Xuemin Yang

2D DOA Estimation of Coherently Distributed Noncircular Sources

A novel method for two-dimensional direction-of-arrival estimation of coherently distributed (CD) noncircular sources is proposed. It is the first time that we introduce the noncircularity of signal into CD model to estimate central azimuth angle and central elevation angle. Numerical simulations are also provided in contrast with the other ESPRIT-like method. The results indicate that our proposed method owns better estimation performance under both low signal-to-noise ratio and small number of array elements.

Low-complexity 2D DOA estimator of coherently distributed noncircular sources

In this communication, a novel low-complexity method for two dimensional (2D) DOA estimation of coherently distributed noncircular sources impinging on L-shape sensor array is proposed. Firstly, according to the noncircular property, the proposed method utilizes both the received signals and its conjugate to extend the received data matrix and form extended cross-covariance matrix. Then, we can obtain two approximate rotational invariance relation of extended steering vector by using selection matrices. At last, a novel ESPRIT-like method is employed to estimate the central azimuth angle and the central elevation angle. Numerical simulations are also provided in contrast with the other ESPRIT-like method. The results indicate that the proposed method owns better estimation performance and resolution probability in both low signal to noise ratio (SNR) and small number of sensors.

Parameter estimation of coherently distributed sources using sparse representation

In this paper, a new estimator of coherently distributed source employing the sparse representation technology is proposed by utilizing subspace fitting principle. The proposed method uses the eigenvalue-decomposition method on the sample covariance matrix of the sensor array received data and obtains the signal eigenvectors. We represent the generalized steering vectors of coherently distributed source containing central direction-of-arrival (DOA) and angular spread on over complete dictionaries subject to sparse constraint in subspace fitting method. Then subspace fitting problem is transformed into a sparse reconstruction problem. Finally, we use L1 norm method to solve the sparse reconstruction problem, which is optimized by the second order cone programming (SOCP) framework. Compared with the existing algorithms for coherently distributed source, such as DSPE and ESPRIT, the simulation results show that the proposed method has better resolution performance, especially in small number of snapshots.

TOA Estimation with Cross Correlation-Based Music Algorithm for Wireless Location

The location method based on TOA estimation is a research hotspot in the field of wireless location. In this paper, an new TOA estimation algorithm is proposed for providing a better estimation performance. The cross correlation matrix is employed to process channel estimation in frequency domain, which is benefit to the noise suppression. Channel estimation based on the optimal threshold is employed in the algorithm, too. Compared with the existing algorithms, the proposed algorithm is better adopted to the scenario with low SNR.

Low-complexity 2D parameter estimation of coherently distributed noncircular signals using modified propagator

In this paper, a new algorithm is proposed for two-dimensional parameter estimation of coherently distributed noncircular signals. Based on the special sensor array geometry of L-shaped uniform linear arrays, 2D angular parameters are obtained independently by using the modified propagator method. Specifically, two selection matrices are employed to obtain rotation invariance matrices under considering signal noncircularity. By making use of the rotation invariance matrices, we then obtain the central elevation and azimuth direction-of-arrivals, respectively. After that, the pair-matching of them is accomplished by searching the minimums of a cost function of the estimated 2D angular parameters. Finally, numerical results to testify the effectiveness of the proposed algorithm are provided. It is also shown that the proposed algorithm performs well in a wide signal-to-noise ratio range.

Central DOA Estimation of Incoherently Distributed Noncircular Sources with Cross-Correlation Matrix

In this communication, a new method is proposed to estimate the central direction-of-arrival (DOA) of multiple incoherently distributed noncircular sources from using the received data in two closely spaced uniform linear arrays. Both the received data vector and its conjugate are utilized to estimate the extended cross-correlation (CC) matrix. Singular value decomposition is then applied on the extended CC matrix to obtain the left and right singular vectors. Subsequently, the central DOA is estimated by using the left and right singular vectors associated with the largest singular values. The effectiveness and performance of the technique are accessed through numerical results.

Low-complexity 2D central DOA estimation of coherently distributed noncircular sources using an L-shaped antenna array

A new algorithm using modified propagator for two-dimensional (2D) central DOA estimation of coherently distributed (CD) noncircular (NC) sources impinging on the L-shaped array structured by two uniform linear arrays (ULAs) is proposed. Without the computationally intensive and time-consuming estimation of sample covariance matrix and eigendecomposition process, the proposed algorithm estimates the central azimuth and elevation direction-of-arrivals (DOAs) independently with a one-dimensional (1D) parameter estimation. The effectiveness of proposed algorithm and the theoretical analysis are verified through numerical experiments.

Parameter estimation of incoherently distributed source based on block sparse Bayesian learning

In practical array signal processing applications, the performance of DOA (direction-of-arrival) estimation methods is known to degrade severely in the presence of angular spread. In this paper, a new approach of estimating parameter via block sparse Bayesian learning is proposed for multiple incoherently distributed sources. Unlike traditional subspace based methods, the new technique makes use of a sparse representation of the received data with a perturbed overcomplete dictionary. Specifically, after using the temporal correlation between snapshots, the central DOA is estimated by using a Bayesian learning algorithm. The new method is able to mitigate the influence of angular spread, and its performance is demonstrated from numerical simulations.

Analysis and optimization of distributed antenna-aided heterogeneous networks relying on fractional frequency reuse

In distributed antenna-aided Heterogeneous Networks, macro cells (MCs) always suffer co-channel interference (CCI) from femtocells (FCs). Hence, in this paper, the downlink (DL) signal to interference ratio (SIR) of MCs and the interferential constituents are investigated. To decrease this adverse impact of FCs and achieve high spectral efficiency, a joint optimization of Particle Swarm Optimization (PSO) and optimal frequency allocation (OFA)among mobile stations (MSs) is proposed to improve both the cell planning and the frequency allocation. Simulation results show high feasibility of PSO algorithm and prove that compared with conventional static system and PSO scheme, the proposed PSO-OFA joint optimizing scheme has significant performance improvement and also achieve some degree of controllability.

A PDF/PMF Function Based Frequency Allocation Scheme in Fractional Frequency Reuse Aided OFDMA Networks

A novel frequency allocation scheme based on probability density/mass function functions (PDF/PMF) of random variables is proposed in this paper, which is capable of adjusting the balance between long term fairness and performance in fractional frequency reuse aided orthogonal frequency division multiple access based networks. This scheme divides the allocation process into two steps, including the intra-group allocation and the inter-group allocation. By adjusting the values of a set of parameters, such as rate parameters of PDF/PMF functions, and the ratio of radii of the center region and the whole cell, the presented scheme achieves a flexible adjustment between user-fairness and cell-throughput. Simulation results indicate that compared with the proportional fairness allocation and the equal rate allocation, the proposed scheme has significant performance advantage when the values of parameters are appropriate, and also has continuous controllability between “absolutely fair” and “absolutely unfair”.