arXiv subjects

Chandan Kumar Sheemar

Publications and source records attributed to Chandan Kumar Sheemar.

At least 37 records · Page 2Linked to original sources

arXiv2025

RIS-based Physical Layer Security for Integrated Sensing and Communication: A Comprehensive Survey

Integrated Sensing and Communication (ISAC) is a crucial component of future wireless networks, enabling seamless integration of Communication and Sensing (C\&S) functionalities. However, ensuring security in ISAC systems remains a significant challenge, as both C\&S data are susceptible to adversarial threats. Physical Layer Security (PLS) has emerged as a key framework for mitigating these risks at the transmission level. Reconfigurable Intelligent Surfaces (RIS) further enhance PLS by dynamically shaping the radio environment to improve both secrecy along with C\&S performance. This survey begins with an overview of RIS, PLS, and ISAC fundamentals, establishing a foundation for understanding their integration. The state-of-the-art RIS-assisted PLS approaches in ISAC systems are then categorized into passive RIS and Active RIS (ARIS) paradigms. Passive RIS-based techniques focus on optimizing system throughput, covert communication, and Secrecy Rates (SRs), alongside improving sensing Signal-to-Noise Ratio (SNR) and Weighted Sum Rate (WSR) under various constraints. ARIS-based strategies extend these capabilities by actively optimizing beamforming to enhance secrecy and covert rates while ensuring robust sensing under communication and security constraints. By reviewing both passive and ARIS-based security frameworks, this survey highlights the transformative role of RIS in strengthening ISAC security. Furthermore, it explores key optimization methodologies, technical challenges, and future research directions for integrating RIS with PLS to ensure secure and efficient ISAC in next-generation 6G wireless networks.

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arXiv2025

Minimum Mean Squared Error Holographic Beamforming for Sum-Rate Maximization

This paper studies the problem of hybrid holographic beamforming for sum-rate maximization in a communication system assisted by a reconfigurable holographic surface. Existing methodologies predominantly rely on gradient-based or approximation techniques necessitating iterative optimization for each update of the holographic response, which imposes substantial computational overhead. To address these limitations, we establish a mathematical relationship between the mean squared error (MSE) criterion and the holographic response of the RHS to enable alternating optimization based on the minimum MSE (MMSE). Our analysis demonstrates that this relationship exhibits a quadratic dependency on each element of the holographic beamformer. Exploiting this property, we derive closed-form optimal expressions for updating the holographic beamforming weights. Our complexity analysis indicates that the proposed approach exhibits only linear complexity in terms of the RHS size, thus, ensuring scalability for large-scale deployments. The presented simulation results validate the effectiveness of our MMSE-based holographic approach, providing useful insights.

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arXiv2025

Enhancing Physical Layer Security in Cognitive Radio-Enabled NTNs with Beyond Diagonal RIS

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.

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arXiv2025

Beyond Diagonal RIS Enhanced Cognitive Radio Enabled Multilayer Non-Terrestrial Networks

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.

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arXiv2025

Secrecy Rate Maximization for 6G Reconfigurable Holographic Surfaces Assisted Systems

Reconfigurable holographic surfaces (RHS) have emerged as a transformative material technology, enabling dynamic control of electromagnetic waves to generate versatile holographic beam patterns. This paper addresses the problem of secrecy rate maximization for an RHS-assisted systems by joint designing the digital beamforming, artificial noise (AN), and the analog holographic beamforming. However, such a problem results to be non-convex and challenging. Therefore, to solve it, a novel alternating optimization algorithm based on the majorization-maximization (MM) framework for RHS-assisted systems is proposed, which rely on surrogate functions to facilitate efficient and reliable optimization. In the proposed approach, digital beamforming design ensures directed signal power toward the legitimate user while minimizing leakage to the unintended receiver. The AN generation method projects noise into the null space of the legitimate user channel, aligning it with the unintended receiver channel to degrade its signal quality. Finally, the holographic beamforming weights are optimized to refine the wavefronts for enhanced secrecy rate performance Simulation results validate the effectiveness of the proposed framework, demonstrating significant improvements in secrecy rate compared to the benchmark method.

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arXiv2025

Joint Holographic Beamforming and User Scheduling with Individual QoS Constraints

Reconfigurable holographic surfaces (RHS) have emerged as a transformative material technology, enabling dynamic control of electromagnetic waves to generate versatile holographic beam patterns. This paper addresses the problem of joint hybrid holographic beamforming and user scheduling under per-user minimum quality-of-service (QoS) constraints, a critical challenge in resource-constrained networks. However, such a problem results in mixed-integer non-convex optimization, making it difficult to identify feasible solutions efficiently. To overcome this challenge, we propose a novel iterative optimization framework that jointly solves the problem to maximize the RHS-assisted network sum-rate, efficiently managing holographic beamforming patterns, dynamically scheduling users, and ensuring the minimum QoS requirements for each scheduled user. The proposed framework relies on zero-forcing digital beamforming, gradient-ascent-based holographic beamformer optimization, and a greedy user selection principle. Our extensive simulation results validate the effectiveness of the proposed scheme, demonstrating their superior performance compared to the benchmark algorithms in terms of sum-rate performance, while meeting the minimum per-user QoS constraints

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arXiv2025

Joint Beamforming and 3D Location Optimization for Multi-User Holographic UAV Communications

This paper pioneers the field of multi-user holographic unmanned aerial vehicle (UAV) communications, laying a solid foundation for future innovations in next-generation aerial wireless networks. The study focuses on the challenging problem of jointly optimizing hybrid holographic beamforming and 3D UAV positioning in scenarios where the UAV is equipped with a reconfigurable holographic surface (RHS) instead of conventional phased array antennas. Using the unique capabilities of RHSs, the system dynamically adjusts both the position of the UAV and its hybrid beamforming properties to maximize the sum rate of the network. To address this complex optimization problem, we propose an iterative algorithm combining zero-forcing digital beamforming and a gradient ascent approach for the holographic patterns and the 3D position optimization, while ensuring practical feasibility constraints. The algorithm is designed to effectively balance the trade-offs between power, beamforming, and UAV trajectory constraints, enabling adaptive and efficient communications, while assuring a monotonic increase in the sum-rate performance. Our numerical investigations demonstrate that the significant performance improvements with the proposed approach over the benchmark methods, showcasing enhanced sum rate and system adaptability under varying conditions.

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arXiv2025

Holographic Joint Communications and Sensing With Cramer-Rao Bounds

Joint Communication and Sensing (JCAS) technology facilitates the seamless integration of communication and sensing functionalities within a unified framework, enhancing spectral efficiency, reducing hardware complexity, and enabling simultaneous data transmission and environmental perception. This paper explores the potential of holographic JCAS systems by leveraging reconfigurable holographic surfaces (RHS) to achieve high-resolution hybrid holographic beamforming while simultaneously sensing the environment. As the holographic transceivers are governed by arbitrary antenna spacing, we first derive exact Cramér-Rao Bounds (CRBs) for azimuth and elevation angles to rigorously characterize the three-dimensional (3D) sensing accuracy. To optimize the system performance, we propose a novel weighted multi-objective problem formulation that aims to simultaneously maximize the communication rate and minimize the CRBs. However, this formulation is highly non-convex due to the inverse dependence of the CRB on the optimization variables, making the solution extremely challenging. To address this, we propose a novel algorithmic framework based on the Majorization-Maximization (MM) principle, employing alternating optimization to efficiently solve the problem. The proposed method relies on the closed-form surrogate functions that majorize the original objective derived herein, enabling tractable optimization. Simulation results are presented to validate the effectiveness of the proposed framework under diverse system configurations, demonstrating its potential for next-generation holographic JCAS systems.

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arXiv2025

Beyond Diagonal RIS: A New Frontier for 6G Internet of Things Networks

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.

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arXiv2024

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 interoperability opportunities, but also exhibits unique design challenges. To this end, the success of JCAS 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 JCAS research is lately expanding, there still exist relevant directions of investigation that hold tremendous potential to profoundly transform the sixth generation (6G), and beyond, cellular networks. This article presents new opportunities and challenges brought up by FD-enabled JCAS, taking into account the key technical peculiarities of FD systems. Unlike simplified JCAS scenarios, we delve into the most comprehensive configuration, encompassing uplink and downlink users, as well as monostatic and bistatic radars, all harmoniously coexisting to jointly push the boundaries of both communications and sensing. The performance improvements resulting from this advancement bring forth numerous new challenges, each meticulously examined and expounded upon.

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arXiv2024

Holographic MIMO for Next Generation Non-Terrestrial Networks: Motivation, Opportunities, and Challenges

In this article, we propose the integration of the Holographic Multiple Input Multiple Output (HMIMO) as a transformative solution for next generation Non-Terrestrial Networks (NTNs), addressing key challenges, such as high hardware costs, launch expenses, and energy inefficiency. Traditional NTNs are constrained by the financial and operational limitations posed by bulky, costly antenna systems, alongside the complexities of maintaining effective communications in space. HMIMO offers a novel approach utilizing compact and lightweight arrays of densely packed radiating elements with real-time reconfiguration capabilities, thus, capable of optimizing system performance under dynamic conditions such as varying orbital dynamics and Doppler shifts. By replacing conventional antenna systems with HMIMO, the complexity and cost of satellite manufacturing and launch can be substantially reduced, enabling more streamlined and cost-effective satellite designs. This advancement holds significant potential to democratize space communications, making them accessible to a broader range of stakeholders, including smaller nations and commercial enterprises. Moreover, the inherent capabilities of HMIMO in enhancing energy efficiency, scalability, and adaptability position this technology as a key enabler of new use cases and sustainable satellite operations.

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arXiv2024

Beyond Diagonal IRS Assisted Ultra Massive THz Systems: A Low Resolution Approach

The terahertz communications have the potential to revolutionize data transfer with unmatched speed and facilitate the development of new high-bandwidth applications. This paper studies the performance of downlink terahertz system assisted by beyond diagonal intelligent reconfigurable surface (BD-IRS). For enhanced energy efficiency and low cost, a joint precoding and BD-IRS phase shift design satisfying the $1$-bit resolution constraints to maximize the spectral efficiency is presented. The original problem is non-linear, NP-hard, and intricately coupled, and obtaining an optimal solution is challenging. To reduce the complexity, we first transform the optimization problem into two problems and then iteratively solve them to achieve an efficient solution. Numerical results demonstrate that the proposed approach for the BD-IRS assisted terahertz system significantly enhances the spectral efficiency compared to the conventional diagonal IRS assisted system.

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arXiv2024

Demonstration of Safe Electromagnetic Radiation Emitted by 5G Active Antenna Systems

The careful planning and safe deployment of 5G technologies will bring enormous benefits to society and the economy. Higher frequency, beamforming, and small-cells are key technologies that will provide unmatched throughput and seamless connectivity to 5G users. Superficial knowledge of these technologies has raised concerns among the general public about the harmful effects of radiation. Several standardization bodies are active to put limits on the emissions which are based on a defined set of radiation measurement methodologies. However, due to the peculiarity of 5G such as dynamicity of the beams, network densification, Time Division Duplexing mode of operation, etc, using existing EMF measurement methods may provide inaccurate results. In this context, we discuss our experimental studies aimed towards the measurement of radiation caused by beam-based transmissions from a 5G base station equipped with an Active Antenna System(AAS). We elaborate on the shortcomings of current measurement methodologies and address several open questions. Next, we demonstrate that using user-specific downlink beamforming, not only better performance is achieved compared to non-beamformed downlink, but also the radiation in the vicinity of the intended user is significantly decreased. Further, we show that under weak reception conditions, an uplink transmission can cause significantly high radiation in the vicinity of the user equipment. We believe that our work will help in clearing several misleading concepts about the 5G EMF radiation effects. We conclude the work by providing guidelines to improve the methodology of EMF measurement by considering the spatiotemporal dynamicity of the 5G transmission.

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arXiv2023

Reconfigurable Intelligent Surfaces for 6G Non-Terrestrial Networks: Assisting Connectivity from the Sky

This paper studies the potential of RIS-integrated NTNs to revolutionize the next-generation connectivity. First, it discusses the fundamentals of RIS technology. Secondly, it delves into reporting the recent advances in RIS-enabled NTNs. Subsequently, it presents a novel framework based on the current state-of-the-art for low earth orbit satellites (LEO) communications, wherein the signal received at the user terminal traverses both a direct link and an RIS link, and the RIS is mounted on a high-altitude platform (HAP) situated within the stratosphere. Finally, the paper concludes by highlighting open challenges and future research directions to revolutionize the realm of RIS-integrated NTNs.

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arXiv2023

Deep Reinforcement Learning for Backscatter Communications: Augmenting Intelligence in Future Internet of Things

Backscatter communication (BC) technology offers sustainable solutions for next-generation Internet-of-Things (IoT) networks, where devices can transmit data by reflecting and adjusting incident radio frequency signals. In parallel to BC, deep reinforcement learning (DRL) has recently emerged as a promising tool to augment intelligence and optimize low-powered IoT devices. This article commences by elucidating the foundational principles underpinning BC systems, subsequently delving into the diverse array of DRL techniques and their respective practical implementations. Subsequently, it investigates potential domains and presents recent advancements in the realm of DRL-BC systems. A use case of RIS-aided non-orthogonal multiple access BC systems leveraging DRL is meticulously examined to highlight its potential. Lastly, this study identifies and investigates salient challenges and proffers prospective avenues for future research endeavors.

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arXiv2023

Signal Processing Based Antenna Pattern Characterization for MIMO Systems

Sophisticated antenna technologies are constantly evolving to meet the escalating data demands projected for 6G and future networks. The characterization of these emerging antenna systems poses challenges that necessitate a reevaluation of conventional techniques, which rely solely on simple measurements conducted in advanced anechoic chambers. In this study, our objective is to introduce a novel endeavour for antenna pattern characterization (APC) in next-generation multiple-input-multiple-output (MIMO) systems by utilizing the potential of signal processing tools. In contrast to traditional methods that struggle with multi-path scenarios and require specialized equipment for measurements, we endeavour to estimate the antenna pattern by exploiting information from both line-of-sight (LoS) and non-LoS contributions. This approach enables antenna pattern characterization in complex environments without the need for anechoic chambers, resulting in substantial cost savings. Furthermore, it grants a much wider research community the ability to independently perform APC for emerging complex 6G antenna systems, without relying on anechoic chambers. Simulation results demonstrate the efficacy of the proposed novel approach in accurately estimating the true antenna pattern.

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arXiv2023

Adaptive Timers and Buffer Optimization for Layer-2 Protocols in 5G Non-Terrestrial Networks

Interest in the integration of Terrestrial Networks (TN) and Non-Terrestrial Networks (NTN); primarily satellites; has been rekindled due to the potential of NTN to provide ubiquitous coverage. Especially with the peculiar and flexible physical layer properties of 5G-NR, now direct access to 5G services through satellites could become possible. However, the large Round-Trip Delays (RTD) in NTNs require a re-evaluation of the design of RLC and PDCP layers timers ( and associated buffers), in particular for the regenerative payload satellites which have limited computational resources, and hence need to be optimally utilized. Our aim in this work is to initiate a new line of research for emerging NTNs with limited resources from a higher-layer perspective. To this end, we propose a novel and efficient method for optimally designing the RLC and PDCP layers' buffers and timers without the need for intensive computations. This approach is relevant for low-cost satellites, which have limited computational and energy resources. The simulation results show that the proposed methods can significantly improve the performance in terms of resource utilization and delays.

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arXiv2023

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

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