Abstract
This paper is concerned with the spectrum sensing problem for cognitive radio networks with correlated receiving multiple antennas in the time-varying fading channel. We first consider the scenario that all the antennas have the same noise variance and present a generalized real-valued weighted-covariance-based detection (GRWCD) method. In particular, we derive the distribution of the GRWCD statistic under the null hypothesis, which allows us to develop the theoretical decision threshold for a given false alarm probability. Besides, we derive the distribution of the GRWCD statistic under the alternative hypothesis, which enables us to provide a mathematical expression for the detection probability as well as the theoretical receiver operating characteristic. Meanwhile, we consider a more general scenario of unequal per-antenna noise variances and present a modified GRWCD method as well as the theoretical expressions of the decision threshold. The simulation results are provided to verify the accuracy of the derived results and show that the proposed two methods are capable of providing performance improvement over several advanced methods in the literature.
Highlights
Cognitive radio (CR) based communication networks have been put forward as a promising paradigm for designing the upcoming fifth-generation wireless networks, due to its unprecedented advantage in spectral efficiency [1]–[4]
When multiple antennas are available at the secondary users (SUs), the detectors can overcome the aforementioned limitations, such as the maximum-minimum eigenvalue (MME) [21], covariance absolute value (CAV) [22], covariance Frobenius norm (CFN) [22], arithmetic-to-geometric mean (AGM) [23], scaled largest eigenvalue (SLE) [24], locally most powerful invariant test (LMPIT) [25], Hadamard ratio test [26], volume-based detection (VD) [27], [28] and eigenvalue moment ratio (EMR) [29] methods have been proposed without any prior knowledge and can deliver desirable performance
Motivated by the above researches, this paper focuses on the SS problem for CR networks with correlated receiving multiple antennas in time-varying fading channels
Summary
Cognitive radio (CR) based communication networks have been put forward as a promising paradigm for designing the upcoming fifth-generation wireless networks, due to its unprecedented advantage in spectral efficiency [1]–[4]. When multiple antennas are available at the SU, the detectors can overcome the aforementioned limitations, such as the maximum-minimum eigenvalue (MME) [21], covariance absolute value (CAV) [22], covariance Frobenius norm (CFN) [22], arithmetic-to-geometric mean (AGM) [23], scaled largest eigenvalue (SLE) [24], locally most powerful invariant test (LMPIT) [25], Hadamard ratio test [26], volume-based detection (VD) [27], [28] and eigenvalue moment ratio (EMR) [29] methods have been proposed without any prior knowledge and can deliver desirable performance. Where 1/2 is the matrix square root of , and h(k) ∼ CN (0M , IM ) is an independent and identically distributed (i.i.d.) CSCG random vector
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