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

机译：衰落建模，MIMO信道生成和用于无线通信的频谱检测。

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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.
机译：我们研究了衰落信道建模，MIMO信道生成和无线通信频谱检测。我们提出了改进的隐式半马尔可夫模型（MHSMM），用于对平坦衰落包络过程进行建模。 MHSMM将包络过程的时变统计信息合并到一个模型中，这有助于计算包络概率密度函数和自相关函数。提出了一种参数估计方案。我们通过仿真和实验数据证明了该参数估计方案，这些数据被用于IEEE 802.11和全球移动通信系统中。;各种通信和MIMO系统的多样性技术利用空间和时间分集属性来减轻无线通信的不良影响。衰落的渠道。我们提出了一种统一的方法，该方法能够生成具有所需自相关函数，互相关函数和概率密度函数（pdf）的相关平坦衰落包络过程。所提出的方法利用了高斯矢量自回归过程和逆变换采样技术。与以往的研究集中在生成同一家族的衰落信道的研究相比，该方法的新颖之处在于它能够生成异构pdf的衰落过程。演示了包括Nakagami，Rician和Rayleigh通道的示例。传感器网络已被证明在各种应用中很有用。重要的应用之一是基于多个传感器的协作检测，以提高检测性能。为了利用认知无线电中的频谱空缺，我们考虑在似然比测试（LRT）框架中通过传感器网络进行协作频谱感知。我们提供了显式算法来解决LRT融合规则，错误警报的概率以及对融合中心的检测概率。我们研究了在各种衰落信道下的单传感器检测和多个传感器的协同检测，并得出了具有已知衰落统计量的LRT的测试统计量。

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