Incorporating Energy maps to measure and compare the coherence time and spreading period across mobile wireless networks

Literature Review Report

M.Sc Wireless Communication Systems Engineering 

Table of Contents: 

1. Introduction 

   1.1 Problem Definition

   1.2 Aim of the Project

   1.3 Objectives of the Project 

2. Project Deliverables 

3. Research Methodlogy 

4. Concepts of Energy Maps

    4.1 Modified DSR 

    4.2 Implementation of Overhead Reduction

         4.2.1 Algorithm for Overhead Reduction 

    4.3 Efficient management of Energy in Modified DSR

         4.3.1 Algorithm for implementing power management

    4.4 Hybrid Wireless networks

                 4.4.1 Security Issues

            In Uplink Opportunistic Throughput Maximization

            In Downlink Opportunistic Utility Maximization

            Scheduling Proportional Fair

            Scheduling General Utility-Based                    




Problem definition:

            Efficiency of mobile wireless networks plays a very important role in estimating the overall performance of wireless communication. Estimating the performance of mobile wireless networks at individual node is an easy process, but the actual end-to-end quality of service of these networks can be estimated perfectly when the entire network with all the nodes is considered. Energy consumption is the main issue with the mobile wireless networks and to reduce the energy consumption, energy maps can be opted as the best choice in these wireless networks. Planning the perfect energy consumption mechanism across the mobility nodes is really a critical task and there are many existing techniques to achieve this and they are proved to be failure in case of high mobility nodes in the mobile wireless communication networks. 

            To achieve the optimal energy consumption, an end-to-end energy maps are incorporated in the proposed algorithm, where few metrics like energy potential, distribution time, sharing time and fusing time are also taken in to consideration. Internal logic is used to calculate the energy and the coherence time across the mobile wireless networks. Maximum duration for which the end-to-end QoS metrics remains same is predicted with the coherence time and spreading period represents the period of time taken to spread these QoS metrics across all the nodes in the mobile wireless networks. Energy maps are constructed based on these metrics. 

Aim of the Project:


            To incorporate the energy maps across the mobile wireless networks for optimal energy consumption and to compare the QoS metrics with the help of Coherence time and spreading period. 

Objective of the Project:


Following are the research objectives 

  • To understand the concept of energy consumption across the nodes of mobile wireless networks and how to optimize the energy consumption.
  • To document the critical analysis of the energy optimization techniques and QoS metric across the mobile wireless nodes.
  • To design and propose logic which can be simple enough to calculate the energy consumption across the mobile nodes.
  • To calculate coherence time and spreading period of the QoS metrics considered and compare them with respective to the energy maps across the nodes
  • To develop a dot net based code to demonstrate the proposed algorithm/logic practically

To evaluate the system is developed and also to document the observations.

Project Deliverables: 

    Following are the deliverables of this project:

  • Literature review on mobile wireless networks and the importance of coherence time and spreading period across them with the limitations of existing systems.
  • Path integration algorithm that can incorporate energy maps across mobile wireless networks.
  • Design document explaining the front end and backend of the application
  • Dot net code that can demonstrate the application practically
  • Results and observations in a proper thesis format 

Research Method: 

          I will make use of both qualitative and quantitative methods of research to proceed with this project. I will study the concepts of energy maps using qualitative methods and develop the proposed algorithm using quantitative methods of research.