Single carrier frequency domain equalization and energy efficiency optimization for MIMO cognitive radio.

This dissertation studies two separate topics in wireless communication systems. One topic focuses on the Single Carrier Frequency Domain Equalization (SC-FDE), which is a promising technique to mitigate the multipath effect in the broadband wireless communication. Another topic targets on the energy efficiency optimization in a multiple input multiple output (MIMO) cognitive radio network. For SC-FDE, the conventional linear receivers suffer from the noise amplification in deep fading channel. To overcome this, a fractional spaced frequency domain (FSFD) receiver based on frequency domain oversampling (FDO) is proposed for SC-FDE to improve the performance of the linear receiver under deep fading channels. By properly designing the guard interval, a larger sized Discrete Fourier Transform (DFT) is equipped to oversample the received signal in frequency domain. Thus, the effect of frequency-selective fading can still be eliminated by a one-tap frequency domain filter. Two types of FSFD receivers are proposed based on the least square (LS) and minimum mean square error (MMSE) criterion. Both the semi-analytical analysis and simulation results are given to evaluate the performance of the proposed receivers. Another challenge in SC-FDE is the in-phase/quadrature phase (IQ) imbalance caused by unideal radio frequency (RF) front-end at the transmitter or the receiver. Most existing works in single carrier transmission employ linear compensation methods, such as LS and MMSE, to combat the interference caused by IQ imbalance. Actually, for single carrier transmissions, it is possible for the receivers to adopt advanced nonlinear compensation methods to improve the system performance under IQ imbalance. For such purpose, an iterative decision feedback receiver is proposed to compensate the IQ imbalance caused by unideal RF front-end in SC-FDE. Numerical results show that the proposed iterative IQ imbalance compensation can significantly improve the performance of SC-FDE system under IQ imbalance compared with the conventional linear method. For the energy efficiency optimization in the MIMO cognitive radio network, multiple secondary users (SUs) coexisting with a primary user (PU) adjust their antenna radiation patterns and power allocations to achieve energy-efficient transmission. The optimization problems are formulated to maximize the energy efficiency of a cognitive radio network in both distributed and centralized point of views. Also, constraints on the transmission power and the interference to PU are introduced to protect the PU’s transmission. In order to solve the non-convex optimization problems, convex relaxations are used to transform them into equivalent problems with better tractability. Then three optimization algorithms are proposed to find the energy-efficient transmission strategies. Simulation results show that the proposed energy-efficiency optimization algorithms outperform the existing algorithms

Non-Orthogonal Signal and System Design for Wireless Communications

The thesis presents research in non-orthogonal multi-carrier signals, in which: (i) a new signal format termed truncated orthogonal frequency division multiplexing (TOFDM) is proposed to improve data rates in wireless communication systems, such as those used in mobile/cellular systems and wireless local area networks (LANs), and (ii) a new design and experimental implementation of a real-time spectrally efficient frequency division multiplexing (SEFDM) system are reported. This research proposes a modified version of the orthogonal frequency division multiplexing (OFDM) format, obtained by truncating OFDM symbols in the time-domain. In TOFDM, subcarriers are no longer orthogonally packed in the frequency-domain as time samples are only partially transmitted, leading to improved spectral efficiency. In this work, (i) analytical expressions are derived for the newly proposed TOFDM signal, followed by (ii) interference analysis, (iii) systems design for uncoded and coded schemes, (iv) experimental implementation and (v) performance evaluation of the new proposed signal and system, with comparisons to conventional OFDM systems. Results indicate that signals can be recovered with truncated symbol transmission. Based on the TOFDM principle, a new receiving technique, termed partial symbol recovery (PSR), is designed and implemented in software de ned radio (SDR), that allows efficient operation of two users for overlapping data, in wireless communication systems operating with collisions. The PSR technique is based on recovery of collision-free partial OFDM symbols, followed by the reconstruction of complete symbols to recover progressively the frames of two users suffering collisions. The system is evaluated in a testbed of 12-nodes using SDR platforms. The thesis also proposes channel estimation and equalization technique for non-orthogonal signals in 5G scenarios, using an orthogonal demodulator and zero padding. Finally, the implementation of complete SEFDM systems in real-time is investigated and described in detail

Optical OFDM based on the fractional Fourier transform for an indoor VLC system

The fractional Fourier transform (FRFT), which is a family of linear transformations generalizing the classical Fourier transform, has been used in the fields of filter design, signal processing, phase retrieval, and pattern recognition due to its unique properties. The FRFT of a signal can be interpreted as a decomposition of the signal in terms of chirps. In this paper, for the first time, to the best of our knowledge, we introduce an optical FRFT (OFRFT)based orthogonal frequency division multiplexing (OFDM) visible light communications (VLC) system and compare numerical results with a direct current-biased optical (DCO)-OFDM system. First, the optimal fractional order is calculated to improve the performance of the proposed system by minimizing the bit error rate (BER). The numerical results show that OFRFT-OFDM with the optimal fractional order offers a significantly improved BER performance compared with DCO-OFDM under the same computational complexity and spectral efficiency. In addition, the peak to average power ratio, which is an issue in light emitting diode-based VLC systems, is reduced by <1 dB using OFRFT-OFDM for the same BER compared with DCO-OFDM

Waveform Advancements and Synchronization Techniques for Generalized Frequency Division Multiplexing

To enable a new level of connectivity among machines as well as between people and machines, future wireless applications will demand higher requirements on data rates, response time, and reliability from the communication system. This will lead to a different system design, comprising a wide range of deployment scenarios. One important aspect is the evolution of physical layer (PHY), specifically the waveform modulation. The novel generalized frequency division multiplexing (GFDM) technique is a prominent proposal for a flexible block filtered multicarrier modulation. This thesis introduces an advanced GFDM concept that enables the emulation of other prominent waveform candidates in scenarios where they perform best. Hence, a unique modulation framework is presented that is capable of addressing a wide range of scenarios and to upgrade the PHY for 5G networks. In particular, for a subset of system parameters of the modulation framework, the problem of symbol time offset (STO) and carrier frequency offset (CFO) estimation is investigated and synchronization approaches, which can operate in burst and continuous transmissions, are designed. The first part of this work presents the modulation principles of prominent 5G candidate waveforms and then focuses on the GFDM basic and advanced attributes. The GFDM concept is extended towards the use of OQAM, introducing the novel frequency-shift OQAM-GFDM, and a new low complexity model based on signal processing carried out in the time domain. A new prototype filter proposal highlights the benefits obtained in terms of a reduced out-of-band (OOB) radiation and more attractive hardware implementation cost. With proper parameterization of the advanced GFDM, the achieved gains are applicable to other filtered OFDM waveforms. In the second part, a search approach for estimating STO and CFO in GFDM is evaluated. A self-interference metric is proposed to quantify the effective SNR penalty caused by the residual time and frequency misalignment or intrinsic inter-symbol interference (ISI) and inter-carrier interference (ICI) for arbitrary pulse shape design in GFDM. In particular, the ICI can be used as a non-data aided approach for frequency estimation. Then, GFDM training sequences, defined either as an isolated preamble or embedded as a midamble or pseudo-circular pre/post-amble, are designed. Simulations show better OOB emission and good estimation results, either comparable or superior, to state-of-the-art OFDM system in wireless channels

Algorithms for Blind Equalization Based on Relative Gradient and Toeplitz Constraints

Blind Equalization (BE) refers to the problem of recovering the source symbol sequence from a signal received through a channel in the presence of additive noise and channel distortion, when the channel response is unknown and a training sequence is not accessible. To achieve BE, statistical or constellation properties of the source symbols are exploited. In BE algorithms, two main concerns are convergence speed and computational complexity. In this dissertation, we explore the application of relative gradient for equalizer adaptation with a structure constraint on the equalizer matrix, for fast convergence without excessive computational complexity. We model blind equalization with symbol-rate sampling as a blind source separation (BSS) problem and study two single-carrier transmission schemes, specifically block transmission with guard intervals and continuous transmission. Under either scheme, blind equalization can be achieved using independent component analysis (ICA) algorithms with a Toeplitz or circulant constraint on the structure of the separating matrix. We also develop relative gradient versions of the widely used Bussgang-type algorithms. Processing the equalizer outputs in sliding blocks, we are able to use the relative gradient for adaptation of the Toeplitz constrained equalizer matrix. The use of relative gradient makes the Bussgang condition appear explicitly in the matrix adaptation and speeds up convergence. For the ICA-based and Bussgang-type algorithms with relative gradient and matrix structure constraints, we simplify the matrix adaptations to obtain equivalent equalizer vector adaptations for reduced computational cost. Efficient implementations with fast Fourier transform, and approximation schemes for the cross-correlation terms used in the adaptation, are shown to further reduce computational cost. We also consider the use of a relative gradient algorithm for channel shortening in orthogonal frequency division multiplexing (OFDM) systems. The redundancy of the cyclic prefix symbols is used to shorten a channel with a long impulse response. We show interesting preliminary results for a shortening algorithm based on relative gradient