Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks

Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be promising in the fifth generation (5G) wireless networks. H-CRANs enable users to enjoy diverse services with high energy efficiency, high spectral efficiency, and low-cost operation, which are achieved by using cloud computing and virtualization techniques. However, H-CRANs face many technical challenges due to massive user connectivity, increasingly severe spectrum scarcity and energy-constrained devices. These challenges may significantly decrease the quality of service of users if not properly tackled. Non-orthogonal multiple access (NOMA) schemes exploit non-orthogonal resources to provide services for multiple users and are receiving increasing attention for their potential of improving spectral and energy efficiency in 5G networks. In this article a framework for energy-efficient NOMA H-CRANs is presented. The enabling technologies for NOMA H-CRANs are surveyed. Challenges to implement these technologies and open issues are discussed. This article also presents the performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure

A Comprehensive Study of Multiple Access Techniques in 6G Networks

With the proliferation of numerous burgeoning services such as ultra-reliable low-latency communication (URLLC), massive machine type communications (mMTC), enhanced mobile broadband (eMBB), among others, wireless communication systems are expected to face daunting challenges. In order to satisfy these ever-increasing traffic demands, diverse quality-of-services (QoS) requirements, and the massive connectivity accompanied by these new applications, various innovative and promising technologies, and architectures need to be developed. Novel multiple-access techniques are currently being explored in both academia and industry in order to accommodate such unprecedented requirements. Non-orthogonal multiple access (NOMA) has been deemed as one of the vital enabling multiple access techniques for the upcoming six-generation (6G) networks. This is due to its ability to enhance network spectral efficiency (NSE) and support a massive number of connected devices. Owing to its potential benefits, NOMA is recognized as a prominent member of next-generation multiple access (NGMA). Several emerging techniques such as full-duplex (FD) communication, device-to-device (D2D) communications, reconfigurable intelligent surface (RIS), coordinated multipoint (CoMP), cloud radio access networks, are being gradually developed to address fundamental problems in future wireless networks. In this thesis, and with the goal of converging toward NGMA, we investigate the synergistic integration between NOMA and other evolving physical layer technologies. Specifically, we analyze this integration aiming at improving the performance of cell-edge users (CEUs), mitigating the detrimental effect of inter-cell interference (ICI), designing energy-efficient multiple access toward ``green’’ wireless networks, guarantying reliable communication between NOMA UEs and base stations (BSs)/remote radio heads (RRHs), and maintaining the required QoS in terms of the minimum achievable data rate, especially at CEUs. Regarding the ICI mitigation in multi-cell NOMA networks and tackling the connectivity issue in traditional CoMP-based OMA networks, we first investigate the integration between location-aware CoMP transmission and NOMA in downlink heterogeneous C-RAN. In doing so, we design a novel analytical framework using tools from stochastic geometry to analyze the system performance in terms of the average achievable data rate per NOMA UE. Our results reveal that CoMP NOMA can provide a significant gain in terms of network spectral efficiency compared to the traditional CoMP OMA scheme. In addition, with the goal of further improving the performance of CEUs and user fairness, cooperative transmission with the aid of D2D communication and FD or half-duplex (HD) transmission, has been introduced to NOMA, which is commonly known as cooperative NOMA (C-NOMA). As a result, we extend our study to also investigate the potential gains of investigating CoMP and C-NOMA. In such a framework, we exploit the cooperation between the RRHs/BSs and the successive decoding strategy at NOMA UEs that are near the RRHs/BSs. Specifically, we investigate both performance analysis and resource management optimization (power control and user pairing). Our results show that the transmit power at the BS, the transmit power at the relay user, and the self-interference (SI) value at the relay user determine which multiple access technique, CoMP NOMA, CoMP HD C-NOMA, and CoMP FD C-NOMA, should be adopted at the BSs. Now, to assist in designing energy-efficient multiple access techniques and guarantying reliable communication for NOMA UEs, this thesis explores the interplay between FD/HD C-NOMA and RIS. We show that the proposed model has the best performance in terms of network power consumption compared to other multiple access techniques in the literature, which leads to ``green'' future wireless networks. Moreover, our results show that the network power consumption can be significantly reduced by increasing the number of RIS elements. A more significant finding is that the location of the RIS depends on the adopted multiple access techniques. For example, it is not recommended to deploy the RIS besides the BS if the adopted multiple access is HD C-NOMA. Another insight that has been unveiled is the FD C-NOMA with the assistance of RIS has more resistance to the residual SI effect, due to the FD transmission, and can tolerate high SI values compared to the same scheme without RIS. Although much work has been conducted to improve the network spectral efficiency of multi-cell NOMA cellular networks, the required QoS by the upcoming 6G applications, in terms of the minimum achievable rate, may not be guaranteed at CEUs. This is due to their distant locations from their serving BSs, and thus, they experience severe path-loss attenuation and high ICI. This thesis addresses this research gap by studying the synergistic integration between RIS, NOMA, and CoMP in a multi-user multi-cell scenario. Unlike the developed high-complexity optimal solutions or the low-complexity sub-optimal solutions in the literature for the power allocation problem, we derive a low-complexity optimal solution in a such challenging scenario. We also consider the interdependency between the user clustering policies in different coordinated cells, which has been ignored in the literature. Finally, we prove that this integration between RIS, NOMA, and CoMP can attain a high achievable rate for CEUs, ameliorate spectral efficiency compared to existing literature, and can form a novel paradigm for NGMA

A survey of multi-access edge computing in 5G and beyond : fundamentals, technology integration, and state-of-the-art

Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research

A Tutorial on Clique Problems in Communications and Signal Processing

Since its first use by Euler on the problem of the seven bridges of K\"onigsberg, graph theory has shown excellent abilities in solving and unveiling the properties of multiple discrete optimization problems. The study of the structure of some integer programs reveals equivalence with graph theory problems making a large body of the literature readily available for solving and characterizing the complexity of these problems. This tutorial presents a framework for utilizing a particular graph theory problem, known as the clique problem, for solving communications and signal processing problems. In particular, the paper aims to illustrate the structural properties of integer programs that can be formulated as clique problems through multiple examples in communications and signal processing. To that end, the first part of the tutorial provides various optimal and heuristic solutions for the maximum clique, maximum weight clique, and $k$-clique problems. The tutorial, further, illustrates the use of the clique formulation through numerous contemporary examples in communications and signal processing, mainly in maximum access for non-orthogonal multiple access networks, throughput maximization using index and instantly decodable network coding, collision-free radio frequency identification networks, and resource allocation in cloud-radio access networks. Finally, the tutorial sheds light on the recent advances of such applications, and provides technical insights on ways of dealing with mixed discrete-continuous optimization problems

Signal Processing and Learning for Next Generation Multiple Access in 6G

Wireless communication systems to date primarily rely on the orthogonality of resources to facilitate the design and implementation, from user access to data transmission. Emerging applications and scenarios in the sixth generation (6G) wireless systems will require massive connectivity and transmission of a deluge of data, which calls for more flexibility in the design concept that goes beyond orthogonality. Furthermore, recent advances in signal processing and learning have attracted considerable attention, as they provide promising approaches to various complex and previously intractable problems of signal processing in many fields. This article provides an overview of research efforts to date in the field of signal processing and learning for next-generation multiple access, with an emphasis on massive random access and non-orthogonal multiple access. The promising interplay with new technologies and the challenges in learning-based NGMA are discussed

Mathematical Modelling and Analysis of Spatially Correlated Heterogeneous and Vehicular Networks - A Stochastic Geometry Approach

Heterogeneous Cellular Networks (HCNs) and vehicular communications are two key ingredients of future 5G communication networks, which aim at providing high data rates on the one former case and high reliability on the latter one. Nevertheless, in these two scenarios, interference is the main limiting factor, which makes achieving the required performance, i.e., data rate or reliability, a challenging task. Hence, in order to cope with such issue, concepts like uplink/downlink (UL/DL) decoupling, Interference-Aware (IA) strategies or cooperative communications with Cloud Radio Access Networks (CRANs) has been introduced for new releases of 4G and future 5G networks. Additionally, for the sake of increasing the data rates, new multiple access schemes like Non-Orthogonal Multiple Access (NOMA) has been proposed for 5G networks. All these techniques and concepts require accurate and tractable mathematical modelling for performance analysis. This analysis allows us to obtain theoretical insights about key performance indicators leading to a deep understanding about the considered techniques. Due to the random and irregular nature that exhibits HCNs, as well as vehicular networks, stochastic geometry has appeared recently as a promising tool for system-level modelling and analysis. Nevertheless, some features of HCNs and vehicular networks, like power control, scheduling or frequency planning, impose spatial correlations over the underlying point process that complicates significantly the mathematical analysis. In this thesis, it has been used stochastic geometry and point process theories to investigate the performance of these aforementioned techniques. Firstly, it is derived a mathematical framework for the analysis of an Interference-Aware Fractional Power Control (IAFPC) for interference mitigation in the UL of HCNs. The analysis reveals that IAFPC outperforms the classical FPC in terms of Spectral Efficiency (SE), average transmitted power, and mean and variance of the interference. Then, it is investigated the performance of a scheduling algorithm where the Mobile Terminals (MTs) may be turned off if they cause a level of interference greater than a given threshold. Secondly, a multi-user UL model to assess the coverage probability of different MTs in each cell is proposed. Then, the coverage probability of cellular systems under Hoyt fading (Nakagami-q) is studied. This fading model, allows us to consider more severe fading conditions than Rayleigh, which is normally the considered fading model for the sake of tractability. Thirdly, a novel NOMA-based scheme for CRANs is proposed, modelled and analyzed. In this scheme, two users are scheduled in the same resources according to NOMA; however the performance of cell-edge users is enhanced by means of coordinated beamforming. Finally, the performance of a decentralized Medium Access Control (MAC) algorithm for vehicular communications is investigated. With this strategy, the cellular network provides frequency and time synchronization for direct Vehicle to Vehicle (V2V) communication, which is based on its geographical information. The analysis demonstrates that there exists an operation regime where the performance is noise-limited. Then, the optimal transmit power that maximizes the Energy Efficiency (EE) of the system subject to a minimum capture probability constraint is derived