Multiple-input Multiple-output Algorithms Research Articles

Equalization system of low differential mode delay few-mode fibers based on the neural network MIMO algorithm.

In recent years, with the development of information networks, higher requirements for transmission capacity have been recommended. Yet, at the same time, the capacity of single-mode fiber is rapidly approaching the theoretical limit. The multidimensional multiplexing technique is an effective way to solve this problem. Since the high differential mode delay (DMD) of transmission fiber increases the complexity of demultiplexing in equalization algorithms, we use an intelligent design method to optimize the trench-assisted gradient refractive index structure in this paper. The maximum DMD of the optimized optical fiber structure is 19.6 ps/km. A least mean squares-feedforward neural network constant modulus algorithm (LMS-FNNCMA) is also designed by using the theory of the least mean squares (LMS), constant modulus algorithm (CMA), and the multiple input multiple output (MIMO) neural networks. In order to verify the accuracy of the algorithm, a polarization division multiplexing-wavelength division multiplexing-mode division multiplexing (PDM-WDM-MDM) optical transmission system is constructed through simulation. The algorithm successfully realizes the de-crosstalk over a transmission distance of 1200 km at a rate of 1.2 Tbps under simulation conditions.

A Novel MIMO Control for Interleaved Buck Converters in EV DC Fast Charging Applications

This brief proposes a new multiple input multiple output (MIMO) control for off-board electric vehicle (EV) dc fast chargers. The proposed feedback matrix design avoids multiple tuning of controllers in multiple and interconnected loops while improving the performance of interleaved dc buck converters over classical PI/PID controls. The innovative features of the presented strategy are the reference current monotonic tracking from any initial state of charge with an arbitrarily fast settling time and the fast compensation of both load variations and imbalances among the legs. Numerical results validate the performance improvements of the proposed discrete-time MIMO algorithm for interleaved buck converters over classical PI/PID controls. Full-scale hardware-in-the-loop (HIL) and scaled-down prototype experimental results prove the feasibility and effectiveness of the proposal.

Performance Analysis of MIMO Techniques for a Pyramid Receiver in an Indoor MIMO-VLC System

In an indoor multiple-input multiple-output (MIMO) visible light communication (VLC) system, line of sight (LoS) channel links are present between a light-emitting diode (LED) based transmitter and a photodetector (PD) based receiver. The PDs in the receiver are closely packed resulting in a high channel correlation. To overcome channel correlation and improve the performance of the MIMO-VLC system, angle diversity receivers (ADRs) are commonly employed. The channel matrix entries depend on the normal vectors of the PDs, which in turn depend on the elevation angle (EA) of the PDs. Thus, by having normal vectors pointing in different directions, the channel correlation can be considerably reduced. This paper considers a special type of ADR called pyramid receiver (PR) and employs a 4x4 MIMO-VLC system. In this paper, different MIMO algorithms such as repetition coding (RC) and spatial multiplexing (SMP) are considered to exhibit and compare the bit-error-rate (BER) performance of the fixed and variable EA MIMO-VLC systems. The results show that an SMP-employed MIMO-VLC system outperforms the RC-employed MIMO-VLC system. SMP results in an spatial multiplexing gain that varies linearly with the number of LEDs whereas RC does not yield any spatial multiplexing gain. To attain the same spectral efficiency i.e. 4 bit/s/Hz, a larger signal constellation size is required for RC employed MIMO-VLC system to achieve the same BER as of an SMP employed MIMO-VLC system. Similarly, the BER performance of variable EA MIMO-VLC systems is better as compared to fixed EA MIMO-VLC systems.

Array Gain Analyses of Single User MIMO in 5G NR PDSCH

In the last decade, Multiple-Input Multiple-Output (MIMO) algorithms have been developed for mobile communications networks to increase spectrum efficiency and reduce the transmitted power, which are also two of the main Key Performance Indicators of Fifth Generation New Radio (5G NR). Therefore, various MIMO algorithm are being researched for their suitability in 5G NR specifications. The objective of this study is to examine the performance gains achieved through the use of multiple transmit antennas and multiple receive antennas in 5G NR Physical Shared Downlink Channel (PDSCH). The study examines separately the array gains of Single-Input Multiple Output (SIMO) and Multiple-Input Single Output (MISO) then combines the transmitter and the receiver diversities in a MIMO system for 5G PDSCH. The array gains are achieved through precoding and combining vectors obtained by the use of Singular Value Decomposition (SVD). The results show that theoretical array gains are achieved in simulation environment.

Performance Comparison of Repetition Coding MIMO Optical Wireless Communications with Distinct Light Beams.

In current optical wireless communications (OWC) oriented research works, the various multiple input multiple output (MIMO) techniques are introduced and utilized to enhance the coverage performance. Objectively, this Lambertian light beam based MIMO research paradigm neglects the light beam diversity and the potential performance gains. In this work, the distinct non-Lambertian light beams of commercially available light emitting diodes (LEDs) were adopted to configure MIMO OWC links. Specifically, the homogenous and heterogeneous non-Lambertian MIMO configurations were constituted in typical indoor scenarios. Moreover, applying the repetition coding (RC) MIMO algorithm with low complexity, a spatial coverage performance comparison was made between the several above mentioned non-Lambertian configurations and the well-discussed Lambertian MIMO configuration. Numerical results illustrate that the homogeneous NSPW light beam configuration could provide a more than 30 dB average signal to noise ratio (SNR), while the achievable average SNR of the heterogeneous light beam configuration was up to 28.77 dB. On the other side, the counterpart of the Lambertian configuration achieved just about 27.00 dB. Objectively, this work paves the fundamental and essential way for the further design and optimization of MIMO OWC in this novel light beam dimension.

Joint equalization scheme of ultra-fast RSOP and large PMD compensation in presence of residual chromatic dispersion.

Polarization demultiplexing is generally carried out by a multiple-input multiple-output (MIMO) based algorithm in polarization division multiplexing (PDM) coherent systems. However, in some extreme environments, the MIMO algorithm becomes inapplicable due to the ultra-fast rotation of the state of polarization (RSOP) and large polarization mode dispersion (PMD). In addition, the residual chromatic dispersion (RCD) is always present because of the mismatch of the compensated chromatic dispersion and real value induced in the optical fiber channel. According to the literature, the Kalman filter-based polarization demultiplexing algorithms possess very weak RCD tolerance. Faced with this dilemma, in this paper, a new Kalman filter structure is proposed, which can jointly compensate ultra-fast RSOP, large PMD and RCD. This Kalman filter structure enables the equalization of the RSOP in the time domain and compensation for RCD and PMD in the frequency domain. We verified the performance of the proposed Kalman scheme in the 28 Gbaud PDM-QPSK/16 QAM coherent system, with a comparison to constant modulus algorithm/multiple modulus algorithm (CMA/MMA). The simulation results confirm that, compared with CMA/MMA, the proposed Kalman scheme can provide a significant performance enhancement to cope with ultra-fast RSOP (up to 3 Mrad/s) and large PMD (more than 200 ps) with a large tolerance to RCD (over the range of ± 820 ps/nm in PDM-QPSK and ± 500 ps/nm in PDM-16 QAM).

A Correlation Theory of Antenna Directivity With Applications to Superdirective Arrays

We develop a general approach to antenna directivity by combining the infinitesimal dipole model (IDM) and the cross-correlation Green's function (CGF) in a new formulation. The theory is deployed for the analysis and synthesis of antenna systems via the proposed IDM-CGF method after integration with global optimization algorithms. The IDM-CGF theory opens the door for hitherto unexplored connections between applications involving antenna gain engineering on one side, and multiple-input–multiple-output (MIMO) and diversity methods on the other, helping to devise new techniques for applications like massive MIMO and millimeter-wave beamforming algorithms, wireless power transfer, in-package antennas, and full three-dimensional isotropicity.

MIMO Transceiver based on Software Defined Radio

Amplitude-phase consistency of multiple input multiple output (MIMO) transceivers has a significant impact on the performance of digital beamforming algorithms and MIMO communication algorithms. Based on the concept of software defined radio (SDR), architecture of a MIMO transceiver with a amplitude-phase consistency calibration scheme was designed. By looping the output signals into input channels, amplitude-phase consistency of the output or input channels can be measured, thus the channel calibration was performed in the digital signal processing. Based on the designed architecture, a MIMO transceiver prototype was implemented by adopting SDR radio frequency (RF) agile transceivers and a digital signal processing system on chip (SOC), with software running on it also implemented. Experiments show that the MIMO transceiver achieves high amplitude-phase consistency performance after calibration, and has the characteristics of high integration, miniaturization and high flexibility.

Multi‐taper spectrum‐based estimator for cognitive radio using multiple antennas and STBC techniques

An effective approach for the design of spectrum estimation (SE) in cognitive radio systems using multi-taper method (MTM) and spatiotemporal features is presented in this study, whereas the MTM balances the bias-variance dilemma, the multiple-input–multiple-output (MIMO) and space–time block code (STBC) are customarily aimed to defeat the adverse channel effects and enhance the system capacity and performance. The singular value decomposition is exploited to determine the dominant eigenchannels in MIMO and STBC setups. The maximum-ratio combining, on the other hand, is adopted to produce higher signal-to-noise ratios usually intended for high data rates and reliability levels. The statistical analysis and modelling of the performance metrics associated with the SE based on MTM-STBC and MIMO are approached using the quadratic form approximation. Simulation exercises are employed to compare this different SE, which will be called multitaper spectrum estimation (MTSE), against other typical methods such as the periodogram without tapering options. The results exhibit performance gains due to the merger of MTSE and STBC technologies over MIMO and periodogram SE (PSE) algorithms. Further computational analysis shows that the MTSE–STBC has no extra burdens compared with its PSE counterpart.

Feasibility Demonstration of a Mode-Division Multiplexed MIMO-Enabled Radio-Over-Fiber Distributed Antenna System

In this paper the feasibility of mode-division multiplexing (MDM) for implementing multiple-input multiple-output (MIMO)radio-over-fiber (RoF)distributed antenna systems (DAS) is experimentally demonstrated, where the MIMO algorithm is able to reconstruct the data signals by overcoming distortion and cross-talk in both the free-space RF and optical fiber channels. This is achieved through RF characterization of an MDM RoF link, which is experimentally demonstrated to be capable of supporting at least $4 \times 4$ MIMO with 6 GHz channels over long lengths of MMF (2 km compared to $\sim$ 300 m typically found in MMF-based RoF DASs) and under tight fiber bending conditions (bend radius as low as 7.6 mm), which are commonly encountered in in-building fiber installations. First, experimental RF measurements are performed over a 2 km section of OM2 fiber, mode-multiplexed using a spatial light modulator (SLM) based MUX/DEMUX system, and it is shown to offer an RF condition number of <14 dB for up to $4 \times 4$ MIMO with 6 GHz channels, sufficient to enable good performance for most modern wireless protocols. Next, the effect of fiber curvature on RF performance is experimentally analysed using a 10 m section of OM3 fiber. It is seen that with a bend radius as low as 7.2 mm, a condition number of ${\sim}10$ dB can be achieved for up to a $6 \times 6$ MIMO system with 6 GHz channels. Although an SLM-based MUX/DEMUX is used here, condition number is not dependent on the exact mode-launching system used provided that orthogonal combinations of modes are excited, which is true of most MDM systems. It is therefore concluded that the RF characterization presented here demonstrates by proof-of-principle the feasibility of graded-index) MMF to support at least $4 \times 4$ MIMO with broadband channels via MDM over lengths up to 2 km and with fiber bend radii as low as 7.2 mm.

Characterization of Implemented Algorithm for MIMO Spatial Multiplexing in Reverberation Chamber

Previously, the throughput for a single-input multiple-output (SIMO) system was successfully tested in a reverberation chamber (RC), and the results were in good agreement with a model based on the ideal threshold receiver. In the present communication, we measure the throughput of a 2 × 2 open loop multiple-input multiple-output (MIMO) system with full spatial multiplexing (i.e., two data streams), and we compare the results with an extended throughput model taking the spatial multiplexing into account. The measured throughput is found to be in agreement with the simulated one of a simple zero-forcing (ZF) receiver. The throughput degradations due to correlation and power imbalance (caused by different embedded radiation efficiencies of antennas) are studied and referred to as a throughput multiplexing efficiency. These can, to a large extent, be explained by the ZF algorithm. The results show clearly that the rich isotropic multipath (RIMP) environment generated by an RC can be used to study how effective different MIMO algorithms are when there is correlation and efficiency imbalance between the antenna elements.

The Optimal Traffic Information Process System by Using MIMO Algorithm

This paper presented dynamic vehicle information for wireless communication and safe systems by integrating radio frequency identification (RFID) technology. The systems provied different particular and advantage between RFID and other recognition technology. The car black box is the best choice and innovates specific application. It is not only the system can guard car but differentiate the responsibility for car accident event. Furthermore, the car black box is integrated the RFID, general packet radio service (GPRS), Bluetooth, personal digital assistant (PDA) and global positioning system (GPS). The proposed system has been trending the merger goal of digitization. Therefore, it is created a tremendous amount of commercial opportunity. The car black box is also combined multiple-user with real-time navigation information system. The system is integrated the independent real-time traffic information database and Geographical Information System (GIS) through data fusion method. We adopted a traffic information system offering advanced personalized route planning, including added services for traffic jam alerting by means of Short Message Service (SMS) in Global System for Mobile (GSM) communication network. It is shown small and low-cost GSM modules for data process by using the Multiple Input Multiple Output (MIMO), Ant colony optimization (ACO) algorithm, which developed a real-time software solution to help users and evaluation of user preferences for car traffic information system.

Robust train-to-wayside video communications in tunnels using H.264 error-resilient video encoding combined with multiple antenna systems

With the development of driverless metro systems, the demand for high data rate train-to-wayside wireless transmission is increasing drastically in order to satisfy operational needs such as maintenance, video surveillance of the inside of the trains and passenger information. Thus, the association of new transmission techniques such as new video coding techniques, multi antennas at transmission and reception sides and recent precoders provides technically and economically efficient solutions to improve existing systems. This paper presents and evaluates two novel strategies to enhance train-to-wayside wireless video transmissions in tunnels using realistic channel models obtained with ray tracing previously experimentally validated. Multiple Description Coding (MDC) or Region Of Interest (ROI) coding, using the new Flexible Macroblock Ordering (FMO) technique, is combined with appropriate Multiple Input Multiple Output (MIMO) schemes, namely, spatial multiplexing (SM), orthogonal spatial multiplexing (OSM) and precoded orthogonal spatial multiplexing (P-OSM) depending if full channel state information at transmitter side (CSI-T) is available or not. For each strategy, both video encoding process and MIMO algorithm are combined in an efficient way to provide the best video quality at the receiver with no increase of the number of radio access points along the infrastructure.

Energy Consumption Analysis and Algorithms Based on Energy Efficiency for Cooperative Networks

In this paper, a unified cooperative network model is set up, the selective decoding forward and multiple-input multiple-output algorithms are analyzed, and the factors that affect energy consumption are investigated, proposing a cooperative algorithm based on energy efficiency to relay data. According to the relative position of relay nodes to the direct transmission path, cooperative algorithms based on energy efficiency can effectively decide the relaying decision. Without considering the energy consumption of the circuit, our research results indicated that the energy consumption of the selective decoding forward system was lower than that of the single-input single-output system for a fixed ABER value. When the number of transmitting nodes is fixed, an optimal number of receiving nodes is required for the lowest energy consumption. The energy consumption of a multiple-input multiple-output system is higher than that of traditional single-input single-output for a short distance. The energy consumption can only be saved unless the distance is longer than the critical value. The proposed cooperative algorithms based on energy efficiency can save a lot of energy compared to the direct transmission method.

MIMO Detection Techniques Based on Low Complexity Adaptive QR-Decomposition with M-Algorithm for 3GPP LTE Systems

In this paper, two novel multiple-input multiple-output (MIMO) detection algorithms, adaptive parallel QRDM (APQRDM) and adaptive iterative QRDM (AIQRDM) which are able to achieve the similar detection throughput as conventional QRDM while reducing the computational complexity, are introduced, and the system performances are evaluated on the platform of 3GPP LTE downlink. In both 2 × 2 and 4 × 4 MIMO, APQRDM and AIQRDM algorithms can achieve almost same packet error rate performance as those of conventional QRDM algorithm, while the computational complexity is significantly reduced. Also, the receiver employing APQRDM and AIQRDM detection algorithms shows the almost same throughput as the case of conventional MIMO detection algorithms. Furthermore, practical channel estimation techniques are employed, and the system performances are thoroughly analyzed and discussed.

A load-balanced parallel sorting algorithm for shared-nothing architectures

With the popularity of parallel database machines based on the shared-nothing architecture, it has become important to find external sorting algorithms which lead to a load-balanced computation, i.e., balanced execution, communication and output. If during the course of the sorting algorithm each processor is equally loaded, parallelism is fully exploited. Similarly, balanced communication will not congest the network traffic. Since sorting can be used to support a number of other relational operations (joins, duplicate elimination, building indexes etc.) data skew produced by sorting can further lead to execution skew at later stages of these operations. In this paper we present a load-balanced parallel sorting algorithm for shared-nothing architectures. It is a multiple-input multiple-output algorithm with four stages, based on a generalization of Batcher's odd-even merge. At each stage then keys are evenly distributed among thep processors (i.e., there is no final sequential merge phase) and the distribution of keys between stages ensures against network congestion. There is no assumption made on the key distribution and the algorithm performs equally well in the presence of duplicate keys. Hence our approach always guarantees its performance, as long asn is greater thanp 3, which is the case of interest for sorting large relations. In addition, processors can be added incrementally.