The fluid antenna system (FAS) has emerged as a disruptive technology that promises outstanding diversity and multiplexing gains comparable to or better than multiple-input multiple-output (MIMO), but without the issues of channel state information (CSI) acquisition and the advantage of requiring smaller physical spaces of upcoming user devices. This work investigates the potentialities of this technology to provide secure transmissions by analysing the secrecy outage probability (SOP) of two different implementations of FAS undergoing spatial correlated Nakagami- $m$ fading by assuming $i)$ non-diversity FAS and maximum-gain combining-FAS (MGC-FAS) diversity scheme at the legitimate node and $ii)$ multiple-antennas performing maximal ratio combining (MRC) at the eavesdropper. Specifically, using a novel asymptotic matching method, a simple and accurate closed-form approximations to the end-to-end signal-to-noise-ratio (SNR) distributions are derived in terms of well-known functions without incurring tricky functions or multi-fold integrals. Our findings reveal that the secrecy performance of the MGC-FAS beats the non-diversity FAS counterpart only when $i)$ the antenna size of the FAS tube is large enough, and $ii)$ the average SNR of the legitimate path is much greater than that of the eavesdropper link. Finally, numerical results validate our approximations of the SOP for the MGC-FAS scheme and demonstrate its accuracy under different FAS conditions.

New perspectives for wireless communications have brought new techniques, such as a very large number of antennas at a base station (BS) serving multiple user terminals (UTs) with a single antenna each, known as massive MIMO (M-MIMO). M-MIMO linear detectors, such as maximal-ratio combining (MRC), zero-forcing (ZF) or minimum-mean-square error (MMSE) can achieve excellent performance with low complexity due to the channel hardening property. However, imperfect channel estimation produces a penalty in the performance. An average bit error rate (BER) performance analysis over time-invariant channel is presented for M-MIMO systems under imperfect channel estimation in contrast with most of MMIMO literature that uses the ergodic capacity approach. Closed-form expressions and bounds to evaluate the average BER are derived for MRC, ZF and MMSE detectors in a unicellular environment considering M-QAM modulation. Furthermore, an expression to evaluate the normalized signal-to-noise ratio (Eb=N0) penalty due to the imperfect channel estimation is presented. Montecarlo numerical simulations are used to verify the tightness of the derived equations which are a function of the number of BS antennas, number of users, coherence time interval, number of pilot symbols and the Eb=N0 of pilot and data symbols used for channel estimation and data detection.

The modernization of the current electric power grid into a smart grid requires the integration of advanced instrumentation, automation, and communication technologies to optimize efficiency, safety, and reliability. In traditional power grids, communication and control tasks are concentrated in substations, limiting their coverage to high-power equipment. As distributed energy resources increase in different sections of the grid, power flow becomes bi-directional. This requires monitoring and control at the Transmission and Distribution (T&D) level, which forms the largest portion of the power grid. To achieve efficient energy flow management and enable consumer participation in demand management, the integration of information and communication technologies (ICTs) is essential. Wireless sensor networks (WSNs) have been identified as a suitable solution for communications within the distribution network. An ongoing challenge, however, is the definition of the best candidates to solve this problem, among the currently available wireless technologies. This paper reviews different wireless communication technologies that provide robustness, reliability, speed, scalability, and cost-effectiveness for monitoring distribution lines. An outline of the architecture for smart grid communications, the definition of sensor network requirements for power line environments, and an overview of specific studies focusing on technology comparisons are the main contributions of this paper. The purpose of this review is to delineate current technologies in order to establish potential future research directions within the field.

Sparse code multiple access (SCMA) is an interesting proposal for supporting massive machine-type communications (mMTC) in future mobile networks. In this use case, mobile networks connect to Internet of Things (IoT) devices, which may have low computational processing capacities, and thus, they are exposed to different security threats. In this regard, physical-layer security (PLS) arises as an alternative technique to protect information. This work proposes a new scheme based on the design of unknown codebooks to an external eavesdropper aiming at guaranteeing PLS in the uplink of SCMA systems over generalized $\kappa$ - $\mu$ fading channels. Considering that the SCMA codebook design can be realized from the rotation of base quadrature-amplitude modulation (QAM) constellations using the signal-space-diversity (SSD) technique, a novel upper-bound expression to calculate the average bit error probability (ABEP) of multidimensional SSD systems is derived. Then, a metric to select the best rotation matrices is determined. With this, a set of optimal and suboptimal rotation matrices can be acquired. A strategy to obtain secret keys in the SCMA system is presented by considering imperfect channel estimation. The secret keys are used to select matrices for rotating the base QAM constellations used in the codebooks generation. Finally, an uncoded and turbo-encoded SCMA system is evaluated using Monte Carlo simulations. The results show that our proposal ensures a near-optimal SCMA performance while the eavesdropper cannot decode the information.

This paper investigates the outage performance of the downlink of a wireless network, where a base station communicates with two users using the Rate-Splitting Multiple Access (RSMA) protocol. To overcome obstacles that block direct transmission, a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is used to enable communication. The users are positioned on opposite sides of the STAR-RIS, which operates under a mode-switching protocol, assigning elements for either transmission or reflection. The channels are assumed to undergo Rician fading, and the system performance is analyzed considering the correlation effects caused by closely spaced STAR-RIS elements, for which the model employed to generate correlated channels is introduced. Additionally, at the users’ receiver side, we consider that the decoding of users’ messages is subject to imperfect successive interference cancellation (SIC). An approximate analytical expression is also derived for the scenario with uncorrelated STAR-RIS elements and imperfect SIC. Monte-Carlo simulations further explore the system performance, focusing on key parameters such as the number of STAR-RIS elements, channel-correlation factor, power allocation factors of common and private streams relative to the RSMA protocol, and error factor of imperfect SIC. This work’s contributions provide a deeper understanding of the impact of correlated channels and imperfect SIC on STAR-RIS-aided networks, offering insights for optimizing performance under realistic deployment conditions.

The growing complexity and uncertainty in modern power systems—driven by increased integration of renewable energy sources and variable loads—underscore the need for robust tools to assess dynamic stability. This paper presents an enhanced methodology for modal analysis that combines Adaptive Variational Mode Decomposition (A-VMD) with Prony’s method. A novel energy-based selection mechanism is introduced to determine the optimal number of intrinsic mode functions (IMFs), improving the decomposition’s adaptability and precision. The resulting modes are analyzed to estimate modal frequencies and damping ratios. Validation is conducted using both synthetic datasets and real synchrophasor measurements from Ecuador’s national power grid under ambient and disturbed operating conditions. The proposed approach is benchmarked against established techniques, including a matrix pencil, conventional VMD-Prony, and commercial tools such as WAProtector and DIgSILENT PowerFactory. The results demonstrate that A-VMD consistently delivers more accurate and robust performance, especially for low signal-to-noise ratios and low-energy ambient conditions. These findings highlight the method’s potential for real-time oscillation mode identification and small-signal stability monitoring in wide-area power systems.