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Introduction

  • Tho Le-Ngoc
  • Khoa Tran Phan
Chapter
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Abstract

The past decade has seen the tremendous growth of wireless communications with the increasing demand for various emerging applications such as video transmissions, mobile entertainment, mobile healthcare etc., which require higher data rate and/or more stringent delay quality-of-service (QoS). Consequently, in the development of next-generation wireless systems, it is a crucial task to provide wireless connections with better QoS such as higher data rate, smaller delay etc. [1, 2]. However, such task is not easy due to many inherent challenges. One challenge is the fact that wireless signal strength randomly fluctuates over time due to varying fading [3]. There are large-scale fading effects, where the received signal strength changes over distance because of the path loss and shadowing, and small-scale fading effects, where the received signal strength changes because of the constructive and destructive interference of multiple reflecting and refracting signal paths. In addition, the available radio resources are limited. Hence, efficient (radio) resource allocation is crucial to combat the fading effects of wireless channels, and providing satisfactory QoS to the users [4].

Keywords

Fading Channel Power Allocation Energy Harvesting Markov Decision Process Delay Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Tho Le-Ngoc
    • 1
  • Khoa Tran Phan
    • 2
  1. 1.Department of Electrical and Computer EngineeringMcGill UniversityMontrealCanada
  2. 2.Department of Electrical and Computer Systems EngineeringMonash UniversityClaytonAustralia

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