Noise Modulation over Wireless Energy Transfer: JEIH-Noise Mod

This letter presents an innovative energy harvesting (EH) and communication scheme for Internet of Things (IoT) devices by utilizing the emerging noise modulation (Noise-Mod) technique. Our proposed approach embeds information into the mean value of real Gaussian noise samples, enabling simultaneous power transfer and data transmission. We analyze our system under the Rician fading channels with path loss and derive the bit error probability (BEP) expression. Our simulation results demonstrate that the proposed scheme outperforms conventional modulation schemes in terms of energy harvesting capability across various channel conditions. This scheme offers a novel solution by directly embedding data into the noise-modulated signal to enable information decoding through mean-based detection. Furthermore, it increases energy harvesting capability thanks to the utilized Gaussian waveform.

Modern Base Station Architecture: Enabling Passive Beamforming with Beyond Diagonal RISs

Beamforming plays a crucial role in millimeter wave (mmWave) communication systems to mitigate the severe attenuation inherent to this spectrum. However, the use of large active antenna arrays in conventional architectures often results in high implementation costs and excessive power consumption, limiting their practicality. As an alternative, deploying large arrays at transceivers using passive devices, such as reconfigurable intelligent surfaces (RISs), offers a more cost-effective and energy-efficient solution. In this paper, we investigate a promising base station (BS) architecture that integrates a beyond diagonal RIS (BD-RIS) within the BS to enable passive beamforming. By utilizing Takagi's decomposition and leveraging the effective beamforming vector, the RIS profile can be designed to enable passive beamforming directed toward the target. Through the beamforming analysis, we reveal that BD-RIS provides robust beamforming performance across various system configurations, whereas the traditional diagonal RIS (D-RIS) exhibits instability with increasing RIS size and decreasing BS-RIS separation-two critical factors in optimizing RIS-assisted systems. Comprehensive computer simulation results across various aspects validate the superiority of the proposed BS-integrated BD-RIS over conventional D-RIS architectures, showcasing performance comparable to active analog beamforming antenna arrays.

Efficient Localization with Base Station-Integrated Beyond Diagonal RIS

This paper introduces a novel approach to efficient localization in next-generation communication systems through a base station (BS)-enabled passive beamforming utilizing beyond diagonal reconfigurable intelligent surfaces (BD-RISs). Unlike conventional diagonal RISs (D-RISs), which suffer from limited beamforming capability, a BD-RIS provides enhanced control over both phase and amplitude, significantly improving localization accuracy. By conducting a comprehensive Cram\'er-Rao lower bound (CRLB) analysis across various system parameters in both near-field and far-field scenarios, we establish the BD-RIS structure as a competitive alternative to traditional active antenna arrays. Our results reveal that BD-RISs achieve near active antenna arrays performance in localization precision, overcoming the limitations of D-RISs and underscoring its potential for high-accuracy positioning in future communication networks. This work envisions the use of BD-RIS for enabling passive beamforming-based localization, setting the stage for more efficient and scalable localization strategies in sixth-generation networks and beyond.

A Practical Validation of RIS Detection and Identification

Reconfigurable intelligent surface (RIS)-assisted communication is a key enabling technology for next-generation wireless communication networks, allowing for the reshaping of wireless channels without requiring traditional radio frequency (RF) active components. While their passive nature makes RISs highly attractive, it also presents a challenge: RISs cannot actively identify themselves to user equipments (UEs). Recently, a new method has been proposed to detect and identify RISs by letting them modulate their identities in the signals reflected from their surfaces. In this letter, we first propose a new and simpler modulation method for RISs and then validate the concept of RIS detection and identification (RIS-ID) using a real-world experimental setup. The obtained results validate the RIS-ID concept and show the effectiveness of our proposed modulation method over different operating scenarios and systems settings.

Noise-Domain Non-Orthogonal Multiple Access

In this paper, we present noise-domain non-orthogonal multiple access (ND-NOMA), an innovative communication scheme that utilizes the modulation of artificial noise mean and variance to convey information. Distinct from traditional methods such as power-domain non-orthogonal multiple access (PD-NOMA) that heavily relies on successive interference cancellation (SIC), ND-NOMA utilizes the noise domain, considerably reducing power consumption and system complexity. Inspired by noise modulation, ND-NOMA enhances energy efficiency and provides lower bit error probability (BEP), making it highly suitable for next-generation Internet-of-things (IoT) networks. Our theoretical analyses and computer simulations reveal that ND-NOMA can achieve exceptionally low bit error rates in both uplink and downlink scenarios, in the presence of Rician fading channels. The proposed multi-user system is supported by a minimum distance detector for mean detection and a threshold-based detector for variance detection, ensuring robust communication in low-power environments. By leveraging the inherent properties of noise, ND-NOMA offers a promising platform for long-term deployments of low-cost and low-complexity devices.

Fast Network Recovery from Large-Scale Disasters: A Resilient and Self-Organizing RAN Framework

Extreme natural phenomena are occurring more frequently everyday in the world, challenging, among others, the infrastructure of communication networks. For instance, the devastating earthquakes in Turkiye in early 2023 showcased that, although communications became an imminent priority, existing mobile communication systems fell short with the operational requirements of harsh disaster environments. In this article, we present a novel framework for robust, resilient, adaptive, and open source sixth generation (6G) radio access networks (Open6GRAN) that can provide uninterrupted communication services in the face of natural disasters and other disruptions. Advanced 6G technologies, such as reconfigurable intelligent surfaces (RISs), cell-free multiple-input-multiple-output, and joint communications and sensing with increasingly heterogeneous deployment, consisting of terrestrial and non-terrestrial nodes, are robustly integrated. We advocate that a key enabler to develop service and management orchestration with fast recovery capabilities will rely on an artificial-intelligence-based radio access network (RAN) controller. To support the emergency use case spanning a larger area, the integration of aerial and space segments with the terrestrial network promises a rapid and reliable response in the case of any disaster. A proof-of-concept that rapidly reconfigures an RIS for performance enhancement under an emergency scenario is presented and discussed.

Hybrid STAR-RIS Enabled Integrated Sensing and Communication

Integrated sensing and communication (ISAC) is recognized as one of the key enabling technologies for sixth-generation (6G) wireless communication networks, facilitating diverse emerging applications and services in an energy and cost-efficient manner. This paper proposes a multi-user multi-target ISAC system to enable full-space coverage for communication and sensing tasks. The proposed system employs a hybrid simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) comprising active transmissive and passive reflective elements. In the proposed scheme, the passive reflective elements support communication and sensing links for nearby communication users and sensing targets, while low-power active transmissive elements are deployed to improve sensing performance and overcome high path attenuation due to multi-hop transmission for remote targets. Moreover, to optimize the transmissive/reflective coefficients of the hybrid STAR-RIS, a semi-definite relaxation (SDR)-based algorithm is proposed. Furthermore, to evaluate sensing performance, signal-to-interference-noise ratio (SINR) and Cramer-Rao bound (CRB) metrics have been derived and investigated via conducting extensive computer simulations.

Hybrid Reconfigurable Intelligent Surface Enabled Over the Air Index Modulation

Users' desire for enhanced performance drive the inevitable technological progress on vertical applications in wireless communication systems. To meet these demands, researchers vigorously investigate potential 6G and beyond technologies and solutions. Reconfigurable intelligent surfaces (RISs) have risen in popularity and attracted the attention of academia as well as industry and seem to be a promising candidate for 6G technology. RISs are reflective metamaterials with many configurable elements consisting of pin diodes that have the ability to manipulate the impinging signals' properties, hence, enabling some sort of virtual control over the wireless channel. In this paper, we propose a novel over-the-air index modulation (IM) scheme through the use of a hybrid RIS with active and passive partitions to convey additional IM bits over-the-air. In addition we propose another modified scheme that allows the transmission for even more IM bits but at the expense of certain trade-offs. First, we present the system model for both of the proposed schemes. Furthermore, comprehensive computer simulation results are provided and discussed presenting the superior bit error rate (BER) performance and additional benefits of the proposed systems compared to similar benchmarks.

Time Index Modulation-Driven Standalone RIS Mechanism for Symbiotic Radio

The rising demand for energy and spectrum resources in next-generation Internet-of-things (IoT) systems accounts for innovative modes of information and power transfer. One potential solution is to harness the active transmission capability of devices to facilitate data transmission and wireless energy harvesting (WEH) for backscatter communication so as to form a symbiotic radio (SR) environment in a mutualistic manner. Additionally, incorporating reconfigurable intelligent surfaces (RISs) into the SR environment can provide an additional link and enhance the reliability of backscatter communication, thereby reinforcing the symbiotic relationships between active and passive devices. This paper proposes a novel SR system where a standalone RIS sustains its functions through WEH based on a low-power RIS structure and establishes mutualistic symbiosis by utilizing a signal conveyed by the primary transmitter (PTx) to assist ongoing transmissions and convey information to the primary receiver (PRx). The PTx employs time index modulation (TIM) to transmit information to the PRx and power to the RIS and energy harvester (EH). A log-likelihood ratio (LLR)-based detector is presented to address challenges in the TIM scheme. Finally, the performance of the proposed scheme is investigated in terms of harvested direct current (DC) power at the RIS and EH, as well as the bit error rate (BER) at the PRx.

Environment-Aware Codebook Design for RIS-Assisted MU-MISO Communications: Implementation and Performance Analysis

Reconfigurable intelligent surface (RIS) provides a new electromagnetic response control solution, which can proactively reshape the characteristics of wireless channel environments. In RIS-assisted communication systems, the acquisition of channel state information (CSI) and the optimization of reflecting coefficients constitute major design challenges. To address these issues, codebook-based solutions have been developed recently, which, however, are mostly environment-agnostic. In this paper, a novel environment-aware codebook protocol is proposed, which can significantly reduce both pilot overhead and computational complexity, while maintaining expected communication performance. Specifically, first of all, a channel training framework is introduced to divide the training phase into several blocks. In each block, we directly estimate the composite end-to-end channel and focus only on the transmit beamforming. Second, we propose an environment-aware codebook generation scheme, which first generates a group of channels based on statistical CSI, and then obtains their corresponding RIS configuration by utilizing the alternating optimization (AO) method offline. In each online training block, the RIS is configured based on the corresponding codeword in the environment-aware codebook, and the optimal codeword resulting in the highest sum rate is adopted for assisting in the downlink data transmission. Third, we analyze the theoretical performance of the environment-aware codebook-based protocol taking into account the channel estimation errors. Finally, numerical simulations are provided to verify our theoretical analysis and the performance of the proposed scheme. In particular, the simulation results demonstrate that our protocol is more competitive than conventional environment-agnostic codebooks.