The advanced notebooks, mobile phones, and Internet applications in today’s world that we use are all entrenched in classical communication bits of zeros and ones. Classical Internet has laid its foundation originating from the amalgamation of mathematics and Claude Shannon’s theory of information. However, today’s Internet technology is a playground for eavesdroppers. This poses a serious challenge to various applications that rely on classical Internet technology, and it has motivated the researchers to switch to new technologies that are fundamentally more secure. By exploring the quantum effects, researchers paved the way into quantum networks that provide security, privacy, and range of capabilities such as quantum computation, communication, and metrology. The realization of Quantum Internet (QI) requires quantum communication between various remote nodes through quantum channels guarded by quantum cryptographic protocols. Such networks rely upon quantum bits (qubits) that can simultaneously take the value of zeros and ones. Due to the extraordinary properties of qubits such as superposition, entanglement, and teleportation, it gives an edge to quantum networks over traditional networks in many ways. At the same time, transmitting qubits over long distances is a formidable task and extensive research is going on satellite-based quantum communication, which will deliver breakthroughs for physically realizing QI in near future. In this paper, QI functionalities, technologies, applications and open challenges have been extensively surveyed to help readers gain a basic understanding of the infrastructure required for the development of the global QI.

Implementing line-of-sight (LOS) and none-line-of-sight (NLOS) identification in ultra-wideband (UWB) systems is crucial. Convolutional neural network (CNN) based identification methods can extract higher-level features automatically, but they are based on channel impulse response (CIR)-turned image ingested features that impose calculation complexity and do not make use of manual features due to the data inundation risk. In this letter, we propose a novel multilayer perceptron (MLP)-based LOS/NLOS identification algorithm that can utilize both manually extracted features and feature from CNN based on raw CIR inputs with only 7.39% calculation complexity as compared to the traditional image-based CNN. Three experiments, at a teaching building, an office, and an underground mine, were conducted to verify the proposed method’s performance. Our proposed features are conducive to LOS/NLOS identification, especially the proposed raw CIR-based feature from the CNN, achieving 26.9% improvement over existing manual features. Furthermore, the proposed method outperformed the traditional image-based CNN with an improvement of 44.16%.

Quantum Key Distribution (QKD) protocols allow the establishment of symmetric cryptographic keys up to a limited distance at limited rates. Due to optical misalignment, noise in quantum detectors, disturbance of the quantum channel or eavesdropping, an error key reconciliation technique is required to eliminate errors. This chapter analyses different key reconciliation techniques with a focus on communication and computing performance. We also briefly describe a new approach to key reconciliation techniques based on artificial neural networks.

Cyborg insects are a major part of the vision of future interactions of the living world and technology, including but not limited to the Internet of Living Things (IoLT). They are crawling or flying insects with additional electronic circuitry allowing remote control of their movement and collection of sensory data. In this critical review, we survey the historical development of cyborg insects engineering, from the first backpacks on insects used for communication and sensing, to different methods of control and actuation of insects’ locomotion. We review the suggested applications of cyborg insects ranging from military use to agriculture, pointing out the problematic connotations of swarms and cyborgs in these contexts. We address the applications and the narratives around engineered insects from the perspective of philosophy, economy, law, and politics. We add perspectives on emancipatory potential of cyborg technology and where the future of it could lie.

Distributed antenna selection for distributed massive multiple input multiple output (MIMO) communication systems reduces computational complexity compared to centralized approaches, and provides high fault tolerance while retaining diversity and spatial multiplexity. We propose a novel distributed algorithm for antenna selection and show its advantage over existing centralized and distributed solutions. The proposed algorithm is shown to perform well with imperfect channel state information, and to execute a small number of simple computational operations per node, converging fast to a steady state. We base it on reversing Petri nets, a variant of Petri nets inspired by reversible computation, capable of both forward and backward execution while obeying conservation laws.

Post-disaster scene understanding frameworks are increasingly crucial in Search And Rescue (SAR) operations. Unmanned Aerial Vehicles (UAVs) provide an efficient means to carry out the task of scene understanding due to the higher altitudes at which they function. However, complex environments in post-disaster scenarios make it difficult for UAVs to detect humans or objects accurately. Inefficient object detection mechanisms lead to low accuracy for object detection tasks. Hence, to mitigate these issues, we propose a UAV and GAN-aided Ensemble Network (UGEN) framework for efficient ORAN-based post-disaster survivor detection. This approach deploys a Context-Conditional Generative Adversarial Network (CCGAN)- based model to remove occlusion in the images obtained from the UAVs. The UGEN framework classifies entities present in the visual scope of the UAV using a semantic segmentation framework deployed on the CCGAN-enhanced images, resulting in a pixel-level prediction of entities present in the post-disaster images. An ensemble network comprising a combination of single-stage and multi-stage detectors detects survivors present in the post-disaster scenario, thereby combining the benefits of both architectures, resulting in a reduced false negative rate and improved performance. An Open Radio Access Network (ORAN) executes data propagation between the UAV and the ground station for reduced transmission latency. The proposed model achieved a survivor detection accuracy of 96.7%.