Resource-Efficient Wireless Systems for Emerging Wireless Networks

As the wireless medium has become the primary source of communication and Internet connectivity, and as devices and wireless technologies become more sophisticated and capable, there has been a surge in the capacity demands and complexity of applications that run over these wireless devices. To sustain the volume and QoE guarantees of the data generated, the opportunity and need to rethink wireless network design across all the layers of the protocol stack has firmly emerged as a solution to enable the timely and reliable delivery of data, while handling the inherent challenges of a crowded wireless medium, such as congestion, interference, and hidden terminals. The research work presented in this dissertation builds efficient solutions and protocols with a theoretical foundation to address the challenges that arise in rethinking wireless network design. Example challenges include managing the overhead associated with complex systems. My work particularly focuses on the opportunities and challenges of sophisticated technology and systems in emerging wireless networks. I target the main thrusts in the evolution of wireless networks that create significant opportunity to achieve higher theoretical capacity, and have direct implications on our day-to-day wireless interactions: from enabling multifold increase in capacity in wireless physical links, to developing medium access techniques to exploit the high speed links, and making the applications more bandwidth efficient. I build deployable, and resource-aware wireless systems that exploit higher bandwidths by leveraging and advancing diverse research areas such as theory, analysis, protocol design, and wireless networking. Specifically, I identify the erroneous assumptions and fundamental limitations of existing solutions in capturing the true and complex interactions between wireless devices and protocols. I use these insights to guide practical and efficient protocol design, followed by thorough analysis and evaluation in testbed implementations via prototypes and measurements. I show that my proposed solutions achieve significant performance gains, at minimum cost to overhead

Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective

This article provides an overview of the state-of-art results on communication resource allocation over space, time, and frequency for emerging cognitive radio (CR) wireless networks. Focusing on the interference-power/interference-temperature (IT) constraint approach for CRs to protect primary radio transmissions, many new and challenging problems regarding the design of CR systems are formulated, and some of the corresponding solutions are shown to be obtainable by restructuring some classic results known for traditional (non-CR) wireless networks. It is demonstrated that convex optimization plays an essential role in solving these problems, in a both rigorous and efficient way. Promising research directions on interference management for CR and other related multiuser communication systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex optimization for signal processin

Spectrally and Energy Efficient Radio Resource Management for Multi-Operator Shared Networks

Commercial mobile communication systems are mainly based on licensed frequency spectrum, and the license is very expensive as the spectrum is a sparse wireless resource. Therefore, sharing this wireless resource is an essential requirement not only at the present but also in the future considering trends like connectivity for everybody and everything. In this thesis, we study the sharing of wireless resources with different approaches for realizing fair, efficient, and predictable sharing solutions in a controlled manner. The efficient use of wireless channel resources is an important target to reduce the costs of network operation and deployment. To achieve this, we need practical scheduling algorithms for wireless resources, out of which several of them will be presented and analyzed in this work. Different optimization frameworks for the spectral efficiency utility are presented, with an individual focus on guaranteeing resource or rate fairness among the operators in a network with shared radio resources. Thus, the presented proposals will help the mobile network operators to overcome the issues of losing network control and traceability of used wireless resources in a shared environment. Besides this, emerging vertical industries, such as automotive, healthcare, industry 4.0, internet of things (IoT) industries will put a certain burden on the wireless networks asking for guaranteed service level requirement from the mobile network operators. In this regard, this thesis provides the necessary methods addressing these challenges with the help of scheduling methods which are based on the joint optimization of spectral and energy efficiency. Thus, wireless networks will be enabled as a service function in a controlled and scalable way for new emerging markets. Furthermore, the presented solutions t well with the requirements of fifth generation (5G) network slicing

Resource Allocation in Wireless Body Area Networks: A Smart City Perspective

Healthcare is an essential service in smart cities. To deploy healthcare systems in such cities, personal health monitoring systems, infrastructure for collecting and delivering individual data, and a system for diagnosing symptoms are required. For the first requirement, wireless body area networks (WBANs) have recently received considerable attention from research communities. Owing to their main distinguishable features from general wireless sensor networks, research challenges regarding WBANs have been focused on network topology around the body and implanted nodes, efficient resource allocation, and power control. In this chapter, we provide a comprehensive discussion on the emerging research trends in the area of wireless sensor networks and a discussion of WBANs in terms of their resource allocation

Energy-efficient optimal power allocation in integrated wireless sensor and cognitive satellite terrestrial networks

This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach’s method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint

Matching Theory for Future Wireless Networks: Fundamentals and Applications

The emergence of novel wireless networking paradigms such as small cell and cognitive radio networks has forever transformed the way in which wireless systems are operated. In particular, the need for self-organizing solutions to manage the scarce spectral resources has become a prevalent theme in many emerging wireless systems. In this paper, the first comprehensive tutorial on the use of matching theory, a Nobelprize winning framework, for resource management in wireless networks is developed. To cater for the unique features of emerging wireless networks, a novel, wireless-oriented classification of matching theory is proposed. Then, the key solution concepts and algorithmic implementations of this framework are exposed. Then, the developed concepts are applied in three important wireless networking areas in order to demonstrate the usefulness of this analytical tool. Results show how matching theory can effectively improve the performance of resource allocation in all three applications discussed

When Cost-Efficient Technologies Meet Politics: A Case Study of Radical Wireless Network Implementation

Cost efficiency has been a dominant perspective in the traditional IT literature. However, in complex technology and business environment, the widely recognized cost efficient assumption of information technology has been increasingly challenged. Drawing from a case study of wireless network implementation situated in a politically sensitive workplace, this paper provided practice insights for IT managers in today’s networked economy. More specifically, stories experienced in the case study illustrated that despite well-calculated cost efficiency of wireless network infrastructure, the radical implementation process in the case organization encountered enormous challenges and opposition due to the fact that administrators failed to consider various stakeholders’ positions and interests. Eventually, the implementation objectives and outcome were considerably undermined. Implications from this empirical case research reemphasized the significance of understanding political forces situated in any business environment where different stakeholders hold conflicting interests. Lessons learned from the case story further encouraged IT managers and policy makers to better strategize emerging information technology in general and wireless networks in particular as the whole global society and business environment are increasingly facing an emerging wireless world