueron las primeras herramientas para resolver este problema, donde se intenta predecir el valor de nivel de señal en diferentes escenarios de terreno. El RND es un problema NP – duro de optimización, por lo tanto, es factible de ser tratado con metaheurísticas. El objetivo de esta línea de investigación es realizar el análisis, estudio e implementación de diferentes metaheurísticas utilizando un modelo de propagación de radio frecuencia real en la resolución del problema de localización de antenas para la distribución de servicios inalámbricos.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI
Metaheurísticas aplicadas a la optimización de cobertura de señales de radio frecuencia con un modelo de propagación adaptable
Desde el surgimiento de las comunicaciones inalámbricas la selección de un conjunto de puntos geográficos que permitan una cobertura óptima de una señal ha sido una tarea crítica. El costo de los equipamientos para brindar el servicio con la calidad adecuada es elevado, por lo tanto minimizar su cantidad es fundamental. A este problema se lo denomina diseño de la red de radio (RND) [1]. Los métodos analíticos fueron las primeras herramientas para resolver este problema, donde se intenta predecir el valor de nivel de señal en diferentes escenarios de terreno. El RND es un problema NP – duro de optimización, por lo tanto, es factible de ser tratado con metaheurísticas. El objetivo de esta línea de investigación es realizar el análisis, estudio e implementación de diferentes metaheurísticas utilizando un modelo de propagación de radio frecuencia real en la resolución del problema de localización de antenas para la distribución de servicios inalámbricos.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI
Metaheurísticas aplicadas a la optimización de cobertura de señales de radio frecuencia con un modelo de propagación adaptable
Desde el surgimiento de las comunicaciones inalámbricas la selección de un conjunto de puntos geográficos que permitan una cobertura óptima de una señal ha sido una tarea crítica. El costo de los equipamientos para brindar el servicio con la calidad adecuada es elevado, por lo tanto minimizar su cantidad es fundamental. A este problema se lo denomina diseño de la red de radio (RND) [1]. Los métodos analíticos fueron las primeras herramientas para resolver este problema, donde se intenta predecir el valor de nivel de señal en diferentes escenarios de terreno. El RND es un problema NP – duro de optimización, por lo tanto, es factible de ser tratado con metaheurísticas. El objetivo de esta línea de investigación es realizar el análisis, estudio e implementación de diferentes metaheurísticas utilizando un modelo de propagación de radio frecuencia real en la resolución del problema de localización de antenas para la distribución de servicios inalámbricos.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI
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