Determination of Cramer-Rao Lower Bound (CRLB) and Minimum Variance Unbiased Estimator of a DC Signal in AWGN Using Laplace Transform

This paper presents an alternative approach for the determination of Cramer-Rao Lower Bound (CRLB) and Minimum Variance Unbiased Estimator (MVUE) using Laplace transformation. In this work, a DC signal in Additive White Gaussian Noise (AWGN) was considered. During the investigation, a number of experiments were conducted to analyze different possible outputs under different conditions, and then the patterns of the outcomes were studied. Finally closed-form expressions for the CRLB and MVUE were deduced employing the Laplace transformation. The resulting expressions showed that the proposed method has almost the same number of steps as the existing method. However, the latter requires only the knowledge of algebra to arrive at the CRLB expressions contrary to the existing approach where a strong mathematical background is required and hence making it superior over the existing method, in that sense. Keywords: Additive White Gaussian Noise, Cramer-Rao Lower Bound, DC-Value, Laplace transform, and Minimum Variance Unbiased Estimator (MVUE)

Multipath Exploitation-Based Indoor Target Localization Model Using Single Marginal Antenna

Recently, indoor target localization became an area of interest due to its diverse applications. In indoor target localization, surrounding environment creates multipath components, which can be exploited to aid in localization process. A number of studies have been proposed to employ multipath exploitation in localizing indoor targets. However, their localization errors can still be improved. This study proposed a new localization model based on multipath exploitation techniques by using triangulation method. Ultra-wide band signals were resolved and associated using marginal antenna-based scheme. The estimate of the target location was then obtained using measured round-trip time delays. The location was determined by applying the simple trigonometry on the triangle in which real radar, virtual radars, and the target location are the vertices of the triangle in question. Simulation results show that the proposed method has improved the localization error over a wide range of timing errors, target locations and room sizes with the overall maximum localization error of 1.4 m equivalent to 22.2% improvement as compared to 1.8 m localization error obtained using the method developed by the Muqaibel et al. (2017)

Efficient Load Balancing Algorithm in Long Term Evolution (LTE) Heterogeneous Network Based on Dynamic Cell Range Expansion Bias

The traditional scheme for load balancing in a homogeneous Long Term Evolution (LTE) Network where User Equipment (UEs) associate to a node with the strongest received signal strength is not practical for LTE Heterogeneous Network (LTE HetNet) due to power disparity between the nodes. Therefore, dynamic Cell Range Expansion (CRE) based load-balancing schemes were employed by several scholars to address the challenges in the LTE HetNet. However, the fairness index in achieving the desired average user throughput and UE offloading effect is relatively low. In this work, an efficient load-balancing algorithm for LTE HetNet based on dynamic Cell Range Expansion (CRE) was developed to improve the fairness of the network for the desired throughput and UE offloading effect. The simulation results achieve a throughput gain improvement of up to 11%, while the fairness index improves by 6% compared to the existing algorithm. Further, the UEs offloading effect shows a significant improvement of 3% relative to the existing algorithm. Keywords: Fairness Index; Cell Range Expansion; Load Balancing; LTE Heterogeneous Network; Throughpu

IoT-Based Smart Fishing Gear for Sustainability of the Tanzania Blue Economy

The fishing industry engages many Tanzanians and is among the leading sectors of Blue Economy in the country. However, fishing practices are small-scale with poor and insufficient number of fishing facilities, hence limiting productivity and efficacy. Studies argue that the low level of technology currently used in the country could possibly be an impeding factor. Specifically, fishers use non-interactive gears that cannot instantaneously update status and alert them whenever the gears are ready for collection. In such scenarios, fishers not only waste their time but also scarce resources such as fuel to facilitate trips to and from the fishing sites to check status of the gears. Thus, the application of Information and Communication Technology (ICT) could improve the production and lower operational costs is hypothesized. ICT solutions can help realize the processes with minimum human interventions while adding intelligence to the systems to make informed decisions and hence improve systems’ efficiency. In this work, an IoT based smart fishing gear that counts and records the number of fishes in the gear and then displays them on a mobile application is proposed. The system can send alerts to the user when the required number of fish is attained, and provides navigation support to localize the distant filled gears. Results show that the system can send the location of a given gear and timely update the number of catches via the mobile application

Resource Efficient Advanced Metering Infrastructure Model

Advanced Metering Infrastructure (AMI) enables two-way communication between smart devices and utility control centers. This involves remote monitoring and control of energy consumption as well as other parameters in the electrical power network in real time. However, increasing technologies in AMI due to huge deployment of smart meters, integration of devices and application of sensors, demand a strong architectural model with the best network topology to guarantee efficient usage of network resources with minimal latency. In this work, a resource efficient multi-hop network architecture is proposed using hybrid media access protocols. The architecture combines queuing and random-access protocol to achieve optimal network performance. Numerical results show that the probability of delay incurred by an arbitrary smart meter depends on the mean and distribution of the queue switch over a period. It is also observed that for a single queued system, the throughput performance is equal to the existing hybrid method. As the number of smart meters increases to 500, the throughput of the proposed method improves by 10% compared to the existing method. Likewise, as the number of smart meters increases to 500, the delay reduced by 15% compared to the existing method. Keywords: Advanced Metering Infrastructure; hybrid media access protocols; Smart Meter; Smart Grid; Power Network

Comparative Analysis of Multiplicative and Additive Noise Based Automated Regularizations in Non-Linear Diffusion Image Reconstruction

Multiplicative and additive noises are often introduced in image signals during the image acquisition process and result into degradation of image features. The work done by Perona and Malik in 1990 and its modified versions revolutionized the way through which noises or speckles are removed. The Perona-Malik model requires tuning of the regularization parameter to control and prevent staircase artifacts in restored images. The current manual tuning is a challenging and time consuming practice when a long queue of images is registered for processing. Attempt to automate the regularization parameter appeared in Perona-Malik model with self-adjusting shape-defining constant. Although both multiplicative and additive noise based automated regularizations were presented, the paper stayed silent on matters concerning the automation method that fits with speckle reduction. This paper therefore, presents a comparative analysis of additive and multiplicative noise based automated regularizations. Simulation results and paired samples T-tests reveal that the multiplicative noise based automation outperforms the additive noise based automation for small speckle variances. However, the two automation methods do not significantly differ when large speckle variances are assumed

Device–to-Device Association Algorithm for Optimal Neighbour Selection and Channel Sharing in 5G Cellular Networks

The integration of device-to-device (D2D) communication in 5G cellular networks has generated the possibility of multiple transmission modes in a single cell. This has motivated scholars to investigate different mode selection and D2D association algorithms that guarantee the selection of proper transmission mode. However, the complexity of algorithms and tractability of devices in the cell are still remarkably challenging. This paper, therefore, presents a utility based D2D association algorithm that ensures optimal neighbour selection by using numerical linear algebra to minimize computational complexity. Simulation results show that the minimum utility based D2D association increases the expected values of attached devices by 6% and 10% compared to the relative distance and maximum utility based D2D associations, respectively. Alternatively, the throughput expectation increases by 2.5% and 4% compared to the relative distance and maximum utility based D2D associations, respectively. Keywords: Cooperative Communication; D2D, Mode Selection; Relay-assisted; Traffic Overloa

Design and Implementation of Distributed Identity and Access Management Framework for Internet of Things (IoT) Enabled Distribution Automation

The smart grid and Internet of Things (IoT) technologies play vital roles in improving the quality of services offered in traditional electrical grid. They open a room for the introduction of new services like distribution automation (DA) that has a significant advantage to both utility companies and final consumers. DA integrates sensors, actuators, intelligent electrical devices (IED) and information and communication technologies to monitor and control electrical grid. However, the integration of these technologies poses security threats to the electrical grid like Denial of Service (DoS) attacks, false data injection attacks, and masquerading attacks like system node impersonation that can transmit wrong readings, resulting in false alarm reports and hence leading to incorrect node actuation. To overcome these challenges, researchers have proposed a centralized public key infrastructure (PKI) with bridged certificate authority (CA) which is prone to DoS attacks. Moreover, the proposed blockchain based distributed identity and access management (DIAM) in IoT domain at the global scale is adding communicational and computational overheads. Also. It is imposing new security threats to the DA system by integrating it with online services like IoTEX and IoTA. For those reasons, this study proposes a DIAM security scheme to secure IoT-enabled distribution automation. The scheme divides areas into clusters and each cluster has a device registry and a registry controller. The registry controller is a command line tool to access and manage a device registry. The results show that the scheme can prevent impersonated and non-legitimate system nodes and users from accessing the system by imposing role-based access control (RBAC) at the cluster level. Keywords: Distributed Identity and Access Management; Electrical Secondary Distribution Network; Internet of Things; IoT Enabled Distribution Automation; Smart Grid Securit

Multipath Ghosts in Through‐the‐Wall Radar Imaging: Challenges and Solutions

In through‐the‐wall radar imaging (TWRI), the presence of front and side walls causes multipath propagation, which creates fake targets called multipath ghosts. They populate the scene and reduce the probability of correct target detection, classification, and localization. In modern TWRI, specular multipath exploitation has received considerable attention for reducing the effects of multipath ghosts. However, this exploitation is challenged by the requirements of the reflecting geometry, which is not always available. Currently, the demand for a high radar image resolution dictates the use of a large aperture and wide bandwidth. This results in a large amount of data. To tackle this problem, compressive sensing (CS) is applied to TWRI. With CS, only a fraction of the data are used to produce a high‐quality image, provided that the scene is sparse. However, owing to multipath ghosts, the scene sparsity is highly deteriorated; hence, the performance of the CS algorithms is compromised. This paper presents and discusses the adverse effects of multipath ghosts in TWRI. It describes the physical formation of ghosts, their challenges, and existing suppression techniques