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Presentations and discussion on research results on smart antennas, spanning theoretical analyses as well as technical and implementation aspects, in modern wireless communications. Topics of interest includes: - Massive MIMO and Beyond - Network/Distributed MIMO - Multicell Systems and Interference - Beamforming Techniques - Cloud Radio Access Networks - Millimetre Wave and Terahertz Communication - Ultra-Low Latency Communication - Channel Modelling and Estimation - Compressive Sensing and Sparse Processing - Machine Learning for PHY/MAC Design - Multi-antenna Techniques and Security - MIMO Radar and Multi-sensor Processing - Joint Communication and Sensing - Cooperative and Sensor Networks - Device-to-Device Communication - Vehicular Communication - Uncoordinated and Massive Access - Localization - Field Trials and Demonstrators.

Machine Learning --- Wireless Communications --- Beamforming Techniques --- Smart Antenna --- Wireless Technology --- Channel Modelling --- Cloud Radio Access Networks --- Massive/Full-Dimension MIMO --- Network/Distributed MIMO --- Ultra-Low Latency Communic. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Wireless communication systems --- Beamforming --- Smart Antennas --- Wireless sensor networks --- C-RAN (Cloud-RAN) --- Centralized-RAN --- Ultra-Low Latency Communications --- WSNs (Sensor networks) --- Computer networks --- Low voltage systems --- Sensor networks --- Context-aware computing --- Spatial filtering (Signal processing) --- Signal processing

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The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic.

fog computing --- heterogeneous networks --- distributed mechanism --- energy efficiency --- scheduling --- CSMA --- throughput --- grant-free --- D2D communication --- MAC --- Industrial Internet of Things --- estimation --- 5G --- survey --- liquid detection --- power control --- sensor --- SINR --- radio propagation --- MU association --- Raspberry Pi --- reliability --- latency --- deterministic --- Industry 4.0 --- stochastic geometry --- dielectric constant --- Cyber Physical System --- IoT --- successive interference cancellation --- URLLC --- end-to-end delay --- resource allocation --- polynomial interpolation --- industrial automation --- cloud computing --- mMTC --- smart factory --- deployment --- ultra-reliable and low-latency communications --- PHY --- aperiodic traffic --- NB-IoT --- irregular repetition slotted ALOHA --- edge computing --- time-critical --- eMBB --- medium access control --- M2M --- Internet of Things --- internet of things --- sensor network --- random access --- smart devices --- non-orthogonal multiple access --- USRP --- WCI --- narrowband --- congestion

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The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads formerly reserved for the cloud, such as deep learning. These devices allow processing close to where data are generated, avoiding bottlenecks due to communication limitations. The efficient integration of hardware, software and artificial intelligence capabilities deployed in real sensing contexts empowers the edge intelligence paradigm, which will ultimately contribute to the fostering of the offloading processing functionalities to the edge. In this Special Issue, researchers have contributed nine peer-reviewed papers covering a wide range of topics in the area of edge intelligence. Among them are hardware-accelerated implementations of deep neural networks, IoT platforms for extreme edge computing, neuro-evolvable and neuromorphic machine learning, and embedded recommender systems.

Information technology industries --- high-level synthesis --- HLS --- SDSoC --- support vector machines --- SVM --- code refactoring --- Zynq --- ZedBoard --- extreme edge --- embedded edge computing --- internet of things deployment --- hardware design --- IoT security --- Contiki-NG --- trustability --- embedded systems --- collaborative filtering --- recommender systems --- parallelism --- reconfigurable hardware --- neuroevolution --- block-based neural network --- dynamic and partial reconfiguration --- scalability --- reinforcement learning --- embedded system --- artificial intelligence --- hardware acceleration --- neuromorphic processor --- power consumption --- harsh environment --- fog computing --- edge computing --- cloud computing --- IoT gateway --- LoRa --- WiFi --- low power consumption --- low latency --- flexible --- smart port --- quantisation --- evolutionary algorithm --- neural network --- FPGA --- Movidius VPU --- 2D graphics accelerator --- line-drawing --- Bresenham’s algorithm --- alpha-blending --- anti-aliasing --- field-programmable gate array --- deep learning --- performance estimation --- Gaussian process --- high-level synthesis --- HLS --- SDSoC --- support vector machines --- SVM --- code refactoring --- Zynq --- ZedBoard --- extreme edge --- embedded edge computing --- internet of things deployment --- hardware design --- IoT security --- Contiki-NG --- trustability --- embedded systems --- collaborative filtering --- recommender systems --- parallelism --- reconfigurable hardware --- neuroevolution --- block-based neural network --- dynamic and partial reconfiguration --- scalability --- reinforcement learning --- embedded system --- artificial intelligence --- hardware acceleration --- neuromorphic processor --- power consumption --- harsh environment --- fog computing --- edge computing --- cloud computing --- IoT gateway --- LoRa --- WiFi --- low power consumption --- low latency --- flexible --- smart port --- quantisation --- evolutionary algorithm --- neural network --- FPGA --- Movidius VPU --- 2D graphics accelerator --- line-drawing --- Bresenham’s algorithm --- alpha-blending --- anti-aliasing --- field-programmable gate array --- deep learning --- performance estimation --- Gaussian process

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The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out.

unmanned aerial vehicle --- UAV positioning --- machine learning --- wireless communications --- drones --- network --- DTN --- mobility schedule --- routing algorithms --- data delivery --- Internet of drones --- communication --- security --- privacy --- UAV base station --- MIMO --- millimeter-wave band --- blind beamforming --- signal recovery --- UAV relay networks --- resource management --- transmit time allocation --- unmanned aerial vehicles --- dynamic spectrum access --- quality of service --- reinforcement learning --- multi-armed bandit --- aerial communication --- FANET --- not-spots --- stratospheric communication platform --- UAV --- UAV-assisted network --- 5G --- global positioning system --- GPS spoofing attacks --- detection techniques --- dynamic selection --- hyperparameter tuning --- IoT --- RF radio communication --- Wi-Fi direct --- D2D --- drone-based mobile secure zone --- friendly jamming --- mobility --- internet of things --- non-orthogonal multiple access --- resource allocation --- ultra reliable low latency communication --- uplink transmission --- Deep Q-learning (DQL) --- Double Deep Q-learning (DDQL) --- dynamic spectrum sharing --- High Altitude Platform Station (HAPS) --- cellular communications --- power control --- interference management --- cognitive UAV networks --- clustered two-stage-fusion cooperative spectrum sensing --- continuous hidden Markov model --- SNR estimation --- n/a

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Computing systems are undergoing a transformation from logic-centric towards memory-centric architectures, where overall performance and energy efficiency at the system level are determined by the density, performance, functionality and efficiency of the memory, rather than the logic sub-system.

n/a --- image classification --- bipolar resistive switching characteristics --- bioelectronic devices --- self-directed channel (SDC) --- programmable ramp-down current pulses --- nanoparticles --- protein --- DRAM --- convolutional neural networks --- silicon oxide-based memristors --- electrochemical metallization cell --- magnetic tunnel junction --- power gating --- resistance switching mechanism --- BCH --- Fast Fourier Transform --- nucleic acid --- biomemory --- conductive filament --- resistive random access memory (RRAM) --- non-von Neumann architecture --- emerging technologies --- Galois field --- variability --- logic-in-memory --- charge spreading --- memristor --- Hebbian training --- crossbar --- quantum point contact --- SONOS --- bionanohybrid material --- ECG --- neuromorphic computing --- CUDA --- low-latency --- iBM --- Oxygen-related trap --- nonvolatile memory --- phase change memory --- floating gate --- non-von neumann architecture --- 3D-stacked --- STT-MRAM --- solution-based dielectric --- GPU --- Internet of things --- configurable logic-in-memory architecture --- memory wall --- biologic gate --- synaptic weight --- guide training --- ion conduction --- perpendicular Nano Magnetic Logic (pNML) --- Weibull distribution --- real-time system --- in-DRAM cache --- task placement --- dynamic voltage scaling --- MCU (microprogrammed control unit) --- wire resistance --- multi-level cell --- chalcogenide --- decoder --- character recognition --- matrix-vector multiplication --- hybrid --- magnetoresistive random access memory --- blockchain --- electrochemical metallization (ECM) --- RISC-V --- U-shape recessed channel --- neuromorphic system --- in-memory computing --- crossbar array --- associative processor --- low-power --- plasma treatment --- voltage-controlled magnetic anisotropy --- flash memory --- resistive memory --- analogue computing --- bioprocessor --- annealing temperatures --- data retention --- flip-flop --- low-power technique