Estimation and detection techniques for doubly-selective channels in wireless communications

A fundamental problem in communications is the estimation of the channel. The signal transmitted through a communications channel undergoes distortions so that it is often received in an unrecognizable form at the receiver. The receiver must expend significant signal processing effort in order to be able to decode the transmit signal from this received signal. This signal processing requires knowledge of how the channel distorts the transmit signal, i.e. channel knowledge. To maintain a reliable link, the channel must be estimated and tracked by the receiver. The estimation of the channel at the receiver often proceeds by transmission of a signal called the 'pilot' which is known a priori to the receiver. The receiver forms its estimate of the transmitted signal based on how this known signal is distorted by the channel, i.e. it estimates the channel from the received signal and the pilot. This design of the pilot is a function of the modulation, the type of training and the channel. [Continues.

Advanced transceivers for spectrally-efficient communications

In this thesis, we will consider techniques to improve the spectral efficiency of digital communication systems, operating on the whole transceiver scheme. First, we will focus on receiver schemes having detection algorithms with a complexity constraint. We will optimize the parameters of the reduced detector with the aim of maximizing the achievable information rate. Namely, we will adopt the channel shortening technique. Then, we will focus on a technique that is getting very popular in the last years (although presented for the first time in 1975): faster-than-Nyquist signaling, and its extension which is time packing. Time packing is a very simple technique that consists in introducing intersymbol interference on purpose with the aim of increasing the spectral efficiency of finite order constellations. Finally, in the last chapters we will combine all the presented techniques, and we will consider their application to satellite channels.Comment: PhD Thesi

Reduced Receivers for Faster-than-Nyquist Signaling and General Linear Channels

Fast and reliable data transmission together with high bandwidth efficiency are important design aspects in a modern digital communication system. Many different approaches exist but in this thesis bandwidth efficiency is obtained by increasing the data transmission rate with the faster-than-Nyquist (FTN) framework while keeping a fixed power spectral density (PSD). In FTN consecutive information carrying symbols can overlap in time and in that way introduce a controlled amount of intentional intersymbol interference (ISI). This technique was introduced already in 1975 by Mazo and has since then been extended in many directions. Since the ISI stemming from practical FTN signaling can be of significant duration, optimum detection with traditional methods is often prohibitively complex, and alternative equalization methods with acceptable complexity-performance tradeoffs are needed. The key objective of this thesis is therefore to design reduced-complexity receivers for FTN and general linear channels that achieve optimal or near-optimal performance. Although the performance of a detector can be measured by several means, this thesis is restricted to bit error rate (BER) and mutual information results. FTN signaling is applied in two ways: As a separate uncoded narrowband communication system or in a coded scenario consisting of a convolutional encoder, interleaver and the inner ISI mechanism in serial concatenation. Turbo equalization where soft information in the form of log likelihood ratios (LLRs) is exchanged between the equalizer and the decoder is a commonly used decoding technique for coded FTN signals. The first part of the thesis considers receivers and arising stability problems when working within the white noise constraint. New M-BCJR algorithms for turbo equalization are proposed and compared to reduced-trellis VA and BCJR benchmarks based on an offset label idea. By adding a third low-complexity M-BCJR recursion, LLR quality is improved for practical values of M. M here measures the reduced number of BCJR computations for each data symbol. An improvement of the minimum phase conversion that sharpens the focus of the ISI model energy is proposed. When combined with a delayed and slightly mismatched receiver, the decoding allows a smaller M without significant loss in BER. The second part analyzes the effect of the internal metric calculations on the performance of Forney- and Ungerboeck-based reduced-complexity equalizers of the M-algorithm type for both ISI and multiple-input multiple-output (MIMO) channels. Even though the final output of a full-complexity equalizer is identical for both models, the internal metric calculations are in general different. Hence, suboptimum methods need not produce the same final output. Additionally, new models working in between the two extremes are proposed and evaluated. Note that the choice of observation model does not impact the detection complexity as the underlying algorithm is unaltered. The last part of the thesis is devoted to a different complexity reducing approach. Optimal channel shortening detectors for linear channels are optimized from an information theoretical perspective. The achievable information rates of the shortened models as well as closed form expressions for all components of the optimal detector of the class are derived. The framework used in this thesis is more general than what has been previously used within the area

Design Techniques for High Performance Wireline Communication and Security Systems

As the amount of data traffic grows exponentially on the internet, towards thousands of exabytes by 2020, high performance and high efficiency communication and security solutions are constantly in high demand, calling for innovative solutions. Within server communication dominates todays network data transfer, outweighing between-server and server-to-user data transfer by an order of magnitude. Solutions for within-server communication tend to be very wideband, i.e. on the order of tens of gigahertz, equalizers are widely deployed to provide extended bandwidth at reasonable cost. However, using equalizers typically costs the available signal-to-noise ratio (SNR) at the receiver side. What is worse is that the SNR available at the channel becomes worse as data rate increases, making it harder to meet the tight constraint on error rate, delay, and power consumption. In this thesis, two equalization solutions that address optimal equalizer implementations are discussed. One is a low-power high-speed maximum likelihood sequence detection (MLSD) that achieves record energy efficiency, below 10 pico-Joule per bit. The other one is a phase-shaping equalizer design that suppresses inter-symbol interference at almost zero cost of SNR. The growing amount of communication use also challenges the design of security subsystems, and the emerging need for post-quantum security adds to the difficulties. Most of currently deployed cryptographic primitives rely on the hardness of discrete logarithms that could potentially be solved efficiently with a powerful enough quantum computer. Efficient post-quantum encryption solutions have become of substantial value. In this thesis a fast and efficient lattice encryption application-specific integrated circuit is presented that surpasses the energy efficiency of embedded processors by 4 orders of magnitude.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146092/1/shisong_1.pd

Discrete Time Systems

Discrete-Time Systems comprehend an important and broad research field. The consolidation of digital-based computational means in the present, pushes a technological tool into the field with a tremendous impact in areas like Control, Signal Processing, Communications, System Modelling and related Applications. This book attempts to give a scope in the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications. We think that the contribution of the book enlarges the field of the Discrete-Time Systems with signification in the present state-of-the-art. Despite the vertiginous advance in the field, we also believe that the topics described here allow us also to look through some main tendencies in the next years in the research area

Optimal Channel Shortener Design for Reduced-State Soft-Output Viterbi Equalizer in Single-Carrier Systems

We consider optimal channel shortener design for reduced-state soft-output Viterbi equalizer (RS-SOVE) in singlecarrier (SC) systems. To use RS-SOVE, three receiver filters need to be designed: a prefilter, a target response and a feedback filter. The collection of these three filters are commonly referred to as the “channel shortener”. Conventionally, the channel shortener is designed to transform an intersymbol interference (ISI) channel into an equivalent minimum-phase equivalent form. In this paper, we design the channel shortener to maximize a mutual information lower bound (MILB) based on a mismatched detection model. By taking the decision-feedback quality in the RS-SOVE into consideration, the prefilter and feedback filter are found in closed forms, while the target response is optimized via a gradient-ascending approach with the gradient explicitly derived. The information theoretical properties of the proposed channel shortener are analyzed. Moreover, we show through numerical results that, the proposed channel shortener design achieves superior detection performance compared to previous channel shortener designs at medium and high code-rates