Abstract:Beyond diagonal reconfigurable intelligent surfaces (BD-RIS) have emerged as a transformative technology for enhancing wireless communication by intelligently manipulating the propagation environment. This paper explores the potential of BD-RIS in improving cognitive radio enabled multilayer non-terrestrial networks (NTNs). It is assumed that a high-altitude platform station (HAPS) has set up the primary network, while an uncrewed aerial vehicle (UAV) establishes the secondary network in the HAPS footprint. We formulate a joint optimization problem to maximize the secrecy rate by optimizing BD-RIS phase shifts and the secondary transmitter power allocation while controlling the interference temperature from the secondary network to the primary network. To solve this problem efficiently, we decouple the original problem into two sub-problems, which are solved iteratively by relying on alternating optimization. Simulation results demonstrate the effectiveness of BD-RIS in cognitive radio-enabled multilayer NTNs to accommodate the secondary network while satisfying the constraints imposed from the primary network.
Abstract:Beyond diagonal reconfigurable intelligent surfaces (BD-RIS) have emerged as a transformative technology for enhancing wireless communication by intelligently manipulating the propagation environment. Its interconnected elements offer enhanced control over signal redirection, making it a promising solution for integrated terrestrial and non-terrestrial networks (NTNs). This paper explores the potential of BD-RIS in improving cognitive radio enabled multilayer non-terrestrial networks. We formulate a joint optimization problem that maximizes the achievable spectral efficiency by optimizing BD-RIS phase shifts and secondary transmitter power allocation while controlling the interference temperature from the secondary network to the primary network. To solve this problem efficiently, we decouple the original problem and propose a novel solution based on an alternating optimization approach. Simulation results demonstrate the effectiveness of BD-RIS in cognitive radio enabled multilayer NTNs.
Abstract:Beyond Diagonal Reconfigurable Intelligent Surfaces (BD-RIS) represent a groundbreaking innovation in sixth-generation (6G) wireless networks, enabling unprecedented control over wireless propagation environments compared to conventional diagonal RIS (D-RIS). This survey provides a comprehensive analysis of BD-RIS, detailing its architectures, operational principles, and mathematical modeling while highlighting its performance benefits. BD-RIS classifications, including single-connected, fully-connected, and group-connected architectures, and their reflective, transmissive, hybrid, and multi-sector operating modes are examined. Recent advances in BD-RIS-enabled 6G networks are reviewed, focusing on critical areas such as channel estimation, sum-rate and spectral efficiency optimization, energy efficiency enhancement, and security. The survey identifies fundamental challenges in BD-RIS research, including hardware design limitations, adaptive channel estimation, and the impact of non-ideal hardware effects. Future research directions for BD-RIS are proposed, emphasizing the integration of artificial intelligence and machine learning (AI/ML), joint optimization of communication and sensing, and enhanced physical layer security (PLS). This study concludes by underscoring BD-RIS's transformative potential to redefine 6G wireless networks, offering valuable insights and lessons for future research and development.
Abstract:Recent advancements in onboard satellite communication have significantly enhanced the ability to dynamically modify the radiation pattern of a Direct Radiating Array, which is essential for both conventional communication satellites like GEO and those in lower orbits such as LEO. This is particularly relevant for communication at 28 GHz, a key frequency in the mmWave spectrum, used for high-bandwidth satellite links and 5G communications. Critical design factors include the number of beams, beamwidth, and SLL for each beam. However, in multibeam scenarios, balancing these design factors can result in uneven power distribution, leading to over-saturation in centrally located antenna elements due to frequent activations. This paper introduces a GA-based approach to optimize beamforming coefficients by modulating the amplitude component of the weight matrix, while imposing a constraint on activation instances per element to avoid over-saturation in the RF chain. The proposed method, tested on an 16x16 DRA patch antenna array at 28 GHz for a CubeSat orbiting at 500 km, demonstrates how the algorithm efficiently meets beam pattern requirements and ensures uniform activation distribution. These findings are particularly relevant for emerging satellite systems and 5G networks operating in the mmWave spectrum.
Abstract:The demand for cost-effective, low-profile user terminals for satellite communications supporting multicast services for Geostationary Orbit (GEO) satellites, has become a key focus for many Direct-to-Home (DTH) providers where the high data rates in the downlink are required. Planar antenna arrays with increased frequency bandwidth and improved ratio using meta-surfaces are considered as an effective solution for such systems. This paper presents a low-cost, aperture-coupled metasurface-enhanced patch antenna, operating within the 10.7-12.7 GHz frequency range. The antenna is designed to achieve a realized gain of at least 27 dBi across the band of interest using 32 x 32 array antennas distributed in a rectangular lattice. Initially configured for linear polarization, the antenna can be upgraded to support dual or circular polarization if required.
Abstract:Reconfigurable intelligent surface (RIS) technology has emerged as a promising enabler for next-generation wireless networks, offering a paradigm shift from passive environments to programmable radio wave propagation. Despite the potential of diagonal RIS (D-RIS), its limited wave manipulation capability restricts performance gains. In this paper, we investigate the burgeoning concept of beyond-diagonal RIS (BD-RIS), which incorporates non-diagonal elements in its scattering matrix to deliver more fine-grained control of electromagnetic wavefronts. We begin by discussing the limitations of traditional D-RIS and introduce key BD-RIS architectures with different operating modes. We then highlight the features that make BD-RIS particularly advantageous for 6G IoT applications, including advanced beamforming, enhanced interference mitigation, and flexible coverage. A case study on BD-RIS-assisted vehicle-to-vehicle (V2V) communication in an underlay cellular network demonstrates considerable improvements in spectral efficiency when compared to D-RIS and conventional systems. Lastly, we present current challenges such as hardware design complexity, channel estimation, and non-ideal hardware effects, and propose future research directions involving AI-driven optimization, joint communication and sensing, and physical layer security. Our findings illustrate the transformative potential of BD-RIS in shaping high-performance, scalable, and reliable 6G IoT networks.
Abstract:The reconfigurable intelligent surface (RIS) technology shows great potential in sixth-generation (6G) terrestrial and non-terrestrial networks (NTNs) since it can effectively change wireless settings to improve connectivity. Extensive research has been conducted on traditional RIS systems with diagonal phase response matrices. The straightforward RIS architecture, while cost-effective, has restricted capabilities in manipulating the wireless channels. The beyond diagonal reconfigurable intelligent surface (BD-RIS) greatly improves control over the wireless environment by utilizing interconnected phase response elements. This work proposes the integration of unmanned aerial vehicle (UAV) communications and BD-RIS in 6G NTNs, which has the potential to further enhance wireless coverage and spectral efficiency. We begin with the preliminaries of UAV communications and then discuss the fundamentals of BD-RIS technology. Subsequently, we discuss the potential of BD-RIS and UAV communications integration. We then proposed a case study based on UAV-mounted transmissive BD-RIS communication. Finally, we highlight future research directions and conclude this work.
Abstract:This paper examines integrated satellite-terrestrial networks (ISTNs) in urban environments, where terrestrial networks (TNs) and non-terrestrial networks (NTNs) share the same frequency band in the C-band which is considered the promising band for both systems. The dynamic issues in ISTNs, arising from the movement of low Earth orbit satellites (LEOSats) and the mobility of users (UEs), are addressed. The goal is to maximize the sum rate by optimizing link selection for UEs over time. To tackle this challenge, an efficient iterative algorithm is developed. Simulations using a realistic 3D map provide valuable insights into the impact of urban environments on ISTNs and also demonstrates the effectiveness of the proposed algorithm.
Abstract:This work proposes a T-RIS-equipped LEO satellite communication in cognitive radio-enabled integrated NTNs. In the proposed system, a GEO satellite operates as a primary network, and a T-RIS-equipped LEO satellite operates as a secondary IoT network. The objective is to maximize the sum rate of T-RIS-equipped LEO satellite communication using downlink NOMA while ensuring the service quality of GEO cellular users. Our framework simultaneously optimizes the total transmit power of LEO, NOMA power allocation for LEO IoT (LIoT) and T-RIS phase shift design subject to the service quality of LIoT and interference temperature to the primary GEO network. To solve the non-convex sum rate maximization problem, we first adopt successive convex approximations to reduce the complexity of the formulated optimization. Then, we divide the problem into two parts, i.e., power allocation of LEO and phase shift design of T-RIS. The power allocation problem is solved using KKT conditions, while the phase shift problem is handled by Taylor approximation and semidefinite programming. Numerical results are provided to validate the proposed optimization framework.
Abstract:In this paper, optimal linear precoding for the multibeam geostationary earth orbit (GEO) satellite with the multi-user (MU) multiple-input-multiple-output (MIMO) downlink scenario is addressed. Multiple-user interference is one of the major issues faced by the satellites serving the multiple users operating at the common time-frequency resource block in the downlink channel. To mitigate this issue, the optimal linear precoders are implemented at the gateways (GWs). The precoding computation is performed by utilizing the channel state information obtained at user terminals (UTs). The optimal linear precoders are derived considering beamformer update and power control with an iterative per-antenna power optimization algorithm with a limited required number of iterations. The efficacy of the proposed algorithm is validated using the In-Lab experiment for 16X16 precoding with multi-beam satellite for transmitting and receiving the precoded data with digital video broadcasting satellite-second generation extension (DVB- S2X) standard for the GW and the UTs. The software defined radio platforms are employed for emulating the GWs, UTs, and satellite links. The validation is supported by comparing the proposed optimal linear precoder with full frequency reuse (FFR), and minimum mean square error (MMSE) schemes. The experimental results demonstrate that with the optimal linear precoders it is possible to successfully cancel the inter-user interference in the simulated satellite FFR link. Thus, optimal linear precoding brings gains in terms of enhanced signal-to-noise-and-interference ratio, and increased system throughput and spectral efficiency.