Research Article
Deterministic Models of the Physical Layer through Signal Simulation
@ARTICLE{10.4108/eai.24-8-2015.2261106, author={Daniel Maier and Steffen Moser and Frank Slomka}, title={Deterministic Models of the Physical Layer through Signal Simulation}, journal={EAI Endorsed Transactions on Wireless Spectrum}, volume={2}, number={8}, publisher={ACM}, journal_a={WS}, year={2015}, month={8}, keywords={wireless networks, simulation, physical layer, signal simulation, software-defined radio}, doi={10.4108/eai.24-8-2015.2261106} }
- Daniel Maier
Steffen Moser
Frank Slomka
Year: 2015
Deterministic Models of the Physical Layer through Signal Simulation
WS
EAI
DOI: 10.4108/eai.24-8-2015.2261106
Abstract
Current wireless network simulators provide very detailed and deterministic models of the network protocol layers, whereas rather simple and stochastic models, based on the signal-to-noise ratio, are used for the simulation of the physical layer. Although this approach can be sufficient to study the behavior of different upper layer protocol variations, it prevents an easy alteration of the physical layer because a stochastic abstraction of the physical layer must be provided in advance. In particular, the simulation of distributed systems with physical layers that are designed to have several senders transmitting signals at the same time intentionally, is hardly possible with current approaches. A further problem of stochastic physical layer simulations is the fact that the radio channel's influence must also be carried out stochastically, which limits the advantage of accurate ray-optical channel models. We present a novel approach for the accurate simulation of the physical layer by utilizing existing software-defined radio implementations to create signals, to calculate interference and to decode signals. This technique enables us to simulate wireless networks holistically and, furthermore, we can fully exploit the possibilities of available ray-optical channel models.
Copyright © 2015 D. Maier et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.