Optimal Design of Switchable Wearable Antenna Array for Wireless Sensor Networks

Area of Science:

• Electromagnetics and Antenna Design
• Wireless Communication Systems
• Biomedical Engineering

Background:

• Wearable antenna arrays are crucial for off-body links in wireless body area networks (WBANs).
• Optimizing antenna placement and phasing is key to improving signal quality and reducing interference.
• Existing designs often lack adaptability to dynamic signal and interference environments.

Purpose of the Study:

• To develop an optimum design for a switchable radiation pattern wearable antenna array.
• To enhance the signal-to-interference ratio (SIR) for off-body WBAN links.
• To investigate the effectiveness of genetic algorithms and novel objective functions in antenna array optimization.

Main Methods:

• Utilized a genetic algorithm to optimize the spatial placement and feed phasing of a four-element wearable antenna array.
• Developed a computationally efficient model based on full-wave simulations with a simplified cylindrical human body model.
• Proposed and evaluated four objective functions (min-max, nadir point distance maximization, utopia point distance minimization, full Pareto-like) based on SIR.

Main Results:

• The optimized antenna array design demonstrated a switchable radiation pattern, directing gain towards the signal and away from interference.
• A significant improvement in performance, particularly in signal-to-interference ratio, was achieved compared to the initial heuristic design.
• The proposed simplified model provided efficient and accurate simulations of the array radiation pattern.

Conclusions:

• The novel approach offers an effective method for the optimum design of wearable antenna arrays for WBANs.
• The optimized design significantly improves the signal-to-interference ratio, enhancing the reliability of off-body communication.
• Genetic algorithms and the proposed objective functions are powerful tools for designing adaptive and efficient antenna systems.