Distributed Deep Learning Models for Wireless Signal Classification with Low-Cost Spectrum Sensors

This paper looks into the technology classification problem for a distributed wireless spectrum sensing network. First, a new data-driven model for Automatic Modulation Classification (AMC) based on long short term memory (LSTM) is proposed. The model learns from the time domain amplitude and phase information of the modulation schemes present in the training data without requiring expert features like higher order cyclic moments. Analyses show that the proposed model yields an average classification accuracy of close to 90% at varying SNR conditions ranging from 0dB to 20dB. Further, we explore the utility of this LSTM model for a variable symbol rate scenario. We show that a LSTM based model can learn good representations of variable length time domain sequences, which is useful in classifying modulation signals with different symbol rates. The achieved accuracy of 75% on an input sample length of 64 for which it was not trained, substantiates the representation power of the model. To reduce the data communication overhead from distributed sensors, the feasibility of classification using averaged magnitude spectrum data, or online classification on the low cost sensors is studied. Furthermore, quantized realizations of the proposed models are analyzed for deployment on sensors with low processing power

Position: Health Effects in LED-based Communication Systems and Possible Mitigations

With the invention of Blue LEDs (awarded with the Nobel Prize), white LEDs are now pervasively present in the market, and Visible Light Communication Systems (VLCS) are the result of intensive scientific investigations in the last years. In this work, we review the health effects of LED technology studied in vision science, implications of using VLC with LEDs, and new VLCS design considerations.TRUEpu

Electrosense: Open and Big Spectrum Data

While the radio spectrum allocation is well regulated, there is little knowledge about its actual utilization over time and space. This limitation hinders taking effective actions in various applications including cognitive radios, electrosmog monitoring, and law enforcement. We introduce Electrosense, an initiative that seeks a more efficient, safe and reliable monitoring of the electromagnetic space by improving the accessibility of spectrum data for the general public. A collaborative spectrum monitoring network is designed that monitors the spectrum at large scale with low-cost spectrum sensing nodes. The large set of data is stored and processed in a big data architecture and provided back to the community with an open spectrum data as a service model, that allows users to build diverse and novel applications with different requirements. We illustrate useful usage scenarios of the Electrosense data.Comment: Publishe

Communication Networks of Visible Light Emitting Diodes with Intra-Frame Bidirectional Transmission

Unlike traditional radio frequency communication of consumer devices, the "optical antenna" direction of Visible Light Communication (VLC), i.e., the Field-Of-View (FOV), varies greatly from device to device. This encompasses wide FOVs of ambient infrastructure and directional FOVs of light emitted by low-end embedded devices. This variety of light wave propagation can severely affect the transmission reliability, despite "pointing" devices to each other may seem enough for a reliable link. In particular, the fact that FOVs are unknown makes traditional access protocols in VLC unreliable in presence of interference among nodes of different FOVs and exacerbates the hidden-node problem. In this paper, we propose a Carrier Sensing Multiple Access/Collision Detection&Hidden Avoidance (CSMA/CD-HA) Medium Access Control protocol for a network where each node solely uses one Light Emitting Diode (LED) to transmit and receive data. The CSMA/CD-HA can enable in-band intra-frame bidirectional transmission with just one optical antenna. The key idea is to exploit the intra-frame data symbols without emission of light to introduce an embedded communication channel. This approach enables the transmission of additional data while receiving in the same optical channel and it makes the communication robust to different types of FOVs. We build a software-defined embedded platform running on Linux operating system, implement the CSMA/CD-HA protocol, and evaluate its performance through experiments. Results show that collisions caused by hidden nodes can be reduced and our protocol can increase the saturation throughput by nearly up to 50% and 100% under the two-node and four-node scenarios, respectively.TRUEpu

Location-aware Wireless Resource Allocation in Industrial-like Environment

The advent of the fourth Industrial Revolution (Industry 4.0) requires wireless networked solutions to connect machines. However, the industrial environment is notorious for being averse to wireless communication, with traditional wireless resource mechanisms prone to errors because of metallic objects. In this work, we propose to exploit the knowledge of location to derive context information and dynamically allocate wireless resources in time and space to target devices. We exploit the spatial geometry of the Access Points (APs) and we introduce a statistical model that maps the user position’s spatial distribution to an angle error distribution and derive a hypothesis test to declare if the link is under metallic blockage or not. In order to avoid changes to the client side and operate with a single interface radio, we use the same wireless network both for positioning and scheduling. We experimentally show that our system can localize four mobile robots deployed in a very harsh environment with metal obstacles and reflections. Context information applied to wireless resources protocol help increasing up to 40% of the network throughput in the above industrial-like scenario.pu

Channel quality estimation and impairment mitigation in 802.11 networks

Wireless communication has been boosted by the adoption of 802.11 as standard de facto for WLAN transmission. Born as a niche technology for providing wireless connectivity in small office/enterprise environments, 802.11 has in fact become a common and cheap access solution to the Internet, thanks to the large availability of wireless gateways (home modems, public hot-spots, community networks, and so on). Nowdays, the trend towards increasingly dense 802.11 wireless deployments is creating a real need for effective approaches for channel allocation/hopping, power control, etc. for interference mitigation while new applications such mesh networks in outdoor contexts and media distribution within the home are creating new quality of service demands that require more sophisticated approaches to radio resource allocation. The new framework of WLAN deployments require a complete understanding of channel quality at PHY and MAC layer. Goal of this thesis is to assess the MAC/PHY channel quality and mitigate the different channel impairments in 802.11 networks, both in dense/controlled indoor scenarios and emerging outdoor contexts. More specifically, chapter 1 deals with the necessary background material and gives insight into the different channel impairments/quality it can be encountered in WLAN networks. Then the thesis pursues a down/top approach: chapter 2, 3 and 4 aim at affording impairments/quality at PHY level, while chapter 5 and 6 analyse channel impairments/quality from a MAC level perspective. An important contribution of this thesis is to undisclose that some PHY layer parameters, such as the transmission power, the antenna selection, and interference mitigation scheme, have a deep impact on network performance. Since the criteria for selecting these parameters is left to the vendor specific implementations, the performance spread of most experimental results about 802.11 WLAN could be affected by vendor proprietary schemes. Particularly, in chapter 2 we find that switching transmit diversity mechanisms implemented in off-the-shelf devices with two antenna connectors can dramatically affect both performance and link quality probing mechanisms in outdoor medium-range WLAN deployments, whenever one antenna deterministically works worse than the other one. A second physical algorithm with side-effects is shown in chapter 3. Particulary the chapter shows that interference mitigation algorithms may play havoc with the link-level testbeds, since they may erroneously lower the sensitivity threshold, and thus not detect the 802.11 transmit sources. Finally, once disabled the interference mitigation algorithm — as well as any switching diversity scheme described in the previous chapter — link-level experimental assessment concludes that, unlike 802.11b, which appears a robust technology in most of the operational conditions, 802.11g may lead to inefficiencies when employed in an outdoor scenario, due to the lower multi-path tolerance of 802.11g. Since multipath is hard to predict, a novel mechanism to improve the link-distance estimation accuracy — based on CPU clock information — is outlined in chapter 4. The proposed methodology can not only be applied in localization context, but also for estimating the multi-path profile. The second part of the thesis moves the perspective to the MAC point of view and its impairments. Particularly, chapter 5 provides the design of a MAC channel quality estimator to distinguish the different types of MAC impairments and gives separate quantitative measures of the severity of each one. Since the estimator takes advantage of the native characteristics of the 802.11 protocol, the approach is suited to implementation on commodity hardware and makes available new measures that can be of direct use for rate adaptation, channel allocation, etc. Then, chapter 6 introduces a previous unknown phenomenon, the Hidden ACK, that may cause frame losses into multiple WLAN networks when a node replies with an ACK frame. Again, a solution is provided without requiring any modification to the 802.11 protocol. Whenever possible, the quantitative analysis has been led through experimental assessments with implementation on commodity hardware. This was the adopted methodology in chapter 2, 3, 4 and 5. Particularly, this has required an accurate investigation of two brands of WLAN cards, particularly the Atheros and Intel cards, and their driver/firmware, respectively MADWiFi and IPW2200, which are currently the most adopted, respectively, by researchers and layman users

Evaluation of Self-Positioning Algorithms for Time-of-Flight based Localization

Self-localization systems based on the Time-of-Flight (ToF) of radio signals are highly susceptible to noise and their performance therefore heavily rely on the design and parametrization of robust algorithms. In this work, we study the noise sources of GPS and WiFi ToF ranging techniques and compare the performance of different self-positioning algorithms at a mobile node using those ranges. Our results show that the localization error varies greatly depending on the ranging technology, algorithm selection, and appropriate tuning of the algorithms. We characterize the localization error using real-world measurements and different parameter settings to provide guidance for the design of robust location estimators in realistic settings.TRUEpu

Data Fusion for Hybrid and Autonomous Time-of-Flight Positioning

Existing mobile devices such as smartphones rely on a multi-radio access technology (RAT) architecture to provide pervasive location information in various environmental contexts as the user is moving. Yet, existing architectures consider the different localization technologies as monolithic entities and choose the final navigation position from the RAT that is expected to provide the highest accuracy. In contrast, we propose to fuse timing range measurements of diverse radio technologies in order to circumvent the limitations of the individual radio access technologies. We take a first step in this direction and propose to fuse timing measurements of satellite navigation system and WiFi networks. We introduce different novel methods such as a data fuser, an estimator of WiFi ToF distance and a geometrical-statistical approach to best fuse the set of timing ranging measurements in presence of a rich set of measurements. Experimental results show that our solution allows the mobile device to efficiently self-position itself in diverse challenging scenarios.TRUEpu