GPU-Based Architectures and Their Benefit for Accurate and Efficient Wireless Network Simulations
In recent years, a trend towards the usage of physical layer models with increased accuracy can be observed within the wireless network community. This trend has several reasons. The consideration of signals - instead of packets - as the smallest unit of a wireless network simulation enables the ability to reflect complex radio propagation characteristics properly, and to study novel PHY/MAC/NET cross-layer optimizations that were not directly possible before, e.g. cognitive radio networks and interference cancelation. Yet, there is a price to pay for the increase of accuracy, namely a significant decrease of runtime performance due to computationally expensive signal processing.