Probabilistic Constellation Shaping for Enhancing Spectral Efficiency in NOMA VLC Systems

The limited modulation bandwidth of the light emitting diodes (LEDs) presents a challenge in the development of practical high-data-rate visible light communication (VLC) systems. In this paper, a novel adaptive coded probabilistic shaping (PS)-based nonorthogonal multiple access (NOMA) scheme is proposed to improve spectral efficiency (SE) of VLC systems in multiuser uplink communication scenarios. The proposed scheme adapts its rate to the optical signal-to-noise ratio (OSNR) by utilizing non-uniformly distributed discrete constellation symbols and low complexity channel encoder. Furthermore, an alternate optimization algorithm is proposed to determine the optimal channel coding rate, constellation spacing, and probability mass function (PMF) of each user. The extensive numerical results show that the proposed PS-based NOMA scheme closely approaches the capacity of NOMA with fine granularity. Presented results demonstrate the effectiveness of our scheme in improving the SE of VLC systems in multiuser scenarios. For instance, our scheme exhibits substantial SE gains over existing schemes, namely, the pairwise coded modulation (PCM), geometric shaping (GS), and uniform-distribution schemes. These findings highlight the potential of our approach to significantly enhance VLC systems.

Stochastic differential equations for performance analysis of wireless communication systems

This paper addresses the difficulty of characterizing the time-varying nature of fading channels. The current time-invariant models often fall short of capturing and tracking these dynamic characteristics. To overcome this limitation, we explore using of stochastic differential equations (SDEs) and Markovian projection to model signal envelope variations, considering scenarios involving Rayleigh, Rice, and Hoyt distributions. Furthermore, it is of practical interest to study the performance of channels modeled by SDEs. In this work, we investigate the fade duration metric, representing the time during which the signal remains below a specified threshold within a fixed time interval. We estimate the complementary cumulative distribution function (CCDF) of the fade duration using Monte Carlo simulations, and analyze the influence of system parameters on its behavior. Finally, we leverage importance sampling, a known variance-reduction technique, to estimate the tail of the CCDF efficiently.

3-D Position Optimization of Solar-Powered Hovering UAV Relay in Optical Wireless Backhaul

A major hurdle in widespread deployment of UAVs (unmanned aerial vehicle) in existing communications infrastructure is the limited UAV onboard energy. Therefore, this study considers solar energy harvesting UAVs for wireless communications. In this context, we consider three dimensional position optimization of a solar-powered UAV relay that connects a distant sensor field to an optical ground station (OGS) for data processing. The integrated sensor-UAV-OGS network utilizes radio frequency band for sensor-to-UAV links and the optical band for the UAV-to-OGS feeder link. Since atmospheric conditions affect both the harvested solar energy as well as the optical wireless signal, this study tackles UAV position optimization problems under various channel conditions such as clouds, atmospheric turbulence and dirt. From this study, we discover that the optimum position of the UAV -- that maximizes the end-to-end channel capacity -- is heavily dependent on the atmospheric channel conditions.

On Performance of Integrated Satellite HAPS Ground Communication: Aerial IRS Node vs Terrestrial IRS Node

With a motive of ubiquitous connectivity over the globe with enhanced spectral efficiency, intelligent reflecting surfaces (IRS) integrated satellite-terrestrial communications is a topic of research interest in an infrastructure-deficient remote terrains. In line with this vision, this paper entails the performance analysis of satellite-terrestrial networks leveraging both aerial and terrestrial IRS nodes, with the support of high altitude platforms over diverse fading channels including shadowed Rician, Rician, and Nakagami-$m$ fading channels. The merits of IRS in enhancing spectral efficiency is analyzed through closed-form expressions of outage probability and ergodic rate. Further, the average symbol error rate analysis for the higher-order quadrature amplitude modulation (QAM) schemes such as hexagonal QAM, rectangular QAM, cross QAM, and square QAM is performed. Practical constraints like antenna gains, path loss, and link fading are considered to characterize the satellite terrestrial links. Finally, a comparison between the high-altitude platforms based IRS node and terrestrial IRS nodes is performed and various insights are drawn under various fading scenarios and path loss conditions. This paper contribute towards understanding and potential implementation of IRS-integrated satellite-terrestrial networks for efficient and reliable communication.

Combinatorial Stochastic-Greedy Bandit

We propose a novel combinatorial stochastic-greedy bandit (SGB) algorithm for combinatorial multi-armed bandit problems when no extra information other than the joint reward of the selected set of $n$ arms at each time step $t\in [T]$ is observed. SGB adopts an optimized stochastic-explore-then-commit approach and is specifically designed for scenarios with a large set of base arms. Unlike existing methods that explore the entire set of unselected base arms during each selection step, our SGB algorithm samples only an optimized proportion of unselected arms and selects actions from this subset. We prove that our algorithm achieves a $(1-1/e)$-regret bound of $\mathcal{O}(n^{\frac{1}{3}} k^{\frac{2}{3}} T^{\frac{2}{3}} \log(T)^{\frac{2}{3}})$ for monotone stochastic submodular rewards, which outperforms the state-of-the-art in terms of the cardinality constraint $k$. Furthermore, we empirically evaluate the performance of our algorithm in the context of online constrained social influence maximization. Our results demonstrate that our proposed approach consistently outperforms the other algorithms, increasing the performance gap as $k$ grows.

Multi-hop Sub-THz-FSO: A Technique for High-rate Uninterrupted Backhauling in 6G

Moving towards $6^{\text{th}}$ generation (6G), backhaul networks require significant improvements to support new use-cases with restricted joint capacity and availability requirements. In this paper, we investigate the potentials and challenges of joint sub-teraHertz (sub-THz) and free space optical (FSO), in short sub-THz-FSO, multi-hop networks as a candidate technology for future backhaul communications. As we show, with a proper deployment, sub-THz-FSO networks have the potential to provide high-rate reliable backhauling, while there are multiple practical challenges to be address before they can be used in large-scale.

Exploiting Hybrid Terrestrial/LEO Satellite Systems for Rural Connectivity

Satellite networks are playing an important role in realizing global seamless connectivity in beyond 5G and 6G wireless networks. In this paper, we develop a comprehensive analytical framework to assess the performance of hybrid terrestrial/satellite networks in providing rural connectivity. We assume that the terrestrial base stations are equipped with multiple-input-multiple-output (MIMO) technologies and that the user has the option to associate with a base station or a satellite to be served. Using tools from stochastic geometry, we derive tractable expressions for the coverage probability and average data rate and prove the accuracy of the derived expressions through Monte Carlo simulations. The obtained results capture the impact of the satellite constellation size, the terrestrial base station density, and the MIMO configuration parameters.

Trajectory and Power Design for Aerial Multi-User Covert Communications

Unmanned aerial vehicles (UAVs) can provide wireless access to terrestrial users, regardless of geographical constraints, and will be an important part of future communication systems. In this paper, a multi-user downlink dual-UAVs enabled covert communication system was investigated, in which a UAV transmits secure information to ground users in the presence of multiple wardens as well as a friendly jammer UAV transmits artificial jamming signals to fight with the wardens. The scenario of wardens being outfitted with a single antenna is considered, and the detection error probability (DEP) of wardens with finite observations is researched. Then, considering the uncertainty of wardens' location, a robust optimization problem with worst-case covertness constraint is formulated to maximize the average covert rate by jointly optimizing power allocation and trajectory. To cope with the optimization problem, an algorithm based on successive convex approximation methods is proposed. Thereafter, the results are extended to the case where all the wardens are equipped with multiple antennas. After analyzing the DEP in this scenario, a tractable lower bound of the DEP is obtained by utilizing Pinsker's inequality. Subsequently, the non-convex optimization problem was established and efficiently coped by utilizing a similar algorithm as in the single-antenna scenario. Numerical results indicate the effectiveness of our proposed algorithm.

Trajectory and power design for aerial CRNs with colluding eavesdroppers

Unmanned aerial vehicles (UAVs) can provide wireless access services to terrestrial users without geographical limitations and will become an essential part of the future communication system. However, the openness of wireless channels and the mobility of UAVs make the security of UAV-based communication systems particularly challenging. This work investigates the security of aerial cognitive radio networks (CRNs) with multiple uncertainties colluding eavesdroppers. A cognitive aerial base station transmits messages to cognitive terrestrial users using the spectrum resource of the primary users. All secondary terrestrial users and illegitimate receivers jointly decode the received message. The average secrecy rate of the aerial CRNs is maximized by jointly optimizing the UAV's trajectory and transmission power. An iterative algorithm based on block coordinate descent and successive convex approximation is proposed to solve the non-convex mixed-variable optimization problem. Numerical results verify the effectiveness of our proposed algorithm and show that our scheme improves the secrecy performance of airborne CRNs.

Aerial-Aided mmWave VANETs Using NOMA: Performance Analysis, Comparison, and Insights

In this paper, we propose the integration of tethered flying platforms in cooperative vehicular ad hoc networks (VANETs) to alleviate the problems of rapid urbanization. In this context, we study the performance of VANETs by deriving approximate outage probability and average achievable rate expressions using tools from stochastic geometry. We compare between the usage of networked tethered flying platforms (NTFPs) and traditional roadside units (RSUs). On the other hand, the rapid increase of smart devices in vehicles and the upcoming urban air mobility (UAM) vision will congest the spectrum and require increased data rates. Hence, we use non-orthogonal multiple access (NOMA) to improve spectral efficiency and compare its performance to orthogonal access schemes. Furthermore, we utilize millimeter-wave (mmWave) frequencies for high data rates and implement a sectored beamforming model. We extensively study the system using three transmission schemes: direct, relay, and hybrid transmission. The results show that when acting as relays, NTFPs outperform RSUs for larger distances between the transmitting and the receiving vehicles, while RSUs outperform NTFPs for short distances. However, NTFPs are the best solution when acting as a source. Moreover, we find that, in most cases, direct transmission is preferred to achieve a high rate compared to other schemes. Finally, the results are summarized in two tables that provide insights into connecting VANETs by selecting the most suitable platform and type of communication for a given set of parameters, configurations, and requirements.