A theoretical study and an experimental evaluation on the performance of the long-range (LoRa) technology are presented in this paper. After an instructive mathematical review of important concepts, we assess the LoRa performance in additive white Gaussian noise (AWGN) channels through a numerical model, to elucidate its communication capabilities in negative signal-to-noise ratio (SNR) conditions and, as consequence, in the long distances promised by such low power and narrowband technology. Because of the significance of forward error correction codes in the performance of modern systems, we propose an analytical bit-error-rate (BER) expression that considers the influence of LoRa code rate (CR) parameter. The agreement between the theoretical and the numerical results of a Hamming coded system validated the closed-form BER, evaluated in terms of SNR in AWGN channels. Moreover, an experimental setup with off-the-shelf LoRa wide area network (LoRaWAN) equipment was prepared to demonstrate the feasibility of this promising technology, as well the impact of the CR parameter on the packet error rate (PER), in a link with a single end-device. As expected, communication in urban and open areas with distances up to ≈3 and ≈10 km, respectively, were achieved, according to measurements of the average received signal indicators around -100 dBm for an average SNR ≈5 dB. The usefulness of the practical analysis was confirmed by the agreement between the theoretical and the measured noise floors, and by the verification of the substantial impact of the parameter CR on the system PER.

A resource optimization methodology is proposed for application in long range wide area networks (LoRaWANs). Using variable neighborhood search (VNS) and a minimum-cost spanning tree algorithm, it reduces the implementation and the maintenance costs of such low power networks. Performance evaluations were conducted in LoRaWANs with LoRa repeaters to increase coverage, in scenario where the number and the location of the repeaters are determined by the VNS metaheuristic. Parameters such as spread factor ($SF$), bandwidth and transmission power were adjusted to minimize the network’s total energy per useful bit ($E_{bit}$) and the total data collection time. The importance of the $SF$ in the trade-off between ($E_{bit}$) and time on-air is evaluated, considering a device scaling factor. Simulation results, obtained after model adjustments with experimental data, show that, in networks with few associated devices, there is a preference for small values of $SF$ aiming at reduction of $E_{bit}$. The usage of large $SF$’s becomes relevant when reach extensions are required. The results also demonstrate that, for networks with high number of nodes, the scaling of devices over time become relevant in the fitness function, forcing an equal distribution of time slots per $SF$ to avoid discrepancies in the time data collection.

Visible Light Communication (VLC) is an interesting solution in Intensive Care (IC) medical environments to, among others, prevent the spread of emerging diseases. This work presents the design of a low-cost and stable VLC transceiver system in addition to practical characterizations and experimental performance evaluations for application in IC environments. The application focuses on the transmission of Manchester-based on-off keying signals, in a proof-of-concept apparatus that makes use of the Eye Opening Penalty (EOP) metric to illustrate a comprehensive picture of the potentials of the evaluated VLC system. Parameters such as Light-Emitting Diode (LED) bias current, modulation frequency, line-of-sight link distance, and signal pattern were analyzed here. Experimental results show an outstanding behavior considering an LED bias current of 400 mA, a signal frequency of 1 MHz and a VLC transmission link length of 2.5 m. To validate our system, vital parameters as heart rate, oxygen saturation, pulse rate, respiration rate, temperature and non-intrusive blood pressure signals were transmitted for VLC links of 1.5, 5 and 15 m, which were received by a multi-parameter monitor, with EOP values of 0.89, 0.96 and 2.67 dB, respectively.

In this paper, artificial intelligence tools are implemented in order to predict trajectory positions, as well as channel performance of an optical wireless communications link. Case studies for industrial scenarios are considered to this aim. In a first stage, system parameters are optimized using a hybrid multi-objective optimization (HMO) procedure based on the grey wolf optimizer and the non-sorting genetic algorithm III with the goal of simultaneously maximizing power and spectral efficiency. In a second stage, we demonstrate that a long short-term memory neural network (LSTM) is able to predict positions, as well as channel gain. In this way, the VLC links can be configured with the optimal parameters provided by the HMO. The success of the proposed LSTM architectures was validated by training and test root-mean square error evaluations below 1%.

In this paper, we report an experimental demonstration of using an integrated silicon photonic neural network to overcome the chromatic distortion of direct-detection optical systems based on orthogonal frequency-division multiplexing (OFDM). The precompensation is conducted in the optical domain of a 125 km link of standard single-mode fiber (SSMF), i.e., the proposed approach enables OFDM pre-equalization directly in the optical domain instead of electronic distortion compensation that characterizes common OFDM-based systems. Thanks to the intrinsic features of the OFDM multiplexing format, and to the elimination of cyclic prefix provided by our proposal, improvements in spectral and power efficiencies can be achieved. The performance enhancements registered in the conducted experiments show that photonic integrated circuits can be embedded in future OFDM-based commercial transceivers, paving the way for new and promising architectures of intensity modulation and direct-detection optical communication systems.