HiperLAN2 for Vehicle-to-Vehicle Communication

The objective of the IST project MIND is to facilitate IP-based broadband services for mobile users in various operating environments. Activities within MIND concentrate on the development, optimisation and harmonisation of the appropriate layers involved. The physical (PHY) layer was chosen to base on the High Performance Radio Local Area Network type 2 standard (HiperLAN2). The work presented here demonstrates the applicability of HiperLAN2 to scenarios with increased mobility. Initially, HiperLAN2 was designed for rather static environments providing hot spot data rates of up to 54Mbps. Mitigation techniques to overcome the drawbacks of a fast fading environment are thus studied within IST-MIND. The extracted transceiver structures allow the deployment of HiperLAN2 in almost any environments currently envisaged. Particularly, the system deployment of HiperLAN2 to a Vehicle-to-Vehicle communication scenario is studied in this paper and preliminary system level performance results presented

Link residual-time estimation for VANET cross-layer design

Abstract – Traditional network design may underestimate the dependencies between different layers of the protocol stack and fail to exploit the direct coupling of physical-layer operations to the network topology. In the case of a highly dynamic network, as observed in vehicular communications, the network architecture needs to be able to optimally adapt to the changes brought on by nodes ’ mobility. In this paper we propose a crosslayer approach, where the received power metric, logged at the physical layer, can be used to produce estimates of the links’ residual lifetime. Such information is crucial for the decision processes of higher layers, such as hand-off, scheduling and routing. The method comprises of utilizing a time series based on physical-layer measurements to estimate the current state of the link and the remaining time during which the link can be used for efficient communication. Shadowing, small scale fading and limited opportunities to sample the channel make the problem challenging. The proposed algorithms are tested against simulations which depict the mobile wireless channel realistically