COOPERATIVE AND MULTI-CHANNEL ENERGY-BASED SENSING IN THE VEHICULAR ENVIRONMENT: ON THE MINIMUM TIME TO SENSE

Dusan Borota
unpublished
Thesis Director: Professor Predrag Spasojevic 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
more » ... 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 ii 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 1 kW, at 10 km distance from transmitter, with power variance higher than 3dB, sensing time of 1 msec is sufficient to obtain P MZSS = 0 :01 for range of speeds from 20 to 140 km/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. iii
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