Visible light communication (VLC) has been proposed as an alternative or complementary technology to radio frequency vehicular communications. Front and back vehicle lights can serve as wireless transmitters making VLC a natural vehicular connectivity solution. In this paper, we evaluate the performance limits of vehicular VLC systems. First, we use non-sequential ray tracing to obtain the channel impulse responses (CIRs) for vehicle-to-vehicle (V2V) link in various weather conditions. Based on these CIRs, we present a closedform path loss expression which builds upon the summation of geometrical loss and attenuation loss and takes into account asymmetrical patterns of vehicle light sources and geometry of V2V transmission. The proposed expression is an explicit function of link distance, lateral shift between two vehicles, weather type (quantified by the extinction coefficient), transmitter beam divergence angle and receiver aperture diameter. Then, we utilize this expression to determine the maximum achievable link distance of V2V systems for clear, rainy and foggy weather conditions while ensuring a targeted bit error rate.

Predicting students’ grades has emerged as a major area of investigation in education due to the desire to identify the underlying factors that influence academic performance. Because of limited success in predicting the grade point average (GPA), most of the prior research has focused on predicting grades in a specific set of classes based on students’ prior performances. The issues associated with data-driven models of GPA prediction are further amplified by a small sample size and a relatively large dimensionality of observations in an experiment. In this paper, we utilize the state-of-the-art machine learning techniques to construct and validate a predictive model of GPA solely based on a set of self-regulatory learning behaviors determined in a relatively small-sample experiment. We quantify the predictability of each constituents of the constructed model and discuss its relevance. Ultimately, the goal of grade prediction in similar experiments is to use the constructed models for the design of intervention strategies aimed at helping students at risk of academic failure. In this regard, we lay the mathematical groundwork for defining and detecting probably helpful interventions using a probabilistic predictive model of GPA. We demonstrate the application of this framework by defining basic interventions and detecting those interventions that are probably helpful to students with a low GPA. The use of self-regulatory behaviors is warranted, because the proposed interventions can be easily practiced by students.

In this paper, we investigate cooperative visible light communication (VLC) system where an intermediate light source acts as a relay terminal. We assume that relay terminal operates in full-duplex mode. In contrast to radio frequency counterparts, full-duplex VLC terminal is relatively easier to implement due to directive propagation characteristic of light. We first model VLC relay terminal taking into account loop interference channel based on ray tracing simulations. Then, we investigate error rate performance of the relay-assisted VLC system. Our performance evaluations demonstrate the superiority of full-duplex relaying over half-duplex counterpart especially for high modulation sizes.

In this paper, we investigate link adaptation for an orthogonal frequency division multiplexing (OFDM)-based multiple-input multiple-output (MIMO) visible light communication (VLC) system. The proposed adaptive OFDM VLC system supports both repetition coding (RC) and spatial multiplexing (SM) as MIMO modes and allows spatial mode switching based on channel conditions. Regarding to the instantaneous signal-to-noise ratio for both RC and SM modes, the maximum constellation size that can be supported for each MIMO mode on each subcarrier is determined. The MIMO mode that gives the highest spectral efficiency (SE) is then selected. The proposed joint MIMO mode selection and bit loading scheme maximizes the SE while satisfying a target bit error rate. Our numerical results reveal that a peak data rate up to 18.3 Gb/sec can be achieved in a $16 \times 16$ MIMO setting using light emitting diodes with cut-off frequency of 10 MHz in typical indoor environments.

Visible light communication (VLC) builds upon the idea of using existing lighting infrastructure for wireless data transmission. In a conventional VLC network, each light fixture acts as an access point (AP) which are connected to each other through electrical grid as well as data backbone. These VLC-enabled fixtures consist baseband unit (BBU) followed by the optical front-end (OFE). In this paper, we propose the so-called centralized light access network (C-LiAN) which aggregates all AP computational resources into a central pool that is managed by a centralized controller. Unlike the distributed architecture where each light fixture performs both baseband processing and optical transmission/reception, the centralized architecture employs “dummy” fixtures with a VLC OFE. Moving the baseband processing to a central pool reduces the associated cost and complexity of each VLC-enabled LED luminary. It further enables joint processing of signals from different APs making possible an efficient implementation of joint processing, offloading, handover, interference management, scheduling, and resource management algorithms. As an example to demonstrate the virtues of C-LiAN, we further present the performance of coordinated multi-point transmission and enhanced inter-cell interference coordination with almost blank subframe techniques originally proposed for Long Term Evolution-Advanced in the context of indoor VLC networks.