Multiple-input Multiple-output Wireless Research Articles

Latency and Residual Energy Analysis of MIMO Heterogeneous Wireless Sensor Networks

Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized application of MIMO technology within WSNs. This approach operates effectively, especially in challenging and resource-constrained environments. By facilitating collaboration among sensor nodes, Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments. Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring, industrial automation, and healthcare applications. This research paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO using Network Simulator NS2.35 for analysis of End to End Delay for packet transmission and Residual energy of nodes. The research work shows application of MIMO in Wireless Sensor Networks with considerable improvements in Quality of Service parameters which is achieved through Spatial Multiplexing and Diversity Gain. MIMO enables multiple spatial streams, allowing several data streams to be transmitted simultaneously on the same channel. This increases the overall throughput as multiple sensors can transmit their data concurrently without interference. MIMO systems also provide diversity gain by transmitting multiple copies of the same data over different antennas which helps in mitigating the effects of fading and interference, resulting in a more reliable and higher-throughput communication link as compared to a SISO channel. Another advantage of employing MIMO in WSN is reduction in End-to-End delays in data transmission. Last but not the least, MIMO can be configured to optimize the power consumption of individual sensors by adjusting the number of antennas used and transmission power levels based on channel conditions. Hence, MIMO can help to extend the network's lifetime by conserving energy in resource-constrained sensor nodes by preservation of Residual Energy.

A Hybrid of Encryption and Error Correction Method for Multiple-Input Multiple-Output Wireless Communication Systems

A Hybrid of Encryption and Error Correction Method for Multiple-Input Multiple-Output Wireless Communication Systems

Optimal Resource Management for Hierarchical Federated Learning Over HetNets With Wireless Energy Transfer

Remote monitoring systems analyze the environment dynamics in different smart industrial applications, such as occupational health and safety, and environmental monitoring. Specifically, in industrial Internet of Things (IoT) systems, the huge number of devices and the expected performance put pressure on resources, such as computational, network, and device energy. Distributed training of Machine and Deep Learning (ML/DL) models for intelligent industrial IoT applications is very challenging for resource limited devices over heterogeneous wireless networks (HetNets). Hierarchical Federated Learning (HFL) performs training at multiple layers offloading the tasks to nearby Multi-Access Edge Computing (MEC) units. In this paper, we propose a novel energy-efficient HFL framework enabled by Wireless Energy Transfer (WET) and designed for heterogeneous networks with massive Multiple-Input Multiple-Output (MIMO) wireless backhaul. Our energy-efficiency approach is formulated as a Mixed-Integer Non-Linear Programming (MINLP) problem, where we optimize the HFL device association and manage the wireless transmitted energy. However due to its high complexity, we design a Heuristic Resource Management Algorithm, namely H2RMA, that respects energy, channel quality, and accuracy constraints, while presenting a low computational complexity. We also improve the energy consumption of the network using an efficient device scheduling scheme. Finally, we investigate device mobility and its impact on the HFL performance. Our extensive experiments confirm the high performance of the proposed resource management approach in HFL over HetNets, in terms of training loss and grid energy costs.

Robust Linear Decentralized Tracking of a Time-Varying Sparse Parameter Relying on Imperfect CSI

Robust linear decentralized tracking of a time varying sparse parameter is studied in a multiple-input multiple-output (MIMO) wireless sensor network (WSN) under channel state information (CSI) uncertainty. Initially, assuming perfect CSI availability, a novel sparse Bayesian learning-based Kalman filtering (SBL-KF) framework is developed in order to track the time varying sparse parameter. Subsequently, an optimization problem is formulated to minimize the mean square error (MSE) in each time slot, followed by the design of a fast block coordinate descent (FBCD)-based iterative algorithm. A unique aspect of the proposed technique is that it requires only a single iteration per time slot to obtain the transmit precoder (TPC) matrices for all the sensor nodes (SNs) and the receiver combiner (RC) matrix for the fusion center (FC) in an online fashion. The recursive Bayesian Cramer Rao bound (BCRB) is also derived for benchmarking the performance of the proposed linear decentralized estimation (LDE) scheme. Furthermore, for considering a practical scenario having CSI uncertainty, a robust SBL-KF (RSBL-KF) is derived for tracking the unknown parameter vector of interest followed by the conception of a robust transceiver design. Our simulation results show that the schemes designed outperform both the traditional sparsity-agnostic KF and the state-of-the-art sparse reconstruction methods. Furthermore, as compared to the uncertainty-agnostic design, the robust transceiver architecture conceived is shown to provide improved estimation performance, making it eminently suitable for practical applications.

Pattern Shaping by Utilizing EBG Phase Response and Its Use in MIMO Radio Altimeter Antenna Design for Aircraft

In this study, a novel pattern shaping technique is presented and applied to the uniquely designed multiple-input multiple-output (MIMO) radio altimeter antenna, acquiring area gain. Inspired by the behavior of the perfect electric conductor, the tendency to gather a diffuse pattern is exploited to create pattern shaping. A surface with a phase response of 0° at 3.824 GHz was designed to ensure that the target radio altimeter frequency of 4.3 GHz is in the immediate vicinity of the outer phase region, where the impedance is around 166.84 Ω, transforming the diffuse pattern of the top antenna into the target conical shape. Antenna reflection values are measured as −20.072 dB at 4.344 GHz (port 1) and −27.44 dB at 4.32 GHz (port 2), while there is 6 mm between the top antenna and its reflector. At 4.32 GHz, the envelope correlation coefficient is 0.0043, the diversity gain is 9.999, and the transmission value between the opposing ports is −29.08 dB, which indicates a low mutual coupling. A MIMO antenna with a measured gain of 10.1497 dBi for port 1 and 10.5617 dBi for port 2 conforming to the design criteria of the radio altimeter is achieved.

Measurements and Characteristics Analysis of 6G Ultra-Massive MIMO Wireless Channels With Different Antenna Configurations and Scenarios

In this paper, ultra-massive multiple-input multiple-output (MIMO) channel measurements at 5.3 GHz are conducted, including different antenna array configurations and different measurement scenarios. The antenna array configurations include uniform linear array (ULA) and distributed uniform linear array (DULA). The measurement scenarios include single-user fixed-to-fixed (F2F), multi-user F2F, and single-user fixed-to-mobile (F2M) measurement scenarios. The statistical properties of ultra-massive MIMO channels are studied, including delay power spectral density (DPSD), space cross-correlation function (SCCF), angle cross-correlation function (ACCF), frequency correlation function (FCF), root mean square (RMS) delay spread (DS), RMS angle spread (AS), singular value spread (SVS), scalar product (SP), level crossing rate (LCR), average fading duration (AFD), Doppler power spectral density (PSD), etc. The specific ultra-massive MIMO channel characteristics are investigated and validated by channel measurements, including spatial non-stationarity, spherical wavefront behavior, channel hardening, and sparse properties in the angle domain. In addition, channel capacities are investigated. The channel measurement results will be a great importance for ultra-massive MIMO communication system deployments.

Three-Dimensional Image Transmission of Integral Imaging through Wireless MIMO Channel.

For the reconstruction of high-resolution 3D digital content in integral imaging, an efficient wireless 3D image transmission system is required to convey a large number of elemental images without a communication bottleneck. To support a high transmission rate, we herein propose a novel wireless three-dimensional (3D) image transmission and reception strategy based on the multiple-input multiple-output (MIMO) technique. By exploiting the spatial multiplexing capability, multiple elemental images are transmitted simultaneously through the wireless MIMO channel, and recovered with a linear receiver such as matched filter, zero forcing, or minimum mean squared error combiners. Using the recovered elemental images, a 3D image can be reconstructed using volumetric computational reconstruction (VCR) with non-uniform shifting pixels. Although the received elemental images are corrupted by the wireless channel and inter-stream interference, the averaging effect of the VCR can improve the visual quality of the reconstructed 3D images. The numerical results validate that the proposed system can achieve excellent 3D reconstruction performance in terms of the visual quality and peak sidelobe ratio though a large number of elemental images are transmitted simultaneously over the wireless MIMO channel.

4096-QAM OFDM THz-Over-Fiber MIMO Transmission Using Delta-Sigma Modulation

A terahertz (THz)-over-fiber multiple-input multiple-output (MIMO) transmission of 4096-ary quadrature amplitude modulation (QAM) orthogonal frequency division multiplexing (OFDM) supported by 46-GBaud quadrature phase shift keying (QPSK) signal at 320 GHz is experimentally demonstrated in this letter. By employing the polarization division multiplexing (PDM) technique and 1-bit delta-sigma modulation (DSM) quantization, we successfully implement 4.6-GHz 4096-QAM OFDM signal transmission over 20 km of standard single-mode fiber (SSMF) and a 3-m MIMO wireless link, and satisfy the soft-decision forward error correction (SD-FEC) threshold of 1.0 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> with 15% overhead, which corresponds to a net rate of 84.4 Gbps for THz-over-fiber transmission. To the best of our knowledge, fusing OFDM and PDM, this is the highest rate achievable for DSM applications in THz communication. This experimental demonstration can provide a promising solution for high-order QAM signals in a fiber-wireless seamless network in future 6G networks.

Low complexity joint hybrid precoding for RIS-assisted wideband wireless systems

Reconfigurable intelligent surface (RIS) has been expected to be a promising technology for next generation communication systems based on its capability of tailoring propagation environments. At the same time, hybrid analog and digital precoding is also a key technology for improving the energy efficiency of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) wireless systems. The requirements of low cost and power consumption for future wireless systems can be met by combining these two technologies. In this paper, we formulate the problem of jointly designing the hybrid precoding at the base station (BS) and the phase shifts at the RIS for both single-cell and multi-cell scenarios to maximize the achievable sum rate. For the single-cell scenario, we propose an improved sparse precoding (ISP) scheme for analog transmit precoding (TPC) design while considering the beam squint effect, and utilize the two-stage digital TPC scheme to reduce the computational complexity. Inspired by the two-stage digital TPC design, we propose the three-stage digital TPC design for the multi-cell scenario, which handles inter-cell and intra-cell interference, and power allocation respectively. Finally, simulation results demonstrate that the proposed scheme has better performance than existing hybrid precoding schemes.

Iterative algorithms and architectures in massive MIMO detection

Massive multiple-input multiple-output (MIMO) wireless systems play an important role in the 5G networks. The complexity of signal detection in massive MIMO is increasing rapidly due to the growth of the number of transmitting antennas. In this paper, we introduced different iterative algorithms to decrease the computational cost of the approximate minimum mean-square error (MMSE) algorithm, including the Neumann Series algorithm, Jacobi method, Gauss-Seidel method, Successive Over Relaxation method and the Conjugate Gradient method. In addition, the VLSI architecture implementations of algorithms mentioned above are also discussed in the article.

MIMO Channel Estimation Using Score-Based Generative Models

Channel estimation is a critical task in multiple-input multiple-output (MIMO) digital communications that substantially effects end-to-end system performance. In this work, we introduce a novel approach for channel estimation using deep score-based generative models. A model is trained to estimate the gradient of the logarithm of a distribution and is used to iteratively refine estimates given measurements of a signal. We introduce a framework for training score-based generative models for wireless MIMO channels and performing channel estimation based on posterior sampling at test time. We derive theoretical robustness guarantees for channel estimation with posterior sampling in single-input single-output scenarios, and experimentally verify performance in the MIMO setting. Our results in simulated channels show competitive in-distribution performance, and robust out-of-distribution performance, with gains of up to 5 dB in end-to-end coded communication performance compared to supervised deep learning methods. Simulations on the number of pilots show that high fidelity channel estimation with 25% pilot density is possible for MIMO channel sizes of up to 64 × 256. Complexity analysis reveals that model size can efficiently trade performance for estimation latency, and that the proposed approach is competitive with compressed sensing in terms of floating-point operation (FLOP) count.

Hybrid precoding design for secure smart-grid enabled MIMO wireless communications in Industry 5.0

Secure and reliable wireless communication systems are essential for the successful integration of smart grid-enabled wireless communications and Industry 5.0 applications. This work proposes a hybrid precoding design for secure smart-grid multiple-input multiple-output (MIMO) wireless communications in Industry 5.0 to maximize the average secrecy capacity of the system while minimizing user outages crucial for maintaining the security and privacy of sensitive data in critical infrastructure. To achieve this, we develop a mathematical model that considers the impact of various system parameters, such as eavesdropping and interference caused by the active eavesdropper and noise, on the secrecy capacity. To find an efficient solution to the optimization problem, we propose an algorithm that decouples the original optimization problem into a series of subproblems and uses iterative techniques to find the optimal values, thereby improving computational efficiency. The hybrid precoding scheme is an effective technique for optimizing the design parameters of MIMO-based secure wireless communication systems. Our proposed approach provides a practical solution for achieving this optimization. Our numerical results demonstrate that our proposed scheme outperforms traditional benchmark schemes, maximizing the average secrecy capacity while minimizing user outages. Our work highlights the importance of secure wireless communication systems in Industry 5.0 and smart grid applications. The proposed approach provides an efficient method for designing secure wireless communication systems that can effectively address the unique challenges posed by these critical infrastructure systems.

65,536-QAM OFDM signal transmission over a fiber-THz system at 320 GHz with delta-sigma modulation.

The transmission of a 65,536-ary quadrature amplitude modulation (QAM) orthogonal frequency division multiplexing (OFDM) signal supported by a hybrid fiber-terahertz (THz) multiple-input multiple-output (MIMO) system at 320 GHz is experimentally demonstrated in this Letter. We adopt the polarization division multiplexing (PDM) technique to double the spectral efficiency. Based on a 23-GBaud 16-QAM link, 2-bit delta-sigma modulation (DSM) quantization enables 65,536-QAM OFDM signal transmission over a 20-km standard single-mode fiber (SSMF) and a 3-m 2 × 2 MIMO wireless delivery, and satisfies the hard-decision forward error correction (HD-FEC) threshold of 3.8 × 10-3, corresponding to a net rate of 60.5 Gbit/s for THz-over-fiber transport. Meanwhile, below the fronthaul error vector magnitude (EVM) threshold of 0.34%, a maximum signal-to-noise ratio (SNR) of 52.6 dB is achieved. To the best of our knowledge, this is the highest modulation order achievable for DSM applications in THz communication.

Beyond 300-Gbps/λ photonics-aided THz-over-fiber transmission employing MIMO single-carrier frequency-domain equalizer.

We experimentally realized a 320-GHz 320-Gbps/λ terahertz (THz) radio-over-fiber (RoF) system based on a photonics-aided scheme with the help of polarization-division multiplexing (PDM) technology and multiple-input, multiple-output (MIMO) transmission. In this system, the low-complexity MIMO single-carrier frequency-domain equalizer (SCFDE) is implemented to compensate for the polarization-related impairments of the PDM signal, and the demultiplexing performances between SCFDE and the commonly used constant modulus algorithm (CMA) are also compared in this proposed system. After 20-km standard single-mode fiber (SSMF) and 3-m 2 × 2 MIMO wireless link transmission, the bit error rate (BER) of the received 46-GBaud PDM 16-ary quadrature amplitude modulation (16QAM) signal satisfies the soft-decision forward error correction (SD-FEC) threshold with 15% overhead, which corresponds to a record-breaking net bit rate of 320 Gbit/s.

A Self-Decoupling Technique to Realize Dense Packing of Antenna Elements in MIMO Arrays for Wideband Sub-6 GHz Communication Systems.

A self-decoupled technique is described that enables the radiating elements in the antenna array to be densely packed for multiple-input multiple-output (MIMO) wireless communications systems. High isolation between the adjacent antenna elements is obtained by fixing the radiating elements in an orthogonal configuration with respects to each other. Current from the adjacent ports cancels their impact which results in low mutual coupling. The additional benefit of this configuration is realizing a densely packed array. The ground plane of each radiating element on the array board itself are isolated to mitigate surface wave propagations to suppress mutual coupling between the antenna elements. The radiating elements are based on a modified edge-fed circular patch antenna that includes a curved slot line and open-circuited stub to widen the array's impedance bandwidth with no impact on the antenna's footprint size. The proposed technique was verified with the design of an antenna array of matrix size 4 × 4 centered at 3.5 GHz. The array had a measured impedance bandwidth of 4 GHz from 1.5 GHz to 5.5 GHz, which corresponds to a fractional bandwidth of 114%, peak gain of 3 dBi and radiation efficiency of 84%. Its average diversity gain and envelope correlation coefficient (ECC) over its operating band are 9.6 dB and &lt;0.016, respectively. The minimum isolation achieved between the radiating elements is better than 15 dB. The dimensions of the array are 0.4 × 0.4 × 0.039λ_g^3. The proposed array has characteristics suitable for sub-6 GHz wireless communication systems.

Energy Efficiency Maximization of Massive MIMO Communications With Dynamic Metasurface Antennas

Future wireless communications are largely inclined to deploy massive numbers of antennas at the base stations (BSs) by leveraging cost- and energy-efficient as well as environmentally friendly antenna arrays. The emerging technology of dynamic metasurface antennas (DMAs) is promising to realize such massive antenna arrays with reduced physical size, hardware cost, and power consumption. The goal of this paper is the optimization of the energy efficiency (EE) performance of DMA-assisted massive multiple-input multiple-output (MIMO) wireless communications. Focusing on the uplink, we propose an algorithmic framework for designing the transmit precoding of each multi-antenna user and the DMA tuning strategy at the BS to maximize the EE performance, considering the availability of either instantaneous or statistical channel state information (CSI). Specifically, the proposed framework is shaped around Dinkelbach's transform, alternating optimization, and deterministic equivalent methods. In addition, we obtain a closed-form solution to the optimal transmit signal directions for the statistical CSI case, which simplifies the corresponding transmission design for the multiple-antenna case. Our numerical results verify the good convergence behavior of the proposed algorithms, and showcase the considerable EE performance gains of the DMA-assisted massive MIMO transmissions over the baseline schemes.

Diversity Order and Measure of MIMO Antennas in Single-User, Multiuser, and Massive MIMO Wireless Communications

In this letter, the diversity order (DO) and the diversity measure (DM) of multiple-input multiple-output (MIMO) antennas in generic single-user, multiuser, and massive MIMO wireless communications are calculated for several practical case studies. These performance metrics are calculated from the antenna correlation coefficient (ACC) matrix. The DO is calculated from the rank of the ACC matrix, and the DM is obtained from the trace and Frobenius norm of the ACC matrix. Numerical results are provided. In particular, it is shown that though the DM is always less than the DO, it incorporates the effect of antenna correlation on the diversity gain in a better way.

Demonstration of 4096QAM THz MIMO wireless delivery employing one-bit delta-sigma modulation.

We experimentally demonstrate 2-Gbaud 4096-ary quadrature amplitude modulation (4096QAM) signal transmission over 2-m wireless distance at 370 GHz in a photonics-aided terahertz (THz)-wave communication system. By using one-bit quantized delta-sigma modulation (DSM) and photonics-aided technology, we successfully achieve the transmission of high-order QAM signals over THz multiple-input multiple-output (MIMO) links. After 2 m of free space transmission, its bit error rate (BER) is below the 20% soft-decision forward error correction (20% SD-FEC) threshold of 2.4 × 10-2. To the best of our knowledge, this is the first time to apply DSM technology in a THz MIMO link transmission.

Delay-Doppler and Angular Domain 4D-Sparse CSI Estimation in OTFS Aided MIMO Systems

A convenient delay, Doppler and angular-(DDA) domain representation of the multiple-input multiple-output (MIMO) wireless channel is conceived for deriving the end to end relationship in the delay-Doppler (DD)-domain for orthogonal time frequency space (OTFS)-based communications. Subsequently, a time-domain pilot based model is developed for estimating the DDA-domain channel state information (CSI) of our MIMO OTFS system. The key differentiating feature of the CSI estimation model derived is its ability to exploit the 4-dimensional (4D)-sparsity arising in the DDA-domain, given the limited number of dominant scatterers. Furthermore, the training overhead of the proposed framework is low, and the pilot placement is quite flexible, necessitating no guard-interval. Finally, an orthogonal matching pursuit (OMP) framework is employed for 4D-sparse CSI acquisition, followed by deriving the Oracle minimum mean squared error (Oracle-MMSE) and its Bayesian Cramer-Rao lower bound (BCRLB). Our simulation results confirm the improved CSI estimation performance attained over the benchmarks.

Secrecy Throughput Maximization for IRS-Aided MIMO Wireless Powered Communication Networks

In this paper, we consider deploying an intelligent reflecting surface (IRS) to enhance the downlink (DL) energy transfer and uplink (UL) information transmission efficiency for secure multiple-input multiple-output (MIMO) wireless powered communication networks (WPCNs). We aim to maximize the secrecy throughput of all users by jointly optimizing the DL/UL time allocation, the energy transmit covariance matrix of hybrid access point (AP), the information transmit beamforming matrix of users and the phase shifts of IRS in DL/UL, subject to constraints of energy/information transmit power at the hybrid AP/users and that of unit-modulus IRS phase shifts for DL/UL. To tackle the non-convex problem, we first transform the original problem into an equivalent form based on the mean-square error (MSE) method given time allocation, and then apply the alternating algorithm to update the optimization variables iteratively. Specifically, the energy covariance matrix and the information beamforming matrix are obtained based on the dual subgradient method. For the IRS phase shifts, we investigate two IRS beamforming reflection setups, namely different DL/UL IRS beamforming and identical DL/UL IRS beamforming. For the former case, the second-order cone programming technique and the Majorization-Minimization algorithm/element by element iterative algorithm are applied to obtain the DL and UL IRS phase shifts, respectively. For the latter case, the IRS phase shifts are obtained by the successive convex approximation technique. To further reduce the computational complexity of the single-user system, we derive the closed-form solutions of IRS phase shifts in each iteration for the two different reflection setups. Simulation results show that all the proposed algorithms can greatly improve the secrecy throughput compared to the conventional system without IRS.