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

Pilot design for channel estimation in Doubly Selective Channel

We consider pilot sequence designs for channel estimation in doubly-selective channels (DSC) which are modeled using the basis expansion model (BEM) approach. We propose to use pilot sequences (instead of impulse pilots) to reduce the peak-to-average power ratio (PAPR) of the transmitted signal. Specifically, by analysing the mean square error (MSE) metric of the BEM channel coefficients, we propose the use of Huffman sequences to reduce the PAPR during channel estimation. Furthermore, we show that a systematic re-arrangement of the pilot sequence within the transmission frame can significantly improve the channel estimation performance of the system, as compared to the conventional periodic pilot placement

Pilot Design for Enhanced Channel Estimation in Doubly Selective Channels

This paper investigates pilot design for enhanced channel estimation in single carrier communication systems over doubly-selective channels (DSC). Our contribution is twofold: first, we propose to use Huffman sequences as pilot clusters with low peak-to-average power ratio (PAPR), yet with good channel estimation performance when periodic pilot placement is adopted; second, we propose a low-complexity pilot placement strategy based on the analysis of the complex-exponential basis expansion model (CE-BEM) of the DSC. The latter leads to improved channel estimation performance with useful insights for pilot placement

Third-order Complex Amplitudes Tracking Loop for Slow Flat Fading Channel On-Line Estimation

12 pagesInternational audienceThis paper deals with channel estimation in tracking mode over a flat Rayleigh fading channel with Jakes' Doppler Spectrum. Many estimation algorithms exploit the time-domain correlation of the channel by employing a Kalman filter based on a first-order (or sometimes second-order) approximation model of the time-varying channel. However, the nature of the approximation model itself degrades the estimation performance for slow to moderate varying channel scenarios. Furthermore, the Kalman-based algorithms exhibit a certain complexity. Hence, a different model and approach has been investigated in this work to tackle all of these issues. A novel PLL-structured third-order tracking loop estimator with a low complexity is proposed. The connection between a steady-state Kalman filter based on a random walk approximation model and the proposed estimator is first established. Then, a sub-optimal mean-squared-error (MSE) is given in a closed-form expression as a function of the tracking loop parameters. The parameters that minimize this sub-optimal MSE are also given in a closed-form expression. The asymptotic MSE and Bit-Error-Ratio (BER) simulation results demonstrate that the proposed estimator outperforms the first and second order Kalman-based filters reported in literature. The robustness of the proposed estimator is also verified by a mismatch simulation

Frequency-domain receiver design for doubly-selective channels

This work is devoted to the broadband wireless transmission techniques, which are serious candidates to be implemented in future broadband wireless and cellular systems, aiming at providing high and reliable data transmission and concomitantly high mobility. In order to cope with doubly-selective channels, receiver structures based on OFDM and SC-FDE block transmission techniques, are proposed, which allow cost-effective implementations, using FFT-based signal processing. The first subject to be addressed is the impact of the number of multipath components, and the diversity order, on the asymptotic performance of OFDM and SC-FDE, in uncoded and for different channel coding schemes. The obtained results show that the number of relevant separable multipath components is a key element that influences the performance of OFDM and SC-FDE schemes. Then, the improved estimation and detection performance of OFDM-based broadcasting systems, is introduced employing SFN (Single Frequency Network) operation. An initial coarse channel is obtained with resort to low-power training sequences estimation, and an iterative receiver with joint detection and channel estimation is presented. The achieved results have shown very good performance, close to that with perfect channel estimation. The next topic is related to SFN systems, devoting special attention to time-distortion effects inherent to these networks. Typically, the SFN broadcast wireless systems employ OFDM schemes to cope with severely time-dispersive channels. However, frequency errors, due to CFO, compromises the orthogonality between subcarriers. As an alternative approach, the possibility of using SC-FDE schemes (characterized by reduced envelope fluctuations and higher robustness to carrier frequency errors) is evaluated, and a technique, employing joint CFO estimation and compensation over the severe time-distortion effects, is proposed. Finally, broadband mobile wireless systems, in which the relative motion between the transmitter and receiver induces Doppler shift which is different or each propagation path, is considered, depending on the angle of incidence of that path in relation to the direction of travel. This represents a severe impairment in wireless digital communications systems, since that multipath propagation combined with the Doppler effects, lead to drastic and unpredictable fluctuations of the envelope of the received signal, severely affecting the detection performance. The channel variations due this effect are very difficult to estimate and compensate. In this work we propose a set of SC-FDE iterative receivers implementing efficient estimation and tracking techniques. The performance results show that the proposed receivers have very good performance, even in the presence of significant Doppler spread between the different groups of multipath components

Low-Complexity Algorithms for Channel Estimation in Optimised Pilot-Assisted Wireless OFDM Systems

Orthogonal frequency division multiplexing (OFDM) has recently become a dominant transmission technology considered for the next generation fixed and mobile broadband wireless communication systems. OFDM has an advantage of lessening the severe effects of the frequency-selective (multipath) fading due to the band splitting into relatively flat fading subchannels, and allows for low-complexity transceiver implementation based on the fast Fourier transform algorithms. Combining OFDM modulation with multilevel frequency-domain symbol mapping (e.g., QAM) and spatial multiplexing (SM) over the multiple-input multiple-output (MIMO) channels, can theoretically achieve near Shannon capacity of the communication link. However, the high-rate and spectrumefficient system implementation requires coherent detection at the receiving end that is possible only when accurate channel state information (CSI) is available. Since in practice, the response of the wireless channel is unknown and is subject to random variation with time, the receiver typically employs a channel estimator for CSI acquisition. The channel response information retrieved by the estimator is then used by the data detector and can also be fed back to the transmitter by means of in-band or out-of-band signalling, so the latter could adapt power loading, modulation and coding parameters according to the channel conditions. Thus, design of an accurate and robust channel estimator is a crucial requirement for reliable communication through the channel, which is selective in time and frequency. In a MIMO configuration, a separate channel estimator has to be associated with each transmit/receive antenna pair, making the estimation algorithm complexity a primary concern. Pilot-assisted methods, relying on the insertion of reference symbols in certain frequencies and time slots, have been found attractive for identification of the doubly-selective radio channels from both the complexity and performance standpoint. In this dissertation, a family of the reduced-complexity estimators for the single and multiple-antenna OFDM systems is developed. The estimators are based on the transform-domain processing and have the same order of computational complexity, irrespective of the number of pilot subcarriers and their positioning. The common estimator structure represents a cascade of successive small-dimension filtering modules. The number of modules, as well as their order inside the cascade, is determined by the class of the estimator (one or two-dimensional) and availability of the channel statistics (correlation and signal-to-noise power ratio). For fine precision estimation in the multipath channels with statistics not known a priori, we propose recursive design of the filtering modules. Simulation results show that in the steady state, performance of the recursive estimators approaches that of their theoretical counterparts, which are optimal in the minimum mean square error (MMSE) sense. In contrast to the majority of the channel estimators developed so far, our modular-type architectures are suitable for the reconfigurable OFDM transceivers where the actual channel conditions influence the decision of what class of filtering algorithm to use, and how to allot pilot subcarrier positions in the band. In the pilot-assisted transmissions, channel estimation and detection are performed separately from each other over the distinct subcarrier sets. The estimator output is used only to construct the detector transform, but not as the detector input. Since performance of both channel estimation and detection depends on the signal-to-noise power vi ratio (SNR) at the corresponding subcarriers, there is a dilemma of the optimal power allocation between the data and the pilot symbols as these are conflicting requirements under the total transmit power constraint. The problem is exacerbated by the variety of channel estimators. Each kind of estimation algorithm is characterised by its own SNR gain, which in general can vary depending on the channel correlation. In this dissertation, we optimise pilot-data power allocation for the case of developed low-complexity one and two-dimensional MMSE channel estimators. The resultant contribution is manifested by the closed-form analytical expressions of the upper bound (suboptimal approximate value) on the optimal pilot-to-data power ratio (PDR) as a function of a number of design parameters (number of subcarriers, number of pilots, number of transmit antennas, effective order of the channel model, maximum Doppler shift, SNR, etc.). The resultant PDR equations can be applied to the MIMO-OFDM systems with arbitrary arrangement of the pilot subcarriers, operating in an arbitrary multipath fading channel. These properties and relatively simple functional representation of the derived analytical PDR expressions are designated to alleviate the challenging task of on-the-fly optimisation of the adaptive SM-MIMO-OFDM system, which is capable of adjusting transmit signal configuration (e.g., block length, number of pilot subcarriers or antennas) according to the established channel conditions

Analysis of data-aided channel tracking for hybrid massive MIMO systems in millimeter wave communications

As the data traffic in future wireless communications will explosively grow up to 1000 folds by the deployment of 5G, several technologies are emerging to satisfy this demand, including massive multiple-input multiple-output (MIMO), millimeter wave(mmWave) communications, Non-Orthogonal Multiple Access (NOMA), etc. The combination of millimeter wave communication and massive MIMO is a promising solution since it can provide tens of GHz bandwidth by fundamentally exploring higher unoccupied spectrum resources. As the wavelength of higher frequency shrinks, it is possible to design more compact antenna array with a very large number of antennas. However, this will cause enormous hardware cost, energy consumption and computation complexity of decent RF(Radio Frequency) chains. To this end, spatial sparsity is widely explored to enable hybrid mmWave massive MIMO systems with limited RF chains to achieve high spectral and energy efficiency. On the other hand, channel estimation problem for systems with limited RF chains is quite challenging due to the unaffordable overhead. To be specific, the conventional pilot-based channel estimation requires to repeatedly transmit the same pilot because only a limited number of antennas will be activated for each time slot. Therefore, it consumes a huge amount of temporal and spectral resources. To overcome this problem, channel estimation for mmWave massive MIMO systems is still an on-going research area. Among plenty of candidates, channel tracking is the most promising one. To achieve the extremely low cost and complexity, which is also the greatest motivation of this thesis, data-aided channel tracking method is thoroughly investigated with closed-form CRLB(Cram´er-Rao lower bound). In this thesis, data-aided channel tracking systems with different types of antenna, including ULA(Uniform Linear Antenna array), DLA(Discrete Lens Antenna ar ray) and UPA(Uniform Planar Antenna array), are comprehensively studied and proposed, and the closed-form expressions of the corresponding CRLBs are carefully derived. The numerical results of the simulations for each case are shown respectively, and they reveal that the performance of the proposed data-aided channel tracking system approaches the CRLB very well. In addition, to further explore the data-aided channel tracking system, the multi-user scenario is investigated in this thesis. This is motivated by the highway and high-speed railway application, where overtaking operation happens frequently. In this case, the users in the same beam suffer from high channel interference, thus degrading the channel estimation performance or even causing outage. To deal with this issue, we proposed an estimated SER(Symbol Error Rate) metric to indicate if a scheduling operation is necessary to be taken place and restart of the whole channel tracking system is required. This metric is included as the Update phase in the proposed channel tracking method for multiuser scenario with DLA. The theoretical SER closed-form expression is also derived for multi-user data detection. The numerical results of the simulations verified the theoretical SER expression, and the scheduling metric based on the estimated SER performance is also discussed

Unified Framework for Multicarrier and Multiple Access based on Generalized Frequency Division Multiplexing

The advancements in wireless communications are the key-enablers of new applications with stringent requirements in low-latency, ultra-reliability, high data rate, high mobility, and massive connectivity. Diverse types of devices, ranging from tiny sensors to vehicles, with different capabilities need to be connected under various channel conditions. Thus, modern connectivity and network techniques at all layers are essential to overcome these challenges. In particular, the physical layer (PHY) transmission is required to achieve certain link reliability, data rate, and latency. In modern digital communications systems, the transmission is performed by means of a digital signal processing module that derives analog hardware. The performance of the analog part is influenced by the quality of the hardware and the baseband signal denoted as waveform. In most of the modern systems such as fifth generation (5G) and WiFi, orthogonal frequency division multiplexing (OFDM) is adopted as a favorite waveform due to its low-complexity advantages in terms of signal processing. However, OFDM requires strict requirements on hardware quality. Many devices are equipped with simplified analog hardware to reduce the cost. In this case, OFDM does not work properly as a result of its high peak-to-average power ratio (PAPR) and sensitivity to synchronization errors. To tackle these problems, many waveforms design have been recently proposed in the literature. Some of these designs are modified versions of OFDM or based on conventional single subcarrier. Moreover, multicarrier frameworks, such as generalized frequency division multiplexing (GFDM), have been proposed to realize varieties of conventional waveforms. Furthermore, recent studies show the potential of using non-conventional waveforms for increasing the link reliability with affordable complexity. Based on that, flexible waveforms and transmission techniques are necessary to adapt the system for different hardware and channel constraints in order to fulfill the applications requirements while optimizing the resources. The objective of this thesis is to provide a holistic view of waveforms and the related multiple access (MA) techniques to enable efficient study and evaluation of different approaches. First, the wireless communications system is reviewed with specific focus on the impact of hardware impairments and the wireless channel on the waveform design. Then, generalized model of waveforms and MA are presented highlighting various special cases. Finally, this work introduces low-complexity architectures for hardware implementation of flexible waveforms. Integrating such designs with software-defined radio (SDR) contributes to the development of practical real-time flexible PHY.:1 Introduction 1.1 Baseband transmission model 1.2 History of multicarrier systems 1.3 The state-of-the-art waveforms 1.4 Prior works related to GFDM 1.5 Objective and contributions 2 Fundamentals of Wireless Communications 2.1 Wireless communications system 2.2 RF transceiver 2.2.1 Digital-analogue conversion 2.2.2 QAM modulation 2.2.3 Effective channel 2.2.4 Hardware impairments 2.3 Waveform aspects 2.3.1 Single-carrier waveform 2.3.2 Multicarrier waveform 2.3.3 MIMO-Waveforms 2.3.4 Waveform performance metrics 2.4 Wireless Channel 2.4.1 Line-of-sight propagation 2.4.2 Multi path and fading process 2.4.3 General baseband statistical channel model 2.4.4 MIMO channel 2.5 Summary 3 Generic Block-based Waveforms 3.1 Block-based waveform formulation 3.1.1 Variable-rate multicarrier 3.1.2 General block-based multicarrier model 3.2 Waveform processing techniques 3.2.1 Linear and circular filtering 3.2.2 Windowing 3.3 Structured representation 3.3.1 Modulator 3.3.2 Demodulator 3.3.3 MIMO Waveform processing 3.4 Detection 3.4.1 Maximum-likelihood detection 3.4.2 Linear detection 3.4.3 Iterative Detection 3.4.4 Numerical example and insights 3.5 Summary 4 Generic Multiple Access Schemes 57 4.1 Basic multiple access and multiplexing schemes 4.1.1 Infrastructure network system model 4.1.2 Duplex schemes 4.1.3 Common multiplexing and multiple access schemes 4.2 General multicarrier-based multiple access 4.2.1 Design with fixed set of pulses 4.2.2 Computational model 4.2.3 Asynchronous multiple access 4.3 Summary 5 Time-Frequency Analyses of Multicarrier 5.1 General time-frequency representation 5.1.1 Block representation 5.1.2 Relation to Zak transform 5.2 Time-frequency spreading 5.3 Time-frequency block in LTV channel 5.3.1 Subcarrier and subsymbol numerology 5.3.2 Processing based on the time-domain signal 5.3.3 Processing based on the frequency-domain signal 5.3.4 Unified signal model 5.4 summary 6 Generalized waveforms based on time-frequency shifts 6.1 General time-frequency shift 6.1.1 Time-frequency shift design 6.1.2 Relation between the shifted pulses 6.2 Time-frequency shift in Gabor frame 6.2.1 Conventional GFDM 6.3 GFDM modulation 6.3.1 Filter bank representation 6.3.2 Block representation 6.3.3 GFDM matrix structure 6.3.4 GFDM demodulator 6.3.5 Alternative interpretation of GFDM 6.3.6 Orthogonal modulation and GFDM spreading 6.4 Summary 7 Modulation Framework: Architectures and Applications 7.1 Modem architectures 7.1.1 General modulation matrix structure 7.1.2 Run-time flexibility 7.1.3 Generic GFDM-based architecture 7.1.4 Flexible parallel multiplications architecture 7.1.5 MIMO waveform architecture 7.2 Extended GFDM framework 7.2.1 Architectures complexity and flexibility analysis 7.2.2 Number of multiplications 7.2.3 Hardware analysis 7.3 Applications of the extended GFDM framework 7.3.1 Generalized FDMA 7.3.2 Enchantment of OFDM system 7.4 Summary 7 Conclusions and Future work