The next D3 seminar will take place on November 14th, 13:30-14:30, room B013.
Title : “Optimized resource management in Cognitive Radio Vehicular Networks with soft and hard reliability guarantees” by Nicola Cordeschi (Sapienza University of Rome)
Abstract:
In current vehicular networks, the communication traffic flows typically generated by safety applications and routed in downlink over the available backbones are of burst-type, presenting inter-arrival gaps of non-negligible time duration that can be opportunistically exploited by Vehicular Clients (VCs). Recent studies about the mobile computation offloading in real-life cloud-assisted scenarios point out that the usage of WiFi-based traffic offloading in place of 3G-assisted one may reduce the average energy consumption of current smartphones of about 55%.
In this seminar, we focus on primary–secondary user resource-management controllers in cognitive radio (CR) vehicular networks, for Vehicle-to-Infrastructure (V2I) based access scenario, under hard and soft collision constraints, where VCs equipped with heterogeneous CR-capabilities and energy budgets (playing the role of secondary users) opportunistically exploit the time and frequency holes of the traffic flow generated by the Service Provider, and compete for acceding to the serving Roadside Units (RSUs) (the primary user of the Internet backbone), through WiFi connections. These bandwidth-demanding applications are expected to have a significant impact on the commercial success of Vehicular Communication (VC) and will contribute to accelerate its implementation and deployment. We will discuss the twofold objective of this kind of networks, i.e. the joint maximization of the aggregate access goodput of the overall network and the average per-client access rates. One of the problems of conventional approaches is that, even if they fulfill the collision probability constraints, they may incur in quite long transients, where the instantaneous collision-rate is definitely too high, completely destroying the information.
We discuss and compare MAC strategies able to take into account the energy budget, the parameters and the specific fading phenomena of the vehicular wireless channels in the optimization framework, so as to self-acquire context information about the currently available bandwidth-energy resources, and quickly adapt to the mobility-induced changes of the state of the vehicular network, even in the presence of intermittent Vehicular-to-Infrastructure connectivity. We discuss different families of controllers and derive theoretical results about their hierarchy of performances (throughput-gain, performance bounds, and not immediately intuitive situations where the more constrained controllers we propose do not present any optimality gap compared to more standard less reliable approaches). After discussing conditions of applicability and advantages of each subclass, we give some insight into probabilistic fairness constrained problems, and controllers exploiting cognitive data-fusion techniques and fully distributed implementations able to adapt to unpredictable and abrupt changes of the network statistics, without requiring any a priori knowledge of the vehicular traffic patterns.
Bio:
Nicola Cordeschi received the PhD degree in Information and Communication Engineering from the Sapienza University of Rome in 2008. He received the master degree (summa cum laude) in Communication Engineering in 2004. His Ph.D. dissertation was on the adaptive QoS Transport of Multimedia over Wireless Connections via cross layer approaches based on the Calculus of Variations. He was Fellow Researcher with the DIET Dept., Sapienza University of Rome for ten years, and Assistant Professor from 2009 to 2016 giving lectures in the topics of wireless communication, modulation and digital communication, signal processing, coding and information theory. His research activity is focused on wireless communications and deals with the design and optimization of high-performance energy-efficient transmission systems for wireless multimedia applications, distributed and scalable resource allocation and management for vehicular communications, medium access control, multi-antenna systems, cross-layer optimization via the tools of convex optimization, game theory and competitive optimality.
