In this paper, we experimentally compare orthogonal frequency-division multiplexing (OFDM) and on-off keying (OOK) modulation in the context of the IEEE 802.15.13-2023 standard at bandwidths up to 50 MHz across a Li-Fi link with distances up to 5 m and a lateral offset up to 51°. Error vector magnitude (EVM) and bit error rate (BER) evaluations confirm that the high peak-to-average power ratio (PAPR) of OFDM limits the achievable transmission distance, but it offers higher data rates due to its higher spectral efficiency. Due to the lower PAPR, OOK-based Pulsed Modulation PHY (PM-PHY) shows a significantly higher link range. As the structure of the PM-PHY is based on OFDM symbols, the two solutions may also be combined to open a wider range of use cases for optical wireless communications.
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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%.
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Quantifying measures of physical loading has been an essential part of performance monitoring within elite able-bodied sport, facilitated through advancing innovative technology. In wheelchair court sports (WCS) the inter-individual variability of physical impairments in the athletes increases the necessity for accurate load and performance measurements, while at the same time standard load monitoring methods (e.g. heart-rate) often fail in this group and dedicated WCS performance measurement methods are scarce. The objective of this review was to provide practitioners and researchers with an overview and recommendations to underpin the selection of suitable technologies for a variety of load and performance monitoring purposes specific to WCS. This review explored the different technologies that have been used for load and performance monitoring in WCS. During structured field testing, magnetic switch based devices, optical encoders and laser systems have all been used to monitor linear aspects of performance. However, movement in WCS is multidirectional, hence accelerations, decelerations and rotational performance and their impact on physiological responses and determination of skill level, is also of interest. Subsequently both for structured field testing as well as match-play and training, inertial measurement units mounted on wheels and frame have emerged as an accurate and practical option for quantifying linear and non-linear movements. In conclusion, each method has its place in load and performance measurement, yet inertial sensors seem most versatile and accurate. However, to add context to load and performance metrics, position-based acquisition devices such as automated image-based processing or local positioning systems are required.
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