Spectrum- and Energy-Efficient Radio Resource Allocation for Wireless Communications

Wireless communications has been evolved significantly over the last decade. During this period, higher quality of service (QoS) requirements have been proposed to support various services. In addition, due to the increasing number of wireless devices and transmission, the energy consumption of the wireless networks becomes a burden. Therefore, the energy efficiency is considered as important as spectrum efficiency for future wireless communications networks, and spectrum and energy efficiency have become essential research topics in wireless communications. Moreover, due to the exploding of number mobile devices, the limited radio resources have become more and more scarce. With large numbers of users and various QoS requirements, a lot of wireless communications networks and techniques have emerged and how to effectively manage the limited radio resources become much more important. In this dissertation, we focus our research on spectrum- and energy-efficient resource allocation schemes in wireless communication networks. Recently, heterogeneous networks (HetNets) have been proposed and studied to improve the spectrum efficiency. In a two-tier heterogeneous network, small base stations reuse the same spectrum with macro base stations in order to support more transmission over the limited frequency bands. We design a cascaded precoding scheme considering both interference cancellation and power allocation for the two-tier heterogeneous network. Besides heterogeneous networks, as the fast development of intelligent transportation, we study the spectrum- and energy-efficient resource allocation in vehicular communication networks. The intelligent transportation and vehicular communications both have drawn much attention and are faced special wireless environment, which includes Doppler effects and severe uncertainties in channel estimation. A novel designed spectrum efficiency scheme is studied and verified. With consideration of energy efficiency, the device-to-device (D2D) enabled wireless network is an effective network structure to increase the usage of spectrum. From a device\u27s perspective, we design an energy-efficient resource allocation scheme in D2D communication networks. To improve the energy efficiency of wireless communication networks, energy harvesting technique is a powerful way. Recently, the simultaneous wireless information and power transfer (SWIPT) has been proposed as a promising energy harvesting method for wireless communication networks, based on which we derive an energy-efficient resource allocation scheme for SWIPT cooperative networks, which considers both the power and relay allocation. In addition to the schemes derivation for spectrum- and energy-efficient resource allocation, simulation results and the proofs of the proposed propositions are provided for the completeness of this dissertation

Real-time Optimal Resource Allocation for Embedded UAV Communication Systems

We consider device-to-device (D2D) wireless information and power transfer systems using an unmanned aerial vehicle (UAV) as a relay-assisted node. As the energy capacity and flight time of UAVs is limited, a significant issue in deploying UAV is to manage energy consumption in real-time application, which is proportional to the UAV transmit power. To tackle this important issue, we develop a real-time resource allocation algorithm for maximizing the energy efficiency by jointly optimizing the energy-harvesting time and power control for the considered (D2D) communication embedded with UAV. We demonstrate the effectiveness of the proposed algorithms as running time for solving them can be conducted in milliseconds.Comment: 11 pages, 5 figures, 1 table. This paper is accepted for publication on IEEE Wireless Communications Letter

Optimal Resource Allocation in Ultra-low Power Fog-computing SWIPT-based Networks

In this paper, we consider a fog computing system consisting of a multi-antenna access point (AP), an ultra-low power (ULP) single antenna device and a fog server. The ULP device is assumed to be capable of both energy harvesting (EH) and information decoding (ID) using a time-switching simultaneous wireless information and power transfer (SWIPT) scheme. The ULP device deploys the harvested energy for ID and either local computing or offloading the computations to the fog server depending on which strategy is most energy efficient. In this scenario, we optimize the time slots devoted to EH, ID and local computation as well as the time slot and power required for the offloading to minimize the energy cost of the ULP device. Numerical results are provided to study the effectiveness of the optimized fog computing system and the relevant challenges

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

Efficient energy management for the internet of things in smart cities

The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, and so on. The Internet of Things offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while IoT devices continue to grow in both numbers and requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle the associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low-power devices and its related challenges. We detail two case studies. The first one targets energy-efficient scheduling in smart homes, and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for the case studies demonstrate the tremendous impact of energy-efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities