Iterative Receiver for MIMO-OFDM System with ICI Cancellation and Channel Estimation

As a multi-carrier modulation scheme, Orthogonal Frequency Division Multiplexing (OFDM) technique can achieve high data rate in frequency-selective fading channels by splitting a broadband signal into a number of narrowband signals over a number of subcarriers, where each subcarrier is more robust to multipath. The wireless communication system with multiple antennas at both the transmitter and receiver, known as multiple-input multiple-output (MIMO) system, achieves high capacity by transmitting independent information over different antennas simultaneously. The combination of OFDM with multiple antennas has been considered as one of most promising techniques for future wireless communication systems. The challenge in the detection of a space-time signal is to design a low-complexity detector, which can efficiently remove interference resulted from channel variations and approach the interference-free bound. The application of iterative parallel interference canceller (PIC) with joint detection and decoding has been a promising approach. However, the decision statistics of a linear PIC is biased toward the decision boundary after the first cancellation stage. In this thesis, we employ an iterative receiver with a decoder metric, which considerably reduces the bias effect in the second iteration, which is critical for the performance of the iterative algorithm. Channel state information is required in a MIMO-OFDM system signal detection at the receiver. Its accuracy directly affects the overall performance of MIMO-OFDM systems. In order to estimate the channel in high-delay-spread environments, pilot symbols should be inserted among subcarriers before transmission. To estimate the channel over all the subcarriers, various types of interpolators can be used. In this thesis, a linear interpolator and a trigonometric interpolator are compared. Then we propose a new interpolator called the multi-tap method, which has a much better system performance. In MIMO-OFDM systems, the time-varying fading channels can destroy the orthogonality of subcarriers. This causes serious intercarrier interference (ICI), thus leading to significant system performance degradation, which becomes more severe as the normalized Doppler frequency increases. In this thesis, we propose a low-complexity iterative receiver with joint frequency- domain ICI cancellation and pilot-assisted channel estimation to minimize the effect of time-varying fading channels. At the first stage of receiver, the interference between adjacent subcarriers is subtracted from received OFDM symbols. The parallel interference cancellation detection with decision statistics combining (DSC) is then performed to suppress the interference from other antennas. By restricting the interference to a limited number of neighboring subcarriers, the computational complexity of the proposed receiver can be significantly reduced. In order to construct the time variant channel matrix in the frequency domain, channel estimation is required. However, an accurate estimation requiring complete knowledge of channel time variations for each block, cannot be obtained. For time- varying frequency-selective fading channels, the placement of pilot tones also has a significant impact on the quality of the channel estimates. Under the assumption that channel variations can be approximated by a linear model, we can derive channel state information (CSI) in the frequency domain and estimate time-domain channel parameters. In this thesis, an iterative low-complexity channel estimation method is proposed to improve the system performance. Pilot symbols are inserted in the transmitted OFDM symbols to mitigate the effect of ICI and the channel estimates are used to update the results of both the frequency domain equalizer and the PICDSC detector in each iteration. The complexity of this algorithm can be reduced because the matrices are precalculated and stored in the receiver when the placement of pilots symbols is fixed in OFDM symbols before transmission. Finally, simulation results show that the proposed MIMO-OFDM iterative receiver can effectively mitigate the effect of ICI and approach the ICI-free performance over time-varying frequency-selective fading channels

A combined channel-modified adaptive array MMSE canceller and viterbi equalizer

In this thesis, a very simple scheme is proposed which couples a maximum-likelihood sequence estimator (MLSE) with a X-element canceller. The method makes use of the MLSE\u27s channel estimator to modify the locally generated training sequence used to calculate the antenna array weights. This method will increase the array\u27s degree of freedom for interference cancellation by allowing the dispersive, desired signal to pass through the array undisturbed. Temporal equalization of the desired signal is then accomplished using maximum-likelihood sequence estimation. The T-spaced channel estimator coefficients and the array weights are obtained simultaneously using the minimum mean square error criteria. The result is a X-element receiver structure capable of canceling X- 1 in-band interferences without compromising temporal equalization

Space Time MUSIC: Consistent Signal Subspace Estimation for Wide-band Sensor Arrays

Wide-band Direction of Arrival (DOA) estimation with sensor arrays is an essential task in sonar, radar, acoustics, biomedical and multimedia applications. Many state of the art wide-band DOA estimators coherently process frequency binned array outputs by approximate Maximum Likelihood, Weighted Subspace Fitting or focusing techniques. This paper shows that bin signals obtained by filter-bank approaches do not obey the finite rank narrow-band array model, because spectral leakage and the change of the array response with frequency within the bin create \emph{ghost sources} dependent on the particular realization of the source process. Therefore, existing DOA estimators based on binning cannot claim consistency even with the perfect knowledge of the array response. In this work, a more realistic array model with a finite length of the sensor impulse responses is assumed, which still has finite rank under a space-time formulation. It is shown that signal subspaces at arbitrary frequencies can be consistently recovered under mild conditions by applying MUSIC-type (ST-MUSIC) estimators to the dominant eigenvectors of the wide-band space-time sensor cross-correlation matrix. A novel Maximum Likelihood based ST-MUSIC subspace estimate is developed in order to recover consistency. The number of sources active at each frequency are estimated by Information Theoretic Criteria. The sample ST-MUSIC subspaces can be fed to any subspace fitting DOA estimator at single or multiple frequencies. Simulations confirm that the new technique clearly outperforms binning approaches at sufficiently high signal to noise ratio, when model mismatches exceed the noise floor.Comment: 15 pages, 10 figures. Accepted in a revised form by the IEEE Trans. on Signal Processing on 12 February 1918. @IEEE201

Design and development of mobile channel simulators using digital signal processing techniques

A mobile channel simulator can be constructed either in the time domain using a tapped delay line filter or in the frequency domain using the time variant transfer function of the channel. Transfer function modelling has many advantages over impulse response modelling. Although the transfer function channel model has been envisaged by several researchers as an alternative to the commonly employed tapped delay line model, so far it has not been implemented. In this work, channel simulators for single carrier and multicarrier OFDM system based on time variant transfer function of the channel have been designed and implemented using DSP techniques in SIMULINK. For a single carrier system, the simulator was based on Bello's transfer function channel model. Bello speculated that about 10Βτ(_MAX) frequency domain branches might result in a very good approximation of the channel (where в is the signal bandwidth and τ(_MAX) is the maximum excess delay of the multi-path channel). The simulation results showed that 10Bτ(_MAX) branches gave close agreement with the tapped delay line model(where Be is the coherence bandwidth). This number is π times higher than the previously speculated 10Bτ(_MAX).For multicarrier OFDM system, the simulator was based on the physical (PHY) layer standard for IEEE 802.16-2004 Wireless Metropolitan Area Network (WirelessMAN) and employed measured channel transfer functions at the 2.5 GHz and 3.5 GHz bands in the simulations. The channel was implemented in the frequency domain by carrying out point wise multiplication of the spectrum of OFDM time The simulator was employed to study BER performance of rate 1/2 and rate 3/4 coded systems with QPSK and 16-QAM constellations under a variety of measured channel transfer functions. The performance over the frequency selective channel mainly depended upon the frequency domain fading and the channel coding rate

The Multi-Input Multi-Output (MIMO) Channel Modeling, Simulation and Applications

This thesis mainly focus on the Multi-Input Multi-Output (MIMO) channel modeling, simulation and applications. There are several ways to design a MIMO channel. Most of the examples are given in Chapter 2, where we can design channels based on the environments and also based on other conditions. One of the new MIMO channel designs based on physical and virtual channel design is discussed in Unitary-Independent- Unitary (UIU) channel modeling. For completeness, the different types of capacity are discussed in details. The capacity is very important in wireless communication. By understanding the details behind different capacity, we can improve our transmission efficiently and effectively. The level crossing rate and average duration are discussed.One of the most important topics in MIMO wireless communication is estimation. Without having the right estimation in channel prediction, the performance will not be correct. The channel estimation error on the performance of the Alamouti code was discussed. The design of the transmitter, the channel and the receiver for this system model is shown. The two different types of decoding scheme were shown - the linear combining scheme and the Maximum likelihood (ML) decoder. Once the reader understands the estimation of the MIMO channel, the estimation based on different antenna correlation is discussed. Next, the model for Mobile-to-Mobile (M2M) MIMO communication link is proposed. The old M2M Sum-of-Sinusoids simulation model and the new two ring models are discussed. As the last step, the fading channel modeling using AR model is derived and the effect of ill-conditioning of the Yule-Walker equation is also shown. A number of applications is presented to show how the performance can be evaluated using the proposed model and techniques

Techniques and errors in measuring cross- correlation and cross-spectral density functions

Techniques and errors in measuring cross spectral density and cross correlation functions of stationary dynamic pressure dat

Analysis of and techniques for adaptive equalization for underwater acoustic communication

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2011Underwater wireless communication is quickly becoming a necessity for applications in ocean science, defense, and homeland security. Acoustics remains the only practical means of accomplishing long-range communication in the ocean. The acoustic communication channel is fraught with difficulties including limited available bandwidth, long delay-spread, time-variability, and Doppler spreading. These difficulties reduce the reliability of the communication system and make high data-rate communication challenging. Adaptive decision feedback equalization is a common method to compensate for distortions introduced by the underwater acoustic channel. Limited work has been done thus far to introduce the physics of the underwater channel into improving and better understanding the operation of a decision feedback equalizer. This thesis examines how to use physical models to improve the reliability and reduce the computational complexity of the decision feedback equalizer. The specific topics covered by this work are: how to handle channel estimation errors for the time varying channel, how to use angular constraints imposed by the environment into an array receiver, what happens when there is a mismatch between the true channel order and the estimated channel order, and why there is a performance difference between the direct adaptation and channel estimation based methods for computing the equalizer coefficients. For each of these topics, algorithms are provided that help create a more robust equalizer with lower computational complexity for the underwater channel.This work would not have been possible without support from the O ce of Naval Research, through a Special Research Award in Acoustics Graduate Fellowship (ONR Grant #N00014-09-1-0540), with additional support from ONR Grant #N00014-05- 10085 and ONR Grant #N00014-07-10184