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Spectrum sensing is a key technique in the cognitive radio. It enables secondary users to detect spectrum holes and monitor primary users' activity. However, many factors make spectrum sensing much difficult, such as very low signal-to-noise ratio, and noise uncertainty, and quite short sensing time, etc. In this paper, a uniform linear array is configured for each secondary user's receiver. The sample...
The constant modulus algorithm (CMA) has been known as blind adaptive beamforming because it requires no knowledge about the signal except that the transmitted signal waveform has a constant envelope. But in practical applications, the performance of the linearly constrained CMA is known to degrade severely in the presence of even slight signal steering vector mismatches. To account for the mismatches,...
A novel robust least squares constant modulus algorithm (LSCMA) is proposed for blind adaptive beamforming, which is based on explicit modeling of uncertainty in the desired signal array. To improve robustness, the weight vector is optimized to involve minimization of cost function, while imposing the oblique projection constraint on the weight vector and maintaining a distortionless response for...
The conventional constrained least squares constant modulus algorithm (LSCMA) can suffer significant performance degradation in the presence of the slight mismatches between the actual and assumed signal steering vectors. In this paper, to combat the mismatches, a novel robust constrained LSCMA is proposed for implementing double constraints with Taylor-series expansion and Lagrange multipliers method,...
In practical applications, mismatches between assumed and actual array responses lead to serious degradation of SINR at the array output. In this paper, we propose robust CMA based on the quadratic constraint, which improves the output performance. The quadratic constraint on the weight can provide excellent robustness to signal steering vector mismatches and to random perturbations in sensor parameters...
In practical problems, the constrained least square constant modulus algorithm (LSCMA) can suffer significant performance degradation in the presence of the slight mismatches between the actual and presumed array responses to the desired signal. In this paper, a novel robust constrained LSCMA is proposed based on explicit modeling of uncertainties in the desired signal array response. The proposed...
When the array steering vector is precisely known, adaptive beamforming is known to have resolution and interference rejection capability. However, the performance of adaptive beamforming techniques may degrade severely in the presence of mismatches between the assumed array response and the true array response. Similar types of degradation can occur when the signal array response is known exactly,...
A computationally efficient method for 2D direction-of-arrival (DOA) estimation of coherently distributed source is presented. The key idea is to construct second-order statistics calculated analytically based on the Schur-Hadamard product steering vector. So a closed form solution to 2D DOA estimation can be derived, which does not involve any eigendecomposition or singular value decomposition as...
Adaptive beamforming is known to have resolution and interference rejection capability when the array steering vector is precisely known. However, the performance of adaptive beamforming techniques may degrade severely in the presence of mismatches between the assumed array response and the true array response. In this paper, we propose a novel neural network approach to robust adaptive beamforming...
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