Channel modeling, estimation and equalization in wireless communication

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file viewed on (May 25, 2006)Includes bibliographical references.Vita.Thesis (Ph. D.) University of Missouri-Columbia 2005.Dissertations, Academic -- University of Missouri--Columbia -- Electrical engineering.Channel modeling, estimation and equalization are discussed throughout this dissertation. Relevant research topics are first studied at the beginning of each chapter and the new methods are proposed to improve the system performance. MLSE is an optimum equalizer for all the case. However, due to its computational complexity, it is impractical for today technologies in third generation wireless communication. Thus, a suboptimum equalizer so-called perturbation equalizer is proposed, which outperforms the RSSE equalizer in the sense of bit error rate or computational complexity. In order to improve the system performance dramatically, the iterative equalization algorithm is implemented. It has been shown that the turbo equalization using the trellis based Maximum A Posteriori equalizer is a powerful receiver that yielding the optimum system performance. Unfortunately, due to its exhausted computational complexity, a suboptimal equalizer is required. An improved DFE algorithm, which only requires low computational complexity, is proposed for turbo equalization. The promising simulation results indicate that the proposed equalizer provides significant improvement in bit error rate while compared to the conventional DFE algorithm. Prior to channel equalization, channel estimation enable us to extract the necessary channel information from the pilot symbols for equalizers. Least-squares algorithm is a promising estimation algorithm providing the channel is time-invariant in a given period. Based on the derivations, we show that the channel is no longer constant and a new least-squares based algorithm is proposed to estimate the channel accurately. Simulation results convince us that the new algorithm provides the equalizer more reliable information. Besides, antenna diversity is another promising technique implemented practically to improve the system performance provided that the channels of antennas are not correlated. A new three dimensional multiple-input multiple-output abstract model is proposed for the investigation and understanding of the correlation of fading channel. The new model allows us to consider the channel correlation of which the mobile stations receive the incoming waves from any directions and angle spreads. Based on this abstract model, the closed form and mathematical tractable formula is derived for space-time correlation function. The new function can be further simplified other known special cases

Space-Time Fading Correlation Functions of a 3-D MIMO Channel Model

Space-time correlation functions between the links of MIMO Rayleigh fading channels are derived using a new three-dimensional (3-D) cylinder scattering model. Closed form, mathematically tractable formulas are obtained for the space-time correlation functions for general MIMO systems where the base station and mobile station antennas may be arranged in 3-D space. It is shown that the correlation functions computed by the 3-D cylinder model are of significant difference than those of the conventional 2-D Clarke\u27\u27s isotropic scattering model for vertically placed antennas. The general formulas of the correlation functions includes the 2-D Clarke\u27\u27s model and the 3-D SIMO, MISO models as special cases

Iterative Equalization Using Improved Block DFE for Synchronous CDMA Systems

Iterative equalization using optimal multiuser detector and trellis-based channel decoder in coded CDMA systems improves the bit error rate (BER) performance dramatically. However, given large number of users employed in the system over multipath channels causing significant multiple-access interference (MAI) and intersymbol interference (ISI), the optimal multiuser detector is thus prohibitively complex. Therefore, the sub-optimal detectors such as low-complexity linear and non-linear equalizers have to be considered. In this paper, a novel low-complexity block decision feedback equalizer (DFE) is proposed for the synchronous CDMA system. Based on the conventional block DFE, the new method is developed by computing the reliable extrinsic log-likelihood ratio (LLR) using two consecutive received samples rather than one received sample in the literature. At each iteration, the estimated symbols by the equalizer is then saved as a priori information for next iteration. Simulation results demonstrate that the proposed low-complexity block DFE algorithm offers very good performance gain over the conventional block DFE

Fast Time-Varying Dispersive Channel Estimation and Equalization for 8-PSK Cellular System

In this paper, a novel channel-estimation scheme for an 8-PSK enhanced data rates for GSM evolution (EDGE) system with fast time-varying and frequency-selective fading channels is presented. via a mathematical derivation and simulation results, the channel impulse response (CIR) of the fast fading channel is modeled as a linear function of time during a radio burst in the EDGE system. Therefore, a least-squares-based method is proposed along with the modified burst structure for time-varying channel estimation. Given that the pilot-symbol blocks are located at the front and the end of the data block, the LS-based method is able to estimate the parameters of the time-varying CIR accurately using a linear interpolation. The proposed time-varying estimation algorithm does not cause an error floor that existed in the adaptive algorithms due to a nonideal channel tracking. Besides, the time-varying CIR in the EDGE system is not in its minimum-phase form, as is required for low-complexity reduced-state equalization methods. In order to maintain a good system performance, a Cholesky-decomposition method is introduced in front of the reduced-state equalizer to transform the time-varying CIR into its minimum-phase equivalent form. via simulation results, it is shown that the proposed algorithm is very well suited for the time-varying channel estimation and equalization, and a good bit-error-rate performance is achieved even at high Doppler frequencies up to 300 Hz with a low complexity

A discrete-time model for spatio-temporally correlated MIMO WSSUS multipath channels

Abstract — In this paper, a statistical discrete-time model is proposed for simulating wideband MIMO channels which experience spatially and temporally correlated, widesense stationary uncorrelated scattering (WSSUS)multipath Rayleigh fading. A new method is also presented to efficiently generate the correlated MIMO channel coefficients, which can be used for accurate simulation of physical continuous-time MIMO channels. The statistic accuracy of the discrete-time MIMO channel model is rigorously verified through theoretical analysis and extensive simulations in different criteria. I

Improved BDFE Using A Priori Information for Turbo Equalization

Turbo equalization improves communication system performance by iteratively exchanging information between soft-input soft-output (SISO) equalizer and SISO channel decoder. The trellis-based maximum a posteriori probability (MAP) algorithm serves as the optimum SISO equalizer for turbo equalization. However, MAP algorithm is unsuitable for systems with large modulation constellation size and severe inter-symbol interference (ISI) due to its prohibitively high computational complexity. In this paper, an improved SISO block decision feedback equalizer (BDFE) is proposed for low complexity turbo equalization. Unlike other sub-optimum equalizers which perform symbol by symbol detection, the proposed equalizer generates the soft output for each data bit by collecting information from a sequence of samples as in MAP algorithm. The sequence-based equalization is enabled by using not only soft a priori input from channel decoder, but also hard a priori information obtained from BDFE in previous iteration. The combination of soft a priori information and hard a priori information renders better performance with less iterations compared to other suboptimum algorithms. In addition, the computational complexity of the proposed algorithm is on the same order as conventional SISO BDFE algorithm, and is much lower compared to the trellis-based MAP algorithm

A Discrete-Time Model for Triply Selective MIMO Rayleigh Fading Channels

Abstract—A statistical discrete-time model is proposed for simulating wideband multiple-input multiple-output (MIMO) fading channels which are triply selective due to angle spread, Doppler spread, and delay spread. The new discrete-time MIMO channel model includes the combined effects of the transmit filter, physical MIMO multipath channel fading, and receive filter, and it has the same sampling period as that of the MIMO receiver. This leads to very efficient simulation of physical continuous-time MIMO channels. A new method is also presented to efficiently generate the MIMO channel stochastic coefficients. The statistical accuracy of the discrete-time MIMO channel model is rigorously verified through theoretical analysis and extensive simulations in different conditions. The high computational efficiency of the discrete-time MIMO channel model is illustrated by comparing it to that of the continuous-time MIMO channel model. The new model is further employed to evaluate the channel capacity of MIMO systems in a triply selective Rayleigh fading environment. The simulation results reveal some interesting effects of spatial correlations, multipaths, and number of antennas on the MIMO channel capacity. Index Terms—Discrete-time channel model, multiple-input multiple-output (MIMO) channel, multiple-input multiple-output multipath channel capacity, Rayleigh fading, triply selective fading, wide-sense stationary uncorrelated scattering (WSSUS) multipath channel. I