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Hangsong Yan

Publications and source records attributed to Hangsong Yan.

16 recordsLinked to original sources

Spectral Approximation and Ergodic-Capacity Convergence of HMIMO Channels under Spatial-Wavenumber Domain Mismatch

We establish quantitative results on finite-dimensional spectral approximation and ergodic-capacity convergence for continuous Holographic Multiple-Input Multiple-Output (HMIMO) channels with square apertures and physically prescribed circular wavenumber support. The resulting spatial-wavenumber domain mismatch leads to a non-separable square-disk concentration problem for which the classical separable construction based on prolate spheroidal wave functions (PSWFs) cannot be directly applied. We project the continuous operator onto a tensor-product subspace of one-dimensional (1D) PSWFs while preserving the circular wavenumber support, yielding a generally non-diagonal but highly sparse finite-dimensional matrix. We show that the whole-spectrum approximation error, accounting for retained-eigenvalue perturbations and the residual spectral tail, remains controlled by a 1D PSWF eigenvalue-tail envelope despite the loss of separability and induced off-diagonal coupling. Beyond an explicit 1D truncation threshold, this error decays super-exponentially. This analysis further yields an asymptotic upper envelope for the eigenspectrum under the flattened two-dimensional eigenvalue ordering. We further establish a non-asymptotic upper bound on the gap between the actual ergodic capacities of the continuous and tensor-PSWF-truncated channels under their respective transmit-covariance optimizations. Combined with the spectral result, this capacity-gap bound inherits the same super-exponential dependence on the truncation order. Finally, quadrature rules with explicit radial and angular node thresholds are developed for evaluating the projected matrix. Numerical results show that conventional truncation based on spatial degrees of freedom can omit performance-relevant modes, particularly for compact apertures.

cs.IT

Computational and Effective Degrees of Freedom for Spatially Stationary HMIMO Channel Modeling

This paper establishes a comprehensive theoretical framework for the continuous-to-discrete modeling of spatially stationary holographic MIMO (HMIMO) channels utilizing the Nystrom method with Gauss-Legendre quadrature (NGLQ). Starting with an operator-theoretic analysis of the NGLQ method, we prove that its quadrature error exhibits a super-exponential decay. Furthermore, we derive a spatial sampling threshold, termed computational degrees of freedom (cDoF), which reveals a {\pi}/2 oversampling penalty over the physical DoF for 1D arrays, compounding to a 68% computational redundancy for 2D separable grids. To address the ill-conditioning of the eigenvalue decomposition (EVD) problem inherent to the Nystrom discretization, we invoke the multidimensional Szego-Widom asymptotic expansion. This analysis yields a physically grounded semi-analytical expression for the effective DoF (eDoF) of 2D rectangular apertures, capturing the anisotropic boundary truncation effects to guide partial EVD and reduce computational complexity. Numerical evaluations confirm the tightness of the cDoF threshold under worst-case end-fire conditions. Moreover, simulations utilizing closed-form kernels for isotropic scattering verify that the derived eDoF acts as an accurate asymptotic approximation. Finally, by deploying the exact non-uniform discrete Fourier transform to eliminate interpolation error floors, we demonstrate spectral convergence down to the machine-precision level for non-isotropic scattering environments.

eess.SP

Robust Multi-Stream Massive MIMO Satellite Systems Based on Statistical CSI

This paper investigates multi-stream downlink precoding for massive multiple-input multiple-output low-Earthorbit satellite (SAT) communication systems. We adopt a delay and Doppler precompensation approach to achieve coherent transmission. Under this setting, we formulate a signal transmission model that incorporates the near-independent properties of inter-SAT interference and compensation errors. We then demonstrate that moving beyond single-stream transmission requires both multi-SAT cooperation and multi-antenna UTs. Based on this configuration and the established signal transmission model, we derive the first- and second-order statistical channel characteristics and utilize them to design locally optimal precoding algorithms for both total power constraint (TPC) and per-antenna power constraint (PAPC) conditions, which rely only on statistical channel state information (sCSI). In particular, the designed PAPC algorithm achieves linear complexity with respect to the number of antennas on the cooperative SATs. To reduce the computational complexity of the locally optimal precoder under TPC, we propose a low-complexity and robust precoding scheme optimized for both minimum mean squared error and sum-rate maximization objectives. Using majorization theory, we also provide a rigorous theoretical analysis of the optimal precoding structure under TPC. Moreover, the Lanczos algorithm is adopted to further reduce the complexity of the proposed robust designs. Simulation results show that when each SAT is equipped with a sufficiently large number of antennas, the proposed sCSI-based designs achieve performance comparable to that of instantaneous CSI-based designs.

eess.SP

Spatial Correlation and Degrees of Freedom in Arched HMIMO Arrays: A Closed-Form Analysis

This paper presents a closed-form analysis of spatial correlation and degrees of freedom (DoF) for arched holographic multiple-input multiple-output (HMIMO) arrays, which can be viewed as a special form of fluid antenna systems (FAS) when their geometry is fluidically adaptable. Unlike traditional planar configurations, practical HMIMO surfaces may exhibit curvature, significantly influencing their spatial characteristics and performance. We derive exact correlation expressions for both arched uniform linear arrays and arched uniform rectangular arrays, capturing curvature effects under far field propagation. Our results reveal that isotropic scattering results in DoF being dominated by the maximum span of the HMIMO array, such that shape effects are weakened, and bending does not significantly reduce the available spatial DoF. Numerical simulations validate the accuracy of the closed-form formulas and demonstrate the robustness of DoF against curvature variations, supporting flexible array designs. These findings offer fundamental insights into geometry-aware optimization for next-generation HMIMO/FAS systems and pave the way for practical implementations of curved HMIMO arrays.

eess.SY

Deep Learning-Based Beamforming Design Using Target Beam Patterns

This paper proposes a deep learning-based beamforming design framework that directly maps a target beam pattern to optimal beamforming vectors across multiple antenna array architectures, including digital, analog, and hybrid beamforming. The proposed method employs a lightweight encoder-decoder network where the encoder compresses the complex beam pattern into a low-dimensional feature vector and the decoder reconstructs the beamforming vector while satisfying hardware constraints. To address training challenges under diverse and limited channel station information (CSI) conditions, a two-stage training process is introduced, which consists of an offline pre-training for robust feature extraction using an auxiliary module, followed by online training of the decoder with a composite loss function that ensures alignment between the synthesized and target beam patterns in terms of the main lobe shape and side lobe suppression. Simulation results based on NYUSIM-generated channels show that the proposed method can achieve spectral efficiency close to that of fully digital beamforming under limited CSI and outperforms representative existing methods.

eess.SP

Channel Knowledge Maps for 6G Wireless Networks: Construction, Applications, and Future Challenges

The advent of 6G wireless networks promises unprecedented connectivity, supporting ultra-high data rates, low latency, and massive device connectivity. However, these ambitious goals introduce significant challenges, particularly in channel estimation due to complex and dynamic propagation environments. This paper explores the concept of channel knowledge maps (CKMs) as a solution to these challenges. CKMs enable environment-aware communications by providing location-specific channel information, reducing reliance on real-time pilot measurements. We categorize CKM construction techniques into measurement-based, model-based, and hybrid methods, and examine their key applications in integrated sensing and communication systems, beamforming, trajectory optimization of unmanned aerial vehicles, base station placement, and resource allocation. Furthermore, we discuss open challenges and propose future research directions to enhance the robustness, accuracy, and scalability of CKM-based systems in the evolving 6G landscape.

eess.SP

Small-Scale Spatial-Temporal Correlation and Degrees of Freedom for Reconfigurable Intelligent Surfaces

The reconfigurable intelligent surface (RIS) is an emerging promising candidate technology for future wireless networks, where the element spacing is usually of sub-wavelength. Only limited knowledge, however, has been gained about the spatial-temporal correlation behavior among the elements in an RIS. In this paper, we investigate the spatial-temporal correlation for an RIS-enabled wireless communication system. Specifically, a joint small-scale spatial-temporal correlation model is derived under isotropic scattering, which can be represented by a four-dimensional sinc function. Furthermore, based upon the spatial-only correlation at a certain time instant, an essential RIS property -- the spatial degrees of freedom (DoF) -- is revisited, and an analytical expression is propounded to characterize the spatial DoF for RISs with realistic hence non-infinitesimal element spacing and finite aperture sizes. The results are vital to the accurate evaluation of various system performance metrics.

cs.NI

Can Massive MIMO Support URLLC?

We investigate the feasibility of using Massive MIMO to support URLLC in both coherence interval based and 3GPP compliant pilot settings. We consider grant-free uplink transmission with MMSE receiver and adopt 3GPP channel models. In the coherence interval based pilot setting, by extensive system level simulations, we find that using a Massive MIMO base station with 128 antennas and MMSE receiver, URLLC requirements can be achieved in Urban Macro (UMa) Non-Line of Sight (NLoS) with orthogonal pilots and Neyman-Pearson detector. However, in the 3GPP compliant pilot setting, even by using the covariance matrix of Physical Resource Block (PRB) subcarriers for active UE detection and channel estimation as well as open-loop power control, we find that URLLC requirements are still challenging to achieve due to the insufficient pilot length and pilot symbol location regulations in a PRB.

cs.IT

Optimally Supporting IoT with Cell-Free Massive MIMO

We study internet of things (IoT) systems supported by cell-free (CF) massive MIMO (mMIMO) with optimal linear channel estimation. For the uplink, we consider optimal linear MIMO receiver and obtain an uplink SINR approximation involving only large-scale fading coefficients using random matrix (RM) theory. Using this approximation we design several max-min power control algorithms that incorporate power and rate weighting coefficients to achieve a target rate with high energy efficiency. For the downlink, we consider maximum ratio (MR) beamforming. Instead of solving a complex quasi-concave problem for downlink power control, we employ a neural network (NN) technique to obtain comparable power control with around 30 times reduction in computation time. For large networks we proposed a different NN based power control algorithm. This algorithm is sub-optimal, but its big advantage is that it is scalable.

cs.IT

Channel Estimation for Reconfigurable Intelligent Surface-Assisted Wireless Communications Considering Doppler Effect

In wireless systems aided by reconfigurable intelligent surfaces (RISs), channel state information plays a pivotal role in achieving the performance gain of RISs. Mobility renders accurate channel estimation (CE) more challenging due to the Doppler effect. In this letter, we propose two practical wideband CE schemes incorporating Doppler shift adjustment (DSA) for multi-path and single-path propagation environments, respectively, for RIS-assisted communication with passive reflecting elements. For the multi-path scenario, ordinary CE is first executed assuming quasi-static channels, followed by DSA realized via joint RIS reflection pattern selection and transformations between frequency and time domains. The proposed CE necessitates only one more symbol incurring negligible extra overhead compared with the number of symbols required for the original CE. For the single-path case which is especially applicable to millimeter-wave and terahertz systems, a novel low-complexity CE method is devised capitalizing on the form of the array factors at the RIS. Simulation results demonstrate that the proposed algorithms yield high CE accuracy and achievable rate with low complexity, and outperform representative benchmark schemes.

cs.IT

A Scalable and Energy Efficient IoT System Supported by Cell-Free Massive MIMO

An IoT (Internet of things) system supports a massive number of IoT devices wirelessly. We show how to use Cell-Free Massive MIMO (multiple-input and multiple-output) to provide a scalable and energy efficient IoT system. We employ optimal linear estimation with random pilots to acquire CSI (channel state information) for MIMO precoding and decoding. In the uplink, we employ optimal linear decoder and utilize RM (random matrix) theory to obtain two accurate SINR (signal-to-interference plus noise ratio) approximations involving only large-scale fading coefficients. We derive several max-min type power control algorithms based on both exact SINR expression and RM approximations. Next, we consider the power control problem for downlink (DL) transmission. To avoid solving a time-consuming quasi-concave problem that requires repeat tests for the feasibility of a SOCP (second-order cone programming) problem, we develop a neural network (NN) aided power control algorithm that results in 30 times reduction in computation time. This power control algorithm leads to scalable Cell-Free Massive MIMO networks in which the amount of computations conducted by each AP does not depend on the number of network APs. Both UL and DL power control algorithms allow visibly improve the system spectral efficiency (SE) and, more importantly, lead to multi-fold improvements in Energy Efficiency (EE), which is crucial for IoT networks.

eess.SY

Joint MMSE Transceiver Design for Downlink Heterogeneous Network

In this paper, we propose a minimum mean square error (MMSE) based transceiver design scheme for a downlink multiple-input multiple-output (MIMO) two-tier heterogeneous network with general linear equality per-cell power constraints. Three practical channel models with both perfect and imperfect channel state information are used in simulations. In each channel model, we consider two system configurations, two data transmission schemes and two cellular cooperation scenarios. Our study shows that the proposed MMSE scheme is more flexible than interference alignment (IA) based scheme. For the cases where the IA-type scheme is applicable, the proposed scheme generally outperforms IA-type scheme in terms of average sum rate and bit error rate (BER), but is computationally more complex than the IA-type scheme.

cs.IT

Small-Scale, Local Area, and Transitional Millimeter Wave Propagation for 5G Communications

This paper studies radio propagation mechanisms that impact handoffs, air interface design, beam steering, and MIMO for 5G mobile communication systems. Knife edge diffraction (KED) and a creeping wave linear model are shown to predict diffraction loss around typical building objects from 10 to 26 GHz, and human blockage measurements at 73 GHz are shown to fit a double knife-edge diffraction (DKED) model which incorporates antenna gains. Small-scale spatial fading of millimeter wave received signal voltage amplitude is generally Ricean-distributed for both omnidirectional and directional receive antenna patterns under both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions in most cases, although the log-normal distribution fits measured data better for the omnidirectional receive antenna pattern in the NLOS environment. Small-scale spatial autocorrelations of received voltage amplitudes are shown to fit sinusoidal exponential and exponential functions for LOS and NLOS environments, respectively, with small decorrelation distances of 0.27 cm to 13.6 cm (smaller than the size of a handset) that are favorable for spatial multiplexing. Local area measurements using cluster and route scenarios show how the received signal changes as the mobile moves and transitions from LOS to NLOS locations, with reasonably stationary signal levels within clusters. Wideband mmWave power levels are shown to fade from 0.4 dB/ms to 40 dB/s, depending on travel speed and surroundings.

cs.IT

Millimeter Wave Small-Scale Spatial Statistics in an Urban Microcell Scenario

This paper presents outdoor wideband small-scale spatial fading and autocorrelation measurements and results in the 73 GHz millimeter-wave (mmWave) band conducted in downtown Brooklyn, New York. Both directional and omnidirectional receiver (RX) antennas are studied. Two pairs of transmitter (TX) and RX locations were tested with one line-of-sight (LOS) and one non-line-of-sight (NLOS) environment, where a linear track was employed at each RX to move the antenna in half-wavelength increments. Measured data reveal that the small-scale spatial fading of the received signal voltage amplitude are generally Ricean-distributed for both omnidirectional and directional RX antenna patterns under both LOS and NLOS conditions in most cases, except for the log-normal distribution for the omnidirectional RX antenna pattern in the NLOS environment. Sinusoidal exponential and typical exponential functions are found to model small-scale spatial autocorrelation of the received signal voltage amplitude in LOS and NLOS environments in most cases, respectively. Furthermore, different decorrelation distances were observed for different RX track orientations, i.e., for different directions of motion relative to the TX. Results herein are valuable for characterizing small-scale spatial fading and autocorrelation properties in multiple-input multiple-output (MIMO) systems for fifth-generation (5G) mmWave frequencies.

cs.IT

A Flexible Wideband Millimeter-Wave Channel Sounder with Local Area and NLOS to LOS Transition Measurements

This paper presents a millimeter-wave (mmWave) wideband sliding correlator channel sounder with flexibility to operate at various transmission rates. The channel sounder can transmit and receive up to 1 GHz of RF null-to-null bandwidth while measuring a 2 nanosecond multipath time resolution. The system architecture takes advantage of field-programmable gate arrays (FPGAs), high-speed digital-to-analog converters (DACs), and low phase noise Rubidium (Rb) references for synchronization. Using steerable narrowbeam antennas, the system can measure up to 185 dB of path loss. The channel sounder is used to measure the directional and omnidirectional received power as a receiver transitions from line-of-sight to non-line-of-sight conditions down an urban canyon. A 25 dB drop in omnidirectional received power was observed as the receiver transitioned from line-of-sight (LOS) conditions to deeply shadowed non-LOS (NLOS) conditions. The channel sounder was also used to study signal variation and spatial consistency for a local set of receiver locations arranged in a cluster spanning a 5 m x 10 m local area, where the omnidirectional received power in LOS and NLOS environments is found to be relatively stable with standard deviations of received power of 2.2 dB and 4.3 dB, respectively. This work shows that when implementing beamforming at the transmitter at mmWave, the omnidirectional received power over a local area has little fluctuation among receiver locations separated by a few to several meters.

cs.IT

Millimeter Wave Wireless Communications: New Results for Rural Connectivity

This paper shows the remarkable distances that can be achieved using millimeter wave communications, and presents a new rural macrocell (RMa) path loss model for millimeter wave frequencies, based on measurements at 73 GHz in rural Virginia. Path loss models are needed to estimate signal coverage and interference for wireless network design, yet little is known about rural propagation at millimeter waves. This work identifies problems with the RMa model used by the 3rd Generation Partnership Project (3GPP) TR 38.900 Release 14, and offers a close-in (CI) reference distance model that has improved accuracy, fewer parameters, and better stability as compared with the existing 3GPP RMa path loss model. The measurements and models presented here are the first to validate rural millimeter wave path loss models.

cs.IT