Enabling Accurate Cross-Layer PHY/MAC/NET Simulation Studies of Vehicular Communication Networks

Vehicle-to-vehicle and vehicle-to-roadside communications is required for numerous applications that aim at improving traffic safety and efficiency. In this setting, however, gauging system performance through field trials can be very expensive especially when the number of studied vehicles is high. Therefore, many existing studies have been conducted using either network or physical layer simulators; both approaches are problematic. Network simulators typically abstract physical layer details (coding, modulation, radio channels, receiver algorithms, etc.) while physical layer ones do not consider overall network characteristics (topology, network traffic types, and so on). In particular, network simulators view a transmitted frame as an indivisible unit, which leads to several limitations. First, the impact of the vehicular radio channel is typically not reflected in its appropriate context. Further, interference due to frame collisions is not modeled accurately ( if at all) and, finally, the benefits of advanced signal processing techniques, such as interference cancellation, are difficult to assess. To overcome these shortcomings we have integrated a detailed physical layer simulator into the popular NS-3 network simulator. This approach aims to bridge the gap between the physical and network layer perspectives, allow for more accurate channel and physical layer models, and enable studies on cross-layer optimization. In this paper, we exemplify our approach by integrating an IEEE 802.11a and p physical layer simulator with NS-3. Further, we validate the augmented NS-3 simulator against an actual IEEE 802.11 wireless testbed and illustrate the additional value of this integration

Revamping the ieee 802.11a phy simulation models

In simulating wireless networks, modeling of the physical layer behavior is an important yet difficult task. Modeling and estimating wireless interference is receiving great research attention, and is crucial in a wireless network performance study. The implementation of physical layer capture, preamble detection, and carrier sense threshold plays an important role in successful frame reception in the presence of interference. We showed in our previous testbed study that the operations of the frame reception and the capture effect in real IEEE 802.11a systems differ from those of popular research simulators. We present our modifications of the IEEE 802.11a PHY models to the current simulators. The modifications can be summarized as follows. (i) The current simulators ’ frame reception is based only on the received signal strength. However, the real 802.11 systems can start the frame reception only when the Signal-to-Interference Ratio (SIR) is high enough to detect the preamble. (ii) Different chipset vendors implement the frame reception and capture algorithms differently, resulting in different operations for the same event. We provide different simulation models for several popular chipset vendors and show the performance differences between the models. (iii) The current simulators set the carrier sense threshold equal to the receiver sensitivity. The standard however states that it should be 20 dB higher than the receiver sensitivity. We implement our modifications to the QualNet simulator and conduct a wireless network performance study to evaluate the impact of PHY model implementation

Scalable Map Information Dissemination for Connected and Automated Vehicle Systems

Situational awareness in connected and automated vehicle (CAV) systems becomes particularly challenging in the presence of non-line of sight objects and/or objects beyond the sensing range of local onboard sensors. Despite the fact that fully autonomous driving requires the use of multiple redundant sensor systems, primarily including camera, radar, and LiDAR, the non-line of sight object detection problem still persists due to the inherent limitations of those sensing techniques. To tackle this challenge, the inter-vehicle communication system is envisioned that allows vehicles to exchange self-status updates aiming to extend their effective field of view and thus compensate for the limitations of the vehicle tracking subsystem that relies substantially on onboard sensing devices. Tracking capability in such systems can be further improved through the cooperative sharing of locally created map data instead of transmitting only self-update messages containing core basic safety message (BSM) data. In the cooperative sharing of safety messages, it is imperative to have a scalable communication protocol to ensure optimal use of the communication channel. This dissertation contributes to the analysis of the scalability issue in vehicle-to-everything (V2X) communication and then addresses the range issue of situational awareness in CAV systems by proposing a content-adaptive V2X communication architecture. To that end, we first analyze the BSM scheduling protocol standardized in the SAE J2945/1 and present large-scale scalability results obtained from a high-fidelity simulation platform to demonstrate the protocol\u27s efficacy to address the scalability issues in V2X communication. By employing a distributed opportunistic approach, the SAE J2945/1 congestion control algorithm keeps the overall offered channel load within an optimal operating range, while meeting the minimum tracking requirements set forth by upper-layer applications. This scheduling protocol allows event-triggered and vehicle-dynamics driven message transmits that further the situational awareness in a cooperative V2X context. Presented validation results of the congestion control algorithm include position tracking errors as the performance measure, with the age of communicated information as the evaluation measure. In addition, we examine the optimality of the default settings of the congestion control parameters. Comprehensive analysis and trade-off study of the control parameters reveal some areas of improvement to further the algorithm\u27s efficacy. Motivated by the effectiveness of channel congestion control mechanism, we further investigate message content and length adaptations, together with transmit rate control. Reasonably, the content of the exchanged information has a significant impact on the map accuracy in cooperative driving systems. We investigate different content control schemes for a communication architecture aimed at map sharing and evaluate their performance in terms of position tracking error. This dissertation determines that message content should be concentrated to mapped objects that are located farther away from the sender to the edge of the local sensor range. This dissertation also finds that optimized combination of message length and transmit rate ensures the optimal channel utilization for cooperative vehicular communication, which in turn improves the situational awareness of the whole system

Characterization, Avoidance and Repair of Packet Collisions in Inter-Vehicle Communication Networks

This work proposes a combined and accurate simulation of wireless channel, physical layer and networking aspects in order to bridge the gaps between the corresponding research communities. The resulting high fidelity simulations enable performance optimizations across multiple layers, and are used in the second part of this thesis to evaluate the impact of fast-fading channel characteristics on Carrier-Sense Multiple Access, and to quantify the benefit of successive interference cancellation

Characterization, Avoidance and Repair of Packet Collisions in Inter-Vehicle Communication Networks

This work proposes a combined and accurate simulation of wireless channel, physical layer and networking aspects in order to bridge the gaps between the corresponding research communities. The resulting high fidelity simulations enable performance optimizations across multiple layers, and are used in the second part of this thesis to evaluate the impact of fast-fading channel characteristics on Carrier-Sense Multiple Access, and to quantify the benefit of successive interference cancellation