Multiuser Systems Research Articles

The Orthogonal Time Frequency Space (OTFS) Technique In 6G Wireless Communications

The orthogonal time-frequency space (OTFS) technique is a potential waveform modulation method that modulates data in the delaydoppler (DD) domain. OTFS differs from traditional multiplexing techniques by utilizing two-dimensional modulation to switch between the time-frequency (TF) domain and the delay-Doppler domain. This allows for handling Doppler shifts caused by fast-moving objects, a capability lacking in traditional modulation techniques like orthogonal frequency division multiplexing (OFDM). The primary goal of this paper is to offer an overview and short survey of this new topic, highlighting its system model. We also examine key aspects of OTFS modulation such as data detection methods, channel estimation, MIMO, and multiuser systems.

Channel Estimation Considerate Precoder Design for Multi-user Massive MIMO-OFDM Systems: The Concept and Fast Algorithms

Channel Estimation Considerate Precoder Design for Multi-user Massive MIMO-OFDM Systems: The Concept and Fast Algorithms

Hybrid Precoding Design in Multi-User mmWave Massive MIMO Systems for BER Minimization

Hybrid Precoding Design in Multi-User mmWave Massive MIMO Systems for BER Minimization

MultiResp: Robust Respiration Monitoring for Multiple Users using Acoustic Signal

In recent years, we have seen efforts made to monitor respiration for multiple users. Existing approaches capture chest movement relying on signals directly reflected from chest or separate breath waves based on breath rate difference between subjects. However, several limitations exist: 1) they may fail when subjects face away from the transceiver or are blocked by obstacles or other subjects; 2) they may fail to separate subjects' breath waves with the same or similar rates (i.e., breath rate difference < 1 bpm); 3) they assume a priori knowledge of number of subjects and cannot adapt to dynamic change of subject number during monitoring. To overcome these limitations, in this paper we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MultiResp</i> , a multi-user respiration monitoring system using acoustic signal. By fully leveraging the abundant acoustic signals reflected indirectly from subjects' chest, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MultiResp</i> can robustly capture chest movement even when they face away from the transceiver or are blocked. By extracting fine-grained breath rate and phase difference between different subjects, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MultiResp</i> can separate the breath waves with the same or similar rates and adapt to dynamic change of subject number during monitoring. Extensive experiments show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MultiResp</i> is able to accurately monitor the respiration of multiple users with a median error of 0.3 bpm in various indoor scenarios, however, it fails when the sound pressure is lower than 55 dB or body movement is happening.

Location-driven beamforming for massive multi-user MIMO systems

Location-driven beamforming for massive multi-user MIMO systems

Iterative Channel Estimation for Multi-User OTFS Uplink Systems With Superimposed Full Pilots

Iterative Channel Estimation for Multi-User OTFS Uplink Systems With Superimposed Full Pilots

Learning End-to-End Hybrid Precoding for Multi-User mmWave Mobile System With GNNs

Learning End-to-End Hybrid Precoding for Multi-User mmWave Mobile System With GNNs

User-Specific Channel Estimation Overhead Optimization and Resource Allocation for Multi-User OTFS Systems

User-Specific Channel Estimation Overhead Optimization and Resource Allocation for Multi-User OTFS Systems

Development of fishery information system for production processes organization

The article substantiates the relevance of developing a software product that carries out the digitalization of the country’s fisheries management processes. The use of general scientific methods of structural analysis, synthesis, and formalization allowed us to develop a formal model of the subject area. Such a model became the basis for using object-oriented programming methods to obtain a full-fledged multi-user information system. Graphic images of screens of mobile and web-oriented versions of the system with a description of the functionality of user categories are presented. The developed information system allows to systematize and unify fishery processes, provide state control of the industry, and attract monetary investments into the industry.

Channel Estimation for Tethered Aerial Platform Enabled Multi-User Communication Systems

Channel Estimation for Tethered Aerial Platform Enabled Multi-User Communication Systems

A Two-Layer Iterative Algorithm for Max-Min Rate Optimization in IRS Assisted Multiuser Systems With Improper Gaussian Signaling

A Two-Layer Iterative Algorithm for Max-Min Rate Optimization in IRS Assisted Multiuser Systems With Improper Gaussian Signaling

Iterative Detection and Decoding for Multiuser Systems Based on MMSE Refinements With Active or Passive RIS

Iterative Detection and Decoding for Multiuser Systems Based on MMSE Refinements With Active or Passive RIS

Optimizing Multi-UAV Multi-User System Through Integrated Sensing and Communication for Age of Information (AoI) Analysis

Optimizing Multi-UAV Multi-User System Through Integrated Sensing and Communication for Age of Information (AoI) Analysis

Fog Computing for Control of Cyber-Physical Systems in Industry Using BCI.

Brain-computer interfaces use signals from the brain, such as EEG, to determine brain states, which in turn can be used to issue commands, for example, to control industrial machinery. While Cloud computing can aid in the creation and operation of industrial multi-user BCI systems, the vast amount of data generated from EEG signals can lead to slow response time and bandwidth problems. Fog computing reduces latency in high-demand computation networks. Hence, this paper introduces a fog computing solution for BCI processing. The solution consists in using fog nodes that incorporate machine learning algorithms to convert EEG signals into commands to control a cyber-physical system. The machine learning module uses a deep learning encoder to generate feature images from EEG signals that are subsequently classified into commands by a random forest. The classification scheme is compared using various classifiers, being the random forest the one that obtained the best performance. Additionally, a comparison was made between the fog computing approach and using only cloud computing through the use of a fog computing simulator. The results indicate that the fog computing method resulted in less latency compared to the solely cloud computing approach.

Multi-User Tracking in Reconfigurable Intelligent Surface Aided Near-Field Wireless Communications System

An uplink multi-user tracking problem aided by multiple passive reconfigurable intelligent surfaces (RISs) is addressed in this work. Under a near-field circumstance, a multi-antenna base station (BS) localizes multiple moving single-antenna users by processing the received signals transmitted by users and reflected by RISs. Considering the users’ mobility and the potential obstruction of line-of-sight paths, a multi-user tracking system based on the extended Kalman filter (EKF) which fully exploits the temporal correlations between each user’s coordinate changes is designed. Then, the Bayesian Cramér–Rao bound (BCRB) of tracking errors is derived in a pattern consistent with the EKF process. Subsequently, an optimization scheme for passive phase shift design at the RISs is devised by minimizing the derived BCRB and is solved using the Gradient Descent method. Numerical results indicate that the accuracy of our tracking algorithm can approach the BCRB. With abundant RISs deployed and optimized, high-precision multi-user tracking via a single BS can be realized even in harsh localization environments.

Performance analysis of IRS-aided multi-user millimeter wave communications system

Performance analysis of IRS-aided multi-user millimeter wave communications system

Multiuser downlink communication for MIMO-VLC system using spatial modulation and optical orthogonal codes

In this paper, a novel multiuser spatial modulation (SM) scheme is proposed and applied in downlink multiple input-multiple output (MIMO) visible light communication (VLC) system. In the transmitter side, each user's temporal symbol is first modulated onto user specific optical orthogonal code (OOC), then being emitted by the specific LED that is activated by its spatial symbol. At the front end of each user terminal (UT), array of photodetectors (PDs) convert optical into electrical signal, then chip-level detection scheme is employed to eliminate multiuser interference (MUI). Two computationally attractive detection algorithms are then proposed: Maximum likelihood (ML) algorithm premises on jointly estimating both temporal and spatial symbols. While the two-stages algorithm first identifies the index of the activated LED followed by a M-ary PAM demodulator to extract the desired user's spatial and temporal symbols sequentially. Extensive Monte Carlo simulations are undertaken to evaluate system performance in terms of the overall symbol error rate (SER). It is demonstrated that the chip-level detection scheme can effectively alleviate MUI and both ML and the two-stages detection algorithms work reliably in various scenarios. Hence, it is promising to apply the proposed scheme in multiuser MIMO-VLC system.

Clustering Approach for Reliable Wireless Communication

Multiple access techniques for 5G systems are based on principles related to security, efficiency, and performance increase. Multi-user shared access (MUSA) is included in code-domain non-orthogonal multiple access (CD-NOMA) techniques with multiple benefits including multiple-access interference minimization and system capacity increase. The additional benefits of MUSA include its grant-free nature, which makes it applicable to scenarios involving random access channels, minimal latency communications, etc. Depending on the high-frequency diversity of the fading-affected channels, this technique is also used to lessen their effects. This paper illustrates the concept of code correlation used in MUSA by proposing a method to allocate MUSA codes to active users in an uplink data transmission system based on clusters. This clustering approach (grouping of 3GPP TR 38.812 spreading codewords) enables performance improvement in different system configurations by implementing various scenarios and providing reliable results. It is demonstrated that four-length spreading code selection from 3GPP family codes is a satisfactory solution, and this cluster grouping can be designed in a less overloaded multi-user system. The challenges, advantages, and limitations of the proposed method are outlined throughout the study.

Numerical Evaluation of the MU-MIMO Beamforming Performance with Channel Estimation

This paper presents the numerical evaluation of the ZF beamforming algorithm and DFT precoding using the LS channel estimation in the multiuser multiantenna (MU-MIMO) downlink system. The sum rate performance depending on a number of users are presented. The arising inter user correlation degrades the sum rate (spectral efficiency) performance of multiuser MIMO system especially in scenarios where the number of users is larger than the number of antennas at the BS. For MIMO channel simulation the QuaDRiGa channel model reflecting the real propagation conditions is used. The obtained performance of MU-MIMO ZF precoding in spatially correlated channel are compared with DFT precoding based on the empirical cumulative density function of the sum rate of multiple users. Numerical results show that the ZF precoder outperforms the DFT precoder in channel with less spatial correlation. The DFT precoder in spatially more correlated channel has advantage over ZF precoder.

Multi-user communications for line-of-sight large intelligent surface systems

In this paper, we propose a new interference-suppression beamformer design and a Direction-of-Arrival (DoA) estimation method for Line-of-Sight (LoS) multi-user communication systems with circular Large Intelligent Surfaces (LISs). This symmetrical circular-shaped LIS allows signals defined on it to be formed by combining Fourier and Bessel series. The Fourier harmonics are orthogonal along the rotational direction and the Bessel functions constituting the Bessel series are orthogonal along the radial direction. Synthesizing basis functions from these two series results in the proposed interference-suppression beamformer, with their coefficients designed to cancel inter-user interference. Also by exploiting signal structure of a circular LIS communicating with Mobile Stations (MSs), we devise a DoA estimation method to obtain directional information of incoming signals. Under LoS channel, the DoA corresponds to elevation and Azimuth angles of MSs relative to the LIS. This method is numerically demonstrated to have promising performance with high-frequency carriers.