Adaptive fusion of correlated local decisions

An adaptive fusion algorithm is proposed for an environment where the observations and local decisions are dependent from one sensor to another. An optimal decision rule, based on the maximum posterior probability (MAP) detection criterion for such an environment, is derived and compared to the adaptive approach. In the algorithm, the log-likelihood ratio function can be expressed as a linear combination of ratios of conditional probabilities and local decisions. The estimations of the conditional probabilities are adapted by reinforcement learning. The error probability at steady state is analyzed theoretically and, in some cases, found to be equal to the error probability obtained by the optimal fusion rule. The effect of the number of sensors and correlation coefficients on error probability in Gaussian noise is also investigated. Simulation results that conform to the theoretical analysis are also presented     

Mobility support for IP over wireless ATM

A wireless ATM system consists of a core network infrastructure that provides mobility support to end terminals and a wireless access link. This article outlines two schemes for supporting mobility of IP terminals in this network. In the first scheme, location management and handoff support is integrated within the ATM signaling and control framework (“mobile ATM”), and mobility is transparently supported at the IP layer by mobile ATM underneath. In the second approach, the IP protocol stack is directly executed on ATM switches (without an intermediate ATM signaling stack) using an IP switching technique called IPSOFACTO (IP Switching Over Fast ATM Cell Transport), and terminal mobility is supported via mobile IP     

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.     

Bandwidth allocation for multiservice access on EPONs

Ethernet passive optical networks are a low-cost high-speed solution to the bottleneck problem of the broadband access network. A major characteristic of EPONs is the shared upstream channel among end users, mandating efficient medium access control to facilitate statistical multiplexing and provision multiple services for different types of traffic. This article addresses and provides an overview of the upstream bandwidth allocation issue for multiservice access provisioning over EPONs, and proposes an algorithm for dynamic bandwidth allocation with service differentiation. Based on the multipoint control protocol (MPCP) and bursty traffic prediction, our algorithm enhances QoS metrics such as average frame delay, average queue length, and frame loss probability over other existing protocols     

A New Architecture for Nonblocking Optical Switching Networks

With the current technology, all-optical networks require nonblocking switch architectures for building optical cross-connects. The crossbar switch has been widely used for building an optical cross-connect due to its simple routing algorithm and short path setup time. It is known that the crossbar suffers from huge signal loss and crosstalk. The Clos network uses a crossbar as building block and reduces switch complexity, but it does not significantly reduce signal loss and crosstalk. Although the Spanke's network eliminates the crosstalk problem, it increases the number of switching elements required considerably (to 2N ² - 2N). In this paper, we propose a new architecture for building nonblocking optical switching networks that has much lower signal loss and crosstalk than the crossbar without increasing switch complexity. Using this architecture we can build non-squared nonblocking networks that can be used as building block for the Clos network. The resulting Clos network will then have not only lower signal loss and crosstalk but also a lower switch complexity.     

A modified rain attenuation prediction model for tropical V‐band satellite earth link

Radio wave propagation plays a very important part in the design and eventually dictates performance of space communication systems. Over time, the requirements of satellite communication have grown extensively where higher capacity communications systems are needed. Escalating demands of microwave and millimetre wave communications are causing frequency spectrum congestion. Hence, existing and future satellite system operators are planning to employ frequency bands well above 10 GHz. The challenge in operating at such high frequencies for communication purposes is that there exists stronger electromagnetic interaction between the radio signals and atmospheric hydrometeors. Such instances will degrade the performance of such high frequency satellite communication systems. The development of a revised model for a better‐improved rain fade prediction of signal propagations in tropical region is considered very important. Researchers and engineers can employ the model to accurately plan the future high frequencies satellite services. Copyright © 2014 John Wiley & Sons, Ltd.     

Effects of feeding an aquatic weed Lemna trisulaca as partial replacement of fish meal on the performance of growing ducklings

Growing ducklings were fed diets containing an aquatic weed Lemna trisulaca meal (LTM) replacing, on a protein basis, either 40, 60 or 80 g kg^?1 of the fish meal (FM) from a control diet which contained 120 g FM kg^?1. Partial replacement of FM (40 and 60 g kg^?1 of the FM) by LTM on a protein basis showed good growth and low food consumption but food conversion efficiency was found to be comparable. It was concluded that LTM could be considered as a protein feed supplement for growing ducklings and also as a part replacement of animal protein (FM) in the nutrition of growing ducklings without deleterious effect on performance.     

A back-projection autofocus algorithm based on flight trajectory optimization for synthetic aperture radar imaging

In this paper, a new autofocus algorithm is presented for back-projection (BP) image formation of synthetic aperture radar (SAR) imaging. The approach is based on maximizing a cost function obtained by prominent points in different sub-apertures of constructed SAR image by varying the flight trajectory parameters. While image-quality-based autofocus approach together with BP algorithm can be computationally intensive, we use approximations that allow optimal corrections to be derived. The approach is applicable for focusing different signal processing algorithms by obtaining modified flight trajectory parameters. Different examples demonstrate the effectiveness of the new autofocus approach applied to the frequency modulated continuous wave mode SAR dataset.