Application of integer quadratic programming in detection of high-dimensional wireless systems

High-dimensional wireless systems have recently generated a great deal of interest due to their ability to accommodate increasing demands for high transmission data rates with high communication reliability. Examples of such large-scale systems include single-input, single-output symbol spread OFDM system, large-scale single-user multi-input multi-output (MIMO) OFDM systems, and large-scale multiuser MIMO systems. In these systems, the number of symbols required to be jointly detected at the receiver is relatively large. The challenge with the practical realization of these systems is to design a detection scheme that provides high communication reliability with reasonable computational complexity, even as the number of simultaneously transmitted independent communication signals becomes very large.^ Most of the optimal or near-optimal detection techniques that have been proposed in the literature of relatively low-dimensional wireless systems, such as MIMO systems in which number of antennas is less than 10, become problematic for high-dimensional detection problems. That is, their performance degrades or the computational complexity becomes prohibitive, especially when higher-order QAM constellations are employed.^ In the first part of this thesis, we propose a near-optimal detection technique which offers a flexible trade-off between complexity and performance. The proposed technique formulates the detection problem in terms of Integer Quadratic Programming (IQP), which is then solved through a controlled Branch and Bound (BB) search tree algorithm. In addition to providing good performance, an important feature of this approach is that its computational complexity remains roughly the same even as we increase the constellation order from 4-QAM to 256-QAM. The performance of the proposed algorithm is investigated for both symbol spread OFDM systems and large-scale MIMO systems with both frequency selective and at fading channels.^ The second part of this work focuses on a reduced complexity version of IQP referred to as relaxed quadratic programming (QP). In particular, QP is used to reformulate two widely used detection schemes for MIMO OFDM: (1) Successive Interference Cancellation (SIC) and (2) Iterative Detecting and Decoding (IDD). First, SIC-based algorithms are derived via a QP formulation in contrast to using a linear MMSE detector at each stage. The resulting QP-SIC algorithms offer lower computational complexity than the SIC schemes that employ linear MMSE at each stage, especially when the dimension of the received signal vector is high. Three versions of QP-SIC are proposed based on various trade-offs between complexity and receiver performance; each of the three QP-SIC algorithms outperforms existing SIC techniques. Second, IDD-based algorithms are developed using a QP detector. We show how the soft information, in terms of the Log Likelihood Ratio (LLR), can be extracted from the QP detector. Further, the procedure for incorporating the a-priori information that is passed from the channel decoder to the QP detector is developed. Simulation results are presented demonstrating that the use of QP in IDD offers improved performance at the cost of a reasonable increase in complexity compared to linear detectors

High capacity high spectral efficiency transmission techniques in wireless broadband systems

Ph.DDOCTOR OF PHILOSOPH

MIMO designs for filter bank multicarrier and multiantenna systems based on OQAM

From the perspective of increasingly data rate requirements in mobile communications, it is deemed necessary to do further research so that the future goals can be reached. To that end, the radio-based communications are resorting to multicarrier modulations and spatial diversity. Until today, the orthogonal frequency division multiplexing (OFDM) modulation is regarded as the dominant technology. On one hand, the OFDM modulation is able to accommodate multiantenna configurations in a very straightforward manner. On the other hand, the poor stopband attenuation exhibited by the OFDM modulation, highlights that a definitely tight synchronization is required. In addition, the cyclic prefix (CP) has to be sufficiently long to avoid inter-block interference, which may substantially reduce the spectral efficiency. In order to overcome the OFDM drawbacks, the filter bank multicarrier modulation based on OQAM (FBMC/OQAM) is introduced. This modulation does not need any CP and benefits from pulse shaping techniques. This aspect becomes crucial in cognitive radio networks and communication systems where nodes are unlikely to be synchronized. In principle, the poor frequency confinement exhibited by OFDM should tip the balance towards FBMC/OQAM. However, the perfect reconstruction property of FBMC/OQAM systems does not hold in presence of multipath fading. This means that the FBMC/OQAM modulation is affected by inter-symbol and inter-carrier interference, unless the channel is equalized to some extent. This observation highlights that the FBMC/OQAM extension to MIMO architectures becomes a big challenge due to the need to cope with both modulation- and multiantenna-induced interference. The goal of this thesis is to study how the FBMC/OQAM modulation scheme can benefit from the degrees of freedom provided by the spatial dimension. In this regard, the first attempt to put the research on track is based on designing signal processing techniques at reception. In this case the emphasis is on single-input-multiple-output (SIMO) architectures. Next, the possibility of pre-equalizing the channel at transmission is investigated. It is considered that multiple antennas are placed at the transmit side giving rise to a multiple-input-single-output (MISO) configuration. In this scenario, the research is not only focused on counteracting the channel but also on distributing the power among subcarriers. Finally, the joint transmitter and receiver design in multiple-input-multiple-output (MIMO) communication systems is covered. From the theory developed in this thesis, it is possible to conclude that the techniques originally devised in the OFDM context can be easily adapted to FBMC/OQAM systems if the channel frequency response is flat within the subchannels. However, metrics such as the peak to average power ratio or the sensitivity to the carrier frequency offset constraint the number of subcarriers, so that the frequency selectivity may be appreciable at the subcarrier level. Then, the flat fading assumption is not satisfied and the specificities of FBMC/OQAM systems have to be considered. In this situation, the proposed techniques allow FBMC/OQAM to remain competitive with OFDM. In addition, for some multiantenna configurations and propagation conditions FBMC/OQAM turns out to be the best choice. The simulation-based results together with the theoretical analysis conducted in this thesis contribute to make progress towards the application of FBMC/OQAM to MIMO channels. The signal processing techniques that are described in this dissertation allow designers to exploit the potentials of FBMC/OQAM and MIMO to improve the link reliability as well as the spectral efficiency

CELLULAR-ENABLED MACHINE TYPE COMMUNICATIONS: RECENT TECHNOLOGIES AND COGNITIVE RADIO APPROACHES

The scarcity of bandwidth has always been the main obstacle for providing reliable high data-rate wireless links, which are in great demand to accommodate nowadays and immediate future wireless applications. In addition, recent reports have showed inefficient usage and under-utilization of the available bandwidth. Cognitive radio (CR) has recently emerged as a promising solution to enhance the spectrum utilization, where it offers the ability for unlicensed users to access the licensed spectrum opportunistically. By allowing opportunistic spectrum access which is the main concept for the interweave network model, the overall spectrum utilization can be improved. This requires cognitive radio networks (CRNs) to consider the spectrum sensing and monitoring as an essential enabling process for the interweave network model. Machine-to-machine (M2M) communication, which is the basic enabler for the Internet-of-Things (IoT), has emerged to be a key element in future networks. Machines are expected to communicate with each other exchanging information and data without human intervention. The ultimate objective of M2M communications is to construct comprehensive connections among all machines distributed over an extensive coverage area. Due to the radical change in the number of users, the network has to carefully utilize the available resources in order to maintain reasonable quality-of-service (QoS). Generally, one of the most important resources in wireless communications is the frequency spectrum. To utilize the frequency spectrum in IoT environment, it can be argued that cognitive radio concept is a possible solution from the cost and performance perspectives. Thus, supporting numerous number of machines is possible by employing dual-mode base stations which can apply cognitive radio concept in addition to the legacy licensed frequency assignment. In this thesis, a detailed review of the state of the art related to the application of spectrum sensing in CR communications is considered. We present the latest advances related to the implementation of the legacy spectrum sensing approaches. We also address the implementation challenges for cognitive radios in the direction of spectrum sensing and monitoring. We propose a novel algorithm to solve the reduced throughput issue due to the scheduled spectrum sensing and monitoring. Further, two new architectures are considered to significantly reduce the power consumption required by the CR to enable wideband sensing. Both systems rely on the 1-bit quantization at the receiver side. The system performance is analytically investigated and simulated. Also, complexity and power consumption are investigated and studied. Furthermore, we address the challenges that are expected from the next generation M2M network as an integral part of the future IoT. This mainly includes the design of low-power low-cost machine with reduced bandwidth. The trade-off between cost, feasibility, and performance are also discussed. Because of the relaxation of the frequency and spatial diversities, in addition, to enabling the extended coverage mode, initial synchronization and cell search have new challenges for cellular-enabled M2M systems. We study conventional solutions with their pros and cons including timing acquisition, cell detection, and frequency offset estimation algorithms. We provide a technique to enhance the performance in the presence of the harsh detection environment for LTE-based machines. Furthermore, we present a frequency tracking algorithm for cellular M2M systems that utilizes the new repetitive feature of the broadcast channel symbols in next generation Long Term Evolution (LTE) systems. In the direction of narrowband IoT support, we propose a cell search and initial synchronization algorithm that utilizes the new set of narrowband synchronization signals. The proposed algorithms have been simulated at very low signal to noise ratios and in different fading environments

Sub-carrier allocation schemes for MC-DS-CDMA systems

Master'sMASTER OF ENGINEERIN

Cross-layer Optimization for Video Delivery over Wireless Networks

As video streaming is becoming the most popular application of Internet mo- bile, the design and the optimization of video communications over wireless networks is attracting increasingly attention from both academia and indus- try. The main challenges are to enhance the quality of service support, and to dynamically adapt the transmitted video streams to the network condition. The cross-layer methods, i.e., the exchange of information among different layers of the system, is one of the key concepts to be exploited to achieve this goals. In this thesis we propose novel cross-layer optimization frameworks for scalable video coding (SVC) delivery and for HTTP adaptive streaming (HAS) application over the downlink and the uplink of Long Term Evolution (LTE) wireless networks. They jointly address optimized content-aware rate adaptation and radio resource allocation (RRA) with the aim of maximiz- ing the sum of the achievable rates while minimizing the quality difference among multiple videos. For multi-user SVC delivery over downlink wireless systems, where IP/TV is the most representative application, we decompose the optimization problem and we propose the novel iterative local approxi- mation algorithm to derive the optimal solution, by also presenting optimal algorithms to solve the resulting two sub-problems. For multiple SVC de- livery over uplink wireless systems, where healt-care services are the most attractive and challenging application, we propose joint video adaptation and aggregation directly performed at the application layer of the transmit- ting equipment, which exploits the guaranteed bit-rate (GBR) provided by the low-complexity sub-optimal RRA solutions proposed. Finally, we pro- pose a quality-fair adaptive streaming solution to deliver fair video quality to HAS clients in a LTE cell by adaptively selecting the prescribed (GBR) of each user according to the video content in addition to the channel condi- tion. Extensive numerical evaluations show the significant enhancements of the proposed strategies with respect to other state-of-the-art frameworks

Spectrally and Energy Efficient Wireless Communications: Signal and System Design, Mathematical Modelling and Optimisation

This thesis explores engineering studies and designs aiming to meeting the requirements of enhancing capacity and energy efficiency for next generation communication networks. Challenges of spectrum scarcity and energy constraints are addressed and new technologies are proposed, analytically investigated and examined. The thesis commences by reviewing studies on spectrally and energy-efficient techniques, with a special focus on non-orthogonal multicarrier modulation, particularly spectrally efficient frequency division multiplexing (SEFDM). Rigorous theoretical and mathematical modelling studies of SEFDM are presented. Moreover, to address the potential application of SEFDM under the 5th generation new radio (5G NR) heterogeneous numerologies, simulation-based studies of SEFDM coexisting with orthogonal frequency division multiplexing (OFDM) are conducted. New signal formats and corresponding transceiver structure are designed, using a Hilbert transform filter pair for shaping pulses. Detailed modelling and numerical investigations show that the proposed signal doubles spectral efficiency without performance degradation, with studies of two signal formats; uncoded narrow-band internet of things (NB-IoT) signals and unframed turbo coded multi-carrier signals. The thesis also considers using constellation shaping techniques and SEFDM for capacity enhancement in 5G system. Probabilistic shaping for SEFDM is proposed and modelled to show both transmission energy reduction and bandwidth saving with advantageous flexibility for data rate adaptation. Expanding on constellation shaping to improve performance further, a comparative study of multidimensional modulation techniques is carried out. A four-dimensional signal, with better noise immunity is investigated, for which metaheuristic optimisation algorithms are studied, developed, and conducted to optimise bit-to-symbol mapping. Finally, a specially designed machine learning technique for signal and system design in physical layer communications is proposed, utilising the application of autoencoder-based end-to-end learning. Multidimensional signal modulation with multidimensional constellation shaping is proposed and optimised by using machine learning techniques, demonstrating significant improvement in spectral and energy efficiencies

A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

IEEE Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area