Ahmed O. Abdul Salam

Energy saving in tunnels lighting using shading structures

This paper introduces a constructive proposal to save energy in tunnels lighting using shading structures. These structures aim at the reduction of sunlight levels at tunnels portals. Accordingly, such sunlight reduction will reduce the artificial lighting requirements at the entrances and exits and hence provide further energy saving without additional smart intervention using control methods. The aesthetic appearance of shading structures needs to be considered without sacrificing the traffic safety requirements. The energy saving in addition to initial costs reduction render shading structures as a good candidate for permanent installations with low maintenance requirements compared to conventional lighting installations. Our proposal could be applied equally at the design stage of new tunnels and underpasses, or as a retrofit for existing roads structures to turn them into green energy facilities. Renderings and payback calculations predict flourishing future for the proposed tunnel lighting energy conservation by shade structures. This study shows that up to 50% saving in the lighting electrical load can be achieved.

Automatic Modulation Classification in Cognitive Radio Using Multiple Antennas and Maximum-Likelihood Techniques

The automatic modulation classification (AMC) is linked to the accurate identification of a received signal modulation. The AMC represents an important part of cognitive radio (CR) systems recently envisioned to be an appropriate platform to adjust against changing work conditions. The two main distinguished streams of AMC are either by using the likelihood based (LB) statistical tests or featured based (FB) recognitions. The LB is viewed to be optimum providing that all statistical signal descriptions are available to a receiver, while the FB usually viewed as suboptimal. In some practical situations, especially when the AMC process is carried out blindly, a signal enhancement is viewed necessary to boost the detection accuracy. The multiple-input multiple-output (MIMO) antennas configuration is widely accepted as key enhancer to signal and system performance. This paper is intended to explore opportunities of the AMC detection accuracy improvements using MIMO and diversity combining settings. The probability of error detection is reformulated using diagonalized MIMO channel through singular value decomposition (SVD) realization. Simulation results show that classification performance is improved by adopting multiple antennas with appropriate signal combining configuration.

A Multi-Taper Spectrum Based Estimator for Cognitive Radio Using Multiple Antennas and Space-Time Block Code Techniques

An effective approach for the design of spectrum estimation (SE) in cognitive radio systems using multi-taper method (MTM) and spatiotemporal features is presented in this study, whereas the MTM balances the bias-variance dilemma, the multiple-input–multiple-output (MIMO) and space–time block code (STBC) are customarily aimed to defeat the adverse channel effects and enhance the system capacity and performance. The singular value decomposition is exploited to determine the dominant eigenchannels in MIMO and STBC setups. The maximum-ratio combining, on the other hand, is adopted to produce higher signal-to-noise ratios usually intended for high data rates and reliability levels. The statistical analysis and modelling of the performance metrics associated with the SE based on MTM-STBC and MIMO are approached using the quadratic form approximation. Simulation exercises are employed to compare this different SE, which will be called multitaper spectrum estimation (MTSE), against other typical methods such as the periodogram without tapering options. The results exhibit performance gains due to the merger of MTSE and STBC technologies over MIMO and periodogram SE (PSE) algorithms. Further computational analysis shows that the MTSE–STBC has no extra burdens compared with its PSE counterpart.

Establishment of industrial control laboratory for undergraduate and postgraduate curricula

This paper provides an active proposal for the establishment of an industrial control laboratory at an academic institution level. The laboratory is mainly intended for teaching undergraduate and postgraduate students who are majoring in the areas of industrial control and mechatronics programs, respectively. Further services this laboratory could provide are to conduct seminars and workshops for field engineers from local and regional industrial communities. The total costs were suitable since the adopted setups are modular and can be expanded to cover wider range of topics upon the arrival of new devices and equipments. This laboratory was offered to students and their number has been increased ever since with satisfaction.

Adaptive tracking of maneuvering targets using two-stage Kalman filter

This paper presents a novel approach to the adaptive tracking of maneuvering targets using Kalman filter. The adaptation technique is achieved by constructing a pursuing system of two stages. The first stage comprises a vector Kalman filter of three states undergoes some biasing drift or mismodeling during a target evasive maneuver. While the second stage consists of a scalar Kalman filter basically developed to estimate the biasing term and then feeds back correction factors to the main processor to enhance its performance. This innovative adaptation technique will be called as bias removal (BR). Comparison and simulation exercises are presented against the interacting multiple model (IMM) adaptation technique showed that the target state estimates is improved by employing this BR adaptation policy.

Multi-taper and MIMO techniques for spectrum sensing in cognitive radio

Frequency spectrum sensing is a key and challenging task of modern wireless communication systems. Cognitive radio (CR) has recently been envisioned as an intelligent platform capable of achieving better spectrum sensing and, hence, promotes efficient spectrum utilization. The multi-taper method (MTM) is a good candidate to achieve such a requirement. This paper focuses on the application of MTM spectrum sensing using multiple antenna arrangement environments. Maximal ratio combining (MRC) is employed as near to optimum candidate for diversity combining technique to process the spectrum estimate at the output of multiple receive antennas. Analysis and results show that such an arrangement provides better performance compared to the single antenna option under additive white Gaussian noise (AWGN) conditions. Moreover, a proposal for a new and simple approach to derive the decision statistical measures reveals that the probability density functions (PDFs) share common factors in both time and frequency domains. Furthermore, transmit antenna diversity also assumes direct positive influence on the spectrum sensing performance.

A unified practical approach to modulation classification in cognitive radio using likelihood-based techniques

The automatic classification of digital modulated signals has been subject to extensive studies over the last decade, with numerous scholarly articles and research studies published. This paper provides an insightful guidance and discussion on the most practical approaches of automatic modulation classification (AMC) in cognitive radio (CR) using likelihood based (LB) statistical tests. It also suggests a novel idea of storing the known constellation sets on the receiver side using a look-up table (LUT) to detect the transmitted replica. Relevant performance measures with simulated comparisons in flat fading additive white Gaussian noise (AWGN) channels are examined. Namely, the average likelihood ratio test (ALRT), generalized LRT (GLRT) and hybrid LRT (HLRT) are particularly illustrated using linearly phase-modulated signals such as M-ary phase shift keying (MPSK) and quadrature amplitude modulation (MQAM). When the unknown signal constellation is estimated using the maximum likelihood (ML) method, results indicate that the HLRT performs well and near optimal in most situations without extra computational burden.

An overview on non-parametric spectrum sensing in cognitive radio

The scarcity of frequency spectrum used for wireless communication systems has attracted a considerable amount of attention in recent years. The cognitive radio (CR) terminology has been widely accepted as a smart platform mainly aimed at the efficient interrogation and utilization of permitted spectrum. Non-parametric spectrum sensing, or estimation, represents one of the prominent tools that can be proposed when CR works under an undetermined environment. As such, the periodogram, filter bank, and multi-taper methods are well considered in many studies without relying on the transmission channels characteristics. A unified approach to all these non-parametric spectrum sensing techniques is presented in this paper with analytical and performance comparison using simulation methods. Results show that the multi-taper method outperforms the others.

A general perspective on software-hardware defined cognitive radio based on emergency ad-hoc network topology

This paper presents a different perspective on the collective concept of software-hardware defined radio (SHDR) in cognitive radio (CR) networks. The SHDR is proposed considering the multiple hardware functionalities conceived by software defined radio, which generally reflects on the adaptable recognition of network services and operational conditions. An ad-hoc network scheme is envisaged as an alternative to a conventional cellular network to accommodate for emergency situations. The connection to such emergency backup network could be established on CR engines built in normal or dedicated smart phone handsets.