Habib F. Rashvand

Energy and cost impacts of relay and femtocell deployments in long-term-evolution advanced

In long-term-evolution-advanced (LTE-advanced), heterogeneous deployments of relays, femtocells and conventional macrocells are expected to provide coverage extension and throughput enhancement, while significantly lowering the energy consumption and total-cost-of-ownership (TCO) in cellular networks. This study presents a methodology for estimating the total energy consumption, taking into account the total operational power and embodied energy, and TCO of wireless cellular networks, and in particular provides a means to compare homogeneous and heterogeneous network (HetNets) deployments. The authors introduce realistic energy models and energy metrics based on information available from mobile-network operators (MNOs) and base stations manufacturers. Additionally, up-to-date operational and capital expenditure (OPEX and CAPEX) models are used to calculate TCO of candidate networks. The authors evaluate two scenarios for HetNets, namely a joint macro-relay network and a joint macro–femtocell network, with different relay and femtocell deployments densities. The results obtained show that compared to macro-centric networks, joint macro-relay networks are both energy and cost efficient, whereas joint macro–femtocell networks reduce the networks TCO at the expense of increased energy-consumption. Finally, it is observed that energy and cost gains are highly sensitive to the OPEX model adopted.

Robust energy detection in cognitive radio

The success of advanced dynamic utilisation of the scarce spectrum in cognitive radio depends upon reliable primary signal detection where accurate noise power estimation plays a critical role. However, in practical scenarios, the noise power cannot be accurately estimated, which significantly degrades the performance of primary signal detection. To avoid inaccurate noise power estimation and associated accumulated problems. A novel two-stage Bayesian estimation-based energy detection algorithm is introduced here. This algorithm, as supported by simulation results, shows two main features: (a) a superior performance of 1 dB compared with previous methods; (b) the consistency of the algorithm has been proved indicating that 100 correct primary user signal detection can be approached as the number of samples tends to infinity.

Wireless sensor systems for space and extreme environments : a review

Using wireless sensor network (WSN) for building new sensing and actuating applications in space and extreme environments (SEEs) can fuel a new application paradigm if it can be adopted into a new strategy. This complementary contribution from the Guest Editors carries an important message of breaking away from conventional WSN research and developments and adopting a heterogeneous agile unconventional wireless sensing (UWS) approach deployment. For this, we urge the use of lightweight WSN known as wireless sensor systems (WSS) to develop optimized solutions for SEE. This paper also discusses some critical technologies of WSS-SEE and includes three key aspects of a new approach to examine: 1) the characterizes of SEE; 2) potential applications of UWS; and 3) heterogeneously nature of the applications. A further clarification for deployment of UWS is demonstrated using a table with six groups of typical application areas from the recent publications media.

ADCA: Adaptive Duty Cycle Algorithm for Energy Efficient IEEE 802.15.4 Beacon-Enabled Wireless Sensor Networks

Using of wireless sensor networks in extreme and inaccessible environments usually has energy issues of some kind. The IEEE 802.15.4 is designed in general to fulfill this requirement of low data rate ad hoc networks, i.e., a low complex system with ultralow-power consumption. Similar to all IEEE standards, however, IEEE 802.15.4 comes with many flexible variables for optimized local solution such that its beacon-enabled duty cycle mode power management mechanism. Here, we propose a novel adaptive duty cycle algorithm making maximum use of network traffic for automatically adjusting the duty cycle for minimum energy. The system simulation results show superiority of the proposed algorithm for reducing the energy consumption and increasing the throughput for comparative techniques in the literature.

Linear Feature Detection in Polarimetric SAR Images

Recently, the use of linear features for processing remote-sensing images has shown its importance in applications. Unfortunately, traditional linear feature detection methods rely heavily on the images local information which makes them vulnerable to the presence of noise in the image. This problem becomes particularly difficult for synthetic aperture radar (SAR) image applications where SAR images are corrupted by speckle noise. In order to overcome this problem, we propose a novel method that processes the polarimetric synthetic aperture radar (Pol-SAR) images by combining the multiscale image analysis with polarimetric information in a new fashion. A two-scale approach is adopted here. On a coarse level, the coarse regions of the linear features are extracted by a curvelet transform from a speckle noise reduced image obtained by the polarimetric whitening filter. On a fine level, we develop a fuzzy polarimetric detector to accurately locate the linear features inside the regions. The effectiveness of the proposed method is demonstrated using simulated Pol-SAR data acquired from both EMISAR and Convair-580 systems.

Efficient sampling and compressive sensing for urban monitoring vehicular sensor networks

Vehicular sensor network (VSN) using vehicle-based sensors is an emerging technology that can provide an inexpensive solution for surveillance and urban monitoring applications. For the constantly moving vehicles, resulting in unpredictable network topology, data transmission in VSN is vulnerable to packet losses, thus deteriorating the surveillance quality. To resolve this problem, a cooperative data sampling and compression approach is proposed. Based on compressive sensing, this approach does not require inter-sensor communication and adopts sparse random projections to remove redundancy in spatially neighbouring measurements. It is experimentally shown that the proposed algorithm provides fairly accurate reconstruction of the field under surveillance, and incurs much less communication traffic load compared to conventional sampling strategies. Practical data sets, including the temperature distribution in Beijing and the global position system (GPS) tracking data of over 6000 taxis in the city, are used in our experiments to verify the reconstruction accuracy and energy efficiency of the scheme. Different vehicular mobility models are also employed to study the impact of movement behavior. Simulation results show that our proposed approach outperforms the conventional sampling and interpolation strategy, which propagates data in uncompressed format, by 5 dB in reconstruction quality and by 50% in communication complexity reduction for the same sampling rate.

Mobile-Taiwan experience in voice over IP-worldwide interoperability for microwave access trial

Considering voice as a dominant telecommunication service, the performance of Voice over IP (VoIP) plays a critical role in deployment of worldwide interoperability for microwave access (WiMAX) technology providing all-IP network services. To that effect, in this study, the authors investigate the performance of a WiMAX-based VoIP established under the mobile Taiwan (M-Taiwan) field-trial funded program. To achieve the objectives of the trial the measurement results expressed in the form of mean opinion score (MOS), packet loss, packet delay and jitters. For the worst-case scenario, the tests were conducted under a stringent condition of both communicating devices, wirelessly connected to the same WiMAX base station under a heavy background traffic and interference, were experiencing simultaneous handovers during the communication. Upon their analysis, the field measurements confirm an excellent performance when both communicating devices kept stationary and show an acceptable quality for the service when both communicating devices are on the move at a speed of 50 km/h.

Body Language and Augmented Reality Learning Environment

A recent national survey of Taiwanese students shows that their physical health condition has been worsening more than many other countries. In this study we examine use of a new learning system enhanced with augmented reality (AR) to address this growing global problem. In order to apply three different physical activities for the experiment the learners use their body language for interacting with the computer. In order to increase effectiveness of the AR system, we then combine students¡¦ academic achievement and their preferences for using the system. The experimental results from 419 students indicate much higher achievements in their academic work and gain significantly more those who come with their minds set for stronger challenging preferences in the seven subscales.

Genetic algorithm quality of service design in resilient dense wavelength division multiplexing optical networks

The important role of quality of service (QoS) in deployment of a resilient dense wavelength division multiplexing (DWDM) backbone for global networks requires critical design-phase planning optimisation. The design issues of resilient DWDM networks for bandwidth and delay sensitive applications of dedicated path protection are addressed. A genetic algorithm (GA) model has been developed to solve the routing and wavelength assignment problem using binary variable-length chromosome encoding under two different schemes of bandwidth optimisation (BOS) and delay optimisation (DOS).The performance of the new GA-based resiliency model has been evaluated for four benchmark networks: PAN EUROPEAN, COST239, NSFNET and ARPA2. Simulation results show a superior capability and efficiency for the model to solve this complex, multi-constraint and nondeterministic polynomial-hard problem for BOS and DOS. The nonlinear nature of this process reveals a significant sensitivity for optical layer network topology on the optimum-design QoS. The results also demonstrate that the PAN EUROPEAN network shows the highest flexibility for primary path design, NSFNET for the secondary path and ARPA2 comes with the lowest design flexibility for both primary and secondary paths.

ZebraBAN: a heterogeneous high-performance energy efficient wireless body sensor network

Recently, there are much research on wireless body sensor network (WBSN) as the growing demands of pervasive health and personal entertainment. Supporting high-speed data transmission becomes a challenge in development of WBSN in medical and entertainment applications. In this study, the authors present ZebraBAN, a high-speed low-power WBSN based on single-carrier ultra-wideband (SC-UWB) and IEEE 802.15.4. The heterogeneous network combines the strengths of SC-UWB and IEEE 802.15.4 technologies while offsetting their weakness. Like SC-UWB, the system achieves medium to high data rate and reduces radiation and power consumption at a low cost. Like IEEE 802.15.4, ZebraBAN achieves low data rate and low latency under low contention. In ZebraBAN, the authors introduce the idea of control plane and data plane for controlling multiple PHYs and MACs according to energy and data rate balance. Experimental results based on the prototype system are presented to evaluated the network performance. The result demonstrates that high reliability transmission for every sensor data stream within 4 m around the person, with a low-power consumption for fabricated application specific integrated circuits (ASIC) about 8.2 mW when it works on transmitting one channel video. The network has a peak capacity of 100 Mbps that could support multiple sensor nodes, including four channel video stream and multiple low-speed sensor datas.