Leveraging Reconfigurable Massive MIMO Antenna Arrays for Enhanced Wireless Connectivity in Biomedical IoT...

Area of Science:

• Wireless Communication
• Biomedical Engineering
• Antenna Systems

Background:

• Smart healthcare demands real-time, energy-efficient, and interference-resilient communication.
• Biomedical Internet of Things (Bio-IoT) systems face challenges with reliable wireless connectivity for sensors due to mobility, latency, power, and interference.
• Existing solutions struggle to meet the stringent requirements of modern healthcare monitoring.

Purpose of the Study:

• To propose a novel reconfigurable massive multiple-input multiple-output (MIMO) antenna architecture for Bio-IoT systems.
• To enhance wireless connectivity reliability, energy efficiency, and interference resilience in smart healthcare environments.
• To address challenges posed by mobility, latency sensitivity, and multi-user interference in wearable and implantable biomedical sensors.

Main Methods:

• Developed a reconfigurable massive MIMO antenna architecture with hybrid analog-digital beamforming and adaptive signal processing.
• Integrated conventional algorithms (LMS, ZF, MVDR) with a novel mobility-aware beamforming scheme.
• Conducted system-level simulations using realistic channel models (Rayleigh, Rician, 3GPP UMa) to evaluate performance metrics.

Main Results:

• The proposed hybrid beamforming system significantly outperformed benchmarks.
• Achieved up to 35% higher throughput and a 65% reduction in packet drop rate.
• Demonstrated sub-10 ms latency even under high-mobility conditions, with robust interference nulling and dynamic lobe steering.

Conclusions:

• The proposed architecture is highly suitable for next-generation Bio-IoT deployments in smart hospitals.
• Enables secure, adaptive, and power-aware connectivity for critical healthcare monitoring.
• Addresses key challenges in wireless communication for advanced healthcare applications.