Masters Thesis.

Added on - 20 Sep 2019

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Masters ThesisAbstract1.Abstract:2.Introduction: (5 pages) Including problem statement, motivation.3.Chapter 4: in the end of the paper, including (1 page) future research and (3 pages)conclusion.Please, all linked and according to the paper.2. INTRODUCTIONII. VEHICLE-TO-VEHICLE ADHOC NETWORKThe recent advances in ad hoc networks have allowed multiple implementation of architecturesfor vehicular networks [1]. These architectures support different requirements, and satisfydifferent constraints. When a notive is introduced to the concept of vehicular networks, all he canthink of is vehicles talking to each other. This concept is known as vehicle-to-vehicle (V2V) adhoc network, which will be the focus of this chapter.V2V network allows the direct communication between vehicles without de- pending on a fixedinfrastructure support [2]. It is simply the wireless transmission of data between motor vehicles.
The principal goal of V2V is to prevent accidents by allowing vehicles share speed data andposition data with one another over an ad hoc mesh network. V2V is expected to present a 360degree level of awareness about the surrounding to a moving vehicle [3].V2V is becoming an important part of the intelligent transport system of the United states. Datafrom vehicle-to-vehicle communication is currently being used to improve traffic managementevident in traffic lights and signs. It is expected that this technology will become a mandatorypart of the transportation system, and immensely aid in the quest for driverless-cars all acrossAmerica. The major incentive of V2V is that the technology can increase the performance ofvehivle stafety systems and help save lives. It is expected that connected vehicle technolo- gieswill provide drivers with the tools to not only survive crashes, but to avoid it altogether [4].Without the use of a trusted authority, implementing V2V raises questions about thecommunication mechanism to ensure effective connectivity, as well as address- ing the inherentsecurity challenges in this form of communication. Discussion of V2V in this chapter will be interms of the connectivity mechanism and security measures. An approach to ensuring effectiveand secured communication in V2V will be discussed.A. Proposed approachDedicated for wireless vehicular communications is the IEEE 802.11p standard where 6 out ofthe 7 available channels are used for actual communication and the last channel for controlmessages [5]. However, with the overall goal of having all communicable cars on US roads,these channels could be easily overwhelmed. Within a mile radius, there could be several carsespecially on busy roads in highly populous geographical region all expected to providetransportation intelligence through V2V communication. This introduces a requirement for avirtually unlimited available communication channel in vehicular communication [6]. Thetimeliness constraint of V2V networks must also be factored as time- critical emergencymessages cannot be delayed.Subsequently in this chapter, an evaluation of the various connectivity options available for V2Vis considered, with an approach considering the communication range, speed, tavel direction etc.Also, a trust-based security model for V2V communication is proposed.B. ConnectivityIn the context of IoV, the time to takes to fully transit emergency messages can mean thedifference between life and death. However, messages may be delayed due to a limitation in the
channel availability of the IEEE 802.11 channels, which are governed by the IEEE 802.11pstandard for wireless vehicular communications. IEEE 802.11 consists of seven channels in total.One of these acts as the common control channel while the remaining six are employed forvehicular communications [6]. As the popularity and prevalence of vehicles that cancommunicate with one another wirelessly increases, there is a strong possibility that the IEEE802.11 channel will become overwhelmed, and this could result in delays in messages andscarcity in the radio spectrum [7], [8]. As such, cognitive radio technologies could represent aviable solution by which it is possible to achieve the low latency inter-vehicle communicationsrequire while also preventing spectrum scarcity [9]. Cognitive radio is a relatively newtechnology that involves optimizing the spectrum by exploiting unutilized spectrum holes [10].The cognitive radio network typically employs three different approaches to identify and exploitunused channels: geo- location database, beacons, and spectrum sensing. Each of these methodswill be examined in more depth below:Beacons utilize signals by proliferating signals across different channels with the objective ofdetecting a free channel [11]. Beacons have been integrated in a range of different applications;for example, [12], [13] , and [14]. One area in which beacons have been particularly usefulwithin the context of IoV is through the use of signals to detect the speed, direction, and positionof other vehicles within a network. Beacons are not without their downsides. One major issuewith the use of beacons to identify unexploited channels is that their use reduces the efficiency ofthe spectrum because they rely on a high and adequate radio frequency. In addition, the signalssent and received by beacons may suffer interference from alternative sources [15].The geo-location database is a digital archive that obtains, processes, compiles, and proliferatesinformation about the spectrum band [16]. The CR system accesses the geolocation databasescheme, which contains data about the primary user systems, to identify vacant bands. When thisscheme is employed, there is no requirement for the CR users to perform spectrum sensing onthe bands; as such, in comparison to the other methods of identifying unused channels, theoverheads associated with using the geo-location database are relatively low [17]. Furthermore,as this approach does not involve any sensing errors, it is easier to protect the primary users. Toemploy this scheme effectively, there is a requirement to establish a stable connection betweenthe spectrum database and the CR users. As such, while it is relatively easy to employ thisscheme in a cellular CR system, it is more complex to employ it an ad-hoc situation because aconnection of this nature may not exist [8]. For this reason, it is unlikely that the geolocationdatabase scheme will find application in an ad-hoc CR environment.Spectrum sensing is widely considered to represent a fundamental component of a cognitive
radio network [18]. It operates by sensing the various channels that are available. As previouslydescribed, cognitive radio exploits the vacant spectrum as a means of serving a secondary user.However, this can enhance the interface between those users who are licensed to use thespectrum (the primary users) and those who are not (the secondary users) and ultimatelydiminish the service that is available to the licensed user [19]. To avoid this issue, the use ofspectrum sensing can enrich spectrum utilization without reducing the parity of the service that isavailable to licensed users [19]. In addition, secondary users can access the RF spectrum in anad-hoc manner to detect unused channels without undermining the quality of the service that isavailable to the primary users. As such, the users of unlicensed vehicles need to use spectrumsensing and evaluation to identify the idle band for opportunistic communications in IoV [20]. Itis worth employing mathematical approaches to examine the joint impacts of licensed andunlicensed user activity on the performance of the spectrum sensing approach within the contextof opportunistic communications between vehicles that are fitted with wireless communicationand spectrum sensing functionality.To prevent licensed users from suffering negative interference, secondary vehic- ular users canemploy spectrum sensing to verify whether licensed users are em- ploying their channels [21],[22]. Within the context of cognitive IoV, vehicles are frequently traveling at high speeds acrossvarious distances; as such, the network structure can rapidly change. Existing studies have beenbased on the assumption that secondary users are stationary when they are in the process ofexecuting spectrum sensing, and PUs are assumed to be passive during ad-hoc transmissions bysecondary users of the network. Within the majority of existing literature user mobility has beenexamined in non-cooperative spectrum sensing [23], cooperative spectrum sensing [24],spectrum sensing in the presence of primary user mobility [25] and spectrum sensing usingrandom way point model for secondary users where primary users were motionless [26].It is important to highlight that the contemporary sensing methods that are in use do not take intoconsideration the cumulative impact of the vehicle speed, primary users mobility, and secondaryusers sensing range while calculating the function of spectrum sensing in cognitive IoV wherethe secondary users are traveling at a speed measured in miles per hour. The most significantaspect of IoV is that the users travel in an identical direction or opposite directions in accordancewith the structure of the road [27]. Identifying the intersection between the protection range ofthe primary user and the sensing range of the secondary user and the distance between the twousers (which is directly dependent on their relative speed) plays a critical role in determiningwhether a primary user is within the sensing range. Furthermore, the dynamic spectrum accessfor ad-hoc communication is also of significance from the perspective of anticipated
transmission time, realistic per-user rate, and the anticipated transmission count.Dynamic spectrum access (DSA) represents a viable method of solving the spec- truminadequacy issues outlined above [6]. This novel area of study forecasts the evolution of CRnetworks to enhance spectrum efficiency [28]. The licensed user indisputably has the priority onthe spectrum band and, as such, takes precedence over any unlicensed user that accesses thespectrum band. DSA, which is also referred to as opportunistic spectrum access involvesconstraining the SUs such that they can only opportunistically access the spectrum holes. In thecase of the interweave DSA model, secondary users employ the cognitive radio to detect theproximate spectrum environment before an idle spectrum band is selected and the CR is switchedto that band to transmit a message [29]. DSA and CR have attracted significant attention fromresearchers in recent years due to the potential of these technologies to significantly enhance theefficiency of spectrum utilization.THE APPROACHEvery conventional vehicular network consists of a collection of licensed primary spectrum usersand unlicensed (secondary) vehicular users as shown in Fig. 1. In this approach, communicationbetween vehicles is leveraged on the dynamic spec- trum access to radio frequency channels.The secondary user is considered to have a sensing range s, and primary users with a protectionradii r. These constraints allows the consideration of the joint impact of secondary user mobilityand primary user activity to avoid harmful interference during the dynamic spectrum accessprocess.It is assumed that the primary user protection range is shorter than the sensing range of thespectrum sensor such that r < s. To determine the relative speed between a primary user and asecondary user in this approach, it is assumed that the primary user is stationary while thesecondary user is mobile. Thus, this relative speed is determined by the speed of the secondaryuser (vehicle). In reality, when a vehicular user is moving towards a primary user, the overlaptime is greater than when the vehicle is moving away from the primary user. Considering that avehicle could be moving closer or away from a primary user, the distance between them isestablished as a function of the geographical distance between them, direction of travel, sensingrange of vehicular user, primay user’s protection range and the relative speed.For a secondary user to opportunistically establish communication via a channel, the primaryuser activity for a particular location and time must be checked. This activity is known asspectrum sensing. The activities of a primary user in the channel is represented by ON and OFFstates [30]. The secpndary user detects the activity of the primary user by noise being present inthe channel. The signal received by a mobile secondary user rs(t) can be represented as a
function of two hypotheses as in (1). H0represents the presence of only noise in the channel, andH1indicating the presence of a primary user.It is important that a misdetection of primary user activity is reduced as it can cause harmfulinterference. In this vein, it can be said that reducing the misdetection probability is moreimportant than reducing false alarm (false positive) as this does not lead to harmful interferencewith primary users. An evaluation of the effect of primary user activity and secondary usermobility defined in terms of probability of misdetection of spectrum opportunities and expectedoverlapping time between static primary user and mobile secondary user is conducted. Thefollowing propositions are made based on Definition 1 and Definition 2 to formally analyzeevent A and event B.Proposition 1: For a separation distance D between a secondary user and primary user, thecondition for the primary user being inside the sensing range of secondary user is r < DS. Theprobability for the event B Pr(B)i.e. the probability that the primary user is inside the sensingrange of secondary user and the secondary user detects that the primary user is present in a givenchannel, is given as:Proposition 2: The probability of misdetection that depends on sensing range of vehicular user,protection range of primary user, velocity of vehicular user and energy detection threshold isexpressed as....Proposition 3: The expected overlap time duration between static primary userand mobile secondary user is...EvaluationTo evaluate the approach discussed so far, simulations are conducted with numerical resultsobtained used to substantiate the formal descriptions given. It is important to note that thesecondary user is assumed to be mobile, while the primary user is static in all the simulations. Itis further assumed that access points and base stations are primary users, each with its protectiverange. Secondary users are not expected to use channels actively used by primary users in itheprimary user’s protective range.To understand the effect of the sensing range on the probability of event B, a plot of the variationof Pr(B) vs the sensing range for a given primary user with a protective range r = 110 meter isdone. It is oberved that Pr(B) increases with increased sensing range as shown in Fig. 2.
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