Distributed Adaptation Techniques for Connected Vehicles

In this PhD dissertation, we propose distributed adaptation mechanisms for connected vehicles to deal with the connectivity challenges. To understand the system behavior of the solutions for connected vehicles, we first need to characterize the operational environment. Therefore, we devised a large scale fading model for various link types, including point-to-point vehicular communications and multi-hop connected vehicles. We explored two small scale fading models to define the characteristics of multi-hop connected vehicles. Taking our research into multi-hop connected vehicles one step further, we propose selective information relaying to avoid message congestion due to redundant messages received by the relay vehicle. Results show that the proposed mechanism reduces messaging load by up to 75% without sacrificing environmental awareness. Once we define the channel characteristics, we propose a distributed congestion control algorithm to solve the messaging overhead on the channels as the next research interest of this dissertation. We propose a combined transmit power and message rate adaptation for connected vehicles. The proposed algorithm increases the environmental awareness and achieves the application requirements by considering highly dynamic network characteristics. Both power and rate adaptation mechanisms are performed jointly to avoid one result affecting the other negatively. Results prove that the proposed algorithm can increase awareness by 20% while keeping the channel load and interference at almost the same level as well as improve the average message rate by 18%. As the last step of this dissertation, distributed cooperative dynamic spectrum access technique is proposed to solve the channel overhead and the limited resources issues. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this work by using a computationally efficient numerical approach. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors. An interdisciplinary approach referred to as entropy-based weighting is used for defining the neighbor credibility. Once the vehicle accesses the channel, we propose a decision mechanism for channel switching that is inspired by the optimal flower selection process employed by bumblebees foraging. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero

Cooperative Content Dissemination on Vehicle Networks

As redes veiculares têm sido alvo de grandes avanços nos últimos anos, sobretudo devido ao crescente interesse por veículos inteligentes e autónomos que motiva investimentos avultados por parte da indústria automóvel. A inexistência de uma forma oportuna e económica de executar atualizações OTA (over-the-air) está a contribuir para o adiar do lançamento de grandes frotas de veículos inteligentes. O custo associado à transmissão de dados através de redes celulares é muito elevado e não se pode garantir que cada veículo tenha acesso a uma estação ou estacionamento com conectividade adequada em tempo útil, onde possa obter os dados esperados. Com base nestas premissas, esta tese apresenta a concepção e implementação de um protocolo cooperativo de disseminação de conteúdos que aproveita as ligações Veículo-a-Veículo (V2V) para assegurar uma distribuição de dados pela rede com custos reduzidos. Além disso, este trabalho é complementado e suportado com uma análise do desempenho do protocolo numa rede de 25 veículos.Vehicular networks have seen great advancements over the last few years, mostly due to the increased eagerness for smart and autonomous vehicles that motivate hefty investments by the automotive industry. The absence of a timely and cost-effective way to perform over-the-air (OTA) updates is contributing to defer the deployment of large fleets of connected vehicles. There is a high cost associated with transmitting data over cellular networks and it cannot be expected that every vehicle has access to a station or depot with adequate connectivity where it can get the awaited data cheaply nor that this solution happens timely enough. With this in mind, this thesis presents the design and implementation of a cooperative content dissemination protocol that takes advantage of Vehicle-to-Vehicle (V2V) communication links to distribute data across a network with reduced costs. Moreover, this work is complemented with a performance analysis of the protocol on a deployed network of 25 vehicles

Propagation modelling and resource allocation in mobile radio communications

Over the past years, ray tracing (RT) models popularity has been increasing. From the nineties, RT has been used for field prediction in environment such as indoor and urban environments. Nevertheless, with the advent of new technologies, the channel model has become decidedly more dynamic and to perform RT simulations at each discrete time instant become computationally expensive. In this thesis, a new dynamic ray tracing (DRT) approach is presented in which from a single ray tracing simulation at an initial time t0, through analytical formulas we are able to track the motion of the interaction points. The benefits that this approach bring are that Doppler frequencies and channel prediction can be derived at every time instant, without recurring to multiple RT runs and therefore shortening the computation time. DRT performance was studied on two case studies and the results shows the accuracy and the computational gain that derives from this approach. Another issue that has been addressed in this thesis is the licensed band exhaustion of some frequency bands. To deal with this problem, a novel unselfish spectrum leasing scheme in cognitive radio networks (CRNs) is proposed that offers an energy-efficient solution minimizing the environmental impact of the network. In addition, a network management architecture is introduced and resource allocation is proposed as a constrained sum energy efficiency maximization problem. System simulations demonstrate an increment in the energy efficiency of the primary users’ network compared with previously proposed algorithms