A Cooperative Transmission Scheme for Wearable Sensor Networks
As we become more aware of the connection between physical health and physiological signal measurement, healthcare monitoring becomes an interesting field in body area networks (BANs). Healthcare monitoring systems use sensor network and communication technologies to detect the health state of a person and transmit the related information to the monitoring center. In BANs, the sensors attached on or embedded in the human body for collecting and transmitting the physiological information are energy limited. Therefore, saving energy is one of the key issues in designing BANs. Because the application of cooperative transmission provides energy saving, it is necessary to form the cooperative transmission using body sensors together. In addition, the modulation constellation size also affects the energy consumption in BANs. Therefore, according to the transmission distance, it is necessary to choose the right transmission scheme by selecting the appropriate modulation to save energy consumption in BANs. In this paper, an adaptive cooperative transmission scheme is proposed for BANs in healthcare systems. In the proposed scheme, the cooperative transmission is constructed over intra-body phase and on-off body phase whereas the adaptive transmission is constructed over the forwarding phase. Results from the simulations show that the proposed adaptive cooperative transmission scheme achieves significant energy savings when compared with the existing schemes.
Authors
- Mohammad Meraj Mirza (ORCID: https://orcid.org/0000-0002-1143-3237)
- Yuyang Peng (ORCID: https://orcid.org/0000-0003-3685-1977)
- Fawaz AL-Hazemi (ORCID: https://orcid.org/0000-0003-3212-8941)
Institutions
- Macau University of Science and Technology (MO)
- Taif University (SA)
- University of Jeddah (SA)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/jsen.2025.3560508
- Citations
- 1
- Primary Topic
- Energy Efficient Wireless Sensor Networks
- Type
- article
- Field-Weighted Citation Impact
- 1.49