IRS Assisted MIMO Full Duplex: Rate Analysis and Beamforming Under Imperfect CSI

Intelligent reflecting surfaces (IRS) have emerged as a promising technology to enhance the performance of wireless communication systems. By actively manipulating the wireless propagation environment, IRS enables efficient signal transmission and reception. In recent years, the integration of IRS with full-duplex (FD) communication has garnered significant attention due to its potential to further improve spectral and energy efficiencies. IRS-assisted FD systems combine the benefits of both IRS and FD technologies, providing a powerful solution for the next generation of cellular systems. In this manuscript, we present a novel approach to jointly optimize active and passive beamforming in a multiple-input-multiple-output (MIMO) FD system assisted by an IRS for weighted sum rate (WSR) maximization. Given the inherent difficulty in obtaining perfect channel state information (CSI) in practical scenarios, we consider imperfect CSI and propose a statistically robust beamforming strategy to maximize the ergodic WSR. Additionally, we analyze the achievable WSR for an IRS-assisted MIMO FD system under imperfect CSI by deriving both the lower and upper bounds. To tackle the problem of ergodic WSR maximization, we employ the concept of expected weighted minimum mean squared error (EWMMSE), which exploits the information of the expected error covariance matrices and ensures convergence to a local optimum. We evaluate the effectiveness of our proposed design through extensive simulations. The results demonstrate that our robust approach yields significant performance improvements compared to the simplistic beamforming approach that disregards CSI errors, while also outperforming the robust half-duplex (HD) system considerably

Robust Beamforming for IRS Aided MIMO Full Duplex Systems

In this paper, a novel robust beamforming for an intelligent reflecting surface (IRS) assisted FD system is presented. Since perfect channel state information (CSI) is often challenging to acquire in practice, we consider the case of imperfect CSI and adopt a statistically robust beamforming approach to maximize the ergodic weighted sum rate (WSR). We also analyze the achievable WSR of an IRS-assisted FD with imperfect CSI, for which the lower and the upper bounds are derived. The ergodic WSR maximization problem is tackled based on the expected Weighted Minimum Mean Squared Error (WMMSE), which is guaranteed to converge to a local optimum. The effectiveness of the proposed design is investigated with extensive simulation results. It is shown that our robust design achieves significant performance gain compared to the naive beamforming approaches and considerably outperforms the robust Half-Duplex (HD) system.

Full Duplex Joint Communications and Sensing for 6G: Opportunities and Challenges

The paradigm of joint communications and sensing (JCAS) envisions a revolutionary integration of communication and radar functionalities within a unified hardware platform. This novel concept not only opens up unprecedented possibilities, but also presents unique challenges. Its success is highly dependent on efficient full-duplex (FD) operation, which has the potential to enable simultaneous transmission and reception within the same frequency band. While ongoing research explores the potential of JCAS, there are related avenues of investigation that hold tremendous potential to profoundly transform the sixth generation (6G) and beyond cellular networks. This article sheds light on the new opportunities and challenges presented by JCAS by taking into account the key technical challenges of FD systems. Unlike simplified JCAS scenarios, we delve into the most comprehensive configuration, encompassing uplink (UL) and downlink (DL) users, as well as monostatic and bistatic radars, all harmoniously coexisting to jointly push the boundaries of both the communications and sensing performance. The performance improvements introduced by this advancement bring forth numerous new challenges, each meticulously examined and expounded upon.

THz-Empowered UAVs in 6G: Opportunities, Challenges, and Trade-Offs

Envisioned use cases of unmanned aerial vehicles (UAVs) impose new service requirements in terms of data rate, latency, and sensing accuracy, to name a few. If such requirements are satisfactorily met, it can create novel applications and enable highly reliable and harmonized integration of UAVs in the 6G network ecosystem. Towards this, terahertz (THz) bands are perceived as a prospective technological enabler for various improved functionalities such as ultra-high throughput and enhanced sensing capabilities. This paper focuses on THzempowered UAVs with the following capabilities: communication, sensing, localization, imaging, and control. We review the potential opportunities and use cases of THz-empowered UAVs, corresponding novel design challenges, and resulting trade-offs. Furthermore, we overview recent advances in UAV deployments regulations, THz standardization, and health aspects related to THz bands. Finally, we take UAV to UAV (U2U) communication as a case-study to provide numerical insights into the impact of various system design parameters and environment factors.

Evolution of Non-Terrestrial Networks From 5G to 6G: A Survey

Non-terrestrial networks (NTNs) traditionally had certain limited applications. However, the recent technological advancements opened up myriad applications of NTNs for 5G and beyond networks, especially when integrated into terrestrial networks (TNs). This article comprehensively surveys the evolution of NTNs highlighting its relevance to 5G networks and essentially, how it will play a pivotal role in the development of 6G and beyond wireless networks. The survey discusses important features of NTNs integration into TNs by delving into the new range of services and use cases, various architectures, and new approaches being adopted to develop a new wireless ecosystem. Our survey includes the major progresses and outcomes from academic research as well as industrial efforts. We first start with introducing the relevant 5G use cases and general integration challenges such as handover and deployment difficulties. Then, we review the NTNs operations in mmWave and their potential for the internet of things (IoT). Further, we discuss the significance of mobile edge computing (MEC) and machine learning (ML) in NTNs by reviewing the relevant research works. Furthermore, we also discuss the corresponding higher layer advancements and relevant field trials/prototyping at both academic and industrial levels. Finally, we identify and review 6G and beyond application scenarios, novel architectures, technological enablers, and higher layer aspects pertinent to NTNs integration.