A Survey on LPWAN Technologies in WBAN for Remote Health-Care Monitoring
Abstract
:1. Introduction
- An overview of WBAN systems in HCM, peculiarities, and QoS parameters were thoroughly reviewed.
- The newly emerged LPWAN communication systems were extensively investigated for WBANs in HCM.
- The comparison of the LPWAN communication systems were considered in the context of energy efficiency, security, health data reliability, data rate, latency, cost-effectiveness, and communication coverage, in order to exploit their potentials to support the growth of the next-generation WBAN systems.
- Identification of the power-saving modes and the modulation mechanisms utilized by the LPWAN communication systems to determine their suitability in terms of energy efficiency.
- Discussions and recommendations on the impacts of electromagnetic radiation on the human body.
- Directions for future research to bridge the gaps in knowledge and recommendations are provided.
2. Related Work
3. Overview and Concept of WBAN Solutions in HCM
3.1. Wireless Body Area Networks
3.2. Peculiarities of WBANs
4. LPWAN Communication Systems in WBANs
4.1. Proprietary-Based LPWAN Communication Systems
4.1.1. RPMA/Ingenu Network
4.1.2. Sigfox Network
4.1.3. LoRa Network
4.2. Non-Proprietary-Based LPWAN Communication Systems
4.2.1. LTE CAT Technology
4.2.2. EC-GSM Technology
4.2.3. NB-IoT Technology
4.3. Summary of LPWAN Technologies
5. WBAN QoS Requirements
5.1. Energy Efficiency
- Medical personnel are often situated far away from their patients, especially patients that are suffering from chronic diseases, so the only cost-effective way that could be employed to monitor such patients is by deploying efficient HCM sensing and communication technologies to gather and transfer medical data about such patients. The sensor devices involved in the technologies cannot afford to spend more energy on data gathering and data transmission since they mostly operate on batteries.
- Energy efficiency is a fundamental issue in any communication network. Once the energy of a network is exhausted or drained, the network becomes inactive. Therefore, it is very necessary for a WBAN system to be energy efficient in order to achieve a sustainable network operation.
- Due to the disparity in the WBAN applications, some applications require low data rate, while some require high data rate. The disparity in data rate requirements among WBAN applications will encourage a higher amount of power to be consumed by the applications with high data rate requirements. This is technically due to the trade-off in data rate and power consumption. Therefore, to strike a balance between power consumption and high data rate, there is a need for energy-efficient schemes to optimize data transmission, in order to reduce energy spent on data transfer.
5.2. Health Data Security Requirement
5.3. Health Data Transmission and Reliability
5.4. Health Data Latency
5.5. Throughput Requirement
5.6. Coexistence Issues in Communication Bands
5.7. Low Electromagnetic Radiation
5.8. Mobility Support
5.9. Interference Issues
6. Research Gaps and Recommendations for Next-Generation WBANs in HCM
6.1. Development of Efficient Transmission Strategies for Improving LPWAN-Enabled WBAN Communication Systems
6.2. Improving the Efficiency of the Medical Nanosensor Devices in WBAN Systems
- How the nanosensors can effectively communicate their data because of the tiny nature of the allowable radio, i.e., how the communication channel of the medical nanosensors can be efficiently modelled. For communication purposes, two major communication alternatives are envisaged, the nano-electromagnetic communication and the molecular communication. The molecular communication has been proposed in recent times as a newly emerging communication paradigm that employs biochemical signals to transmit information from a nanodevice to another within a short distance [78]. More research on the channel modelling and the development of networking protocols could be investigated and exploited for the nanosensors in WBAN systems. The electromagnetic nanosensors employ electromagnetic radiation to transmit information. It can support two frequency bands for their operation, such as the megahertz band upper part and the terahertz band (0.1–10 THz). The megahertz frequency could be enabled by employing an electromechanical nano-transceiver, while the terahertz band could be achieved through novel nano-antennas. For instance, a research work was done [79] for intra-body nanoscale communication, in which the authors developed a robust terahertz channel model for in-body communication, taking into consideration the impact of the propagation of the electromagnetic waves and the molecular absorption generated from the patients’ tissue. More research to insightfully investigate the accuracy of this research can be done and also developing new channel models for the terahertz band for the WBAN communication systems. In addition, more research investigations into developing novel health information encoding and modulation methods that can encourage the exploitation of the wide bandwidth offered by the terahertz channel are worth exploring. Additionally, novel communication protocols for the electromagnetic wireless nanosensor networks could be explored for further research.
- How to efficiently utilize the ultra-limited power resources also calls for a serious concern for a fruitful WBAN system deployment. To address this issue in the nanosensor-based WBAN systems, since such systems cannot afford to spend much power to transmit their health data due to their ultra-limited power constraint, new policies for optimal power control can be pursued by using energy-efficient techniques, like network coding, optimal control methods, queuing theory, and game theoretic methods.
- The placement of the medical nanosensor devices among multiple alternatives is also an interesting problem that needs to be deeply investigated, as this would enhance the power efficiency of the WBAN systems since power constraint is a complex issue in WBAN systems that are coupled with medical nanosensor devices. As an insight into addressing such problem, the consideration of new optimization algorithms for the optimal placement of the devices is envisaged as a promising solution.
6.3. Development of Energy-Aware MAC Protocols for WBAN Communication
6.4. Employing Software Defined Nework (SDN) Technology to Improve WBAN Energy Efficiency
6.5. Addressing Energy-Efficiency Issue in LPWAN-Enabled WBANs through Congestion Control Using Queuing Theory
6.6. Consideration of Interference Management Solutions in LPWAN-enabled WBAN Systems
6.7. Improving WBAN Mobility Support
6.7.1. Mobility Predictions and Management
6.7.2. Mobility Models
6.8. Development of Energy-Efficient Resource-Allocation Schemes to Enhance the LPWAN-enabled WBAN Sensor’s Lifetime
7. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Reference | Focus on Short-Range Technologies | Concept of LPWAN Solution in HCM | Concept of LPWAN Solution in WBANs | LPWAN Implementation Design WBANs |
---|---|---|---|---|
[5] | ✓ | X | X | X |
[6] | ✓ | X | X | X |
[8] | ✓ | X | X | X |
[10] | ✓ | X | X | X |
[13] | ✓ | X | X | X |
[14] | ✓ | X | X | X |
[15] | ✓ | X | X | X |
[16] | X | ✓ | ✓ | X |
[17] | X | ✓ | ✓ | X |
[18] | ✓ | X | X | X |
[19] | ✓ | X | X | X |
Communication Solution Parameters | Proprietary-Based LPWAN Communication Systems | Non-Proprietary Based LPWAN Communication Systems | ||||
---|---|---|---|---|---|---|
RPMA/Ingenu | Sigfox | LoRa | LTE-M1 | EC-GSM | NB-IoT | |
Transmission power | __ | 14 dBm [54] | 15 dBm [54] | 20 dBm [33] | 33 dBm [33] | 20 dBm or 23 dBm [54] |
Battery lifespan | 10 years | 5 years [49] | 10 years [49] | 10 years [49] | 10 years [49] | More than 10 years [45,56] |
Data rate | 20 kbps [57] | 100 bps [48] | 50 kbps [57] | 1 Mbps [48] | 10 kbps | Downlink: 160–250 kbps Uplink: 160–200 kbps [45] |
Latency of health data | 10 s [58] | 10 s [58] | 10 s [58] | 150 ms [58] | __ | <10 s [58] |
Communication range/Link budget | Rural: 10 km Urban: 3 km/168 dB | Rural: 50 km Urban: 10 km/160 dB | Rural: 15 km Urban: 5 km/157 dB [49] | Rural: 15 km Urban: -/155.7 dB | Rural: 15 km Urban:-/164 dB (33 dBm) and 154 dB(23 dBm) | Rural: 35 km Urban: 8 km/164 dB [48] |
Topology/Network | Star, tree/WAN | Star/WAN | Star/WAN | Star/WAN | Star/WAN | Star/WAN |
Deployment cost | High | High | High | Low | Low | Low |
Carrier frequency | 2.4 GHz ISM free-licensed band | Free-licensed Sub-GHz ISM band | Free-licensed Sub-GHz ISM band | Licensed Sub-GHz | Licensed Sub-GHz | Licensed Sub-GHz |
Network capacity per cell | More than 50,000 sensor devices | 50,000 sensor devices | 40,000 sensor devices | 20,000 sensor devices | 50,000 sensor devices | More than 50,000 sensor devices |
Security mechanism | AES 256-bit, 16 B hash [16] | 140 message limit per day, scrambling techniques and encryption, signing message with private key | AES encryption | Authentication method using MME [35] | Supports 3GP Psecurity mechanism [57] | Supports the 3GPP S3 mechanisms, such as device identification, identity confidentiality, health data integrity, and authentication |
Modulation scheme | CDMA, RPMA-DSSS | DBPSK or GFSK or UNB | CSS | Downlink: FDMA Uplink: C-FDMA | Downlink and Uplink TDMA or FDMA, GMSK and 8PSK | Downlink: OFDMA Uplink: SC-FDMA |
Mobility support | Limited support [56] | No support [56] | Support [56] | Support [56] | Support [56] | No support [56] |
Advantage | Support long communication range, energy efficiency, and low operational cost | Support long communication range, energy efficiency, and low operational cost | Support long communication range, energy efficiency, and low operational cost | Support remote health-care monitoring, energy efficient, provide fast and reliable network | Support remote health-care monitoring, energy efficient, | Support remote health-care monitoring, energy efficient provide fast and reliable network |
Disadvantage | Interference issue, high deployment cost, and low health data reliability | Interference issue, high deployment cost, and low health data reliability | Interference issue, high deployment cost, and limited network size | Limited network capacity | Extremely low data rate | High maintenance and operational cost since it is on the licensed spectrum, also cost of SIM card purchase. |
WBANs suitability | Low | Low | Moderate | High | Low | High |
Application Type | Sensor Devices | Data Rate | Frequency (Hz) | Accuracy (bits) | Energy Consumption | Latency (ms) | Reference |
---|---|---|---|---|---|---|---|
Implantable medical application | Peacemaker | <1 kbps | <500 Hz | 12 | Low | <150 | [70,71,72] |
Endoscope capsule | >2 Mbps | __ | __ | High | <150 | ||
Glucose level sensor | <1 kbps | < 50 Hz | 16 | Very low | <150 | ||
Drug delivery capsule | <320 kbps | __ | __ | Low | <150 | ||
Brain depth simulator | <16 kbps | 130 Hz | __ | __ | <150 | ||
Cochlear implant | <1Mbps | 5, 12, 49 MHz | __ | __ | <150 | ||
Wearable medical application | Blood pressure | <10 kbps | <100 Hz | 12 | High | <150 | [73,74] |
ECG | 3 kbps | <500 Hz | 12 | High | <150 | ||
Blood flow rate | 480 kbps | <40 Hz | 12 | Low | <150 | ||
Temperature | 120 bps | <1Hz | 12 | Low | <150 | ||
Nonmedical application | Audio streaming | 1 Mbps | __ | __ | High | <250 | [75] |
Video streaming | <10 Mbps | __ | __ | High | <250 | ||
Voice | 100 kbps | __ | __ | __ | <250 | ||
Motion sensor | 4.8–35 kbps | 30–100 Hz (depending on the activity recognition or other tasks) | 12–16 | __ | <250 |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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Olatinwo, D.D.; Abu-Mahfouz, A.; Hancke, G. A Survey on LPWAN Technologies in WBAN for Remote Health-Care Monitoring. Sensors 2019, 19, 5268. https://doi.org/10.3390/s19235268
Olatinwo DD, Abu-Mahfouz A, Hancke G. A Survey on LPWAN Technologies in WBAN for Remote Health-Care Monitoring. Sensors. 2019; 19(23):5268. https://doi.org/10.3390/s19235268
Chicago/Turabian StyleOlatinwo, Damilola D., Adnan Abu-Mahfouz, and Gerhard Hancke. 2019. "A Survey on LPWAN Technologies in WBAN for Remote Health-Care Monitoring" Sensors 19, no. 23: 5268. https://doi.org/10.3390/s19235268
APA StyleOlatinwo, D. D., Abu-Mahfouz, A., & Hancke, G. (2019). A Survey on LPWAN Technologies in WBAN for Remote Health-Care Monitoring. Sensors, 19(23), 5268. https://doi.org/10.3390/s19235268