Channel Prediction for Mobile MIMO Wireless Communication Systems

Temporal variation and frequency selectivity of wireless channels constitute a major drawback to the attainment of high gains in capacity and reliability offered by multiple antennas at the transmitter and receiver of a mobile communication system. Limited feedback and adaptive transmission schemes such as adaptive modulation and coding, antenna selection, power allocation and scheduling have the potential to provide the platform of attaining the high transmission rate, capacity and QoS requirements in current and future wireless communication systems. Theses schemes require both the transmitter and receiver to have accurate knowledge of Channel State Information (CSI). In Time Division Duplex (TDD) systems, CSI at the transmitter can be obtained using channel reciprocity. In Frequency Division Duplex (FDD) systems, however, CSI is typically estimated at the receiver and fed back to the transmitter via a low-rate feedback link. Due to the inherent time delays in estimation, processing and feedback, the CSI obtained from the receiver may become outdated before its actual usage at the transmitter. This results in significant performance loss, especially in high mobility environments. There is therefore a need to extrapolate the varying channel into the future, far enough to account for the delay and mitigate the performance degradation. The research in this thesis investigates parametric modeling and prediction of mobile MIMO channels for both narrowband and wideband systems. The focus is on schemes that utilize the additional spatial information offered by multiple sampling of the wave-field in multi-antenna systems to aid channel prediction. The research has led to the development of several algorithms which can be used for long range extrapolation of time-varyingchannels. Based on spatial channel modeling approaches, simple and efficient methods for the extrapolation of narrowband MIMO channels are proposed. Various extensions were also developed. These include methods for wideband channels, transmission using polarized antenna arrays, and mobile-to-mobile systems. Performance bounds on the estimation and prediction error are vital when evaluating channel estimation and prediction schemes. For this purpose, analytical expressions for bound on the estimation and prediction of polarized and non-polarized MIMO channels are derived. Using the vector formulation of the Cramer Rao bound for function of parameters, readily interpretable closed-form expressions for the prediction error bounds were found for cases with Uniform Linear Array (ULA) and Uniform Planar Array (UPA). The derived performance bounds are very simple and so provide insight into system design. The performance of the proposed algorithms was evaluated using standardized channel models. The effects of the temporal variation of multipath parameters on prediction is studied and methods for jointly tracking the channel parameters are developed. The algorithms presented can be utilized to enhance the performance of limited feedback and adaptive MIMO transmission schemes

Signal-perturbation-free semi-blind channel estimation for MIMO-OFDM systems

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) has been considered as a strong candidate for the beyond 3G (B3G) wireless communication systems, due to its high data-rate wireless transmission performance. It is well known that the advantages promised by MIMO-OFDM systems rely on the precise knowledge of the channel state information (CSI). In real wireless environments, however, the channel condition is unknown. Therefore, channel estimation is of crucial importance in MIMO-OFDM systems. Semi-blind channel estimation as a combination of the training-based or pilot-assisted method and the pure blind approach is considered to be a feasible solution for practical wireless systems due to its better estimation accuracy as well as spectral efficiency. In this thesis, we address the semi-blind channel estimation issue of MIMO-OFDM systems with an objective to develop very efficient channel estimation approaches. In the first part of the dissertation, several nulling-based semi-blind approaches are presented for the estimation of time-domain MIMO-OFDM channels. By incorporating a blind constraint that is derived from MIMO linear prediction (LP) into a training-based least-square method, a semi-blind solution for the time-domain channel estimation is first obtained. It is revealed through a perturbation analysis that the semi-blind solution is not subject to signal perturbation and therefore is superior to pure blind estimation methods. The LP-based semi-blind method is then extended for the channel estimation of MIMO-OFDM systems with pulse-shaping. By exploiting the pulse-shaping filter in the transmitter and the matched filter in the receiver, a very efficient semi-blind approach is developed for the estimation of sampling duration based multipath channels. A frequency-domain correlation matrix estimation algorithm is also presented to facilitate the computation of time-domain second-order statistics required in the LP-based method. The nulling-based semi-blind estimation issue of sparse MIMO-OFDM channels is also addressed. By disclosing and using a relationship between the positions of the most significant taps (MST) of the sparse channel and the lags of nonzero correlation matrices of the received signal, a novel estimation approach consisting of the MST detection and the sparse channel estimation, both in a semi-blind fashion, is developed. An intensive simulation study of all the proposed nulling-based methods with comparison to some existing techniques is conducted, showing a significant superiority of the new methodologies. The second part of the dissertation is dedicated to the development of two signal-perturbation-free (SPF) semi-blind channel estimation algorithms based on a novel transmit scheme that bears partial information of the second-order statistics of the transmitted signal to receiver. It is proved that the new transmit scheme can completely cancel the signal perturbation error in the noise-free case, thereby improving largely the estimation accuracy of correlation matrix for channel estimation in noisy conditions. It is also shown that the overhead caused by the transmission of the 8PF data is negligible as compared to that of regular pilot signals. By using the proposed transmit scheme, a whitening rotation (WR)-based algorithm is first developed for frequency-domain MIMO-OFDM channel estimation. It is shown through both theoretical analysis and simulation study that the new WR-based algorithm significantly outperforms the conventional WR-based method and the nulling-based semi-blind method. By using MIMO linear prediction, the new WR-based algorithm utilizing the 8PF transmit scheme is then extended for time-domain MIMO-OFDM channel estimation. Computer simulations show that the proposed signal-perturbation-free LP-based semi-blind solution performs much better than the LP semi-blind method without using the proposed transmit scheme, the LS method as well as the nulling-based semi-blind method in terms of the MSE of the channel estimate

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Solutions for large scale, efficient, and secure Internet of Things

The design of a general architecture for the Internet of Things (IoT) is a complex task, due to the heterogeneity of devices, communication technologies, and applications that are part of such systems. Therefore, there are significant opportunities to improve the state of the art, whether to better the performance of the system, or to solve actual issues in current systems. This thesis focuses, in particular, on three aspects of the IoT. First, issues of cyber-physical systems are analysed. In these systems, IoT technologies are widely used to monitor, control, and act on physical entities. One of the most important issue in these scenarios are related to the communication layer, which must be characterized by high reliability, low latency, and high energy efficiency. Some solutions for the channel access scheme of such systems are proposed, each tailored to different specific scenarios. These solutions, which exploit the capabilities of state of the art radio transceivers, prove effective in improving the performance of the considered systems. Positioning services for cyber-physical systems are also investigated, in order to improve the accuracy of such services. Next, the focus moves to network and service optimization for traffic intensive applications, such as video streaming. This type of traffic is common amongst non-constrained devices, like smartphones and augmented/virtual reality headsets, which form an integral part of the IoT ecosystem. The proposed solutions are able to increase the video Quality of Experience while wasting less bandwidth than state of the art strategies. Finally, the security of IoT systems is investigated. While often overlooked, this aspect is fundamental to enable the ubiquitous deployment of IoT. Therefore, security issues of commonly used IoT protocols are presented, together with a proposal for an authentication mechanism based on physical channel features. This authentication strategy proved to be effective as a standalone mechanism or as an additional security layer to improve the security level of legacy systems

Device characteristics-based differentiated energy-efficient adaptive solution for multimedia delivery over heterogeneous wireless networks

Energy efficiency is a key issue of highest importance to mobile wireless device users, as those devices are powered by batteries with limited power capacity. It is of very high interest to provide device differentiated user centric energy efficient multimedia content delivery based on current application type, energy-oriented device features and user preferences. This thesis presents the following research contributions in the area of energy efficient multimedia delivery over heterogeneous wireless networks: 1. ASP: Energy-oriented Application-based System profiling for mobile devices: This profiling provides services to other contributions in this thesis. By monitoring the running applications and the corresponding power demand on the smart mobile device, a device energy model is obtained. The model is used in conjunction with applications’ power signature to provide device energy constraints posed by running applications. 2. AWERA 3. DEAS: A Device characteristics-based differentiated Energy-efficient Adaptive Solution for video delivery over heterogeneous wireless networks. Based on the energy constraint, DEAS performs energy efficient content delivery adaptation for the current application. Unlike the existing solutions, DEAS takes all the applications running on the system into account and better balances QoS and energy efficiency. 4. EDCAM 5. A comprehensive survey on state-of-the-art energy-efficient network protocols and energy-saving network technologies

ATHENA Research Book

The ATHENA European University is an alliance of nine Higher Education Institutions with the mission of fostering excellence in research and innovation by facilitating international cooperation. The ATHENA acronym stands for Advanced Technologies in Higher Education Alliance. The partner institutions are from France, Germany, Greece, Italy, Lithuania, Portugal, and Slovenia: the University of Orléans, the University of Siegen, the Hellenic Mediterranean University, the Niccolò Cusano University, the Vilnius Gediminas Technical University, the Polytechnic Institute of Porto, and the University of Maribor. In 2022 institutions from Poland and Spain joined the alliance: the Maria Curie-Skłodowska University and the University of Vigo. This research book presents a selection of the ATHENA university partners' research activities. It incorporates peer-reviewed original articles, reprints and student contributions. The ATHENA Research Book provides a platform that promotes joint and interdisciplinary research projects of both advanced and early-career researchers

ATHENA Research Book, Volume 1

The ATHENA European University is an alliance of nine Higher Education Institutions with the mission of fostering excellence in research and innovation by facilitating international cooperation. The ATHENA acronym stands for Advanced Technologies in Higher Education Alliance. The partner institutions are from France, Germany, Greece, Italy, Lithuania, Portugal, and Slovenia: the University of Orléans, the University of Siegen, the Hellenic Mediterranean University, the Niccolò Cusano University, the Vilnius Gediminas Technical University, the Polytechnic Institute of Porto, and the University of Maribor. In 2022 institutions from Poland and Spain joined the alliance: the Maria Curie-Skłodowska University and the University of Vigo. This research book presents a selection of the ATHENA university partners' research activities. It incorporates peer-reviewed original articles, reprints and student contributions. The ATHENA Research Book provides a platform that promotes joint and interdisciplinary research projects of both advanced and early-career researchers