Wireless Powered Underground Sensor Networks (WPUSNs) extend the lifetime of underground Internet of Things (IoT) through Radio Frequency (RF) harvesting technology. However, severe transmission attenuation and dynamic Quality of Service (QoS) requirements often lead to energy imbalance and waste issues in WPUSNs. To address the challenges, we introduce a recycling mechanism that enables nodes to harvest energy from each other, thereby proposing the recycling WPUSN. Under this framework, the time allocation strategy is key to balancing energy harvesting and transmission performance. We take time slot as the optimization variable and formulate an energy efficiency maximization problem under heterogeneous QoS constraints. To solve this nonconcave fractional programming problem, we develop a Quadratic Transform-based Projected (QTP) Algorithm, which iteratively applies Karush–Kuhn–Tucker (KKT) conditions and projection operations to approximate the optimal solution. The simulation results demonstrate that the proposed method improves energy efficiency performance by 17.454% and converges 70 times faster compared with the commercial optimization solvers. The proposed recycling WPUSN opens up new prospects for sustainable underground environmental monitoring.

Low-altitude economy networking (LAENet) aims to deploy various aerial vehicles to support diverse services, where data collection from edge devices via unmanned aerial vehicles (UAVs) is a critical task. The key challenge lies in jointly optimizing energy consumption and data freshness in spectrum-constrained and eavesdropping-prone low-altitude environments during the data collection process. Although deep reinforcement learning (DRL) has become a viable solution for UAV-assisted data collection, the RL agent still has limited ability to obtain and utilize informative feedback from complex low-altitude environments. In this paper, we propose a large language model (LLM)-enhanced DRL framework for secure data collection in the LAENet, where we leverage an LLM to process environmental feedback for the RL agent. Specifically, we employ the LLM as (i) a state processor to transform basic environmental observations into task-aligned representations, (ii) a reward designer to generate enriched reward signals that guide the agent's actions toward the optimization objective, and (iii) a simulator to construct a virtual LAENet environment for evaluating enhanced state-reward pairs before policy training. Theoretical analysis and numerical results demonstrate that the proposed LLM-enhanced DRL framework achieves faster convergence, improved training stability, and superior performance compared with state-of-the-art baselines.

Satellite networks are crucial for future 6G communications, offering global coverage. However, traditional Transmission Control Protocol (TCP) struggles with poor stability in dynamic satellite networks. In contrast, QUIC is capable of providing stability in such environments thanks to features like seamless connection migration. Nevertheless, the loss detection and recovery strategy of QUIC needs improvement in satellite networks with relatively high transmission errors. To address this, we propose Polar-QUIC, an adaptive packet-level polar coding-assisted QUIC scheme. By leveraging the robust error correction capabilities of polar codes, we design a packet-level encoder/decoder, loss detection tuning module, and adaptive redundancy module that combines packet loss rate and congestion window size. Experimental results demonstrate that Polar- QUIC effectively reduces the average Download Completion Time (DCT) of QUIC in satellite networks. Specifically, Polar-QUIC minimizes the average DCT by up to 35.8% and 74.5%, respectively, compared to general forward error correction schemes such as Reed-Solomon Codes and Random Linear Codes.

This research investigates the digital-to-analog converter (DAC) free architecture for the digital reconfigurable intelligent surface (RIS) system, where the transmission lines are implemented for reflection coefficient (RC) control to reduce power consumption. In the proposed architecture, the radio frequency (RF) switch based phase shifter is considered. By using a single-pole four-throw (SP4T) switch to simultaneously control the RCs of a group of elements, a 2-bit phase shifter is realized for passive beam steering. A novel modulation scheme is developed to explore the cost effectiveness, which approaches the performance of traditional quadrature amplitude modulation (QAM). Specifically, to overcome the limitation of the phase shift bits, joint frequency-shift and phase-rotation operations are applied to the constellation points. The simulation and experimental results demonstrate that the proposed architecture is capable of providing an ideal transmission performance. Moreover, 64- and 256-QAM modulation schemes could be implemented by expanding the elements and phase bits.

Multiple-antenna backscatter is emerging as a promising approach to combat the cascaded backscatter channel fading to offer a high data rate for ambient backscatter communication (AmBC). However, related designs in AmBC fail to provide both diversity and multiplexing gains to backscatter tags. To address this issue, in this paper, we present a unified generalized space-time shift keying (GSTSK)-Backscatter architecture for AmBC to strike a flexible tradeoff between the attainable diversity and multiplexing gains in an efficient but low-complexity manner. Moreover, taking the non-identically distributed characteristics of the backscatter channel into account, we first derive asymptotic BER bounds for both the source and backscatter signals, which are verified by simulation results. Furthermore, we propose a residual- and threshold-based joint error correction mechanism (JECM) and design the near-optimal and low-complexity detector for GSTSK-Backscatter systems. Simulation results validate the analysis and show that our proposed JECM-based detector approaches the optimal detector and balances the BER and complexity performance.

In this paper, generalized space-time block-coded (GSTBC) spatial modulation (SM)-assisted reconfigurable intelligent surface (RIS) structures are designed for three communication scenarios, where RIS works as a transmitter, passive relay as well as active relay. Specifically, the information bits are first mapped to an appropriate GSTBC-SM symbol according to the required transmit rate and diversity order. Then, the mapped GSTBC-SM symbol is transmitted by the based station or the RIS elements based on the communication scenario. Both the signal detector and the upper bounds of average bit error probability are derived for the three cases, which are verified by the simulation results. Simulation results show that the proposed GSTBC-SM-RIS scheme is capable of providing a significant performance gain over the existing SM-RIS scheme, as well as the conventional GSTBC-SM counterpart.