Cognitive radio-enabled Internet of Vehicles (IoVs): a cooperative spectrum sensing and allocation for vehicular communication

Internet of Things (IoTs) era is expected to empower all aspects of Intelligent Transportation System (ITS) to improve transport safety and reduce road accidents. US Federal Communication Commission (FCC) officially allocated 75MHz spectrum in the 5.9GHz band to support vehicular communication which many studies have found insufficient. In this paper, we studied the application of Cognitive Radio (CR) technology to IoVs in order to increase the spectrum resource opportunities available for vehicular communication, especially when the officially allocated 75MHz spectrum in 5.9GHz band is not enough due to high demands as a result of increasing number of connected vehicles as already foreseen in the near era of IoTs. We proposed a novel CR Assisted Vehicular NETwork (CRAVNET) framework which empowers CR enabled vehicles to make opportunistic usage of licensed spectrum bands on the highways. We also developed a novel co-operative three-state spectrum sensing and allocation model which makes CR vehicular secondary units (SUs) aware of additional spectrum resources opportunities on their current and future positions and applies optimal sensing node allocation algorithm to guarantee timely acquisition of the available channels within a limited sensing time. The results of the theoretical analyses and simulation experiments have demonstrated that the proposed model can significantly improve the performance of a cooperative spectrum sensing and provide vehicles with additional spectrum opportunities without harmful interference against the Primary Users (PUs) activities

Cooperative and fair MAC protocols for cognitive radio ad-hoc networks

A secondary user (SU) in multichannel cognitive radio ad hoc network (CRAHN) has a limited transmission range, which may raise a hidden multichannel sensing problem. In addition, CRAHNs can be deployed ubiquitously, and SUs from any CRAHNs could co-exist utilizing the spectrum. This situation leads to the fairness issue of spectrum resource sharing between the SUs. Both cooperative and fairness issues are important to CRAHN performance. In this paper, a cooperative and a non-cooperative multichannel (MC)-MAC protocol is proposed. In order to address the fairness issue, a fair multichannel (FMC)-MAC protocol for CRAHN is proposed, which orientates to the fairness in resource sharing. In this FMC-MAC, the SU keeps the current backoff (CB) counter when a PU appears to claim the intended channel. These proposed MAC protocols are simulated using NS2 and compared with other protocols. In addition, a mathematical model using Markov chain is constructed for FMC-MAC and the performance measures are derived. From results, the MC-MAC protocol has enhanced the network utilization and the cooperative scheme has significantly enhanced the packet delivery ratio and decreased the end-to-end delay of SUs in high traffic. The cooperative protocol enhances packet delivery ratio up to 15 % and decreases end-to-end delay down to 32 %, compared to the non-cooperative one. The FMC-MAC protocol with other two existing protocols. From the comparison results, a higher fairness has been shown by FMC-MAC CB while still maintaining a high throughput

Smart Sensing and Performance Analysis for Cognitive Radio Networks

Static spectrum access policy has resulted in spectrum scarcity as well as low spectrum utility in today\u27s wireless communications. To utilize the limited spectrum more efficiently, cognitive radio networks have been considered a promising paradigm for future network. Due to the unique features of cognitive radio technology, cognitive radio networks not only raise new challenges, but also bring several fundamental problems back to the focus of researchers. So far, a number of problems in cognitive radio networks have remained unsolved over the past decade. The work presented in this dissertation attempts to fill some of the gaps in the research area of cognitive radio networks. It focuses primarily on spectrum sensing and performance analysis in two architectures: a single cognitive radio network and multiple co-existing cognitive radio networks. Firstly, a single cognitive radio network with one primary user is considered. A weighted cooperative spectrum sensing framework is designed, to increase the spectrum sensing accuracy. After studying the architecture of a single cognitive radio network, attention is shifted to co-existing multiple cognitive radio networks. The weakness of the conventional two-state sensing model is pointed out in this architecture. To solve the problem, a smart sensing model which consists of three states is designed. Accordingly, a method for a two-stage detection procedure is developed to accurately detect each state of the three. In the first stage, energy detection is employed to identify whether a channel is idle or occupied. If the channel is occupied, received signal is further analyzed at the second stage to determine whether the signal originates from a primary user or an secondary user. For the second stage, a statistical model is developed, which is used for distance estimation. The false alarm and miss detection probabilities for the spectrum sensing technology are theoretically analyzed. Then, how to use smart sensing, coupled with a designed media access control protocol, to achieve fairness among multiple CRNs is thoroughly investigated. The media access control protocol fully takes the PU activity into account. Afterwards, the significant performance metrics including throughput and fairness are carefully studied. In terms of fairness, the fairness dynamics from a micro-level to macro-level is evaluated among secondary users from multiple cognitive radio networks. The fundamental distinctions between the two-state model and the three-state sensing model are also addressed. Lastly, the delay performance of a cognitive radio network supporting heterogeneous traffic is examined. Various delay requirements over the packets from secondary users are fully considered. Specifically, the packets from secondary users are classified into either delay-sensitive packets or delay-insensitive packets. Moreover, a novel relative priority strategy is designed between these two types of traffic by proposing a transmission window strategy. The delay performance of both a single-primary user scenario and a multiple-primary user scenario is thoroughly investigated by employing queueing theory

Qualité de service dans des environnements réseaux mobiles, contraints et hétérogènes

Les télécommunications sans fil ont connu ces dernières années un immense succès à tel point que le spectre des fréquences est désormais surchargé et nécessite la disponibilité de nouvelles ressources. Pour répondre à ce besoin, des techniques de réutilisation dynamique du spectre ont alors vu le jour sous la dénomination de radio cognitive. Elles consistent à partager de manière opportuniste et efficace certaines fréquences ayant été initialement allouées à d'autres systèmes. Cette thèse se place dans le contexte de réseaux sans fil tactiques hétérogènes comportant des segments de radios cognitives. La difficulté provient alors de la garantie de qualité de service de bout en bout : respect du débit négocié, du délai et de la gigue. Nous nous sommes tout d'abord intéressés au contrôle d'admission dans ce type de réseaux en proposant une méthode de calcul de bande passante résiduelle de bout en bout s'appuyant sur un algorithme de complexité polynomiale et pouvant être implanté de manière distribuée. Nous nous sommes ensuite concentrés sur le routage en proposant une nouvelle métrique tenant compte des particularités de ce type de réseaux. Enfin, nous nous focalisons sur la thématique du routage à contraintes multiples en étudiant et implantant en environnement réel des algorithmes d'approximation proposés dans la littérature. ABSTRACT : The unprecedented success of wireless telecommunication systems has resulted in the wireless spectrum becoming a scarce resource. Cognitive Radio systems have been proposed as the enabling technology allowing unlicensed equipments to opportunistically access the licensed spectrum when not in use by the licensed users. The focus of this thesis is on heterogeneous tactical networks deploying cognitive radios in parts or in their entirety. Such networks can be organized in multiple sub-networks, each characterized by a specific topology, medium access scheme and spectrum access policy. As a result, providing end-to-end Quality of Service guarantees in terms of bandwidth, delay and jitter, emerges as a key challenge. We first address the admission control in multi-hop cognitive radio networks and propose a polynomial time algorithm that can be implemented in a distributed fashion for estimating the end-to-end bandwidth. Then, we focus on routing and propose a new metric that takes into account the specifics of such networks. Finally, as quality of service requirements can be expressed using multiple metrics, we turn our attention to multi-constrained routing and implement on a real testbed low complexity approximation algorithms