More and more wireless networks are deployed with overlapping coverage. Especially in the unlicensed bands, we see an increasing density of heterogeneous solutions, with very diverse technologies and application requirements. As a consequence, interference from heterogeneous sources-also called cross-technology interference-is a major problem causing an increase of packet error rate (PER) and decrease of quality of service (QoS), possibly leading to application failure. This issue is apparent, for example, when an IEEE 802.15.4 wireless sensor network coexists with an IEEE 802.11 wireless LAN, which is the focus of this work. One way to alleviate cross-technology interference is to avoid it in the frequency domain by selecting different channels. Different multichannel protocols suitable for frequency-domain interference avoidance have already been proposed in the literature. However, most of these protocols have only been investigated from the perspective of intratechnology interference. Within this work, we create an objective comparison of different candidate channel selection mechanisms based on a new multichannel protocol taxonomy using measurements in a real-life testbed. We assess different metrics for the most suitable mechanism using the same set of measurements as in the comparison study. Finally, we verify the operation of the best channel selection metric in a proof-of-concept implementation running on the testbed.

Due to the advances in wireless technology and spectrum scarcity, unlicensed band heterogeneous networks are growing rapidly. Increasing users of these networks should compete for the shared spectrum. Therefore, interoperability and coexistence of such networks are becoming key issues that require novel media access protocols equipped with dynamic channel selection to avoid harmful interference. In this paper we focus on dynamic channel selection for coexistence of IEEE 802.11 Wireless LAN and IEEE 802.15.4 sensor networks. Dynamic channel selection algorithm can either be implemented on top of an existing wireless sensor network or assisted with an auxiliary spectrum sensing device. In this research couple of dynamic channel selection algorithms have been developed and implemented to evaluate the added value of the auxiliary sensing device. As such, we propose a novel energy-aware metric to detect and quantify the harmfulness of dynamic interference. We also investigated the impact of interference dynamism on algorithms performance and validated the efficiency of the implemented mechanisms by three sets of experiments. Experiments results primarily validate the efficiency of both interference mitigation techniques. Besides, these measurements suggest that the auxiliary sensing device is most beneficial for highly complex interference profiles.