Abstract
Hardware-based link quality estimators (LQEs) in wireless sensor networks generally use physical layer parameters to estimate packet reception ratio, which has advantages of high agility and low overhead. However, many existing studies didn’t consider the impacts of environmental changes on the applicability of these estimators. This paper compares the performance of typical hardware-based LQEs in different environments. Meanwhile, aiming at the problematic Signal-to-Noise Ratio (SNR) calculation used in existing studies, a more reasonable calculation method is proposed. The results show that it is not accurate to estimate the packet reception rate using the communication distance, and it may be useless when the environment changes. Meanwhile, the fluctuation range of the Received Signal Strength Indicator (RSSI) and SNR will be affected and that of Link Quality Indicator (LQI) is almost unchanged. The performance of RSSI based LQEs may degrade when the environment changes. Fortunately, this degradation is mainly caused by the change of background noise, which could be compensated conveniently. The best environmental adaptability is gained by LQI and SNR based LQEs, as they are almost unaffected when the environment changes. Moreover, LQI based LQEs are more accurate than SNR based ones in the transitional region. Nevertheless, compared with SNR, the fluctuation range of LQI is much larger, which needs a larger smoothing window to converge. In addition, the calculation of LQI is typically vendor-specific. Therefore, the tradeoff between accuracy, agility, and convenience should be considered in practice.
Highlights
In the past few decades, wireless sensors networks (WSNs) have drawn much attention from academia and industry
The results show that the fluctuation range of Received Signal Strength Indicator (RSSI) and Signal-to-Noise Ratio (SNR) is more sensitive to environmental changes, while that of Link Quality Indicator (LQI) is almost unaffected when the environment changes
Hardware-based link quality estimators (LQEs) are usually employed which depend on mapping models between packet reception rate (PRR) and some indirect metrics such as the SNR, RSSI, and LQI
Summary
In the past few decades, wireless sensors networks (WSNs) have drawn much attention from academia and industry. Link quality could be estimated indirectly by constructing mapping models between these metrics and PRR, which improves the estimating agility greatly. Such approaches are often called hardware-based Link. The experimental environment in which the mapping model was obtained in most existing studies is relatively single, and the possible impacts of environmental changes are ignored. (4) Impacts of environmental changes on typical hardware-based LQEs are analyzed. Conclusions are presented and suggestions are made for future works
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