# Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate
## 5 Conclusions  
Based on the Sub-1 GHz, this paper proposed a fuzzy-based adaptive data rate and transmission power control algorithm, then demonstrated that the sensor node has the characteristic of extremely low power consumption. As for the topology, it retained the capability of network topology and low power consumption of star topology. The actual field test was affected by several external factors. The proposed control algorithm adaptively controlled the data rate and transmission power to overcome the effect from external environment and noise interference. The long-term experimental results demonstrated that the PER of the sensor node from the experimental group is mostly controlled at approximately 1% to maintain a balance between communication quality and power consumption. To retain the features of low power consumption and communication quality, the algorithm tried to reduce the transmission power to obtain lower power consumption when the communication reached a level of stability. The proposed algorithm effectively avoided the high PER from the sudden appearance of communication errors and maintained a level of communication quality. The experimental results of power consumption indicated that the battery life of each experimental group node is more than 6.8 years (improvement by 73% compared with previous results). However, the battery life will only be about 2 years in order to keep the PER below 1% with the most power consumed combination. The control algorithm proposed in this paper has the characteristics of maintaining stable communication and power saving, although the battery life of 6G WSN is expected to be 20 years, which is slightly larger than the result of this paper. Nevertheless, the experimental data are obtained from the long-time testing setting in the realistic field. Its feasibility and effect are verified. To summarize, the proposed method with above advantages can provide a better solution for WSN based on current techniques. For future work, the technique of Adaptive Modulation and Coding (AMC) and Channel Estimation (CE) can be implemented in this system to achieve a better communication quality with lower power consumption.  
[PERSON], [PERSON] and [PERSON] initiated and developed ideas for this research, developed the presented novel methods, derived relevant formulations, and performed performance analyses of simulation and experimental results. [PERSON], [PERSON] and [PERSON] wrote the paper draft under the guidance of [PERSON], who finalized the paper. All authors have read and agreed to the published version of the manuscript.  
This study was partly supported by the Ministry of Science and Technology, Taiwan, under Contract MOST-110-2634-F-009-024, 110-2221-E-A49-121-MY2, 110-2221-E-224-026, 110-2622-E-224-012, 110-2622-E-224-012, 110-2634-F-007-027, and IRIS \"Intelligent Recognition Industry Service Research Center\" from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Node Number** & **Battery Life** \\ \hline
1 & 7.03 years \\
3 & 6.82 years \\
5 & 7.04 years \\
7 & 7.26 years \\
9 & 7.12 years \\ Parameters which consume the most power & 2.04 years \\ \hline \hline \end{tabular}
\end{table}
Table 9: Battery life of sensor nodes.