Vehicular Dynamic Spectrum Access Research Articles

Memory Enabled Bumblebee-Based Dynamic Spectrum Access for Platooning Environments

In this paper, we propose a novel memory-enabled non-uniform sampling-based bumblebee foraging algorithm (MEB) designed for optimal channel selection in a distributed Vehicular Dynamic Spectrum Access (VDSA) framework employed in a platoon operating environment. Given how bumblebee behavioral models are designed to support adaptation in complex and highly time-varying environments, these models can be employed by connected vehicles to enable their operation within a dynamically changing network topology and support their selection of optimal channels possessing low levels of congestion to achieve high throughput. As a result, the proposed VDSA-based optimal channel selection employs fundamental concepts from the bumblebee foraging model. In the proposed approach, the Channel Busy Ratio (CBR) of all channels is computed and stored in memory to be accessed by the MEB algorithm to make the necessary channel switching decisions. Two averaging techniques, Sliding Window Average (SWA) and Exponentially Weighted Moving Average (EWMA), are employed to leverage past samples and are evaluated against the no-memory case. Due to the high variability of the environment (e.g., high velocities, changing density of vehicles on the road), we propose to calculate the CBR by employing non-uniform channel sampling allocations as well as evaluate it using both simplified numerical and realistic Vehicle-to-Vehicle (V2V) computer simulations. The numerical simulation results show that gains in the probability of the best channel selection can be achieved relative to a uniform sampling allocation approach. By utilizing memory, we observe an additional increase in the channel selection performance. Similarly, we see an increase in the probability of successful reception when utilizing the bumblebee algorithm via a system-level simulator.

On Employing a Savitzky-Golay Filtering Stage to Improve Performance of Spectrum Sensing in CR Applications Concerning VDSA Approach

Abstract In this paper, a filtering stage based on employing a Savitzky-Golay (SG) filter is proposed to be used in the spectrum sensing phase of a Cognitive Radio (CR) communication paradigm for Vehicular Dynamic Spectrum Access (VDSA). It is used to smooth the acquired spectra, which constitute the input for a spectrum sensing algorithm. The sensing phase is necessary, since VDSA is based on an opportunistic approach to the spectral resource, and the opportunities are represented by the user-free spectrum zones, to be detected through the sensing phase. Each filter typology presents peculiarities in terms of its computational cost, de-noising ability and signal shape reconstruction. The SG filtering properties are compared with those of the linear Moving Average (MA) filter, widely used in the CR framework. Important improvements are proposed.

Robust and continuous connectivity maintenance for vehicular dynamic spectrum access networks

In vehicular networks (VNs), limited transmission range of roadside units (RSUs), the high mobility of vehicles and channel status (busy or idle) cause dramatic changes in spatial and temporal behaviors of the network topology. These dynamic topological changes bring a crucial problem in terms of network connectivity maintenance. Moreover, the high number of channel switching becomes also a problem due to dynamic topology changes in VNs. These aforementioned two challenges cause expressive degradations both in the user satisfaction and wireless communication quality in the VNs. To overcome these challenges, in this paper, we propose a novel queuing theory based framework for Vehicular Dynamic Spectrum Access Networks (VDSANs). Specifically, our proposed framework uses queuing theory analytics to model the dynamic behaviors of vehicles and obtain high satisfaction ratio of vehicles. Moreover, we propose six novel dynamic channel selection algorithms to provide minimal channel switching ratio while conserving the network connectivity. The thorough evaluations show that the network connectivity can be enhanced while optimizing the channel switching with our proposed queuing theoretic VDSANs paradigm.

Feasibility analysis of vehicular dynamic spectrum access via queueing theory model

In this article, we present a feasibility analysis for performing vehicular dynamic spectrum access across vacant television channels via a queueing theory approach. In this study, we model the vacant TV channels as a multiserver, multipriority, preemptive queue. Queueing theory has been extensively employed in the open literature to model multiple access architectures as well as analyze network performance in both wired and wireless communication frameworks. On the other hand, to the best of the authors' knowledge, not many researchers have tried to resort to a queueing theory approach to analyze dynamic spectrum access networks on a system level, including the specific case of vehicular dynamic spectrum access (VDSA). Leveraging previously reported quantitative measurements obtained from a wireless spectrum measurement campaign conducted along a major interstate highway (I-90) located in Massachusetts, we modeled vacant TV channels as a multiserver queueing system in which available servers represent vacant TV channels. The servers become unavailable from the perspective of a vehicle in a time/location-varying fashion such that they represent spatially occupied TV channels. Both M/M/m and M/G/m models are employed to evaluate the probability that a vehicle finds all channels busy, as well as to derive the expected waiting times. We also consider cases where there are multiple priority classes of service requests such as a channel request by a first--responder vehicle.