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The quality of an optical signal degrades due to physical layer impairments as it propagates from a transmitter to a receiver. As a result, the signal quality at the receiver of a lightpath may not be sufficiently high, leading to increased call blocking. Consequently, an all-optical network’s routing and wavelength assignment algorithm must verify the quality of the lightpath before accepting it. In this paper, analytical expressions for the total blocking probability are derived for first-fit wavelength assignment for networks suffering from transmission impairments. The new technique effectively predicts the performance of wavelength selection techniques that consider either a single candidate channel or all channels for quality of transmission compliance. The analysis is also applicable to first-fit algorithms with different static channel orderings. [ABSTRACT FROM PUBLISHER]

In long-haul fiber-optic networks, precise modeling of physical-layer impairments (PLIs) is crucial to optimizing network resource usage while ensuring adequate transmission quality. In order to accurately estimate PLIs, many mathematical models have been proposed. Among them, the so-called Gaussian noise (GN) model is one of the most accurate and simple enough to use on complex continental-size networks. However, the closed-form GN model assumes that the signals can be represented as having rectangular spectra, leading to a significant estimation error in typical cases when this assumption is violated. We propose the component-wise Gaussian noise (CWGN) PLI model that can account for arbitrary spectral-shaped demands. The CWGN model is computationally simple and suitable for most network management approaches. Results indicate that the CWGN model can prevent as much as a 136% overestimation of the PLIs resulting from the closed-form GN model applied to network lightpaths containing cascaded filters.

Visible light communications (VLC) is a short-range optical wireless communication technology that uses light-emitting diodes (LEDs) as lighting devices and data transmitters. This paper describes a multiuser VLC system using Hadamard-coded modulation (HCM) for indoor data transmission. Considering the peak transmitted power limit of the LEDs, a DC-reduced HCM (DCR-HCM) is used to reduce the nonlinear clipping distortion. Since the Hadamard codewords have different bandwidth requirements for a given symbol rate, they can be assigned to users with varying hardware capabilities. Optimally assigning codewords to users is found to significantly improve the average throughput, up to twice higher than a random assignment for a typical scenario. When the number of active users is less than the size of the Hadamard matrix used, more than one codeword can be assigned per user, which further improves the throughput. This paper also examines a scenario where multiple lamps in an indoor space transmit the same data. Since the time of arrival for the received signals emitted from different lamps is different, the Hadamard codes received are no longer orthogonal, resulting in multiple access interference and inter-chip interference. The number of acceptable codewords is computed based on the specific interference experienced in different parts of the indoor space. The spatial distribution of the maximum throughput is also simulated, showing that the ratio of the maximum to the minimum data rate can be as high as 10 when considering the entire area of a typical indoor room. This article is part of the theme issue 'Optical wireless communication'.

Gait impairment in multiple sclerosis (MS) can result from muscle weakness, physical fatigue, lack of coordination, and other symptoms. Walking speed, as measured by a number of clinician-administered walking tests, is the primary measure of gait impairment used by clinical researchers, but inertial gait features from body-worn sensors have been proven to add clinical value. This paper seeks to understand and differentiate the physiological significance of four such features with proven value in MS to facilitate adoption by clinical researchers and incorporation in gait monitoring and analysis systems. In addition, this information can be used to select features that might be appropriate in other forms of disability. Two of the four features are computed using the dynamic time warping (DTW) algorithm: The "DTW Score" is based on the usual DTW distance, and the "Warp Score" is based on the warping length. The third feature, based on kernel density estimation (KDE), is the "KDE Peak" value. Finally, the "Causality Index" is based on the phase slope index between inertial signals from different body parts. Relationships between these measures and the aforementioned gait-related symptoms are determined by applying factor analysis to three common, clinical walking outcomes, then correlating the inertial measures as well as walking speed to each extracted factor. Statistically significant differences in correlation coefficients to the three extracted clinical factors support their distinct physiological meaning and suggest they may have complimentary roles in the analysis of MS-related walking disability.

Most multiple sclerosis (MS) patients eventually suffer from mobility impairment, and thus it is critical that walking disability in MS be accurately assessed. The six-minute walk test (6MWT), a reliable MS measure, is traditionally used to determine the distance covered in six minutes using a standard protocol. With the availability of body sensor networks (BSNs), researchers are interested in leveraging BSN data for finding new gait assessment anchors for improved separability performance. Further, current methods for gait assessments are insufficient since assessments are absolute, performed by comparing outcomes to the statistical norms established from diverse patient data despite natural inter-patient variability. For example, walking at a slower pace may be a personal trait rather than a fatigue-induced impact in MS. Thus instead of using actual values, changes in gait features during a 6MWT can be used to draw clinical conclusions and remove inter-subject variability. We use 6MWT gait time series BSN data of MS subjects to determine changes in their gait speed and gait cycle length variance over six minutes. We also determine the relationships between these variables and three subjective assessments, namely functional systems scores, modified fatigue impact scale, and multiple sclerosis walking scale. These relationships are important in order to validate features and make them clinically meaningful for a doctor. In MS, feelings of fatigue can occur more often, and have a greater impact on a subject's daily life. The results show that MS patients who reported high motor-related fatigue slowed down and had high gait cycle length variance in the last minute of the test, in contrast to those on whom fatigue had minimal impact, enhancing the separability between MS subjects of varied disabilities based on their scores. It is also observed that FSS components related to coordination, balance, and physical activities show strong correlation with gait parameters.