Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Experimental evaluation of wireless simulation assumptions
MSWiM '04 Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
Empirical determination of channel characteristics for DSRC vehicle-to-vehicle communication
Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks
Overhaul of ieee 802.11 modeling and simulation in ns-2
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
On the accuracy of IEEE 802.11g wireless LAN simulations using OMNeT++
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
OMNeT++-Based cross-layer simulator for content transmission over wireless ad hoc networks
EURASIP Journal on Wireless Communications and Networking - Special issue on simulators and experimental testbeds design and development for wireless networks
MaxMAC: a maximally traffic-adaptive MAC protocol for wireless sensor networks
EWSN'10 Proceedings of the 7th European conference on Wireless Sensor Networks
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When performing wireless network simulations, the lack of precise channel modeling in simulator frameworks becomes a serious problem. Often deterministic models are used for packet propagation, which describe real conditions insufficiently. To close this gap we extended the OMNeT++ Mobility Framework to support probabilistic propagation models. We provide an implementation for the Log-Normal-Shadowing, Nakagami, Rayleigh and Rice wave propagation models and set up a framework that allows easy integration of additional models in future. Due to the characteristics of probabilistic radio models a fixed maximum packet propagation range encounters the problem of inaccurate simulation results as relevant events may be suppressed. On the other hand, unlimited packet propagation, which guarantees for correct simulation runs, causes unnecessary simulation overhead. In this work we present an approach to limit the event delivery to the area where the probability that the event is relevant to the simulation exceeds an adjustable threshold. In order to validate our extensions we successfully performed a detailed crosscheck with the network simulator NS-2 and run a performance evaluation and comparison.