A QoS Optimization Approach in Cognitive Body Area Networks for Healthcare Applications

Wireless body area networks are increasingly featuring cognitive capabilities. This work deals with the emerging concept of cognitive body area networks. In particular, the paper addresses two important issues, namely spectrum sharing and interferences. We propose methods for channel and power allocation. The former builds upon a reinforcement learning mechanism, whereas the latter is based on convex optimization. Furthermore, we also propose a mathematical channel model for off-body communication links in line with the IEEE 802.15.6 standard. Simulation results for a nursing home scenario show that the proposed approach yields the best performance in terms of throughput and QoS for dynamic environments. For example, in a highly demanding scenario our approach can provide throughput up to 7 Mbps, while giving an average of 97.2% of time QoS satisfaction in terms of throughput. Simulation results also show that the power optimization algorithm enables reducing transmission power by approximately 4.5 dBm, thereby sensibly and significantly reducing interference.

• Publication year

  2017

• Venue

  Italian National Conference on Sensors

• Publication date

  2017-04-01

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.3390/s17040780PMID 28383500PMCID 5422053
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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