Hybrid satellite–terrestrial networks toward 6G : key technologies and open issues

Future wireless networks will be required to provide more wireless services at higher data rates and with global coverage. However, existing homogeneous wireless networks, such as cellular and satellite networks, may not be able to meet such requirements individually, especially in remote terrain, including seas and mountains. One possible solution is to use diversified wireless networks that can exploit the inter-connectivity between satellites, aerial base stations (BSs), and terrestrial BSs over inter-connected space, ground, and aerial networks. Hence, enabling wireless communication in one integrated network has attracted both the industry and the research fraternities. In this work, we provide a comprehensive survey of the most recent work on hybrid satellite–terrestrial networks (HSTNs), focusing on system architecture, performance analysis, design optimization, and secure communication schemes for different cooperative and cognitive HSTN network architectures. Different key technologies are compared. Based on this comparison, several open issues for future research are discussed

DESIGN AND OPTIMIZATION OF SIMULTANEOUS WIRELESS INFORMATION AND POWER TRANSFER SYSTEMS

The recent trends in the domain of wireless communications indicate severe upcoming challenges, both in terms of infrastructure as well as design of novel techniques. On the other hand, the world population keeps witnessing or hearing about new generations of mobile/wireless technologies within every half to one decade. It is certain the wireless communication systems have enabled the exchange of information without any physical cable(s), however, the dependence of the mobile devices on the power cables still persist. Each passing year unveils several critical challenges related to the increasing capacity and performance needs, power optimization at complex hardware circuitries, mobility of the users, and demand for even better energy efficiency algorithms at the wireless devices. Moreover, an additional issue is raised in the form of continuous battery drainage at these limited-power devices for sufficing their assertive demands. In this regard, optimal performance at any device is heavily constrained by either wired, or an inductive based wireless recharging of the equipment on a continuous basis. This process is very inconvenient and such a problem is foreseen to persist in future, irrespective of the wireless communication method used. Recently, a promising idea for simultaneous wireless radio-frequency (RF) transmission of information and energy came into spotlight during the last decade. This technique does not only guarantee a more flexible recharging alternative, but also ensures its co-existence with any of the existing (RF-based) or alternatively proposed methods of wireless communications, such as visible light communications (VLC) (e.g., Light Fidelity (Li-Fi)), optical communications (e.g., LASER-equipped communication systems), and far-envisioned quantum-based communication systems. In addition, this scheme is expected to cater to the needs of many current and future technologies like wearable devices, sensors used in hazardous areas, 5G and beyond, etc. This Thesis presents a detailed investigation of several interesting scenarios in this direction, specifically concerning design and optimization of such RF-based power transfer systems. The first chapter of this Thesis provides a detailed overview of the considered topic, which serves as the foundation step. The details include the highlights about its main contributions, discussion about the adopted mathematical (optimization) tools, and further refined minutiae about its organization. Following this, a detailed survey on the wireless power transmission (WPT) techniques is provided, which includes the discussion about historical developments of WPT comprising its present forms, consideration of WPT with wireless communications, and its compatibility with the existing techniques. Moreover, a review on various types of RF energy harvesting (EH) modules is incorporated, along with a brief and general overview on the system modeling, the modeling assumptions, and recent industrial considerations. Furthermore, this Thesis work has been divided into three main research topics, as follows. Firstly, the notion of simultaneous wireless information and power transmission (SWIPT) is investigated in conjunction with the cooperative systems framework consisting of single source, multiple relays and multiple users. In this context, several interesting aspects like relay selection, multi-carrier, and resource allocation are considered, along with problem formulations dealing with either maximization of throughput, maximization of harvested energy, or both. Secondly, this Thesis builds up on the idea of transmit precoder design for wireless multigroup multicasting systems in conjunction with SWIPT. Herein, the advantages of adopting separate multicasting and energy precoder designs are illustrated, where we investigate the benefits of multiple antenna transmitters by exploiting the similarities between broadcasting information and wirelessly transferring power. The proposed design does not only facilitates the SWIPT mechanism, but may also serve as a potential candidate to complement the separate waveform designing mechanism with exclusive RF signals meant for information and power transmissions, respectively. Lastly, a novel mechanism is developed to establish a relationship between the SWIPT and cache-enabled cooperative systems. In this direction, benefits of adopting the SWIPT-caching framework are illustrated, with special emphasis on an enhanced rate-energy (R-E) trade-off in contrast to the traditional SWIPT systems. The common notion in the context of SWIPT revolves around the transmission of information, and storage of power. In this vein, the proposed work investigates the system wherein both information and power can be transmitted and stored. The Thesis finally concludes with insights on the future directions and open research challenges associated with the considered framework

Highly Efficient Resource Allocation Techniques in 5G for NOMA-based Massive MIMO and Relaying Systems

The explosive proliferation of smart devices in the 5-th generation (5G) network expects 1,000-fold capacity enhancement, leading to the urgent need of highly resource-efficient technologies. Non-orthogonal multiple access (NOMA), a promising spectral efficient technology for 5G to serve multiple users concurrently, can be combined with massive multiple input multiple output (MIMO) and relaying technology, to achieve highly efficient communications. Hence, this thesis studies the design and resource allocation of NOMA-based massive MIMO and relaying systems. Due to hardware constraints and channel condition variation, the first topic of the thesis develops efficient antenna selection and user scheduling algorithms for sum rate maximization in two MIMO-NOMA scenarios. In the single-band scenario, the proposed algorithm improves antenna search efficiency by limiting the candidate antennas to those are beneficial to the relevant users. In the multi-band scenario, the proposed algorithm selects the antennas and users with the highest contribution total channel gain. Numerical results show that our proposed algorithms achieve similar performance to other algorithms with reduced complexity. The second part of the thesis proposes the relaying and power allocation scheme for the NOMA-assisted relaying system to serve multiple cell-edge users. The relay node decodes its own message from the source NOMA signal and transmits the remaining part of signal to cell-edge users. The power allocation scheme is developed by minimizing the system outage probability. To further evaluate the system performance, the ergodic capacity is approximated by analyzing the interference at cell-edge users. Numerical results proves the performance improvement of the proposed system over conventional orthogonal multiple access mechanism

Spatial Modulation for Generalized MIMO:Challenges, Opportunities, and Implementation

A key challenge of future mobile communication research is to strike an attractive compromise between wireless network's area spectral efficiency and energy efficiency. This necessitates a clean-slate approach to wireless system design, embracing the rich body of existing knowledge, especially on multiple-input-multiple-output (MIMO) technologies. This motivates the proposal of an emerging wireless communications concept conceived for single-radio-frequency (RF) large-scale MIMO communications, which is termed as SM. The concept of SM has established itself as a beneficial transmission paradigm, subsuming numerous members of the MIMO system family. The research of SM has reached sufficient maturity to motivate its comparison to state-of-the-art MIMO communications, as well as to inspire its application to other emerging wireless systems such as relay-aided, cooperative, small-cell, optical wireless, and power-efficient communications. Furthermore, it has received sufficient research attention to be implemented in testbeds, and it holds the promise of stimulating further vigorous interdisciplinary research in the years to come. This tutorial paper is intended to offer a comprehensive state-of-the-art survey on SM-MIMO research, to provide a critical appraisal of its potential advantages, and to promote the discussion of its beneficial application areas and their research challenges leading to the analysis of the technological issues associated with the implementation of SM-MIMO. The paper is concluded with the description of the world's first experimental activities in this vibrant research field

Quadrature spatial modulation aided single-input multiple-output-media based modulation: application to cooperative network and golden code orthogonal super-symbol systems.

Doctoral Degree. University of KwaZulu-Natal, Durban.SIMO-MBM (single-input multiple-output media-based modulation) overcomes the limitations of SIMO (single-input multiple-output) systems by reducing the number of antennas required to achieve a high data rate and improved error performance. In this thesis, the quadrature dimension of the spatial constellation is used to improve the overall error performance of the conventional SIMO-MBM and to achieve a higher data rate by decomposing the amplitude/phase modulation (APM) symbol into real and imaginary components, similar to quadrature spatial modulation (QSM). The average bit error probability of the proposed technique is expressed using a lower bound approach and validated using the results of Monte Carlo simulation (MCS). The proposed system also investigates the effect of antenna correlation in combination with channel amplitude to select a sub-optimal mirror activation pattern. The results of MCS show a 3.5dB improvement at 10b/s/Hz with m =2 and a 7dB improvement at 12b/s/Hz with =2 over the traditional SIMO-MBM scheme. The effect of imperfect channel estimation on the proposed scheme is investigated, with a trade-off of 2dB in coding gain due to channel estimation errors. Cooperative Networking (CN) improves wireless network reliability, link quality, and spectrum efficiency by collaborating among nodes. The decode and forward relaying technique is used in this thesis to investigate the performance of QSM aided SIMO-MBM in a Cooperative Network (CN). This technique uses two source nodes that simultaneously transmit a unique message block on the same time slot to the relay node, which then decodes the received message block from both transmitting nodes before re-encoding and re-transmitting the decoded message block in the next time slot to the destinations in order to significantly improve the QSM aided SIMO-MBM’s error performance. Using network coding (NC) techniques, each Node can decode the data of the other Node. To enhance network performance, complexity, robustness, and minimize delays, data is encoded and decoded in NC; algebraic techniques are applied to the detected message to collect the various transmissions. The proposed scheme's theoretical average error probability was defined using a lower bound technique, and the results of Monte Carlo simulation (MCS) validated the result. The MCS results achieved exhibit a significant improvement of 8 dB at 6 b/s/Hz and 12 dB at 8 b/s/Hz over the conventional QSM aided SIMO-MBM scheme. The media-based modulation (MBM) technique can achieve significant throughput, increase spectrum efficiency, and improve bit-error-rate performance (BER). In this thesis, the use of MBM in single-input multiple-output systems is examined using radio frequency (RF) mirrors and Golden code (GC-SIMO). The goal is to lower the system's hardware complexity by maximizing the linear relationship between RF mirrors and spectral efficiency in MBM in order to achieve a high data rate with less hardware complexity. The GC scheme's encoder uses orthogonal pairs of the super-symbol, each transmitted via a separate RF mirror at a different time slot to achieve full rate full diversity. In the results of MCS obtained, at a BER of 10−5, the GC-SIMO-MBM exhibits a significant performance of approximately 7dB and 6.5 dB SNR gain for 4 b/s/Hz and 6 b/s/Hz, respectively, compared to GC-SIMO. The proposed scheme's derived theoretical average error probability is validated by the results of the Monte Carlo simulation

Energy-efficient resource allocation in limited fronthaul capacity cloud-radio access networks

In recent years, cloud radio access networks (C-RANs) have demonstrated their role as a formidable technology candidate to address the challenging issues from the advent of Fifth Generation (5G) mobile networks. In C-RANs, the modules which are capable of processing data and handling radio signals are physically separated in two main functional groups: the baseband unit (BBU) pool consisting of multiple BBUs on the cloud, and the radio access networks (RANs) consisting of several low-power remote radio heads (RRH) whose functionality are simplified with radio transmission/reception. Thanks to the centralized computation capability of cloud computing, C-RANs enable the coordination between RRHs to significantly improve the achievable spectral efficiency to satisfy the explosive traffic demand from users. More importantly, this enhanced performance can be attained at its power-saving mode, which results in the energy-efficient C-RAN perspective. Note that such improvement can be achieved under an ideal fronthaul condition of very high and stable capacity. However, in practice, dedicated fronthaul links must remarkably be divided to connect a large amount of RRHs to the cloud, leading to a scenario of non-ideal limited fronthaul capacity for each RRH. This imposes a certain upper-bound on each user’s spectral efficiency, which limits the promising achievement of C-RANs. To fully harness the energy-efficient C-RANs while respecting their stringent limited fronthaul capacity characteristics, a more appropriate and efficient network design is essential. The main scope of this thesis aims at optimizing the green performance of C-RANs in terms of energy-efficiency under the non-ideal fronthaul capacity condition, namely energy-efficient design in limited fronthaul capacity C-RANs. Our study, via jointly determining the transmit beamforming, RRH selection, and RRH–user association, targets the following three vital design issues: the optimal trade-off between maximizing achievable sum rate and minimizing total power consumption, the maximum energy-efficiency under adaptive rate-dependent power model, the optimal joint energy-efficient design of virtual computing along with the radio resource allocation in virtualized C-RANs. The significant contributions and novelties of this work can be elaborated in the followings. Firstly, the joint design of transmit beamforming, RRH selection, and RRH–user association to optimize the trade-off between user sum rate maximization and total power consumption minimization in the downlink transmissions of C-RANs is presented in Chapter 3. We develop one powerful with high-complexity and two novel efficient low-complexity algorithms to respectively solve for a global optimal and high-quality sub-optimal solutions. The findings in this chapter show that the proposed algorithms, besides overcoming the burden to solve difficult non-convex problems within a polynomial time, also outperform the techniques in the literature in terms of convergence and achieved network performance. Secondly, Chapter 4 proposes a novel model reflecting the dependence of consumed power on the user data rate and highlights its impact through various energy-efficiency metrics in CRANs. The dominant performance of the results form Chapter 4, compared to the conventional work without adaptive rate-dependent power model, corroborates the importance of the newly proposed model in appropriately conserving the system power to achieve the most energy efficient C-RAN performance. Finally, we propose a novel model on the cloud center which enables the virtualization and adaptive allocation of computing resources according to the data traffic demand to conserve more power in Chapter 5. A problem of jointly designing the virtual computing resource together with the beamforming, RRH selection, and RRH–user association which maximizes the virtualized C-RAN energy-efficiency is considered. To cope with the huge size of the formulated optimization problem, a novel efficient with much lower-complexity algorithm compared to previous work is developed to achieve the solution. The achieved results from different evaluations demonstrate the superiority of the proposed designs compared to the conventional work

Resource Allocation Techniques for Non-Orthogonal Multiple Access in Beyond 5G

To support the wide range of envisioned applications, including autonomous vehicles, augmented reality, holographic communication, and Internet of Everything (IoE), future wireless networks must meet demanding requirements for higher spectral and energy efficiency, lower end-to-end latency and massive connectivity. This requires a vast upgrade in the technologies of the sixth-generation (6G) wireless networks. Non-orthogonal multiple access (NOMA) has been advocated as a prospective effective multiple access technique for future wireless networks due to the wide range of its potential benefits, including superior spectral efficiency (SE), energy efficiency (EE), compatibility, user fairness, and flexibility. To exploit additional degrees of freedom and address the computational complexity with massive connectivity, NOMA has been recently combined with different types of multiple access techniques and appropriate optimization designs. Hence, this thesis attempts to utilize the combination of NOMA with different key technologies, including multiple antenna techniques, conventional OMA techniques, and intelligent reflecting surface (IRS). In particular, different resource allocation techniques have been developed for such integrated NOMA systems, from the downlink (DL) single-input single-output (SISO)-NOMA system, to DL multiple-input single-output (MISO)-NOMA system, as well as the IRS-assisted NOMA system. Firstly, a hybrid time division multiple access (TDMA)-NOMA system is considered, where both the available time slots and the available transmit power are jointly allocated to maximize the global EE. To further exploit the promising advantages of this hybrid system, the SE-EE trade-off based design and max-min fairness based design are presented in this thesis. By utilizing different convex relaxation and approximation techniques, the non-convexity of the formulated optimization problems are transformed into convex problems. Finally, this thesis investigates a worst-case robust design for an IRS-assisted NOMA multi-user MISO system to maximize the EE with a set of quality of service (QoS) constraints. In particular, an iterative algorithm based on alternating optimization (AO) is proposed to design the transmit beamforming vectors at the base station (BS) and reflection coefficient matrix for IRS. The effectiveness advantages of all the proposed schemes are demonstrated through numerical simulation results