Interpretation of X-ray Powder Diffraction Patterns . By H. Lipson and H. Steeple. Pp. viii + 335 + 3 plates. (Mac-millan: London; St Martins Press: New York, May 1970.) £4.

X-Ray Diffraction

Mobile network is evolving from a communication-only network towards the one with joint communication and radio/radar sensing (JCAS) capabilities, that we call perceptive mobile network (PMN). Radio sensing here refers to information retrieval from received mobile signals for objects of interest in the environment surrounding the radio transceivers. In this paper, we provide a comprehensive survey for systems and technologies that enable JCAS in PMN, with a focus on works in the last ten years. Starting with reviewing the work on coexisting communication and radar systems, we highlight their limits on addressing the interference problem, and then introduce the JCAS technology. We then set up JCAS in the mobile network context, and envisage its potential applications. We continue to provide a brief review for three types of JCAS systems, with particular attention to their differences on the design philosophy. We then introduce a framework of PMN, including the system platform and infrastructure, three types of sensing operations, and signals usable for sensing, and discuss required system modifications to enable sensing on current communication-only infrastructure. Within the context of PMN, we review stimulating research problems and potential solutions, organized under eight topics: mutual information, waveform optimization, antenna array design, clutter suppression, sensing parameter estimation, pattern analysis, networked sensing under cellular topology, and sensing-assisted secure communication. This paper provides a comprehensive picture for the motivation, methodology, challenges, and research opportunities of realizing PMN. The PMN is expected to provide a ubiquitous radio sensing platform and enable a vast number of novel smart applications.

Enabling Joint Communication and Radio Sensing in Mobile Networks -- A Survey

Beamforming has a great potential for joint communication and radar sensing (JCAS), which is becoming a demanding feature on many emerging platforms, such as unmanned aerial vehicles and smart cars. Although beamforming has been extensively studied for communication and radar sensing respectively, its application in the joint system is not straightforward due to different beamforming requirements by communication and sensing. In this paper, we propose a novel multibeam framework using steerable analog antenna arrays, which allows seamless integration of communication and sensing. Different to conventional JCAS schemes that support JCAS using a single beam, our framework is based on the key innovation of multibeam technology: providing fixed subbeam for communication and packet-varying scanning subbeam for sensing, simultaneously from a single transmitting array. We provide a system architecture and protocols for the proposed framework, complying well with modern packet communication systems with multicarrier modulation. We also propose low-complexity and effective multibeam design and generation methods, which offer great flexibility in meeting different communication and sensing requirements. We further develop sensing parameter estimation algorithms using conventional digital Fourier transform and one-dimensional compressive sensing techniques, matching well with the multibeam framework. Simulation results are provided and validate the effectiveness of our proposed framework, beamforming design methods, and the sensing algorithms.

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Multibeam for Joint Communication and Radar Sensing Using Steerable Analog Antenna Arrays

Effective emergency and natural disaster management depend on the efficient mission-critical voice and data communication between first responders and victims. Land mobile radio system (LMRS) is a legacy narrowband technology used for critical voice communications with limited use for data applications. Recently, long term evolution (LTE) emerged as a broadband communication technology that has a potential to transform the capabilities of public safety technologies by providing broadband, ubiquitous, and mission-critical voice and data support. For example, in the United States, FirstNet is building a nationwide coast-to-coast public safety network based on LTE broadband technology. This paper presents a comparative survey of legacy and the LTE-based public safety networks, and discusses the LMRS-LTE convergence as well as mission-critical push-to-talk over LTE. A simulation study of LMRS and LTE band class 14 technologies is provided using the NS-3 open source tool. An experimental study of APCO-25 and LTE band class 14 is also conducted using software-defined radio to enhance the understanding of the public safety systems. Finally, emerging technologies that may have strong potential for use in public safety networks are reviewed.

A Survey on Legacy and Emerging Technologies for Public Safety Communications

Traffic offloading and resource sharing are two common methods for delivering cellular data traffic over unlicensed bands. In this paper, we first develop a hybrid method to take full advantages of both traffic offloading and resource sharing methods, where cellular base stations (BSs) offload traffic to WiFi networks and simultaneously occupy certain number of time slots on unlicensed bands. Then, we analytically compare the cellular throughput of the three methods with the guarantee of WiFi per-user throughput in the single-BS scenario. We find that traffic offloading can achieve better performance than resource sharing when existing WiFi user number is below a threshold and the hybrid method achieves the same performance as the resource sharing method when existing WiFi user number is large enough. In the multi-BS scenario where the coverage of small cells and WiFi access points are mutually overlapped, we consider to maximize the minimum average per-user throughput of each small cell and derive a closed-form expression for the throughput upper bound in each method. Meanwhile, practical traffic offloading and resource sharing algorithms are also developed for the three methods, respectively. Numerical results validate our theoretical analysis and demonstrate the effectiveness of the proposed algorithms as well.

Cellular Meets WiFi: Traffic Offloading or Resource Sharing?

Modern radar systems tend to utilize high bandwidth, which requires high sampling rate, and in many cases, these systems involve phased array configurations with a large number of transmit–receive elements. In contrast, the ultimate goal of a radar system is often to estimate only a limited number of target parameters. Thus, there is a pursuit to find better means to perform the radar signal acquisition as well as processing with much reduced amount of data and power requirement. Recently, there has been a great interest to consider compressive sensing (CS) for radar system design; CS is a novel technique which offers the framework for sparse signal detection and estimation for optimized data handling. In radars, CS enables the achievement of better range-Doppler resolution in comparison with the traditional techniques. However, CS requires the selection of suitable (sparse) signal model, the design of measurement system as well as the implementation of appropriate signal recovery method. This work attempts to present an overview of these CS aspects, particularly when CS is applied in monostatic pulse-Doppler and MIMO type of radars. Some of the associated challenges, e.g., grid mismatch and detector design issues, are also discussed.

Compressive sensing applied to radar systems: an overview

Herein, we report the synthesis of nanoparticles and doping of Cu-doped Co–Zn ferrites using the auto-combustion sol–gel synthesis technique. X-ray diffraction studies confirmed the single-phase structure of the samples with space group Fd3m and crystallite size in the range of 20.57–32.69 nm. Transmission electron microscopy micrographs and selected area electron diffraction patterns confirmed the polycrystalline nature of the ferrite nanoparticles. Energy-dispersive X-ray spectroscopy revealed the elemental composition in the absence of any impurity phases. Fourier-transform infrared studies showed the presence of two prominent peaks at approximately 420 cm−1 and 580 cm−1, showing metal–oxygen stretching and the formation of ferrite composite. X-ray photoelectron spectroscopy was employed to determine the oxidation states of Fe, Co, Zn, and Cu and O vacancies based on which cationic distributions at tetrahedral and octahedral sites are proposed. Dielectric spectroscopy showed that the samples exhibit Maxwell–Wagner interfacial polarization, which decreases as the frequency of the applied field increases. The dielectric loss of the samples was less than 1, confirming that the samples can be used for the fabrication of multilayer inductor chips. The ac conductivity of the samples increased with increasing doping and with frequency, and this has been explained by the hopping model. The hysteresis loops revealed that coercivity decreases slightly with doping, while the highest saturation magnetization of 55.61 emu/g was obtained when x = 0.1. The magnetic anisotropic constant was found to be less than 0.5, which suggests that the samples exhibit uniaxial anisotropy rather than cubic anisotropy. The squareness ratio indicates that the samples are useful in high-frequency applications.

Tuning of Structural, Dielectric, and Electronic Properties of Cu Doped Co–Zn Ferrite Nanoparticles for Multilayer Inductor Chip Applications

Improved room temperature dielectric properties of Gd3+ and Nb5+ co-doped Barium Titanate ceramics

The next generation’s sensor nodes will be more intelligent, energy conservative, and perpetual lifetime in the set-up of wireless sensor networks (WSNs). These sensors nodes are facing the overwhelming challenge of energy consumption which gradually decreases the lifetime of overall network. The wireless power transfer (WPT) is one of the most emerging technologies of energy harvesting that deploys at the heart of sensor nodes for efficient lifetime solution. A wireless portable charging device (WPCD) is drifting inside the WSN to recharge all the nodes which are questing for the eternal life. In this paper, we aspire to optimize a multi-objective function for charging trail of WPCD, and self-learning algorithm for data routing jointly. We formulated that the objective functions can optimize the fair energy consumption as well as maximize the routing efficiency of WPCD. The fundamental challenge of the problem is, to integrate the novel path for WPCD by applying the Nodal A* algorithm. We proposed a novel method of sensor node’s training for intellectual data transmission by using of clustering and reinforcement learning (SARSA) defined as clustering SARSA (C-SARSA) along with an optimal solution of objective functions. The whole mechanism outperforms in terms of trade-off between energy consumption and stability (fair energy consumption among all nodes) of the WSN; moreover, it prolongs the lifetime of the WSN. The simulated results demonstrate that our proposed method did better than compared literature in terms of energy consumption, stability, and lifetime of the WSN.

Muhammad Usman Hadi

Papers

Compressive sensing applied to radar systems: an overview

Tuning of Structural, Dielectric, and Electronic Properties of Cu Doped Co–Zn Ferrite Nanoparticles for Multilayer Inductor Chip Applications

Improved room temperature dielectric properties of Gd3+ and Nb5+ co-doped Barium Titanate ceramics

Optimal Wireless Charging Inclusive of Intellectual Routing Based on SARSA Learning in Renewable Wireless Sensor Networks

Optimized digital radio over fiber system for medium range communication