Abstract

In this thesis, we introduce an approach to jointly minimizing energy consumption of wireless transmitters and the harmful interference on sensitive medical devices, and optimizing the central controller placement for collecting data from transmitters. More specifically, a multi-objective non-convex mixed-integer non-linear programming (MINLP) problem is defined and formulated to optimize transmit power of wireless users and CPP deployment along with guaranteeing minimized EMI to comply with the immunity level of medical devices. To solve this problem, an important step is to convexify it. Then we propose the use of a standard branch-and-bound algorithm. Also the program is coded in MATLAB with the help of OPTItoolbox to find the optimal solution. To conduct a numerical result analysis, we considered different cases within a single floor of a hospital and a few scenarios for a two-story hospital building. The values of different variables are changed throughout the simulation and the results are compared. These variables include immunity level of sensitive medical devices, maximum transmission power of wireless users, floor attenuation factor, etc. Our results show the improvement in throughput and guaranteed immunity for medical devices, when the proposed formulation is deployed along with a branch-and-bound algorithm.

Highlights

  • The improvements in computing and communication systems have had great influence in different aspect of our lives

  • We described the formulation of our problem of transmission power and electromagnetic interference (EMI) minimization, central processing point (CPP) deployment optimization, and CPP-to-SA association

  • An approach to solve a multi-objective problem of EMI-aware central processing point (CPP) deployment for wireless sensor networks in hospitals, was presented

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Summary

Introduction

The improvements in computing and communication systems have had great influence in different aspect of our lives. Sensors, electrical devices, networks and wireless communication systems can replace traditional systems in healthcare environments, as trustworthiness of these technologies have reached to an acceptable extent This will minimize both operational and capital costs by increasing efficiency while improving the delivery of service to patients [1]. This can be addressed by controlling the maximum transmission power of wireless devices and keeping the more sensitive devices as far as possible from the transmitters In this sense, minimizing the transmission power reduces the harmful interferences and increases the life time of battery powered nodes. Quality of service methods can be deployed to maintain desired throughput for such nodes Another commonly used terminology for integration of information and communications technology within healthcare, is m-Health or mobile health. We will focus on jointly minimizing energy consumption of wireless transmitters and the harmful interference on sensitive medical devices, and optimizing the central controller placement for collecting data from transmitters

Motivation and contribution
Thesis organization
Background
Networks at hospitals
Cognitive radio-based communication networks
Optimization problems and nonlinear programming
Chapter summary
Literature Review
Technologies and standards
Potential challenges in design and implementation
Hospital environment
Transceiver model
Channel model
Chapter 5 Problem Formulation
Initial formulation
Reformulation
Branch-and-bound algorithm
30: Stop: problem in solving subproblem
Simulation setup
One CPP
Two CPP’s
More Random SA’s
EMI sensitivity
Summary and conclusion
Findings
Future work
Full Text
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