Wireless receiver designs: from information theory to VLSI implementation

Receiver design, especially equalizer design, in communications is a major concern in both academia and industry. It is a problem with both theoretical challenges and severe implementation hurdles. While much research has been focused on reducing complexity for optimal or near-optimal schemes, it is still common practice in industry to use simple techniques (such as linear equalization) that are generally significantly inferior. Although digital signal processing (DSP) technologies have been applied to wireless communications to enhance the throughput, the users' demands for more data and higher rate have revealed new challenges. For example, to collect the diversity and combat fading channels, in addition to the transmitter designs that enable the diversity, we also require the receiver to be able to collect the prepared diversity. Most wireless transmissions can be modeled as a linear block transmission system. Given a linear block transmission model assumption, maximum likelihood equalizers (MLEs) or near-ML decoders have been adopted at the receiver to collect diversity which is an important metric for performance, but these decoders exhibit high complexity. To reduce the decoding complexity, low-complexity equalizers, such as linear equalizers (LEs) and decision feedback equalizers (DFEs) are often adopted. These methods, however, may not utilize the diversity enabled by the transmitter and as a result have degraded performance compared to MLEs. In this dissertation, we will present efficient receiver designs that achieve low bit-error-rate (BER), high mutual information, and low decoding complexity. Our approach is to first investigate the error performance and mutual information of existing low-complexity equalizers to reveal the fundamental condition to achieve full diversity with LEs. We show that the fundamental condition for LEs to collect the same (outage) diversity as MLE is that the channels need to be constrained within a certain distance from orthogonality. The orthogonality deficiency (od) is adopted to quantify the distance of channels to orthogonality while other existing metrics are also introduced and compared. To meet the fundamental condition and achieve full diversity, a hybrid equalizer framework is proposed. The performance-complexity trade-off of hybrid equalizers is quantified by deriving the distribution of od. Another approach is to apply lattice reduction (LR) techniques to improve the ``quality' of channel matrices. We present two widely adopted LR methods in wireless communications, the Lenstra-Lenstra-Lovasz (LLL) algorithm [51] and Seysen's algorithm (SA), by providing detailed descriptions and pseudo codes. The properties of output matrices of the LLL algorithm and SA are also quantified. Furthermore, other LR algorithms are also briefly introduced. After introducing LR algorithms, we show how to adopt them into the wireless communication decoding process by presenting LR-aided hard-output detectors and LR-aided soft-output detectors for coded systems, respectively. We also analyze the performance of proposed efficient receivers from the perspective of diversity, mutual information, and complexity. We prove that LR techniques help to restore the diversity of low-complexity equalizers without increasing the complexity significantly. When it comes to practical systems and simulation tool, e.g., MATLAB, only finite bits are adopted to represent numbers. Therefore, we revisit the diversity analysis for finite-bit represented systems. We illustrate that the diversity of MLE for systems with finite-bit representation is determined by the number of non-vanishing eigenvalues. It is also shown that although theoretically LR-aided detectors collect the same diversity as MLE in the real/complex field, it may show different diversity orders when finite-bit representation exists. Finally, the VLSI implementation of the complex LLL algorithms is provided to verify the practicality of our proposed designs.Ph.D.Committee Chair: Ma, Xiaoli; Committee Member: Anderson, David; Committee Member: Barry, John; Committee Member: Chen, Xu-Yan; Committee Member: Kornegay, Kevi

Proceedings of the Fall 1995 Advanced Digital Communication Systems

Coordinated Science Laboratory was formerly known as Control Systems Laborator

Electronic processing for optical communication systems

I sistemi di comunicazione in fibra ottica risentono di diversi tipi di disturbi, quali ad esempio la dispersione cromatica e la dispersione dei modi di polarizzazione. La compensazione ottica di tali disturbi è possibile ma complessa e costosa, mentre le tecniche di elaborazione elettronica del segnale presentano diversi vantaggi, semplicità, costo, adattabilità. L'equalizzazione elettronica e la strategia di rivelazione di sequenza a massima verosimiglianza rappresentano soluzioni efficaci e realizzabili con semplici modulazioni di ampiezza e anche con più avanzate modulazioni di fase e fase-ampiezza.Optical communication systems are suffering from several typical impairments, chromatic dispersion and polarization mode dispersion. Optical compensation of such impairments is possible but it is technological demanding and expensive, whereas electronic signal processing presents many advantages, implementation ease, cost-efficiency, adaptability. Electronic equalization and maximum likelihood sequence detection represent effective and feasible solutions for simple amplitude modulation formats as well as for more advanced phase and phase-amplitude modulation formats

Digital signal processing techniques for fiber nonlinearity compensation in coherent optical communication systems

The capacity of long-haul coherent optical communication systems is limited by the detrimental effects of fiber Kerr nonlinearity. The power-dependent nature of the Kerr nonlinearity restricts the maximum launch power into the fiber. That results in the reduction of the optical signal-to-noise ratio at the receiver; thereby, the maximum transmission reach is limited. Over the last few decades, several digital signal processing (DSP) techniques have been proposed to mitigate the effects of fiber nonlinearity, for example, digital back-propagation (DBP), perturbation based nonlinearity compensation (PB-NLC), and phase-conjugated twin wave (PCTW). However, low-complexity and spectrally efficient DSP-based fiber nonlinearity mitigation schemes for long-haul transmission systems are yet to be developed. In this thesis, we focus on the computationally efficient DSP-based techniques that can help to combat various sources of fiber nonlinearity in long-haul coherent optical communication systems. With this aim, we propose a linear time/polarization coded digital phase conjugation (DPC) technique for the mitigation of fiber nonlinearity that doubles the spectral efficiency obtained in the PCTW technique. In addition, we propose to investigate the impact of random polarization effects, like polarization-dependent loss and polarization mode dispersion, on the performance of the linear-coded DPC techniques. We also propose a joint technique that combines single-channel DBP with the PCTW technique. We show that the proposed scheme is computationally efficient and achieves similar performance as multi-channel DBP in wavelength division multiplexed superchannel systems. The regular perturbation (RP) series used to analytically approximate the solution of the nonlinear Schrödinger equation (NLSE) has a serious energy divergence problem when truncated to the first-order. Recent results on the transmission of high data-rate optical signals reveal that the nonlinearity compensation performance of the first-order PB-NLC technique decreases as the product of the transmission distance and launch power increases. The enhanced RP (ERP) method can improve the accuracy of the first-order RP approximation by partially solving the energy divergence problem. On this ground, we propose an ERP-based nonlinearity compensation technique to compensate for the fiber nonlinearity in a polarization-division multiplexed dispersion unmanaged optical communication system. Another possible solution to improve the accuracy of the PB-NLC technique is to increase the order of the RP solution. Based on this idea, we propose to extend the first-order solution of the NLSE to the second-order to improve the nonlinearity compensation performance of the PB-NLC technique. Following that, we investigate a few simplifying assumptions to reduce the implementation complexity of the proposed second-order PB-NLC technique