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.

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.

scholarly journals Beam division multiple access for millimeter wave massive MIMO: Hybrid zero-forcing beamforming with user selection

2022 ◽  
Vol 12 (1) ◽  
pp. 445
Author(s):  
Hong Son Vu ◽  
Kien Truong ◽  
Minh Thuy Le
Keyword(s):  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Zero Forcing ◽  
Multiuser Interference ◽  
Novel Approach ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Promising Solution

<p>Massive multiple-input multiple-output (MIMO) systems are considered a promising solution to minimize multiuser interference (MUI) based on simple precoding techniques with a massive antenna array at a base station (BS). This paper presents a novel approach of beam division multiple access (BDMA) which BS transmit signals to multiusers at the same time via different beams based on hybrid beamforming and user-beam schedule. With the selection of users whose steering vectors are orthogonal to each other, interference between users is significantly improved. While, the efficiency spectrum of proposed scheme reaches to the performance of fully digital solutions, the multiuser interference is considerably reduced.</p>

scholarly journals Deep Scanning—Beam Selection Based on Deep Reinforcement Learning in Massive MIMO Wireless Communication System

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1844
Author(s):  
Minhoe Kim ◽  
Woongsup Lee ◽  
Dong-Ho Cho
Keyword(s):  
Communication Systems ◽  
Large Scale ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Q Learning ◽  
Multiple Input ◽  
Beam Selection ◽  
Input Multiple Output ◽  
Optimal Beam ◽  
Resource Allocation Scheme

In this paper, we investigate a deep learning based resource allocation scheme for massive multiple-input-multiple-output (MIMO) communication systems, where a base station (BS) with a large scale antenna array communicates with a user equipment (UE) using beamforming. In particular, we propose Deep Scanning, in which a near-optimal beamforming vector can be found based on deep Q-learning. Through simulations, we confirm that the optimal beam vector can be found with a high probability. We also show that the complexity required to find the optimum beam vector can be reduced significantly in comparison with conventional beam search schemes.

scholarly journals Spectral Efficiency Improvement Techniques In Massive Mimo For 5G Communications

2021 ◽  
Vol 12 (2) ◽  
pp. 1457-1465
Author(s):  
Naraiah R , Et. al.
Keyword(s):  
Spectral Efficiency ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Broad Band ◽  
Cell System ◽  
Base Station ◽  
Information Rate ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Long Time

Wireless communications has gotten one of the quickest developing zones in our advanced life and makes colossal effect on practically every component of our day by day life. 5G should support a large number of new applications with a wide assortment of prerequisites, including higher pinnacle and client information rates, diminished dormancy, improved indoor inclusion, expanded number of gadgets, etc. The normal traffic development in at least a long time from now can be fulfilled by the consolidated utilization of more range, higher spectral efficiency, and densification of cells. The increment in spectral effectiveness will improve the throughput of the system which straightforwardly serves the Enhanced Mobile Broad band use instance of the 5G assistance. In massive Multiple-Input Multiple-Output (M-MIMO) systems few hundred quantities of antennas are conveyed at each base station (BS) to serve a moderately modest number of single-reception apparatus terminals with multiuser, giving higher information rate and lower idleness. Massive Multiple-Input Multiple-Output is the arising innovation in cell system for higher information rate correspondence. It utilizes enormous number of communicating reception apparatus at the base station which is made conceivable by the radio wire cluster which can be electronically steerable and adequately utilized for shaft framing. Spectral proficiency is the vital boundary to be improved in expanding throughput. The system execution under different commonsense limitations and conditions, for example, restricted soundness block length, number of base station (BS) antennas, and number of dynamic clients are assessed through simulation.  

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 Sectoral dual-polarized MIMO antenna for 5G-NR band N77 base station

2021 ◽  
Vol 21 (3) ◽  
pp. 1611
Author(s):  
Muhsin Muhsin ◽  
Afina Lina Nurlaili ◽  
Aulia Saharani ◽  
Indah Rahmawti Utami
Keyword(s):  
High Performance ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Mimo Antenna ◽  
Future Technology ◽  
New Radio ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Dual Polarized

<span>Massive internet of things (IoT) in 5G has many advantages as a future technology. It brings some challenges such as a lot of devices need massive connection. In this case, multiple-input multiple-output (MIMO) systems offer high performance and capacity of communications. There is a challenge of correlation between antennas in MIMO. This paper proposes three-sectors MIMO base station antenna for 5G-New Radio (5G-NR) band N77 with dual polarized configuration to reduce the correlation. The proposed antenna has a maximum coupling of -16.90 dB and correlation below 0.01. The obtained bit error rate (BER) performance is very close to non-correlated antennas with bandwidth of 1.87 GHz. It means that the proposed antenna has been well designed.</span>

Fault-tolerant PWM inverter model development for safety electrical drives

2016 ◽  
Vol 7 (2) ◽  
pp. 77-83 ◽  
Author(s):  
Cs. Szász ◽  
R. Şinca
Keyword(s):  
Energy Efficiency ◽  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Mean Square ◽  
Maximum Ratio Combining ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Better Than

This paper deals with the most recent technology in wireless communication which is massive multiple input multiple output system. The paper studies the performance of massive multiple input multiple output uplink system over Rayleigh fading channel. The performance is measured in terms of spectral and energy efficiency using three schemes of linear detection, maximum-ratio-combining, zero forcing receiver, and minimum mean-square error receiver. The simulation results show that the spectral and energy efficiency increases with increasing the number of base station antennas. Also, the spectral and energy efficiency with minimum mean-square error receiver is better than that withzero forcing receiver, and the latter is better than that with maximum-ratio-combining. Furthermore, the energy efficiency decreases with increasing the spectral efficiency.

A Comparison of Norm Based Antenna Selection and Random Antenna Selection with Regard to Energy Efficiency in Wireless System with Large Number of Users

2020 ◽  
Vol 10 (2) ◽  
pp. 189-196
Author(s):  
Ashu Taneja ◽  
Nitin Saluja
Keyword(s):  
Energy Efficiency ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Transmit Antenna Selection ◽  
Wireless System ◽  
Multiple Input ◽  
Input Multiple Output

Background: The paper considers the wireless system with large number of users (more than 50 users) and each user is assigned large number of antennas (around 200) at the Base Station (BS). Objective: The challenges associated with the defined system are increased power consumption and high complexity of associated circuitry. The antenna selection is introduced to combat these problems while the usage of linear precoding reduces computational complexity. The literature suggests number of antenna selection techniques based on statistical properties of signal. However, each antenna selection technique suits well to specific number of users. Methods: In this paper, the random antenna selection is compared with norm-based antenna selection. It is analysed that the random antenna selection leads to inefficient spectral efficiency if the number of users are more than 50 in Multi-User Multiple-Input Multiple Output (MU-MIMO) system. Results: The paper proposes the optimization of Energy-Efficiency (EE) with random transmit antenna selection for large number of users in MU-MIMO systems. Conclusion: Also the computation leads to optimization of number of transmit antennas at the BS for energy efficiency. The proposed algorithm results in improvement of the energy efficiency by 27% for more than 50 users.

scholarly journals Effects of Path Visibility on Urban MIMO Systems

1970 ◽  
Vol 5 (1) ◽  
pp. 22-30
Author(s):  
Sirichai Hemrungrote ◽  
Toshikazu Hori ◽  
Mitoshi Fujimoto ◽  
Kentaro Nishimori
Keyword(s):  
Channel Capacity ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Propagation Characteristics ◽  
Simple Method ◽  
Limited Bandwidth ◽  
Multiple Input ◽  
Input Multiple Output

Multiple-Input Multiple-Output (MIMO) wireless communication technology is expected to improve the channel capacity over the limited bandwidth of existing networks. Since urban MIMO systems have complex propagation characteristics, the channel capacity cannot be estimated using a simple method. Hence, we introduce channel capacity characteristics to urban MIMO systems by using a combination of imaging and ray-launching methods as a ray-tracing scheme. A simulation based on these methods with variable parameters can reproducibly estimate various urban propagation characteristics and discriminate the effects of the urban model and antenna configurations. The characteristics of the Signal-to-Noise Ratio (SNR), the channel capacity, the spatial correlation, as well as the path visibility are then determined from the results of the simulation. The parameter called path visibility introduced in our previous study is considered again herein. We clarify that only this single parameter can be used to determine the channel capacity characteristics in urban MIMO scenarios. This parameter also provides guidance in determining the appropriate range for the base station (BS) height.

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

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