Multiple-input Multiple-output Transmission Research Articles

Impact of Hardware Impairment on the Joint Reconfigurable Intelligent Surface and Robust Transceiver Design in MU-MIMO System

Reconfigurable intelligent surface (RIS) is a revolutionary passive radio technique to facilitate capacity enhancement beyond the current massive multiple-input multiple-output (MIMO) transmission. However, the potential hardware impairment (HWI) of the RIS usually causes inevitable performance degradation and the amplification of imperfect CSI. These impacts still lack full investigation in the RIS-assisted wireless network. This paper developed a robust joint RIS and transceiver design algorithm to minimize the worst-case mean square error (MSE) of the received signal under the HWI effect and imperfect channel state information (CSI) in the RIS-assisted multi-user MIMO (MU-MIMO) wireless network. Specifically, since the proposed robust joint RIS and transceiver design problem yields non-convex characteristics under severe HWI, an iterative three-step convex algorithm is developed to approach the optimality by relaxation and convex transformation. Compared with the state-of-the-art baselines that ignore the HWI, the proposed robust algorithm inhibits the destruction of HWI while raising the worst-case MSE effectively in several numerical simulations. Moreover, due to the properties of the HWI, the performance loss is notable under the magnification of the number of reflected elements in the RIS-assisted MU-MIMO wireless network.

A Novel OFDM-Based Time Domain Quadrature GSM for Visible Light Communication System

In order to improve the spectral efficiency (SE) as well as the receiver performance of band-limited visible light communications (VLCs), two orthogonal frequency division multiplexing (OFDM)-based quadrature generalized multiple-input multiple-output (QG-MIMO) transmission schemes, including time domain (TD) quadrature generalized spatial modulation (TD-QGSM) and TD quadrature generalized spatial multiplexing (TD-QGSMP), are proposed in this paper. Firstly, the constellation symbols in the frequency domain are split into in-phase and quadrature components to perform the OFDM modulation separately. Then, the corresponding time domain signal is spatially mapped on different light emitting diodes (LEDs) for achieving the diversity or multiplexing. In addition, we also propose an illegal vector correction (IVC)-based orthogonal matching pursuit (OMP) detection algorithm to deal with the error propagation and noise amplification effect, where a novel correction criterion is involved for assisting the index vectors estimation and thus for improving the demodulation performance. The simulation results demonstrate that the SE can be significantly improved by the proposed schemes as compared with the existing OFDM-based generalized MIMO schemes, with the TD-QGSM increasing by at least 56.5% and the TD-QGSMP increasing by at least 72.3%. Moreover, the bit error rate (BER) performance can be further improved when applying the proposed IVC-OMP detection method, which outperforms the traditional maximum-likelihood and maximum ratio combining (ML-MRC) detection by at least 62.5%.

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.

Passive OFE WDM-over-POF Gigabits per Second Performance Comparison of Spatial Diversity and Spatial Multiplexing

We present a novel indoor communication network using 1-mm core diameter step-index plastic optical fibres as a feeder line, and using the light emitted by the POF-end for wireless data transmission, creating a fully passive access point (AP). This has the advantage that it does not require electrical powering, resulting in low maintenance. Due to the large numerical aperture, the light emitted by the POF is extremely divergent, thus a lens must be placed in front of the POF-end to adjust the size of the coverage area to enable users moving within the area or to increase the number of users served by the wireless link. We present a theoretical model for both multiple-input multiple-output (MIMO) transmission modes, spatial diversity (SD) and spatial multiplexing (SM) concepts, using orthogonal frequency division multiplexing (OFDM). We report the system throughput, that is estimated using the singular value decomposition (SVD) of the experimentally measured channel matrix <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf {H}(f)$</tex-math></inline-formula> . We then present the experimental results applying both SD and SM concepts and make a comparison between theoretical and experimental results. We demonstrate that this passive AP concept using OFDM achieves throughputs of around 5.2 Gbps when SM is applied, and 3.8 Gbps when SD is applied. Furthermore, we use eye-safe visible light laser at the beginning of the POF feeder which, due to optical losses by POF and components, limited the wireless link to 1 m only and the coverage area to 45 cm diameter. We believe the proposed system represents a low-cost, high-capacity, highly secure, interference free wireless system, suitable for next generation for industrial and home applications.

Adaptive Transmission Based on MIMO Mode Switching Over Malaga Turbulence Channel With Pointing Error

In this paper, we propose a dynamic adaptive multiple input multiple output (MIMO) free space optical (FSO) system with spatial mode switching. Based on the channel conditions, the proposed system can select different MIMO transmission modes: diversity, multiplexing or hybrid mode that yields the maximum average channel capacity while satisfying the reliable average bit error rate (BER). Considering the combined effects of path loss, pointing error and atmospheric turbulence-induced fading modeled by Malaga distribution, we derive the closed-form expressions of average channel capacity and average BER of MIMO system for each transmission mode. From adaptive system performance evaluated results, we establish the signal-to-noise ratio (SNR) threshold look-up table (LUT) in different scenarios to select the optimal transmission mode. The extensive numerical results demonstrate that the proposed adaptive system has a significant improvement in average channel capacity compared with each stand-alone mode system. Finally, Monte Carlo simulation is also provided to verify the correctness of the proposed adaptive scheme and conclusions.

Spatial multiplexing in near field MIMO channels with reconfigurable intelligent surfaces

AbstractWe consider a multiple‐input multiple‐output (MIMO) channel in the presence of a reconfigurable intelligent surface (RIS). Specifically, our focus is on analysing the spatial multiplexing gains in line‐of‐sight and low‐scattering MIMO channels in the near field. We prove that the channel capacity is achieved by diagonalising the end‐to‐end transmitter‐RIS‐receiver channel, and applying the water‐filling power allocation to the ordered product of the singular values of the transmitter‐RIS and RIS‐receiver channels. The obtained capacity‐achieving solution requires an RIS with a non‐diagonal matrix of reflection coefficients. Under the assumption of nearly‐passive RIS, that is, no power amplification is needed at the RIS, the water‐filling power allocation is necessary only at the transmitter. We refer to this design of RIS as a linear, nearly‐passive, reconfigurable electromagnetic object (EMO). In addition, we introduce a closed‐form and low‐complexity design for RIS, whose matrix of reflection coefficients is diagonal with unit‐modulus entries. The reflection coefficients are given by the product of two focusing functions: one steering the RIS‐aided signal towards the mid‐point of the MIMO transmitter and one steering the RIS‐aided signal towards the mid‐point of the MIMO receiver. We prove that this solution is exact in line‐of‐sight channels under the paraxial setup. With the aid of extensive numerical simulations in line‐of‐sight (free‐space) channels, we show that the proposed approach offers performance (rate and degrees of freedom) close to that obtained by numerically solving non‐convex optimization problems at a high computational complexity. Also, we show that it provides performance close to that achieved by the EMO (non‐diagonal RIS) in most of the considered case studies.

MIMO Terahertz Quantum Key Distribution Under Restricted Eavesdropping

Quantum key distribution (QKD) can provide unconditional security to next generation communication networks guaranteed by the laws of quantum physics. This paper studies the secret key rate (SKR) of a continuous variable quantum key distribution (CV-QKD) system using multiple-input multipleoutput (MIMO) transmission and operating at Terahertz (THz) frequencies. Distinct from previous works, we consider a practical “restricted" eavesdropping scenario in which Eve can collect only a fraction of photons lost in the environment. We propose a system model for the MIMO THz CV-QKD system that accounts for restricted eavesdropping via a lossy wireless channel between Alice and Eve. We derive for this system new SKR expressions for both coherent-state-based and squeezed-state-based CV-QKD protocols. Our results show that previous analysis assuming unrestricted eavesdropping leads to overly pessimistic SKRs, and that in practice, the achievable SKR can be significantly increased under restricted eavesdropping. The increase in the SKR is quantified by the simplified SKR expansions derived in this paper. Our results also reveal that squeezing is beneficial for improving the SKR only for unrestricted eavesdropping. However, in a practical setting with restricted eavesdropping, increased squeezing leads to a reduction in the SKR.

Integrated Polarization and Spatial Modulation

In this contribution, the concepts of polarization modulation (PM) and spatial modulation (SM) are integrated, to reap their respective advantages toward single-radio frequency (RF) multiple-input multiple-output (MIMO) transmissions. In the so-called polarization and spatial modulation (PSM) system, the information is conveyed by activated antenna indices as well as polarization modulated symbols, while at the receiver, a low-complexity near-optimal detection algorithm based on compressive sensing (CS) is proposed. Furthermore, a closed-form union bound of the average bit-error rate (BER) over fading channels is quantified by theoretical derivation, which is then extended to the case of spatial correlation (SC) as well as channel estimation error (CSE) toward practical use. Finally, our simulation results demonstrate the superiority of the developed PSM system over conventional PM in terms of BER performance over various fading channels.

Receiver Design for MIMO Unsourced Random Access With Sparse Kronecker-Product Coding

In this letter, we extend the sparse Kronecker-product (SKP) coding scheme, originally designed for the additive white Gaussian noise (AWGN) channel, to multiple input multiple output (MIMO) unsourced random access (URA). With the SKP coding adopted for MIMO transmission, we develop an efficient Bayesian iterative receiver design to solve the intended challenging trilinear factorization problem. Numerical results show that the proposed design outperforms the existing counterparts, and that it performs well in all simulated settings with various antenna sizes and active-user numbers.

A Next-Generation Codebook Evolution Strategy for Massive Arrays Using Deep Neurals Networks

The discrete Fourier transform (DFT)-based codebook is currently among the mostly commonly adopted codebooks for beamforming using arrays of different shapes and sizes, including the large-scale two-dimensional uniform planar array (UPA). DFT-based codevectors can be easily generated in arbitrary angle resolutions and apply well to millimeter-wave (mmWave) channels due to their directive nature of resulting beams. However, a fixed set of codevectors is applied regardless of the user distributions and the propagation environment, which may exhibit limited beamforming performance under certain transmission scenarios. In this paper, we propose a new way of generating a set of beamforming vectors for multiple-input multiple-output (MIMO) transmission using massive arrays under the limited feedback of the channel state information (CSI). Precoder matrix indicator (PMI) and channel quality indicator (CQI) reports from the users have become the sources for the generation of a new set of codevectors, which are autonomously determined by the deep learning (DL) module at the base station (BS). The process is operated in an iterative fashion to produce updated versions of the codebook with the reduced return of the loss function at the deep neural network (DNN). The time-varying codebook for each BS automatically reflects the characteristics of a given wireless environment to adapt to its channel and traffic conditions. The reference signal (RS) at the BS is periodically transmitted in the form of beamformed CSI-RS, thus the operation is transparent to the users of the system and no significant specification changes are necessary. A simple plug-and-play type of BS installation suffices to achieve the potential gain of the proposal, which is demonstrated by the implementation details of the DL engine and the corresponding performance simulation results.

Digital Predistortion Combined with Iterative Method for MIMO Transmitters

In this article, an auxiliary module is proposed to mitigate the crosstalk effect in multiple input–multiple output (MIMO) transmitters. Other branches do not need considering when linearizing the local branch, which reduces the complexity of the auxiliary module, and some branches can be linearized selectively to make the module application more flexible. In the end, the feasibility of the proposed algorithm is verified through the experimental platform. Experimental results demonstrate that for a 2 × 2 MIMO transmitter with −20 dB nonlinear crosstalk, the proposed DPD improves the adjacent channel power ratio (ACPR) more than 16 dB, and normalized mean square error (NMSE) more than 12.8 dB, which has similar performance to the PH model. The predistorter can be implemented with fewer coefficients by separating the crosstalk from the nonlinearity, enabling the technique to be used in 5G massive MIMO scenarios.

Training Data Selection and Dimensionality Reduction for Polynomial and Artificial Neural Network MIMO Adaptive Digital Predistortion

In 5G and beyond radios, the increased bandwidth, the fast-changing waveform scenarios, and the operation of large array multiple-input multiple-output (MIMO) transmitter architectures have challenged both the polynomial and the artificial neural network (ANN) MIMO adaptive digital predistortion (DPD) schemes. This article proposes training data selection methods and dimensionality reduction techniques that can be combined to enable relevant reductions of the DPD training time and the implementation complexity for MIMO transmitter architectures. In this work, the combination of an efficient uncorrelated equation selection (UES) mechanism together with orthogonal least squares (OLS) is proposed to reduce the training data length and the number of basis functions at every behavioral modeling matrix in the polynomial MIMO DPD scheme. For ANN MIMO DPD architectures, applying UES and principal component analysis (PCA) is proposed to reduce the input dataset length and features, respectively. The UES-OLS and the UES-PCA techniques are experimentally validated for a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2 \,\times \, 2$ </tex-math></inline-formula> MIMO test setup with strong power amplifier (PA) input and output crosstalk.

LoS MIMO transmission for LEO satellite communication systems

To provide global service with low latency, the broadband low earth orbits (LEO) satellite constellation based communication systems have become one of the focuses in academic and industry. To allow for wideband access for user links, the feeder link of LEO satellite is correspondingly required to support high throughput data communications. To this end, we propose to apply line-of-sight (LoS) multiple-input multiple-output (MIMO) transmission for the feeder link to achieve spatial multiplexing by optimizing the antenna arrangement. Unlike the LoS MIMO applications for static scenarios, the movement of LEO satellites make it impractical to adjust the optimal antenna separation for all possible satellite positions. To address this issue, we propose to design the antenna placement to maximize the ergodic channel capacity during the visible region of the ground station. We first derive the closed-form probability distribution of the satellite trajectory in visible region. Based on which the ergodic channel capacity can be then calculated numerically. The antenna placement can be further optimized to maximize the ergodic channel capacity. Numerical results verify the derived probability distribution of the satellite trajectory, and show that the proposed LoS MIMO scheme can significantly increase the ergodic channel capacity compared with the existing SISO one.

Deep learning-based AMP for massive MIMO detection

Low-complexity detectors play an essential role in massive multiple-input multiple-output (MIMO) transmissions. In this work, we discuss the perspectives of utilizing approximate message passing (AMP) algorithm to the detection of massive MIMO transmission. To this end, we need to efficiently reduce the divergence occurrence in AMP iterations and bridge the performance gap that AMP has from the optimum detector while making use of its advantage of low computational load. Our solution is to build a neural network to learn and optimize AMP detection with four groups of specifically designed learn-able coefficients such that divergence rate and detection mean squared error (MSE) can be significantly reduced. Moreover, the proposed deep learning-based AMP has a much faster converging rate, and thus a much lower computational complexity than conventional AMP, providing an alternative solution for the massive MIMO detection. Extensive simulation experiments are provided to validate the advantages of the proposed deep learning-based AMP.

Massive MIMO Hybrid Precoding for LEO Satellite Communications With Twin-Resolution Phase Shifters and Nonlinear Power Amplifiers

The massive multiple-input multiple-output (MIMO) transmission technology has recently attracted much attention in the non-geostationary, e.g., low earth orbit (LEO) satellite communication (SATCOM) systems since it can significantly improve the energy efficiency (EE) and spectral efficiency. In this work, we develop a hybrid analog/digital precoding technique in the massive MIMO LEO SATCOM downlink, which reduces the onboard hardware complexity and power consumption. In the proposed scheme, the analog precoder is implemented via a more practical twin-resolution phase shifting (TRPS) network to make a meticulous tradeoff between the power consumption and array gain. In addition, we consider and study the impact of the distortion effect of the nonlinear power amplifiers (NPAs) in the system design. By jointly considering all the above factors, we propose an efficient algorithmic approach for the TRPS-based hybrid precoding problem with NPAs. Numerical results show the EE gains considering the nonlinear distortion and the performance superiority of the proposed TRPS-based hybrid precoding scheme over the baselines.

Power Allocation Optimization for OAM-MIMO Systems With Unaligned Antennas

Crosstalk among different orbital angular momentum (OAM) states, mainly caused by the atmospheric turbulence and the misalignment between the transmitting and receiving antennas, leads to the increase of error probability of OAM transmission systems. Considering the OAM-based multiple-input multiple-output (OAM-MIMO) transmission system with unaligned antennas, the error probability model is derived under the non-Kolmogorov turbulence. Furthermore, a power allocation optimization algorithm is proposed to alleviate the crosstalk among different OAM states, thus effectively decreasing the error probability of the OAM-MIMO transmission system. Numerical results show that the error probability reduction of the OAM-MIMO transmission system by using the proposed optimization algorithm is up to 26.1 dB.

Modeling and Optimization of OAM-MIMO Communication Systems With Unaligned Antennas

The orbital angular momentum (OAM) wireless communication technique is emerging as one of potential techniques for the Sixth generation (6G) wireless communication system. The most advantage of OAM wireless communication technique is the natural orthogonality among different OAM states. However, one of the most disadvantages is the crosstalk among different OAM states which is widely caused by the atmospheric turbulence and the misalignment between the transmitting and receiving antennas. Considering the OAM-based multiple-input multiple-output (OAM-MIMO) transmission system with unaligned antennas, a new channel model is proposed for performance analysis. Moreover, the purity and crosstalk models of the OAM-MIMO transmission system with unaligned antennas are derived for the non-Kolmogorov turbulence. Furthermore, the error probability, bit error rate (BER) and capacity models are derived for OAM-MIMO transmission systems with unaligned antennas. To overcome the disadvantage caused by the unaligned antennas and non-Kolmogorov turbulence, a new optimization algorithm of OAM state interval is proposed to improve the capacity of the OAM-MIMO transmission system. Numerical results indicate that the capacity of OAM-MIMO transmission system is improved by the proposed optimization algorithm. Specifically, the capacity increment of the OAM-MIMO transmission system adopting the proposed optimization algorithm is up to 28.7% and 320.3% when the angle of deflection between the transmitting and receiving antennas is −24 dB and −5 dB, respectively.

Multi-User Massive MIMO Visible Light Communications With Limited Pilot Transmission

Visible light communication (VLC) building on the existing illumination infrastructure utilizes light emitting diode (LED) luminaries as wireless transmitters. To achieve data rates on the order of gigabits per second in VLC systems, multiple-input multiple-output (MIMO) transmission has been identified as a key technology. In this paper, we consider a centralized network architecture where the ceiling LED luminaries act as transmitter elements of a distributed massive MIMO VLC system. To obtain the full benefits of massive MIMO, channel state information must be available at the transmitter side. Downlink (DL) channel estimation in a massive MIMO system requires huge pilot overhead in DL as well as feedback overhead in uplink. This makes the implementation of massive MIMO system infeasible if not properly designed. In our study, we address the design of massive MIMO VLC systems with a limited number of DL pilot signals. We explore different DL pilot patterns (PPs) in frequency, time, and spatial domains where interpolation is performed to obtain the global channel matrix taking advantage of the indoor environment geometry and layout of luminaries. We then present data rate results for different DL PPs under the consideration of varying number of active user equipments through Monte-Carlo simulations.

Operational Characteristics of Square-Law Combining Energy Detector in MIMO-OFDM Cognitive Radio Systems

To ensure effective spectrum usage, cognitive radio networks (CRNs) are being investigated extensively. The important function of CRNs is spectrum sensing (SS). This is the process of sensing the unused frequency spectrum and deciding whether the signal transmission of a primary user (PU) exists. In this work, the results of a performance analysis related to detecting PU signals using the energy detection (ED) SS method realized by employing the square-law combining (SLC) technique are presented. The assessment of the effectiveness of the ED method is performed in relation to prominent communication technology based on Orthogonal Frequency Division Multiplexing (OFDM) and Multiple-Input Multiple-Output (MIMO) transmissions. Due to the impact of changes in the noise power of the PU signal, referred to as noise uncertainty (NU), the MIMO-OFDM transmission in a real communication environment cannot guarantee accurate sensing performed by employing ED based on the SLC method at the secondary user (SU). More precise SS can be achieved if dynamic detection threshold (DDT) changes are employed according to the channel conditions impacted by NU. Thus, this work investigated the effect of NU variations and DDT adjustments on the detection probability for various levels of false alarm probability. This interdependence is presented as receiver operating characteristic (ROC) curves. A mathematical model including different operational parameters was developed to define the fundamental parameters of the ED method based on the SLC approach. Using the developed mathematical model, an algorithm was created which simulates SLC ED processes using DDT in single-input single-output (SISO)- and MIMO-OFDM communication systems affected by NU. Based on the simulation results, comprehensive analyses of the impact of versatile DDT adaptations and NU variations on the shape of the ROC curves for the ED process performed with different numbers of transmitting and receiving antenna, modulation techniques, detection sample numbers, PU transmitting powers, and SNR values are presented.

Multiuser MIMO Uplink Transmission With Electromagnetic Exposure Constraints: Spectral Efficiency and Energy Efficiency Tradeoff

Along with the relentless development of wireless communications, the electromagnetic (EM) radiation emitted by wireless devices has gradually turned into a significant concern of the public. A growing number of government departments and communication regulatory agencies require that EM radiation be limited to a suitable level with the measurement of specific absorption rate (SAR). Meanwhile, both spectral efficiency (SE) and energy efficiency (EE) are key indicators of wireless transmission systems, so that they generally need to be considered at the same time. To this end, we investigate the resource efficiency (RE), which characterizes the weighted sum of SE and EE, in uplink multiuser multiple-input multiple-output (MIMO) transmission with EM constraints. We first simplify the RE calculation by applying its deterministic equivalents (DEs) and deal with the objective function by the quadratic transform algorithm. Then, a modified RE maximization water-filling algorithm is proposed for the precoder design at the users. Numerical results indicate the superior performance of the EM aware RE oriented transmission scheme.