A survey of localization in wireless sensor network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

Intelligent Reflecting Surfaces Assisted Secure Transmission Without Eavesdropper's CSI

In this letter, improving the security of an intelligent reflecting surface (IRS) assisted multiple-input single-output (MISO) communication system is studied. Different from the ideal assumption in existing literatures that full eavesdropper's (Eve's) channel state information (CSI) is available, we consider a more practical scenario without Eve's CSI. To enhance the security of this system given a total transmit power at transmitter (Alice), we propose a joint beamforming and jamming approach, in which a minimum transmit power is firstly optimized at Alice so as to meet the quality of service (QoS) at legitimate user (Bob), and then artificial noise (AN) is emitted to jam the eavesdropper by using the residual power at Alice. Two efficient algorithms exploiting oblique manifold (OM) and minorizationmaximization (MM) algorithms, respectively, are developed for solving the resulting non-convex optimization problem. Simulation results have been provided to validate the performance and convergence of the proposed algorithms

Seven Defining Features of Terahertz (THz) Wireless Systems: A Fellowship of Communication and Sensing

Wireless communication at the terahertz (THz) frequency bands (0.1-10THz) is viewed as one of the cornerstones of tomorrow's 6G wireless systems. Owing to the large amount of available bandwidth, THz frequencies can potentially provide wireless capacity performance gains and enable high-resolution sensing. However, operating a wireless system at the THz-band is limited by a highly uncertain channel. Effectively, these channel limitations lead to unreliable intermittent links as a result of a short communication range, and a high susceptibility to blockage and molecular absorption. Consequently, such impediments could disrupt the THz band's promise of high-rate communications and high-resolution sensing capabilities. In this context, this paper panoramically examines the steps needed to efficiently deploy and operate next-generation THz wireless systems that will synergistically support a fellowship of communication and sensing services. For this purpose, we first set the stage by describing the fundamentals of the THz frequency band. Based on these fundamentals, we characterize seven unique defining features of THz wireless systems: 1) Quasi-opticality of the band, 2) THz-tailored wireless architectures, 3) Synergy with lower frequency bands, 4) Joint sensing and communication systems, 5) PHY-layer procedures, 6) Spectrum access techniques, and 7) Real-time network optimization. These seven defining features allow us to shed light on how to re-engineer wireless systems as we know them today so as to make them ready to support THz bands. Furthermore, these features highlight how THz systems turn every communication challenge into a sensing opportunity. Ultimately, the goal of this article is to chart a forward-looking roadmap that exposes the necessary solutions and milestones for enabling THz frequencies to realize their potential as a game changer for next-generation wireless systems.Comment: 26 pages, 6 figure

Novel techniques of computational intelligence for analysis of astronomical structures

Gravitational forces cause the formation and evolution of a variety of cosmological structures. The detailed investigation and study of these structures is a crucial step towards our understanding of the universe. This thesis provides several solutions for the detection and classification of such structures. In the first part of the thesis, we focus on astronomical simulations, and we propose two algorithms to extract stellar structures. Although they follow different strategies (while the first one is a downsampling method, the second one keeps all samples), both techniques help to build more effective probabilistic models. In the second part, we consider observational data, and the goal is to overcome some of the common challenges in observational data such as noisy features and imbalanced classes. For instance, when not enough examples are present in the training set, two different strategies are used: a) nearest neighbor technique and b) outlier detection technique. In summary, both parts of the thesis show the effectiveness of automated algorithms in extracting valuable information from astronomical databases