EETP-MAC: energy efficient traffic prioritization for medium access control in wireless body area networks

Wireless body area network (WBAN) has witnessed significant attentions in the healthcare domain using biomedical sensor-based monitoring of heterogeneous nature of vital signs of a patient’s body. The design of frequency band, MAC superframe structure, and slots allocation to the heterogeneous nature of the patient’s packets have become the challenging problems in WBAN due to the diverse QoS requirements. In this context, this paper proposes an Energy Efficient Traffic Prioritization for Medium Access Control (EETP-MAC) protocol, which provides sufficient slots with higher bandwidth and guard bands to avoid channels interference causing longer delay. Specifically, the design of EETP-MAC is broadly divided in to four folds. Firstly, patient data traffic prioritization is presented with broad categorization including Non-Constrained Data (NCD), Delay-Constrained Data (DCD), Reliability-Constrained Data (RCD) and Critical Data (CD). Secondly, a modified superframe structure design is proposed for effectively handling the traffic prioritization. Thirdly, threshold based slot allocation technique is developed to reduce contention by effectively quantifying criticality on patient data. Forth, an energy efficient frame design is presented focusing on beacon interval, superframe duration, and packet size and inactive period. Simulations are performed to comparatively evaluate the performance of the proposed EETP-MAC with the state-of-the-art MAC protocols. The comparative evaluation attests the benefit of EETP-MAC in terms of efficient slot allocation resulting in lower delay and energy consumption.

     

A computationally efficient selected mapping technique for reducing PAPR of OFDM

In orthogonal frequency division multiplexing (OFDM) system, high value of peak-to-average power ratio (PAPR) is an operational problem that may cause non-linear distortion resulting in high bit error rate. Selected mapping (SLM) is a well known technique that shows good PAPR reduction capability but inflicts added computational overhead. In this paper, using Riemann sequence based SLM method, we applied reverse searching technique to find out low PAPR yielding phase sequences with significant reduction in computational complexity. Additionally, we explored side-information free transmission that achieves higher throughput but sacrifices PAPR reduction. Finally, to overcome this loss in PAPR reduction, we proposed application of Square-rooting companding technique over the output OFDM transmitted signal. Simulation results show that the proposed method is able to compensate the sacrifice in PAPR and achieved PAPR reduction of 8.9 dB with very low computational overhead.     

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.     

Software‐defined networking approach for enhanced evolved packet core network

The evolved packet core (EPC) network is the mobile network standardized by the 3rd Generation Partnership Project and represents the recent evolution of mobile networks providing high‐speed data rates and on‐demand connectivity services. Software‐defined networking (SDN) is recently gaining momentum in network research as a new generation networking technique. An SDN‐based EPC is expected to introduce gains to the EPC control plane architecture in terms of simplified, and perhaps even software‐based, vendor independent infrastructure nodes. In this paper, we propose a novel SDN‐based EPC architecture along with the protocol‐level detailed implementation and provide a mechanism for identifying information fields exchanged between SDN‐EPC entities that maintains correct functionality with minimal impact on the conventional design. Furthermore, we present the first comprehensive network performance evaluation for the SDN‐based EPC versus the conventional EPC and provide a comparative analysis of 2 networks performances identifying potential bottlenecks and performance issues. The evaluation focuses on 2 network control operations, namely, the S1‐handover and registration operations, taking into account several factors, and assessing performance metrics such as end‐to‐end delay (E2ED) for completion of the respective control operation, and EPC nodes utilization figures.     

Wireless Brain Computer Interface for Smart Home and Medical System

Wireless Personal Communications - The number of aged and disabled people has been increasing worldwide. To look after these people is a big challenge in this era. However, scientists overcome the...     

Proposal for st-Routing Protocol

A routing protocol chooses one of the several paths (routes) from a source node to a destination node in the computer network, to send a packet of information. In this paper, we propose a new routing protocol, which we call st-routing protocol, based on st-numbering of a graph. The protocol fits well in noisy environments where robustness of routing using alternative paths is a major issue. The proposed routing protocol provides a systematic way to retry alternative paths without generating any duplicate packets. The protocol works for only those networks that can be represented by biconnected graphs.     

Estimation of solar radiation components incident on Helwan site using neural networks

Field testing carried out for solar energy applications is costly, time consuming and depends heavily on prevailing weather conditions. Adequate security and weather protection must be provided at the test site. Measurements may also suffer from delays that can be caused by system failures and bad weather. To overcome these problems the need for accurate model becomes evermore important. To achieve such prediction task, an artificial neural network, ANN, model is regarded as a cost-effective technique superior to traditional statistical methods. In this paper, Levenberg optimization function is adopted to predict insolation data in different spectral bands for Helwan (Egypt) monitoring station. The predicted values were then compared with the actual values and presented in terms of usual statistics. The results hint that, the ANN model predicted infrared, ultraviolet, and global insolation with a good accuracy of approximately 95%, 93% and 96%, respectively. In addition, ANN model was tested to predict the same components for Aswan over an 11 month period. The predicted values of the ANN model compared to the actual values for Aswan produced an accuracy of 95%, 91% and 92%, respectively. Data for Aswan were not included as a part of ANN training set. Hence, these results demonstrate the generalization capability of this approach over unseen data and its ability to produce accurate estimates.     

IGCC for PAPR Reduction in OFDM Systems Over the Nonlinearity of SSPA and Wireless Fading Channels

High peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems seriously impacts power efficiency in radio frequency section due to the nonlinearity of high-power amplifiers. In this article, an improved gamma correction companding (IGCC) is proposed for PAPR reduction and investigated under multipath fading channels. It is shown that the proposed IGCC provides a significant PAPR reduction while improving power spectral levels and error performances when compared with the previous gamma correction companding. IGCC outperforms existing companding methods when a nonlinear solid-state power amplifier (SSPA) is considered. Additionally, with the introduction of \(\alpha , \beta , \gamma \), and \(\varDelta \) parameters, the improved companding can offer more flexibility in the PAPR reduction and therefore achieves a better trade-off among the PAPR gain, bit error rate (BER), and power spectral density (PSD) performance. Moreover, IGCC improves the BER and PSD performances by minimizing the nonlinear companding distortion. Further, IGCC improves signal-to-noise ratio (SNR) degradation (\(\varDelta _{\mathrm{SNR}}\)) and total degradation performances by 12.2 and 12.8 dB, respectively, considering an SSPA with input power back-off of 3.0 dB. Computer simulation reveals that the performances of IGCC are independent of the modulation schemes and works with arbitrary number of subcarriers (N), while it does not increase computational complexity when compared with the existing companding schemes used for PAPR reduction in OFDM systems.     

Side-Channel Information Characterisation Based on Cascade-Forward Back-Propagation Neural Network

Traditional cryptanalysis assumes that an adversary only has access to input and output pairs, but has no knowledge about internal states of the device. However, the advent of side-channel analysis showed that a cryptographic device can leak critical information. In this circumstance, Machine learning is known as a powerful and promising method of analysing of side-channel information. In this paper, an experimental investigation on a FPGA implementation of elliptic curve cryptography (ECC) was conducted to explore the efficiency of side-channel information characterisation based on machine learning techniques. In this work, machine learning is used in terms of principal component analysis (PCA) for the preprocessing stage and a Cascade-Forward Back-Propagation Neural Network (CFBP) as a multi-class classifier. The experimental results show that CFBP can be a promising approach in characterisation of side-channel information.     

Design and performance evaluation of amplifier modules in stackable ROADMs for low-cost CWDM access networks

Coarse wavelength division multiplexing (CWDM) network has proven to be promising lower cost network architecture for a significant cost advantage over dense wavelength division multiplexing due to the lower cost of lasers and the filters used in CWDM modules. A compatible amplifier module having bidirectional amplification capability was deployed for introducing inside stackable reconfigurable optical add/drop multiplexers in realizing large-scale CWDM networks. The amplifier module for use in the bidirectional IP transmission confirmed that the insertion losses of the nodes and the losses of the fibers connecting the nodes can be compensated effectively, allowing the network administrator to increase the number of nodes and fiber length of the network. However, the noise generated from the amplification due to amplified spontaneous emission must be considered in network design issues. In this paper, optical power penalties due to the bidirectional amplification were estimated by conducting experimentation on minimum detectable power of optical transceivers. After analyzing the power penalty issue, an IP-over-CWDM ring network was implemented and the performance of network was evaluated by monitoring the power and packet transmissions before and after the amplifier module was turned on.