In this paper, we propose a Sustainable Sensing Federated Learning (S2FL) system where Internet-of-Things (IoT) devices and mobile users harvest energy wirelessly to perform data sensing, local Federated Learning (FL) training, and model update transmissions. We formulate a joint optimization problem that considers transmission power, CPU frequency, bandwidth allocation, and time allocation to maximize long-term learning efficiency. To solve this complex and dynamic problem, we develop an algorithm that integrates Deep Reinforcement Learning (DRL) with optimization techniques, leveraging the Deep Deterministic Policy Gradient (DDPG) algorithm for time allocation and a Lagrangian-Based Block Coordinate Descent (BCD) Method for per-slot resource optimization. Simulation results demonstrate that our proposed DDPG-based DRL-S2FL algorithm significantly outperforms benchmark schemes, achieving up to 15 % higher average reward compared to Deep Q-Networks (DQN) and 40 % greater performance than Random strategies. This work highlights the effectiveness of combining advanced optimization techniques with deep reinforcement learning to enhance federated learning performance in dynamic wireless environments.

Satellite Internet of Things (IoT) network plays a crucial role in providing global coverage. To improve the efficient utilization of spectral and hardware resources in the satellite communications, integrated sensing and communication (ISAC) has attracted considerable attention. In addition, the greater broadcast nature of the satellite-terrestrial integrated network makes it extremely vulnerable to illegal eavesdropper (Eve). In this paper, we adopt non-orthogonal multiple access (NOMA) to support more users for the ISAC of a low earth orbit satellite system, with well-designed precoding according to whether the channel state information (CSI) of the Eve is perfect to ensure security. First, a joint precoding optimization problem is proposed to maximize the sum secrecy rate (SSR) of multiple users by considering the perfect CSI of the Eve. Then, we formulate a secure precoding optimization problem based on the imperfect CSI of the Eve, aiming to maximize the SSR of multiple users via artificial jamming. To address the non-convexity of the optimization problems, we transform them into the convex ones based on successive convex approximation, which includes Taylor’s approximation, arithmetic-geometric mean inequality, and linear matrix inequality. In addition, semi-definite relaxation and iterative penalty function methods are respectively used to optimize the secure precoding problems in the two cases: perfect CSI and imperfect CSI. Simulation results show that the proposed NOMA-ISAC scheme improves the SSR compared to the traditional time division multiple access while ensuring the sensing performance.

Vehicle road cooperation systems are the vital components of intelligent transportation systems, destined to play an irreplaceable role in the future smart cites. Such systems are mandated to achieve elevated data rates, ultralow latency, and enhanced reliability. To meet these requirements, we incorporate full-duplex (FD) and rate splitting multiple access (RSMA) into vehicle road cooperation systems and propose a downlink FD RSMA vehicle road cooperation system. More importantly, we introduce a crucial metric to evaluate the influence of the delay constraints on the system performance. Specifically, analytical expressions for the effective capacity of the nearby vehicle and the distant pedestrian are derived. We also provide the approximate expressions for the effective capacity at the low and high-signal-to-noise ratios (SNRs) and the upper bound on the effective capacity to gain further insights. Furthermore, we expand our evaluation to include both throughput and energy efficiency for the FD RSMA vehicle road cooperation system. Results illustrate that: the effective capacity of the nearby vehicle increases with the increasing transmitted power at low SNRs and stabilizes at a constant level at high SNRs. Conversely, the effective capacity of the distant pedestrian increases continuously with the higher transmitted power. The effective capacities of the vehicle and pedestrian are influenced by various factors, such as the transmitted power, power allocation coefficients, and Quality-of-Service exponent.

In this paper, we investigate the physical layer security for multi-beam satellite communications in the presence of multiple eavesdroppers (Eves). In particular, a worst-case eavesdropping scheme is considered. To achieve a positive secrecy rate, we consider a non-orthogonal multiple access (NOMA) scheme with imperfect channel state information on Eves. Fur-thermore, we design a robust precoding algorithm to maximize the achievable secrecy rate of legitimate ground user equipments, which satisfies the quality of service for each user, secure outage probability constraint and the NOMA decoding order between legitimate users. In contrast to the conventional total transmit power constraint, the algorithm is designed under joint total and per-beam transmit power constraints. We first combine the decomposition-based large deviation inequality, the arithmetic-geometric mean inequality with a penalty function iterative algorithm to solve the non-convex precoding problem, and further analyze the computational complexity of the algorithm. Simulation results verify the robustness and superiority of the proposed algorithm.

We investigate multi-user physical layer security assisted by an unmanned aerial vehicle (UAV) for multi-beam satellite communications in the presence of an eavesdropper (Eve) within the same beam. In particular, the UAV is exploited as a jammer that deliberately generates artificial noise to confuse Eve. To achieve a positive secrecy rate, we consider a non-orthogonal multiple access (NOMA) scheme with imperfect channel state information at the user and Eve. Specifically, we design a robust precoding algorithm to maximize the minimum achievable secrecy rate that satisfies the quality of service for each user and the NOMA decoding order between legitimate users in each beam. In addition, the algorithm is designed under joint total and per-beam transmit power constraints. We first combine the Bernstein-type inequality, the arithmetic-geometric mean inequality with a semi-definite relaxation iterative algorithm to solve the non-convex problem, and further analyze the complexity of the proposed precoding design. Simulation results show that the algorithm significantly improves the security performance.

This paper investigates the secure performance of multi‐antenna decode‐and‐forward (DF) relaying networks where the Nakagami‐ m fading channel is taken into account. In practice, the joint impact of residual transceiver hardware impairments (HIs) and channel estimation errors (CEEs) on the outage probability (OP) and intercept probability (IP) are taken into account. Considering HIs and CEEs, an optimal transmit antenna selection scheme is proposed to enhance the secure performance and then a collaborative eavesdropping scheme is proposed. More specifically, they derive exact closed‐form expressions for the outage and intercept probabilities. To obtain more useful insights the asymptotic behaviours for the OP are examined in the high signal‐to‐noise ratio (SNR) regime and the diversity orders are obtained and discussed. Simulation results confirm the analytical derivations and demonstrate that: (i) As the power distribution coefficient increases, OP decreases, while IP increases; (ii) There exist error floors for the OP at high SNRs, which is determined by CEEs; (iii) The secure performance can be improved by increasing the number of source antennas and artificial noise quantisation coefficient, while as the number of eavesdropping increases, the security of the system is reduced; (iv) There is a trade‐off between the OP and IP.

In this study, the secrecy performance of the classic Wyner's wiretap model over shadowed fading channels is studied. More specifically, the authors derive two analytical expressions for the lower bound of secure outage probability at high signal‐to‐noise ratio regime and the probability of strictly positive secrecy capacity over shadowed fading channels, respectively. As there exist infinite series in the two derived expressions, they further obtain two simple and explicit approximate expressions for the lower bound of secure outage probability and the probability of strictly positive secrecy capacity with the aid of the moment matching method. It is shown that the match between the analytical results and simulations is very excellent for all parameters under considerations.