Claro Noda

Quantifying the channel quality for interference-aware wireless sensor networks

Reliability of communications is key to expand application domains for sensor networks. Since Wireless Sensor Networks (WSN) operate in the license-free Industrial Scientific and Medical (ISM) bands and hence share the spectrum with other wireless technologies, addressing interference is an important challenge. In order to minimize its effect, nodes can dynamically adapt radio resources provided information about current spectrum usage is available. We present a new channel quality metric, based on availability of the channel over time, which meaningfully quantifies spectrum usage. We discuss the optimum scanning time for capturing the channel condition while maintaining energy-efficiency. Using data collected from a number of Wi-Fi networks operating in a library building, we show that our metric has strong correlation with the Packet Reception Rate (PRR). This suggests that quantifying interference in the channel can help in adapting resources for better reliability. We present a discussion of the usage of our metric for various resource allocation and adaptation strategies.

On packet size and error correction optimisations in low-power wireless networks

In wireless networks that operate in those bands where spectrum sharing occurs across a variety of wireless technologies, such as the license-free Industrial Scientific and Medical (ISM) bands, mitigating interference becomes challenging. Addressing interference is an important aspect for the design and development of solutions intended to satisfy the demands of applications requiring QoS guarantees. In this paper, we investigate dynamic radio resource adaptation techniques based on instantaneous spectrum usage. Using a novel metric to quantify the spectrum usage, we address packet size and error correction code overhead optimizations. On one hand, large payloads lead to energy and throughput gains due to the amortization of the transmission overheads, but on the other hand, larger payloads imply larger resource wastage in the event of packet collisions. Using real-world data, we found that payload size in the neighbourhood of 100 bytes leads to near-optimal performance in general in the IEEE 802.15.4 networks. Our data also shows that for very high interference scenarios, erasure codes capable of correcting 10% of the packet payload can provide an equivalent Signal to Interference plus Noise Ratio (SINR) gain of 25 dB with probability greater than 0.6. This is significant for interference management and for increasing spatial re-use by employing lower transmission power. We show that erasure codes drastically improve energy-efficiency and throughput of low-power wireless links. In the heavy interference regime, even though interference doubles the energy-per-usable-bit cost, erasure codes remain cost-effective for very large payload sizes, up-to 1500 bytes. Finally, we discuss interference-dependent dynamic adjustment of the correction capacity of erasure codes.

External Radio Interference

An important factor contributing to the degradation and variability of the link quality is radio interference. The increasingly crowded radio spectrum has triggered a vast array of research activities on interference mitigation techniques and on enhancing coexistence among electronic devices sharing the same or overlapping frequencies. This chapter gives an overview of the interference problem in low-power wireless sensor networks and provides a comprehensive survey on related literature, which covers experimentation, measurement, modelling, and mitigation of external radio interference. The aim is not to be exhaustive, but rather to accurately group and summarize existing solutions and their limitations, as well as to analyse the yet open challenges.

Radio Link Quality Estimation in Low-Power Wireless Networks

This book provides a comprehensive survey on related work for radio link quality estimation, which covers the characteristics of low-power links, the fundamental concepts of link quality estimation in wireless sensor networks, a taxonomy of existing link quality estimators and their performance analysis. It then shows how link quality estimation can be used for designing protocols and mechanisms such as routing and hand-off. The final part is dedicated to radio interference estimation, generation and mitigation.

On the Scalability of Constructive Interference in Low-Power Wireless Networks

Constructive baseband interference has been recently introduced in low-power wireless networks as a promising technique enabling low-latency network flooding and sub-μs time synchronisation among network nodes. The scalability of this technique has been questioned in regards to the maximum temporal misalignment among baseband signals, due to the variety of path delays in the network. By contrast, we find that the scalability is compromised, in the first place, by emerging fast fading in the composite channel, which originates in the carrier frequency disparity of the participating repeaters nodes. We investigate the multisource wave problem and show the resulting signal becomes vulnerable in the presence of noise, leading to significant deterioration of the link whenever the carriers have similar amplitudes.

Demo Abstract: Battery-Free 802.15.4 Receiver

We present the architecture for an 802.15.4 receiver that enables battery-free operation. To reach micro-power consumption, the architecture diverges from that of commodity receivers in the following ways: First, similar to backscatter transmitters, it offloads the power-hungry local oscillator to an external device. Second, we avoid the energy cost of demodulating a phase-modulated signal by treating 802.15.4 as a frequency-modulated one, allowing us to receive with a simple passive detector and an energy-efficient thresholding circuit. We demonstrate an off-the-shelf prototype of our receiver receives 802.15.4 from a distance of 470 cm with the carrier generator 30 cm away. This range is sufficient to integrate with deployed wireless sensor networks (WSNs). We demonstrate this integration by pairing our receiver with a 802.15.4 backscatter transmitter and integrating it with unmodified commodity sensor nodes running the TSCH protocol.

Characteristics of Low-Power Links

This chapter aims at providing a summary of key properties of low-power links. First, it gives an overview of the radio technology most commonly used in low-power wireless networks. Then, it distils from the vast array of empirical studies on low-power links a set of high-level observations, which are classified into spatial and temporal characteristics, link asymmetry, and interference. Such observations are helpful not only to design efficient Link Quality Estimators (LQEs) that take into account the most important aspects affecting link quality, but also to design efficient network protocols that have to handle link unreliability.

Performance Evaluation of Link Quality Estimators

The objective of this chapter is twofold: First, we present a methodology to evaluate the performance of LQEs regardless their type (e.g., PRR-based versus RNP or score-based, hardware-based vs. software-based). We follow this methodology to evaluate the performance of six representative and well-known LQEs in the literature. The results presented in this chapter should help network protocol designers fully understand the strengths and weaknesses of these LQEs, thus enabling them to make an informed choice.

On the Use of Link Quality Estimation for Improving Higher Layer Protocols and Mechanisms

Several network protocols and mechanisms rely on efficient link quality estimation to mitigate the unreliability of low-power links. A LQE can be efficient on a per-link basis, but it may lead to a poor performance when integrated in a particular protocol or mechanism. The objective of this chapter is to show how to use link quality estimation for improving higher layer protocols and mechanisms—especially routing and mobility management.

Overview of Link Quality Estimation

Low-power links exhibit a complex and dynamic behavior, e.g., frequent quality fluctuations, highly asymmetric connectivity, large transitional region. They are more unreliable than traditional wireless links. This is due to the use of low-power and low-cost radio transceivers. These facts raised the need for link quality estimation as a fundamental building block for higher-layer protocols. This chapter presents the fundamental concepts related to link quality estimation in low-power wireless networks, such as the definition of the link quality estimation process, and the requirements for efficient Link Quality Estimators (LQEs). This chapter gives also and a comprehensive survey of existing LQEs.