Performance Investigation of High-Speed Train OFDM Systems under the Geometry-Based Channel Model

The high-speed of train (HST) in combination with the high carrier frequency of HST systems leads to the severe inter carrier interference (ICI) in the HST orthogonal frequency division multiplexing (HST-OFDM) systems. To avoid the complexity in OFDM receiver design for ICI eliminations, the OFDM system parameters such as symbol duration, signal bandwidth, and the number of subcarriers should be chosen appropriately. This paper aims to propose a process of HST-OFDM system performance investigation to determine these parameters in order to enhance spectral efficiency and meet a given quality-of-service (QoS) level. The signal-to-­interference-­plus-­noise ratio (SINR) has been used as a figure of merit to analyze the system performance instead of signal-to-noise ratio (SNR) as most of recent research studies. Firstly, using the non-stationary geometry-based stochastic HST channel model, the SINR of each subcarrier has been derived for different speeds of the train, signal bandwidths, and number of subcarriers. Consequently, the system capacity has been formulated as the sum of all the single channel capacity from each sub-carrier. The constraints on designing HST-OFDM system parameters have been thoughtfully analyzed using the obtained expressions of SINR and capacity. Finally, by analyzing the numerical results, the system parameters can be found for the design of HST-OFDM systems under different speeds of train. The proposed process can be used to provide hints to predict performance of HST communication systems before doing further high cost implementations as hardware designs

Channel Estimation and ICI Cancelation in Vehicular Channels of OFDM Wireless Communication Systems

Orthogonal frequency division multiplexing (OFDM) scheme increases bandwidth efficiency (BE) of data transmission and eliminates inter symbol interference (ISI). As a result, it has been widely used for wideband communication systems that have been developed during the past two decades and it can be a good candidate for the emerging communication systems such as fifth generation (5G) cellular networks with high carrier frequency and communication systems of high speed vehicles such as high speed trains (HSTs) and supersonic unmanned aircraft vehicles (UAVs). However, the employment of OFDM for those upcoming systems is challenging because of high Doppler shifts. High Doppler shift makes the wideband communication channel to be both frequency selective and time selective, doubly selective (DS), causes inter carrier interference (ICI) and destroys the orthogonality between the subcarriers of OFDM signal. In order to demodulate the signal in OFDM systems and mitigate ICIs, channel state information (CSI) is required. In this work, we deal with channel estimation (CE) and ICI cancellation in DS vehicular channels. The digitized model of the DS channels can be short and dense, or long and sparse. CE methods that perform well for short and dense channels are highly inefficient for long and sparse channels. As a result, for the latter type of channels, we proposed the employment of compressed sensing (CS) based schemes for estimating the channel. In addition, we extended our CE methods for multiple input multiple output (MIMO) scenarios. We evaluated the CE accuracy and data demodulation fidelity, along with the BE and computational complexity of our methods and compared the results with the previous CE procedures in different environments. The simulation results indicate that our proposed CE methods perform considerably better than the conventional CE schemes

Reliability of Trigonometric Transform-based Multi-Carrier Scheme

This work is looking for a new physical layer of a multi-carrier wireless communication system to be implemented in low complexity way, resorting to suitable fast transform. The work presents and assesses a scheme based on Discrete Trigonometric Transform with appending symmetric redundancy either in each or multiple consecutive transformed blocks. A receiver front-end filter is proposed to enforce whole symmetry in the channel impulse response, and bank of one tap filter per sub-carrier is applied as an equalizer in the transform domain. The behaviour of the transceiver is studied in the context of practical impairments like fading channel, carrier frequency offset and narrow band interference. Moreover, the performance is evaluated in contrast with the state of art methods by means of computer simulations, and it has been found that the new scheme improves robustness and reliability of communication signal, and record lower peak to average power ratio. The study demonstrates that front-end matched filter effectively performs frequency synchronization to compensate the carrier frequency offset in the received signal

Advanced index modulation techniques for future wireless networks

In the research study proposed in this Ph.D Thesis, we consider Index Modulation as a novel tool to enhance energy and spectral efficiencies for upcoming 5G networks, including wireless sensor networks and internet of things. In this vein, spatial modulation was proposed to enhance the capacity of wireless systems to partially achieve the capacity of MIMO systems but at lower cost, making it a technique that has attracted significant attention over the past few years. As such, SM schemes have been regarded as possible candidates for spectrum- and energy-efficient next generation MIMO systems. However, the implementation of the SM is also challenging because of its heavy dependence on channel characteristics, channel correlation, corrupted CSI and the need to have adequate spacing between antennas. Moreover, the SM requires multiple antennas at the transmitter which adds cost to the hardware implementation. In addition, the number of mapped bits in SM is limited by the physical size of the wireless device where only small number of antennas can be used. The switching time wasted by RF antenna switches adds to the complexity of the issue. In this Thesis, we study the drawbacks of SM in the articles indicated, namely Performance Comparison of Spatial Modulation Detectors Under Channel Impairments that is placed in the Appendix at the end of Thesis as it is a conference paper, and The Impact of Antenna Switching Time on Spatial Modulation that is put in Chapter 1. In the first article, we have shown that channel impairments have serious impacts on the BER performance and on the capacity of the SM system and that the SM is too sensitive to both imperfect and correlated channels. In the second article, we have demonstrated that the switching time defined as the time needed by the system to turn off an antenna and turn on another one, which is an inherent property of RF industrial switches used in SM systems, is in the order of nanoseconds and naturally influences the transmission rate of SM systems because of introducing systematic transmission gaps or pauses. Given the speed limitation of practical RF switches in performing transitions, antenna transition-based technologies like SM schemes are capped in terms of data rate performance. In fact, the effective data rate of SM will remain hostage to developments in industrial RF switches. This brings restrictions to the implementation and operation issues when extremely high data rates become a necessity. It is shown by the assemblage of our results that the switching time Tsw which is a requirement for transitions between antennas to happen, dictates restrictions on data rate, capacity and spectral efficiency of SM systems. Furthermore, we propose baseband non-hardware-based indexing modulation schemes based on frequency-index modulation, coherent chaotic modulation and non-coherent differential chaotic modulation schemes as potential alternatives to SM, that would also fit wireless sensor networks and internet of things applications. In this regard, we have proposed three articles. The first article which represents frequency index modulation is called Frequency Index Modulation for Low Complexity Low Energy Communication Networks and is placed in Chapter 2 of this Thesis. In this article, we explore a low complexity multi-user communication system based on frequency index modulation that suits Internet of Things (IoT) applications and we show that such a system would constitute an excellent candidate for wireless sensor applications, where it represents a simpler substitution for frequency-hopping (FH) based architectures, in which the hops carry extra bits. The third article which concerns coherent chaotic modulation is called Design of an Initial-Condition Index Chaos Shift Keying Modulation and is located in Chapter 3. In this article, an initial condition index chaos shift keying modulation is proposed. This design aims to increase the spectral and energy efficiencies to unprecedented levels. The proposed scheme exploits the initial conditions to generate different chaotic sequences to convey extra bits per transmission. In comparison to rival modulation schemes, the results obtained in the proposed work show a promising data rate boost and a competitive performance. The last article employs a non-coherent differential chaotic shift-key system named Permutation Index DCSK Modulation Technique for Secure Multi-User High-Data-Rate Communication Systems that is found in the Appendix. In this original design, where each data frame is divided into two time slots in which the reference chaotic signal is sent in the first time slot and a permuted replica of the reference signal multiplied by the modulating bit is sent in the second time slot, we target enhancing data security, energy and spectral efficiencies. Overall, in light of the high demands for bandwidth and energy efficiencies of futuristic systems, the suggested soft indexing mechanisms are successful candidates with promising results

Orthogonal frequency division multiplexing multiple-input multiple-output automotive radar with novel signal processing algorithms

Advanced driver assistance systems that actively assist the driver based on environment perception achieved significant advances in recent years. Along with this development, autonomous driving became a major research topic that aims ultimately at development of fully automated, driverless vehicles. Since such applications rely on environment perception, their ever increasing sophistication imposes growing demands on environmental sensors. Specifically, the need for reliable environment sensing necessitates the development of more sophisticated, high-performance radar sensors. A further vital challenge in terms of increased radar interference arises with the growing market penetration of the vehicular radar technology. To address these challenges, in many respects novel approaches and radar concepts are required. As the modulation is one of the key factors determining the radar performance, the research of new modulation schemes for automotive radar becomes essential. A topic that emerged in the last years is the radar operating with digitally generated waveforms based on orthogonal frequency division multiplexing (OFDM). Initially, the use of OFDM for radar was motivated by the combination of radar with communication via modulation of the radar waveform with communication data. Some subsequent works studied the use of OFDM as a modulation scheme in many different radar applications - from adaptive radar processing to synthetic aperture radar. This suggests that the flexibility provided by OFDM based digital generation of radar waveforms can potentially enable novel radar concepts that are well suited for future automotive radar systems. This thesis aims to explore the perspectives of OFDM as a modulation scheme for high-performance, robust and adaptive automotive radar. To this end, novel signal processing algorithms and OFDM based radar concepts are introduced in this work. The main focus of the thesis is on high-end automotive radar applications, while the applicability for real time implementation is of primary concern. The first part of this thesis focuses on signal processing algorithms for distance-velocity estimation. As a foundation for the algorithms presented in this thesis, a novel and rigorous signal model for OFDM radar is introduced. Based on this signal model, the limitations of the state-of-the-art OFDM radar signal processing are pointed out. To overcome these limitations, we propose two novel signal processing algorithms that build upon the conventional processing and extend it by more sophisticated modeling of the radar signal. The first method named all-cell Doppler compensation (ACDC) overcomes the Doppler sensitivity problem of OFDM radar. The core idea of this algorithm is the scenario-independent correction of Doppler shifts for the entire measurement signal. Since Doppler effect is a major concern for OFDM radar and influences the radar parametrization, its complete compensation opens new perspectives for OFDM radar. It not only achieves an improved, Doppler-independent performance, it also enables more favorable system parametrization. The second distance-velocity estimation algorithm introduced in this thesis addresses the issue of range and Doppler frequency migration due to the target’s motion during the measurement. For the conventional radar signal processing, these migration effects set an upper limit on the simultaneously achievable distance and velocity resolution. The proposed method named all-cell migration compensation (ACMC) extends the underlying OFDM radar signal model to account for the target motion. As a result, the effect of migration is compensated implicitly for the entire radar measurement, which leads to an improved distance and velocity resolution. Simulations show the effectiveness of the proposed algorithms in overcoming the two major limitations of the conventional OFDM radar signal processing. As multiple-input multiple-output (MIMO) radar is a well-established technology for improving the direction-of-arrival (DOA) estimation, the second part of this work studies the multiplexing methods for OFDM radar that enable simultaneous use of multiple transmit antennas for MIMO radar processing. After discussing the drawbacks of known multiplexing methods, we introduce two advanced multiplexing schemes for OFDM-MIMO radar based on non-equidistant interleaving of OFDM subcarriers. These multiplexing approaches exploit the multicarrier structure of OFDM for generation of orthogonal waveforms that enable a simultaneous operation of multiple MIMO channels occupying the same bandwidth. The primary advantage of these methods is that despite multiplexing they maintain all original radar parameters (resolution and unambiguous range in distance and velocity) for each individual MIMO channel. To obtain favorable interleaving patterns with low sidelobes, we propose an optimization approach based on genetic algorithms. Furthermore, to overcome the drawback of increased sidelobes due to subcarrier interleaving, we study the applicability of sparse processing methods for the distance-velocity estimation from measurements of non-equidistantly interleaved OFDM-MIMO radar. We introduce a novel sparsity based frequency estimation algorithm designed for this purpose. The third topic addressed in this work is the robustness of OFDM radar to interference from other radar sensors. In this part of the work we study the interference robustness of OFDM radar and propose novel interference mitigation techniques. The first interference suppression algorithm we introduce exploits the robustness of OFDM to narrowband interference by dropping subcarriers strongly corrupted by interference from evaluation. To avoid increase of sidelobes due to missing subcarriers, their values are reconstructed from the neighboring ones based on linear prediction methods. As a further measure for increasing the interference robustness in a more universal manner, we propose the extension of OFDM radar with cognitive features. We introduce the general concept of cognitive radar that is capable of adapting to the current spectral situation for avoiding interference. Our work focuses mainly on waveform adaptation techniques; we propose adaptation methods that allow dynamic interference avoidance without affecting adversely the estimation performance. The final part of this work focuses on prototypical implementation of OFDM-MIMO radar. With the constructed prototype, the feasibility of OFDM for high-performance radar applications is demonstrated. Furthermore, based on this radar prototype the algorithms presented in this thesis are validated experimentally. The measurements confirm the applicability of the proposed algorithms and concepts for real world automotive radar implementations

Robust frequency-domain turbo equalization for multiple-input multiple-output (MIMO) wireless communications

This dissertation investigates single carrier frequency-domain equalization (SC-FDE) with multiple-input multiple-output (MIMO) channels for radio frequency (RF) and underwater acoustic (UWA) wireless communications. It consists of five papers, selected from a total of 13 publications. Each paper focuses on a specific technical challenge of the SC-FDE MIMO system. The first paper proposes an improved frequency-domain channel estimation method based on interpolation to track fast time-varying fading channels using a small amount of training symbols in a large data block. The second paper addresses the carrier frequency offset (CFO) problem using a new group-wise phase estimation and compensation algorithm to combat phase distortion caused by CFOs, rather than to explicitly estimate the CFOs. The third paper incorporates layered frequency-domain equalization with the phase correction algorithm to combat the fast phase rotation in coherent communications. In the fourth paper, the frequency-domain equalization combined with the turbo principle and soft successive interference cancelation (SSIC) is proposed to further improve the bit error rate (BER) performance of UWA communications. In the fifth paper, a bandwidth-efficient SC-FDE scheme incorporating decision-directed channel estimation is proposed for UWA MIMO communication systems. The proposed algorithms are tested by extensive computer simulations and real ocean experiment data. The results demonstrate significant performance improvements in four aspects: improved channel tracking, reduced BER, reduced computational complexity, and enhanced data efficiency --Abstract, page iv