Standard open loop linear adaptive signal processing algorithms derived from the least squares minimization criterion require estimates of the N-dimensional input interference and noise statistics. Often, estimated statistics are biased by contaminant data (such as outliers and non-stationary data) that do not fit the dominant distribution, which is often modeled as Gaussian. In particular, convergence of sample covariance matrices used in block processed adaptive algorithms, such as the Sample Matrix Inversion (SMI) algorithm, are known to be affected significantly by outliers, causing undue bias in subsequent adaptive weight vectors. The convergence measure of effectiveness (MOE) of the benchmark SMI algorithm is known to be relatively fast (order K = 2N training samples) and independent of the (effective) rank of the external interference covariance matrix, making it a useful method in practice for non-contaminated data environments. Novel robust adaptive algorithms are introduced here that perform superior to SMI algorithms in contaminated data environments while some retain its valuable convergence independence feature. Convergence performance is shown to be commensurate with SMI in non-contaminated environments as well. The robust algorithms are based on the Gram Schmidt Cascaded Canceller (GSCC) structure where novel building block algorithms are derived for it and analyzed using the theory of Robust Statistics. Coined M – cancellers after M – estimates of Huber, these novel cascaded cancellers combine robustness and statistical estimation efficiency in order to provide good adaptive performance in both contaminated and non-contaminated data environments. Additionally, a hybrid processor is derived by combining the Multistage Wiener Filter (MWF) and Median Cascaded Canceller (MCC) algorithms. Both simulated data and measured Space-Time Adaptive Processing (STAP) airborne radar data are used to show performance enhancements. The STAP application area is described in detail in order to further motivate research into robust adaptive processing. / Ph. D.

Recognition of speech at the receiver end generally gets degraded in distant talking atmospheres of laptops, teleconfereing, video conferences and in hands free telephony, where the quality of speech gets contaminated and severely disturbed because of the additive noises. To make useful and effective, the exact speech signals has to be extracted from the noise signals and the user has to be given the clean speech. In such conditions the convenience of microphone array has been preferred as a means of civilizing the quality of arrested signals. A consequential growth in laptop technology and microphone array processing have made possible to improve intelligibility of speech while communication. So this contention target on reducing the additive noises from the original speech, beside design and use of different algorithms. In this thesis a multi-channel microphone array with its speech enhancement of signals to Wiener Beamformar and Generalized side lobe canceller (GSC) are used for Laptops in a noisy environment. Systems prescribed above were implemented, processed and evaluated on a computer using Mat lab considering SNR, SNRI as the main objective of quality measures. Systems were tested with two speech signals, among which one is Main speech signal and other is considered as Noise along with another random noise, sampling them at 16 KHz .Three Different source originations were taken into consideration with different input SNR’s of 0dB, 5dB, 10dB, 15dB, 20dB, 25dB. Simulation Results showed that Noise is been attenuated to a great extent. But Variations in SNR and SNRI has been observed, because of the different point origination of signals in the respective feilds.Variation in SNR and SNRI is been observed when the distance between the main speech originating point and microphone is too long compared to the noise signals. This states that origination of signals plays a huge role in maintaining the speech quality at the receiver end. / D.No 4-22, Gandla street, papanaidupeta-517526 chittoor district,Andhra pradesh India naveenkumarthupalli@gmail.com

A common problem encountered in phased array signal processing is how to remove sources of interference from a desired signal. Two existing methods to accomplish this are the Linearly Constrained Minimum Variance (LCMV) beamformer and the Side-Lobe Canceller (SLC). LCMV provides better performance than SLC, but comes with much higher computational costs. The Steered Auxiliary Beam Canceller (SABC) presented in this thesis is a new algorithm developed to improve the performance of SLC without the computational costs of LCMV. SABC performs better than SLC because it uses high-gain auxiliary channels for cancellation. This new technique is now possible because digital arrays allow for direction finding algorithms such as Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) to estimate the directions of the interference sources. With this added knowledge, high gain beams similar to the main beam may be used as auxiliaries instead of low-gain antenna elements. Another contribution is a method introduced to calculate the computational complexity of LCMV, SLC, and SABC much more accurately than existing methods which only provide order-of-magnitude estimates. The final contribution is a derivation of the signal loss experienced by SLC and SABC and simulations that verify the performance of LCMV, SLC, and SABC. / Master of Science

The extension of Multi-mode Absorption Spectroscopy (MUMAS) to the infra-red spectral region for multi-species gas sensing is reported. A computationally efficient, theoretical model for analysis of MUMAS spectra is presented that avoids approximations used in previous work and treats arbitrary and time-dependent spectral intensity envelopes, thus facilitating the use of commercially available Interband Cascade Lasers (ICLs) and Quantum Cascade Lasers (QCLs). The first use of an ICL for MUMAS is reported using a multi-mode device operating at 3.7 μm to detect CH₄ transitions over a range of 30 nm. Mode-linewidths are measured using the pressure-dependent widths of an isolated absorption feature in HCl. Multi- species sensing is demonstrated by measurement of partial pressures of CH₄, C₂H₂ and H₂CO in a low-pressure mixture with uncertainties of around 10%. Detection of CH₄ in N₂ at 1 bar is demonstrated using a shorter-cavity ICL to resolve spectral features in pressure-broadened and congested spectra. The first use of a QCL for MUMAS is reported using a commercially available device operating at 5.3 μm to detect multiple absorption transitions of NO at a partial pressure of 2.79 μbar in N₂ buffer gas. The revised model is shown to enable good fits to MUMAS data by accounting for the time-variation of the spectral intensity profile during frequency scanning. Individual mode-linewidths are derived from fits to pressure- dependent MUMAS spectra and features from background interferences due to H₂O in laboratory air are distinguished from those of the target species, NO. Data obtained at scan rates up to 10 kHz demonstrate the potential for achieving short measurement times. The development of a balanced ratiometric detection scheme for MUMAS with commercially available multi-mode lasers operating at 1.5 μm is reported for simultaneous detection of CO and CO₂ showing improved SNR performance over previous direct transmission methods and suitability for a compact field-employable instrument. In addition, MUMAS spectra of CO₂ are used to derive gas temperatures with an uncertainty of 3.2% in the range 300 - 700 K.

Master of Engineering (Research) / Multiple antenna systems are an appealing candidate for emerging fourth-generation wireless networks due to its potential to exploit space diversity for increasing conveyed throughput without wasting bandwidth and power resources. Particularly, layered space-time architecture (LST) proposed by Foschini, is a technique to achieve a significant fraction of the theoretical capacity with a reasonable implementation complexity. There has been a great deal of challenges in the detection of space-time signal; especially to design a low-complexity detector, which can efficiently remove multi-layer interference and approach the interference free bound. The application of iterative principle to joint detection and decoding has been a promising approach. It has been shown that, the iterative receiver with parallel interference canceller (PIC) has a low linear complexity and near interference free performance. Furthermore, it is widely accepted that the performance of digital communication systems can be considerably improved once the channel state information (CSI) is used to optimize the transmit signal. In this thesis, the problem of the design of a power allocation strategy in LST architecture to simultaneously optimize coding, diversity and weighting gains is addressed. A more practical scenario is also considered by assuming imperfect CSI at the receiver. The effect of channel estimation errors in LST architecture with an iterative PIC receiver is investigated. It is shown that imperfect channel estimation at an LST receiver results in erroneous decision statistics at the very first iteration and this error propagates to the subsequent iterations, which ultimately leads to severe degradation of the overall performance. We design a transmit power allocation policy to take into account the imperfection in the channel estimation process. The transmit power of various layers is optimized through minimization of the average bit error rate (BER) of the LST architecture with a low complexity iterative PIC detector. At the receiver, the PIC detector performs both interference regeneration and cancellation simultaneously for all layers. A convolutional code is used as the constituent code. The iterative decoding principle is applied to pass the a posteriori probability estimates between the detector and decoders. The decoder is based on the maximum a posteriori (MAP) algorithms. A closed-form optimal solution for power allocation in terms of the minimum BER is obtained. In order to validate the effectiveness of the proposed schemes, substantial simulation results are provided.

In this thesis, we present a new low-complexity receiver with the modified hybrid signature direct-sequence code division multiple access (DS-CDMA) system framework that use the multiple-input multiple-output (MIMO) antennas along with Alamouti¡¦s space-time block code (ST-BC). In the transceiver, the modified hybrid signature is exploited. It is not only used to counteract the inter-symbol interference (ISI) introduced by the channel fading duo to multipath propagation but also very useful for extracting the full channel information in the receiver. For reducing computational complexity, we propose a new modified partial adaptivity (MPA) filter. It is not only having the advantage of subspace-based PA-GSC filter to enhance the system performance but also avoid the computation requirement when the Eigen-decomposition approach was adopted. Next, with the modified transceiver framework, in the receiver, based on the linearly constrained constant modulus (LCCM) criterion, we propose a novel semi-blind multiple detector schemes for MIMO-CDMA systems, which is implementing with the adaptive RLS algorithm and framework in the modified partially adaptive (MPA) generalized sidelobe canceller (GSC) . Our proposed scheme is able to perform the two-branch filterbank of LCCM MIMO-CDMA receiver. Computer simulations demonstrate that the proposed receiver has better performance than the convention CM-GSC-RLS receiver with much lower computational load.

The Orthogonal frequency division multiplexing (OFDM) technique has been intensively used in many wireless communication systems to achieve higher data rate transmissions. Due to the fact that the OFDM technique entails redundant block transmissions; the transmitted blocks suffer from the inter-symbol interference (ISI) and inter-block interference (IBI). To compensate this serious effect, in many literatures redundant symbols (or guard interval) with adequate length are inserted in the transmitted symbols to prevent the IBI. Also, in the receiver the equalizer can be employed to deal with ISI. In this thesis, we present a new pseudo random cyclic-postfix (PRCP-) OFDM associated with the multiple-input multiple-output (MIMO) antenna system configuration to further improve the system performance. In fact, the MIMO system can enhance channel capacity and achieve high data-rate. The above-mentioned PRCP-OFDM technique combines with the MIMO antennas system, through the appropriate model design can be used to combat the multi-path effect or the inter-block interference. As evident from the simulation results, the proposed ST-BC MIMO PRCP-OFDM system can avoid the interference of transmitted signals during the estimation of channel impulse response (CIR) with proposed cyclic-postfix sequences. In addition, to further improve and eliminate the residual IBI and ICI, the equalizer with the framework of the generalized sidelobe canceller (GSC) is considered. Specifically, when SNR grows, the proposed ST-BC MIMO PRCP-OFDM system can perform successfully in terms of symbol-error rate and semi-blind channel estimation. This is verified via the computer simulations.

Capacity of CDMA system is limited to interference due to other users. System performance is degraded by near-far problem when undesired users are closer to base station. Beside, the channel parameters could not be estimated perfectly at receiver, refer to as mismatch problem, which would also degrade the system performance. We would like to consider the MAI and near-far interference cancellation by adaptive linear constraint algorithms to implement linear constraint minimum variance (LCMV) approach. To exploit the linearly constrained filtering, the structure of the generalized side-lobe canceller (GSC) has been employed, where the constrained problem is converted into an unconstrained form with fewer parameters. GSC structure is an indirect but simpler implementation of LCMV algorithm. Moreover, it is also known that the constant modulus (CM) criteria has advantage to combat the channel mismatch, and the performance of the adaptive constraint algorithm based on CM criteria will be investigate. In this thesis, we will derive a new GSC-IQRD-RLS algorithm to combat MAI and near-far problems by combining LC-IQRD-RLS algorithm [1][5] and GSC structure [17]; and prove that the GSC and LC structures based IQRD-RLS algorithms are equivalent, which means that the good performance of LC-IQRD-RLS algorithm can be achieved by a simpler GSC structure algorithm. We will also derive a new GSC-CM-IQRD-RLS algorithm to improve the system performance under mismatch problem by combining CM criteria [20] and GSC-IQRD-RLS algorithm.

The conventional temporal filtering approach cannot be used to separate signal from interference which occupies the same temporal frequency band as signal. Using a spatial filtering at the receiver can separate signals from interference that originates from different spatial location. Many adaptive array beamforming algorithms, based on linear constraints, have been proposed for suppressing undesired interference and being applied to wireless communication systems for multiuser detection. The adaptive array system can be employed to automatically adjust its directional to achieve the purpose that nulls the interferences or jammers and thus, enhances the reception of the desired signal. Inverse QR Decomposition Recursive Least-square (IQRD-RLS) algorithm has many advantages such as where the LS weight vector be computed without back substitution, a well known numerical stable algorithm and offering better convergence rate, steady-state means-square error, and parameter tracking capability over the adaptive least mean square (LMS) based algorithms. In this thesis, a new application, GSC-IQRD-RLS combining Generalized Sidelobe Canceller (GSC) and IQRD-RLS algorithm, is developed. It preserves the advantages of GSC such as simple structure, less computations, and converts a linearly constrained optimization problem into a standard optimum filtering problem. But the performance is equivalent between GSC-IQRD-RLS and LC-IQRD-RLS algorithms.

In recent years, demands on all kinds of wireless communications become heavier due to the developments of new services and devices. At the same time, future wireless networks are expected to provide services with high quality and data rate. A possible solution which can attain these objectives is wireless communication systems that use multiple-input multiple-output (MIMO) antennas along with Alamouti¡¦s space-time block code and direct-sequence code division multiple access (DS-CDMA) modulation technique. In such systems, spatial diversity rendered by multiple antennas as well as coding in spatial and time domains are the keys to improve quality of transmission. Many multiuser detection techniques for the space-time block coded CDMA systems have been investigated. In [8], the blind Capon receiver was proposed, which consists of a two-branch filterbank followed by the blind Capon channel estimator. The design of blind Capon receiver is based on linearly constrained minimum variance (LCMV) criterion, which is known to be sensitive to inaccuracies in the acquisition or tracking of the desired user's timing, referred to as mismatch effect. In other words, the LCMV-based receiver may perform undesirably under mismatch effect. In this thesis, we propose a new blind adaptive MIMO-CDMA receiver based on the linearly constrained constant modulus (LCCM) criterion. This work is motivated by the robustness of LCCM approach to the mismatch effect. To reduce the complexity of receiver design, framework of the generalized sidelobe canceller (GSC) associated with the recursive least squares (RLS) algorithm is adopted for implementing the adaptive LCCM MIMO-CDMA filterbank. Based on the GSC-RLS structure, we derive the proposed MIMO CM-GSC-RLS algorithm. For the purpose of comparison, an adaptive implementation of the blind Capon receiver proposed in [8] is also derived, which is referred to as the MIMO MV-GSC-RLS algorithm. We note that the signal model in [8] was constructed under assumption of frequency-flat channels. To obtain a more practical and realistic signal model, in this thesis we extend the system and channel model by including multipath effects in the beginning of our work. In completing this extension, inter-symbol interference (ISI) caused by the special coding scheme of ST-BC will be specifically analyzed. Finally, a full discussion of the multipath signal model will be provided, including necessity of truncating the received signals as well as modifications in the signal model when considering time-varying channels. Via computer simulations, advantages of the proposed scheme will be verified. Compared to the conventional blind Capon receiver, we will show that the performance of the proposed CM-GSC-RLS algorithm is better. This is especially true when mismatch problem is considered in the MIMO-CDMA systems of interest. The proposed scheme show more robustness against the mismatch effects than the conventional blind Capon receiver. Moreover, the benefit resulted by truncating the received signals is also demonstrated, especially for binary phase-shift-keying (BPSK) modulated source symbol. Finally, simulations considering time-varying channels are provided to reveal that our proposed scheme can adapt itself to the time-varying environments appropriately.