The current understanding of activity in the wireless spectrum is limited to mostly punctual studies of aggregated energy values. However, there is a need and increasing technological means for a better understanding of spectrum usage by automatically detecting and recognizing wireless transmissions in an unlicensed or shared frequency band. In this paper we propose, implement and evaluate a framework for automatic detection of wireless transmissions. Our framework includes a manual component as our assessment suggests manual labor has a paramount impact on tuning and maintaining good performance of an automatic transmission detection system. However, a considerable problem in this aspect is represented by the disagreement amongst human annotations which is a universally recognized issue. To this end, we discuss and evaluate challenges in generating labeled datasets that can then be used as ground truth for evaluating and possibly training automatic transmission detection systems. We also propose two methods for automatic transmission detection that are not based on machine learning and therefore do not need training data and evaluate their performance against each other and manually labeled data. Our results show that generating human-labeled ground truth data is an expensive and imperfect process. Humans on average require 90 minutes to label 56 minutes of unlicensed European narrowband spectrum. The experts that generate the ground truth sometimes only agree on as little as 40.18% of the labeled cases.

Uplink transmissions, within coexisting distinct sub-GHz technologies operating in the same unlicensed band, can be exposed to detrimental impact of the interference. In such scenarios, transmission scheduling becomes important for mitigating interference or minimizing the impact of the interference. For this purpose, we aim to whitelist relatively better channels in terms of their yielded packet reception ratio using our proposed channel quality metric that is based on the received signal-to-interference-plus-noise ratio. In this paper, we investigate the trade-offs of the channel whitelisting in random frequency division multiple access (RFDMA) networks in the presence of the cumulative intra- and inter-technology interferences. Our main findings indicate that, although channel whitelisting reduces the degree of freedom, and thus the overall capacity, it empowers a certain amount of devices to be served at a much lower received signal power, whereas this is infeasible for non-whitelisting scenarios at larger received signal power, which signifies the energy conservation ability of our proposed whitelisting method. It is experimentally demonstrated, on Sigfox, a particular type of RFDMA network, that non-whitelisting scenarios are not capable of supporting any devices at a received signal power below -118 dBm. Even for lower received signal power, we are able to reduce the required number of retransmissions at the same reception probability, which indeed indicates that the overall reliability of the network is improved.

In this paper, we propose an adaptive channel quality metric that is suitable for uplink channel estimation in ultra-narrowband networks. The proposed metric relies on channel measurements rather than on packet information, therefore it doesn't need a large number of packets to initialize, and is simple enough that can be computed per channel for a large number of channels. Our results show that the proposed metric should be able to identify channels with the least amount of interference for a wide range of expected received packet powers.

Lack of unallocated spectrum and increasing demand for bandwidth in wireless networks is forcing new devices and technologies to share frequency bands. Spectrum sensing is a key enabler for frequency sharing and there is a large body of existing work on signal detection methods. However a unified methodology that would be suitable for objective comparison of detection methods based on experimental evaluations is missing. In this paper we propose such a methodology comprised of seven steps that can be applied to evaluate methods in simulation or practical experiments. Using the proposed methodology, we perform the most comprehensive experimental evaluation of signal detection methods to date: we compare energy detection, covariance-based and eigenvalue-based detection and cyclostationary detection. We measure minimal detectable signal power, sensitivity to noise power changes and computational complexity using an experimental setup that covers typical capabilities from low-cost embedded to high-end software defined radio devices. Presented results validate our premise that a unified methodology is valuable in obtaining reliable and reproducible comparisons of signal detection methods.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. COST Action CA15104 Experimental Facilities Report Slawomir Ambroziak, K Bregar, K Cwalina, M Deruyck, Céline Fortuna, G Gardašević, U Gregorc, A Hrovat, T. Javornik, F. Kaltenberger, et al.

Several alternatives for more efficient spectrum management have been proposed over the last decade, resulting in new techniques for automatic wideband spectrum sensing. However, while spectrum sensing technology is important, understanding, using and taking actions on this data for better spectrum and network resource management is at least equally important. In this paper, we propose a system that is able to automatically detect wireless spectrum events from streaming spectrum sensing data, and enables the consumption of the events as they are produced, as a statistical report or on a per-query basis. The proposed system is referred to as spectrum streamer and is wireless technology agnostic, scalable, able to deliver actionable information to humans and machines and also enables application development by custom querying of the detected events.

The adoption of social coding platforms among software developers is particularly high because it increases collaboration and productivity as well as code re-use. On the other hand research testbeds do not generally have such high adoption rate. The learning curve of adopting new technology represents an initial drop in performance before it increases. However this effect is unexpected by many users and there is a risk that they will abandon new technology before their performance increases. The main contribution of this paper is to introduce methodology to take advantage of the high adoption rate of social coding platforms to improve the adoption of research testbeds. The proposed approach is that a social coding platform serves as a common gateway to various testbeds since it is something many developers are comfortable with and thus the initial effort needed to start using the testbed is decreased and the probability that experimenters continue to use a testbed is higher.

Network testing plays an important role in the iterative process of developing new communication protocols and algorithms. However, test environments have to keep up with the evolution of technology and require continuous update and redesign. In this article, we propose COINS, a framework that can be used by wireless technology developers to enable CI practices in their testbed infrastructure. As a proof-of-concept, we provide a reference architecture and implementation of COINS for controlled testing of multi-technology 5G MTC networks. The implementation upgrades an existing wireless experimentation testbed with new software and hardware functionalities. It blends web service technology and operating system virtualization technologies with emerging Internet of Things technologies enabling CI for wireless networks. Moreover, we also extend an existing qualitative methodology for comparing similar frameworks and identify and discuss open challenges for wider use of CI practices in wireless technology development.

Machine-type communications (MTC) in 5G will be mostly realized using low-cost transceivers with a small, discrete set of possible configurations. This is in contrast to more capable devices with software defined radio capabilities that support configurations over a practically continuous domain. We find that existing theoretical work assuming continuous domains cannot be immediately applied to such constrained MTC devices. Therefore, we propose a methodology that guides researchers in the process of developing effective MTC wireless systems with devices that have restricted capabilities. By following the proposed methodology, existing theories can be experimentally evaluated and replicated. We show how this methodology can be applied for developing and evaluating efficient interference mitigation systems on a case study using devices that support only discrete transmit power levels. In this case study, we formulate an interference mitigation problem and a corresponding game-theoretic formalism that can support discrete output power levels. We validated some of the existing results obtained analytically and in simulation and we also found that: 1) in practice, devices have to be penalized stronger than in theory to determine them to select all the available transmit power levels; 2) in practice, for the discrete case of the power allocation algorithm, the convergence speed does not increase exponentially with the number of devices; and 3) the proposed power selection algorithm converges in two to four iterations. Similarly, as in the presented case study, the methodology can be used to adapt and test other resource management solutions in an operating environment with real-world restrictions.

Low-Power Wide Area Networks (LP-WANs) are emerging as a promising solution for connecting Internet of Things and Machine Type Communication devices. If ultra-narrowband (UNB) networks, a subclass of LP-WANs, reach predicted deployment numbers and densities, they will face two challenges: inter-technology and intra-technology interference. This paper proposes the first experimental architecture designed for the optimization of UNB networks. We illustrate its implementation on a case study of a SIGFOX network and the resulting extension of the existing LOG-a-TEC testbed. The proposed architecture enables context data collection, context model development, optimization and transmission control using rapid experimentation cycle approach enabled by flow based programming using Node-RED. Through preliminary results, we show the feasibility of PHY and MAC context data collection, point out challenges that are specific for UNB context modeling and discuss options for optimization. All datasets, context modeling and optimization tools used in the paper will be released as open source.

Having a huge potential to improve the way radio spectrum is being used, the techniques that are used for the research in cognitive radio are maturing and therefore move from being evaluated in a simulation environment to more realistic environments such as dedicated testbeds. In this chapter we describe our experiences with the design, deployment and experimental use of the LOG-a-TEC embedded, outdoor cognitive radio testbed, based on the VESNA sensor node platform. We describe the choice of experimental low-cost reconfigurable radio frontends for LOG-a-TEC and discuss the potential capabilities of custom designs. The core part of this chapter gives practical experiences with designing the embedded testbed infrastructure, covering topology design and performance evaluation of the management network as well as our considerations in the choice of network protocols employed in the LOG-a-TEC testbed. Finally, we provide two use cases where the LOG-a-TEC testbed has been used for performing experiments with cognitive radio, one relevant to the investigation of coexistence of primary and secondary users in TV white spaces and the other addressing power allocation and interference control in the case of shared spectrum.

TV White Spaces (TVWS) technology allows wireless devices to opportunistically use locally-available TV channels enabled by a geolocation database. The UK regulator Ofcom has initiated a pilot of TVWS technology in the UK. This paper concerns a large- scale series of trials under that pilot. The purposes are to test aspects of white space technology, including the white space device and geolocation database interactions, the validity of the channel availability/powers calculations by the database and associated interference effects on primary services, and the performances of the white space devices, among others. An additional key purpose is to perform research investigations such as on aggregation of TVWS resources with conventional resources and also aggregation solely within TVWS, secondary coexistence issues and means to mitigate such issues, and primary coexistence issues under challenging deployment geometries, among others. This paper provides an update on the trials, giving an overview of their objectives and characteristics, some aspects that have been covered, and some early results and observations.

The assumption that current unlicensed bands are overused is instrumental in the effort for opening up more spectrum to license-free consumer devices. While many studies have been made on the overall spectrum occupancy, few have focused specifically on the usage of unlicensed bands in environments common for consumer devices. To improve this situation we have performed an in-door survey of the 2.4 GHz frequency band in 5 different residential and 1 conference location in Slovenia between April and June 2014. In this paper we present a portable and robust device used for the measurements, describe the methodology for data analysis and show results from 6 shortterm and 1 long-term measurement campaigns.

This demonstration shows how VESNA wireless sensor nodes can be used for cognitive radio experiments involving wireless sensor networks. SNE-ISMTV is a radio frontend that has been developed for this purpose. Spectrum sensing capability in the TV white-spaces and 2.4 GHz ISM band is demonstrated by running receivers in a swept-tuned spectrum analyzer configuration and displaying measured spectrograms on a laptop PC. Analogue signal transmission simulating a wireless microphone is demonstrated by executing a direct digital synthesis algorithm on the sensor node microprocessor, transmitting the modulated signal using a narrow-band sub-1 GHz transceiver and monitoring the transmission using an USRP.

We present steps involved in planning a wireless sensor network for the LOG-a-TEC outdoor testbed, part of the CREW federation for cognitive radio experiments. Based on initial testbed requirements and estimates of the management network load we have selected two clusters of locations from a large pool of possible locations. We have then performed a verification step. By measuring signal strength and packet loss with a mobile setup we have verified that nodes in the chosen testbed configuration would be able to form a usable mesh network. Finally, we compare our initial estimates of network performance with measurements obtained from the deployed testbed.

The radio spectrum used by wireless communication systems is becoming increasingly crowded. One approach to overcome this problem is to perform real-time dynamic spectrum assignment. To this end, it is necessary to collect information about the radio spectrum, also called spectrum sensing. In this paper a framework is presented which can be used for collecting information about radio spectrum usage. This framework is based on the lowcost and versatile VESNA sensor platform. A spectrum sensing experiment has been performed in the 2.4 GHz to demonstrate the capabilities of the framework.

Wireless intra-aircraft communication is expected to be the enabler for more flexible avionic systems and the reduction of weight and cost in system installations. An alternative to the usage of a dedicated frequency band for wireless intra-aircraft avionics could be the usage of a virtually unregulated ISM band. Cognitive radio techniques could be used to increase system robustness in the likely case of interferences in this kind of frequency bands. A cognitive wireless cabin management system is discussed as a use-case for the validation of this approach. Using the mobile cognitive radio testbed of the FP7 project CREW, spectrum sensing experiments are carried out in a realistic aircraft cabin environment as a baseline for the development of suitable cognitive protocols and to record interference scenarios for the further system design.