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A major challenge in wide deployment of smart wireless devices, using different technologies and sharing the same 2.4 GHz spectrum, is to achieve coexistence across multiple technologies. The IEEE 802.11 (WLAN) and the IEEE 802.15.4e TSCH (WSN) where designed with different goals in mind and both play important roles for respective applications. However, they cause mutual interference and degraded performance while operating in the same space. To improve this situation we propose an approach to enable a cooperative control which type of network is transmitting at given time, frequency and place.We recognize that Time-Slotted Channel Hopping (TSCH) based sensor network is expected to occupy only small share of time, and that the nodes are by design tightly synchronized. We develop mechanism enabling over-the-air synchronization of the Wi-Fi network to the TSCH based sensor network. Finally, we show that Wi-Fi network can avoid transmitting in the "collision periods". We provide full design and show prototype implementation based on the Commercial off-the-shelf (COTS) devices. Our solution does not require changes in any of the standards.Index Terms-Wireless LAN , Wireless sensor networks, Heterogeneous networks, Cooperative communication • A single Wi-Fi basic service set working in the infrastructure mode i.e., consisting of one Access Point (AP) and multiple Stations. Wi-Fi devices under consideration are using COTS hardware with the standard spectrum sensing 978-1-5090-0223-8

Abstract-The paradigm shift towards the Internet-of-Things results in an increasing number of wireless applications being deployed. Since many of these applications contend for the same physical medium (i.e. the unlicensed ISM bands), there is a clear need for beyond-state-of-the-art solutions that coordinate medium access across heterogeneous wireless networks. Such solutions demand fine-grained control of each device and technology, which currently requires a substantial amount of effort given that the control APIs are different on each hardware platform, technology and operating system.In this paper an open architecture is proposed that overcomes this hurdle by providing unified programming interfaces (UPIs) for monitoring and controlling heterogeneous devices and wireless networks. The UPIs enable to create and test advanced coordination solutions while minimizing the complexity and implementation overhead. The availability of such interfaces is also crucial for the realization of emerging software-defined networking approaches for heterogeneous wireless networks. To illustrate the use of UPIs, a showcase is presented that simultaneously changes the medium access control (MAC) behavior of multiple wireless technologies in order to mitigate cross technology interference taking advantage of the enhanced monitoring and control functionality.An open source implementation of the UPIs is available for wireless researchers and developers. It currently supports multiple widely used technologies (IEEE-802.11, IEEE-802.15.4, LTE), operating systems (Linux, Windows, Contiki) and radio platforms (Atheros, Broadcom, CC2520, Xylink Zynq, …), as well as advanced reconfigurable radio systems (IRIS, GNURadio, WMP, TAISC).

Distributed sensing is commonly used to obtain accurate spectral information over a large area. More and more heterogeneous devices are being incorporated in distributed sensing with the aim of obtaining more flexible sensing performance at lower cost. Although the concept of combining the strengths of various sensing devices is promising, the question of how to compare and combine the heterogeneous sensing results in a meaningful way is still open. To this end, this paper proposes a set of methodologies that are derived from several spectrum sensing experiments using heterogeneous sensing solutions. Each of the solutions offers different radio frequency front-end flexibility, sensing speed and accuracy and varies in the way the samples are processed and stored. The proposed methodologies cover four fundamental aspects in heterogeneous sensing: (i) storing experiment descriptions and heterogeneous results in a common data format; (ii) coping with different measurement resolutions (in time or frequency domain); (iii) calibrating devices under strictly controlled conditions and (iv) processing techniques to efficiently analyse the obtained results. We believe that this paper provides an important first step towards a standardized and systematic approach of heterogeneous sensing solutions.