Wireless Scheduling Algorithms in Complex Environments
Helga Gudmundsdottir, Eyj\'olfur I \'Asgeirsson, Marijke H. L., Bodlaender, Joseph T. Foley, Magn\'us M. Halld\'orsson, Ymir Vigfusson

TL;DR
This paper introduces a new framework using gain matrices to model complex wireless environments more accurately than traditional geometric models, validated through experiments in indoor testbeds.
Contribution
It develops a novel gain matrix-based modeling approach and a metricity parameter to better predict wireless performance in complex environments, extending existing algorithms.
Findings
Gain matrices outperform geometric models in predicting packet reception.
The metricity parameter $$ measures environmental complexity.
Multiple channels improve environment metricity and performance.
Abstract
Efficient spectrum use in wireless sensor networks through spatial reuse requires effective models of packet reception at the physical layer in the presence of interference. Despite recent progress in analytic and simulations research into worst-case behavior from interference effects, these efforts generally assume geometric path loss and isotropic transmission, assumptions which have not been borne out in experiments. Our paper aims to provide a methodology for grounding theoretical results into wireless interference in experimental reality. We develop a new framework for wireless algorithms in which distance-based path loss is replaced by an arbitrary gain matrix, typically obtained by measurements of received signal strength (RSS). Gain matrices allow for the modeling of complex environments, e.g., with obstacles and walls. We experimentally evaluate the framework in two indoors…
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Taxonomy
TopicsMobile Ad Hoc Networks · Energy Efficient Wireless Sensor Networks · Wireless Networks and Protocols
