Di He

Performance Characterization of a Hybrid Satellite-Terrestrial System with Co-Channel Interference over Generalized Fading Channels

The transmission of signals in a hybrid satellite-terrestrial system (HSTS) in the presence of co-channel interference (CCI) is considered in this study. Specifically, we examine the problem of amplify-and-forward (AF)-based relaying in a hybrid satellite-terrestrial link, where the relay node is operating in the presence of a dominant co-channel interferer. It is assumed that direct connection between a source node (satellite) and a destination node (terrestrial receiver) is not available due to masking by obstacles in the surrounding. The destination node is only able to receive signals from the satellite with the help of a relay node located at the ground. In the proposed HSTS, the satellite-relay channel follows the shadowed Rice fading; and the channels of interferer-relay and relay-destination links experience generalized Nakagami-m fading. For the considered AF-based HSTS, we first develop the analytical expression for the moment generating function (MGF) of the overall output signal-to-interference-plus-noise ratio (SINR). Then, based on the derived exact MGF, we derive novel expressions for the average symbol error rate (SER) of the considered HSTS for the following digital modulation techniques: M-ary phase shift keying (M-PSK), M-ary quadrature amplitude modulation (M-QAM) and M-ary pulse amplitude modulation (M-PAM). To significantly reduce the computational complexity for utility in system-level simulations, simple analytical approximation for the exact SER in the high signal-to-noise ratio (SNR) regime is presented to provide key insights. Finally, numerical results and the corresponding analysis are presented to demonstrate the effectiveness of the developed performance evaluation framework and to view the impact of CCI on the considered HSTS under varying channel conditions and with different modulation schemes.

2D DOA estimation method based on channel state information for uniform circular array

In orthogonal frequency division multiplexing (OFDM) based communication systems multiple carriers having different frequencies are used to transmit different data at the same time. Complex values that describe attenuation on different subcarriers are called channel state information (CSI). This paper describes a novel method of two dimensional (2D) direction of arrival (DOA) estimation for uniform circular array (UCA) using CSI, available in transmitted OFDM signal. Firstly, using the fact that CSI among subcarriers comprises phase shift due to DOA and Time-of-Flight (ToF) number of antennas is virtually extended. Secondly, beamspace transform is applied to UCAs array manifold for CSI smoothing to virtually extend the number of observations. Finally, multiple signal classification (MUSIC) algorithm is applied on smoothed data for 2D DOA estimation. Comprehensive results and analysis are provided to show the superior performance of the proposed algorithm compared to the previous literature.

Improved subspace direction-of-arrival estimation in unknown nonuniform noise fields

This paper improves the classic subspace DOA estimation methods to combat unknown nonuniform noise. Utilizing an approximate orthogonality between the signal subspace and a tailored eigen-space of the array covariance matrix in high signal-to-noise ratio (SNR) conditions, we modify the classic multiple signal classification (MUSIC) and root-MUSIC algorithms to be competent in unknown nonuniform noise. Compared to the MUSIC and root-MUSIC methods, the proposed methods are able to achieve significant better performance in unknown nonuniform noise environments. Simulation results show that the two proposed methods significantly outperform the MUSIC and root-MUSIC methods in the whole SNR range and approach the Cramer-Rao bound (CRB) at high SNR.

A Novel Accurate Source Number Estimation Method Based on GBSA-MDL Algorithm

Several classical source number estimation methods have been proposed in the past based on information theoretic criteria such as minimum description length (MDL). However, in most known real applications there is a scenario in which the number of sensors goes to infinity at the same speed as the number of snapshots (general asymptotic case) which yields to a blind performance for the classical MDL and results in an inaccurate source number estimation. Accordingly, in this work, the Galaxy Based Search Algorithm (GBSA) is modified and applied with the MDL criteria in order to optimize and correct the detection of source number under such sample-starving case. Simulation results show that the proposed GBSA-MDL based method gives reliable results compared to several used source number estimation methods.