Ultra-dense Internet of Things (IoT) networks and machine type communications herald an enormous opportunity for new computing paradigms and are serving as a catalyst for profound change in the evolution of the Internet. We explore leveraging the communication within IoT to serve data processing by appropriately shaping the aggregate behavior of a network to parallel more traditional computation methods. This paper presents an element of this vision, whereby we map the operations of an artificial neural network onto the communication of an IoT network for simultaneous data processing and transfer. That is, we provide a framework to treat a network holistically as an artificial neural network, rather than placing neural networks within the network. The operation of components of a neural network, neurons and connections between neurons, are performed by the various elements of the IoT network, i.e., the devices and their connections. The proposed approach reduces the latency in delivering processed information and supports the locality of information inherent to IoT by removing the need for transfer to remote data processing sites.

We explore the state of the art in solutions for low power wide area (LPWA) networks and technologies serving the Internet of Things (IoT) and Connectivity for Everything markets. These networks are forecast to capture up to 55% market share using battery-powered devices operating up to 10 years and link distances measured in tens of kilometers. In this paper, we survey two LPWA technologies; ultra-narrow band solutions by SigFox and the LoRa technology by Semtech. Both technologies operate in the licence-exempt industrial, scientific, & medical (ISM) bands (EU 868 MHz / US 915 MHz). We survey both solutions in terms of physical layer (PHY) and associated medium access control (MAC) capabilities from an end-to-end system viewpoint. We then proceed to explore coverage ranges in eastern Ireland.We present results indicating a potential coverage area of 3,800 km2and from a real-world experimental test case involving the use of SigFox's technology operating over a 25 km test link between a 25 mW LPWA client test and a basestation. Finally, we provide example results demonstrating a received SNR consistently exceeding 20 dB over this test link distance.

In this paper, we focus on two methods that can be used to increase the resilience of remotely-deployed and unattended IoT devices that must operate without direct human intervention. The methods include adaptive messaging rates for power-constrained devices where the most energy intensive process involves the transmission and reception of data via wireless means, and data caching and replay for extended network connectivity outages. In this paper, we discuss how these techniques were applied in a real-world wireless IoT sensor network in Dublin, Ireland. Specifically, we show that: 1) The operating lifetime of a power-constrained device can be extended through the use of adaptive messaging rates 2) Sensor data backfilling following extended periods of network outages is a feasible method of preventing sensor data loss. We provide a example demonstrating that the operating lifetime of a power-constrained IoT device can be extended using the adaptive message rate approach. Additionally, we demonstrate how extended network connectivity outages can be recovered from using an elastic message cache approach. Finally, we conclude that the combination of both of these techniques are feasible methods to increase the resilience of real-world IoT devices operating in volatile power and wireless communications environments.

We present a novel technique for radio transmitter identification based on frequency domain characteristics. Our technique detects the unique features imbued in a signal as it passes through a transmit chain. We are the first to propose the use of discriminatory classifiers based on steady state spectral features. In laboratory experiments, we achieve 97% accuracy at 30 dB SNR and 66% accuracy at OdB SNR based on eight identical universal software radio peripherals (USRP) transmitters. Our technique can be implemented using today's low cost high-volume receivers and requires no manual performance tuning.

We define a cyclostationary signature as a feature which may be intentionally embedded in a digital communications signal, detected through cyclostationary analysis and used as a unique identifier. The purpose of this paper is to demonstrate how cyclostationary signatures can be exploited to overcome a number of the challenges associated with network coordination in emerging cognitive radio applications and spectrum sharing regimes. In particular we show their uses for signal detection, network identification and rendezvous and discuss these in the context of dynamic spectrum access. We present a theoretical discussion followed by application-oriented examples of the cyclostationary signatures used in practical cognitive radio and dynamic spectrum usage scenarios. We focus on orthogonal frequency division multiplexing (OFDM) based systems and present an analysis of a transceiver implementation employing these techniques developed on a cognitive radio test platform.

The Centre for Telecommunications Value-Chain Research (CTVR) and the Center for Wireless Telecommunications (CWT) are undertaking a joint collaborative research project investigating the potential of different software-defined radio (SDR) and cognitive radio (CR) systems that can interoperate and co-exist in common frequency bands.This paper presents some key results from this experience so far, including an over-the-air interoperability analysis of two different SDR architectures in the same frequency band.An initial analysis of actual co-existence experiences involving primary users and secondary opportunistic spectrum users in a common frequency band is also presented.

The ever increasing demands for access to frequency spectrum and more efficient methods of using this spectrum involving multi-carrier techniques are driving the development of reconfigurable and cognitive wireless devices. The potential for, and the need to accommodate the potentially time-varying entropy in these wireless systems presents several design and implementation challenges. However, significant opportunities for innovation extending from the wireless terminal implementation to the business and market models also exist. This paper focuses on the physical (PHY) and medium-access control (MAC) layer issues of these emerging systems, highlighting the following three main contributions: An introduction to reconfigurable multi-carrier code division multiple access (MC-CDMA), an exploration of the use of reconfigurable MC-CDMA and its impact on the design of the physical (PHY) and medium access control (MAC) layers in a cognitive radio context and overview of the practical design and development considerations of this novel system which is being implemented on a real cognitive radio development testbed.

In this paper, we present findings relating to frame synchronization algorithms for software radio based OFDM systems in addition to an overview of the design and implementation of an (OFDM) software radio based on a general-purpose processor (GPP) platform. The objectives of this work are to advance on existing research carried out in the area of reconfigurable wireless flexible architecture nodes, which are subject to multipath fading, Doppler effects, and adjacent channel interference and have low cost yet robust and reliable operation requirements. We also include findings dealing with bit error rate (BER) versus channel signal to noise ratio (SNR) for BPSK and QPSK modulation schemes, and also the effect of non real-time operating systems (OS) running on GPPs on the transmitter processing time.

This paper describes an automatic modulation scheme recognition technique. The technique is designed for a real-time software radio using general-purpose processors and is based on modified pattern recognition and signal space approaches. It is robust and efficient with a processing time overhead that still allows the software radio to maintain its real-time operating objectives. Both digital and analogue modulation schemes can be identified. Tests and simulations using an AWGN channel show that the SNR threshold for correct analogue modulation scheme classification is approximately 6.5 dB.