Hybrid solutions to instantaneous MIMO blind separation and decoding: narrowband, QAM and square cases

Future wireless communication systems are desired to support high data rates and high quality transmission when considering the growing multimedia applications. Increasing the channel throughput leads to the multiple input and multiple output and blind equalization techniques in recent years. Thereby blind MIMO equalization has attracted a great interest.Both system performance and computational complexities play important roles in real time communications. Reducing the computational load and providing accurate performances are the main challenges in present systems. In this thesis, a hybrid method which can provide an affordable complexity with good performance for Blind Equalization in large constellation MIMO systems is proposed first. Saving computational cost happens both in the signal sep- aration part and in signal detection part. First, based on Quadrature amplitude modulation signal characteristics, an efficient and simple nonlinear function for the Independent Compo- nent Analysis is introduced. Second, using the idea of the sphere decoding, we choose the soft information of channels in a sphere, and overcome the so- called curse of dimensionality of the Expectation Maximization (EM) algorithm and enhance the final results simultaneously. Mathematically, we demonstrate in the digital communication cases, the EM algorithm shows Newton -like convergence.Despite the widespread use of forward -error coding (FEC), most multiple input multiple output (MIMO) blind channel estimation techniques ignore its presence, and instead make the sim- plifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In final part of this work, we exploit the iterative channel estimation and decoding performance for blind MIMO equalization. Experiments show the improvements achievable by exploiting the existence of coding structures and that it can access the performance of a BCJR equalizer with perfect channel information in a reasonable SNR range. All results are confirmed experimentally for the example of blind equalization in block fading MIMO systems

Frequency Domain Independent Component Analysis Applied To Wireless Communications Over Frequency-selective Channels

In wireless communications, frequency-selective fading is a major source of impairment for wireless communications. In this research, a novel Frequency-Domain Independent Component Analysis (ICA-F) approach is proposed to blindly separate and deconvolve signals traveling through frequency-selective, slow fading channels. Compared with existing time-domain approaches, the ICA-F is computationally efficient and possesses fast convergence properties. Simulation results confirm the effectiveness of the proposed ICA-F. Orthogonal Frequency Division Multiplexing (OFDM) systems are widely used in wireless communications nowadays. However, OFDM systems are very sensitive to Carrier Frequency Offset (CFO). Thus, an accurate CFO compensation technique is required in order to achieve acceptable performance. In this dissertation, two novel blind approaches are proposed to estimate and compensate for CFO within the range of half subcarrier spacing: a Maximum Likelihood CFO Correction approach (ML-CFOC), and a high-performance, low-computation Blind CFO Estimator (BCFOE). The Bit Error Rate (BER) improvement of the ML-CFOC is achieved at the expense of a modest increase in the computational requirements without sacrificing the system bandwidth or increasing the hardware complexity. The BCFOE outperforms the existing blind CFO estimator [25, 128], referred to as the YG-CFO estimator, in terms of BER and Mean Square Error (MSE), without increasing the computational complexity, sacrificing the system bandwidth, or increasing the hardware complexity. While both proposed techniques outperform the YG-CFO estimator, the BCFOE is better than the ML-CFOC technique. Extensive simulation results illustrate the performance of the ML-CFOC and BCFOE approaches

Semi-Blind Space-Time Equalization for Single-Carrier MIMO Systems with Block Transmission

Publication in the conference proceedings of EUSIPCO, Florence, Italy, 200

Complex-valued Adaptive Digital Signal Enhancement For Applications In Wireless Communication Systems

In recent decades, the wireless communication industry has attracted a great deal of research efforts to satisfy rigorous performance requirements and preserve high spectral efficiency. Along with this trend, I/Q modulation is frequently applied in modern wireless communications to develop high performance and high data rate systems. This has necessitated the need for applying efficient complex-valued signal processing techniques to highly-integrated, multi-standard receiver devices. In this dissertation, novel techniques for complex-valued digital signal enhancement are presented and analyzed for various applications in wireless communications. The first technique is a unified block processing approach to generate the complex-valued conjugate gradient Least Mean Square (LMS) techniques with optimal adaptations. The proposed algorithms exploit the concept of the complex conjugate gradients to find the orthogonal directions for updating the adaptive filter coefficients at each iteration. Along each orthogonal direction, the presented algorithms employ the complex Taylor series expansion to calculate time-varying convergence factors tailored for the adaptive filter coefficients. The performance of the developed technique is tested in the applications of channel estimation, channel equalization, and adaptive array beamforming. Comparing with the state of the art methods, the proposed techniques demonstrate improved performance and exhibit desirable characteristics for practical use. The second complex-valued signal processing technique is a novel Optimal Block Adaptive algorithm based on Circularity, OBA-C. The proposed OBA-C method compensates for a complex imbalanced signal by restoring its circularity. In addition, by utilizing the complex iv Taylor series expansion, the OBA-C method optimally updates the adaptive filter coefficients at each iteration. This algorithm can be applied to mitigate the frequency-dependent I/Q mismatch effects in analog front-end. Simulation results indicate that comparing with the existing methods, OBA-C exhibits superior convergence speed while maintaining excellent accuracy. The third technique is regarding interference rejection in communication systems. The research on both LMS and Independent Component Analysis (ICA) based techniques continues to receive significant attention in the area of interference cancellation. The performance of the LMS and ICA based approaches is studied for signals with different probabilistic distributions. Our research indicates that the ICA-based approach works better for super-Gaussian signals, while the LMS-based method is preferable for sub-Gaussian signals. Therefore, an appropriate choice of interference suppression algorithms can be made to satisfy the ever-increasing demand for better performance in modern receiver design

Semi-blind CFO estimation and ICA based equalization for wireless communication systems

In this thesis, a number of semi-blind structures are proposed for Orthogonal Frequency Division Multiplexing (OFDM) based wireless communication systems, with Carrier Frequency Offset (CFO) estimation and Independent Component Analysis (ICA) based equalization. In the first contribution, a semi-blind non-redundant single-user Multiple-Input Multiple-Output (MIMO) OFDM system is proposed, with a precoding aided CFO estimation approach and an ICA based equalization structure. A number of reference data sequences are carefully designed and selected from a pool of orthogonal sequences, killing two birds with one stone. On the one hand, the precoding based CFO estimation is performed by minimizing the sum cross-correlations between the CFO compensated signals and the rest of the orthogonal sequences in the pool. On the other hand, the same reference data sequences enable the elimination of permutation and quadrant ambiguities in the ICA equalized signals. Simulation results show that the proposed semi-blind MIMO OFDM system can achieve a Bit Error Rate (BER) performance close to the ideal case with perfect Channel State Information (CSI) and no CFO. In the second contribution, a low-complexity semi-blind structure, with a multi-CFO estimation method and an ICA based equalization scheme, is proposed for multiuser Coordinated Multi-Point (CoMP) OFDM systems. A short pilot is carefully designed offline for each user and has a two-fold advantage. On the one hand, using the pilot structure, a complex multi-dimensional search for multiple CFOs is divided into a number of low-complexity mono-dimensional searches. On the other hand, the cross-correlation between the transmitted and received pilots is explored to allow the simultaneous elimination of permutation and quadrant ambiguities in the ICA equalized signals. Simulation results show that the proposed semi-blind CoMP OFDM system can provide a BER performance close to the ideal case with perfect CSI and no CFO. In the third contribution, a semi-blind structure is proposed for Carrier Aggregation (CA) based CoMP Orthogonal Frequency Division Multiple Access (OFDMA) systems, with an ICA based joint Inter-Carrier Interference (ICI) mitigation and equalization scheme. The CFO-induced ICI is mitigated implicitly via ICA based equalization, without introducing feedback overhead for CFO correction. The permutation and quadrant ambiguities in the ICA equalized signals can be eliminated by a small number of pilots. Simulation results show that with a low training overhead, the proposed semi-blind equalization scheme can provide a BER performance close to the ideal case with perfect CSI and no CFO

FGPA Implementation of Low-Complexity ICA Based Blind Multiple-Input-Multiple-Output OFDM Receivers

In this thesis Independent Component Analysis (ICA) based methods are used for blind detection in MIMO systems. ICA relies on higher order statistics (HOS) to recover the transmitted streams from the received mixture. Blind separation of the mixture is achieved based on the assumption of mutual statistical independence of the source streams. The use of HOS makes ICA methods less sensitive to Gaussian noise. ICA increase the spectral efficiency compared to conventional systems, without any training/pilot data required. ICA is usually used for blind source separation (BSS) from their mixtures by measuring non-Gaussianity using Kurtosis. Many scientific problems require FP arithmetic with high precision in their calculations. Moreover a large dynamic range of numbers is necessary for signal processing. FP arithmetic has the ability to automatically scale numbers and allows numbers to be represented in a wider range than fixed-point arithmetic. Nevertheless, FP algorithm is difficult to implement on the FPGA, because the algorithm is so complex that the area (logic elements) of FPGA leads to excessive consumption when implemented. A simplified 32-bit FP implementation includes adder, Subtractor, multiplier, divider, and square rooter The FPGA design is based on a hierarchical concept, and the experimental results of the design are presented

A Joint Optimization Criterion for Blind DS-CDMA Detection

This paper addresses the problem of the blind detection of a desired user in an asynchronous DS-CDMA communications system with multipath propagation channels. Starting from the inverse filter criterion introduced by Tugnait and Li in 2001, we propose to tackle the problem in the context of the blind signal extraction methods for ICA. In order to improve the performance of the detector, we present a criterion based on the joint optimization of several higher-order statistics of the outputs. An algorithm that optimizes the proposed criterion is described, and its improved performance and robustness with respect to the near-far problem are corroborated through simulations. Additionally, a simulation using measurements on a real software-radio platform at 5 GHz has also been performed.Ministerio de Ciencia y tecnología TEC2004-06451-C05-0