The demand for relay-transmission technologies has recently been increasing. We study relay transmission using multiband to reduce transmission delay and meet the increasing demand. In the relay transmission, the relay node initiates relay transmission while receiving data on another frequency band. However, despite its potential, the difference of data rates between reception and forwarding causes data loss from buffer overflow. To solve this problem, we propose an algorithm that selects appropriate channels, such that the transmission rates become as high as possible without buffer overflow, and evaluate the effectiveness of the proposal.

Recent advances in quantum computing have prompted urgent consideration of the migration of classical cryptographic systems to post-quantum alternatives. However, it is impossible to fully understand the impact that migrating to current Post-Quantum Cryptography (PQC) algorithms will have on various applications without the actual implementation of quantum-resistant cryptography. On the other hand, PQC algorithms come with complexity and long processing times, which may impact the quality of service (QoS) of many applications. Therefore, PQC-based protocols with practical implementations across various applications are essential. This paper introduces a new framework for PQC standalone and PQC–AES (Advanced Encryption Standard) hybrid public-key encryption (PKE) protocols. Building on prior results, we focus on securing applications such as file transfer, video streaming, and chat-based communication using enhanced PQC-based protocols. The extended PQC-based protocols use a sequence number-based mechanism to effectively counter replay and man-in-the-middle attacks and mitigate standard cybersecurity attack vectors. Experimental evaluations examined encryption/decryption speeds, throughput, and processing overhead for the standalone PQC and the PQC–AES hybrid schemes, benchmarking them against traditional AES-256 in an existing client–server environment. The results demonstrate that the new approaches achieve a significant balance between security and system performance compared to conventional deployments. Furthermore, a comprehensive security analysis confirms the robustness and effectiveness of the proposed PQC-based protocols across diverse attack scenarios. Notably, the PQC–AES hybrid protocol demonstrates greater efficiency for applications handling larger data volumes (e.g., 10–100 KB) with reduced latency, underscoring the practical necessity of carefully balancing security and operational efficiency in the post-quantum migration process.

Demands for high-speed wireless connectivity are pushing the boundaries of Wireless Local Area Networks (WLANs), prompting a transition towards Terahertz (THz) technology for 6G networks. THz technology is capable of supporting higher data rates and lower latency, enabling the miniaturization and denser placements of Access Points (APs), particularly in urban environments. Joint transmission strategies, coordinating data from multiple APs, can further improve THz network performance and reliability. Despite its advantages, THz signals face challenges with signal penetration and attenuation. To tackle these issues, Intelligent Reflecting Surfaces (IRS), a planar surface made with reconfigurable meta-material elements, have emerged as a solution with the abilities to create beyond Line-of-Sight (LoS) communication and passive beamforming. In this paper, we study the channel estimation and resource allocation problem with considering the user mobility and increased system complexity. A combined clustering and Kalman Filtering (KF) approach is proposed to continuously estimate user statuses and efficiently organize network elements. The simulation results demonstrate that our approach markedly enhances the performance of joint transmission and reduces the overhead associated with channel estimation, thereby highlighting the potential of integrating THz joint transmission and IRS in future WLANs.

Access point (AP) coordinated spatial reuse with Q-learning enables efficient spectrum utilization [1]. Although sharing of transmission schedules among APs is necessary for coordination, there is no mechanism to identify the APs with which the schedules are to be shared, resulting in excess information being shared among APs. In this study, we propose a scheme to identify the interference-free APs that are not required for sharing of information by comparing Q-values. A simple simulation demonstrates that this scheme successfully reduces shared information without throughput degradation.

Using the real wireless spectrum occupancy status in 2.4 and 5 GHz bands collected at a railway station as representative of a heavy wireless LAN (WLAN) traffic environment, this paper studies the modeling of durations of busy/idle (B/I) status and its predictability based on predictability theory. We first measure and model the channel status in the heavy traffic environment over almost all of the WLAN channels at 2.4 GHz and 5 GHz bands in a busy (rush hour) period and non-busy period. Then, using two selected channels at 2.4 GHz and 5 GHz bands, we analyze the upper bound (UB) and lower bound (LB) of predictability of the busy/idle durations based on predictability theory. The analysis shows that the LB predictability of durations can be easily increased by changing their probability distribution. Based on this property, we introduce the data categorization (DC) method. By categorizing the busy/idle durations into different streams, the proposed data categorization can improve the prediction performance of some streams with large LB predictability, even if it employs a simple low-complexity auto-regressive (AR) predictor.