Throughout the history of wireless communications, spatial antenna diversity has been important in improving the radio link between wireless users. Historically, microscopic antenna diversity has been used to reduce the fading seen by a radio receiver, whereas macroscopic diversity provides multiple listening posts to ensure that mobile communication links remain intact over a wide geographic area. In recent years, the concepts of spatial diversity have been expanded to build foundations for emerging technologies, such as smart (adaptive) antennas and position location systems. Smart antennas hold great promise for increasing the capacity of wireless communications because they radiate and receive energy only in the intended directions, thereby greatly reducing interference. To properly design, analyze, and implement smart antennas and to exploit spatial processing in emerging wireless systems, accurate radio channel models that incorporate spatial characteristics are necessary. In this tutorial, we review the key concepts in spatial channel modeling and present emerging approaches. We also review the research issues in developing and using spatial channel models for adaptive antennas.

Cognitive radio (CR) is viewed as a possible solution to the problem of radio spectrum congestion. The CR technique utilizes a temporarily unoccupied licensed band. Before investigating the technical and political implications of CR, it is necessary to know to what extent the licensed bands are temporally unoccupied. This paper describes a spectral occupancy measurement campaign conducted in the frequency range between 806 MHz and 2750 MHz in urban Auckland, New Zealand. The purpose of the measurement is to identify potential spectral opportunities for CR.Statistical analysis of the measurement results are presented in the form of noise distributions, signal amplitude probability distributions, and spectral occupancy rates as percentages of time. These analyses indicate that, on average, the actual spectral usage in this band is only about 6.2%. Point-to-point links and some mobile uplink channels are identified as the most probable candidates for future CR operations. These results suggest that CR could bring significant gains in spectral usage. These results also imply that, in order to provide a reliable detection of the primary signal, cooperative sensing techniques may be necessary to mitigate various wireless channel effects.

Modifying the indoor wireless physical propagation environment to reduce the interference level was investigated and demonstrated in this research. A common office partition wall (that was in the main propagation path) was transformed into a frequency-selective (FS) wall by attaching a custom-designed band-stop frequency-selective surface (FSS) as a cover on the wall surface. In-situ measurements showed that this frequency-selective wall filtered out signals operating at 5.4-6.0 GHz (IEEE 802.1 Ia) by an additional attenuation of 10-15 dB compared to the unmodified wall, for incident angles ranging from 0°-550 in the azimuth plane and 0°-200 in the elevation plane. An attenuation of 10-15 dB in signal strength in the stop band is considered to be significant and beneficial in interference reduction, whereas in the pass-band region (such as 1.8 GHz for cellular telephones), signals experienced only marginally more attenuation than that through the unmodified wall. Results also suggest that the interactions between the FSS and the wall surface can be minimized with an appropriate FSS design, which leads to a feasible and practical product solution: frequency-selective wallpapers. In addition, installation issues, such as misalignment of FSS sheets on the wall, were also examined.

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Radio Frequency (RF) fingerprinting is a technique, where a transmitter is identified from its electromagnetic emission. Most existing RF fingerprinting techniques have been evaluated with high-end receivers and promising classification results have been reported in the literature. However, the realization of RF fingerprinting in todays low-end (i.e. low cost) portable devices requires the validation of the existing RF fingerprinting techniques with low-end receivers. This contribution analyzes the performance of RF fingerprinting for low-end receivers. Experiments are performed for three transmitters and signals are captured with one high-end receiver and three low-end receivers using Universal Software Radio Peripheral (USRP). It is found that the classification accuracy of RF fingerprinting varies for different low-end receivers. Results show that low-end receivers provide good classification results at high receiver SNR but high receiver SNR is rare in a typical wireless communication environment. Whereas high-end receiver performs well even at low SNR.