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This paper presents a design of linear-phase, low-complexity, reconfigurable digital filter bank that offers independent and complete control over the bandwidth as well as the center frequency of all subbands. The proposed filter bank is designed by integrating spectral parameter approximation (SPA) technique with the modified coefficient decimation method (MCDM), referred to as SPA-MCDM-FB. The architectural...
In this paper, we will firstly show that the Cyclic Autocorrelation function (CAF) is a sparse function in the cyclic frequency domain. Then using this property we propose a new CAF estimator, using Compressed Sensing (CS) technique with OMP algorithm [1]. This estimator outperforms the classic estimator used in [2]. Furthermore, since our estimator does not need any information, we claim that it...
Based on the use of compressed sensing applied to recover the sparse cyclic autocorrelation (CA) in the cyclic frequencies domain on the one hand, and by exploiting the symmetry property of the cyclic autocorrelation on the other hand, this paper proposes a new totally blind narrow band spectrum sensing algorithm with relatively low complexity in order to detect free bands in the radio spectrum. This...
Spectrum sensing is the key function in implementing cognitive radio, which enables secondary users to identify and utilize vacant spectrum resource allocated to primary users. Recent studies have proposed four major sensing methods, including matched filter, energy, feature, and eigenvalue-based detectors. However, there are some drawbacks along with them. In this paper, we propose a hybrid architecture,...
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