Fairness-Oriented and QoS-Aware Radio Resource Management in OFDMA Packet Radio Networks: Practical Algorithms and System Performance

During the last two decades, wireless technologies have demonstrated their importance in people’s personal communications but also as one of the fundamental drivers of economic growth, first in the form of cellular networks (2G, 3G and beyond) and more recently in terms of wireless computer networks (e.g. Wi-Fi,) and wireless Internet connectivity. Currently, the development of new packet radio systems is evolving, most notably in terms of 3GPP Long Term Evolution (LTE) and LTE-Advanced, in order to utilize the available radio spectrum as efficiently as possible. Therefore, advanced radio resource management (RRM) techniques have an important role in current and emerging future mobile networks. In all wireless systems, the data throughput and the average data delay performance, especially in case of best effort services, are greatly degraded when the traffic-load in the system is high. This is because the radio resources (time, frequency and space) are shared by multiple users. Another big problem is that the transmission performance can vary heavily between different users, since the channel state greatly depends on the communication environment and changes therein. To solve these challenges, new major technology innovations are needed. This thesis considers new practical fairness-oriented and quality-of-service (QoS) -aware RRM algorithms in OFDMA-based packet radio networks. Moreover, using UTRAN LTE radio network as application example, we focus on analyzing and enhancing the system-level performance by utilizing state-of-the-art waveform and radio link developments combined with advanced radio resource management methods. The presented solutions as part of RRM framework consist of efficient packet scheduling, link adaptation, power control, admission control and retransmission mechanisms. More specifically, several novel packet scheduling algorithms are proposed and analyzed to address these challenges. This dissertation deals specifically with the problems of QoS provisioning and fair radio resource distribution among users with limited channel feedback, admission and power control in best effort and video streaming type traffic scenarios, and the resulting system-level performance. The work and developments are practically-oriented taking aspects like finite channel state information (CSI), reporting delays and retransmissions into account. Consequently, the multi-user diversity gain with opportunistic frequency domain packet scheduling (FDPS) is further explored in spatial domain by taking the multiantenna techniques and spatial division multiplexing functionalities into account. Validation and analysis of the proposed solutions is performed through extensive system level simulations modeling the behavior and operation of a complete multiuser cell in the overall network. Based on the obtained performance results, it is confirmed that greatly improved fairness can be fairly easily built in to the scheduling algorithm and other RRM mechanisms without considerably degrading e.g. the average cell throughput. Moreover, effective QoS-provisioning framework in video streaming type traffic scenarios demonstrate the effectiveness of the presented solutions as increased system capacity measured in terms of the number of users or parallel streaming services supported simultaneously by the network

Advanced Wireless LAN

The past two decades have witnessed starling advances in wireless LAN technologies that were stimulated by its increasing popularity in the home due to ease of installation, and in commercial complexes offering wireless access to their customers. This book presents some of the latest development status of wireless LAN, covering the topics on physical layer, MAC layer, QoS and systems. It provides an opportunity for both practitioners and researchers to explore the problems that arise in the rapidly developed technologies in wireless LAN

Massive MIMO for Internet of Things (IoT) Connectivity

Massive MIMO is considered to be one of the key technologies in the emerging 5G systems, but also a concept applicable to other wireless systems. Exploiting the large number of degrees of freedom (DoFs) of massive MIMO essential for achieving high spectral efficiency, high data rates and extreme spatial multiplexing of densely distributed users. On the one hand, the benefits of applying massive MIMO for broadband communication are well known and there has been a large body of research on designing communication schemes to support high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT) is still a developing topic, as IoT connectivity has requirements and constraints that are significantly different from the broadband connections. In this paper we investigate the applicability of massive MIMO to IoT connectivity. Specifically, we treat the two generic types of IoT connections envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable low-latency communication (URLLC). This paper fills this important gap by identifying the opportunities and challenges in exploiting massive MIMO for IoT connectivity. We provide insights into the trade-offs that emerge when massive MIMO is applied to mMTC or URLLC and present a number of suitable communication schemes. The discussion continues to the questions of network slicing of the wireless resources and the use of massive MIMO to simultaneously support IoT connections with very heterogeneous requirements. The main conclusion is that massive MIMO can bring benefits to the scenarios with IoT connectivity, but it requires tight integration of the physical-layer techniques with the protocol design.Comment: Submitted for publicatio

Mobile and Wireless Communications

Mobile and Wireless Communications have been one of the major revolutions of the late twentieth century. We are witnessing a very fast growth in these technologies where mobile and wireless communications have become so ubiquitous in our society and indispensable for our daily lives. The relentless demand for higher data rates with better quality of services to comply with state-of-the art applications has revolutionized the wireless communication field and led to the emergence of new technologies such as Bluetooth, WiFi, Wimax, Ultra wideband, OFDMA. Moreover, the market tendency confirms that this revolution is not ready to stop in the foreseen future. Mobile and wireless communications applications cover diverse areas including entertainment, industrialist, biomedical, medicine, safety and security, and others, which definitely are improving our daily life. Wireless communication network is a multidisciplinary field addressing different aspects raging from theoretical analysis, system architecture design, and hardware and software implementations. While different new applications are requiring higher data rates and better quality of service and prolonging the mobile battery life, new development and advanced research studies and systems and circuits designs are necessary to keep pace with the market requirements. This book covers the most advanced research and development topics in mobile and wireless communication networks. It is divided into two parts with a total of thirty-four stand-alone chapters covering various areas of wireless communications of special topics including: physical layer and network layer, access methods and scheduling, techniques and technologies, antenna and amplifier design, integrated circuit design, applications and systems. These chapters present advanced novel and cutting-edge results and development related to wireless communication offering the readers the opportunity to enrich their knowledge in specific topics as well as to explore the whole field of rapidly emerging mobile and wireless networks. We hope that this book will be useful for students, researchers and practitioners in their research studies

Cross-layer Design for Wireless Mesh Networks with Advanced Physical and Network Layer Techniques

Cross-layer optimization is an essential tool for designing wireless network protocols. We present a cross-layer optimization framework for wireless networks where at each node, various smart antenna techniques such as beam-forming, spatial division multiple access and spatial division multiplexing are employed. These techniques provide interference suppression, capability for simultaneous communication with several nodes and transmission with higher data rates, respectively. By integrating different combinations of these multi-antenna techniques in physical layer with various constraints from MAC and network layers, three Mixed Integer Linear Programming models are presented to minimize the scheduling period. Since these optimization problems are combinatorially complex, the optimal solution is approached by a Column Generation (CG) decomposition method. Our numerical results show that the resulted directive, multiple access and multiplexing gains combined with scheduling, effectively increase both the spatial reuse and the capacity of the links and therefore enhance the achievable system throughput. The introduced cross-layer approach is also extended to consider heterogeneous networks where we present a multi-criteria optimization framework to model the design problem with an objective of jointly minimizing the cost of deployment and the scheduling period. Our results reveal the significant benefits of this joint design method. We also investigate the achievable performance gain that network coding (with opportunistic listening) when combined with Successive Interference Cancellation (SIC) brings to a multi-hop wireless network. We develop a cross-layer formulation in which SIC enables concurrent receptions from multiple transmitters and network coding reduces the transmission time-slot for minimizing the scheduling time. To solve this combinatorially complex non-linear problem, we decompose it to two linear sub-problems; namely opportunistic network coding aware routing, and scheduling sub-problems. Our results affirm our expectation for a remarkable performance improvement when both techniques are jointly used. Further, we develop an optimization model for combining SIC with power control (PC). Our model optimally adjusts the transmission power of nodes to avoid interference on unintended receivers and properly embraces undesired interference through SIC. Therefore, it provides a balance between usage of PC and SIC at the transmitting and receiving sides, respectively. Our results show considerable throughput improvement in dense and heavily loaded networks

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