With the popularization of machine learning (ML) techniques and the increased chipset's performance, the application of ML to pedestrian localization systems has received significant attention in the last years. Several survey papers have attempted to provide a state-of-the-art overview, but they usually limit their scope to a particular type of positioning system or technology. In addition, they are written from the point of view of ML techniques and their practice, not from the point of view of the localization system and the specific problems that ML techniques can help to solve. This article is intended to offer a comprehensive state-of-the-art survey of the ML techniques that have been adopted over the last ten years to improve the performance of pedestrian localization systems, addressing the applicability of ML techniques in this domain, along with the main localization strategies. It concludes by indicating the underlying open issues and challenges associated with the existing systems, and possible future directions in which ML techniques could improve the performance of pedestrian localization systems. Among other open issues, most previous authors have focused their attention on position estimation accuracy, which wastes the potential of ML techniques to improve other performance parameters (e.g., response time, computational complexity, robustness, scalability or energy efficiency). This study shows that there is a strong trend towards the application of supervised learning. Consequently, there are many potential research opportunities in the use of other learning types, such as unsupervised and reinforcement learning, to improve the performance of pedestrian localization systems.

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KEY WORDS RESUMENDescubrimiento e interacción de servicios móviles ubicuos utilizando Bluetooth y Wifi

1 Resumen-La ubicuidad y el amplio despliegue de redes inalámbricas de área local (WLAN) han aumentado el riesgo inherente de interferencia. En numerosos estudios se ha demostrado que el control de potencia es una alternativa eficiente para hacer frente a esta situación y una técnica sobresaliente para realizar control de potencia es la teoría de juegos (GT). Sin embargo, la investigación en este campo se ha enfocado en desarrollos teóricos y simulación a nivel de sistema dada la complejidad de implementar control de potencia en un entorno real. Este artículo presenta la implementación de un algoritmo de control de potencia basado en teoría de juegos en redes WLAN, específicamente en el estándar IEEE 802.11 a través de plataformas de radio definidas por software (SDR, Software Defined Radio) y hardware reconfigurable. Los resultados demuestran que el algoritmo aumenta significativamente el ahorro de energía y la eficiencia energética de las STA y disminuye la interferencia. Esta reducción de interferencia mejora el rendimiento general de la red, disminuyendo la FER y aumentando la velocidad de datos ___________________________________ 1 Producto derivado del proyecto de investigación "Implementación de un algoritmo de control de potencia basado en teoría de juegos en redes WLAN". Presentado por el Grupo de Radio