arXiv subjects

Yipeng Liu

Publications and source records attributed to Yipeng Liu.

94 records · Page 6Linked to original sources

arXiv2010

A Robust Beamformer Based on Weighted Sparse Constraint

Applying a sparse constraint on the beam pattern has been suggested to suppress the sidelobe level of a minimum variance distortionless response (MVDR) beamformer. In this letter, we introduce a weighted sparse constraint in the beamformer design to provide a lower sidelobe level and deeper nulls for interference avoidance, as compared with a conventional MVDR beamformer. The proposed beamformer also shows improved robustness against the mismatch between the steering angle and the direction of arrival (DOA) of the desired signal, caused by imperfect estimation of DOA.

cs.IT↗

arXiv2010

Improved OMP Approach to Sparse Multi-path Channel Estimation via Adaptive Inter-atom Interference Mitigation

Since most components of sparse multi-path channel (SMPC) are zero, impulse response of SMPC can be recovered from a short training sequence. Though the ordinary orthogonal matching pursuit (OMP) algorithm provides a very fast implementation of SMPC estimation, it suffers from inter-atom interference (IAI), especially in the case of SMPC with a large delay spread and short training sequence. In this paper, an adaptive IAI mitigation method is proposed to improve the performance of SMPC estimation based on a general OMP algorithm. Unlike the ordinary OMP algorithm, a sensing dictionary is designed adaptively and posterior information is utilized efficiently to prevent false atoms from being selected due to serious IAI. Numeral experiments illustrate that the proposed general OMP algorithm based on adaptive IAI mitigation outperform both the ordinary OMP algorithm and the general OMP algorithm based on non-adaptive IAI mitigation.

cs.IT↗

arXiv2010

Power-Efficient Ultra-Wideband Waveform Design Considering Radio Channel Effects

This paper presents a power-efficient mask-constrained ultra-wideband (UWB) waveform design with radio channel effects taken into consideration. Based on a finite impulse response (FIR) filter, we develop a convex optimization model with respect to the autocorrelation of the filter coefficients to optimize the transmitted signal power spectrum, subject to a regulatory emission mask. To improve power efficiency, effects of transmitter radio frequency (RF) components are included in the optimization of the transmitter-output waveform, and radio propagation effects are considered for optimizing at the receiver. Optimum coefficients of the FIR filter are obtained through spectral factorization of their autocorrelations. Simulation results show that the proposed method is able to maximize the transmitted UWB signal power under mask constraints set by regulatory authorities, while mitigating the power loss caused by channel attenuations.

cs.IT↗

arXiv2010

Compressive Wideband Spectrum Sensing for Fixed Frequency Spectrum Allocation

Too high sampling rate is the bottleneck to wideband spectrum sensing for cognitive radio (CR). As the survey shows that the sensed signal has a sparse representation in frequency domain in the mass, compressed sensing (CS) can be used to transfer the sampling burden to the digital signal processor. An analog to information converter (AIC) can randomly sample the received signal with sub-Nyquist rate to obtained the random measurements. Considering that the static frequency spectrum allocation of primary radios means the bounds between different primary radios is known in advance, here we incorporate information of the spectrum boundaries between different primary user as a priori information to obtain a mixed l2/l1 norm denoising operator (MNDO). In the MNDO, the estimated power spectrum density (PSD) vector is divided into block sections with bounds corresponding different allocated primary radios. Different from previous standard l1-norm constraint on the whole PSD vector, a sum of the l2 norm of each section of the PSD vector is minimized to encourage the local grouping distribution while the sparse distribution in mass, while a relaxed constraint is used to improve the denoising performance. Simulation demonstrates that the proposed method outperforms standard sparse spectrum estimation in accuracy, denoising ability, etc.

cs.IT↗