Mohamed Abdel-Maguid

Spectral efficient compressive transmission framework for wireless communication systems

Increasing demand of high-speed data rate is leading to a challenging task to provide services to the users within exponentially growing market for wireless multimedia services. Subsequently, the available radio resources are becoming scarce because of different factors such as spectrum segmentation and dedicated frequency allocation to existing wireless standards. Exploring new techniques for enhancing the spectral efficiency in wireless communication has been an important research challenge. In this study, the enhancement of spectral efficiency of wireless communication systems is considered. A framework is proposed to implement the concept of compressive sampling (CS) for compressing the natural random signals. The performance of proposed framework is evaluated in the context of multiple input multiple output orthogonal frequency division multiplexing system. Simulation-based results show that 25% of resources can be saved by marginal trade-off with the quality of service (QoS) requirement applying CS to the natural random signals. Furthermore, it can be claimed that this QoS trade-off can be optimised with dynamic selection of random measurement matrices.

On the spatial characterization of 3-D air-to-ground radio communication channels

A three dimensional (3-D) geometric channel model is proposed for air-to-ground (A2G) communication environments. The proposed model considers air station (AS) and ground base station (BS) located at foci points of a virtual bounding ellipsoid corresponded from the delay of longest propagation path. The scattering region around the ground BS is thus designed based on this virtual bounding ellipsoid truncated by the ground plane and average rooftop level of the BSs surroundings. Closed-form expressions for joint and marginal probability density functions (PDFs) of angle of arrival (AoA) observed at both AS and BS in correspondence with both azimuth and elevation planes are derived. Impact of various physical channel parameters on the elevational and azimuthal angular dispersion is thoroughly observed; which is useful in designing advanced signal processing techniques for directional antennas employed in aeronautical communication links. To establish the models validity, the obtained analytical results are compared with simulation results. For 105 uniformly distributed scattering points, the best matching is observed between simulation and analytical results.

Universal and Dynamic Clustering Scheme for Energy Constrained Cooperative Wireless Sensor Networks

Energy conservation is considered to be one of the key design challenges within resource constrained wireless sensor networks that leads the researchers to investigate energy efficient protocols with some application specific challenges. Dynamic clustering is generally considered as one of the energy conservation techniques; but unbalanced distribution of cluster heads, highly variable number of sensor nodes in the clusters and high number of sensor nodes involved in event reporting tend to drain out the network energy quickly resulting premature decrease in network lifetime. In this paper, a dynamic and cooperative clustering and neighborhood formation scheme is proposed that is expected to evenly distribute energy demand from the cluster heads and optimize the number of sensor nodes involved in event reporting. Assuming multiple sensors will form a cluster, while responding to an event to report to the fusion center. However, all the sensor nodes are assuming to report the sensing parameters to a cluster-head; which are to be summarized and then report it to fusion center. The transmission of the same event data from multiple sensors within the cluster at different distances with single or multiple antennas to the cluster-head with similar antenna characteristics can be realized as multiple-input multiple-output (MIMO) channel set up as found in the literature. Such realization among clusters of MIMO channel and existence of a feedback channel between the clusters and fusion center is the key of the proposed framework. The dynamic behavior has been adopted within the framework with a proposed index derived from the received measure of the channel quality, which has been attained through the feedback channel from the fusion center. The dynamic property of the proposed framework makes it robust against time-varying behavior of the propagation environment. The proposed framework is independent of the nature of the sensing application, providing with universal behavior. From simulation results, it is observed that the proposed clustering scheme enhances network lifetime by 24.5% and 36% as compared to existing schemes e.g. DDEEC and EDDEEC respectively. Furthermore, it is validated by simulation results that the proposed framework provides a trade-off model between network lifetime and transmission reliability.

Angular characteristics of a unified 3-D scattering model for emerging cellular networks

A stochastic geometry-based unified three-dimensional (3-D) channel model for emerging land mobile radio cellular systems is proposed. Uniformly distributed scattering objects are assumed bounded within an ellipsoidal shaped scattering region (SR) hollowed with an elliptical-cylindric scattering free region. To ensure the degree of expected accuracy of the proposed model, the outer bounding ellipsoid and inner bounding elliptical-cylinder are designed to be tuneable as required, unlike its counterparts in the existing literature, independently along all the axes and rotatable in horizontal plane around their origin centered at the mobile station (MS). Closed-form analytical expressions for joint and marginal probability density functions (PDFs) of angle-of-arrival (AoA) in azimuth and elevation planes observed at the base station (BS) are derived. The obtained analytical results for angular statistics of the channel are presented along with a thorough analysis. Moreover, the impact of various physical model parameters on angular statistics of the channel is presented. To evaluate the robustness of the proposed generalized model and analytical method, a comparison with experimental datasets is also presented. The obtained analytical results are seen to fit a vast range of empirical datasets obtained for different outdoor propagation environments available in the literature.

Repeater for 5G wireless: A complementary contender for Spectrum Sensing intelligence

Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the fifth generation (5G) of wireless communications. In this context, this paper proposes a novel concept of an intelligent Amplify and Forward (AF) 5G repeater for enabling the densification of future cellular networks. The proposed repeater features a Spectrum Sensing (SS) intelligence capability and utilizes such intelligence in a complementary fashion in comparison to its existing counterpart (e.g., Cognitive Radio) by detecting the active channels within the assigned spectrum. This intelligence allows the proposed repeater to carry out selective amplification of the active channels in contrast to the full amplification in conventional AF repeaters. Furthermore, the performance of a Frequency Division Multiple Access (FDMA) based two hop cellular network utilizing the proposed repeater is evaluated in terms of the system throughput. Simulation results demonstrate up to 13 % increase when compared with the conventional repeaters. Moreover, the effect of SS errors on the system capacity is analyzed.

Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter.

The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper.

The development and validation of an internet-based training package for the management of perineal trauma following childbirth: MaternityPEARLS

Background Birth-related perineal trauma has a major impact on womens health. Appropriate management of perineal injuries requires clinical knowledge and skill. At present, there is no agreement as to what constitutes an effective clinical training programme, despite the presence of sufficient evidence to support standardised perineal repair techniques. To address this deficiency, we developed and validated an interactive distance learning multi-professional training package called MaternityPEARLS. Method MaternityPEARLS was developed as a comprehensive e-learning package in 2010. The main aim of the MaternityPEARLS project was to develop, refine and validate this multi-professional e-learning tool. The effect of MaternityPEARLS in improving clinical skills and knowledge was compared with two other training models; traditional training (lectures + model-based hands on training) and offline computer lab-based training. Midwives and obstetricians were recruited for each training modality from three maternity units. An analysis of covariance was done to assess the effects of clinical profession and years of experience on scoring within each group. Feedback on MaternityPEARLS was also collected from participants. The project started in January 2010 and was completed in December 2010. Results Thirty-eight participants were included in the study. Pretraining and post-training scores in each group showed considerable improvement in skill scores (p<0.001 in all groups). Mean changes were similar across all three groups for knowledge (3.24 (SD 5.38), 3.00 (SD 3.74), 3.30 (SD 3.73)) and skill (25.34 (SD 8.96), 22.82 (SD 9.24), 20.7 (SD 9.76)) in the traditional, offline computer lab-based and e-learning groups, respectively. There was no evidence of any effect of clinical experience and baseline knowledge on outcomes. Conclusions MaternityPEARLS is the first validated perineal trauma management e-learning package. It provides a level of improvement in skill and knowledge comparable to traditional methods of training. However, as an e-learning system, it has the advantage of ensuring the delivery of a standardised, continuously updated curriculum that has global accessibility.

On Lifetime Maximisation of Heterogeneous Wireless Sensor Networks with Multi-Layer Realisation

Lifetime maximisation is a key challenge in the design of resource constrained wireless sensor networks (WSNs). This leads the research communities to investigate energy conservation techniques for WSNs while maintaining the required quality of service. Dynamic clustering is considered as one of the most well established energy conservation techniques in the literature. However, uneven distribution of cluster heads within the network and variable number of sensor nodes in the clusters results inefficient energy consumption; hence minimise the network lifetime. The conventional dynamic clustering become more energy in-efficient, when there exists heterogeneity of sensing devices within a network. In other words, obtaining optimal solution with conventional single layer realisation become more computationally complex. In this paper, a dynamic clustering scheme is proposed for heterogeneous WSNs with multi-layer realisation where each layer comprise of homogeneous sensing devices. To attain energy efficiency, we are proposing intra-layer (horizontal) and inter-layer (vertical) optimisation in the search of global minima, which requires reduced number of iterations in comparison to the conventional single-layer realisation of a heterogeneous WSN. Moreover, cooperation among sensor nodes is considered to relay data to fusion centre receiver to enhance transmission reliability in variable channel conditions. The proposed scheme is expected to provide energy efficient solutions for future generation WSNs. Simulation results demonstrate that for a heterogenous WSN with 50% activity factor, proposed scheme outperforms the existing scheme by saving 11% residual energy of the network.

RF Sensing Based Target Detector for Smart Sensing Within Internet of Things in Harsh Sensing Environments

In this paper, we explore surveillance and target detection applications of Internet of Things (IoT) with radio detection as the primary means of sensing. The problem of surveillance and target detection has found its place in numerous civilian and military applications, and IoT is well suited to address this problem. Radio frequency (RF) sensing techniques are the next generation technologies, which offer distinct advantages over traditional means of sensing used for surveillance and target detection applications of IoT. However, RF sensing techniques have yet to be widely researched due to lack of transmission and computational resources within IoT. Recent advancements in sensing, computing, and communication technologies have made radio detection enabled sensing techniques available to IoT. However, extensive research is yet to be done in developing reliable and energy efficient target detection algorithms for resource constrained IoT. In this paper, we have proposed a multi-sensor RF sensing-based target detection architecture for IoT. The proposed target detection architecture is adaptable to interference, which is caused due to the co-existence of sensor nodes within IoT and adopts smart sensing strategies to reliably detect the presence of the targets. A waveform selection criterion has been proposed to identify the optimum choice of transmit waveforms within a given set of sensing conditions to optimize the target detection reliability and power consumption within the IoT. A dual-stage target detection strategy has been proposed to reduce the computational burden and increase the lifetime of the sensor nodes.

Location-aware cooperative spectrum sensing within cognitive radio networks

Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering with the operations of the licensed network. Spectrum sensing decisions can lead to erroneous sensing due to fading, shadowing and other interferences caused by either terrain inconsistency or dense urban structure. In order to improve spectrum sensing decisions, in this paper a cooperative spectrum sensing scheme is proposed, which takes the propagation conditions such as the variance and intensity of terrain and urban structure between two points with respect to signal propagation into consideration. We have also derived the optimum fusion rule which takes location reliability into consideration. The analytical results show that the proposed scheme outperform the conventional cooperative spectrum sensing approaches.