S.R. Lee

Low-complexity estimation of 2D DOA for coherently distributed sources

We consider the estimation of two-dimensional (azimuth and elevation) direction-of-arrival (DOA) using a pair of uniform circular arrays under a coherently distributed source model. Since the coherently distributed source is characterized by four parameters, the nominal azimuth DOA, angular extension of the azimuth DOA, nominal elevation DOA, and angular extension of the elevation DOA, the computational complexity of the parameter estimation is normally highly demanding. We propose a low-complexity estimation algorithm, called the sequential one-dimensional searching algorithm by concentrating only on the estimation of DOAs. The SOS algorithm has a basis on the eigenstructure between the steering matrix and signal subspace, and utilizes preliminary estimates obtained at a pre-processing stage. The SOS algorithm estimates the DOAs, but not the angular extensions: although the SOS algorithm does not provide estimates of angular extensions, it is useful when the angular extensions are small. Specifically, it is shown from simulation results that the SOS algorithm exhibits as good an estimation performance as the maximum likelihoood method for coherently distributed sources.

A novel detection criterion for weak m-ary signals and its application to ultrawideband multiple access systems

In this paper, we propose a novel criterion for the detection of weak m-ary signals. In the sense of minimizing the error probability, the proposed criterion is optimal when the signal strength approaches zero. Based on the proposed criterion, a detection scheme for ultrawideband multiple access systems is proposed and analyzed in the presence of impulsive interference. Numerical results show that the proposed detector requires less complexity than, and possesses almost the same performance as, the maximum likelihood detector. In impulsive interference, the proposed detector also offers significant performance improvement over the detector optimized for a Gaussian environment.

Average rate performance of two-way amplify-and-forward relaying in asymmetric fading channels

A two-way relaying (TWR) system is analyzed, where two source terminals with unequal numbers of antennas exchange data via an amplify-and-forward relay terminal with a single antenna. In the system considered herein, the link quality between the sources and relay can generally be asymmetric due to the non-identical antenna configuration, power allocation, and relay location. In such a general setup, accurate bounds on the average sum rate (ASR) are derived when beamforming or orthogonal space time block coding is employed at the sources. We show that the proposed bounds are almost indistinguishable from the exact ASR under various system configurations. It is also observed that the ASR performance of the TWR system with unequal numbers of source antennas is more sensitive to the relay location than to the power allocation.

A Novel Spectrum Sensing Scheme for the Cognitive Radio under Impulsive Noise Circumstances

In the study in [1], a novel spectrum sensing scheme has been proposed and the performance characteristics of the proposed scheme have been analyzed in Gaussian noise environment. The test statistic of the proposed scheme is the sum of one or more order statistics of the log-likelihood ratios obtained at the branches of a receiver. In this paper, the performance characteristics of the proposed scheme are addressed in impulsive noise environment. It is demonstrated that the proposed scheme provides significant performance gain and higher level of performance stability over the conventional schemes in non-Gaussian impulsive noise environment.

Performance analysis of estimation methods for incoherently distributed source number

We consider the problem of estimating the number of sources by means of a passive sensor array for distributed sources. This scenario occurs in mobile communications when local scatterers exist in the vicinity of a transmitter. Since the distributed source brings about a full rank data model, the performance of eigenstructure-based detection criteria deteriorates, especially at high signal to noise ratio (SNR). More specifically, the detection criteria overestimate the number of sources at high SNR. We propose a robust detection criterion through a pseudo-procedure which allows us to restore the rank of a signal subspace for a uniform circular array. This criterion is based on a minimum description length (MDL) representing the asymptotically consistent characteristic. We show the improved performance and the robustness of the proposed method for distributed sources.