Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

Ressourcenarme und dezentrale Lokalisierung autonomer Sensorknoten in Sensornetzwerken

Diese Dissertation behandelt Distanz- und Lokalisierungsverfahren in ressourcenarmen Sensornetzwerken. Den Kern der Arbeit bildet die ressourcenarme Lokalisierung von Sensorknoten. In Sensornetzwerken mit geringen Genauigkeitsanforderungen kann die einfache Schwerpunktbestimmung (CL) als Lokalisierungsverfahren eingesetzt werden. In den Randgebieten eines Netzwerkes erreicht der CL-Algorithmus jedoch nur eine sehr geringe Genauigkeit. Das neu vorgestellte Verfahren Centroid Localization with Edge Correction (CLwEC) reduziert diesen Lokalisierungsfehler bei geringfügig höherem Ressourcenaufwand deutlich. Eine weitere Verbesserung der Lokalisierung wird durch ein gewichtete Schwerpunktverfahren (WCL) erreicht.This thesis describes algorithms to determine distances and positions in resource-constrained sensor networks. In sensor networks with low accuracy requirements, node’s positions can be calculated by the centroid localization algorithm (CL) provided that all reference nodes can be configured optimal regarding the presented method. In borderlands of a sensor network, the accuracy of the centroid localization decreases enormously. The new presented algorithm centroid localization with edge correction (CLwEC) reduces this positioning error significantly and requires, in comparison the CL, only slightly increased resources. A further improvement of the positioning error was achieved by the new introduced weighted centroid localization algorithm (WCL)