Soohong Kim

Modeling and analysis of the dynamic location registration and paging in microcellular systems

A 0-1 integer programming model is considered to determine the most appropriate dynamic location registration (LR) area of each subscriber in microcellular systems. The minimization model of the LR area updating and paging signal costs is examined. The model is based on the subscriber characteristics, such as the call arrival rate and the velocity, as well as the regional information. The control channel blocking probabilities are considered as constraints to meet the service level of subscribers. A dynamic scheme which adaptively updates the size and shape of the LR area is developed by solving the minimization problem. Paging and location updating procedures are presented based on the dynamic procedure. The superiority of the proposed scheme is demonstrated with various computational results.

Position tracking of mobiles in a cellular radio network using the constrained bootstrap filter

We propose a new method for tracking a mobile by monitoring the signal powers of the mobile transmitter measured at several base stations. The signal power measurement at a base station, which sometimes called a power map, is a nonlinear (empirical) function of the position of a mobile. We propose to use the Bayesian bootstrap filtering approach to cope with the nonlinearity, assuming that the mobile is vehicle-mounted so that the movement of the mobile is confined in a road.

Satellite orbit determination using a magnetometer-based bootstrap filter

A Bayesian bootstrap filtering approach is applied to the low Earth orbit (LEO) satellite orbit determination problem. The filter uses the magnitude of the magnetic field vector as measurements. Simulation results for the bootstrap filter demonstrate our algorithm rapidly converges to the true orbital parameters even in the presence of large initial position errors.

Finding user position location using the Doppler information in satellite CDMA systems

This paper presents a new method for determining the position of a ground mobile using synthetic aperture radar (SAR) signal processing techniques in the low Earth orbit (LEO) communication satellite. The received signal in the satellite contains the information on the Doppler frequency shift resulting from the relative motion between the satellite and a mobile transmitter over observation interval as measurements. The position of the ground mobile can be obtained by processing the history of Doppler frequencies coherently. Simulation results demonstrating the capability of the proposed position determination method in satellite CDMA communication links are presented.

Blind space-time channel estimation of spread-spectrum using the minimum variance approach

In a mobile radio channel, direct sequence-code division multiple access (DS-CDMA) signals suffer from multiple access interference (MAI) and the multipath-induced delay spread. In this paper, we propose a new blind space-time minimum variance (MV) algorithm for estimating the angle of arrival (AOA) and the time delay, jointly using an antenna array. The proposed algorithm is termed to be blind because it requires the spreading code of the desired signal only. Simulation results show that the proposed method can accurately estimate the channel parameters, and is near-far resistant, even in severe MAI condition.

SAR imaging using the Capon estimator in the 2D subarray processing framework

We develop a 2D subarray processing technique as an extension of 1D subarray processing to form the image of an inverse synthetic aperture radar (ISAR). By using the 2D processing based on the Capons spectral estimation method, a high resolution image can be obtained as compared with the conventional Fourier transform and the 1D subarray based method. Our method minimizes the mean output power as much as possible to minimize the interference energy, while the desired scatterers energy is preserved by using the constraint. Some simulation results are given to demonstrate the performance of the proposed method.

Minimum variance space-time CDMA receiver algorithms based on URV decomposition

A minimum variance space-time (MVST) receiver with an antenna array has recently been proposed as a relatively simple method for designing blind multiuser receivers for code division multiple access (CDMA) systems. For time-varying CDMA systems, it is necessary to update the response vector, which is used to construct the receiver algorithm, of the MV receiver for each symbol interval. In this paper, we propose a new MVST receiver whose the response vector is updated based on the rank-revealing URV-decomposition rather than the eigen decomposition or singular value decomposition (SVD) used in previous MVST receivers. We demonstrate its performance through simulation in varying the number of multipaths and the Rayleigh fading parameters. It is found that the URV-decomposition based MVST receiver is effective for the time-varying CDMA signal, and achieves considerable computational savings.

A new space-time minimum variance receiver for CDMA systems and its performance analysis

We propose a new space-time minimum variance (MV) receiver with an antenna array for asynchronous code division multiple access (CDMA) systems. According to our simulation study, the proposed receiver shows superior performance to the single antenna MV receiver even in the presence of a non-zero angular spread. Furthermore, the performance of the proposed algorithm is insensitive to the degree of the angular spread or the spacing between antenna elements.

Bayesian bootstrap filtering for the LEO satellite orbit determination

This paper presents a new Bayesian bootstrap filtering approach for the low Earth orbit (LEO) satellite orbit determination using magnetometer measurements. To overcome the divergence problem of the extended Kalman filter (EKF), a hybrid bootstrap filter is proposed. The filters uses the magnitude of the magnetic field vector as measurements, and does not need the attitude information of the satellite. According to our simulation study our algorithm converges rapidly to the arc orbital parameters even in the presence of large initial position errors, and attains a few tens of kilometers of the position estimation error.

Comparison of the channel equalizers using the inverse filter, the H/sup 2/ filter and the H/sup /spl infin// filter

An H/sup /spl infin// optimized equalizer is presented to realize an optimal causal and stable equalizer of the single-channel equalization problem in the frequency domain. The proposed algorithm achieves intersymbol interference cancellation and noise attenuation in the view point of H/sup /spl infin// optimization. The communication system usually suffers some uncertainties of the channel parameter and the statistics of noise. Our algorithm is robust while the channel characteristics and the statistics of inputs and external. Noise are uncertain with a bound. Moreover, while the conventional H/sup /spl infin// approach is to minimize a peak error gain over the entire range, we propose a modified H/sup /spl infin// equalizer to emphasize the limited used frequency region by using a weight function. Finally, for the purpose of illustration, some examples and their simulation results are presented.