GNSS spoofing is a growing threat to UAV operations, especially in decentralized drone swarms. In this paper, we present both a practical spoofing attack and a lightweight detection algorithm based on Wi-Fi RSSI and GNSS coordinates. The attack selectively compromises drones by transmitting a subset of satellite signals, causing drones to calculate wrong positions. Our detection method leverages geometric consistency checks to validate GNSS-based positions without requiring any infrastructure or additional sensors. Simulation results show that the proposed attack successfully misleads victim drones, and that the detection method reliably helps drones identify such attacks.

In this paper, we present SDR-LoRa, an open-source, full-fledged Software Defined Radio (SDR) implementation of a LoRa transceiver. First, we conduct a thorough analysis of the LoRa physical layer (PHY) functionalities, encompassing processes such as packet modulation, demodulation, and preamble detection. Then, we leverage on this analysis to create a pioneering SDR-based LoRa PHY implementation. Accordingly, we thoroughly describe all the implementation details. Moreover, we illustrate how SDR-LoRa can help boost research on the LoRa protocol by presenting three exemplary key applications that can be built on top of our implementation, namely fine-grained localization, interference cancellation, and enhanced link reliability. To validate SDR-LoRa and its applications, we test it on two different platforms: (i) a physical setup involving USRP radios and off-the-shelf commercial devices, and (ii) the Colosseum wireless channel emulator. Our experimental findings reveal that (i) SDR-LoRa performs comparably to conventional commercial LoRa systems, and (ii) all the aforementioned applications can be successfully implemented on top of SDR-LoRa with remarkable results. The complete details of the SDR-LoRa implementation code have been publicly shared online, together with a plug-and-play Colosseum container.

In this paper, we present a novel intelligent management system (IMS) for smart retail environments that integrates various components to optimize user experience, energy efficiency, and seamless connectivity. The proposed architecture incorporates an Intelligent Handover Controller, an Energy Harvesting Module, Adaptive Resource Management, Edge Tracking and Localization. Preliminary testbed results show promising performance in maintaining seamless handovers between VLC and WiFi links, as well as accurate tracking of user mobility based on CSI. This advanced architecture offers the potential for significant improvements in smart retail operations by providing uninterrupted connectivity, targeted marketing, optimized store layouts, and enhanced user experiences.

In this paper we study the capability of LoRa technology in rejecting different interfering LoRa signals and the impact on the cell capacity. First, we analyze experimentally the link-level performance of LoRa and show that collisions between packets modulated with the same Spreading Factor (SF) usually lead to channel captures, while different spreading factors can indeed cause packet loss if the interference power is strong enough. Second, we model the effect of such findings to quantify the achievable capacity in a typical LoRa cell: we show that high SFs, generally seen as more robust, can be severely affected by inter-SF interference and that different criteria for deciding SF allocations within the cell may lead to significantly different results. Moreover, the use of power control and packet fragmentation can be detrimental more than beneficial in many deployment scenarios. Finally, we discuss the capacity improvements that can be achieved by increasing the density of LoRa gateways. Our results have important implications for the design of LoRa networks: for example, allocating high SFs to faraway end devices might not improve the experienced performance in case of congested networks because of the increased transmission time and vulnerability period.

The pervasive diffusion of smartphones is boosting indoor positioning solutions and location-based services. We propose a novel methodology to perform indoor positioning of mobile users by the estimation of angles of arrival from access points whose locations are known. Angles of arrival are estimated by correlating WiFi RSSI measurements with data coming from a digital compass, which is provided by most current handsets. Our system has minimal requirements in terms of infrastructure and mobile hardware. The system neither needs calibration, nor radio maps but requires the user to perform a gesture when an estimation is needed. The resulting on-demand localization has advantages in terms of privacy and power efficiency. Initial experimental results, even under severe multipath conditions, show good accuracy in terms of angle of arrival estimation and promising results on localization.

LTE is rapidly gaining momentum for building future 4G cellular systems, and real operational networks are under deployment worldwide. To achieve high throughput performance, in addition to an advanced physical layer design LTE exploits a combination of sophisticated mechanisms at the radio resource management layer. Clearly, this makes difficult to develop analytical tools to accurately assess and optimise the user perceived throughput under realistic channel assumptions. Thus, most existing studies focus only on link-layer throughput or consider individual mechanisms in isolation. The main contribution of this paper is a unified modelling framework of the MAC-level downlink throughput of a sigle LTE cell, which caters for wideband CQI feedback schemes, AMC and HARQ protocols as defined in the LTE standard. We have validated the accuracy of the proposed model through detailed LTE simulations carried out with the ns-3 simulator extended with the LENA module for LTE.

In free space optical (FSO) communications, several factors can strongly affect the link quality. Among them, one of the most important impairments that can degrade the FSO link quality and its reliability – even under the clear sky conditions – consists of optical turbulence. In this work, the authors investigate the generation of both weak and moderate turbulence regimes in an indoor environment to assess the FSO link quality. In particular, they show that, due to the presence of the turbulence, the link experiences both erasure errors and packet losses during transmission, and also compare the experimental statistical distribution of samples with the predicted Gamma–Gamma model. Furthermore, the authors demonstrate that the application of the RaptorQ codes noticeably improves the link quality decreasing the packet error rate (PER) by about an order of magnitude, also offering – in certain cases – an error‐free transmission with a PER of ∼10 −2 at Rytov variance value of 0.5. The results show that the recovery rate increases with the redundancy, the packet length and the number of source packets, and it decreases with increasing data rates.

Recent years have witnessed the increasing adoption of heterogeneous wireless networks working in unlicensed ISM bands, thus creating serious problems of spectrum overcrowding. Although ZigBee, Bluetooth and WiFi networks have been natively designed for working in presence of interference, it has been observed that several performance impairments may occur because of heterogeneous sensitivity to detect or react to the presence of other technologies. In this paper we focus on the WiFi capability to detect interfering ZigBee links. Despite of the narrowband transmissions performed by ZigBee, in emerging scenarios ZigBee interference can have a significant impact on WiFi performance. Therefore, interference detection is essential for improving coexistence strategies in heterogeneous networks. In our work we show how such a detection can be performed on commodity cards working on time and frequency domain and also analysing data in the error domain. Errors are monitored and classified into error patterns observed in the network in terms of occurrence probability and temporal clustering of different error events. Through statistical analysis we are able to detect the presence of ZigBee transmissions measuring the errors raised by the WiFi card.

The huge spread of wireless networks and the success of location-aware applications require novel indoor positioning mechanisms based on existing technologies such as IEEE 802.11. Taking inspiration from the RADAR, we propose WIDAR: a bistatic WI-fi Detection And Ranging system for off-the-shelf devices. WIDAR implementation is based on the USRP2 platform and is able to locate 802.11 stations while they operate in existing legacy networks. No substitution or repositioning of the Access Points is necessary. WIDAR works passively and does not expect any dedicated action from the target WiFi node. No airtime is wasted and the target cannot even detect that it is being ranged. Such features make WIDAR desirable in surveillance and monitoring applications where it can provide real-time tracking functionalities.

The problem of resource allocation in cellular networks has been traditionally faced at two different levels: at the network level, in terms of frequency planning and reuse pattern design, and at the cell level, in terms of cell capacity optimizations based on channel-dependent scheduling, link adaptation, power control, and so on. While this second aspect has been deeply investigated in literature, the first aspect has been mainly faced with static or semi-dynamic reuse utilization solutions. In this paper we deal with the problem of multi-cellular resource allocation in heterogeneous OFDMA environments with reuse factor equal to 1, where base stations with different power constraints coexist. In particular, we analyze the effects of different allocation schemes, independently performed in each cell, on the aggregated network-level performance. By means of simulation results, we enlighten the network scenarios in which network planning and mobile station feedbacks are (or not are) advantageous.

A novel Orthogonal Frequency Division Multiplexing receiver architecture to be employed with standard (e.g. Wireless LAN) transmitters is proposed. It features enhanced error-rate performance with flexible computational complexity and robustness to imperfect channel estimation. It is based on exploitation of the redundancy available in the cyclic prefix after cancellation of interference from the previous block. In order to show the effectiveness of our proposal, a number of comparisons to the standard per-subcarrier receiver and a previously existing method are reported.

Orthogonal frequency division multiplexing based on offset quadrature amplitude modulation (OFDM-OQAM) is a multicarrier signaling technique which trades off robustness for spectral efficiency when compared to conventional OFDM with a cyclic prefix. In this paper, a novel matrix model for passband OFDM-OQAM signaling with a small number of subcarriers over a multipath frequency selective fading channel is presented. Specifically, in OFDM-OQAM a frequency selective channel is divided into many smaller but still frequency selective overlapping channels, so approximating the frequency response of a subchannel by the channel frequency response sampled at the subcarrier frequency may be inadequate. Channel effects may be better characterized if the frequency response of each subchannel is represented as a Taylor expansion at the subcarrier frequency. Simulation results show how the matrix model implemented by means of this approximation is a suitable model for OFDM-OQAM with a small number of subcarriers.