Spectrum Sensing for OFDM-Based Cognitive Radio

Simin Bokharaiee, Ha H. Nguyen, E. Shwedyk
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引用次数: 5

Abstract

Abstract-Given the ever growing demand for radio spectrum,cognitive radio has recently emerged as an attractive wireless technology. Since orthogonal frequency division multiplexing (OFDM) is one of the major wideband transmission techniques, detection of OFDM signals in low signal-to-noise-ratio (SNR)scenario is an important research problem. In this paper, it is shown that the cyclic prefix correlation coefficient (CPCC) algorithm, which has been introduced as a simple and computationally efficient spectrum sensing test for OFDM signals, is a special case of the constrained generalized likelihood ratio test(GLRT) in the absence of multipath. As such, the performance of this algorithm degrades in a multipath scenario where OFDM is usually implemented. Moreover, by considering the multipath correlation in the GLRT algorithm and employing the inherent structure of OFDM signals, a simple and low complexity algorithm, called multipath-based constrained-GLRT (MP-based CGLRT)algorithm is obtained. The MP-based C-GLRT algorithm is shown to outperform the CPCC-based algorithm in a rich multipath environment. Further performance improvement can be achieved by simply combining both the CPCC-based and MPbased C-GLRT algorithms.
基于ofdm的认知无线电频谱感知
摘要:随着对无线电频谱需求的不断增长,认知无线电作为一种极具吸引力的无线技术应运而生。正交频分复用(OFDM)是主要的宽带传输技术之一,在低信噪比(SNR)场景下OFDM信号的检测是一个重要的研究问题。本文证明了循环前缀相关系数(CPCC)算法作为一种简单且计算效率高的OFDM信号频谱感知测试,是无多径情况下约束广义似然比测试(GLRT)的一种特殊情况。因此,在通常实现OFDM的多路径场景中,该算法的性能会下降。此外,考虑到GLRT算法中的多径相关性,利用OFDM信号的固有结构,得到了一种简单、低复杂度的基于多径的约束GLRT (MP-based CGLRT)算法。在丰富的多路径环境中,基于mp的C-GLRT算法优于基于cpcc的算法。进一步的性能改进可以通过简单地结合基于cpcc和基于mpp的C-GLRT算法来实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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