scholarly journals Performance enhancement of MIMO detectors using wavelet de-noising filters

2016 ◽  
Vol 5 (4) ◽  
pp. 131
Author(s):  
Reham Wgeeh ◽  
Amr Hussein ◽  
Mahmoud Attia
Keyword(s):  
Error Rate ◽  
Communication Systems ◽  
Performance Enhancement ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Antenna Element ◽  
Detection Techniques ◽  
Information Signal ◽  
Input Multiple Output

Multiple-Input Multiple-Output (MIMO) technology has attracted great attention in many wireless communication systems. It provides significant enhancement in the spectral efficiency, throughput, and link reliability. There are numerous MIMO signal detection techniques that have been studied in the previous decades such as Maximum Likelihood (ML), Zero Forcing (ZF), Minimum Mean Square Error (MMSE) detectors, etc. It is well known that the additive and multiplicative noise in the information signal can significantly degrade the performance of MIMO detectors. During the last few years, the noise problem has been the focus of much research, and its solution could lead to profound improvements in symbol error rate performance of the MIMO detectors. In this paper, ML, ZF, and MMSE based wavelet de-noising detectors are proposed. In these techniques, the noise contaminated signals from each receiving antenna element are de-noised individually in parallel to boost the SNR of each branch. The de-noised signals are applied directly to the desired signal detector. The simulation results revealed that the proposed detectors constructed on de-noising basis achieve better symbol error rate (SER) performance than that of systems currently in use.

MIMO Detectors: A Comprehensive Performance Analysis

2021 ◽  
Vol 16 (3) ◽  
pp. 24-27
Author(s):  
E. Obi ◽  
B.O. Sadiq ◽  
O.S . Zakariyya ◽  
A. Theresa
Keyword(s):  
Error Rate ◽  
Mimo Systems ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Signal To Noise ◽  
High Data ◽  
Noise Ratio ◽  
Better Than

Multiple-input multiple-output (MIMO) systems are increasingly becoming popular due to their ability to multiply data rates without any expansion in the bandwidth. This is critical in this era of high-data rate applications but limited bandwidth. MIMO detectors play an important role in ensuring effective communication in such systems and as such the performance of the following are compared in this paper with respect to symbol error rate (SER) versus signal-to-noise ratio (SNR): maximum likelihood (ML), zero forcing (ZF), minimum mean square error (MMSE) and vertical Bell laboratories layered space time (VBLAST). Results showed that the ML has the best performance as it has the least Symbol Error Rate (SER) for all values of Signal to Noise Ratio (SNR) as it was 91.9% better than MMSE, 99.6% better than VBLAST and 99.8% better than ZF at 20db for a 2x2 antenna configuration., it can also be deduced that the performance increased with increase in number of antenna for all detectors except the V-BLAST detector.

Low-Complexity MIMO MMSE Receiver with Performance Enhancement via Coordinate Interleaving

2020 ◽  
Vol 29 (14) ◽  
pp. 2050231
Author(s):  
Serdar Özyurt ◽  
Mustafa Öztürk ◽  
Enver Çavuş
Keyword(s):  
Performance Enhancement ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Complexity Reduction ◽  
Error Performance ◽  
Signal Space Diversity ◽  
Mmse Receiver ◽  
Field Programmable ◽  
Input Multiple Output

Multiple-input multiple-output (MIMO) Minimum mean-square error (MMSE) receivers are widely adopted in the latest communication standards and reducing the complexity of these receivers while preserving the error performance is highly desirable. In this work, we study the error performance and implementation complexity of MIMO MMSE receivers when combined with a coordinate interleaved signal space diversity (SSD) technique. Contrary to the well-known trade-off between the error performance and implementation complexity, the proposed system leads to a considerably simplified MIMO MMSE receiver with significant performance gains when compared to the original MIMO MMSE receiver. Unlike the standard MIMO MMSE receiver, the proposed coordinate interleaved technique induces a block diagonal transmit correlation matrix providing both performance enhancement and complexity reduction. The results show that the error performance can be improved more than 10[Formula: see text]dB with up to 71% computational complexity reduction. The complexity comparison between the original and proposed approaches is also verified by means of field-programmable gate array (FPGA) implementation.

scholarly journals An Improved Jacobi-Based Detector for Massive MIMO Systems

Information ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 165 ◽  
Author(s):  
Xiaoqing Zhao ◽  
Zhengquan Li ◽  
Song Xing ◽  
Yang Liu ◽  
Qiong Wu ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Correction Method ◽  
Detection Algorithm ◽  
Detection Accuracy ◽  
Input Multiple Output ◽  
Mmse Detector

Massive multiple-input-multiple-output (MIMO) is one of the key technologies in the fifth generation (5G) cellular communication systems. For uplink massive MIMO systems, the typical linear detection such as minimum mean square error (MMSE) presents a near-optimal performance. Due to the required direct matrix inverse, however, the MMSE detection algorithm becomes computationally very expensive, especially when the number of users is large. For achieving the high detection accuracy as well as reducing the computational complexity in massive MIMO systems, we propose an improved Jacobi iterative algorithm by accelerating the convergence rate in the signal detection process.Specifically, the steepest descent (SD) method is utilized to achieve an efficient searching direction. Then, the whole-correction method is applied to update the iterative process. As the result, the fast convergence and the low computationally complexity of the proposed Jacobi-based algorithm are obtained and proved. Simulation results also demonstrate that the proposed algorithm performs better than the conventional algorithms in terms of the bit error rate (BER) and achieves a near-optimal detection accuracy as the typical MMSE detector, but utilizing a small number of iterations.

Research on UCD Precoding for MIMO System

2012 ◽  
Vol 459 ◽  
pp. 620-623
Author(s):  
Hong He ◽  
Tao Li ◽  
Tong Yang ◽  
Lin He
Keyword(s):  
Communication Systems ◽  
Mimo System ◽  
Geometric Mean ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Error Correcting Codes ◽  
Decomposition Scheme ◽  
Input Multiple Output ◽  
Uniform Channel ◽  
Channel Decomposition

This article mainly describes a new technique of multiple-input multiple-output (MIMO) communication systems based on the recent communication demand. This technique, by pre-coding CSI (the channel state information) at the transmitter, is based on UCD (Uniform Channel Decomposition) algorithm for MIMO system. By Uniform Channel decomposition of channel matrix, the algorithm can decompose a MIMO downlink channel into multiple identical sub-channels. The power allocation applied to each sub channel in MIMO system is identical, and the MIMO channel’s capacity isn’t reduce when the SNR (Signal Noise Ratio) is low. The simulations show that the UCD scheme has a better performance than GMD (Geometric Mean Decomposition) scheme even without the use of error-correcting codes, and the Symbol Error Rate (SER) of UCD algorithm is lower than GMD’s at the same SNR. Consequently, MIMO system gets a better interference performance by UCD algorithm.

Selective Spanning With Fast Enumeration Algorithm for MIMO

2017 ◽  
Vol 6 (10) ◽  
pp. 79
Author(s):  
Sruthy L ◽  
L Bharathi ◽  
P Malini
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Mimo System ◽  
Additive White Gaussian Noise ◽  
Multiple Input Multiple Output ◽  
Symbol Error Rate ◽  
Enumeration Algorithm ◽  
High Data ◽  
Input Multiple Output ◽  
Output System

Multiple input multiple output system have been emerged technology to increase channel capacity and a technical breakthrough for high data rate wireless transmission. The main objective of MIMO system is to obtain low Symbol Error Rate (SER) and acceptable computational complexity. The MIMO system cannot be implemented due to complexity problem. The complexity of MIMO system can be reduced by using different detector algorithms. In this paper, the performance of MIMO system over AWGN (Additive White Gaussian Noise) with ZF, MMSE, SD, K best algorithm and SSFE are analyzed using different antenna configuration. The Bit Error Rate performance of all detectors are studied for 16QAM modulation technique using AWGN channel for the analysis purpose and their effect on BER (Bit Error Rate) have been presented.

Adaptive Beamforming Assisted ReceiverAdaptive Beamforming

2009 ◽  
pp. 60-81 ◽  
Author(s):  
Sheng Chen
Keyword(s):  
High Throughput ◽  
Error Rate ◽  
Performance Enhancement ◽  
Minimum Mean Square Error ◽  
Symbol Error Rate ◽  
Adaptive Beamforming ◽  
Multiple Antenna ◽  
Mean Square ◽  
Space Division Multiple Access ◽  
Significant Performance

Adaptive beamforming is capable of separating user signals transmitted on the same carrier frequency, and thus provides a practical means of supporting multiusers in a space-division multiple-access scenario. Moreover, for the sake of further improving the achievable bandwidth efficiency, high-throughput quadrature amplitude modulation (QAM) schemes have become popular in numerous wireless network standards, notably, in the recent WiMax standard. This contribution focuses on the design of adaptive beamforming assisted detection for the employment in multiple-antenna aided multiuser systems that employ the high-order QAM signalling. Traditionally, the minimum mean square error (MMSE) design is regarded as the state-of-the-art for adaptive beamforming assisted receiver. However, the recent work (Chen et al., 2006) proposed a novel minimum symbol error rate (MSER) design for the beamforming assisted receiver, and it was demonstrated that this MSER design provides significant performance enhancement, in terms of achievable symbol error rate, over the standard MMSE design. This MSER beamforming design is developed fully in this contribution. In particular, an adaptive implementation of the MSER beamforming solution, referred to as the least symbol error rate algorithm, is investigated extensively. The proposed adaptive MSER beamforming scheme is evaluated in simulation, in comparison with the adaptive MMSE beamforming benchmark.

scholarly journals An Enhanced Precoder for Multi User Multiple-Input Multiple-Output Downlink Systems

2020 ◽  
Vol 10 (13) ◽  
pp. 4547 ◽  
Author(s):  
Woon-Sang Lee ◽  
Jae-Hyun Ro ◽  
Young-Hwan You ◽  
Duckdong Hwang ◽  
Hyoung-Kyu Song
Keyword(s):  
Antenna Array ◽  
High Throughput ◽  
Communication Systems ◽  
High Performance ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Data Rate ◽  
Multiple Input ◽  
Input Multiple Output

Recently, as the demand for data rate of users has increased, wireless communication systems have aimed to offer high throughput. For this reason, various techniques which guarantee high performance have been invented, such as massive multiple-input multiple-output (MIMO). However, the implementation of huge base station (BS) antenna array and decrease of reliability as the number of users increases are chief obstacles. In order to mitigate these problems, this paper proposes an adaptive precoder which provides high throughput and bit error rate (BER) performances to achieve the desired data rate in multi user (MU) MIMO downlink systems which have a practical BS antenna array (up to 16). The proposed scheme is optimized with a modified minimum mean square error (MMSE) criterion in order to improve BER gain and reduce data streams in order to obtain diversity gain at low signal to noise ratio (SNR). It is shown that the BER and throughput performances of the proposed scheme are improved.

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

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