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The rapid expansion of Internet of Things (IoT) networks has paved the way for their integration into mission-critical applications requiring secure and reliable monitoring, such as smart grid utilities. However, these advanced power grids face significant challenges in maintaining reliable wireless communication, particularly in hostile environments like high-voltage substations and power plants. These environments are characterized by intense bursts of interference, known as impulsive noise with memory. To address this problem, in this study, we introduce a two-process receiver design. The first process is a multi-step receiver parameter estimation process. The second process is a novel memory-aware log-likelihood ratio (LLR) calculation method designed to mitigate the effects of impulsive noise with memory using the parameters estimated from the first process. This method is computationally efficient, which makes it suitable for IoT devices with limited computational capabilities. Simulation results obtained show that the proposed method achieves a bit error rate (BER) similar to the corresponding BERs of the best-performing algorithms with perfect noise parameters. Furthermore, it outperforms the Viterbi algorithm amid imperfect noise parameters. Notably, it method achieves these benchmarks while substantially improving execution time.

Internet of Things (IoT) can provide an on-line monitoring system for power substations and therefore offer a much more reliable maintenance strategy for power devices. However, energizing the monitoring sensors in a power substation and around High Voltage (HV) devices is difficult and costly. It is possible to reduce the installation costs significantly if the monitoring sensors can be self-sustainable. In this work, we study an autonomous Wireless Sensor Network(WSN), based on energy harvesting and wireless transfer of energy. In order to optimize the performance of this system, we propose and analyze two power allocation techniques, aiming to energize the monitoring sensors wirelessly. This paper concludes that by optimizing the parameters of the system, a self-sustainable WSN in a power substation can be successfully deployed.

A smarter power grid can improve the maintenance system by providing a real-time measurement of equipment operating conditions. Such a monitoring system requires the deployment of an increased number of sensors. However, the wiring sensors in a high voltage environment such as power substation is a very expensive procedure. An autonomous wireless sensor network can reduce the installation cost and make sensors more viable throughout the network. In this paper, we study the possibility of deploying an autonomous wireless sensor network in a substation environment. To this end, we merge energy harvesting and wireless transfer of energy to propose a hierarchical energy harvesting model. In this paper, we show that despite of the wasteful nature of the wireless transfer of energy and with an efficiency not more than what existing technologies can provide, a self-sustainable wireless sensor network in a substation area can be accomplished.

The importance of synergy with industry lies in the possibility of experimental validation of the work research results. With Software-Defined Radio (SDR) platforms, it is possible to implement a physical layer and to have tests with hardware in a real environment. In this paper, we investigate the validation of an impulsive noise resistant physical layer based on Orthogonal Frequency Division Multiplexing (OFDM) and an interesting concatenation of forward error correcting codes: Rank metric Code (RC) and Convolutional Code (CC). We fully design and implement a new block namely RC Encoder + WiFi Mapper in GNU Radio, which acts as a forward error correcting code to mitigate impulsive noise occurring in substations. After showing by simulations that using this coding scheme is very efficient in mitigating the bursty nature of impulsive noise, we then confirm that the same performance is maintained even with various impulsive voltages and experimental scenarios, which confirms the high performance of the proposed approach.

In “S. Rossore, Migliarino, Massaciuccoli” Natural Park (Pisa, I) six-month-old pedunculate oak seedlings (Quercus robur L.) were transplanted within natural gaps of a mixed oak forest. Micro-environmental variability for radiation and water soil content were measured for 145 seedlings during the year. Irradiation relative to the open field (IR) ranged from 5% to 57%. Seven classes of IR each with 20 seedlings were selected. Leaf mass per area was strongly influenced by IR. In the first 3 years survival was high (95, 76 and 75%, respectively) and seedling reached 14±6 cm, 27±13 cm and 39±19 (sd) cm of height. Even if IR and soil water content (SWC) were negatively associated, indicating a lower SWC at the centre of the gaps, height and its relative growth rate increased with IR (explored range: 8-40%) with a significant interaction with SWC in the 1st year, indicating the positive effect of soil moisture. In the 3rd year dimensional traits were higher in L+W+ (high light and humidity) followed by L-W+ (low light and high humidity), L+W- and finally by L-W-. Summer drought typical of the Mediterranean climate was evaluated by chlorophyll fluorescence of PSII on apical leaves of seedlings and mature trees at the beginning (21 June) and in mid-summer (20 July). While in June physiological traits did not differ between low and high IR, in mid-summer (at the peak of water-stress) seedlings of the two highest light classes showed chronic photoinhibition (Fv/Fm

Recently, research topics are focusing on clustering approaches for Ad hoc networks due to their effectiveness in building a virtual backbone formed by a set of suitableclusterheads (CH) to guarantee the communications acrossclusters. In this paper, we propose a clustering approach to elect suitable nodes’ representatives and to store minimum topology information by reducing the propagation of routing information which facilitates the spatial reuse of resource and increase the system capacity. The clusters must adapt dynamically to the environment changes, we also propose a distributed maintenance procedure that allows managing nodes’ adhesion, nodes’ handoff and CHs’ re-election. Based on our analytical model used to estimate the quality of service (QoS) parameters, we implement an admission control algorithm to determine the number of members inside a cluster that can be accommodated while satisfying the constraints imposed by the current applications. This might effectively drive congestion avoidance on the CH andinterclusters load-balancing to achieve better network resource utilization. The obtained results will help us to readjust the clustering algorithm metrics in order to provide better maintenance and QoS guarantees depending on the used applications. Through numerical analysis and simulations, we have studied the performance of our model and compared it with that of other existing algorithms. The results demonstrate better performance in terms of number of clusters, number of handoffs, number of transitions (state change) on CHs, QoS parameters, load balancing and scalability. We also observed how the connectivity and the stability are maximized when the number of nodes increases in presence of the mobility.

Mobile ad hoc networks (MANET) are very difficult to design in terms of scenarios specification and propagation modeling. All these aspects must be taken into account when designing MANET. For cost-effective designing, powerful and accurate simulation tools are needed. Our first contribution in this paper is to provide a global approach process (GAP) in channel modeling combining scenarios and propagation in order to have a better analysis of the physical layer, and finally to improve performances of the whole network. The GAP is implemented in an integrated simulation tool, Ad-SMPro. Moreover, channel statistics, throughput and delay are some key points to be considered when studying a mobile wireless networks. A carefully analysis of mobility effects over second order channel statistics and system performances is made based on our optimized simulation tool, Ad-SMProl. The channel is modeled by large scale fading and small scale fading including Doppler spectrum due to the double mobility of the nodes. Level Cross Rate and Average Duration of Fade are simulated as function of double mobility degree, a defined to be the ratio of the nodes' speeds. These results are compared to the theoretical predictions. We demonstrate that, in mobile ad hoc networks, flat fading channels and frequency-selective fading channels are differently affected. In addition, Bit Error rate is analysed as function of the ratio of the average bit energy to thermal noise density. Other performances (such as throughput, delay and routing traffic) are analysed and conclusions related to the proposed simulation model and the mobility effects are drawn.