Multiple-input Multiple-output Wireless Systems Research Articles

Meta‐heuristic optimization techniques for scheduling in multiple‐input multiple‐output multiple‐access channel system

SummaryIn a highly dense multiple‐input multiple‐output (MIMO) communication system, proper resource allocation is exceedingly challenging. The simultaneous selection of antennas at the base‐station (BS) and scheduling of users in an uplink multiple access channel (MAC) system add up to the signal processing load in the MIMO wireless system. The method chosen for combining the user scheduling and antenna selection must have a very low computational complexity. However, the exhaustive search algorithm (ESA), which achieves the best sum‐rate capacity in a MIMO‐MAC system, has a very high level of complexity. In this paper, we use a metaheuristic‐based optimization algorithms to optimize the sum‐rate capacity in a MAC system with significantly less computational complexity. First, we use the beluga whale optimization (BWO) metaheuristic method to solve the optimization problem. The BWO is a swarm‐based algorithm that draws inspiration from beluga whale behavior. An improved BWO (iBWO) is also presented and is utilized for the same optimization challenge. The proposed iBWO scheme improves the search capability of the algorithm and thereby ensures better exploration and exploitation capabilities of the beluga whales. We compare the performance of these algorithms with a standard differential evolution (DE) algorithm. The simulation results demonstrate that the proposed iBWO is a very competitive meta‐heuristic algorithm for solving optimization problems. The proposed iBWO algorithm achieves near optimal throughput in a MIMO‐MAC system. Also, the computational complexity related to the suggested optimization technique in a MIMO‐MAC system is found to be very less compared with the complexity related to ESA.

Performance Analysis of SNR in MIMO OFDM Downlink System

The goal of future wireless communications systems is to provide a wide variety of high quality high-rate services with minimum requirements on spectrum, power consumption and hardware complexity. Toward this end, proper system structures as well as robust system designs are required to meet the challenges in wireless transmissions, such as multipath fading, limited spectrum resource, and interference. Recent research results have unveiled the multiple-input multiple-output (MIMO) system as a potential candidate to play a key role in future wireless. A MIMO wireless system is commonly deployed by using multiple transmit and receive antennas. Early work on multi-antenna systems involves the use of antenna arrays at the receiver to provide spatial diversity against the random destructive effect of fading. There is a recent rich literature on employing multiple antennas at the transmitter and achieving diversity through space-time coding when there is no channel state information at the transmitter (CSIT), or through transmit beam forming when there is perfect CSIT.

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.

Channel Estimation for IRS-Assisted Millimeter-Wave MIMO Systems: Sparsity-Inspired Approaches

Due to their ability to create favorable line-of-sight (LoS) propagation environments, intelligent reflecting surfaces (IRSs) are regarded as promising enablers for future millimeter-wave (mm-wave) wireless communication. In this paper, we investigate channel estimation for IRS-assisted mm-wave multiple-input multiple-output (MIMO) wireless systems. By leveraging the sparsity of mm-wave channels in the angular domain, we formulate the channel estimation problem as an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> -norm regularized optimization problem with fixed-rank constraints. To tackle the non-convexity of the formulated problem, an efficient algorithm is proposed by capitalizing on alternating minimization and manifold optimization (MO), which yields a locally optimal solution. To further reduce the computational complexity of the estimation algorithm, we propose a compressive sensing- (CS-) based channel estimation approach. In particular, a three-stage estimation protocol is put forward where the subproblem in each stage can be solved via low-complexity CS methods. Furthermore, based on the acquired channel state information (CSI) of the cascaded channel, we design a passive beamforming algorithm for maximization of the spectral efficiency. Simulation results reveal that the proposed MO-based estimation (MO-EST) and beamforming algorithms significantly outperform two benchmark schemes while the CS-based estimation (CS-EST) algorithm strikes a balance between performance and complexity.

Design and Analysis on Decoupling Techniques for MIMO Wireless Systems in 5G Applications

Multiple-input multiple-output (MIMO) wireless system is a hot research topic in 5th generation mobile communication technology (5G), which can increase the channel capacity of the antenna system to meet new communication demands without changing the bandwidth and transmission power. However, adding the number of antenna elements in a limited space size can lead to mutual coupling effects and impair the communication quality. Therefore, it is significant to design a compact MIMO wireless system using decoupling techniques. Several studies on the reduction of mutual coupling effects have been proposed. However, a concrete overview of the features and resemblances of these decoupling techniques is lacking. In this review, we provide a brief description of the research background on the mutual coupling effect of MIMO. Then, various decoupling techniques worthy of reference are classified and outlined. We further summarize the additional impacts due to the existence of different decoupling structures, and the possible usability and defects of these techniques are revealed clearly in this paper. Finally, a future outlook on the development direction of decoupling techniques for MIMO wireless systems is also concluded and discussed.

Gradient Relative Permittivity Superstrate for Decoupling of Two Closely Located Dual-Polarized Slot Antennas

A simple decoupling method between two closely located dual-polarized slot antennas is proposed in this communication. Based on substrate integrated waveguide (SIW), the dual-polarized antenna is realized using cross-shaped slot and U-shaped feed line, and two identical elements are closely located in edge-to-edge space of only <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.031\lambda _{0}$ </tex-math></inline-formula> to form the multiple-input–multiple-output (MIMO) array, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda _{0}$ </tex-math></inline-formula> is the free-space wavelength at the center operating frequency. Wideband characteristics, high dual-polarized isolation, and low envelope correlation coefficient (ECC) are realized by introducing a superstrate with gradient relative permittivity (GRP) above the array. The GRP is obtained using drilling hole arrays on low-cost FR-4 materials. To validate the proposed design, the antenna array is fabricated and measured. The measured result shows that 13 and 16 dB isolation enhancements are provided for two orthogonally polarized fields, simultaneously. Moreover, the measured operating bandwidth is from 8 to 10.35 GHz (about 25.6%, the isolation is more than 20 dB), and the ECC between two antennas is less than −52 dB for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$E_{1}$ </tex-math></inline-formula> -pol and −62.4 dB for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$E_{2}$ </tex-math></inline-formula> -pol over entire operating band. The proposed method has the potential to be used in MIMO wireless systems.

Ultra-High Mobility Analysis of MIMO Wireless System in Tunnel Scenarios

This letter studies the effect of ultra-high mobility on the performance of multiple-input multiple-output (MIMO) wireless communication system in tunnel scenarios. It is found that the Doppler frequency shift generated by the ultra-high mobility reduces the correlation coefficient. Importantly, it is observed that there exists a key inflection point distance in the ultra-high speed tunnel scene. When this distance is exceeded, the channel correlation of MIMO can be significantly reduced. Moreover, it is perceived that the inflection point distance is relatively stable and is less affected by the communication frequency. On this basis, we propose a high-quality communication area with low MIMO channel correlation. For the ultra-high speed of 720km/h, the inflection distance is about 95m, and the reduction of MIMO channel correlation at 3.5GHz and 28GHz can reach up to 52.7% and 41.2%, respectively. The findings are extremely useful for the applications of the mobile MIMO communication system in tunnel and railway scenarios.

Magnetic Field Leakage Cancellation in Multiple-Input Multiple-Output Wireless Power Transfer Systems

This letter presents a method to cancel magnetic field leakage while maintaining high power transfer efficiency (PTE) in multiple-input multiple-output wireless power transfer systems. To achieve low leakage and high PTE, the problem of PTE maximization under the cancellation condition of the magnetic field leakage is solved, which is a maximization problem of affinely constrained Rayleigh quotients. Subsequently, the optimal amplitudes and phases of the input voltages at the transmitter array and the optimal load impedances at the receivers are shown. This method can further reduce the magnetic field leakage by up to 31 dB compared with the PTE maximization method, while having a PTE drop within 5.5%.

Hardware-Aware Beamspace Precoding for All-Digital mmWave Massive MU-MIMO

Massive multi-user multiple-input multiple-output (MU-MIMO) wireless systems operating at millimeter-wave (mmWave) frequencies enable simultaneous wideband data transmission to a large number of users. In order to reduce the complexity of MU precoding in all-digital basestation architectures, we propose a two-stage precoding architecture that first performs precoding using a sparse matrix in the beamspace domain, followed by an inverse fast Fourier transform that converts the result to the antenna domain. The sparse precoding matrix requires a small number of multipliers and enables regular hardware architectures, which allows the design of hardware-efficient all-digital precoders. Simulation results demonstrate that our methods approach the error-rate of conventional Wiener filter precoding with more than $2\times $ reduced complexity.

Computationally Efficient Data Detection in Massive MIMO Wireless Systems via Semi-Iterative Method

Practical data detectors must achieve low error-rate at low-complexity for massive multiple-input multiple-output (MIMO) wireless systems. Since near-optimal minimum mean square error (MMSE) detection exhibits high computational complexity for such wireless systems, various iterative methods as well as their enhanced variants have been proposed. The efficiency of iterative approaches, however, is not satisfying due to slow convergence rate and reduced accuracy. This paper proposes a novel semi-iterative data detection algorithm for massive MIMO systems that simultaneously achieves a large improvement in convergence and accuracy with respect to the corresponding iterative method. We provide a general three-term recurrence expression for semi-iterative detection and incorporate it with Richardson method as a show case. To further improve the convergence rate of the proposed technique, a new trace-diagonal based low-complexity initial method is developed. A sufficient condition for convergence of the proposed method is also provided. We analyze the associated complexity of semi-iterative detector, and provide numerical results which demonstrate that the proposed detector is superior to recently introduced iterative detectors in terms of both the error-rate performance and computational complexity.

Robust conjugate-gradient based LAS detector for massive MIMO systems

ABSTRACT Low-complexity neighbourhood search algorithms for a massive multiple-input multiple-output (MIMO) wireless system has fascinated recent research attention. It performs iterative searches in a constrained maximum-likelihood (ML) space for the solution vector. However, they drive an inversion of large-dimensional matrices with an enormous amount of computations resulting in them becoming practically infeasible. It motivates for development of low-complexity matrix-inversion-free data detection algorithm that is proficient in achieving near-optimal performance in an unconstrained ML space. Using these concepts and the conjugate gradient (CG) approach, this article proposes the computationally efficient CG-based likelihood ascent search (CGLAS) detector. A CGLAS detection algorithm is proposed to achieve a fast update vector within unconstrained ML space in conjugate descent direction with few iterations. Simulation results demonstrate that this robust detection algorithm exerts more influence rather than other recent state-of-the-art detection algorithms that achieve much better performance for massive MIMO systems with superior running time efficiency.

Noncentral complex Wishart matrices: Moments and correlation of minors

Complex Wishart matrices are a class of random matrices with numerous emerging applications. In particular, the statistical characterization of such class of random matrices is essential for solving problems in various fields, including statistics, finance, physics and engineering. This paper establishes a new way to solve such problems based on the statistical moments and correlation of the minors. The first two minors’ moments and correlation for noncentral complex Wishart matrices are derived as a function of size and degrees of freedom, as well as of covariance and noncentrality matrices. As a case study, the findings are applied to the statistical characterization of the capacity of wireless multiple-input–multiple-output systems.

Energy-Efficient Hybrid Symbol-Level Precoding for Large-Scale mmWave Multiuser MIMO Systems

We address the symbol-level precoding design problem for the downlink of a multiuser millimeter wave (mmWave) multiple-input multiple-output (MIMO) wireless system where the transmitter is equipped with a large-scale antenna array. The high cost and power consumption associated with the massive use of radio frequency (RF) chains prohibit fully-digital implementation of the precoder, and therefore, we consider a hybrid analog-digital architecture where a small-sized baseband precoder is followed by two successive networks of analog on-off switches and variable phase shifters according to a fully-connected structure. We jointly optimize the digital baseband precoder and the states of the switching network on a symbol-level basis, i.e., by exploiting both the channel state information (CSI) and the instantaneous data symbols, whereas the phase-shifting network is designed only based on the CSI due to practical considerations. Our approach to this joint optimization is to minimize the Euclidean distance between the optimal fully-digital and the hybrid symbol-level precoders. Remarkably, the use of a switching network allows for power-savings in the analog precoder by switching some of the phase shifters off according to the instantaneously optimized states of the switches. Our numerical results indicate that, on average, up to 50 percent of the phase shifters can be switched off. We provide an analysis of energy efficiency by adopting appropriate power dissipation models for the analog precoder, where it is shown that the energy efficiency of precoding can substantially be improved thanks to the phase shifter selection approach, compared to the fully-digital and the state-of-the-art hybrid symbol-level schemes.

Hybrid beamforming in Multiuser mmWave Massive MIMO System

Conventional MIMO systems typically use full digital processing for optimal performance while it requires an independent radio frequency (RF) chain for each antenna, which is not feasible for large-scale antenna arrays due to the high cost, high-power consumption and high complexity of RF chain components in high frequencies. Fortunately, in recent years, the Hybrid beamforming has been proposed as an efficient and auspicious technique for the practical implementation of millimeter-Wave (mmWave) multiple-input multiple-output (MIMO) wireless systems. In this paper we propose a novel HBF (Hybrid beamforming) algorithm and simulate the sum rate of the proposed approach, then compare it with other algorithms in the sum rates. Specifically, the HBF algorithm as well as the maximizing minimum phase difference algorithm are based on the MMSE (Minimum Mean Square Error). For the full-digital beamforming and the beam steering, the ZF (zero forcing) criterion is employed. Simulations demonstrate that the performance of the proposed algorithm is similar to the full digital algorithm, and its robustness is confirmed by comparisons with other existing algorithms under the same channel model.

Mismatched Data Detection in Massive MU-MIMO

We investigate mismatched data detection for massive multi-user (MU) multiple-input multiple-output (MIMO) wireless systems in which the prior distribution of the transmit signal used in the data detector differs from the true prior. In order to minimize the performance loss caused by the prior mismatch, we include a tuning stage into the recently proposed large-MIMO approximate message passing (LAMA) algorithm, which enables the development of data detectors with optimal as well as sub-optimal parameter tuning. We show that carefully-selected priors enable the design of simpler and computationally more efficient data detection algorithms compared to LAMA that uses the optimal prior, while achieving near-optimal error-rate performance. In particular, we demonstrate that a hardware-friendly approximation of the exact prior enables the design of low-complexity data detectors that achieve near individually-optimal performance. Furthermore, for Gaussian priors and uniform priors within a hypercube covering the quadrature amplitude modulation (QAM) constellation, our performance analysis recovers classical and recent results on linear and non-linear massive MU-MIMO data detection, respectively.

A Review on MIMO Wireless Signals over Fibre for Next Generation Fibre Wireless (FiWi) Broadband Networks

Next-generation access/mobile networks have set high standards in terms of providing wireless services at high data rates in order to keep up with the vast demands for other mobility and multiple services. Wireless-optical broadband access network (WOBAN) technology, also known as fibre-wireless (FiWi), has uncovered incredible opportunities for the future of next-generation networks because it gets the best of both domains: huge bandwidth provided by the optical fibre and high ubiquity of the wireless domain. The objective of FiWi networks is to integrate the high data rate and long reach provided by optical networks and the ubiquity and mobility of wireless networks, with the target to decrease their expense and complexity. Multiple-input–multiple-output (MIMO) is an inevitable technique for most of the new mobile/wireless networks that are driven by the huge data rates required by today’s users. Consequently, to construct any FiWi system for next-generation (NG) access/broadband networks, an MIMO technique has to be considered. This article presents a comprehensive, contemporary review of the latest subsystems, architectures and integrated technologies of MIMO wireless signals backhauling using optical fibre or fibre access networks, such as passive optical networks (PONs). An overview for FiWi, PONs and MIMO wireless systems is provided. In addition, advanced techniques of accommodating the MIMO wireless signals over optical fibre are explained and compared. Different types of wireless MIMO signals over fibre, such as 5G, WiFi and related transport technologies, are reviewed. Moreover, future research trends are also discussed.

Accurate Variable-Order Approximations to the Sum of α – μ Variates With Application to MIMO Systems

Sum of fading signals arises in several communication applications such as maximal-ratio combining (MRC) used in multiple antenna systems and eliminating the inter-symbol interference in high speed wireless networks. The exact formulation of the statistics of the sum is known to be very complicated. This article presents two simple closed-form approximations to the probability density function (PDF) and cumulative distribution function (CDF) of the sum of $\alpha -\mu $ variates, resembling an urban mobile communication environment. By direct integration, it is demonstrated that the PDF of the sum of $\alpha -\mu $ random variables can be approximated by a weighted sum of few identical $\alpha -\mu $ distributions including order one coefficients. The proposed approximations are of variable-order to achieve the desired accuracy and also have specific parameters using which, multiple-input multiple-output (MIMO) diversity systems can be explicitly analyzed as simply as a single-input single-output (SISO) system. In addition, a MIMO wireless system utilizing orthogonal space-time block coding technique (OSTBC-MIMO) in an $\alpha -\mu $ frequency nonselective fading environment is analyzed, and expressions for outage probability (OP) and bit error rate (BER) of digital binary modulations as well as the capacity are obtained. Moreover, the asymptotic OP and BER expressions are derived from the declared approximate expressions. The asymptotic OP and BER performances clearly indicate a diversity order equal to the product of the $\frac {\alpha }{2}$ parameter, the $\mu $ parameter, the number of transmit antennas and the number of receive antennas. Analytical results are verified by simulation.

Minimum Error Pursuit Algorithm for Symbol Detection in MBM Massive-MIMO

Media-based modulation (MBM) with massive multiple-input multiple-output (mMIMO) wireless systems is a viable solution to realize the ever-increasing demand for high-speed data and extensive connectivity in beyond 5G and 6G wireless communications. MBM-mMIMO utilizes less transmit power and radio resources measured against mMIMO to yield high spectral efficiency and high data rate. However, symbol detection in the uplink of MBM-mMIMO is challenging due to the sparse nature of the received signal, and the cumulative effect of inter-user interference and noise. In this letter, support recovery error constraint-based low complexity sequential symbol detection technique is proposed for uplink MBM-mMIMO system. The proposed MBM-mMIMO detection technique exploits the upper bound on support recovery error and iteratively minimizes the residual error associated with the estimated transmit vector. A reduced message space is also introduced to further enrich the exploration capability of the proposed technique. Simulation results reveal the viability of proposed techniques over several state-of-the-art MBM-mMIMO detection techniques as BER performance and computational complexity are concerned.

Low-Complexity Near-Optimal Iterative Signal Detection Based on MSD-CG Method for Uplink Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) wireless system is increasingly becoming a vital factor in fifth-generation (5G) communication systems. It is attracting considerable interest due to improve range, spectral efficiency, and coverage as compared to the conventional MIMO systems. In massive MIMO systems, the maximum likelihood detector achieve the optimum performance but it has exponential complexity for realistic antenna configurations systems, Moreover, Linear detectors commonly suffer from a matrix inversion which is not hardware-friendly. There is an increase in the computational complexity associated with the unique benefits of the massive MIMO systems. The system might be classified as an ill-conditioned problem and hence, the signal cannot be detected. To reduce the data detection complexity, we investigate a linear detector based on the multiple search direction conjugate gradient (MSD-CG) in the massive MIMO uplink systems. Several theoretical iterative techniques that can be used to balance complexity and performance for massive MIMO detection have been proposed in the literature. These methods whose convergence rate for common applications is slow where there is a decrease in the base station to user antenna ratio. In this paper, the performance of the CG method has been advanced by a projection method that necessitates a search direction in each sub-domain instead of making all search directions conjugate to each other. In this regard, our results show that the proposed algorithm with realistic antenna configurations is superior to the existing methods in terms of computational complexity for large-scale MIMO systems.