Text

theses

Vehicular networking has significant potential to enable diverse range of applications, including safety and convenience. As the number of vehicles and applications using wireless spectrum grow, one can expect to see a shortage of either spatially or temporally available spectrum. In this thesis, we advocate that dynamic spectrum access for vehicles be the first step towards solving the spectrum shortage. For this, vehicles must be able to sense the availability of spectrum before attempting to transmit. The existence of other transmitters should be detected in order not to cause or experience interference. However, spectrum sensing in vehicular environments is a challenging task due to mobility, shadowing and other factors that govern vehicular environments. Therefore, spectrum sensing by a single vehicle may not be able to provide accurate information about the spectrum vacancies. Cooperative spectrum sensing, on the other hand, uses spatial diversity and can be employed to overcome the limitations associated with a single sensor/vehicle. Moreover, spectrum sensing in vehicular environments is challenged by mobility of sensors and reflectors causing significant variations in received signal power. Signal power variations over time were not included in sensing system models dealing with wide spectrum sensing. In the first part of this thesis we investigate cooperative spectrum sensing performance in a vehicular environment for sensing signals transmitted from i) a roadside infrastructure and ii) radios located on other vehicles, by using energy-based detection of a transmitted pilot tone as an example. Our goal is to characterize the limits on detection speed and reliability of simple hard and soft cooperative energy-based schemes for this environment. We show how cooperation reduces sensing time by a factor of five in an AWGN channel. The cooperative sensing time reduction is far more significant in a vehicular environment with fading and shadowing. Finally, we illustrate how infrastructure-to-vehicle scenario favors soft equal gain combining while vehicle-to-vehicle scenario favors hard fusion OR rule. In the second part of this thesis we propose a sensing system model for wide band spectrum sensing that encompasses signal power variations over time. Then we propose to use Maximum Likelihood (ML) channel occupancy detection to determine spectrum sub-band activity vector. We are using adjacent lane traffic channel model with set of parameters validated in Winlab experiments, and focus on determining sensing time needed to achieve certain sensing performance. We focus on NTSC TV spectrum and show how using energy-based ML channel occupancy detector of three adjacent NTSC channels, with transmit power of 1kW, at 10km distance from transmitter, with power variance higher than 3dB, sensing time of 1msec is sufficient to obtain PMISS = 0.01 for range of speeds from 20 to 140km/h. Moreover, since we use ML which minimizes overall probability of error when all activity vectors are equally probable, this work provides not only a sensing approach but an assessment of how well any other technique may perform in a mobile environment.

ETD_3707

M.S.

Includes bibliographical references

by Dušan Borota

http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000064047

doi:10.7282/T3J67FZQ

ETD graduate

The author owns the copyright to this work.

446976

windows xp

ETD

application/pdf

application/x-tar

1505280

6300f27bc6ce0c4b6ac8f1ac73ef30822167a552