模拟到数字认知无线电：采样、检测和硬件
Analog to Digital Cognitive Radio: Sampling, Detection and Hardware
摘要：
无线通信的激增最近在频谱可用性方面产生了瓶颈。受频谱稀缺的根源不是缺乏资源而是可以解决的低效管理的观察的启发，已经考虑了频谱带的动态机会主义利用，其名称为认知无线电（CR）。该技术允许次级用户通过检测和跟踪频谱占用来访问当前空闲的频谱带。CR应用重新审视了这一传统任务，在频谱感知和检测性能、实时处理、噪声鲁棒性等方面提出了具体而严格的要求。不幸的是，常规方法不能满足通常具有非常高的奈奎斯特速率的典型信号的这些要求。最近，已经提出了几种采样方法，这些方法利用信号的先验已知结构在低于奈奎斯特速率下对它们进行采样。在这里，我们回顾了其中的一些技术，并将它们与CR背景下的频谱感知任务联系起来。然后，我们将展示如何频谱感知相关的问题可以解决在子奈奎斯特制度。首先，为了应对低信噪比，我们建议从低速率样本中恢复二阶统计量，而不是信号本身。特别是，我们考虑基于循环平稳检测，并调查CR网络，执行协作频谱感知，以克服信道效应。为了提高可用频段检测的效率，本文提出了联合频谱感知和波达方向估计的方法。在整个工作中，我们强调理论算法和它们的实际实现之间的关系。我们展示了在我们构建的原型上进行的硬件模拟，证明了CR背景下的次奈奎斯特频谱感测的可行性。
英文摘要：
The proliferation of wireless communications has recently created a bottleneck in terms of spectrum availability. Motivated by the observation that the root of the spectrum scarcity is not a lack of resources but an inefficient managing that can be solved, dynamic opportunistic exploitation of spectral bands has been considered, under the name of Cognitive Radio (CR). This technology allows secondary users to access currently idle spectral bands by detecting and tracking the spectrum occupancy. The CR application revisits this traditional task with specific and severe requirements in terms of spectrum sensing and detection performance, real-time processing, robustness to noise and more. Unfortunately, conventional methods do not satisfy these demands for typical signals, that often have very high Nyquist rates. Recently, several sampling methods have been proposed that exploit signals' a priori known structure to sample them below the Nyquist rate. Here, we review some of these techniques and tie them to the task of spectrum sensing in the context of CR. We then show how issues related to spectrum sensing can be tackled in the sub-Nyquist regime. First, to cope with low signal to noise ratios, we propose to recover second-order statistics from the low rate samples, rather than the signal itself. In particular, we consider cyclostationary based detection, and investigate CR networks that perform collaborative spectrum sensing to overcome channel effects. To enhance the efficiency of the available spectral bands detection, we present joint spectrum sensing and direction of arrival estimation methods. Throughout this work, we highlight the relation between theoretical algorithms and their practical implementation. We show hardware simulations performed on a prototype we built, demonstrating the feasibility of sub-Nyquist spectrum sensing in the context of CR.
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