Downlink Outage Probability and Channel Capacity for Cell-Free Massive MIMO Systems

LR-FHSS: Analytical Model of Channel Capacity and Header Redundancy Optimization

Abstract A triple-band, planar, miniaturized two-port MIMO antenna with circular polarization (CP), low channel capacity loss (CCL), high isolation, and diversity is implemented. The proposed antenna provides circular polarization at all its three operating bands i.e. 1.8 GHz, 3.5 GHz and 5.2 GHz. The tedious task of having circularly polarized operating band within L-band is achieved through a simple design. To minimize signal interference while maintaining the miniaturization, an isolator is integrated on its ground plane. The fabrication of antenna is implemented on Rogers RO530 substrate of physical dimensions 20×28×0.762mm3(0.12λ0 × 0.16λ0× 0.004λ0). The mechanism of the generation of each operating band is explained and demonstrated in detail. The antenna provides CP with an axial ratio bandwidth (1.67GHz-1.85GHz) at 1.8GHz, (3.17-3.67) at 3.5GHz and (4.65-5.85) at 5.2GHz. The proposed antenna covers -10dB impedance bandwidth of 140MHz (1.71GHz-1.85GHz), 480MHz (3.29GHz-3.77GHz), and 940MHz (5.0GHz-5.94GHz) with high isolation of more than -18dB within the operating bands. The measured fractional bandwidth of 7.8%, 13.5% and 16.9% with a peak gain of 0.78 dBi, 1.5 dBi and 3.4 dBi is attained at 1.8 GHz, 3.5 GHz and 5.2 GHz bands respectively. Radiation plots obtained from simulations and measurements demonstrate the effectiveness of the design in achieving polarization diversity and distinct directional characteristics confirms its pattern diversity. The analysis of diversity parameters supports the MIMO capabilities evaluation of the designed antenna. All the measured results confirm the accuracy of the simulation outcomes.

This work explores solutions for addressing challenges in visible light communication (VLC) within 5G networks, particularly for indoor environments and green Internet of Things (IoT) applications, while considering the evolving demands of 6G networks. These demands include higher spectral efficiency (SE), enhanced data rates, reduced complexity, and reliable quality of service (QoS) for users with varying mobility. The proposed solution integrates optical reconfigurable intelligent surfaces (ORIS)-aided multiple-input multiple-output (MIMO) technology with a novel non-orthogonal multiple access (NOMA) transmission system employing discrete Fourier transform spread orthogonal time-frequency space (DFT-s-OTFS) modulation. This framework enhances spatial diversity, optimizes bandwidth, minimizes Peak-to-Average Power Ratio (PAPR), and improves power allocation. By leveraging OTFS modulation, the system supports delay-Doppler (DD) channels and ensures better control over VLC-IoT environments with physical layer security (PLS). A VLC channel model incorporating MIMO technologies for ORIS-aided NOMA-OTFS systems is developed, addressing a capacity maximization problem that considers transceiver parameters, RIS reflections, transmit power, and DD channels. An optimal solution is achieved using a relaxation algorithm. Numerical results show that the proposed ORIS-aided DFT-s-OTFS-based NOMA-MIMO VLC system outperforms the ORIS-assisted OFDM regarding bit error rate (BER), significantly improving channel capacity, SE, and security rates. These findings provide valuable insights for advancing optical RIS-assisted MIMO-VLC technologies.

Orbital angular momentum (OAM) multiplexing holography has emerged as a pivotal technology for high-capacity optical communication, encryption and display, but it requires multiple inputs for decoding and its security remain constrained due to the rotational symmetry of topological charge (TC) distribution in conventional OAM modes. Here, we introduce a general paradigm of OAM multiplexing holography that enables multi-channel holographic encoding using a single incident light. Our methodology leverages a discontinuous OAM with a spatially varying TC across the azimuth, which breaks the rotational symmetry and imposes angular selectivity for information retrieval. Notably, by rationally designing the TC distribution, the discontinuous OAM exhibits self-orthogonality at different rotation angles, laying the foundation for multiplexed holography. A modified weighted Gerchberg-Saxton algorithm is developed to calculate the holographic phase profile, which can then be encoded onto a pure geometry-phase metasurface. By further integrating different pairs of discontinuous OAMs, we successfully expand the channel capacity for holographic multiplexing, significantly advancing high-security and high-capacity optical information encryption. Our work establishes discontinuous OAM as a versatile platform for secure optical communications, high-density data storage, and dynamic holographic displays, bridging the gap between structured light manipulation and cryptographic robustness.

Abstract High-dimensional quantum systems greatly outperform their two-dimensional counterparts in channel capacity, quantum complexity and efficiency, quantum communication security, etc. Bell-state analyzer (BSA) is a crucial prerequisite for a number of quantum communication protocols. We propose an approach for completely and deterministically distinguishing a set of arbitrary d-dimensional (d ≥ 3) Bell states via indefinite causal order (ICO). In previous schemes, bit and phase information are discriminated in succession. Exploiting the gravitational ICO as the sole resource, we propose some high-dimensional BSA schemes. Independent of the dimensions, a set of generalized Bell states are completely and deterministically discriminated by adjusting the form of the embedded local single-qudit gates within ICO switch and measuring each qudits in the {|0⟩, |1⟩, • • • , |d -1⟩} basis. Notably, in our high-dimensional BSA process, the indefinite causal structure is not consumed. Hence a completely nondestructive high-dimensional BSA can be achieved by iterating the indefinite causal structure process for two rounds.

Exact quantum capacity of decohering channels in arbitrary dimensions

Urban waterlogging, especially post-monsoon, exacerbates environmental, economic and public health problems in rapidly urbanizing areas. This study employed UAV-based orthophotography and bathymetric data to examine waterlogging risks along the Ghazipur Drain in Delhi, India. High-resolution Digital Elevation Models (DEMs) with a 5 cm ground sampling distance and bathymetric profiles revealed considerable drainage losses and sedimentation that reduced channel capacity by 25%. This key finding quantifies the extent of hydraulic degradation and is vital for informing infrastructural needs. A map from the study highlights approximately 1,120 settlements in the low-lying areas, including Kalyan Puri, Jafrabad, Seelampur, and Karawal Nagar, at the highest flood risk during the monsoon months due to poor drainage and a high degree of urbanization. This highlights the scale of precarious urban living and the demand for action. When combined with bathymetry, UAV data are highly beneficial for acquiring the path, elevation, and bottom features of these outflows, revealing issues such as sedimentation and obstacles. Orthophotos (pixel resolution = 0.05 m) provide detailed urban infrastructure visualizations, including drainage systems, to enable site-specific interventions, such as dredging and channel widening. These high-resolution datasets provide a strong evidence base for operational planning and resource allocation. This method emphasizes the social and economic implications of waterlogging, such as property damage, transport disruption, and growing health hazards from waterborne diseases, which profoundly impact low- to middle-income communities. As described in this study, the influence of UAV-bathymetry in urban drainage research can be considerable. This has accurately integrated data from UAVs in flood risk management activities and led to urban systems planning with a higher resilience level. This will translate into actionable insights to improve drainage infrastructure, reduce flood hazards, and increase urban resilience, which is useful information for planners and policymakers. This result confirms that UAV-bathymetry is a scalable, precise, and low-cost solution for urban waterlogging in fast-developing cities worldwide.

Hybrid signal processing is frequently used in millimeter wave (mmWave) massive Multiple-Input Multiple-Output (MIMO) systems to reduce costly hardware and training overheads. However, in wideband systems with frequency-selective channels, fully digital beamforming at mmWave frequencies poses difficulties for channel estimation. This paper proposes a novel Revolutionizing Channel Estimation and Beamforming technique in Multi-Carrier mm-Wave MIMO through Large-Kernel Attention Graph Convolutional Networks (RCE-mmW-LKAGCN) to address these challenges. Then, two advanced channel estimation algorithms based on Large Kernel Attention Graph Convolutional Networks (LKAGCN) and compressive sensing (CS) are employed. The LKAGCN-CS estimates channel supports in the frequency domain for accurate channel reconstruction, while CS utilizes a multi-resolution fine-tuning technique to further enhance the performance. Simulation outcomes show that the proposed algorithm achieves better accuracy, reducing the Cramer Rao Lower Bound (CRLB) gap to 1-1.5 dB, significantly outperforming traditional techniques like Orthogonal Matching Pursuit (OMP) regarding normalized mean-squared error, signal-to-noise ratio, and channel capacity. Analyzed with existing DL-depend techniques, RCE-mmW-LKAGCN reduces complexity by two orders of magnitude with improves SNR.

Abstract This paper has clarified the simulation performance study of ultra-wide dense wavelength division multiplexing and ultra-high channel capacity based outdoor free space/optical wireless system applications in heavy atmospheric channel condition. We have demonstrated that the OWC channel can be reached to 20 km transmission distance with suitable signal to noise ratio while FSO channel can be reached to 250 m with minimum bit error rate through the use of BPSK modulation scheme. This work attempts to study the performance of UW-DWDM optical wireless communication (OWC) and free-space optical (FSO) channels under fog conditions using BPSK and NRZ-OOK modulation. The dense fog density level has bad effects on the performance of both OWC and FSO communication channels. The FSO/OWC communication channels performance is studied under light/thick/dense fog density levels. Non-return to zero (on–off keying (NRZ-OOK) and binary phase shift keying (BPSK) modulation schemes are applied through the FSO/OWC communication channel. Ultra-wide dense wavelength division multiplexing channels are employed to study the channel data rate capacity.

Cancer can result from abnormal regulation of cells by their environment, potentially because cancer cells may misperceive environmental cues. However, the magnitude to which the oncogenic state alters cellular information processing has not been quantified. Here, we apply pseudorandom pulsatile optogenetic stimulation, live-cell imaging, and information theory to compare the information capacity of receptor tyrosine kinase (RTK) signaling pathways in EML4-ALK-driven lung cancer (STE-1) and in non-transformed (BEAS-2B) cells. The average information rate through RTK/ERK signaling in STE-1 cells was less than 0.5 bit/hour, compared to 7 bit/hour in BEAS-2B cells, but increased to 3 bit/hour after oncogene inhibition. Information was transmitted by 50–70% of cells, whose channel capacity (maximum information rate) was estimated through in silico protocol optimization. In BEAS-2B cells, channel capacity of the parallel RTK/calcineurin pathway surpassed that of the RTK/ERK pathway. This study highlights information capacity as a sensitive metric for identifying disease-associated dysfunction and evaluating the effects of targeted interventions.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-23075-y.

Leveraging magic resources for quantum channel capacity enhancement under stabilizer convolution

On the Channel Capacity of Communications With Low-Resolution ADCs Over Fading Channels

This paper investigates an integrated sensing and communication (ISAC) system operating in a rainfall scenario, where a base station (BS) simultaneously serves multiple communication users and performs rainfall detection. Specifically, considering the fading characteristics of the millimeter-wave (mmWave) channel and the impact of rainfall on the signal propagation link, we adopt the Weibull distribution as the channel model between the nodes. Based on the above, the received signal-to-noise ratio (SNR), channel capacity, bit error rate (BER), and outage probability of the users within the system are analyzed to characterize the communication performance. Furthermore, the sensing capability of the BS is demonstrated through the analysis of the probability of rainfall. Simulation results reveal that increasing the distance between the BS and users significantly degrades their communication performance. Furthermore, the performance is highly sensitive to the rainfall intensity. Specifically, compared to storm conditions, light rain yields an improvement of 16.9 dB in the average user SNR, a 7.2 bps/Hz increase in channel capacity, and a 40.2% reduction in the outage probability. Additionally, an increase in the complex dielectric constant of raindrops substantially reduces the backscattering coefficient at the ISAC BS.

Dili, the capital city of Timor-Leste, is increasingly vulnerable to flooding due to its geomorphological characteristics and rapid urban expansion. The Comoro River, the largest of several rivers traversing the city, has experienced multiple significant flood events in recent years—most notably in March 2020, April 2021, and February 2022 resulting in severe damage to infrastructure and disruption to local communities. Urban development has led to watershed degradation, sediment accumulation, reduced channel capacity, and embankment overtopping, exacerbating flood risks in densely populated areas. This study aims to assess flood risk and evaluate embankment resilience using an integrated modeling approach. Design flood discharge was estimated using the Log Pearson Type III distribution and the Nakayasu synthetic unit hydrograph, with validation through Chi-Square and Kolmogorov-Smirnov goodness-of-fit tests. Hydraulic simulations were conducted using HEC-RAS 6.1.0, while flood inundation mapping was performed with ArcGIS 10.3 to identify critical flood-prone zones and guide mitigation strategies. Results indicate a peak discharge of 192.141 m³/s for a 25-year return period flood. Mitigation measures proposed include embankment construction and river normalization at vulnerable cross-sections. HEC-RAS simulations demonstrate that these interventions significantly reduce flood inundation. The embankment slope stability factor was calculated at 14.25, indicating a high level of structural safety. The estimated cost for implementing these flood control measures is USD 571,366.87. This study provides a replicable framework for flood hazard modeling and infrastructure planning in urban river systems, contributing to climate-resilient development and evidence-based decision-making in Southeast Asian contexts.

ABSTRACT Statistical distributions are frequently used to model fading effects introduced by the communication channel on the received signal. Some distributions are directly derived from physical propagation models, while others are adapted from statistics and applied to model fading based on their goodness‐of‐fit to measurements or on account of their mathematical simplicity. In this paper, a line‐of‐sight (LOS) shadowed /gamma‐Rayleigh (/GR) is proposed and thoroughly investigated. The GR distribution was selected for its mathematical simplicity and flexibility. Closed‐form expressions for fundamental statistics such as the probability density function (PDF) and cumulative distribution function (CDF) are derived for the /GR fading model. Additionally, analytical expressions for higher‐order moments, including the amount of fading (AF) and the moment generating function (MGF), are provided in closed‐form expressions. Performance measures of interest, such as outage probability (OP), average symbol error probability (ASEP), and average channel capacity, are derived in closed‐form for communication systems operating under the /GR channel fading conditions. The validity and utility of the proposed composite fading model for characterizing composite fading behavior observed in hybrid powerline‐wireless communication (PLC‐WLC) channels are demonstrated through an extensive series of theoretical comparisons with experimental PLC‐WLC measurements. Hybrid PLC‐WLC channel measurements were performed in various environments, and PLC‐WLC propagation scenarios were classified according to the cable branching characteristics of the PLC segment of the hybrid PLC‐WLC channel. The goodness‐of‐fit of the proposed composite fading model was evaluated using the Kullback‐Leibler (KL) divergence test. The results revealed that the proposed composite fading model exhibited an excellent fit to the fading conditions encountered in hybrid PLC‐WLC channels. Compared with other existing composite fading models, the /GR model provided the most accurate fitting results for measurements in large indoor environments, for which the propagation conditions present strong LOS signal components and weak scattered signal components. Furthermore, it was concluded on the basis of the obtained results that increased branching and terminations in the PLC channel of a PLC‐WLC propagation environment lead to increased shadowing and multipath fading effects on the received signal and, consequently, to increased composite fading.

IntroductionIn this work, we introduce a novel approach to one of the historically fundamental questions in neural networks: how to encode information? More particularly, we look at temporal coding in spiking networks, where the timing of a spike as opposed to the frequency, determines the information content. In contrast to previous temporal-coding schemes, which rely on the statistical properties of populations of neurons and connections, we employ a novel synaptic plasticity mechanism that allows the timing to be learnt at the single-synapse level.MethodsUsing a formal basis from information theory, we show how a phase-coded spike train (relative to some ‘reference’ phase) can, in fact, multiplex multiple different information signals onto the same spike train, significantly improving overall information capacity. We furthermore derive limits on the channel capacity in the phase-coded spiking case, and show that the learning rule also has a continuous derivative in the input-output relation, making it potentially amenable to classical learning rules from artificial neural networks such as backpropagation.ResultsUsing a simple demonstration network, we show the multiplexing of different signals onto the same connection, and demonstrate that different synapses indeed can adapt using this learning rule, to specialise to different interspike intervals (i.e., phase relationships). The overall approach allows for denser encoding, and thus energy efficiency, in neural networks for complex tasks, allowing smaller and more compact networks to achieve combinations of tasks which traditionally would have required high-dimensional embeddings.DiscussionAlthough carried out as a study in computational spiking neural networks, the results may have insights for functional neuroscience, and suggest links to mechanisms that have been shown from neuroscientific studies to support temporal coding. To the best of our knowledge, this is the first study to solve one of the outstanding problems in spiking neural networks: to demonstrate that distinct temporal codings can be distinguished through synaptic learning.

Abstract To expand the vortex beam manipulation dimensions and improve orbital angular momentum (OAM) holographic encryption security, a novel vortex structured light field featuring space‐variant polarization is presented. The space‐variant polarization beam unite the modulation of the phase, amplitude, and polarization of vortex beams. While enabling arbitrary amplitude modulation and beam shaping for vortex light fields, it also achieves arbitrary customization of the local polarization states within the vortex beam. More importantly, leveraging the multi‐dimensional cooperative control characteristics of structured light fields, an OAM holographic encryption system with polarization‐switching capabilities is developed. By dynamically switching the polarization states of space‐variant polarized structured light, the polarization channels of the holographic encryption system can be altered, ultimately enabling controllable reconstruction of image information. Experimental results demonstrate that this work extends the traditional vortex light field control dimensions to triple physical dimension (amplitude, polarization, and topological phase) and also establishes a polarized OAM multiplexing encryption channel. The system supports dynamic polarization reconstruction of images, significantly enhancing security and channel capacity.

Abstract Today, machine learning has a crucial role in wireless communications, notably in 5G and 6G. It contributes significantly for increasing network capacity, improving user experience, and enhancing network reliability. Among machine learning techniques, reinforcement learning is vital due to its suitability for many real-world scenarios. It enables agents to learn from the environment with zero-knowledge and make rational decisions. Thus, in this article, we aim to explore the role of classical reinforcement learning in predicting optimal beam angles within urban environments. The goal is to minimize interference between antennas by finding optimal beamforming angles using ray tracing techniques. We examine various classic reinforcement learning methods in an urban scenario, focusing on maximizing total channel capacity. Initially, we identify the optimal beamforming angles for maximizing channel capacity with four antennas. After validating the learning methods and achieving over 99% accuracy, we proceeded to utilize them in a larger scenario. In the first phase, these methods and their accuracy are validated based on the results of the exhaustive search for a small number of nodes. In the second phase, we predict optimal antenna beam angles for scenarios with an increased number of transmitters and receivers for a realistic urban environment situated in the north-eastern part of Berlin.

This study describes a high-gain, ultra-wideband quad-port THz MIMO antenna designed for 6G, TWPAN, and next-generation wireless communications. The design uses fractal radiating elements, graphene-based tunability, and a defective ground structure (DGS) to improve bandwidth, isolation, and impedance matching. The antenna’s tiny polyimide substrate (130 × 130 μm²) enables an ultra-wide bandwidth of 62 THz, a peak gain of 15.24 dB, and port-to-port isolation of 43 dB, resulting in strong MIMO performance. Integrating metasurface structures and graphene tuning allows for dynamic frequency reconfiguration, making it suitable for a wide range of wireless applications. The performance study reveals good spatial diversity and low signal distortion, with an envelope correlation coefficient (ECC) of less than 0.05 and a Diversity Gain (DG) of nearly 10 dB. Additionally, the Total Active Reflection Coefficient (TARC) and Channel Capacity Loss (CCL) are kept to a minimum, maximising spectral efficiency. UV photolithography and electron beam evaporation (EBE) are employed to fabricate the antenna, yielding high precision and minimal losses. Compared to existing designs, it outperforms them in terms of gain, isolation, and multi-band operation. The suggested THz MIMO antenna’s scalability, compact form factor, and customisable properties make it an attractive choice for future 6G wireless networks, sub-THz IoT systems, and ultra-fast personal area networks (PANs). Future research will focus on adaptive beamforming, real-world prototypes, and experimental validation to improve its application in next-generation THz communication systems.