In this paper, we investigate the detection performance of cooperative spectrum sensing (CSS) using energy detector in several fading scenarios. The fading environments comprise relatively less-studied Hoyt and Weibull channels in addition to the conventional Rayleigh, Rician, Nakagami-m and log-normal shadowing channels. We have presented an analytical framework for evaluating different probabilities related to spectrum sensing, i.e. missed detection, false alarm and total error due to both of them, for all the fading/shadowing models mentioned. The major theoretical contribution is, however, the derivation of closed-form expressions for probability of detection. Based on our developed framework, we present performance results of CSS under various hard decision fusion strategies such as OR rule, AND rule and Majority rule. Effects of sensing channel signal-to-noise ratio, detection threshold, fusion rules, number of cooperating cognitive radios (CRs) and fading/shadowing parameters on the sensing performance have been illustrated. The performance improvement achieved with CSS over a single CR-based sensing is depicted in terms of total error probability. Further, an optimal threshold that minimises total error probability has been indicated for all the fading/shadowing channels.

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The article presents out-of-vehicle channel measurement results in ultra-wide band spanning 3-11 GHz bandwidth using a vector network analyzer for localization applications. Experiments for different distances and different angles around the parked car are carried out. From the power delay profiles, the distance between the antennas is calculated exploiting the linear dependence of distance with line-of-sight delay peak. The coordinates of a transmitting antenna are found with the help of two receiving antennas following a two-dimensional time-of-arrival-based localization technique. A comparison of the calculated coordinates with the original exhibits an error of less than 6% which establishes the suitability of the proposed approach in locating other neighboring cars.

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The article reports vehicular channel measurements in the frequency band of 5.8 GHz for IEEE 802.11p standard. Experiments for both intra-vehicle and out-of-vehicle environments were carried out. It was observed that the large-scale variations (LSVs) of the power delay profiles (PDPs) can be best described through a two-term exponential decay model, in contrast to the linear models which are suitable for popular ultra-wideband (UWB) systems operating in the 3-to 11-GHz band. The small-scale variations (SSVs) are separated from the PDP by subtracting the LSV and characterized utilizing logistic, generalized extreme value (GEV), and normal distributions. Two sample KolmogorovSmirnov (K-S) tests validated that the logistic distribution is optimal for in-car, whereas the GEV distribution serves better for out-of-car measurements. For each measurement, the LSV trend was used to construct the respective channel impulse response (CIR), i.e., tap gains at different delays. Next, the CIR information is fed to an 802.11p simulation testbed to evaluate the bit error rate (BER) performance, following a Rician model. The BER results strongly vouch for the suitability of the protocol for in-car as well as out-of-car wireless applications in stationary environments.