Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

Turbo codes and turbo algorithms

In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular trellis termination of recursive systematic convolutional codes and double-binary turbo codes associated with Max-Log-MAP decoding. A novel evaluation method, called genieinitialised iterative processing (GIIP), is introduced to assess the error performance of iterative processing. We show that using GIIP produces a result that can be viewed as a lower bound of the maximum likelihood iterative decoding and detection performance. Finally, two wireless communication systems are presented to illustrate recent applications of the turbo principle, the first one being multiple-input/multiple-output channel iterative detection and the second one multi-carrier modulation with linear precoding

Review of Recent Trends

This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe

Efficient detection and scheduling for MIMO-OFDM systems

Multiple-input multiple-output (MIMO) antennas can be exploited to provide high data rate using a limited bandwidth through multiplexing gain. MIMO combined with orthogonal frequency division multiplexing (OFDM) could potentially provide high data rate and high spectral efficiency in frequency-selective fading channels. MIMO-OFDM technology has been widely employed in modern communication systems, such as Wireless Local Area Network (WLAN), Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX). However, most of the conventional schemes either are computationally prohibitive or underutilize the full performance gain provided by the inherent merits of MIMO and OFDM techniques. In the first part of this dissertation, we firstly study the channel matrix inversion which is commonly required in various MIMO detection schemes. An algorithm that exploits second-order extrapolation in the time domain is proposed to efficiently reduce the computational complexity. This algorithm can be applied to both linear detection and non-linear detection such as ordered successive interference cancellation (OSIC) while maintaining the system performance. Secondly, we study the complexity reduction for Lattice Reduction Aided Detection (LRAD) of MIMO-OFDM systems. We propose an algorithm that exploits the inherent feature of unimodular transformation matrix that remains the same for relatively highly correlated frequency components. This algorithm effectively eliminates the redundant brute-force lattice reduction iterations among adjacent subcarriers. Thirdly, we analyze the impact of channel coherence bandwidth on two LRAD algorithms. Analytical and simulation results demonstrate that carefully setting the initial calculation interval according to the coherence bandwidth is essential for both algorithms. The second part of this dissertation focuses on efficient multi-user (MU) scheduling and coordination for the uplink of WLAN that uses MIMO-OFDM techniques. On one hand, conventional MU-MIMO medium access control (MAC) protocols require large overhead, which lowers the performance gain of concurrent transmissions rendered by the multi-packet reception (MPR) capability of MIMO systems. Therefore, an efficient MU-MIMO uplink MAC scheduling scheme is proposed for future WLAN. On the other hand, single-user (SU) MIMO achieves multiplexing gain in the physical (PHY) layer and MU-MIMO achieves multiplexing gain in the MAC layer. In addition, the average throughput of the system varies depending on the number of antennas and users, average payload sizes, and signal-to-noise-ratios (SNRs). A comparison on the performance between SU-MIMO and MU-MIMO schemes for WLAN uplink is hence conducted. Simulation results indicate that a dynamic switch between the SU-MIMO and MU-MIMO is of significance for higher network throughput of WLAN uplink

Spectral efficient compressive transmission framework for wireless communication systems

Increasing demand of high-speed data rate is leading to a challenging task to provide services to the users within exponentially growing market for wireless multimedia services. Subsequently, the available radio resources are becoming scarce because of different factors such as spectrum segmentation and dedicated frequency allocation to existing wireless standards. Exploring new techniques for enhancing the spectral efficiency in wireless communication has been an important research challenge. In this study, the enhancement of spectral efficiency of wireless communication systems is considered. A framework is proposed to implement the concept of compressive sampling (CS) for compressing the natural random signals. The performance of proposed framework is evaluated in the context of multiple input multiple output orthogonal frequency division multiplexing system. Simulation-based results show that 25% of resources can be saved by marginal trade-off with the quality of service (QoS) requirement applying CS to the natural random signals. Furthermore, it can be claimed that this QoS trade-off can be optimised with dynamic selection of random measurement matrices

Antenna Design for 5G and Beyond

With the rapid evolution of the wireless communications, fifth-generation (5G) communication has received much attention from both academia and industry, with many reported efforts and research outputs and significant improvements in different aspects, such as data rate speed and resolution, mobility, latency, etc. In some countries, the commercialization of 5G communication has already started as well as initial research of beyond technologies such as 6G.MIMO technology with multiple antennas is a promising technology to obtain the requirements of 5G/6G communications. It can significantly enhance the system capacity and resist multipath fading, and has become a hot spot in the field of wireless communications. This technology is a key component and probably the most established to truly reach the promised transfer data rates of future communication systems. In MIMO systems, multiple antennas are deployed at both the transmitter and receiver sides. The greater number of antennas can make the system more resistant to intentional jamming and interference. Massive MIMO with an especially high number of antennas can reduce energy consumption by targeting signals to individual users utilizing beamforming.Apart from sub-6 GHz frequency bands, 5G/6G devices are also expected to cover millimeter-wave (mmWave) and terahertz (THz) spectra. However, moving to higher bands will bring new challenges and will certainly require careful consideration of the antenna design for smart devices. Compact antennas arranged as conformal, planar, and linear arrays can be employed at different portions of base stations and user equipment to form phased arrays with high gain and directional radiation beams. The objective of this Special Issue is to cover all aspects of antenna designs used in existing or future wireless communication systems. The aim is to highlight recent advances, current trends, and possible future developments of 5G/6G antennas