MIMO Transmission Research Articles

On the Distribution of SINR for Widely Linear MMSE MIMO Systems With Rectilinear or Quasi-Rectilinear Signals

Although the widely linear least mean square error (WLMMSE) receiver has been an appealing option for multiple-input-multiple-output (MIMO) wireless systems, a statistical understanding on its pose-detection signal-to-interference-plus-noise ratio (SINR) in detail is still missing. To this end, we consider a WLMMSE MIMO transmission system with rectilinear or quasi-rectilinear (QR) signals over the uncorrelated Rayleigh fading channel and investigate the statistical properties of its SINR for an arbitrary antenna configuration with $N_t$ transmit antennas and $N_r$ receive ones. We first derive an analytic probability density function (PDF) of the SINR in terms of the confluent hypergeometric function of the second kind, for WLMMSE MIMO systems with an arbitrary $N_r$ and $N_t=2, 3$. For a more general case in practice, i.e., $N_t>3$, we resort to the moment generating function to obtain an approximate but closed form PDF under some mild conditions, which, as expected, is more Gaussian-like as $2N_r-N_t$ increases. The so-derived PDFs are able to provide key insights into the WLMMSE MIMO receiver in terms of the outage probability, the symbol error rate, and the diversity gain, all presented in closed form. In particular, its diversity gain and the gain improvement over the conventional LMMSE one are explicitly quantified as $N_r-(N_t-1)/2$ and $(N_t-1)/2$, respectively. Finally, Monte Carlo simulations support the analysis.

Genetic Optimization of Liquid Crystal Matrix Based Interference Suppression for VLC MIMO Transmissions

Optical channel decorrelation is a key aspect in designing a multi-user visible light communication system. As light-emitting diodes (LEDs) are commonly used for illumination and data transmission in such a system simultaneously, the interference between them is a major problem for suitable modulation schemes. We have proposed to position liquid-crystal (LC) matrix elements in front of the receivers in order to block unwanted light – so effectively acting as filter and reducing the interference. To do so, the appropriate pixels of the LC filter are switched either to a transmissive state or to an opaque state. The selection of the correct pixel patterns is a high-order optimization problem, which makes it challenging for classic algorithms. In this paper, we suggest applying a genetic optimization to find suitable pixel patterns. We combine this kind of receiver-side optimization with conventional convex precoding at the transmitter side in an iterative manner. The overall optimization goal is to maximize the sum rate over all users. To prove the effectiveness, we use a numeric ray-tracing simulation with different settings. Also we analyze the impact of the main parameters for the genetic algorithm.

Analog MIMO Communication for One-Shot Distributed Principal Component Analysis

A fundamental algorithm for data analytics at the edge of wireless networks is distributed principal component analysis (DPCA), which finds the most important information embedded in a distributed high-dimensional dataset by distributed computation of a reduced-dimension data subspace, called principal components (PCs). In this paper, to support one-shot DPCA in wireless systems, we propose a framework of analog MIMO transmission featuring the uncoded analog transmission of local PCs for estimating the global PCs. To cope with channel distortion and noise, two maximum-likelihood (global) PC estimators are presented corresponding to the cases with and without receive channel state information (CSI). The first design, termed coherent PC estimator, is derived by solving a Procrustes problem and reveals the form of regularized channel inversion where the regulation attempts to alleviate the effects of both receiver noise and data noise. The second one, termed blind PC estimator, is designed based on the subspace channel-rotation-invariance property and computes a centroid of received local PCs on a Grassmann manifold. Using the manifold-perturbation theory, tight bounds on the mean square subspace distance (MSSD) of both estimators are derived for performance evaluation. The results reveal simple scaling laws of MSSD concerning device population, data and channel signal-to-noise ratios (SNRs), and array sizes. More importantly, both estimators are found to have identical scaling laws, suggesting the dispensability of CSI to accelerate DPCA. Simulation results validate the derived results and demonstrate the promising latency performance of the proposed analog MIMO

Large-Aperture Metamaterial Lens Antenna for Multi-Layer MIMO Transmission for 6G

A metamaterial lens refers to a planar structure having multiple metamaterial unit cells capable of manipulating electromagnetic waves to improve antenna gains by changing their shape, geometry, size, or orientation. In this paper, we propose a large-aperture metamaterial lens antenna (MLA) designed to improve the gain of multiple beams emitted from a linear feed antenna array, taking multi-layer transmission into account. A new channel model incorporating MLA is presented to evaluate the performance of the proposed MLA on beam gain and system throughput gain. The channel model is derived by decomposing the entire propagation channel from the transmit antenna to the receive antenna through metamaterial lens into five serial channels. The measurement results of the MLA prototype prove that the channel model is valid to reflect the actual multiple beam patterns. Simulation results based on the channel model show that a single large-aperture MLA can achieve beam gain of up to 14 dB compared to the case without a lens. Finally, by adopting the proposed large-aperture MLA, it is shown through system-level simulation that the throughput of user equipment is increased on cellular networks.

An overview of quantum computing and quantum communication systems

An overview of quantum computing and quantum communication systems

Coordinated Average EIRP Control of Radio Transmitters for EMF Exclusion Zone Computation

The 4G and 5G deployment of massive MIMO capable radios increase peak EIRPs, which in turn increase the sizes of the RF EMF exclusion zones applied for the general public and workers if time averaging is not considered, sometimes to dimensions exceeding 20 meters. The deployment becomes even more challenging when multiple massive MIMO transmitters are co-sited with overlapping antenna ranges. This letter therefore proposes an algorithm for joint control of the time averaged EIRP produced by all co-sited radio transmitters at a site. The algorithm minimizes a new throughput degradation criterion, based on long term traffic averages of each radio transmitter. Simulations show that the controller improves the total throughput of the site and/or reduces the size of the total computed RF EMF exclusion zone, as compared to when per-radio average power control is applied.

Cascaded Channel Estimation for RIS Assisted mmWave MIMO Transmissions

Channel estimation is challenging for the reconfigurable intelligence surface (RIS) assisted millimeter wave (mmWave) communications. Since the number of coefficients of the cascaded channels in such systems is closely dependent on the product of the number of base station antennas and the number of RIS elements, the pilot overhead would be prohibitively high. We propose a cascaded channel estimation framework for an RIS assisted mmWave multiple-input multiple-output system, where the wideband effect on transmission model is considered. Then, we transform the wideband channel estimation into a parameter recovery problem and use a few pilot symbols to detect the channel parameters by the Newtonized orthogonal matching pursuit algorithm. Moreover, the Cramer-Rao lower bound on the channel estimation is introduced. Numerical results show the effectiveness of the proposed channel estimation scheme.

Performance analysis of trigger frame in enhanced UL and DL MU MIMO transmissions

Performance analysis of trigger frame in enhanced UL and DL MU MIMO transmissions

Massive MIMO Techniques for 5G and Beyond—Opportunities and Challenges

Telecommunications have grown to be a pillar to a functional society and the urge for reliable and high throughput systems has become the main objective of researchers and engineers. State-of-the-art work considers massive Multiple-Input Multiple-Output (massive MIMO) as the key technology for 5G and beyond. Large spatial multiplexing and diversity gains are some of the major benefits together with an improved energy efficiency. Current works mostly assume the application of well-established techniques in a massive MIMO scenario, although there are still open challenges regarding hardware and computational complexities and energy efficiency. Fully digital, analog, and hybrid structures are analyzed and a multi-layer massive MIMO transmission technique is detailed. The purpose of this article is to describe the most acknowledged transmission techniques for massive MIMO systems and to analyze some of the most promising ones and identify existing problems and limitations.

Multi-Stream Spatial Digital Predistortion for Fully-Connected Hybrid Beamforming Massive MIMO Transmitters

In this paper, a novel multi-stream spatial digital predistortion (DPD) technique is proposed to model and linearize the fully-connected (FC) hybrid beamforming (HBF) transmitters. The proposed scheme solves the DPD implementation issue in the FC HBF array by estimating and linearizing the beam signals instead of the individual PAs. In FC HBF systems, significant intermodulation (IMD) between different transmit signals will be generated due to the analog beamforming and combining network upstream of the power amplifiers (PAs). The IMD beams will end up being radiated in different directions and some of them might fall in the linear beam directions. Therefore, multi-input DPD blocks using a practical multi-variable model are constructed for each RF chain to eliminate the complicated inner- and cross-channel IMDs of the beam signals. Simulations on a 4-stream 64-element FC HBF array and experimental tests on a 2-stream 4-element system are carried out to benchmark the proposed DPD technique against the conventional techniques. Better than 13 dB adjacent channel power ratio (ACPR) improvement and 12 dB normalized mean square error (NMSE) improvement have been achieved by the proposed DPD technique.

Experimental Evaluation of Indoor Optical Wireless MIMO Systems With Square and Linear Array Constellations

In this article, we investigate the performance of the newly designed 4 × 4 optical wireless multiple-input-multiple-output (MIMO-OWC) system based on a linearly-shaped arrangement of transmitters and receivers, to achieve long-distance and high data rate transmission. To highlight the importance of selecting an appropriate arrangement for the optical elements, we carried on a comparative study, considering both the conventional square and the proposed horizontal linear constellation of optical modems. The performance of the bit error rate (BER) is experimentally evaluated at distances up to 65 m, using two important metrics inherent to the MIMO transmission channel matrix, i.e., the Frobenius norm and the condition number. The results show that the channel matrix shape characterized by the condition number dominates the BER if the Frobenius norm is smaller than 1. Furthermore, the proposed MIMO-OWC system employing a linearly-shaped arrangement of transmitters and receivers, shows to be more immune to the calibration error rather than the conventional square constellation optical modems. Moreover, the transmission of 100 Mbps data-rate and a BER lower than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> could be successfully achieved at a 65 m communication range.

Recursively Filtered MIMO Transmission With Quadratic Complexity

Wireless millimeter wave base stations need antenna arrays with a large number of elements to achieve a sufficient coverage. This leads to a high computational complexity when digital MIMO transmission schemes are used. The complexity is further increased by the millimeter wave numerologies that reduce the OFDMA symbol times, and by the ultra reliable low latency communication standard for 5G which allows scheduling on a mini-slot basis. To reduce the complexity this letter exploits a filtered buildup of the channel covariance matrix from low rank contributions. A dual application of the matrix inversion lemma transforms the beam weight computation into a formulation that has quadratic instead of cubic complexity in the number of antenna elements of the base station. The filtering restricts the use of the method to slowly varying radio environments.

Nonlinearities effects on optical MIMO systems

Multimode fibers (MMF) are enjoying a renewed attention boosted by recent advances in multimode complex nonlinear optics. Reason behind nonlinearity is occurred either due to intensity dependence of the medium refractive index or to inelastic-scattering phenomenon. The most commonly occurred non-linear effects in optical Multiple Input Multiple Output (O-MIMO) are the Kerr, Stimulated Brillouin Scattering (SBS) and Stimulated Raman Scattering (SRS) effects. The impact of Kerr, SBS and SRS instigate distortions to the optical signal transmission over MIMO transmission system. In this work, we focus on the impact of the optical Kerr, SBS and SRS effects on the overall performance of a MIMO transmission system. It is observed that in O-MIMO system, nonlinear effects degrade the system performance since many channels propagate simultaneously. They can result in pulse distortion and crosstalk between channels. Here, a comparative study between MIMO communication system with and without nonlinearities allows an accurate performance evaluation. The comparison is performed using Q-factor and Bit Error Rate (BER). The outcome is analyzed using OptiSystem software tool.

Deep Learning Based MIMO Transmission with Precoding and Radio Transformer Networks

In this paper, we study MIMO transmission schemes based on deep learning (DL). We propose a novel DL-based MIMO communication structure by combing a beamforming network at the transmitter side and a radio transformer network (RTN) at the receiver side. Compared with the classical DL-based MIMO communication systems, the interference is potentially mitigated by a precoding network and a RTN network, which is thus beneficial to improve the performance of signal detection. Simulation results show that the proposed scheme outperforms the classical MIMO transmission schemes in terms of bit error rate (BER).

A Generalized Space-Frequency Index Modulation Scheme for Downlink MIMO Transmissions With Improved Diversity

Multidimensional Index Modulations (IM) are a novel alternative to conventional modulations which can bring considerable benefits for future wireless networks. Within this scope, in this paper we present a new scheme, named as Precoding-aided Transmitter side Generalized Space-Frequency Index Modulation (PT-GSFIM), where part of the information bits select the active antennas and subcarriers which then carry amplitude and phase modulated symbols. The proposed scheme is designed for multiuser multiple-input multiple-output (MU-MIMO) scenarios and incorporates a precoder which removes multiuser interference (MUI) at the receivers. Furthermore, the proposed PT-GSFIM also integrates signal space diversity (SSD) techniques for tackling the typical poor performance of uncoded orthogonal frequency division multiplexing (OFDM) based schemes. By combining complex rotation matrices (CRM) and subcarrier-level interleaving, PT-GSFIM can exploit the inherent diversity in frequency selective channels and improve the performance without additional power or bandwidth. To support reliable detection of the multidimensional PT-GSFIM we also propose three different detection algorithms which can provide different tradeoffs between performance and complexity. Simulation results shows that proposed PT-GSFIM scheme, can provide significant gains over conventional MU-MIMO and GSM schemes.

Non-Linear Base-Station Processing Within a 3GPP Compliant Framework

MIMO mobile systems, with a large number of antennas at the base-station side, enable the concurrent transmission of multiple, spatially separated information streams, and therefore, enable improved network throughput and connectivity both in uplink and downlink transmissions. Traditionally, such MIMO transmissions adopt linear base-station processing, that translates the MIMO channel into several single-antenna channels. While such approaches are relatively easy to implement, they can leave on the table a significant amount of unexploited MIMO capacity and connectivity capabilities. Recently-proposed non-linear base-station processing methods claim this unexplored capacity and promise substantially increased network throughput and connectivity capabilities. Still, to the best of the authors’ knowledge, non-linear base-station processing methods not only have not yet been adopted by actual systems, but have not even been evaluated in a standard-compliant framework, involving all the necessary algorithmic modules required by a practical system. In this work, for the first time, we incorporate and evaluate non-linear base-station processing in a 3GPP standard environment. We outline the required research platform modifications and we verify that significant throughput gains can be achieved, both in indoor and outdoor settings, even when the number of base-station antennas is much larger than the number of transmitted information streams. Then, we identify missing algorithmic components that need to be developed to make non-linear base-station practical, and discuss future research directions towards potentially transformative next-generation mobile systems and base-stations (i.e., 6G) that explore currently unexploited non-linear processing gains.

COMBINED INFLUENCE OF DOPPLER EFFECT AND PILOT DE-ORTHOGONALIZATION ON 2×2 TO 4×4 MIMO SYSTEMS AND IMPROVEMENT OF ORTHOGONAL SEQUENCES

The Doppler effect in 2×2, 3×3, and 4×4 MIMO wireless communication systems with channel state estimation is studied. The orthogonal pilot signal approach is used for the channel estimation, where the Hadamard sequences are used for piloting along with the eight Romanuke orthogonal sets similar to the Walsh set. The Doppler effect is additionally aggravated by the pilot signal de-orthogonalization, where two negative-to-positive symbol errors are assumed to have occurred while signal is transmitted. MIMO transmissions are simulated for 10 cases of the frame length and pilot symbols per frame by no Doppler shift to 1100 Hz Doppler shift with a step of 100 Hz. By assuming that the carrier frequency is 5,9 GHz, the step corresponds to a motion speed of about 18.3 km/hr. Based on the simulations, it is ascertained that the Doppler effect negatively influences transmissions of long data packets. It is impracticable to apply MIMO transmissions of long packets at speeds exceeding 100 km/hr. To maintain an appropriate MIMO link data rate, the packet length should be shortened as the motion speed increases. On the other hand, the MIMO performance is substantially improved by increasing the number of antennas, except for the case of transmitting long packets. Besides, under the de-orthogonalization caused by two negative-to-positive symbol errors, the MIMO Walsh pilot sequences are outperformed by MIMO Romanuke pilot sequences, so the latter are considered as an improvement of MIMO orthogonal sequences. However, the performance difference between the Romanuke and Walsh pilot sequences decays as a greater number of transmit-receive antenna pairs is used and the motion speed increases.

Doppler Effect in 2 × 2 to 4 × 4 Mimo Systems of Wireless Communication with Orthogonal Pilot Channel Estimation

Abstract The Doppler effect in 2×2, 3×3, 4×4 MIMO wireless communication systems with channel estimation is studied. The orthogonal pilot signal approach is used for the channel estimation, where the Hadamard sequences are used for piloting, along with the eight alternative orthogonal sets similar to the Walsh set. MIMO transmissions are simulated for 10 cases of the frame length and pilot symbols per frame by no Doppler shift to 1100 Hz Doppler shift with a step of 100 Hz. Based on the simulation, it is ascertained that MIMO transmissions of shorter frames are less sensitive to the Doppler effect. Despite increasing the number of antennas does not mitigate the Doppler effect, and the bit-error rate performance of 4×4 MIMO systems worsens faster than that of 2×2 MIMO systems, it is better to use the maximum number of antennas. The Doppler effect does badly worsen the performance at highway and express train speeds (100 km/hr, and faster), leaving only possibility to further shorten transmissions. This, however, decreases the data rate, but the respective accuracy-versus-data-rate tradeoff must be acceptable.

Evolution and Impact of Wi-Fi Technology and Applications: A Historical Perspective

The IEEE 802.11 standard for wireless local area networking (WLAN), commercially known as Wi-Fi, has become a necessity in our day-to-day life. Over a billion Wi-Fi access points connect close to hundred billion of IoT devices, smart phones, tablets, laptops, desktops, smart TVs, video cameras, monitors, printers, and other consumer devices to the Internet to enable millions of applications to reach everyone, everywhere. The evolution of Wi-Fi technology also resulted in the first commercial piloting of spread spectrum, high speed optical communications, OFDM, MIMO and mmWave pulse transmission technologies, which then became more broadly adopted by cellular phone and wireless sensor networking industries. The popularity and widespread Wi-Fi deployment in indoor areas further motivated innovation in opportunistic cyberspace applications that exploit the ubiquitous Wi-Fi signals. The RF signal radiated from Wi-Fi access points creates an “RF cloud” accessible to any Wi-Fi equipped device hosting or supporting these opportunistic applications. Wi-Fi positioning and location intelligence were the first popular opportunistic applications of Wi-Fi’s RF cloud. Today, researchers are investigating opportunistic applications of Wi-Fi signals for gesture and motion detection as well as authentication and security. This paper provides a holistic overview of the evolution of Wi-Fi technology and its applications as the authors experienced it in the last few decades.

ParEst: joint estimation of the OFDM channel state information in MIMO systems

OFDM channel state information (CSI) is needed for determining key parameters in MIMO transmissions. In this paper, a novel CSI estimation method, ParEst, is proposed, which estimates the CSI from multiple transmitting antennas simultaneously. ParEst is based on a recent discovery that the CSI can be approximated very well by the linear combination of complex-based sinusoids on constant frequencies. ParEst finds the CSI of all antennas jointly by solving an optimization problem and achieves higher accuracy than existing heuristic methods. As the base sinusoids are on constant frequencies, ParEst pre-computes most key steps and reduces the run-time computation complexity to just a modest number of vector dot products equivalent to a few FFT calculations. ParEst can be applied to MIMO links in networks such as LTE, 5G, or Wi-Fi.