Fading modeling, MIMO channel generation, and spectrum detection for wireless communications

We investigate the fading channel modelling, MIMO channel generation, and spectrum detection for wireless communications. We propose the modified hidden semi-Markov model (MHSMM) for modeling the flat fading envelope process. The MHSMM incorporate the time-variant statistics of the envelope process in a single model, which facilitates computations of the envelope probability density function and the autocorrelation function. A parameter estimation scheme is proposed. We demonstrate this parameter estimation scheme by simulated and experimental data, which are used in the IEEE 802.11 and the Global System for Mobile communication system.;Diversity techniques for various communication and MIMO systems exploit the spatial and temporal diversity attributes to mitigate the ill effects of the fading channels. We propose a unified approach capable of generating correlated flat-fading envelope processes with the desired auto-correlation functions, cross-correlation functions, and probability density functions (pdfs). The proposed approach utilizes the Gaussian vector autoregressive process and the inverse transform sampling techniques. Comparing to the past research focusing on generating fading channels of the same family, the novelty of the proposed approach is its capability to generate fading processes of heterogeneous pdfs. Examples including Nakagami, Rician, and Rayleigh channels are demonstrated.;Sensor networks have been shown to be useful in diverse applications. One of the important applications is the collaborative detection based on multiple sensors to increase the detection performance. To exploit the spectrum vacancies in cognitive radios, we consider the collaborative spectrum sensing by sensor networks in the likelihood ratio test (LRT) frameworks. We provide explicit algorithms to solve the LRT fusion rules, the probability of false alarm, and the probability of detection for the fusion center. We investigate the single-sensor detection and collaborative detections of multiple sensors under various fading channels, and derive testing statistics of the LRT with known fading statistics.