Hadeel Elayan

In vivo wireless body communications: State-of-the-art and future directions

The emerging in vivo communication and networking system is a prospective component in advancing health care delivery and empowering the development of new applications and services. In vivo communications construct wirelessly networked cyber-physical systems of embedded devices to allow rapid, correct and cost-effective responses under various conditions. This paper surveys the existing research which investigates the state of art of the in vivo communication. It also focuses on characterizing and modeling the in vivo wireless channel and contrasting this channel with the other familiar channels. MIMO in vivo is as well regarded in this overview since it significantly enhances the performance gain and data rates. Furthermore, this paper addresses current challenges and future research areas for in vivo communications.

Sparse NLMS adaptive algorithms for multipath wireless channel estimation

Embedding a sparse penalty in conventional Least Mean Square (LMS) adaptive algorithms is an established strategy to enhance the performance and robustness against noise in the estimation of sparse plants, such as wireless mul-tipath channels. In this paper we review the most prominent NLMS-based algorithms with ℓp-norm constraint, discussing the underlying mechanisms that lead to improvement gains in sparse scenarios. Simulation results validate the analysis and comparative discussion. Given that adaptive algorithms operating in time domain deteriorate with correlated signals, we propose hereby a novel frequency-domain (FD) ℓp-NLMS that performs in such situations. Simulation results indicate that the proposed method outperforms its time-domain counterparts not only in convergence rate but more importantly in residual misalignment. This important result has not been echoed so far.

On channel characterization in human body communication for medical monitoring systems

The emerging intra-body communication (IBC) and networking system is a prospective component in advancing healthcare delivery and empowering the development of future medical monitoring systems. Using the human body as a transmission medium unfastened the research perspective towards Human Body Communication which has been introduced by the IEEE as a third physical layer. Generally, there are two approaches of HBC, namely, capacitive coupling and galvanic coupling. In this paper, the concept of galvanic coupling is adopted as a method for wireless transmission inside the human body. Then, the channel characteristics of the HBC based on the IEEE 802.15.6 standards are addressed where we focus on both the frequency response and the noise characterization. The results obtained are necessary for developing a realistic human-body channel model capable of estimating the performances of wearable systems using HBC technology.

Photothermal Modeling and Analysis of Intrabody Terahertz Nanoscale Communication

Wireless communication among implanted nano-biosensors will enable transformative smart health monitoring and diagnosis systems. The state of the art of nano-electronics and nano-photonics points to the terahertz (THz) band (0.1–10 THz) and optical frequency bands (infrared, 30–400 THz, and visible, 400–750 THz) as the frequency range for communication among nano-biosensors. Recently, several propagation models have been developed to study and assess the feasibility of intra-body electromagnetic (EM) nanoscale communication. These works have been mainly focused on understanding the propagation of EM signals through biological media, but do not capture the resulting photothermal effects and their impact both on the communication as well as on the body itself. In this paper, a novel thermal noise model for intra-body communication based on the diffusive heat flow theory is developed. In particular, an analytical framework is presented to illustrate how molecules in the human body absorb energy from EM fields and subsequently release this energy as heat to their immediate surroundings. As a result, a change in temperature is witnessed from which the molecular absorption noise can be computed. Such analysis has a dual benefit from a health as well as a communication perspective. For the medical community, the presented methodology allows the quantization of the temperature increase resulting from THz frequency absorption. For communication purposes, the complete understanding of the intra-body medium opens the door toward developing modulations suited for the capabilities of nano-machines and tailored to the peculiarities of the THz band channel as well as the optical window.

In-vivo terahertz EM channel characterization for nano-communications in WBANs

This paper presents an analytical study concerning nanoscale networks operating at the Terahertz frequency. The paper investigates the path loss and absorption coefficients of a simplified human model within wireless body area networks (WBANs). Numerical results indicated that the path loss rises with increased distance and frequency. It was found that the path loss difference across the THz band ranging between 0.1 THz and 10 THz at a distance of 1mm is around 40 dB, for the various body parts. This is an acceptable value especially in the context of in-vivo nano-communication. At 1 THz, the path loss between 1 mm and 1.5 mm ranges betweenb 36 dB and 40 dB, for the different body parts. The results obtained in this paper verify that electromagnetic (EM) communication is a valid analytical assumption for modeling in-vivo THz nano-communication. This is mainly due to the fact that for distances in the order of millimeters, the path loss at THz is not significantly high.

Leveraging the ℓ1-LS criterion for OFDM sparse wireless channel estimation

In order to exploit the inherent sparsity of an OFDM multipath wireless channel, this paper presents a novel estimation technique based on the ℓ1-LS criterion that relies on the selection of the optimal regularization parameter. This term is proven in the paper to be intimately related to the Signal to Noise Ratio (SNR) and Sparsity Degree (ρ) of the channel. Therefore, in order to take full advantage of the ℓ1-LS framework, an ad-hoc technique for estimating blindly the SNR and ρ of the problem is also introduced. The performance of the novel algorithm is compared to a number of reference techniques. Two standard measures, namely the Mean Square Error (MSE) of the estimated channel and the Symbol Error Rate (SER) of the OFDM system validate the robustness of the proposed algorithm. Indeed, this novel technique achieves better estimation along with better spectrum efficiency.

On graphene-based THz plasmonic nano-antennas

Graphene-enabled wireless communications create an innovative archetype proposed to implement wireless communications at the nanoscale. Indeed, graphene-based nano-antennas, or graphennas, are few micrometers in size. Such antennas have been predicted to radiate electromagnetic waves at the Terahertz band. Hence, they do not only provide better integrability for future miniaturized wireless systems but also represent an enabling technology for applications such as wireless nano-sensor networks and Internet-of-Things (IoT). This paper surveys the existing research which investigates the state-of-art of graphene-based plasmonic nano-antennas. The paper focuses on the propagation of Surface Plasmon Polariton (SPP) waves since they set up the main characteristics of these antennas. Various fundamental properties of plasmonic antennas are also discussed providing useful guidelines for future designers of these antennas. The paper also addresses the future research areas of graphene-based Terahertz nano-antennas.

Enhanced WSN localization of moving nodes using a robust hybrid TDOA-PF approach

This paper presents a technique for enhanced localization of moving nodes in Wireless Sensor Networks (WSNs). The proposed technique is based on the use of Time Difference of Arrival (TDOA) along with Particle Filter (PF) method which is demonstrated to be capable of accurate detection since each particle in the PF represents a state which translates into the moving node location in the case of TDOA localization. The proposed technique outperforms other filtering methods, such as the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF), which are restricted to Gaussian distribution of the moving nodes. Numerical simulations verify the accuracy and robustness of the proposed TDOA-PF localization technique.

A survey of in vivo WBAN communications and networking: Research issues and challenges

The emerging in vivo communication and networking system is a prospective component in advancing health care delivery and empowering the development of new applications and services. In vivo communications construct wirelessly networked cyber-physical systems of embedded devices to allow rapid, correct and cost-effective responses under various conditions. This paper surveys the existing research which investigates the state of art of the in vivo communication. It also focuses on characterizing and modeling the in vivo wireless channel and contrasting this channel with the other familiar channels. MIMO in vivo is as well regarded in this overview since it significantly enhances the performance gain and data rates. Furthermore, this paper addresses current challenges and future research areas for in vivo communications.

Stochastic noise model for intra-body terahertz nanoscale communication

The development of miniature plasmonic signal sources, antennas and detectors are paving the way towards advanced healthcare networks, namely, in-vivo Wireless Nanosensor Networks (iWNSNs). These networks are expected to enable a plethora of applications ranging from intra-body health-monitoring to drug-delivery systems. The state of the art of nanoelectronics, nanopho-tonics, and nanoplasmonics points to the Terahertz (THz) band (0.1-10 THz) as the frequency range for communication among nano-biosensors. Several propagation models have been recently developed to study and assess the feasibility of intra-body electromagnetic (EM) nanoscale communication. These works have been mainly focused on understanding the propagation of EM signals through biological media, but do not present extensive formulation which quantify the noise contributions in the intra-body channel. In this paper, a stochastic noise model for iWNSNs is presented upon analyzing the individual noise constituents that affect intra-body systems operating in the THz frequency band. The identified noise sources include Johnson-Nyquist noise, Black-body noise as well as Doppler-shift-induced noise. The probability distribution of each noise component is derived and a comprehensive noise framework is established which allows the total noise power-spectral density of the iWNSN in the THz frequency band to be computed. The proposed analytical model is fundamental as noise is an important metric which affects both the intra-body channel capacity and data rate in the THz band.