Spectrum congestion has motivated the recent introduction of integrated sensing and communication (ISAC) systems where radar and communications functionalities co-exist and share the same spectrum. This is accompanied by extensive research in the area of reconfigurable intelligent surfaces (RIS), thanks to their ability to improve the ISAC systems. In this paper, the physical layer security of a multiuser multiple-input single-output (MU-MISO) ISAC system is investigated when the system is subject to eavesdropping by a malicious unmanned aerial vehicle (UAV). In particular, we propose using an active RIS to maximize the achievable secrecy rate of the system through jointly designing the radar receive beamformers, the active RIS reflection coefficients matrix and the transmit beamformers at the dual-function base station of the ISAC system. This is done while taking into account a minimum radar detection signal-to-noise ratio (SNR) and total system power budget constraints. The resulting non-convex optimization problem is tackled by exploiting fractional programming (FP) and majorization-minimization (MM) techniques to achieve a solution. Our numerical results show the superiority of active RIS to achieve the goal when compared with passive RIS or with an ISAC without an RIS. Results also show that passive RIS could still be a viable solution to achieve this goal but at the expense of a much larger needed size especially when lower power budgets are available.

In this paper, we derive closed-form exact and asymptotic expressions for the symbol error rate (SER) and channel capacity when communicating over Fox's H-function fading channel. The SER expressions are obtained for numerous practically employed modulation schemes in case of single-branch and three multiple-branch diversity receivers: maximal ratio combining (MRC), equal gain combining (EGC), and selection combining (SC). The derived exact expressions are given in terms of the univariate and multivariate Fox's H-functions for which we provide a portable and efficient Python code. Since Fox's H-function fading channel represents the most generalized fading model ever presented in the literature, the derived expressions subsume most of those previously presented for all the known simple and composite fading models. Moreover, easy-to-compute asymptotic expansions are provided to easily study the behavior of the SER and channel capacity at high values of the average signal-to-noise ratio (SNR). The asymptotic expansions are also useful in comparing different modulation schemes and receiver diversity combiners. Numerical and simulation results are also provided to support the mathematical analysis and prove the validity of the obtained expressions.

In this paper, we present novel exact closed-form expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the sum of an arbitrary number of independent and non-identically distributed (i.n.i.d.) Fox's H-function random variables (RVs), which has been recently used to model fading in wireless channels. The obtained expressions are given in terms of the multivariate Fox's H-function, which has multiple implementations already available in the literature. We verify the validity of the obtained expressions using Monte Carlo simulations. Moreover, the distribution of the sum of other RVs for which no exact expressions are available are derived as special cases. This includes the alpha-mu, the extended generalized-K (EGK) and the recently investigated Fisher-Snedecor F RVs. The obtained PDF and CDF expressions can be directly used for evaluating the performance in several wireless communications scenarios, for instance, when calculating the outage probability (OP), the symbol error rate (SER) or the ergodic capacity of the H-function fading channel (or its special cases) with diversity reception as shown in this work. We also present simple asymptotic expansions for such quantities that enjoy low computational burden.

Intelligent reflecting surfaces (IRS) are considered one of the prominent technologies to be adopted in 6G and beyond networks. However, one of the main IRS limitations is restricting the communication to the reflective dimension, which means that users located behind the IRS surface cannot benefit from it. In this paper, we make use of intelligent omni-surfaces (IOS), as an alternative to IRS, in addition to unmanned aerial vehicles (UAV) to achieve secure communication in an Internet-of-Things (IoT) communication system. Specifically, we propose IOS-UAV assisted communication wherein an access point (AP) tries to send confidential information to a legitimate IoT device in presence of an eavesdropper. The UAV serves two fold; it acts as a friendly jammer that is trying to degrade the signal quality at the eavesdropper and as a source of energy to power up the IoT device via simultaneous wireless information and power transfer (SWIPT) to address the limited power available to it. We formulate an average secrecy rate maximization problem, which jointly optimizes the AP and UAV transmission powers, the UAV trajectory, IOS phase shifts and power splitting factor. The formulated problem is non-convex, therefore we exploit successive convex approximation (SCA) to tackle this issue. Simulation results show that the iterative SCA solution converges rapidly. Besides, the proposed scheme outperforms the traditional system without IOS by a gap of 140% in terms of the secrecy capacity.

Spectrally-efficient and low-latency support of local media services is expected to be provided by enabling underlay direct Device-to-Device (D2D) communication mode in future cellular networks. Interference Alignment (IA) can enhance the capacity of a wireless network by providing more degrees of freedom. In this paper, we propose using IA techniques in a D2D underlay network to enhance spectral efficiency. We compare IA transmission and traditional point-to-point (P2P) transmission from the Bit-Error-Rate (BER) and sum-rate points of view. Furthermore, we propose three grouping schemes for the D2D users into groups of 3-pairs such that IA can be applied using a limited number of signal extensions. Results demonstrate that although traditional P2P transmission can achieve better BER performance; IA transmission is still able to achieve gains in the sum rate. Also, system simulations show that the cell total D2D sum rate can be improved using IA. A gain of up to 31.8% is shown to be attainable at a reasonable transmit signal power level.

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.