Massive multiple-input multiple-output (MIMO) systems with one-bit analog-to-digital converters (ADCs) face a severe trade-off between hardware efficiency and channel estimation accuracy. While generative adversarial networks (GANs) show promise for this challenge, their deployment is hindered by training instability and mode collapse. To address these issues, we propose ReRpGAN, a novel adversarial learning framework that integrates a regularized relativistic pairing GAN loss and anL1loss within a deep residual network. This architecture effectively stabilizes the training process and prevents mode collapse, enabling precise channel reconstruction from severely quantized signals. Extensive experiments on a realistic ray-tracing channel dataset validate our theoretical claims. Key findings demonstrate that ReRpGAN consistently outperforms conventional GAN-based and deep learning estimators, particularly in challenging scenarios with low signal-to-noise ratios and limited pilot overhead. Furthermore, unlike existing methods that suffer from divergence, ReRpGAN exhibits superior scalability, delivering improved estimation accuracy as the number of base station antennas increases. This work sets a new benchmark for robust, data-driven channel estimation in next-generation wireless systems.

Modeling the wireless radiance field (WRF) is fundamental to modern communication systems, enabling key tasks such as localization, sensing, and channel estimation. Traditional approaches, which rely on empirical formulas or physical simulations, often suffer from limited accuracy or require strong scene priors. Recent neural radiance field (NeRF)-based methods improve reconstruction fidelity through differentiable volumetric rendering, but their reliance on computationally expensive multilayer perceptron (MLP) queries hinders real-time deployment. To overcome these challenges, we introduce Gaussian splatting (GS) to the wireless domain, leveraging its efficiency in modeling optical radiance fields to enable compact and accurate WRF reconstruction. Specifically, we propose SwiftWRF, a deformable 2D Gaussian splatting framework that synthesizes WRF spectra at arbitrary positions under single-sided transceiver mobility. SwiftWRF employs CUDA-accelerated rasterization to render spectra at over 100 k FPS and uses the lightweight MLP to model the deformation of 2D Gaussians, effectively capturing mobility-induced WRF variations. In addition to novel spectrum synthesis, the efficacy of SwiftWRF is further underscored in its applications in angle-of-arrival (AoA) and received signal strength indicator (RSSI) prediction. Experiments conducted on both real-world and synthetic indoor scenes demonstrate that SwiftWRF can reconstruct WRF spectra up to 500x faster than existing state-of-the-art methods, while significantly enhancing its signal quality.

Phase-time arrays (PTAs), integrating phase shifters and true-time delays, emerge as a cost-effective and energy-efficient architecture for frequency-dependent beamforming in wideband communications. In this work, we investigate a wideband system in which a base station equipped with a PTA and single RF chain serves multiple near-field and far-field users. The goal is to jointly optimize PTA-based beamforming, subband allocation, and power allocation to maximize overall system performance. To this end, we formulate a system utility maximization problem, which includes sum-rate and geometric mean rate maximization as special cases and is highly non-convex. We first develop a three-step alternating optimization (AO) algorithm that iteratively optimizes the beamforming and resource allocations. To further enhance efficiency, we propose an unsupervised learning-based approach that combines a convolutional neural network, a graph attention network (GAT), and a normalization module with a utility-driven loss and a learnable adjacency initialized from hardware couplings. Simulation results confirm that PTAs strike a superior balance between energy efficiency and spectral efficiency compared with fully-digital and phased array architectures. The proposed GAT achieves AO-level performance with orders-of-magnitude lower computational complexity, i.e., only about 0.1% in our simulations.

Maritime channel modeling is crucial for designing robust nearshore communication systems, yet reliable models that account for the dynamic marine environment with varying sea waves, wind conditions, and vessel motions remain scarce. This article investigates land-to-ship maritime wireless channel characteristics at 5.8 GHz based upon an extensive measurement campaign, with concurrent hydrological and meteorological information collection. First, a novel large-scale path loss model with physical foundation and high accuracy is proposed for dynamic marine environments. Then, we introduce the concept of sea-wave-induced fixed-point (SWIFT) fading, a peculiar phenomenon in maritime scenarios that captures the impact of sea surface fluctuations on received power. An enhanced two-ray model incorporating vessel rotational motion is propounded to simulate the SWIFT fading, showing good alignment with measured data, particularly for modest antenna movements. Next, the small-scale fading is studied by leveraging a variety of models including the two-wave with diffuse power (TWDP) and asymmetric Laplace distributions, with the latter performing well in most cases, while TWDP better captures bimodal fading in rough seas. Furthermore, maritime channel sparsity is examined via the Gini index and RicianKfactor, and temporal dispersion is characterized. The resulting channel models and parameter characteristics offer valuable insights for maritime wireless system design and deployment.

This paper studies an integrated sensing and communications (ISAC) system for low-altitude economy (LAE), where a ground base station (GBS) provides communication and navigation services for authorized unmanned aerial vehicles (UAVs), while sensing the low-altitude airspace to monitor the unauthorized mobile target. The expected communication sum-rate over a given flight period is maximized by jointly optimizing the beamforming at the GBS and UAVs’ trajectories, subject to the constraints on the average signal-to-noise ratio requirement for sensing, the flight mission and collision avoidance of UAVs, as well as the maximum transmit power at the GBS. Typically, this is a sequential decision-making problem with the given flight mission. Thus, we transform it to a specific Markov decision process (MDP) model called episode task. Based on this modeling, we propose a novel LAE-oriented ISAC scheme, referred to as Deep LAE-ISAC (DeepLSC), by leveraging the deep reinforcement learning (DRL) technique. In DeepLSC, a reward function and a new action selection policy termed constrained noise-exploration policy are judiciously designed to fulfill various constraints. To enable efficient learning in episode tasks, we develop a hierarchical experience replay mechanism, where the gist is to employ all experiences generated within each episode to jointly train the neural network. Besides, to enhance the convergence speed of DeepLSC, a symmetric experience augmentation mechanism, which simultaneously permutes the indexes of all variables to enrich available experience sets, is proposed. Simulation results demonstrate that compared with benchmarks, DeepLSC yields a higher sum-rate while meeting the preset constraints, achieves faster convergence, and is more robust against different settings.

In mountainous emergency rescue operations, due to terrain occlusion, signals are often in a non-line-of-sight (NLoS) transmission state, resulting in a significant reduction in signal propagation distance. It is necessary to deploy an integrated positioning and communication (ILAC) network based on unmanned aerial vehicles (UAVs) to achieve optimal performance through trajectory planning and resource allocation. However, the complex and unpredictable terrain occlusion, coupled with dynamic user behavior, makes it difficult for traditional optimization methods to work, while the direct application of reinforcement learning (RL) is inefficient. To address these challenges, this paper proposes a hybrid action space soft actor-critic (GeoAgg-HSAC) decision framework based on geographic information state aggregation. First, a state aggregation method based on graph contrastive learning is designed. In this method, a pre-trained graph neural network (GNN) is used to map the UAV network state under similar occlusion conditions to a corresponding low-dimensional representation, thereby reducing the state dimension and allowing similar states to share policy experience, which improves sample efficiency. Then, a hybrid action space SAC network is constructed that can simultaneously make decisions on continuous UAV trajectories and discrete resource allocation. Experiments based on real mountain terrain and wireless data show that the proposed approach has significant advantages in optimizing communication and positioning performance.

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.

Joint phase-time arrays (JPTA) provide a low-cost and energy-efficient solution for enabling flexible frequency-dependent beams in wideband scenarios by incorporating both true-time delays (TTDs) and phase shifters. This paper explores the potential of JPTA with a single radio frequency chain to serve multiple users simultaneously in hybrid near- and far-fields. We concentrate on optimizing subband allocation and JPTA-based hybrid beamforming to maximize the total concave utility function associated with user rates. To achieve this, we propose an unsupervised deep learning (DL) approach. Our DL framework includes a two-layer convolutional neural network for feature extraction, followed by a three-layer graph attention network (GAT) and a normalization module for optimizing resource allocation and beamforming. The GAT effectively captures the interactions between resource allocation and analog beamformers. Simulation results demonstrate the superiority of JPTA over conventional phased arrays in terms of user rate when serving multiple users concurrently. Furthermore, adopting a logarithmic function of user rates as the utility function results in greater fairness than simply maximizing sum rates.

In future air-to-ground integrated networks, the scattering effects from ground-based scatterers, such as buildings, cannot be neglected in millimeter-wave and higher frequency bands, and have a significant impact on channel characteristics. However, current scattering measurement studies primarily focus on single incident angles within the incident plane, leading to insufficient characterization of scattering properties. In this paper, we present scattering measurements conducted at 28 GHz on various real-world building surfaces with multiple incident angles and three-dimensional (3D) receiving angles. The measured data are analyzed in conjunction with parameterized scattering models in ray tracing and numerical simulations. Results indicate that for millimeter-wave channel modeling near building surfaces, it is crucial to account not only for surface materials but also for the scattering properties of the building surfaces with respect to the incident angle and receiving positions in 3D space.

This paper considers an integrated sensing and communication system where a multi-antenna base station transmits a common signal for joint multi-user communication and extend target (ET) sensing. We first propose a second-order truncated Fourier series surface model for an arbitrarily-shaped three-dimensional (3D) ET, characterized by center range, center elevation, center azimuth, orientation, and surface coefficients. Based on this model, we consider the backscattering effects of the visible elements along the ET surface, and derive novel closed-form Cramér-Rao bounds (CRBs) for the ET characteristic parameter estimation. Further, we formulate a CRB minimization problem by optimizing the transmit beamformers, under the constraints of transmit power budget, communication-specific signal-to-interference-plus-noise requirements, and ET-specific beam coverage requirement. The non-convex optimization problem can be efficiently solved by the semidefinite relaxation technique. Numerical results demonstrate that the proposed beamforming design is superior to existing baselines with significantly lower CRBs and a more appropriate beampattern for sensing a 3D ET.

Integrated sensing and communication (ISAC) has attracted growing interests for enabling the future 6G wireless networks, due to its capability of sharing spectrum and hardware resources between communication and sensing systems. However, existing works on ISAC usually need to modify the communication protocol to cater for the new sensing performance requirement, which may be difficult to implement in practice. In this paper, we study a semi-passive intelligent reflecting surface (IRS) aided millimeter-wave (mmWave) ISAC system by exploiting the established beam scanning operation for simultaneous mmWave communications and sensing. First, we propose a two-phase ISAC protocol, consisting of beam scanning and data transmission. Specifically, in the beam scanning phase, the semi-passive IRS finds the optimal beam for reflecting signals from the base station to a communication user via its passive elements and, meanwhile, directly estimates the angle of a nearby target based on echo signals from the target using its active sensing elements. In the data transmission phase, the sensing accuracy is further improved by leveraging the data signals via possible IRS beam splitting. Next, we derive the achievable rate of the communication user as well as the Cramér-Rao bound and the approximate mean square error of the target angle estimation. Finally, extensive simulation results are provided to verify our analysis as well as the effectiveness of the proposed scheme.

This paper studies an integrated sensing and communication (ISAC) system, where a multi-antenna base station transmits beamformed signals for joint downlink multi-user communication and radar sensing of an extended target (ET). By considering echo signals as reflections from valid elements on the ET contour, a set of novel Cramér-Rao bounds (CRBs) is derived for parameter estimation of the ET, including central range, direction, and orientation. The ISAC transmit beamforming design is then formulated as an optimization problem, aiming to minimize the CRB associated with radar sensing, while satisfying a minimum signal-to-interference-pulse-noise ratio requirement for each communication user, along with a 3-dB beam coverage constraint tailored for the ET. To solve this non-convex problem, we utilize semidefinite relaxation (SDR) and propose a rank-one solution extraction scheme for non-tight relaxation circumstances. To reduce the computation complexity, we further employ an efficient zero-forcing (ZF) based beamforming design, where the sensing task is performed in the null space of communication channels. Numerical results validate the effectiveness of the obtained CRB, revealing the diverse features of CRB for differently shaped ETs. The proposed SDR beamforming design outperforms benchmark designs with lower estimation error and CRB, while the ZF beamforming design greatly improves computation efficiency with minor sensing performance loss.

Fast and precise beam alignment is crucial for high-quality data transmission in millimeter-wave (mmWave) communication systems, where large-scale antenna arrays are utilized to overcome the severe propagation loss. To tackle the challenging problem, we propose a novel deep learning-based hierarchical beam alignment method for both multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) systems, which learns two tiers of probing codebooks (PCs) and uses their measurements to predict the optimal beam in a coarse-to-fine search manner. Specifically, a hierarchical beam alignment network (HBAN) is developed for MISO systems, which first performs coarse channel measurement using a tier-1 PC, then selects a tier-2 PC for fine channel measurement, and finally predicts the optimal beam based on both coarse and fine measurements. The propounded HBAN is trained in two steps: the tier-1 PC and the tier-2 PC selector are first trained jointly, followed by the joint training of all the tier-2 PCs and beam predictors. Furthermore, an HBAN for MIMO systems is proposed to directly predict the optimal beam pair without performing beam alignment individually at the transmitter and receiver. Numerical results demonstrate that the proposed HBANs are superior to the state-of-the-art methods in both alignment accuracy and signaling overhead reduction.

In this paper, we consider a cooperative communication network where multiple low-Earth-orbit (LEO) satellites provide services to multiple ground users (GUs) cooperatively at the same time and on the same frequency. The multi-satellite cooperation has great potential in extending communication coverage and increasing spectral efficiency. Considering that the on-board radio-frequency circuit resources and computation resources on each satellite are restricted, we aim to propose a low-complexity yet efficient multi-satellite cooperative transmission framework. Specifically, we first propose a hybrid beamforming method consisting of analog beamforming for beam alignment and digital beamforming for interference mitigation. Then, to establish appropriate connections between the satellites and GUs, we propose a heuristic user scheduling algorithm which determines the connections according to the total spectral efficiency increment of the multi-satellite cooperative network. Next, considering the intrinsic connection between beamforming and user scheduling, a joint hybrid beamforming and user scheduling (JHU) scheme is proposed to dramatically improve the performance of the multi-satellite cooperative network. In addition to the single-connection scenario, we also consider the multi-connection case using the JHU scheme. Extensive simulations conducted over different LEO satellite constellations and across various GU locations demonstrate the superiority of the proposed schemes in both overall and per-user spectral efficiencies.

In this paper, we consider a cooperative communication network where multiple satellites provide services for ground users (GUs) (at the same time and on the same frequency). The communication and computational resources on satellites are usually restricted and the satellite-GU link determination affects the communication performance significantly when multiple satellites provide services for multiple GUs in a collaborative manner. Therefore, considering the limitation of the on-board radio-frequency chains, we first propose a hybrid beamforming method consisting of analog beamforming for beam alignment and digital beamforming for interference mitigation. Then, to establish appropriate connections between satellites and GUs, we propose a heuristic user scheduling algorithm which determines the connections according to the total spectral efficiency (SE) increment of the multi-satellite cooperative network. Next, a joint hybrid beamforming and user scheduling scheme is proposed to dramatically improve the performance of the multi-satellite cooperative network. Moreover, simulations are conducted to compare the proposed schemes with representative baselines and analyze the key factors influencing the performance of the multi-satellite cooperative network. It is shown that the proposed joint beamforming and user scheduling approach can provide 47.2% SE improvement on average as compared with its non-joint counterpart.

Since the start of 5G New Radio (NR) work in the 3rd Generation Partnership Project (3GPP) in early 2016, tremendous progress has been made in both standardization and commercial deployments. The first 5G NR release (Release 15) laid out a solid foundation in accommodating a diverse set of services, a wide range of spectra, and a variety of deployment scenarios, while being forward compatible. Expansion to vertical domain services [e.g., vehicle to everything (V2X), non-terrestrial networks (NTN)] was introduced in Release 16. Such an expansion was further accelerated in Release 17, with the standardization work being completed despite the extreme challenges due to COVID-19.

Since the start of 5G work in 3GPP in early 2016, tremendous progress has been made in both standardization and commercial deployments. 3GPP is now entering the second phase of 5G standardization, known as5G-Advanced, built on the 5G baseline in 3GPP Releases 15, 16, and 17. 3GPP Release 18, the start of 5G-Advanced, includes a diverse set of features that cover both device and network evolutions, providing balanced mobile broadband evolution and further vertical domain expansion and accommodating both immediate and long-term commercial needs. 5G-Advanced will significantly expand 5G capabilities, address many new use cases, transform connectivity experiences, and serve as an essential step in developing mobile communications towards 6G. This paper provides a comprehensive overview of the 3GPP 5G-Advanced development, introducing the prominent state-of-the-art technologies investigated in 3GPP and identifying key evolution directions for future research and standardization.

Integrated ultra-massive multiple-input multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) systems are promising for 6G and beyond Terahertz (0.1-10 THz) communications, to effectively bypass the barriers of limited coverage and line-of-sight blockage. However, excessive dimensions of UM-MIMO and IRS enlarge the near-field region, while strong THz channel sparsity in the far-field is detrimental to spatial multiplexing. Moreover, channel estimation (CE) requires recovering the large-scale channel from severely compressed observations due to limited RF-chains. To tackle these challenges, a hybrid spherical- and planar-wave channel model (HSPM) is introduced for the cascaded channel of the integrated system. The spatial multiplexing gains under near-field and far-field regions are analyzed, which are found to be limited by the segmented channel with a lower rank. Furthermore, a compressive sensing-based CE framework is developed, including a sparse channel representation method, a separate-side estimation (SSE) and a dictionary-shrinkage estimation (DSE) algorithms. Numerical results verify the effectiveness of the HSPM, the capacity of which is only$5\times 10^{-4}$bits/s/Hz deviated from that obtained by the ground-truth spherical-wave-model, with 256 elements. While the SSE achieves improved accuracy for CE than benchmark algorithms, the DSE is more attractive in noisy environments, with 1 dB lower normalized-mean-square error than SSE.

Reconfigurable intelligent surfaces (RISs) have emerged as a prospective technology for next-generation wireless networks due to their potential in coverage and capacity enhancement. Previous works on achievable rate analysis of RIS-assisted communication systems have mainly focused on the rich-scattering environment where Rayleigh and Rician channel models can be applied. This work studies the ergodic achievable rate of RIS-assisted multiple-input multiple-output communication systems in the millimeter-wave band with limited scattering under the Saleh-Valenzuela channel model. Firstly, we derive an upper bound of the ergodic achievable rate by means of majorization theory and Jensen’s inequality. The upper bound shows that the ergodic achievable rate increases logarithmically with the number of antennas at the base station (BS) and user, the number of the reflection units at the RIS, and the eigenvalues of the steering matrices associated with the BS, user and RIS. Then, we aim to maximize the ergodic achievable rate by jointly optimizing the transmit covariance matrix at the BS and the reflection coefficients at the RIS. Specifically, the transmit covariance matrix is optimized by the water-filling algorithm and the reflection coefficients are optimized using the Riemannian conjugate gradient algorithm. Simulation results validate the effectiveness of the proposed optimization algorithms.

Reconfigurable intelligent surface (RIS) has attracted extensive attention in recent years. However, most research focuses on the scenario of the narrowband and/or instantaneous channel state information (CSI), while wide bandwidth with the use of millimeter-wave (mmWave) (including sub-Terahertz) spectrum is a major trend in next-generation wireless communications, and statistical CSI is more practical to obtain in realistic systems. Thus, we consider the ergodic achievable rate of RIS-assisted mmWave multiple-input multiple-output orthogonal frequency division multiplexing communication systems. The widely used Saleh-Valenzuela channel model is adopted to characterize the mmWave channels and only the statistical CSI is available. We first derive the approximations of the ergodic achievable rate by means of the majorization theory and Jensen’s inequality. Then, an alternating optimization based algorithm is proposed to maximize the ergodic achievable rate by jointly designing the transmit covariance matrix at the base station and the reflection coefficients at the RIS. Specifically, the design of the transmit covariance matrix is transformed into a power allocation problem and solved by spatial-frequency water-filling. The reflection coefficients are optimized by the Riemannian conjugate gradient algorithm. Simulation results corroborate the effectiveness of the proposed algorithms.

When signals propagate through forest areas, they will be affected by environmental factors such as vegetation. Different types of environments have different influences on signal attenuation. This paper analyzes the existing classical propagation path loss models and the model with excess loss caused by forest areas and then proposes a new short-range wireless channel propagation model, which can be applied to different types of forest environments. We conducted continuous-wave measurements at a center frequency of 605 MHz on predetermined routes in distinct types of forest areas and recorded the reference signal received power. Then, we use various path loss models to fit the measured data based on different vegetation types and distributions. Simulation results show that the proposed model has substantially smaller fitting errors with reasonable computational complexity, as compared with representative traditional counterparts.

Multi-cell wireless systems usually encounter both intra-cell and inter-cell interference, which can be mitigated via coordinated multipoint (CoMP) transmission. Previous works on multi-cell analysis in the microwave band generally consider fully digital beamforming, requiring a complete radio-frequency chain behind each antenna. This is practically infeasible for millimeter-wave (mmWave) systems where large amounts of antennas are necessary to provide sufficient gain and to enable transmission/reception of multiple streams to/from a user. This paper provides a general methodology to analytically compute the expected per-cell spectral efficiency of an mmWave multi-cell single-stream system using phase-shifter-based analog beamforming and regularized zero-forcing digital beamforming. Four analog-digital hybrid beamforming techniques for multi-cell multi-stream mmWave communication are proposed, assuming that base stations in different cells can share channel state information to cooperatively transmit signals to their home-cell users. Spectral efficiency of the proposed hybrid beamforming approaches is investigated and compared using two channel models suitable for fifth-generation cellular systems, namely the 3rd Generation Partnership Project model and the NYUSIM model. Numerical results show that the benefits of base station coordination (as compared with the non-CoMP case) are governed by the underlying propagation model, and the aggregate interference levels proportional to the cell radius and number of users per cell. We show that in sparse channels, non-CoMP approaches exceed CoMP (coordinated beamforming) performance.

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.

This paper presents details and applications of a novel channel simulation software named NYUSIM, which can be used to generate realistic temporal and spatial channel responses to support realistic physical-and link-layer simulations and design for fifth-generation (5G) cellular communications. NYUSIM is built upon the statistical spatial channel model for broadband millimeter-wave (mmWave) wireless communication systems developed by researchers at New York University (NYU). The simulator is applicable for a wide range of carrier frequencies (500 MHz to 100 GHz), radio frequency (RF) bandwidths (0 to 800 MHz), antenna beamwidths (7° to 360° for azimuth and 7° to 45° for elevation), and operating scenarios (urban microcell, urban macrocell, and rural macrocell), and also incorporates multiple-input multiple-output (MIMO) antenna arrays at the transmitter and receiver. This paper also provides examples to demonstrate how to use NYUSIM for analyzing MIMO channel conditions and spectral efficiencies, which show that NYUSIM is an alternative and more realistic channel model compared to the 3rd Generation Partnership Project (3GPP) and other channel models for mmWave bands.

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.

Channel models describe how wireless channel parameters behave in a given scenario, and help evaluate link- and system-level performance. A proper channel model should be able to faithfully reproduce the channel parameters obtained in field measurements and accurately predict the spatial and temporal channel impulse response along with large-scale fading. This paper compares two popular channel models for next generation wireless communications: the 3rd Generation Partnership Project (3GPP) TR 38.900 Release 14 channel model and the statistical spatial channel model NYUSIM developed by New York University (NYU). The two channel models employ different modeling approaches in many aspects, such as the line-of-sight probability, path loss, and clustering methodology. Simulations are performed using the two channel models to analyze the channel eigenvalue distribution and spectral efficiency leveraging the analog/digital hybrid beamforming methods found in the literature. Simulation results show that the 3GPP model produces different eigenvalue and spectral efficiency distributions for mmWave bands, as compared to the outcome from NYUSIM that is based on massive amounts of real-world measured data in New York City. This work shows NYUSIM is more accurate for realistic simulations than 3GPP in urban environments.

For the development of new 5G systems to operate in bands up to 100 GHz, there is a need for accurate radio propagation models at these bands that currently are not addressed by existing channel models developed for bands below 6 GHz. This document presents a preliminary overview of 5G channel models for bands up to 100 GHz. These have been derived based on extensive measurement and ray tracing results across a multitude of frequencies from 6 GHz to 100 GHz, and this document describes an initial 3D channel model which includes: 1) typical deployment scenarios for urban microcells (UMi) and urban macrocells (UMa), and 2) a baseline model for incorporating path loss, shadow fading, line of sight probability, penetration and blockage models for the typical scenarios. Various processing methodologies such as clustering and antenna decoupling algorithms are also presented.

This paper presents 73 GHz human blockage measurements for a point-to-point link with a 5 m transmitter-receiver separation distance in an indoor environment, with a human that walked at a speed of approximately 1 m/s at a perpendicular orientation to the line between the transmitter and receiver, at various distances between them. The experiment measures the shadowing effect of a moving human body when using directional antennas at the transmitter and receiver for millimeter- wave radio communications. The measurements were conducted using a 500 Megachips-per-second wideband correlator channel sounder with a 1 GHz first null-to-null RF bandwidth. Results indicate high shadowing attenuation is not just due to the human blocker but also is due to the static directional nature of the antennas used, leading to the need for phased-array antennas to switch beam directions in the presence of obstructions and blockages at millimeter-waves. A simple model for human blockage is provided based on the double knife-edge diffraction (DKED) model where humans are approximated by a rectangular screen with infinite vertical height, similar to the human blockage model given by the METIS project.

This paper presents small-scale fading measurements for 28 GHz outdoor millimeter-wave ultrawideband channels using directional horn antennas at the transmitter and receiver. Power delay profiles were measured at half-wavelength spatial increments over a local area (33 wavelengths) on a linear track in two orthogonal receiver directions in a typical base-to-mobile scenario with fixed transmitter and receiver antenna beam pointing directions. The voltage path amplitudes are shown to follow a Rician distribution, with K-factor ranging from 9 - 15 dB and 5 - 8 dB in line of sight (LOS) and non-line of sight (NLOS) for a vertical-to-vertical co- polarized antenna scenario, respectively, and from 3 - 7 dB in both LOS and NLOS vertical-to- horizontal cross-polarized antenna scenario. The average spatial autocorrelation functions of individual multipath components reveal that signal amplitudes reach a correlation of 0 after 2 and 5 wavelengths in LOS and NLOS co-polarized V-V antenna scenarios. The models provided are useful for recreating path gain statistics of millimeter- wave wideband channel impulse responses over local areas, for the study of multi-element antenna simulations and channel estimation algorithms.

This paper presents and compares two candidate large-scale propagation path loss models, the alpha-beta-gamma (ABG) model and the close-in (CI) free space reference distance model, for the design of fifth generation (5G) wireless communication systems in urban micro- and macro-cellular scenarios. Comparisons are made using the data obtained from 20 propagation measurement campaigns or ray- tracing studies from 2 GHz to 73.5 GHz over distances ranging from 5 m to 1429 m. The results show that the one-parameter CI model has a very similar goodness of fit (i.e., the shadow fading standard deviation) in both line-of-sight and non-line-of-sight environments, while offering substantial simplicity and more stable behavior across frequencies and distances, as compared to the three-parameter ABG model. Additionally, the CI model needs only one very subtle and simple modification to the existing 3GPP floating-intercept path loss model (replacing a constant with a close-in free space reference value) in order to provide greater simulation accuracy, more simplicity, better repeatability across experiments, and higher stability across a vast range of frequencies.

It is becoming clear that 5G wireless systems will encompass frequencies from around 500 MHz all the way to around 100 GHz. To adequately assess the performance of 5G systems in these different bands, path loss (PL) models will need to be developed across this wide frequency range. The PL models can roughly be broken into two categories, ones that have some anchor in physics, and ones that curve- match only over the data set without any physical anchor. In this paper we use both real-world measurements from 2 to 28 GHz and ray-tracing studies from 2 to 73.5 GHz, both in an urban-macro environment, to assess the prediction performance of the two PL modeling techniques. In other words, we look at how the two different PL modeling techniques perform when the PL model is applied to a prediction set which is different in distance, frequency, or environment from a measurement set where the parameters of the respective models are determined. We show that a PL model with a physical anchor point can be a better predictor of PL performance in the prediction sets while also providing a parameterization which is more stable over a substantial number of different measurement sets.

Omnidirectional path loss models are vital for radiosystem design in wireless communication systems, as they allow engineers to perform network simulations for systems with arbitrary antenna patterns. At millimeter-wave frequencies, channel measurements are frequently conducted using steerable highgain directional antennas at both the transmitter and receiver to make up for the significant increase in free space path loss at these frequencies compared to traditional cellular systems that operate at lower frequencies. The omnidirectional antenna pattern, and resulting omnidirectional received power must therefore be synthesized from many unique pointing angles, where the transmit and receive antennas are rotated over many different azimuth and elevation planes. In this paper, the equivalent omnidirectional antenna pattern and omnidirectional received power are synthesized by summing the received powers from all measured unique pointing angles obtained at antenna halfpower beamwidth step increments in the azimuth and elevation planes, and this method is validated by demonstrating that the synthesized omnidirectional received power and path loss are independent of antenna beamwidth, through theoretical analyses and millimeter-wave propagation measurements using antennas with different beamwidths. The method in this paper is shown to provide accurate results while enhancing the measurement range substantially through the use of directional antennas.

Recently a measurement campaign was performed and a subsequent channel model proposal was created for an indoor office environment at 73 GHz. The channel model included a detailed modeling of polarization which was designed to capture the expected effects of polarization observed in the literature. Using this new channel model we perform a study of how polarization impacts the performance of an indoor millimeterwave (mmWave) communication system in a small-office environment. Particular emphasis is given to having only a single polarization at both ends of the link. The impact of polarization on large-scale fading, such as angle spread, channel rank, and system-level performance is considered. Results show that some polarization combinations at each end of the link can increase the delay and angle spreads while other combinations can decrease the spread. Results also show the importance of having mixed polarization types at both ends of the link (e.g., circular on one end and linear on the other) when each end has a single polarization type.

Next-generation wireless communications systems are expected to exploit frequency bands above 6 GHz. An important transition towards such bands will be design of channel models capable of supporting the design of efficient air-interface and networks. In this paper, we describe a geometry-based statistical channel model and apply ray-tracing simulation for its validation. Focusing on path loss and root-mean-square (RMS) delay spread as metrics, we show that the proposed modeling approach is flexible and realistic.

The use of millimeter wave (mmWave) frequencies for access links promises to provide an incredible user experience given the large bandwidths available. Using a recently-developed mmWave indoor channel model for the lower E-band (71-76 GHz), we investigate the system-level performance of a mmWave system in a small office-type environment. Particular attention is paid to the performance with different antenna array types. The results show that peak data rates in excess of 14 Gbps are possible and "everywhere" data rates of more than 100 Mbps are seen for all indoor locations. Also the results show that it is best to position the antennas in the azimuth dimension at the access point as opposed to elevation, and that there is little performance difference between circular and linear arrays with the same number of antenna elements. Finally the results demonstrate that the mobile can benefit from having arrays of directional patch antennas as long as there are sufficient patch arrays around the mobile to provide omni-like coverage.

The relatively unused millimeter-wave (mmWave) spectrum offers excellent opportunities to increase mobile capacity due to the enormous amount of available raw bandwidth. This paper presents experimental measurements and empirically-based propagation channel models for the 28, 38, 60, and 73 GHz mmWave bands, using a wideband sliding correlator channel sounder with steerable directional horn antennas at both the transmitter and receiver from 2011 to 2013. More than 15,000 power delay profiles were measured across the mmWave bands to yield directional and omnidirectional path loss models, temporal and spatial channel models, and outage probabilities. Models presented here offer side-by-side comparisons of propagation characteristics over a wide range of mmWave bands, and the results and models are useful for the research and standardization process of future mmWave systems. Directional and omnidirectional path loss models with respect to a 1 m close-in free space reference distance over a wide range of mmWave frequencies and scenarios using directional antennas in real-world environments are provided herein, and are shown to simplify mmWave path loss models, while allowing researchers to globally compare and standardize path loss parameters for emerging mmWave wireless networks. A new channel impulse response modeling framework, shown to agree with extensive mmWave measurements over several bands, is presented for use in link-layer simulations, using the observed fact that spatial lobes contain multipath energy that arrives at many different propagation time intervals. The results presented here may assist researchers in analyzing and simulating the performance of next-generation mmWave wireless networks that will rely on adaptive antennas and multiple-input and multiple-output (MIMO) antenna systems.

This paper presents millimeter wave propagation measurements in New York City and an analysis of signal outage at 28 and 73 GHz using similar spread spectrum sliding correlator channel sounders that employed high gain, directional steerable antennas (24.5 dBi gain antennas at 28 GHz and 27 dBi gain antennas at 73 GHz) at both the transmitter and receiver. Three identical transmitter locations were used for both the 28 and 73 GHz campaigns, while the 73 GHz campaign included two new TX locations. The 28 GHz campaign tested 25 receiver locations for each of the three transmitter locations, and the 73 GHz campaign tested 27 receiver locations in various combinations with the five transmitter sites. Overall, 75 TX-RX location combinations were tested at 28 GHz and 74 TX-RX combinations were tested at 73 GHz, with T-R (transmitter-receiver) separation distances up to 425 m. The maximum transmit power was 30 dBm at 28 GHz and 14.6 dBm at 73 GHz. Our analysis shows that the estimated outage probabilities at 28 and 73 GHz for the cellular communication scenario are 14% and 17%, respectively, and is 16% for the 73 GHz backhaul scenario.

The performance of multi-beam antenna equal gain combining for improving signal quality in future millimeter-wave cellular systems is evaluated in this article. Employing experimental data obtained from 28 GHz and 73 GHz propagation measurements in the dense urban environment of New York City, we present the impact of coherent bi-beam, tri-beam and quad-beam combining on path loss and shadow factors. The results reveal that a maximum of 24.9 dB improvement in path loss at 28 GHz and 34.8 dB at 73 GHz for 100 m T-R (transmitter-receiver) separation distances can be achieved via combining the strongest four received signals from distinct beams, when compared to the case of signals at the receiver with randomly pointed beams. Comparable path loss values are achieved at both 28 and 73 GHz bands. This paper demonstrates the potential of utilizing spatial filtering and beam combining to significantly improve received signal levels and link margins at millimeter-wave frequencies.

With the severe spectrum shortage in conventional cellular bands, millimeter wave (mmW) frequencies between 30 and 300 GHz have been attracting growing attention as a possible candidate for next-generation micro- and picocellular wireless networks. The mmW bands offer orders of magnitude greater spectrum than current cellular allocations and enable very high-dimensional antenna arrays for further gains via beamforming and spatial multiplexing. This paper uses recent real-world measurements at 28 and 73 GHz in New York, NY, USA, to derive detailed spatial statistical models of the channels and uses these models to provide a realistic assessment of mmW micro- and picocellular networks in a dense urban deployment. Statistical models are derived for key channel parameters, including the path loss, number of spatial clusters, angular dispersion, and outage. It is found that, even in highly non-line-of-sight environments, strong signals can be detected 100-200 m from potential cell sites, potentially with multiple clusters to support spatial multiplexing. Moreover, a system simulation based on the models predicts that mmW systems can offer an order of magnitude increase in capacity over current state-of-the-art 4G cellular networks with no increase in cell density from current urban deployments.

Wireless data traffic is projected to skyrocket 10 000 fold within the next 20 years. To tackle this incredible increase in wireless data traffic, a first approach is to further improve spectrally efficient systems such as 4G LTE in bands below 6 GHz by using more advanced spectral efficiency techniques. However, the required substantial increase in system complexity along with fundamental limits on hardware implementation and channel conditions may limit the viability of this approach. Furthermore, the end result would be an extremely spectrally efficient system with little room for future improvement to meet the ever-growing wireless data usage. The second approach is to move up in frequency, into an unused nontraditional spectrum where enormous bandwidths are available, such as at millimeter wave (mmWave). The mmWave option enables the use of simple air interfaces since large bandwidths can be exploited (e.g., 2 GHz) to achieve high data rates rather than relying on highly complex techniques originally aimed at achieving a high spectral efficiency with smaller bandwidths. In addition, mmWave systems will easily evolve to even higher system capacities, because there will be plenty of margin to improve the spectral efficiency as data demands further increase. In this paper, a case is made for using mmWave for a fifth generation (5G) wireless system for ultradense networks by presenting an overview of enhanced local area (eLA) technology at mmWave with emphasis on 5G requirements, spectrum considerations, propagation and channel modeling, air-interface and multiantenna design, and network architecture solutions.

This article demonstrates the performance of multi-beam antenna combining for improving link quality in future millimeter-wave cellular systems. Using experimental data obtained from 28 GHz propagation measurements in New York City [8], we demonstrate how the combination of two, three and four beams, either noncoherently or coherently at the mobile receiver antenna, can improve the propagation link substantially. The results reveal that an average of 28.1 dB improvement in path loss can be achieved via combining the strongest four received signals coherently, when compared to the case of randomly received signals using a single beam at the receiver. This paper is the first to present the potential of multi-beam combining for improving link budget (e.g., extending range) in future mm-wave urban cellular systems.

In this paper, we present reflection coefficients and penetration losses for common building materials at 28 GHz for the design and deployment of future millimeter wave mobile communication networks. Reflections from walls and buildings and penetration losses were measured for indoor and outdoor materials, such as tinted glass, clear glass, brick, concrete, and drywall at 28 GHz in New York City. A 400 Mega-chip-per-second sliding correlator channel sounder and 24.5 dBi steerable horn antennas were used to emulate future mobile devices with adaptive antennas that will likely be used in future millimeter wave cellular systems [1]. Measurements in and around buildings show that outdoor building materials are excellent reflectors with the largest measured reflection coefficient of 0.896 for tinted glass as compared to indoor building materials that are less reflective. We also found that penetration loss is dependent not only on the number of obstructions and distance between transmitter and receiver, but also on the surrounding environment. The greatest penetration loss containing three interior walls of an office building was found to be 45.1 dB, with 11.39 m separation between the transmitter and receiver.

As the mobile cellular carriers are currently facing a spectrum crunch, researchers are concentrating on higher carrier frequency bands, such as E-band (71-76 GHz and 81-86 GHz) for the next generation wireless communication systems. The E-band is promising due to its large available, continuous bandwidth and robust weather resilience. In this paper, we demonstrate a spread spectrum sliding correlator channel sounder operating at a center frequency of 73.5 GHz with an 800 MHz null-to-null bandwidth. The channel sounder provides a multipath time resolution of 2.33 ns. 72 GHz millimeter wave propagation and penetration characteristics in an indoor office environment are investigated using the sliding correlator channel sounding system. Data collected and processed from the measurements shows that strong received power can be achieved from the multipath-rich indoor environment, in the presence of multiple obstructions. The data obtained from this measurement campaign may be utilized for the design of future fifth generation millimeter wave indoor cellular systems.

Propagation measurements at 28 GHz were conducted in outdoor urban environments in New York City using four different transmitter locations and 83 receiver locations with distances of up to 500 m. A 400 mega- chip per second channel sounder with steerable 24.5 dBi horn antennas at the transmitter and receiver was used to measure the angular distributions of received multipath power over a wide range of propagation distances and urban settings. Measurements were also made to study the small-scale fading of closely-spaced power delay profiles recorded at half-wavelength (5.35 mm) increments along a small-scale linear track (10 wavelengths, or 107 mm) at two different receiver locations. Our measurements indicate that power levels for small- scale fading do not significantly fluctuate from the mean power level at a fixed angle of arrival. We propose here a new lobe modeling technique that can be used to create a statistical channel model for lobe path loss and shadow fading, and we provide many model statistics as a function of transmitter- receiver separation distance. Our work shows that New York City is a multipath-rich environment when using highly directional steerable horn antennas, and that an average of 2.5 signal lobes exists at any receiver location, where each lobe has an average total angle spread of 40.3° and an RMS angle spread of 7.8°. This work aims to create a 28 GHz statistical spatial channel model for future 5G cellular networks.