arXiv subjects

Chintha Tellambura

Publications and source records attributed to Chintha Tellambura.

At least 19 recordsLinked to original sources

arXiv2026

Reconfigurable Intelligent Surfaces for Cognitive Radio Networks: Design, Optimization, and Emerging Trends

Reconfigurable intelligent surfaces (RISs) enable programmable wireless propagation environments, offering new opportunities for cognitive radio networks (CRNs) to improve spectrum utilization, enhance spectral and energy efficiency, and operate reliably under low signal-to-noise ratio conditions. By combining the complementary strengths of RISs and CRNs, RIS-assisted CRNs (RCNs) have emerged as a promising architecture for future 6G wireless systems. Despite their growing importance, a comprehensive survey of this rapidly evolving field has been lacking. This paper fills this gap by providing a systematic and comprehensive review of RCNs. The paper first introduces the fundamentals of CRNs and RISs, including dynamic spectrum access models, spectrum sensing techniques, RIS operating principles, and RIS architectures. It then examines the design of RCNs, covering their system architectures, deployment strategies, channel estimation, spectrum access mechanisms, communication protocols, and the joint optimization of RIS and CRN parameters. Next, the existing literature is organized into six major research directions: performance analysis, resource allocation and optimization, secure RCNs, active RISs, simultaneously transmitting and reflecting RISs, and machine learning-enabled RCNs. Finally, the paper discusses key research challenges and future directions, including scalability, practical deployment, integration with emerging 6G technologies, coexistence with evolving network architectures, standardization, and security and privacy. This survey provides a unified reference for researchers and practitioners and establishes a roadmap for the future development of RCNs.

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arXiv2026

Cell-Free Integrated Sensing and Communication

Cell-free (CF) integrated sensing and communication (ISAC) merges the CF architecture with ISAC functionalities. CF-ISAC leverages distributed access points, removes cell boundaries, and enhances coverage, spectral efficiency, and reliability. It also improves energy efficiency, enabling robust multi-user communication, distributed multi-static sensing, and seamless resource optimization. A comprehensive survey on CF-ISAC has been lacking. This monograph addresses that gap by covering the foundational principles, cooperative transmission, radar cross-section, target parameter estimation, ISAC integration levels, sensing metrics, and key applications. It also explores the advantages of multi-static sensing. Performance analysis, resource allocation, security, and user/target-centric designs are discussed. Finally, synchronization, multi-target detection, interference management, and fronthaul limitations are discussed. Advanced antenna technologies, network-assisted systems, near-field CF-ISAC, cross-technology integration, and machine learning approaches are presented.

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arXiv2026

Standard Condition Number-Based Robust Signal Detection with Whitening under Uncertainty

Robust signal detection in colored noise with unknown covariance is essential in radar, cognitive radio, integrated sensing and communication (ISAC), and quantum sensing applications. This paper develops a unified analytical framework for the Standard Condition Number (SCN) detector, which employs the ratio of the largest to smallest eigenvalues of the whitened sample covariance matrix. The framework jointly covers both ideal conditions in which the training and sensing noise statistics are identical and disturbed conditions in which interference or jamming alters the sensing covariance. Despite the SCN's practical relevance, its finite-sample false-alarm and detection behavior has not been analytically characterized. Using random matrix theory (RMT), we derive general expressions for these probabilities, provide closed-form results for special cases, and show that the SCN preserves the Constant False Alarm Rate (CFAR) property under covariance mismatch. Analytical and simulation results confirm that the proposed unified framework delivers consistent detection performance and greater robustness than conventional eigenvalue- and LRT-based detectors.

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arXiv2026

Cell-Free Integrated Sensing and Communication: Principles, Advances, and Future Directions

Cell-free (CF) integrated sensing and communication (ISAC) combines CF architecture with ISAC. CF employs distributed access points, eliminates cell boundaries, and enhances coverage, spectral efficiency, and reliability. ISAC unifies radar sensing and communication, enabling simultaneous data transmission and environmental sensing within shared spectral and hardware resources. CF-ISAC leverages these strengths to improve spectral and energy efficiency while enhancing sensing in wireless networks. As a promising candidate for next-generation wireless systems, CF-ISAC supports robust multi-user communication, distributed multi-static sensing, and seamless resource optimization. However, a comprehensive survey on CF-ISAC has been lacking. This paper fills that gap by first revisiting CF and ISAC principles, covering cooperative transmission, radar cross-section, target parameter estimation, ISAC integration levels, sensing metrics, and applications. It then explores CF-ISAC systems, emphasizing their unique features and the benefits of multi-static sensing. State-of-the-art developments are categorized into performance analysis, resource allocation, security, and user/target-centric designs, offering a thorough literature review and case studies. Finally, the paper identifies key challenges such as synchronization, multi-target detection, interference management, and fronthaul capacity and latency. Emerging trends, including next-generation antenna technologies, network-assisted systems, near-field CF-ISAC, integration with other technologies, and machine learning approaches, are highlighted to outline the future trajectory of CF-ISAC research.

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arXiv2026

Set Transformer-Based Beamforming Design for Cell-Free Integrated Sensing and Communication

Existing cell-free integrated sensing and communication (CF-ISAC) beamforming algorithms predominantly rely on classical optimization techniques, which often entail high computational complexity and limited scalability. Meanwhile, recent learning-based approaches have difficulty capturing the global interactions and long-range dependencies among distributed access points (APs), communication users, and sensing targets. To address these limitations, we propose the first Set Transformer-based CF-ISAC beamforming framework (STCIB). By exploiting attention mechanisms, STCIB explicitly models global relationships among network entities, naturally handles unordered input sets, and preserves permutation invariance across APs, users, and targets. The proposed framework operates in an unsupervised manner, eliminating the need for labeled training data, and supports three design regimes: (i) sensing-centric, (ii) communication-centric, and (iii) joint ISAC optimization. We benchmark STCIB against a convolutional neural network (CNN) baseline and two state-of-the-art optimization algorithms: the convex-concave procedure algorithm (CCPA) and augmented Lagrangian manifold optimization (ALM-MO). Numerical results demonstrate that STCIB consistently outperforms the CNN, achieving substantially higher ISAC performance with only a negligible increase in runtime. For instance, in regime (iii), at $η$=0.4, STCIB improves the sensing and communication sum rates by 14.8 % and 31.6 %, respectively, relative to the CNN, while increasing runtime by only 0.26 %. Compared with CCPA and ALM-MO, STCIB offers significantly lower computational cost while maintaining modest performance gains. In regime (i), for a 3.0 bps/Hz communication threshold, the runtime of STCIB is only 0.1 % and 0.3 % of that required by CCPA and ALM-MO, respectively, while improving the sensing sum rate by 4.45 % and 5.9 %.

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arXiv2026

Backscatter-Assisted High-Speed Rail Communications in Straight Tunnel Environments: Effects of Tag Number and Phase Control

Backscatter communication is a promising technology to enhance the signal strength received by the receiver in straight tunnel environments. The impact of the number of tags and their phase adjustment on system performance remains a challenging issue though. Therefore, in this paper, we investigate the channel gain of backscatter-assisted communication with multiple tags in straight tunnels. In particular, we derive the probabilities that the backscatter link gain is greater than the direct link under adjustable and random phase assumptions by applying the Gaussian and Gamma approximations to derive tractable expressions. The simulation results show that phaseadjustable tags significantly improve the channel gain of the backscatter links compared to the random phase case. Moreover, the number of tags has an upper threshold for an effective tag deployment pattern. These insights provide valuable guidelines for the efficient design of backscatter communication systems in tunnel environments.

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arXiv2025

Rate-Splitting Multiple Access for Secure Near-Field Integrated Sensing and Communication

Near-field integrated sensing and communication (ISAC) leverages distance-dependent channel variations for joint distance and angle estimation. However, full-digital architectures have prohibitive hardware costs, making hybrid analog-digital (HAD) designs the primary alternative. Nevertheless, such architectures compromise beamfocusing precision and lead to energy leakage, which exacerbates inter-user interference and increases eavesdropping risks. To address these challenges, this paper proposes a rate-splitting multiple access (RSMA)-enhanced secure transmit scheme for near-field ISAC. For the first time, it exploits the common stream in RSMA to concurrently (i) flexibly manage interference, (ii) act as artificial noise to suppress eavesdropping, and (iii) serve as sensing sequences. The objective is to maximize the minimum secrecy rate while satisfying the angle and distance Cramer-Rao Bound (CRB) constraints. This results in a hard, non-convex optimization problem, and we employ block coordinate descent to decompose it into three sub-problems with lower computational complexity. In the first stage of optimizing fully digital beamfocusers, we develop an iterative solution using weighted minimum mean-squared error (WMMSE), quadratic transform, and Taylor expansion methods, thus avoiding conventional semidefinite relaxation. In the second and third stages, the analog and digital beamfocusers are optimized in closed form. Simulation results show that the proposed scheme (1) achieves near full-digital beamfocusing performance with a 16-fold reduction in RF chains, (2) provides superior secrecy performance compared to conventional beamfocusing-only and far-field security schemes, and (3) enables high-accuracy sensing with negligible loss in secrecy performance.

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arXiv2025

Hybrid Beamfocusing Design for RSMA-Enhanced Near-Field Secure Communications

Near-field spherical wavefronts enable spotlight-like beam focusing to mitigate unintended energy leakage, creating new opportunities for physical-layer security (PLS). However, under hybrid analog-digital (HAD) antenna architectures, beamfocusing alone may not provide foolproof privacy protection due to reduced focusing precision. To address this issue, this paper proposes a rate-splitting multiple access (RSMA)-enhanced secure transmit scheme for near-field communications with fully-connected or sub-connected HAD architectures. In the proposed scheme, the common stream is designed for dual purposes, delivering the desired message for legitimate users while acting as artificial noise to disrupt eavesdropping. The primary objective is to maximize the minimum secrecy rate by jointly optimizing the analog beamfocuser, digital beamfocuser, and common secrecy rate allocation. To solve the formulated non-convex problem, we develop a penalty-based alternating optimization algorithm. Specifically, the variables are partitioned into three blocks, where one block is solved via a surrogate optimization method, while the others are updated in closed form. Simulation results reveal that our transmit scheme: (1) approaches fully digital beamfocusing with substantially fewer radio frequency chains, (2) outperforms conventional beamfocusing-only and far-field security schemes, and (3) preserves secrecy without significantly compromising communication rates.

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arXiv2025

Hybrid Beamfocusing Design for RSMA-Enabled Near-Field Wideband Communications

Future wireless networks will utilize extremely large-scale antenna arrays (ELAAs) over high-frequency bands, which, however, produce near-field spherical wavefronts and spatial wideband effects. To exploit and mitigate these, this paper proposes a rate-splitting multiple access (RSMA)-enabled transmit scheme for wideband near-field communications (NFC). Our solution leverages true-time-delay (TTD)-based hybrid beamfocusing architectures to mitigate spatial wideband effect and reduce radio frequency chain requirements. The objective is to maximize the minimum rate by jointly optimizing frequency-dependent analog beamfocusing, frequency-independent analog beamfocusing, digital beamfocusing, and common rate allocation. To solve this complicated non-convex problem, we develop a penalty-based iterative algorithm that partitions the variables into three blocks and then employs block coordinate descent (BCD) to optimize each block alternately. This algorithm is further extended to support the sub-connected TTD-based analog beamfocusing architectures. Comprehensive simulation results indicate that our transmit scheme: 1) effectively compensates for spatial wideband effect, addressing a critical challenge in wideband operation; 2) achieves performance comparable to full digital beamfocusing while maintaining lower hardware complexity; 3) achieves substantial performance gains over the other two benchmarks.

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arXiv2025

RIS- and Multi-Snapshot-Enabled SISO 3D Position and Velocity Estimation With Single Base Station

Reconfigurable intelligent surface (RIS) panels can act as cost-effective anchors for radio localization, complementing conventional base station (BS) anchors. This paper investigates joint three-dimensional position and velocity estimation (3D-JPVE) in single-input single-output (SISO) systems with only one BS available. We first theoretically show that 3D-JPVE is infeasible when relying solely on a single RIS or on multiple snapshots alone. To address this, we propose combining RIS deployment with multi-snapshot utilization to enable realizable 3D-JPVE. A two-stage method is developed for multi-snapshot channel parameter estimation, comprising a tensor-based coarse estimation step followed by a maximum likelihood refinement step. In particular, we introduce a third-order tensor formulation to decompose the challenging 3D joint angle-of-departure and Doppler shift estimation (3D-JADE) into two tractable subproblems, which are jointly solved via a low-complexity alternating optimization approach. Building on the channel parameter estimates, we further design a two-stage low-complexity method for optimal 3D-JPVE: coarse estimation is obtained from differential measurements through linear equations, and the preliminary results are refined iteratively using the original measurements. Moreover, we derive the closed-form Cramer-Rao lower bound (CRLB) and show that the proposed 3D-JPVE method approaches CRLB-level accuracy. Simulation results confirm the statistical efficiency of the proposed estimators and demonstrate substantial 3D-JPVE performance gains when deploying active RIS compared to passive RIS.

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arXiv2025

Sub-Connected Hybrid Beamfocusing Design for RSMA-Enabled Near-Field Communications with Imperfect CSI and SIC

Near-field spherical waves inherently encode both direction and distance information, enabling spotlight-like beam focusing for targeted interference mitigation. However, whether such beam focusing can fully eliminate interference under perfect and imperfect channel state information (CSI), rendering advanced interference management schemes unnecessary, remains an open question. To address this, we investigate rate-splitting multiple access (RSMA)-enabled near-field communications (NFC) under imperfect SCI. Our transmit scheme employs a sub-connected hybrid analog-digital (HAD) architecture to reduce hardware overhead while incorporating imperfect successive interference cancellation (SIC) for practical implementation. A minimum rate maximization problem is formulated by jointly optimizing the analog beamfocuser, the digital beamfocuser, and the common rate allocation. To solve the non-convex problem, we develop a penalty-based block coordinate descent (BCD) algorithm, deriving closed-form expressions for the optimal analog and digital beamfocusers solutions. Furthermore, to reduce computational complexity, we propose a low-complexity algorithm, where analog and digital beamfocusers are designed in two separate stages. Simulation results underscore that: 1) beamfocusing alone is insufficient to fully suppress interference even under perfect CSI; 2) RSMA exhibits superior interference management over SDMA under imperfect CSI and SIC conditions; 3) sub-connected HAD architecture delivers near-optimal digital beamfocusing performance with fewer radio frequency chains.

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arXiv2025

Dynamic Scheduling for Enhanced Performance in RIS-assisted Cooperative Network with Interference

Reconfigurable Intelligent Surfaces (RIS) have emerged as transformative technologies, enhancing spectral efficiency and improving interference management in multi-user cooperative communications. This paper investigates the integration of RIS with Flexible-Duplex (FlexD) communication, featuring dynamic scheduling capabilities, to mitigate unintended external interference in multi-user wireless networks. By leveraging the reconfigurability of RIS and dynamic scheduling, we propose a user-pair selection scheme to maximize system throughput when full channel state information (CSI) of interference is unavailable. We develop a mathematical framework to evaluate the throughput outage probability when RIS introduces spatial correlation. The derived analytical results are used for asymptotic analysis, providing insights into dynamic user scheduling under interference based on statistical channel knowledge. Finally, we compare FlexD with traditional Full Duplex (FD) and Half Duplex (HD) systems against RIS-assisted FlexD. Our results show FlexD's superior throughput enhancement, energy efficiency and data management capability in interference-affected networks, typical in current and next-generation cooperative wireless applications like cellular and vehicular communications.

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arXiv2025

Hybrid Beamforming Design for RSMA-enabled Near-Field Integrated Sensing and Communications

Integrated sensing and communication (ISAC) networks leverage extremely large antenna arrays and high frequencies. This inevitably extends the Rayleigh distance, making near-field (NF) spherical wave propagation dominant. This unlocks numerous spatial degrees of freedom, raising the challenge of optimizing them for communication and sensing tradeoffs. To this end, we propose a rate-splitting multiple access (RSMA)-based NF-ISAC transmit scheme utilizing hybrid analog-digital antennas. RSMA enhances interference management, while a variable number of dedicated sensing beams adds beamforming flexibility. The objective is to maximize the minimum communication rate while ensuring multi-target sensing performance by jointly optimizing receive filters, analog and digital beamformers, common rate allocation, and the sensing beam count. To address uncertainty in sensing beam allocation, a rank-zero solution reconstruction method demonstrates that dedicated sensing beams are unnecessary for NF multi-target detection. A penalty dual decomposition (PDD)-based double-loop algorithm is introduced, employing weighted minimum mean-squared error (WMMSE) and quadratic transforms to reformulate communication and sensing rates. Simulations reveal that the proposed scheme: 1) achieves performance comparable to fully digital beamforming with fewer RF chains, (2) maintains NF multi-target detection without compromising communication rates, and 3) significantly outperforms conventional multiple access schemes and far-field ISAC systems.

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arXiv2025

Revolutionizing Medical Data Transmission with IoMT: A Comprehensive Survey of Wireless Communication Solutions and Future Directions

Traditional hospital-based medical examination methods face unprecedented challenges due to the aging global population. The Internet of Medical Things (IoMT), an advanced extension of the Internet of Things (IoT) tailored for the medical field, offers a transformative solution for delivering medical care. IoMT consists of interconnected medical devices that collect and transmit patients' vital signs online. This data can be analyzed to identify potential health issues, support medical decision-making, enhance patient outcomes, and streamline healthcare operations. Additionally, IoMT helps individuals make informed decisions about their health and fitness. There is a natural synergy with emerging communication technologies to ensure the secure and timely transmission of medical data. This paper presents the first comprehensive tutorial on cutting-edge IoMT research focusing on wireless communication-based solutions. It introduces a systematic three-tier framework to analyze IoMT networks and identify application scenarios. The paper examines the medical data transmission process, including intra-wireless Body Area Networks (WBAN), inter-WBAN, and beyond-WBAN communications. It also discusses the challenges of implementing IoMT applications, such as the longevity of biosensors, co-channel interference management, information security, and data processing delays. Proposed solutions to these challenges are explored from a wireless communication perspective, and future research directions are outlined. The survey concludes with a summary of key findings and insights.

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arXiv2025

Wideband Cognitive Radio for Joint Communication and Sensing: Optimization of Subcarrier Allocation and beamforming

As data traffic grows, wireless systems shift to higher frequency bands (6 GHz and above), where radar systems also operate. This coexistence demands effective interference management and efficient wideband utilization. Cognitive Radio (CR) offers a solution but remains limited to single-node or narrowband systems. This paper introduces a generalized wideband CR-enabled communication and sensing system with multiple users and targets. We propose a communication and sensing sub-carrier allocations framework, followed by transmit beamforming for the primary communication BS and sensing signal design for the secondary radar BS. The goal is to maximize the communication sum rate while ensuring sensing requirements, minimizing interference, and adhering to power constraints. To solve the resulting non-convex problem, we develop a manifold optimization algorithm for communication-only sub-carriers and an alternating optimization approach using the generalized Rayleigh quotient and semidefinite relaxation for communication-sensing sub-carriers. Compared to a non-cooperative benchmark, the proposed system achieves a \qty{10}{\percent} gain in communication sum rate and a \qty{32}{\percent} gain in sensing sum rate with \num{12} BS antennas.

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arXiv2025

CRB-Rate Tradeoff in RSMA-enabled Near-Field Integrated Multi-Target Sensing and Multi-User Communications

Extremely large-scale antenna arrays enhance spectral efficiency and spatial resolution in integrated sensing and communication (ISAC) networks while expanding the Rayleigh distance, triggering a shift from conventional far-field plane waves to near-field (NF) spherical waves. However, full-digital beamforming is infeasible due to the need for dedicated radio frequency (RF) chains. To address this, NF-ISAC with a rate-splitting multiple access (RSMA) scheme is developed for advanced interference management, considering fully-connected and partially-connected hybrid analog and digital (HAD) beamforming architectures. Specifically, the Cramér-Rao bound (CRB) for joint distance and angle sensing is derived, and the achievable performance region between the max-min communication rate and the multi-target CRB is defined. To fully characterize the Pareto boundary of the CRB-rate region, a sensing-centric minimization problem is formulated under communication rate constraints for two HAD beamforming architectures. A penalty dual decomposition (PDD)-based double-loop algorithm is developed to optimize fully-connected HAD beamformers. To reduce computational complexity, a two-stage design algorithm for fully connected HAD beamforming is also proposed. Additionally, the PDD-based double-loop algorithm is extended to the partially-connected HAD architecture. Simulations demonstrate the proposed schemes and algorithms: 1) achieve performance comparable to a fully digital beamformer with fewer RF chains, 2) outperform space division multiple access and far-field ISAC, and 3) yield enhanced CRB-rate trade-off performance.

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arXiv2025

Optimization of Rate-Splitting Multiple Access with Integrated Sensing and Backscatter Communication

An integrated sensing and backscatter communication (ISABC) system is introduced herein. This system features a full-duplex (FD) base station (BS) that seamlessly merges sensing with backscatter communication and supports multiple users. Multiple access (MA) for the user is provided by employing rate-splitting multiple access (RSMA). RSMA, unlike other classical orthogonal and non-orthogonal MA schemes, splits messages into common and private streams. With RSMA, the set of common rate forms can be optimized to reduce interference. Optimized formulas are thus derived for communication rates for users, tags, and the BS's sensing rate, with the primary goal of enhancing the transmission efficiency of the BS. The optimization task involves minimizing the BS's overall transmission power by jointly optimizing the BS's beamforming vectors, the tag reflection coefficients, and user common rates. The alternating optimization method is employed to address this challenge. Concrete solutions are provided for the received beamformers, and semi-definite relaxation and slack-optimization techniques are adopted for transmit beamformers and reflection coefficients, respectively. For example, the proposed RSMA-assisted ISABC system achieves a 350% communication rate boost over a nonorthogonal multiple access-assisted ISABC, with only a 24% increase in transmit power, leveraging ten transmit/reception antennas at the BS.

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arXiv2025

Low-Complexity Multi-Target Detection in ELAA ISAC

Multi-target detection and communication with extremely large-scale antenna arrays (ELAAs) operating at high frequencies necessitate generating multiple beams. However, conventional algorithms are slow and computationally intensive. For instance, they can simulate a \num{200}-antenna system over two weeks, and the time complexity grows exponentially with the number of antennas. Thus, this letter explores an ultra-low-complex solution for a multi-user, multi-target integrated sensing and communication (ISAC) system equipped with an ELAA base station (BS). It maximizes the communication sum rate while meeting sensing beampattern gain targets and transmit power constraints. As this problem is non-convex, a Riemannian stochastic gradient descent-based augmented Lagrangian manifold optimization (SGALM) algorithm is developed, which searches on a manifold to ensure constraint compliance. The algorithm achieves ultra-low complexity and superior runtime performance compared to conventional algorithms. For example, it is \num{56} times faster than the standard benchmark for \num{257} BS antennas.

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