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Sixth generation (6G) wireless technology is predicted to bring revolutionary changes to network sensing capabilities and allow for extraordinarily large communication capacities. Because of its unexplored frequency bands, short wavelengths, and bandwidths that provide excellent spatial resolution, the terahertz (THz) frequency range (0.1 THz–10 THz) stands out as a potential enabler. In addition to helping to address the existing spectrum shortage, the enormous bandwidth accessible at THz frequencies can clear the path for the wireless terabit-per-second (Tbps) connectivity needed for 6G networks. This article in contrast to previous surveys concentrates on the difficulties and essential technologies in THz communication. The use of intelligent reflecting surfaces (IRS) in THz communication systems is heavily emphasized. With its capacity to dynamically control electromagnetic waves, IRS technology offers a revolutionary means of addressing issues including excessive path loss and absorption losses related to THz frequencies. In the THz domain, the notion of integrated sensing and communication (ISAC) is also discussed, emphasizing its dual role in enabling data transfer and environmental sensing at the same time. This review attempts to provide a thorough knowledge of the revolutionary influence of these new technologies on future wireless networks by looking at the fundamentals, technological developments, and real-world applications of THz-IRS systems. THz communication integration with IRS and ISAC has the potential to completely transform wireless communication and open the door to incredibly fast, dependable, and intelligent network solutions. [ABSTRACT FROM AUTHOR]

This study introduces a novel approach for energy-efficient resource allocation in millimeter-wave networks, assisted by multiple intelligent reflecting surfaces (IRS). The proposed framework optimizes the dynamic ON/OFF control and phase shifts of IRS elements, along with beamforming (BF) at access points (AP), under practical constraints. Unlike existing methods, our model enhances energy efficiency (EE) by optimizing a fixed number of ON IRS elements. We present innovative algorithms, including a modified nested fractional programming (NFP) for BF and a simulated annealing (SA)-type algorithm for phase shift and element selection. Our results demonstrate a 6.5-fold improvement in EE under a realistic scenario compared to benchmark, highlighting the effectiveness of our approach as a crucial strategy for future 6G networks. [ABSTRACT FROM AUTHOR]

Wireless networking is approaching a new era, which necessitates new frequency ranges and novel strategies. With recent circuit growth, communications over the Terahertz (THz) band is proving to be a viable option because of the tremendous bandwidth and low cost. On the other hand, THz signals suffer from significant direction loss, necessitating the use of precoding. In this paper, Deep Learning (DL) based precoding techniques for upcoming 6G networks were examined, along with their complexities. Based on the signal-to-noise ratio (SNR) and spectral efficiency (SE), the proposed DL-based precoding scheme is compared to traditional model-based precoding schemes. The proposed DL-based precoding technique is ideal for 6G networks, according to simulation results. Furthermore, the proposed DL-based precoding technique has lower computational complexity, making it suitable for parallel processing and high-speed data transmission. [ABSTRACT FROM AUTHOR]

The rapid development road map of 6G networks has posed a new set of challenges to both industrial and academic sectors. On the one hand, it needs more disruptive technologies and solutions for addressing the threefold issues including enhanced mobile broadband, massive machine-type communications, and ultra-reliable and low-latency communications. On the other hand, the ever-massive number of mobile users and Internet of Things devices conveys the huge volume of traffic throughout the 6G networks. In this context, caching is one of the most feasible technologies and solutions that does not require any system architecture changes nor costly investments, while significantly improve the system performance, i.e., quality of service and resource efficiency. Ground caching models deployed at macro base stations, small-cell base stations, and mobile devices have been successfully studied and currently extended to the air done by unmanned aerial vehicles (UAVs) to deal with the challenges of 6G networks. This paper provides a comprehensive survey of UAV caching models, techniques, and applications in 6G networks. In particular, we first investigate the entire picture of caching models moving from the ground to the air as well as the related surveys on UAV communications. Then, we introduce a typical UAV caching system and describe how it works in connection with all types of the transceivers, end users, and applications and services (A&Ss). After that, we present the recent advancements and analyses of the UAV caching models and common system performance metrics. Furthermore, the UAV caching with assisted techniques, UAV caching-enabled mechanisms, and UAV caching A&Ss are discussed to demonstrate the role of UAV caching system in 6G networks. Finally, we highlight the ongoing challenges and potential research directions toward UAV caching in 6G networks. [ABSTRACT FROM AUTHOR]