The prosperity of IEEE 802.11-based Wi-Fi networks aggravates cross-technology interference to IEEE 802.15.4-enabled ZigBee networks widely deployed to enable various Internet-of-Things applications. To make ZigBee communication reliable and robust even in a dense Wi-Fi environment, taming Wi-Fi interference in ZigBee networks especially from the perspective of physical layer is of paramount importance. In this context, this work takes aim to design a novel Wi-Fi interference-resilient ZigBee decoder called PolarScout, which separates collided ZigBee signal samples out of Wi-Fi interference to bootstrap ZigBee data decoding. Unlike several existing solutions which need clear signal preamble, tremendous signal strength difference between ZigBee and Wi-Fi, and Wi-Fi interference recognition in prior to ZigBee decoding, PolarScout aims at direct ZigBee decoding in a more generic and challenging case where Wi-Fi interference features a wide range of power levels and arises within a ZigBee packet at an arbitrary position. At the heart of PolarScout lies a subtle shell-shaping technique which harnesses a customized sample sequence to smooth the shell of corrupted signal samples. PolarScout then refers to the resulting shell to recover each contaminated ZigBee sample. Experimental results validate the superiority of PolarScout and its resilience to a wide range of Wi-Fi interference types.

This paper proposes a heterogeneous carrier-sense multiple access (CSMA) protocol named LoHEC as the first research attempt to improve energy fairness when applying CSMA to long-range wide area network (LoRaWAN). LoHEC is enabled by Channel Activity Detection (CAD), a recently introduced carrier-sensing technique to detect LoRaWAN signals even below the noise floor. The design of LoHEC is inspired by the fact that existing CAD-based CSMA proposals are in a homogeneous manner. In other words, they require LoRaWAN end devices to perform identical CAD regardless of the differences of their used network parameter – spreading factor (SF). This causes energy consumption imbalance among end devices since the consumed energy during CAD is significantly affected by SF. By considering the heterogeneity of LoRaWAN in terms of SF, LoHEC requires end devices to perform different numbers of CAD operations with different CAD intervals during channel access. Particularly, the number of needed CADs and CAD interval are determined based on the CAD energy consumption under different SFs. We conduct extensive experiments regarding LoHEC with a practical LoRaWAN testbed including 60 commercial off-the-shelf end devices. Experimental results show that in comparison with the existing solutions, LoHEC can achieve up to 0.85 $\times$ improvement of the energy fairness on average.

This letter presents ZIP (zero-effort ZIgBee Proximity detection), a novel technique to detect the proximity of two Internet-of-Things devices. Based on the ZigBee technology, ZIP embodies the first zero-effort solution by differing from existing ones that resort to the use of tailor-made hardware, multiple antenna installments, the employment of a third-party device, or user involvement. At the heart of ZIP is the construction of a feature-designated decision tree built on received signal strength. An ensemble prediction method is further designed to aggregate the outputs of multiple decision trees for detection accuracy improvement. Practical experiments are conducted to show the reliability and robustness of ZIP.

Enabling energy-efficient and long-distance wireless networking is expected by various Internet-of-Things systems and consumer electronics applications. Low-power wide area networks can commendably satisfy this requirement because of their combination of low-power and long-range features. Thereinto, open-standard Long-Range Wide Area Network (LoRaWAN) is the representative player with hundreds of deployment cases worldwide. Unfortunately, the current multiple access (MA) strategy for LoRaWAN has been proved to incur severe wireless signal interference under large-scale deployment. This is the inherent hindrance for the current LoRaWAN to support large-scale wireless networking. In this context, this article aims to provide a detailed tutorial of MA issues in large-scale LoRaWAN for the first time. We start with several practical use cases of large-scale LoRaWAN. We then explain the detailed challenges of large-scale LoRaWAN networking. Representative MA solutions for better LoRaWAN networking are then described and compared. Future research directions for enhanced MA protocol design are also discussed.

The last decade has witnessed the ever-increasing deployment of Wi-Fi networks and the explosion of Bluetooth-based applications. As a result, the coexistence of Bluetooth piconets with highly-dense Wi-Fi networks is a common phenomenon currently. Unlike Wi-Fi that conducts carrier sensing before channel access, Bluetooth adopts frequency hopping based on a predefined hop sequence, which inevitably incurs considerable cross-technology interference to Wi-Fi. While the Adaptive Frequency Hopping technique is standardized for interference reduction, it does not perform well in current practice where densely-deployed Wi-Fi networks commonly cover the whole 2.4 GHz unlicensed spectrum. In this context, this paper presents BuSAR, a novel approach to account for the coexistence problem between Bluetooth piconets and dense Wi-Fi networks. BuSAR embodies the first work to aim at mitigating the cross-technology interference between Bluetooth highly-dense Wi-Fi networks in a distributed manner. At the heart of BuSAR lies a subtle technique called Bluetooth slot availability randomization, which exploits the redundancy of erroneous Bluetooth packets for better Bluetooth/Wi-Fi coexistence. With BuSAR adopted, multiple Bluetooth piconets are guaranteed to operate independently and only a lightweight algorithm is needed to be implemented at each Bluetooth device. Both theoretical analysis and experimental results validate the feasibility and superiority of BuSAR.