Electromagnetic Interference-Aware Transmission Scheduling and Power Control for Dynamic Wireless Access in Hospital Environments

• Published in: IEEE transactions on information technology in biomedicine Vol. 15; no. 6; pp. 890 - 899
• Main Authors: Phunchongharn, P., Hossain, E., Camorlinga, S.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2011
• Subjects: Algorithms; Computer Communication Networks - instrumentation; Computer Simulation; Electric Power Supplies; Electromagnetic interference; Electromagnetic interference (EMI); Electromagnetic Phenomena; electronic health (e-Health) applications; Health Facility Environment; Hospitals; Humans; Medical information systems; Medical services; Models, Theoretical; Power control; Quality of service; time-division multiple access (TDMA) with spatial reuse; transmission scheduling; Wireless communication; Wireless Technology - instrumentation
• ISSN: 1089-7771; 1558-0032; 1558-0032
• DOI: 10.1109/TITB.2011.2164258

We study the multiple access problem for e-Health applications (referred to as secondary users) coexisting with medical devices (referred to as primary or protected users) in a hospital environment. In particular, we focus on transmission scheduling and power control of secondary users in multiple spatial reuse time-division multiple access (STDMA) networks. The objective is to maximize the spectrum utilization of secondary users and minimize their power consumption subject to the electromagnetic interference (EMI) constraints for active and passive medical de vices and minimum throughput guarantee for secondary users. The multiple access problem is formulated as a dual objective optimization problem which is shown to be NP-complete. We propose a joint scheduling and power control algorithm based on a greedy approach to solve the problem with much lower computational complexity. To this end, an enhanced greedy algorithm is proposed to improve the performance of the greedy algorithm by finding the optimal sequence of secondary users for scheduling. Using extensive simulations, the tradeoff in performance in terms of spectrum utilization, energy consumption, and computational complexity is evaluated for both the algorithms.