arXiv subjects

Chandan Kumar Sheemar

Publications and source records attributed to Chandan Kumar Sheemar.

At least 19 recordsLinked to original sources

arXiv2026

Joint Communications, Sensing, and Positioning in 6G Multi-Functional Satellite Systems: Survey and Open Challenges

Satellite systems are expected to be a cornerstone of sixth-generation (6G) networks, supporting communications, sensing, and positioning, navigation, and timing (PNT) with global coverage. This survey develops a framework for multi-functional satellite systems (MFSS), which combine at least two of these services through shared or jointly designed payload resources. A two-dimensional taxonomy distinguishes the functional configuration---joint communications and sensing (JCAS), joint communications and PNT (JCAP), joint sensing and PNT (JSAP), or joint communications, sensing, and PNT (JCSAP)---from the integration depth---cooperative, integrated, or joint. After consolidating the communication, sensing, and PNT fundamentals and payload architectures into a single background section, the survey examines the three integration levels and then devotes a dedicated section to each configuration, covering its architecture, classification, state of the art, advantages, key challenges, and research directions. The achievable performance of each configuration is illustrated with representative trade-off results from the literature and compared across configurations, the differences between terrestrial multi-functional networks and satellite MFSS are made explicit, and a life-cycle techno-economic framework balances hardware, spectrum, launch, and operational reuse against engineering, qualification, verification, and common-mode risks. The analysis shows that deeper integration can improve resource utilization and functional synergy, but is not automatically the technical or economic optimum for every mission.

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arXiv2026

A Survey on Stacked Intelligent Metasurfaces: Fundamentals, Recent Advances, and Challenges

Stacked intelligent metasurfaces (SIMs) cascade several closely spaced programmable metasurface layers so that an electromagnetic wave undergoes repeated modulation-propagation interactions before leaving the stack. The stack thereby implements, at the speed of propagation and with few radio-frequency chains, high-dimensional analog transformations that would otherwise require digital precoding, combining, spatial filtering, focusing, or inference. Since 2023, SIM research has produced more than two hundred articles, a dedicated magazine special issue, and two survey-level overviews organized around applications and wave-domain computing. This article complements them with a model-to-hardware perspective. First, we present the electromagnetic modeling hierarchy of SIMs, making explicit the assumptions under which the models coincide, their validity regimes, and their computational complexity, with a common notation for hardware non-idealities and power consumption. Second, we present a methodology-first taxonomy (SIM-aware channel acquisition, model-based optimization, statistical-CSI design, learning-based control, and hardware-aware robust design), compare the families in terms of CSI requirements, complexity, convergence, and hardware constraints, and reconcile conflicting findings in the literature. Third, we synthesize applications by the physical role of the SIM. Fourth, we quantitatively compare experimentally demonstrated multilayer prototypes, separate validated from conceptual architectures, and discuss thermal, tolerance, and calibration issues. Fifth, we provide a tutorial-style performance and trade-off analysis anchored in reported results. Finally, we map evidence-based challenges to research directions with measurable targets. Lessons learned are summarized at the end of every section.

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arXiv2026

Channel Estimation for Stacked Intelligent Metasurfaces with Mutual Coupling

Channel estimation for stacked intelligent metasurfaces (SIMs) has relied on the cascade model, which ignores mutual coupling and inter-layer reflection. Under a coupling-consistent multiport model, we show that the pilots are linear in the unknown channel segments and derive least-squares and linear minimum-mean-square-error estimators, an identifiability condition and an exact error decomposition for the reactance training schedule, and a gradient-based schedule design. Cascade-based estimation floors above $0$~dB normalized error at practical layer spacings and collapses the sum rate below that of the bare feed, whereas the proposed estimators retain about $80\%$ of the perfect-channel-knowledge sum rate.

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arXiv2026

Fundamental Limits and Joint Design for Monostatic Joint Communications and Sensing in LEO Satellites

Monostatic joint communication and sensing (JCAS) from a low-Earth-orbit (LEO) satellite requires full-duplex (FD) operation, with self-interference (SI) $80$--$100$~dB stronger than the ground echo. The echo returns milliseconds after transmission, whereas the onboard coupling spans a few symbols. We develop a theory and a design that exploit this separation. Restricting the analog and digital cancellers to the short SI support is without loss of optimality and essential in practice: a least-squares canceller whose support contains the target delay absorbs the coherent echo and reduces the radar SINR by a closed-form factor, about $18$~dB for a vessel at its zero-Doppler crossing. Modeling the SI that no linear canceller can reconstruct as spatially white and accounting for ADC quantization, we derive in closed form a ceiling on the radar SINR, the minimum pre-ADC SI power under a canceller tap budget, the budget for full cancellation, and the sensing weight at which the optimal design changes over from communication to sensing. We then maximize a weighted sum of the communication and sensing SINRs, each normalized by its half-duplex benchmark, over the beamformers, sensing covariance, combiners, and cancellers for $K$ users and $Q$ targets, using an alternating algorithm with closed-form updates. Simulations confirm the closed forms. The joint design gains up to $13\%$ in the normalized objective over a sequential design that cancels the SI only at the receiver, and more than $10$~dB of downlink and radar SINR with $4$-bit ADCs and in the 10th-percentile worst-target SINR of four targets, whereas ignoring the SI overloads the ADCs.

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arXiv2026

Full-Duplex-Enabled Integrated Sensing and Communications: Opportunities and Challenges

Integrated sensing and communications (ISAC) is one of the six usage scenarios of IMT-2030, with in-band full duplex (IBFD) being the most direct way to realize it. In this paradigm, a base station that transmits and receives on the same time-frequency resources can sense continuously with its own downlink waveform while serving uplink traffic. This article revisits full-duplex-enabled ISAC (FD-ISAC) in light of the technologies lately shaping sixth-generation (6G) radio design, such as extremely large multiple-input multiple-output (XL-MIMO) systems operating in the near field, holographic and dynamic metasurface apertures, fluid and movable antennas, beyond-diagonal reconfigucable intelligent surfaces (BS-RISs) and wave-domain processing with stacked intelligent metasurfaces. We present a holistic FD-ISAC architecture built around a multi-stage, echo-preserving self-interference cancellation chain, and map each 6G technological enabler to the gains it brings and the risks it introduces. A case study with a $28$~GHz full-duplex XL-MIMO base station showcases that near-field-aware beamforming combined with wave-domain, analog, and digital cancellation delivers more than twice the throughput of half-duplex and 3GPP sub-band full-duplex baselines at the same localization-accuracy bound. It is also demonstrated that incorporating a group-connected BD-RIS recovers most of the fully-connected gain at a small fraction of its circuit complexity. The article concludes discussing emerging use cases and open challenges.

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arXiv2026

Movable Beyond-Diagonal RIS for ISAC: Optimal Placement and Pareto Boundary

This letter investigates integrated sensing and communication using a movable beyond-diagonal reconfigurable intelligent surface (BD-RIS). Under a rank-one line-of-sight BS--RIS channel, we derive the exact communication--sensing Pareto boundary of a fully-connected BD-RIS in terms of user--target channel correlation. For line-of-sight RIS links, maximizing this correlation yields the optimal placement. We characterize the minimum track aperture that eliminates the illumination trade-off and show that a movable diagonal RIS then attains the same optimum. Below this threshold, a dynamic program offers certified placement accuracy. Numerical results examine hardware connectivity, angular mismatch, and Rician fading.

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arXiv2026

Secure Integrated Sensing and Communications with Movable Beyond-Diagonal RIS

In integrated sensing and communication (ISAC), when the sensed target is itself an eavesdropper, the illumination required for sensing coincides with the leakage that secrecy must suppress. This paper shows how a beyond-diagonal reconfigurable intelligent surface (BD-RIS) with movable elements decouples the two tasks in a monostatic setting, where the echo returns to the base station through the surface. We prove that a lossless reciprocal BD-RIS maps $K$ incident fields onto $K$ prescribed fields if and only if the two sets share the same Gram matrix and their bilinear Gram matrix is symmetric; unlike a diagonal RIS, it can thus steer a two-dimensional incident subspace onto any prescribed subspace. With a single stream, sensing incurs an unavoidable rate loss, whereas a closed-form zero-forcing design with a confidential and a Gaussian sensing stream nulls the data at the target and the sensing at the user, so that sensing costs only an SNR offset. Since all variables follow in closed form for any placement, the joint design reduces to a monotone search over the element positions, without alternating optimization. Simulations show that the dual-stream design loses only $1.1$ bit/s/Hz when the sensing requirement grows by $30$ dB, against $8.3$ bit/s/Hz for a single stream, while movement, interconnection, and the robust derivative-null design add up to $1.9$, $0.9$, and $2.6$ bit/s/Hz, respectively.

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arXiv2026

Space-Time Stacked Intelligent Metasurfaces for Doppler-Resilient LEO Broadcasting

Stacked intelligent metasurfaces (SIMs) cascade programmable layers in front of a feed. In the SIM designs reported so far, including those proposed for low-Earth-orbit (LEO) satellites, the layer coefficients are space-only controls or are varied randomly in time to support opportunistic scheduling, so that every radiated beam carries the frequency of the feed. This paper introduces space-time SIMs (ST-SIMs), whose layers are modulated in time and use the temporal dimension of the stack deterministically: each spatial mode of the aperture is paired with its own prescribed frequency translation. The application is LEO broadcasting, where a common waveform reaches terminals with different Doppler shifts, and any common Doppler correction leaves residuals of up to half the Doppler span. We derive the harmonic-domain model of the stack, solve the minimum-energy space-frequency synthesis in closed form, and prove that full column rank of the steering matrix is necessary and sufficient for decoupling K terminal-specific translations, a result that extends to groups of terminals. We further propose a phase-only synthesis algorithm with guaranteed stationarity, together with quantization and control-rate laws. Simulations at 20 GHz over 50 random drops show that a four-layer ST-SIM with a single radio-frequency chain removes the Doppler floor of a static SIM for footprint radii above about 45 km and, under the ideal phase-only model and at equal radiated peak energy, approaches ideal digital per-terminal precompensation within 0.5 dB for resolvable terminals, whereas, in the evaluated geometries, a single time-modulated layer cannot synthesize the required modes.

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arXiv2026

One-Shot Beam Tracking for Stacked Intelligent Metasurfaces-Assisted LEO Broadcasting

This letter develops a physics-informed one-shot beam tracking method for stacked intelligent metasurface (SIM)-enabled low-Earth-orbit (LEO) links with $K$ users and an $L$-layer SIM with $N$ meta-atoms per layer. The predictable orbital motion is propagated through the line-of-sight (LoS) geometry to forecast the finite-interval variation of the user signal-to-noise ratio (SNR) profile, and an analytical multilayer Jacobian relates this variation to the $LN$ SIM phase coefficients. Beam tracking is formulated as normalized SNR-profile preservation and solved through a single regularized Gauss--Newton correction that requires one Jacobian evaluation and a $K\times K$ linear solve, thereby avoiding iterative reoptimization. A tracking-error bound separates the regularization residual from the nonlinear Taylor remainder and establishes a second-order local error under a full-row-rank Jacobian. Numerical results show that the proposed method retains approximately $94\%$ and $92\%$ of the iterative-reoptimization rate for $L=2$ and $L=4$, respectively, while running about $350\times$ and $260\times$ faster at $N=225$, and confirm the predicted second-order residual error behavior.

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arXiv2026

Stacked Fluid Metasurfaces: Mutual-Coupling-Aware Modeling and Optimization

Stacked intelligent metasurfaces process the transmitted field layer by layer, and fluid antennas make the position of every radiator a design variable. Combined, they pack radiators at sub-wavelength spacings within and across layers, where mutual coupling governs the physics that current models omit. This paper develops a coupling-consistent model of a fluid transmit layer illuminating a stack of passive fluid beyond-diagonal layers. The multiport impedance matrix of any port constellation is shown to be the impedance kernel sampled at the three-dimensional separations, in one closed spherical-Hankel form whose in-plane restriction is intra-layer coupling and whose axial restriction replaces the scalar Rayleigh--Sommerfeld propagator. Only the transmitter is driven: the layer currents are induced, and the familiar cascade is the single-pass limit of one matrix inversion. In the wavenumber domain the light circle still separates radiation from reaction, now with a plane-wave propagator attached, every Fourier mode sees a transmission line loaded by the layers, and an efficiency identity shows that what the stack costs in efficiency is set by its total induced-current norm, not by its layer count. Because the load is never assumed layer-diagonal, interconnections may join atoms on different sheets, and vertical networks repeated at every site are spectrally local. Alternating optimization designs precoders, positions, and loads with closed-form gradients. Numerically, fluid ports on a $λ/8$ grid perform within a few per cent of continuously movable ones, while a design based on the conventional cascade model can do worse than open-circuiting the stack.

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arXiv2026

Mutual-Coupling-Aware Movable and Fluid Antennas on Holographic Surfaces: A Wavenumber-Domain Circuit-Field Unification

Movable and fluid antenna systems turn antenna position into a design variable. At sub-wavelength spacings, however, their behavior is governed by mutual coupling, modeled today by two disjoint traditions: circuit-theoretic impedance matrices with element-level constants, and field-theoretic kernels with norm-type power constraints. This paper unifies the two. Starting from the impedance kernel of a holographic surface, a Poynting-anchored balance identifies its resistive part with ohmic plus radiated power and its reactive part with stored-energy imbalance, and a circuit-field equivalence shows that the multiport impedance matrix is the kernel sampled at the port separations, in a single closed spherical-Hankel form. In the wavenumber domain the resistive kernel asymptotically diagonalizes in the aperture size: visible modes radiate at closed-form prices, evanescent modes only dissipate, and a flexible port becomes a constant-modulus codeword whose coupling is the pullback of the spectral weight. Coupling-aware multi-user sum-rate maximization over precoders and port positions is then formulated under physical power and voltage constraints and solved by weighted-MMSE and projected-gradient steps with closed-form gradients. A modal relaxation upper-bounds every port configuration and seeds the search by FFT-based codeword projection. A half-wavelength corollary and a superdirectivity margin quantify when coupling hurts, and when it helps.

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arXiv2026

Performance Analysis of RSMA-Enabled Bistatic ISAC in LEO Networks with Holographic Apertures and Fluid-Antenna Users

This paper develops an ergodic performance framework for rate-splitting multiple access (RSMA)-enabled bistatic integrated sensing and communication (ISAC) in a low-Earth-orbit (LEO) satellite network with an amplitude-constrained reconfigurable holographic surface (RHS) and fluid-antenna-system (FAS) users. Deterministic angle-based common and zero-forcing private reference beams are realized through one shared multi-feed RHS amplitude state and stream-specific feed-domain precoders, and the resulting self-, leakage-, and target-direction gains are retained explicitly. Conservative private- and common-rate lower bounds are derived for both reference-port and best-of-$P$ FAS reception while preserving the same-port selection coupling. For sensing, a closed-form average bistatic sensing signal-to-noise ratio (SNR) is obtained under nearest-receiver association and a finite target--receiver guard distance, with extensions to angle-conditioned footprint averaging and angular scheduling. Monte Carlo results confirm the tightness of the analytical rate bounds and validate the sensing expressions. Benchmarks show that scalar RHS-efficiency models can miss strong direction-dependent effects and that nearest-ground-receiver bistatic sensing provides a $17.7$--$25.7$~dB mean SNR advantage over a favorable monostatic LEO reference for $N_{\rm RHS}=16384$ over LEO altitudes of $400$--$1000$~km. FAS gains are largest in scattering-rich regimes, while the realized shared-state RHS target gain need not vary monotonically with aperture size.

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arXiv2026

Terahertz Inter-Satellite Links: Motivation, Challenges and Opportunities

Inter-satellite links (ISLs) are essential to the evolution of next-generation satellite constellations, providing the foundation for low-latency, resilient, and globally scalable connectivity. While low radio-frequency (RF)-based ISLs offer technological maturity, they are increasingly constrained by spectrum scarcity, congestion, and interference. Optical ISLs, on the other hand, deliver unprecedented capacity but demand ultra-precise pointing, suffer from narrow-beam limitations, and are limited to point-to-point links, all of which hinder large-scale deployment, including point-to-multi-point capability. To overcome these limitations, we propose very-high RF terahertz (THz) inter-satellite links (ISLs) as a promising middle-ground solution, merging the ultra-high data rates of optical links with the adaptability, reliability, and relaxed pointing requirements of lower-frequency RF ISLs. However, despite growing interest, research on THz ISLs remains at an early stage, fragmented across isolated studies, and lacking a clear roadmap for practical realization. This paper aims to address this gap by examining the fundamentals of THz ISLs, assessing their potential advantages and key challenges, and identifying the most promising research directions to transform them into a cornerstone of future interconnected mega constellations.

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arXiv2026

Energy Efficient Multi-User Beamforming and 3D Position Optimization for SIM-Assisted UAVs

This paper studies energy-efficient downlink multi-user transmissions with unmanned aerial vehicle (UAV) communication systems equipped with stacked intelligent metasurfaces (SIM), enabling wave-domain analog beamforming through multiple cascaded metasurface layers, while low-dimensional digital precoding is carried out using a limited number of transmit radio-frequency chains. This architecture enables flexible electromagnetic wave manipulation with reduced hardware complexity, making it particularly suitable for energy-constrained aerial platforms. We formulate a hardware-aware energy-efficiency (EE) maximization problem aiming to jointly optimize the digital precoder, the phase shifts of all SIM layers, and the three-dimensional UAV position under transmit-power, SIM operation, and UAV deployment constraints. The resulting problem is highly non-convex due to the fractional objective, the cascaded SIM structure and the unit-modulus phase constraints of the constituent metasurface layers, as well as the non-linear UAV-dependent channel. To address these challenges, we develop a transform-based alternating optimization framework that combines Dinkelbach's method, dual and quadratic transforms, to enable closed-form digital beamforming, Riemannian manifold optimization for SIM phase shifts, and successive convex approximation (SCA) for UAV positioning. Convergence and complexity analyses are provided to characterize the proposed algorithm. The presented numerical results showcase that the proposed joint design significantly improves EE compared with fully digital and maximum ratio transmission benchmark schemes, while revealing important design trade-offs among transmit power, SIM size, and the number of its constituent stacked layers.

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arXiv2026

Extremely Large Beyond-Diagonal RIS: Low-Rank Modal Optimization for Near-Field Communications

Beyond-diagonal reconfigurable intelligent surfaces (BD-RIS) achieve their best performance when fully connected, at the price of an optimization and hardware burden that grows quadratically, and per iteration cubically, with the number of elements. Extremely large surfaces make this burden prohibitive, while their sheer aperture places both the base station and the users in the radiative near field, where far-field design tools break down. This paper introduces the extremely large BD-RIS (XL-BD-RIS) concept and shows that near-field geometry is precisely what makes fully connected performance affordable at scale. Modeling the cascade with the free-space Green function, we prove that the aperture fields live in a low-dimensional subspace spanned by the spherical-wave responses of the terminal positions, and we design a compact unitary modal matrix on this subspace, built from localization information alone, that provably attains the fully connected optimum with a number of reconfigurable entries set by the geometry and independent of the panel size. A weighted-MMSE Riemannian algorithm optimizes the beamformers and the modal matrix with monotone convergence at panel-size-independent cost. Numerical results show that a $24\times24$-element panel reaches the fully connected optimum with about two hundred entries instead of three hundred thousand. A mismatched DFT beamspace pays a sixty-fold entry penalty rooted in the beam spread of spherical wavefronts, while the classical block-wise architecture delivers strictly lower rates at any matched entry budget.

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arXiv2026

Wavenumber-Domain Virtual Arrays for Holographic Near-Field Localization

Monostatic localization of multiple point targets is studied for a holographic aperture operated through wavenumber-domain modes. A specular-point condition delimits the validity of the spectral model as a near-field approximation. A single snapshot observes a projection of dimension at most the target count times the polarization components, while invertible coding recovers the full channel and places the decoded data on the difference lattice of transmit and receive wavenumbers. Rank conditions settle identifiability, and the Fisher matrix reduces to a covariance over the lattice, dictating a nested mode selection that attains full-aperture resolution with only tens of RF chains.

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arXiv2026

Stacked Intelligent Metasurfaces Assisted UAV Communications

In this paper, we investigate an unmanned aerial vehicle (UAV) communication system assisted by stacked intelligent metasurfaces (SIMs), which enable programmable wave-domain signal processing through multiple cascaded metasurface layers. By shifting part of the beamforming functionality from the RF/digital domain to the electromagnetic domain, SIMs allow the realization of energy-efficient hybrid beamforming architectures suitable for aerial platforms. We formulate the joint design of digital precoding, SIM phase configuration, and UAV positioning for multi-user downlink sum-rate maximization. To solve the resulting non-convex problem, we develop an alternating optimization framework that guarantees monotonic improvement of the objective. Numerical results demonstrate that the proposed SIM-assisted architecture significantly improves spectral efficiency while maintaining low hardware complexity, and highlight the impact of the number of metasurface layers and size of each layer on system performance.

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arXiv2026

Low-Complexity Learning-Based Beamforming for Ultra-Massive MIMO THz Communications

Terahertz (THz) communications have emerged as a key technology for escalating data rates in future generation wireless networks. However, severe propagation losses at THz frequencies pose significant challenges, which can be mitigated via ultra-massive multiple-input multiple-output (UM-MIMO) systems employing highly directional transmissions. To this end, codebook-based analog beamforming constitutes a realistic solution, eliminating the need for explicit channel estimation. However, in UM-MIMO systems, the use of extremely narrow beams makes beam training and alignment increasingly challenging, leading to a substantial increase in the number of codewords to be tested and, thus, to high computational complexity. In this paper, a novel artificial neural network architecture for low-complexity beam training in UM-MIMO THz systems is presented, which does not require a constant feedback link between transmitter and receiver to obtain the best beamformer and combiner pair. An inception and residual network, which is trained based on the received signal powers using the transmit and receive codewords generated from predefined hierarchical codebooks, is designed. Our numerical investigations demonstrate that the proposed machine learning approach significantly reduces the complexity of UM-MIMO transmit and receive beamforming design, as compared to the standard exhaustive and hierarchical beam searching methods.

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