A hybrid energy detection approach to spectrum sensing

S. Badrinath, V. Reddy
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引用次数: 13

Abstract

This paper introduces a hybrid energy detection approach to spectrum sensing in cognitive radio. Conventional energy detection technique (with N samples) is based on two hypotheses — i) where all N are signal samples corrupted by noise, ii) where all N are noise-only samples. Based on these two hypotheses a threshold is set for declaring a given N-sample signal as belonging to either of the two cases. This paper considers those cases which occur in practice — M samples out of N being signal corrupted with noise and the rest being noise-only, 0 ≤ M ≤ N, thus covering the conventional two hypotheses as well. The method described here, referred to as “hybrid energy detection”, proposes a combination of a 32-sample detector with a 16-sample detector which yields an improvement in performance in most such mixed signal-noise cases. The “hybrid energy detection” method requires certain thresholds to be set, in order to maximize the gain. We use simulated annealing to find those threshold values. The cost function used for simulated annealing takes into consideration the ratio of sensing time interval to transmit time interval in the secondary user.
一种用于频谱传感的混合能量检测方法
介绍了一种用于认知无线电频谱感知的混合能量检测方法。传统的能量检测技术(有N个样本)基于两个假设——i)其中所有N个都是被噪声破坏的信号样本,ii)其中所有N个都是纯噪声样本。基于这两个假设,设置了一个阈值,用于声明给定的n个样本信号属于这两种情况中的任何一种。本文考虑了实际中N个样本中有M个样本是被噪声破坏的信号,其余样本是纯噪声的情况,0≤M≤N,从而也涵盖了传统的两个假设。这里描述的方法,被称为“混合能量检测”,提出了32个样本检测器和16个样本检测器的组合,在大多数这样的混合信噪情况下,性能得到了改善。“混合能量检测”方法需要设置一定的阈值,以使增益最大化。我们使用模拟退火来找到这些阈值。用于模拟退火的代价函数考虑了二级用户感知时间间隔与传输时间间隔的比值。
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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