Abstract

Abstract: Energy Harvesting (EH) is an emerging communications paradigm to defeat the limitation of network longevity by recharging the nodes by harvesting energy from the environment. The Energy Harvesting Network (EHN) requires a stable and efficient power control scheme like other conventional communication systems. It is more complicated than conventional communication networks, in that it should not only consider the quality of service requirements of the network but also adapt to the randomness of the energy arrival. In this thesis, several optimal offline and online resource allocation strategies for point-to-point and two-hop EH communication networks over wireless fading channels are investigated. As a first step, the RGWF (Recursive Geometric Water-filling) algorithm is introduced, which provides an optimal offline transmission policy for a point-to-point EH communication system. Next, a network composed of a source, a relay, and a destination, where the source is an EH node is considered. Joint time scheduling and power allocation problems are formulated to maximize the network throughput by considering conventional and bufferaided link adaptive relaying protocols. Based on the modified RGWF algorithm, the joint power allocation and transmission time scheduling problem are decoupled, and efficient offline schemes are proposed for a two-hop wireless network for delay-tolerant and delay sensitive applications. In the second part, the aim is to obtain the optimal transmission policy that maximizes the average total throughput of a point-to-point EH communication system with low and high data arrival rate in an online manner. The solution is obtained using dynamic programming by casting the proposed problem as a semi-Markov decision process (SMDP). In a delay-tolerant approach with high data rate, a cross-layer adaptation is considered, where the proposed policy chooses modulation constellation for EH networks dynamically, depending on battery state, data buffer state in addition to channel state. The proposed SMDP-based dynamic programming approach has proven to be dynamically adaptive to the change of the channel and/or buffer states that optimally satisfy the BER requirements at the physical layer, and the overflow requirements at the data-link layer.

Highlights

  • 1.1 Background and MotivationWith increasing demand and explosive growth in wireless communications in recent years, energy conservation has become more desirable to help reducing the world’s energy consumption

  • Studies the traditional two-hop communication system for delay limited (DL) and delay tolerant (DT) relaying networks over fading channels, in which the source node transmits with power drawn from energy harvesting (EH) sources and the relay transmits with conventional non-Energy Harvesting (EH) sources

  • We show the performance of the proposed resource allocation schemes for delay-sensitive relaying in a two-hop wireless network with an EH source over a Rayleigh fading channel, whereas the non-EH relay link experiences an Additive White Gaussian Noise (AWGN) environment

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Summary

References ix

3.1 System model, K=7 epochs in [0,T] with (a) EH source, i.e., random energy arrivals xi. 5.2 Effect of average buffer delay on the throughput among different schemes. 91 5.3 Effect of average packet arrival rate on the throughput and the overflow probxii 5.2 Effect of average buffer delay on the throughput among different schemes. . . 91 5.3 Effect of average packet arrival rate on the throughput and the overflow probxii

Background and Motivation
CHAPTER 1. INTRODUCTION
Energy Harvesting in Wireless Communication Systems
Characteristics of EH Sources
Storage Capacity
Literature Review
Contributions
Thesis Organization
INTRODUCTION
Wireless System Model
Resource Allocation Approaches
Resource Allocation and Service Requirements
Objective Function
Constraints
Optimization Framework and General Tools
Single-hop Conventional Communication Systems
Single-hop EH Communication Systems
Chapter Summary
Introduction
Model Description
RGWF-EH Profile
Transmission policy
Throughput Maximization Problem for the DS case
Optimal Resource Allocation
Sub-optimal Resource Allocation
Pre-defined Data Rates (PDDR) Based
Throughput Maximization Problem for the DT Case
Sub-Optimal Resource Allocation
Relay In Demand using Average Fading (RID-AF) Based
Simulation Results
Problem Formulation
SMDP Formulation Of EH Technology
Set of Actions
Reward Model
Sojourn Time
Transition Probability
Energy Allocation Scheme By SMDP
Performance Evaluation
Channel Model
Battery Model
Data Buffer Model
SMDP Formulation of EH Cross-layer Adaptive
Problem Description
Problem Formulation and Policy
Solution Techniques
Proposed scheme cross-layer policy
Conclusion
Full Text
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