MIMO Research Articles

ST-TNet: An spatio-temporal joint transformer network for CSI feedback in FDD-MIMO systems

In recent years, deep learning methods have been shown to have strong potential and superiority in reducing channel state information (CSI) feedback overhead and further improving feedback accuracy to maximize the performance benefits of massive Multiple-Input Multiple-Output (MIMO) in frequency division duplex (FDD) mode. As the CSI matrices are transformed into sequences for input to the Transformer model, the rearrangement leads to the loss of the original physical location relationships. Based on this problem, this paper proposes a transformer decoder based on spatio-temporal joint (ST-T). We employ a spatial attention mechanism to compensate for this information loss and focus on key spatial features more accurately, further exploiting the potential of single- and two-layer transformers in reconstructing CSI matrices. The results are validated by simulations based on DCRNet and CLNet encoders, which show that higher performance can be achieved with lower computational load compared to other lightweight models.

Dual-channel near-field holographic MIMO communications based on programmable digital coding metasurface and electromagnetic theory

Holographic multiple-input multiple-output (MIMO) method leverages spatial diversity to enhance the performance of wireless communications and is expected to be a key technology enabling for high-speed data services in the forthcoming sixth generation (6G) networks. However, the antenna array commonly used in the traditional massive MIMO cannot meet the requirements of low cost, low complexity and high spatial resolution simultaneously, especially in higher frequency bands. Hence it is important to achieve a feasible hardware platform to support theoretical study of the holographic MIMO communications. Here, we propose a near-field holographic MIMO communication architecture based on programmable digital coding metasurface (PDCM) and electromagnetic theory. The orthogonal holographic patterns on the transmitting and receiving apertures are firstly obtained using the Hilbert-Schmidt decomposition of the radiation operator. Then the information to be transmitted is pre-encoded on PDCM following the principle of direct digital modulations. A PDCM-based holographic MIMO prototype is designed and experimentally verified in microwave frequencies. The measured results of constellations show that the prototype can realize dual-channel signal transmissions under quadrature-phase shift keying scheme. The proposed paradigm features low complexity, low cost and low power consumption, and may become a valuable technique in beyond fifth generation and 6G wireless communications.

Optimal tracking performance of communication constrained systems with fading channel and quantization constraint

AbstractThis paper studies the optimal tracking performance (OTP) of multiple‐input multiple‐output (MIMO) discrete communication constrained systems (CCSs) with fading channel and quantization constraints. An equivalent average channel is used to replace the fading channel with colored noise, and the gain of the output ports of the two channels is consistent in the first and second moments. Combined with spectral decomposition, co‐prime decomposition, partial fractional decomposition and other methods, the quantitative explicit expression of OTP is eventually derived. The result shows that the OTP is related to nonminimum phase (NMP) zeros and unstable poles and their directions of controlled plant, and is also affected by quantization error and colored noise. At last, a numerical example is utilized to verify the theory.

Wireless power transfer empowered by reconfigurable intelligent surfaces

ABSTRACT Reconfigurable Intelligent Surfaces (RIS) represent a significant advancement in hardware technology, enhancing both wireless energy and spectral efficiency within wireless communication systems. Comprising a programmable metasurface, RIS can adeptly manipulate the wavefronts of incident signals – encompassing parameters such as phase, amplitude, frequency, and polarisation – without necessitating complex signal processing techniques. The integration of RIS into wireless communication networks enables the strategic manipulation of radio waves, thereby mitigating the adverse effects associated with natural wireless propagation. This study examines a multi-user (MU) multiple-input multiple-output (MIMO) wireless power transfer (WPT) system augmented by multiple RISs, wherein the transmitter is equipped with a constant-envelope beamformer. The optimisation of the phase shifts of the RIS and the beamformer of the transmitter is conducted jointly to maximise the total power received by users. An alternating optimisation approach is proposed, utilising the semidefinite relaxation (SDR) method. Additionally, a problem is formulated to maximise the total received power while adhering to constraints on the minimum power received by users, thereby addressing issues of user fairness. To resolve this problem, an iterative algorithm based on the Alternating Direction Method of Multipliers (ADMM) is introduced. Analysis and simulation results indicate a significant enhancement in total received power when employing the proposed methodology compared to existing algorithms documented in the literature. Furthermore, in scenarios involving multiple users, a detailed analysis of the system’s transmission performance, facilitated by RIS, is conducted. The numerical results substantiate the validity of the analysis and demonstrate the efficacy of the proposed algorithms.

Inexpensive SAR testbed for 3D mmWave imaging applications

AbstractIn this paper, the authors investigate and develop a low‐cost synthetic aperture radar (SAR) testbed and utilise it to capture and reconstruct high‐resolution 3D mmWave SAR images. Despite much attention from both industrial and academic scholars, cost restraints and complexity have hindered the deployment of SAR systems, particularly in the mmWave domain. This paper outlines the major components and systems of the 3D SAR testbed. The authors build a testbed with low‐cost, commercially available hardware components and include open‐source software that is highly reconfigurable and simple to reproduce. The multiple‐input multiple‐output (MIMO) radar sensor uses a frequency‐modulated continuous wave (FMCW) chirp at the V‐band (40–75 GHz) and synthesises a rectilinear two‐dimensional planar aperture. The authors presented several reconstructed 3D images imitating real‐world scenarios using the testbed. A non‐linear sampling technique that has significantly decreased the amount of time required for data acquisition was implemented. In addition, the authors employed multiple image quality metrics to quantify and compare the images produced by the testbed. The testbed can be used to test and validate new techniques and algorithms.

Improvement of Internet of Things (IoT) Interference Based on Pre-Coding Techniques over 5G Networks

The advent of 5G technology has revolutionized wireless communication, offering unprecedented data rates, reduced latency, and enhanced connectivity. A critical component driving these advancements is Multiple-Input Multiple-Output (MIMO) technology. MIMO utilizes multiple antennas at both the transmitter and receiver ends to improve communication performance. In the context of the Internet of Things (IoT), MIMO plays a pivotal role in enhancing network efficiency, reliability, and capacity and can improve system capacity and reduce interference between different users. By leveraging MIMO, IoT devices can achieve higher data throughput and better signal quality, even in challenging environments. This is particularly important for IoT applications that require real-time data transmission and low latency, such as smart cities, autonomous vehicles, and industrial automation. Additionally, MIMO technology helps in mitigating interference and improving spectrum utilization, making it an essential enabler for the massive connectivity demands of IoT networks in the 5G era. However, due to the high channel dimension, complex channel estimation and precoding algorithms in the system, the system hardware and software overhead will increase. The precoding algorithms of massive MIMO systems are divided into three types: digital, analog and hybrid. The three types of precoding algorithms are summarized and compared, and the advantages and disadvantages of different precoding algorithms and applicable scenarios are summarized. The channel estimation schemes are divided into training estimation and blind estimation, and the advantages and disadvantages of the two types of schemes are summarized. It is pointed out that the reasonable use of the channel sparsity of massive MIMO can improve the quality of channel estimation and reduce the estimation overhead.

Height Measurement Method for Meter-Wave Multiple Input Multiple Output Radar Based on Transmitted Signals and Receive Filter Design.

To address the issue of low-elevation target height measurement in the Multiple Input Multiple Output (MIMO) radar, this paper proposes a height measurement method for meter-wave MIMO radar based on transmitted signals and receive filter design, integrating beamforming technology and cognitive processing methods. According to the characteristics of beamforming technology forming nulls at interference locations, we assume that the direct wave and reflected wave act as interference signals and hypothesize a direction for a hypothetical target. Then, the data received are processed to obtain the height of low-elevation-angle targets using a cognitive approach that jointly optimizes the transmitted signal and receive filter. Firstly, a signal model for the meter-wave MIMO radar based on the transmit weight matrix is established under low-elevation scenarios. Secondly, the signal model is analyzed and transformed. Thirdly, the beamforming algorithm that jointly optimizes the transmitted signals and receive filter is derived and analyzed. The algorithm maximizes the output Signal-to-Interference-plus-Noise ratio (SINR) of the receiver by designing the transmit weight matrix and receive filter. The optimization problem based on the SINR criterion is non-convex and difficult to solve. We transformed it into two sub-optimization problems and approximated the optimal solution through an alternating iteration algorithm. Finally, the proposed height measurement algorithm is compared with the Generalized Multiple Signal Classification (GMUSIC) and Maximum Likelihood (ML) height measurement algorithms. Simulation results show that the proposed algorithm can realize the height measurement of low-elevation targets. Compared to the GMUSIC and ML algorithms, it demonstrates superior performance in terms of computational complexity and multi-target elevation estimation.

A Novel Dual-Band Four Port MIMO Antenna Design for 28/38 GHz Millimeter-Wave 5G Applications

This paper introduces a novel dual-band Multiple-Input Multiple-Output (MIMO) antenna specifically crafted for 5G millimeter-wave communication systems. The antenna is designed to operate within the frequency spectrum of 26 to 31 GHz and 34.5 to 40 GHz. Notably, at 28 GHz, the antenna attains an impressive gain of 10.6 dBi, coupled with an efficiency exceeding 70%. Meanwhile, at 38 GHz, the gain remains substantial at 6.65 dBi, with an efficiency of 50%. Simulation results indicate an average isolation of approximately -30 dB between antenna elements. The diversity gain is nearly 10 dB, and the error-correcting code measures less than 1 × 10-6, highlighting superior performance compared to prior antenna designs. These robust dual-band MIMO antenna performance metrics make it a highly promising solution for millimeter-wave 5G applications.

A low-SAR four-element antenna for ISM/NR78 band applications

ABSTRACT This article introduces a novel four-port doughnut-shaped coplanar waveguide (CPW) multiple-input multiple-output (MIMO) antenna designed for dual-band operation. Operating within the 2.4–2.5 GHz and 4.4–5 GHz frequency ranges, the antenna boasts a remarkable 10 dB impedance bandwidth. Fabricated on a 55 mm x 55 mm x 1.6 mm FR4 substrate, this antenna achieves impressive isolation of over 20 dB among its elements through orthogonal placement, thereby enhancing key MIMO parameters such as envelope correlation coefficient (ECC), total active reflection coefficient (TARC), channel capacity loss (CCL), diversity gain (DG), and mutual coupling enhancement gain (MEG). Fabrication and measurement procedures validate the antenna’s performance, demonstrating close alignment with simulation results. This validation confirms the antenna’s suitability for deployment across various domains, including Industrial, Scientific, and Medical (ISM) bands and the n78 band for biomedical and 5 G applications. Additionally, specific absorption rate (SAR) calculations support the antenna’s performance, ensuring compliance with regulatory standards for human exposure to electromagnetic fields.

Optimal Reconfigurable Intelligent Surface Deployment for Secure Communication in Cell-Free Massive Multiple-Input Multiple-Output Systems with Coverage Area

Optimal Reconfigurable Intelligent Surface Deployment for Secure Communication in Cell-Free Massive Multiple-Input Multiple-Output Systems with Coverage Area

Cross-layer latency analysis for 5G NR in V2X communications.

The 5G network was developed to push the capabilities of wireless networks to previously unseen performance limits, e.g., transmission rates of several gigabits per second, latency of less than a millisecond, and millions of devices connected at the same time. To meet these requirements, it is necessary to access new spectrum (the so-called millimeter waves) and use techniques such as Massive MIMO (Multiple-Input Multiple-Output) and beamforming. This required the design of a new radio interface, known as 5G NR, that includes improvements to its physical components and new protocols. The performance of the 5G network will depend heavily on the behavior of these new protocols under certain configuration parameters, traffic conditions, device density, and network architecture. This paper introduces an analytical model for the performance evaluation of 5G NR. The developed model describes the behavior of the different layer 1 and 2 protocols involved in 5G radio communication. Using the model, it is possible to evaluate the performance of 5G NR in terms of throughput and latency, two key performance metrics used to describe QoS (Quality of Service) thresholds of different applications. The protocol layer approach gives the model sufficient granularity to identify critical behaviors that significantly impact performance. This can help focus efforts on improving these key points or propose improvements/modifications to the operation of network protocols or devices. The use of this model for performance evaluation is exemplified by studying a Remote Driving scenario operated over 5G. This scenario has very stringent delay requirements, which, according to the model's results, can be satisfied if the network conditions are adequate. This model and its results can be used as a starting point for performance evaluations of application involving end-to-end (E2E) communications.

A Hybrid Intelligence-based Deep Learning Model with Reptile Search Algorithm for Effective Channel Estimation in massive MIMO Communication Systems

A Hybrid Intelligence-based Deep Learning Model with Reptile Search Algorithm for Effective Channel Estimation in massive MIMO Communication Systems

A Hybrid Intelligence-based Deep Learning Model with Reptile Search Algorithm for Effective Channel Estimation in massive MIMO Communication Systems

A Hybrid Intelligence-based Deep Learning Model with Reptile Search Algorithm for Effective Channel Estimation in massive MIMO Communication Systems

Uplink MIMO Communications with RIS-Integrated Base Station: Modeling and Experiments

Uplink MIMO Communications with RIS-Integrated Base Station: Modeling and Experiments

Comparative analysis of classification techniques and input-output patterns for monthly rainfall prediction

ABSTRACT Rainfall prediction is one of the crucial stages of the watershed management process. In this research, A comparison of the performance among Monte Carlo and Thomas Fiering, linear regression (LR), multiple linear regression (MLR), and SVM optimized by Simulated Annealing (SVM-SA) is carried out for Monthly rainfall prediction. In addition, the efficiency of the input patterns to the models including single input-multiple output (SIMO), multiple input-multiple output (MIMO), single input-single output (SISO), multiple input-single output (MISO) patterns are investigated. For this purpose, the time series of 34 rain gauge stations in the Karkheh basin was used. The results showed that SISO, MISO, MIMO, SIMO, and Monte Carlo and Thomas Fiering models are ranked first to fifth respectively. By comparing the performance of the models, it can be found that there is no significant difference between the SVM-SA, LR, and MLR models, However, the LR model is a method for predicting monthly rainfall more easily than other methods. This method has fewer adjustable parameters than other models.

A Four Element UWB MIMO Antenna with Band - Notched Characteristics for Wireless Communication Applications

Abstract: This study proposes an innovative approach to enhance isolation in a four-element Ultra Wide Band (UWB) range Multiple Input Multiple Output (MIMO) antenna system. The design employs unique rhombic and cross-shaped slot structures to achieve compactness, with dimensions of 34 mm × 34 mm × 1.6 mm. To minimize mutual coupling, the antenna incorporates orthogonally placed feed lines alongside a parasitic strip measuring 17 mm × 1 mm × 1.6 mm. The antenna effectively suppresses interference from specific bands, including WiMAX, WLAN, and X-band, through the integration of L-shaped and Cshaped slits combined with Electromagnetic Band Gap (EBG) elements. Simulation results, verified through practical testing, confirm an operational bandwidth 2 GHz to 12 GHz, excluding the targeted notched bands. The design achieves superior isolation (S11 < -10 dB), a peak gain of 2.5–5 dB, and excellent interference rejection capabilities. These features establish the antenna as a highly efficient option for next-generation UWB-MIMO wireless communication applications.

Angular Circle Array Multiple Input Multiple Output Underwater Optical Wireless Communications

This paper constructs a simulation platform for underwater wireless optical single-input single-output (SISO) communication systems and quantitatively evaluates communication performance indicators. To improve channel capacity, we propose an angular circle array MIMO scheme. The path loss, CIR, and channel capacity of the angular circular array MIMO communication system are calculated by using the Monte Carlo method. Results show that the proposed angular circular array MIMO communication system has a higher channel capacity compared to planar circular array MIMO communication systems and SISO communication systems.

A Hybrid Genetic Algorithm with Tabu Search Using a Layered Process for High-Order QAM in MIMO Detection

In this paper, we propose a hybrid genetic algorithm (HGA) that embeds the tabu search mechanism into the genetic algorithm (GA) for multiple-input multiple-output (MIMO) detection. We modified the selection and crossover operation to maintain the diverse and wide exploration areas, which is an advantage of the GA, and the mutation operation to perform a local search for a specific region. In the mutation process, the ’tabu’ concept is also employed to prevent the repeated search of the same area. In addition, a layered detection process is applied simultaneously with the proposed algorithm, which not only improves the bit error rate performance but also reduces the computational complexity. We apply the layered HGA (LHGA) to the MIMO system with very high modulation order such as 64-quadrature amplitude modulation (QAM), 256-QAM, and 1024-QAM. Simulation results show that the LHGA outperforms conventional detection approaches. Especially, in the 1024-QAM MIMO system, the LHGA has less than 10% of computational complexity but a 6 dB signal-to-noise ratio (SNR) gain compared to the conventional GA-based MIMO detection scheme.

A drive minimization technique for component-level response replication in multi-input multi-output random control tests

Multiple-Input Multiple-Output (MIMO) vibration control tests are used to replicate operational vibration environments via shakers excitation. In MIMO random tests, the control target is a reference Spectral Density Matrix (SDM) comprising of Power Spectral Densities (PSDs) and Cross Spectral Densities (CSDs). In particular, the CSDs profiles play a key role in the outcome of the test, as they can affect both the test article response and the voltage required by the shakers (the so called drives). The original contribution of this paper is a MIMO random target definition method that allows to replicate the response of the component tested while minimizing the energy required to conduct the test. The proposed methodology provides the minimum excitation PSDs that allow to replicate the response at a specific location of the device under test. The aim of the proposed methodology is to define a new reference SDM that allows to deal the same damage to the component as a target vibration environment, but with minimal energy. In fact, the minimization of the excitation PSDs also minimizes the drives required to conduct the test, thus preserving the delicate excitation system. The paper outlines the mathematical implementation of the proposed method and validates it through experimental tests. The experiments are conducted on a specially designed specimen by utilizing a three-axial electro-dynamic shaker.

Experimental Evaluation of MIMO Channel Capacity for Wireless Communication Channels

This research evaluates the channel capacity (CC) of 5th Generation Multiple Input Multiple Output (MIMO) antennas for propagation channels used in wireless communication. In the presence of several frequency sources for the information and communication channels, the effect on the CC of one-port and multi-port antennas is observed using the Path Loss Model (PLM), which is significantly impacted due to the number of antennas used and their characteristics. The CC is also estimated using a different approach, Kronecker's Model (KM). The channel matrix using both models is estimated by maintaining 5 cm and 25 cm spacing between the transmitting and receiving antennas. At 2.4 GHz for a 1-port antenna-based channel, the CC calculated using PLM is 5.5 bps/Hz for both spacing, whereas the CC calculated using KM is 3.65 bps/Hz and 3.12 bps/Hz for 5 cm and 25 cm spacing, respectively. The CC in the PLM is found between 35 to 140 bps/Hz at a frequency of 3.5 GHz, whereas it is reported between 12 to 38 bps/Hz using the KM at the same frequency, irrespective of distances. The maximum CC calculated using PLM is 5 bps/Hz for a 1-port antenna-based channel, 34 bps/Hz for 2-port MIMO antenna-based channels, 80 bps/Hz for 4-port MIMO antenna-based channels, and 157 bps/Hz for 8-port MIMO antenna based channels in the frequency band from 3.45 GHz to 3.7 GHz. Thus, it is experimentally confirmed that the capacity enriched by approximately 4 times on increasing the number of antenna ports from 2 to 8 and operating frequency.