Effect of a vehicle's mobility on SNR and SINR in vehicular optical camera communication systems.

The widespread use of light-emitting diodes (LEDs) and cameras in vehicular environments provides an excellent opportunity for optical camera communication (OCC) in intelligent transport systems. OCC is a promising candidate for the Internet of Vehicles (IoV), and it uses LEDs as the transmitter and cameras as the receiver. However, the mobility of vehicles has a significant detrimental impact on the OCC system's performance in vehicular environments. In this paper, a traffic light that uses multiple-input multiple-output (MIMO) technology serves as the transmitter, and the receiver is a camera mounted on a moving vehicle. The impact of vehicle mobility on the vehicular MIMO-OCC system in the transportation environment is then examined using precise point spread function (PSF) analysis. The experimental results are used to evaluate the proposed PSF. A good agreement between the laboratory's recorded videos and this PSF model's simulations is observed. Moreover, the signal-to-noise ratio (SNR) and signal-to-interference-plus-noise ratio (SINR) values are evaluated. It is shown that they are greatly influenced by the vehicle's speed, direction of motion, and position of the camera. However, since the angular velocity in a typical transportation environment is low, it does not have a significant impact on the performance of the vehicular OCC systems.

Wireless Body Area Nanonetworks via Vascular Molecular Communication.

Advancements in biotechnology and molecular communication have enabled the utilization of nanomachines in Wireless Body Area Networks (WBAN2) for applications such as drug delivery, cancer detection, and emergency rescue services. To study these networks effectively, it is essential to develop an ideal propagation model that includes the channel response between each pair of in-range nanomachines and accounts for the interference received at each receiver node. In this paper, we employ an advection-diffusion equation to obtain a deterministic channel matrix through a vascular WBAN2. Additionally, the closed forms of inter-symbol interference (ISI) and co-channel interference (CCI) are derived for both full duplex (FDX) and half duplex transmission (HDX) modes. By applying these deterministic formulations, we then present the stochastic equivalents of the ideal channel model and interference to provide an innovative communication model by simultaneously incorporating CCI, ISI, and background noise. Finally, we evaluate the results with numerous experiments and use signal-to-interference-plus-noise ratio (SINR) and capacity as metrics.

Error analysis of the PacBio sequencing CCS reads.

Third generation sequencing technologies such as Pacific Biosciences and Oxford Nanopore provide faster, cost-effective and simpler assembly process generating longer reads than the ones in the next generation sequencing. However, the error rates of these long reads are higher than those of the short reads, resulting in an error correcting process before the assembly such as using the Circular Consensus Sequencing (CCS) reads in PacBio sequencing machines. In this paper, we propose a probabilistic model for the error occurrence along the CCS reads. We obtain the error probability of any arbitrary nucleotide as well as the base calling Phred quality score of the nucleotides along the CCS reads in terms of the number of sub-reads. Furthermore, we derive the error rate distribution of the reads in relation to the pass number. It follows the binomial distribution which can be approximated by the normal distribution for long reads. Finally, we evaluate our proposed model by comparing it with three real PacBio datasets, namely, Lambda, and E. coli genomes, and Alzheimer's disease targeted experiment.

A Novel Electrical Model for Advection-Diffusion-Based Molecular Communication in Nanonetworks.

In this paper, we propose an end-to-end electrical model to characterize the communication between two nanomachines via advection-diffusion motion along the conventional pipe medium. For this modeling, we consider three modules consisting of transmitter, advection-diffusion propagation and receiver. The modulation scheme and releasing molecules through the conventional pipe medium from the transmitter nanomachine is represented in the transmitter module. The advection-diffusion propagation of molecules along the flow-induced path is shown in advection-diffusion propagation module, and the demodulation scheme of bounded particles at the receiver nanomachine is characterized in the receiver module. Our objective is to find an electrical model of each module under the zero initial condition which enables us to represent the electrical circuit related to each module. The transmitter and the signal propagation models are built on the basis of the molecular advection-diffusion physics, whereas the receiver model is interpreted by stemming from the theory of the ligand-receptor binding chemical process. In addition, we employ the transfer function of modules to derive the normalized gain and the delay of each module. Supported by numerical results, we analyze the effect of physical parameters of the pipe medium on the total normalized gain and delay of molecular communications.

Compressive-sampling-based positioning in wireless body area networks.

Recent achievements in wireless technologies have opened up enormous opportunities for the implementation of ubiquitous health care systems in providing rich contextual information and warning mechanisms against abnormal conditions. This helps with the automatic and remote monitoring/tracking of patients in hospitals and facilitates and with the supervision of fragile, elderly people in their own domestic environment through automatic systems to handle the remote drug delivery. This paper presents a new modeling and analysis framework for the multipatient positioning in a wireless body area network (WBAN) which exploits the spatial sparsity of patients and a sparse fast Fourier transform (FFT)-based feature extraction mechanism for monitoring of patients and for reporting the movement tracking to a central database server containing patient vital information. The main goal of this paper is to achieve a high degree of accuracy and resolution in the patient localization with less computational complexity in the implementation using the compressive sensing theory. We represent the patients' positions as a sparse vector obtained by the discrete segmentation of the patient movement space in a circular grid. To estimate this vector, a compressive-sampling-based two-level FFT (CS-2FFT) feature vector is synthesized for each received signal from the biosensors embedded on the patient's body at each grid point. This feature extraction process benefits in the combination of both short-time and long-time properties of the received signals. The robustness of the proposed CS-2FFT-based algorithm in terms of the average positioning error is numerically evaluated using the realistic parameters in the IEEE 802.15.6-WBAN standard in the presence of additive white Gaussian noise. Due to the circular grid pattern and the CS-2FFT feature extraction method, the proposed scheme represents a significant reduction in the computational complexity, while improving the level of the resolution and the localization accuracy when compared to some classical CS-based positioning algorithms.

On the relationship between multicast/broadcast throughput and resource utilizations in wireless mesh networks.

This paper deals with the problem of multicast/broadcast throughput in multi-channel multi-radio wireless mesh networks that suffer from the resource constraints. We provide a formulation to capture the utilization of the network resources and derive analytical relationships for the network's throughput in terms of the node utilization, the channel utilization, and the number of transmissions. Our model relies on the on-demand quality of service multicast/broadcast sessions, where each admitted session creates a unique tree with a specific bandwidth. As an advantage, the derived relationships are independent of the type of tree built for each session and can be used for different protocols. The proposed formulation considers the channel assignment strategy and reflects both the wireless broadcast advantage and the interference constraint. We also offer a comprehensive discussion to evaluate the effects of load-balancing and number of transmissions on the network's throughput. Numerical results confirm the accuracy of the presented analysis.

Energy efficiency and reliability in wireless biomedical implant systems.

The use of wireless implant technology requires correct delivery of the vital physiological signs of the patient along with the energy management in power-constrained devices. Toward these goals, we present an augmentation protocol for the physical layer of the medical implant communications service (MICS) with focus on the energy efficiency of deployed devices over the MICS frequency band. The present protocol uses the rateless code with the frequency-shift keying (FSK) modulation scheme to overcome the reliability and power cost concerns in tiny implantable sensors due to the considerable attenuation of propagated signals across the human body. In addition, the protocol allows a fast start-up time for the transceiver circuitry. The main advantage of using rateless codes is to provide an inherent adaptive duty cycling for power management, due to the flexibility of the rateless code rate. Analytical results demonstrate that an 80% energy saving is achievable with the proposed protocol when compared to the IEEE 802.15.4 physical layer standard with the same structure used for wireless sensor networks. Numerical results show that the optimized rateless coded FSK is more energy efficient than that of the uncoded FSK scheme for deep tissue (e.g., digestive endoscopy) applications, where the optimization is performed over modulation and coding parameters.