scholarly journals Signal Detection in Spatially Multiplexed MIMO Systems

2021 ◽  
Vol 9 (VI) ◽  
pp. 5002-5005
Author(s):  
Mohan Reddy
Keyword(s):  
Signal Detection ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Spatial Multiplexing ◽  
Multiple Receivers ◽  
Rate Versus ◽  
Multiple Input ◽  
The Matrix ◽  
Input Multiple Output

The transmission of several signals and reception of those signals, it requires the implementation of multiple transmitters at the transmitter side and the multiple receivers at the receiver side. This type of system is called multiple input multiple output (M.I.M.O) system. The M.I.M.O systems will result in obtaining the better use of the available spectrum for transmissions of the different signals in the same spectrum and this makes the M.I.M.O systems most dependable for the wireless communications. But the presence of several signals in the same bandwidth of spatial multiplexing matrix in M.I.M.O systems makes it difficult for the signal to get detected at the receiver end. There are plenty of techniques introduced to avoid the difficulty in sensing the signal at receiver in M.I.M.O systems. In this paper we will be discussing about the signal detection technique called minimum mean square error technique (MMSE) which uses the inversion of the matrix to retrieve the signal and the iteration-based method that is an improvised technique than MMSE technique where the matrix inversion step is avoided and provides better results. The results are obtained by plotting the bit error rate versus the signal to nose ratio using MATLAB

scholarly journals Computationally Efficient Channel Estimation in 5G Massive Multiple-Input Multiple-output Systems

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 382 ◽  
Author(s):  
Imran Khan ◽  
Mohammad Zafar ◽  
Majid Ashraf ◽  
Sunghwan Kim
Keyword(s):  
Channel Estimation ◽  
Signal Detection ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Matrix Inversion ◽  
Computationally Efficient ◽  
Estimation Algorithms ◽  
Multiple Input ◽  
Input Multiple Output

Traditional channel estimation algorithms such as minimum mean square error (MMSE) are widely used in massive multiple-input multiple-output (MIMO) systems, but require a matrix inversion operation and an enormous amount of computations, which result in high computational complexity and make them impractical to implement. To overcome the matrix inversion problem, we propose a computationally efficient hybrid steepest descent Gauss–Seidel (SDGS) joint detection, which directly estimates the user’s transmitted symbol vector, and can quickly converge to obtain an ideal estimation value with a few simple iterations. Moreover, signal detection performance was further improved by utilizing the bit log-likelihood ratio (LLR) for soft channel decoding. Simulation results showed that the proposed algorithm had better channel estimation performance, which improved the signal detection by 31.68% while the complexity was reduced by 45.72%, compared with the existing algorithms.

scholarly journals Reduced Complexity by Combining Norm Based Ordering MMSE-BSIDE Detection in MIMO Systems

2017 ◽  
Vol 63 (3) ◽  
pp. 305-308
Author(s):  
Ramya Jothikumar ◽  
Nakkeeran Rangaswamy
Keyword(s):  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Detection Methods ◽  
Mimo Detection ◽  
Detection Scheme ◽  
Tree Traversal ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Simulation Results

AbstractThe breadth first signal decoder (BSIDE) is well known for its optimal maximum likelihood (ML) performance with lesser complexity. In this paper, we analyze a multiple-input multiple-output (MIMO) detection scheme that combines; column norm based ordering minimum mean square error (MMSE) and BSIDE detection methods. The investigation is carried out with a breadth first tree traversal technique, where the computational complexity encountered at the lower layers of the tree is high. This can be eliminated by carrying detection in the lower half of the tree structure using MMSE and upper half using BSIDE, after rearranging the column of the channel using norm calculation. The simulation results show that this approach achieves 22% of complexity reduction for 2×2 and 50% for 4×4 MIMO systems without any degradation in the performance.

scholarly journals Impact of Stair and Diagonal Matrices in Iterative Linear Massive MIMO Uplink Detectors for 5G Wireless Networks

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 71 ◽  
Author(s):  
Mahmoud A. Albreem ◽  
Mohammed H. Alsharif ◽  
Sunghwan Kim
Keyword(s):  
Computational Complexity ◽  
Iterative Methods ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Matrix Inversion ◽  
Multiple Input ◽  
The Matrix ◽  
Input Multiple Output ◽  
The Impact

In massive multiple-input multiple-output (M-MIMO) systems, a detector based on maximum likelihood (ML) algorithm attains optimum performance, but it exhaustively searches all possible solutions, hence, it has a very high complexity and realization is denied. Linear detectors are an alternative solution because of low complexity and simplicity in implementation. Unfortunately, they culminate in a matrix inversion that increases the computational complexity in high loaded systems. Therefore, several iterative methods have been proposed to approximate or avoid the matrix inversion, such as the Neuamnn series (NS), Newton iterations (NI), successive overrelaxation (SOR), Gauss–Siedel (GS), Jacobi (JA), and Richardson (RI) methods. However, a detector based on iterative methods requires a pre-processing and initialization where good initialization impresses the convergence, the performance, and the complexity. Most of the existing iterative linear detectors are using a diagonal matrix ( D ) in initialization because the equalization matrix is almost diagonal. This paper studies the impact of utilizing a stair matrix ( S ) instead of D in initializing the linear M-MIMO uplink (UL) detector. A comparison between iterative linear M-MIMO UL detectors with D and S is presented in performance and computational complexity. Numerical Results show that utilization of S achieves the target performance within few iterations, and, hence, the computational complexity is reduced. A detector based on the GS and S achieved a satisfactory bit-error-rate (BER) with the lowest complexity.

scholarly journals Enhancing performance in a LOS MIMO communication using a passive repeater

2021 ◽  
Vol 2140 (1) ◽  
pp. 012013
Author(s):  
Mahmoud Eissa ◽  
D Sukhanov
Keyword(s):  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Antenna System ◽  
Spatial Multiplexing ◽  
Line Of Sight ◽  
Mimo Communications ◽  
Matrix Rank ◽  
Channel Matrix ◽  
Multiple Input ◽  
Input Multiple Output

Abstract This paper presents a technique for obtaining a well-conditioned channel matrix in a line of sight multiple input multiple output (MIMO) environment. The technique is based on the implementation of a back-to-back antenna system as a passive repeater to enhance performance in MIMO systems. The flexible configuration with no need for a phase controller allows to spread the proposed repeater in MIMO communications to ensure spatial multiplexing and enhance capacity. A condition number and matrix rank are proposed as metrics to demonstrate the validity of the proposed method.

scholarly journals A VLSI Architecture for the V-BLAST Algorithm in Spatial-Multiplexing MIMO Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Pedro Cervantes-Lozano ◽  
Luis F. González-Pérez ◽  
Andrés D. García-García
Keyword(s):  
Fading Channels ◽  
Rayleigh Fading ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Vlsi Architecture ◽  
Spatial Multiplexing ◽  
Data Throughput ◽  
Multiple Input ◽  
Input Multiple Output ◽  
And Control

This paper presents a VLSI architecture for the suboptimal hard-output Vertical-Bell Laboratories Layered Space-Time (V-BLAST) algorithm in the context of Spatial Multiplexing Multiple-Input Multiple-Output (SM-MIMO) systems immersed in Rayleigh fading channels. The design and implementation of its corresponding data-path and control-path components over FPGA devices are considered. Results on synthesis, bit error rate performance, and data throughput are reported.

scholarly journals Accurate Performance Analysis of Coded Large-Scale Multiuser MIMO Systems with MMSE Receivers

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2884 ◽  
Author(s):  
Kai Zhai ◽  
Zheng Ma ◽  
Xianfu Lei
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Path Loss ◽  
Base Station ◽  
Mimo Networks ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Accurate Performance

In this paper, we estimate the uplink performance of large-scale multi-user multiple-input multiple-output (MIMO) networks. By applying minimum-mean-square-error (MMSE) detection, a novel statistical distribution of the signal-to-interference-plus-noise ratio (SINR) for any user is derived, for path loss, shadowing and Rayleigh fading. Suppose that the channel state information is perfectly known at the base station. Then, we derive the analytical expressions for the pairwise error probability (PEP) of the massive multiuser MMSE–MIMO systems, based on which we further obtain the upper bound of the bit error rate (BER). The analytical results are validated successfully through simulations for all cases.

Performance Improvement in Spatially Multiplexed MIMO Systems over Weibull-Gamma Fading Channel

Frequenz ◽  
2016 ◽  
Vol 70 (11-12) ◽  
Author(s):  
Keerti Tiwari ◽  
Davinder S. Saini ◽  
Sunil V. Bhooshan
Keyword(s):  
Interference Cancellation ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Optimal Performance ◽  
Detection Techniques ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Improved Performance ◽  
Ml Detection

AbstractIn multiple-input multiple-output (MIMO) systems, spatial demultiplexing at the receiver has its own significance. Thus, several detection techniques have been investigated. There is a tradeoff between computational complexity and optimal performance in most of the detection techniques. One of the detection techniques which gives improved performance and acceptable level of complexity is ordered successive interference cancellation (OSIC) with minimum mean square error (MMSE). However, optimal performance can be achieved by maximum likelihood (ML) detection but at a higher complexity level. Therefore, MMSE-OSIC with candidates (OSIC

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

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1667
Author(s):  
David Borges ◽  
Paulo Montezuma ◽  
Rui Dinis ◽  
Marko Beko
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Spatial Multiplexing ◽  
Existing Problems ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Transmission ◽  
Diversity Gains

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.

scholarly journals Low-complexity sparse-aware multiuser detection for large-scale MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rong Ran ◽  
Hayoung Oh
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Finite Alphabet ◽  
Multiuser Detectors ◽  
Input Multiple Output ◽  
Error Detector ◽  
Significant Performance

AbstractSparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors.

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