MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh Capture

Abstract

In practical radio transmissions, channel capture is a dominating factor that affects wireless network performance. The capture effect can occur in wireless network when packets arrive with different powers. Packets with high power can effectively swamp low power packets, such that they are received successfully, when otherwise a collision would have occurred. We present a vehicular network performance-prediction model for a Rayleigh capture channel in Drive-thru Internet scenario. The model incorporates the capture effect into a 2-D Markov chain modeling the high-node mobility and distributed coordination function broadcast scheme. The performance-prediction model unveils the impacts of mobility velocity and number of vehicles on the throughput in a Rayleigh capture channel. We use a vehicular traffic flow model to predict vehicular movement on road by aggregating all vehicles into a flow. Simulation results confirm that our performance-prediction model accurately predicts the performance of traveling vehicles with Rayleigh capture channel in the Drive-thru Internet scenario. We demonstrate that using our performance-prediction model, we can obtain optimal contention window value, by which the best system throughput can be reached without wasting contention time. This is also proved by Anastasi et al.

Keywords

• Capture effect
• performance analysis
• Markov chain
• DCF
• Drive-thru Internet
• VANETs