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

Novel Complex Adaptive Signal Processing Techniques Employing Optimally Derived Time-varying Convergence Factors With Applicatio

In digital signal processing in general, and wireless communications in particular, the increased usage of complex signal representations, and spectrally efficient complex modulation schemes such as QPSK and QAM has necessitated the need for efficient and fast-converging complex digital signal processing techniques. In this research, novel complex adaptive digital signal processing techniques are presented, which derive optimal convergence factors or step sizes for adjusting the adaptive system coefficients at each iteration. In addition, the real and imaginary components of the complex signal and complex adaptive filter coefficients are treated as separate entities, and are independently updated. As a result, the developed methods efficiently utilize the degrees of freedom of the adaptive system, thereby exhibiting improved convergence characteristics, even in dynamic environments. In wireless communications, acceptable co-channel, adjacent channel, and image interference rejection is often one of the most critical requirements for a receiver. In this regard, the fixed-point complex Independent Component Analysis (ICA) algorithm, called Complex FastICA, has been previously applied to realize digital blind interference suppression in stationary or slow fading environments. However, under dynamic flat fading channel conditions frequently encountered in practice, the performance of the Complex FastICA is significantly degraded. In this dissertation, novel complex block adaptive ICA algorithms employing optimal convergence factors are presented, which exhibit superior convergence speed and accuracy in time-varying flat fading channels, as compared to the Complex FastICA algorithm. The proposed algorithms are called Complex IA-ICA, Complex OBA-ICA, and Complex CBC-ICA. For adaptive filtering applications, the Complex Least Mean Square algorithm (Complex LMS) has been widely used in both block and sequential form, due to its computational simplicity. However, the main drawback of the Complex LMS algorithm is its slow convergence and dependence on the choice of the convergence factor. In this research, novel block and sequential based algorithms for complex adaptive digital filtering are presented, which overcome the inherent limitations of the existing Complex LMS. The block adaptive algorithms are called Complex OBA-LMS and Complex OBAI-LMS, and their sequential versions are named Complex HA-LMS and Complex IA-LMS, respectively. The performance of the developed techniques is tested in various adaptive filtering applications, such as channel estimation, and adaptive beamforming. The combination of Orthogonal Frequency Division Multiplexing (OFDM) and the Multiple-Input-Multiple-Output (MIMO) technique is being increasingly employed for broadband wireless systems operating in frequency selective channels. However, MIMO-OFDM systems are extremely sensitive to Intercarrier Interference (ICI), caused by Carrier Frequency Offset (CFO) between local oscillators in the transmitter and the receiver. This results in crosstalk between the various OFDM subcarriers resulting in severe deterioration in performance. In order to mitigate this problem, the previously proposed Complex OBA-ICA algorithm is employed to recover user signals in the presence of ICI and channel induced mixing. The effectiveness of the Complex OBA-ICA method in performing ICI mitigation and signal separation is tested for various values of CFO, rate of channel variation, and Signal to Noise Ratio (SNR)

Performance of momentum-based frequency-domain MIMO equalizer in the presence of feedback delay

A frequency-domain multiple-input multiple-output (FD-MIMO) equalizer employing a momentum-based gradient descent update algorithm is proposed for polarization multiplexing coherent receivers. Its performance in operation with dynamically varying optical channels is investigated and the impact of filter update delays, arising from the latency of the fast Fourier transforms (FFTs) and other digital signal processing (DSP) operations in the feedback loop, is assessed. We show that the proposed momentum-based gradient descent algorithm used to control the equalizer response has significantly greater tolerance to feedback delay than the conventional gradient descent algorithm. We considered a 92 Gbaud dual-polarization 64 QAM receiver, with DSP operating at two samples per symbol, and with the equalizer operating on blocks of 512 and 1024 samples (i.e., 512/1024-point FFT). We found that at an optical signal-to-noise power ratio (OSNR) of 35 dB, the momentum-based gradient descent algorithm can successfully track state-of-polarization (SOP) rotation at frequencies of up to 50 kHz and with filter update delays of up to 14 blocks (39 ns). In comparison, using the conventional gradient descent algorithm in an otherwise identical receiver, the equalizer performance starts to deteriorate at SOP rotation frequencies above 20 kHz

MIMO-aided near-capacity turbo transceivers: taxonomy and performance versus complexity

In this treatise, we firstly review the associated Multiple-Input Multiple-Output (MIMO) system theory and review the family of hard-decision and soft-decision based detection algorithms in the context of Spatial Division Multiplexing (SDM) systems. Our discussions culminate in the introduction of a range of powerful novel MIMO detectors, such as for example Markov Chain assisted Minimum Bit-Error Rate (MC-MBER) detectors, which are capable of reliably operating in the challenging high-importance rank-deficient scenarios, where there are more transmitters than receivers and hence the resultant channel-matrix becomes non-invertible. As a result, conventional detectors would exhibit a high residual error floor. We then invoke the Soft-Input Soft-Output (SISO) MIMO detectors for creating turbo-detected two- or three-stage concatenated SDM schemes and investigate their attainable performance in the light of their computational complexity. Finally, we introduce the powerful design tools of EXtrinsic Information Transfer (EXIT)-charts and characterize the achievable performance of the diverse near- capacity SISO detectors with the aid of EXIT charts

Digital Signal Processing for Optical Communications and Coherent LiDAR

Internet data traffic within data centre, access and metro networks is experiencing unprecedented growth driven by many data-intensive applications. Significant efforts have been devoted to the design and implementation of low-complexity digital signal processing (DSP) algorithms that are suitable for these short-reach optical links. In this thesis, a novel low-complexity frequency-domain (FD) multiple-input multiple-output (MIMO) equaliser with momentum-based gradient descent algorithm is proposed, capable of mitigating both static and dynamic impairments arising from the optical fibre. The proposed frequency-domain equaliser (FDE) also improves the robustness of the adaptive equaliser against feedback latencies which is the main disadvantage of FD adaptive equalisers under rapid channel variations. The development and maturity of optical fibre communication techniques over the past few decades have also been beneficial to many other fields, especially coherent light detection and ranging (LiDAR) techniques. Many applications of coherent LiDAR are also cost-sensitive, e.g., autonomous vehicles (AVs). Therefore, in this thesis, a low-cost and low-complexity single-photodiode-based coherent LiDAR system is investigated. The receiver sensitivity performance of this receiver architecture is assessed through both simulations and experiments, using two ranging waveforms known as double-sideband (DSB) amplitude-modulated chirp signal and single-sideband (SSB) frequency-modulated continuous-wave (FMCW) signals. Besides, the impact of laser phase noise on the ranging precision when operating within and beyond the laser coherence length is studied. Achievable ranging precision beyond the laser coherence length is quantified

Bacterial Foraging Based Channel Equalizers

A channel equalizer is one of the most important subsystems in any digital communication receiver. It is also the subsystem that consumes maximum computation time in the receiver. Traditionally maximum-likelihood sequence estimation (MLSE) was the most popular form of equalizer. Owing to non-stationary characteristics of the communication channel MLSE receivers perform poorly. Under these circumstances ‘Maximum A-posteriori Probability (MAP)’ receivers also called Bayesian receivers perform better. Natural selection tends to eliminate animals with poor “foraging strategies” and favor the propagation of genes of those animals that have successful foraging strategies since they are more likely to enjoy reproductive success. After many generations, poor foraging strategies are either eliminated or shaped into good ones (redesigned). Logically, such evolutionary principles have led scientists in the field of “foraging theory” to hypothesize that it is appropriate to model the activity of foraging as an optimization process. This thesis presents an investigation on design of bacterial foraging based channel equalizer for digital communication. Extensive simulation studies shows that the performance of the proposed receiver is close to optimal receiver for variety of channel conditions. The proposed receiver also provides near optimal performance when channel suffers from nonlinearities

Digital Signal Processing for Coherent Transceivers Employing Multilevel Formats

Digital coherent transceivers have revolutionized optical fiber communications due to their superior performance offered compared to intensity modulation and direct detection based alternatives. As systems employing digital coherent transceivers seek to approach their information theoretic capacity, the use of multilevel modulation formats combined with appropriate forward error correction becomes essential. Given this context, in this tutorial paper, we therefore explore the digital signal processing (DSP) utilized in a coherent transceiver with a focus on multilevel modulation formats. By way of an introduction, we open by discussing the photonic technology required to realize a coherent transceiver. After discussing this interface between the analog optical channel and the digital domain, the rest of the paper is focused on DSP. We begin by discussing algorithms that correct for imperfections in the optical to digital conversion, including IQ imbalance and timing skew. Next, we discuss channel equalization including means for their realization for both quasi-static and dynamic channel impairments. Synchronization algorithms that correct for the difference between the transmitter and receiver oscillators both optical and electrical are then discussed and issues associated with symbol decoding highlighted. For most of the cases, we start with polarization division multiplexed quadrature phase-shift keying (PDM-QPSK) format as a basis and then discuss the extension to allow for high order multilevel formats. Finally, we conclude by discussing some of the open research challenges in the field.This work was supported in part by the EU project ICONE (608099) and EPSRC through INSIGHT (EP/L026155/2) and UNLOC (EP/J017582/1)