As the Internet of Things (IoT) is gaining ground and becoming increasingly popular in smart city applications such as smart energy, smart buildings, smart factories, smart transportation, smart farming, and smart healthcare, the digital twin concept is evolving as complementary to its counter physical part. While an object is on the move, its operational and surrounding environmental parameters are collected by an edge computing device for local decision. A virtual replica of such object (digital twin) is based in the cloud computing platform and hosts the real-time physical object data, 2D and 3D models, historical data, and bill of materials (BOM) for further processing, analytics, and visualization. This paper proposes an end-to-end digital twin conceptual model that represents its complementary physical object from the ground to the cloud. The paper presents the proposed digital twin model’s multi-layers, namely, physical, communication, virtual space, data analytic and visualization, and application as well as the overlapping security layer. The hardware and software technologies that are used in building such a model will be explained in detail. A use case will be presented to show how the layers collect, exchange, and process the physical object data from the ground to the cloud.

In this paper, we propose a framework for a non-terrestrial ISAC system, where a high-altitude platform station (HAPS)-mounted full duplex (FD) ISAC base station (BS) is deployed to deliver communication services to multiple user equipment (UEs) and, at the same time, sense multiple targets. Moreover, the ISAC-BS offloads part of the sensed data to a dedicated edge server for computation purposes. Additionally, an unmanned aerial vehicle (UAV) is deployed to transmit jamming signals aimed at degrading the reception quality of malicious targets or potential eavesdroppers identified through the sensing process. A multi-objective optimization problem is formulated to jointly optimize the transmit/receive beamforming and UAV trajectory to maximize the communication sum spectral efficiency under radar performance, security, offloading, and power constraints. Since the formulated problem is non-convex, we use alternating optimization (AO), semi-definite relaxation (SDR), and successive convex approximation (SCA) approaches to solve it. Simulation results show that the communication and radar achieved rates from the proposed algorithm outperforms the cases of using non-optimized UAV’s trajectory and using the Rayleigh-quotient method to design the receive beamforming vectors.

Monolithic integration of high-speed, high-efficiency photodiodes with receiver electronics on a single silicon chip is a key to reduce cost and improve the performance of data centers’ short reach optical interconnects. We report a CMOS-compatible surface illuminated silicon PIN photodiode with integrated micro- and nano-scale holes that trap photons for longer interaction with semiconductors resulting in higher absorption efficiencies. The fabricated photodiode demonstrates more than 55% external quantum efficiency (EQE) at 850nm, and a measured Full-Width at Half Maximum (FWHM) impulse response of 29ps, 31ps, and 34ps at 15V, 10V, and 3V reverse biases, respectively. Simulation results indicate the possibility of operation up to 12.5Gb/s (NRZ) with no equalization.

Ubiquitous connectivity through the integration of terrestrial and non-terrestrial networks has become one of the crucial usage scenarios in the sixth generation (6G) vision. In this paper, we analyze the outage performance of a multi-user aerial intelligent reflecting surface (IRS)-assisted space-air-ground integrated network (SAGIN) operating in the terahertz (THz) band. The system consists of a low earth orbit (LEO) satellite that communicates with a group of user equipment (UEs) through a terrestrial base station (TBS) relay. Due to the presence of obstacles and shadowing, a high-altitude platform station (HAPS)-mounted IRS is utilized to assist the communication scenario. We derive exact closed-form expressions for the outage probabilities at the UEs through the TBS relay and through the HAPS using the multivariate Fox’s H-function assuming optimal IRS phase shifts. Moreover, we derive approximate closed-form expressions using the central limit theory (CLT) for a sufficiently large number of IRS elements for both optimal phase shifts and phase shift estimation errors cases. Monte Carlo simulations are conducted to validate the derived expressions. Simulation results demonstrate that deploying HAPS-mounted IRS significantly enhances the outage performance at lower satellite transmit power and provides coverage over larger service areas.

Pulse position modulation (PPM) presents several advantages in free-space optical systems, unrepeatered fiber transmission, and passive optical networks. In this paper, we study the error performance in direct-detection optically preamplified M-ary PPM optical communication systems. We consider the impact of the amplifier spontaneous emission noise, as well of the finite extinction ratio of the transmitter, on the probability of bit error at the receiver. We derive expressions for the probability of bit error under both assumptions of noise polarization, namely, single- and dual-polarized amplifier noise, and compute it numerically for different symbol sizes M and extinction ratios. In addition, we present the power penalty due to the transmitter finite extinction ratio for systems with and without forward error correction. Our findings show that, in the cases of practically achievable finite extinction ratios, systems with smaller M may perform equally well when compared to those using higher values of M. We also show that there is little benefit, if any, associated with using a polarization filter in the receiver since the additional size, weight, and power consumption requirements outweigh the error performance improvement.

With the extensive deployment of Internet-of-Things (IoT) in next generation wireless systems, the problems of energy efficiency and battery life become exacerbated, highlighting the pressing need for innovative solutions. Symbiotic radio (SR) is considered one of the emerging technologies that aims at providing an energy-efficient solution for the ubiquitous IoT applications. In this paper, we propose an SR system that is assisted with a double-faced active intelligent reflecting surface (DFA-IRS). The proposed system consists of an active transmitter (AT), an active receiver (AR), a backscatter receiver (BR), a DFA-IRS, and an IoT device that is connected to the DFA-IRS. We formulated a BR spectral efficiency maximization problem via optimizing the active beamforming vector at the AT, the power amplification factors of the IRS active elements, and the IRS phase shift at each active element under the constraints of a maximum power budget and the AR spectral efficiency requirements. The formulated problem is non-convex due to the coupling between different variables. Hence, we divided the main problems into three sub-problems and utilized the successive convex approximation (SCA) and the semidefinite relaxation (SDR) techniques to obtain a convex equivalent problem that can be solved using conventional optimization tools such as CVX. Simulation results show that the proposed algorithm converges in few number of iterations. Moreover, the proposed scheme achieves better BR spectral efficiency when compared to the case where a single-faced active IRS or a simultaneously transmitting and reflecting IRS (STAR-IRS) counterpart is used.