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

EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design

The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application

Cognitive Hierarchy Theory for Distributed Resource Allocation in the Internet of Things

In this paper, the problem of distributed resource allocation is studied for an Internet of Things (IoT) system, composed of a heterogeneous group of nodes compromising both machine-type devices (MTDs) and human-type devices (HTDs). The problem is formulated as a noncooperative game between the heterogeneous IoT devices that seek to find the optimal time allocation so as to meet their quality-of-service (QoS) requirements in terms of energy, rate and latency. Since the strategy space of each device is dependent on the actions of the other devices, the generalized Nash equilibrium (GNE) solution is first characterized, and the conditions for uniqueness of the GNE are derived. Then, to explicitly capture the heterogeneity of the devices, in terms of resource constraints and QoS needs, a novel and more realistic game-theoretic approach, based on the behavioral framework of cognitive hierarchy (CH) theory, is proposed. This approach is then shown to enable the IoT devices to reach a CH equilibrium (CHE) concept that takes into account the various levels of rationality corresponding to the heterogeneous computational capabilities and the information accessible for each one of the MTDs and HTDs. Simulation results show that the proposed CHE solution keeps the percentage of devices with satisfied QoS constraints above 96% for IoT networks containing up to 10,000 devices without considerably degrading the overall system performance.Comment: To appear in IEEE Transactions on Wireless Communications, 201