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 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.

scholarly journals MBER Space Time Equalization assisted Multiuser Detection

2012 ◽  
pp. 47-50
Author(s):  
Yogeshwary B.H. ◽  
T.L. Purushottama ◽  
M Z Kurian
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Minimum Mean Square Error ◽  
Space Time ◽  
Decision Feedback ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Estimation Errors ◽  
Time Equalization

A novel minimum bit-error rate (MBER) space–time-equalization (STE)-based multiuser detector (MUD) is proposed for multiple-receive-antenna-assisted space-division multiple-access systems. It is shown that the MBER-STE-aided MUD significantly outperforms the standard minimum mean-square error design in terms of the achievable bit-error rate (BER). Adaptive implementations of the MBER STE are considered, and both the block-databased and sample-by-sample adaptive MBER algorithms are proposed. The latter, referred to as the least BER (LBER) algorithm, is compared with the most popular adaptive algorithm, known as the least mean square (LMS) algorithm. It is shown that in case of binary phase-shift keying, the computational complexity of the LBER-STE is about half of that required by the classic LMS-STE. Our simulation results demonstrate that the MBER ST-DFE assisted MUD is more robust to channel estimation errors as well as to potential error propagation imposed by decision feedback errors, compared to the MMSE ST-DFE assisted MUD.

Performance Enhancement of 16 Channels Back Haul DWDM OADM Ring Network Using Electronic Dispersion Compensation

2014 ◽  
Vol 513-517 ◽  
pp. 4357-4360
Author(s):  
Anurag Sharma ◽  
Vikrant Sharma ◽  
Dalvir Kaur ◽  
H.P. Singh
Keyword(s):  
Mean Square Error ◽  
Performance Enhancement ◽  
Dispersion Compensation ◽  
Minimum Mean Square Error ◽  
Mean Square ◽  
Ring Network ◽  
Eye Opening ◽  
Electronic Dispersion ◽  
Error Optimization ◽  
Inter Symbol Interference

In this paper, electronic dispersion compensation (EDC) based on minimum mean square error optimization has been employed to improve the performance of 16 channels, gigabit capacity, back haul DWDM OADM ring network.. It is observed that EDC significantly reduce BER by e-33 and improved Q2 dB by 3 dB, thus resulting in improved eye opening and considerably reduced inter-symbol interference.

Effective performance improvement of organic thin film transistors with multi-layer modifications

2020 ◽  
Vol 91 (3) ◽  
pp. 30201
Author(s):  
Hang Yu ◽  
Jianlin Zhou ◽  
Yuanyuan Hao ◽  
Yao Ni
Keyword(s):  
Thin Film ◽  
Thin Film Transistors ◽  
Performance Enhancement ◽  
Organic Thin Film Transistors ◽  
Electrical Performance ◽  
Hole Injection ◽  
Organic Thin Film ◽  
Effective Performance ◽  
Significant Performance ◽  
P Type

Organic thin film transistors (OTFTs) based on dioctylbenzothienobenzothiophene (C8BTBT) and copper (Cu) electrodes were fabricated. For improving the electrical performance of the original devices, the different modifications were attempted to insert in three different positions including semiconductor/electrode interface, semiconductor bulk inside and semiconductor/insulator interface. In detail, 4,4′,4′′-tris[3-methylpheny(phenyl)amino] triphenylamine (m-MTDATA) was applied between C8BTBTand Cu electrodes as hole injection layer (HIL). Moreover, the fluorinated copper phthalo-cyanine (F16CuPc) was inserted in C8BTBT/SiO2 interface to form F16CuPc/C8BTBT heterojunction or C8BTBT bulk to form C8BTBT/F16CuPc/C8BTBT sandwich configuration. Our experiment shows that, the sandwich structured OTFTs have a significant performance enhancement when appropriate thickness modification is chosen, comparing with original C8BTBT devices. Then, even the low work function metal Cu was applied, a normal p-type operate-mode C8BTBT-OTFT with mobility as high as 2.56 cm2/Vs has been fabricated.

Performance enhancement of Echo Cancellation Using a Combination of Partial Update ( PU) Methods and New Variable Length LMS (NVLLMS) Algorithm

2018 ◽  
Vol 24 (5) ◽  
pp. 66
Author(s):  
Thamer M. Jamel ◽  
Faez Fawzi Hammood
Keyword(s):  
Mean Square Error ◽  
Return Loss ◽  
Performance Enhancement ◽  
Variable Length ◽  
Echo Cancellation ◽  
Convergence Time ◽  
Length Variation ◽  
Mean Square ◽  
Step Size ◽  
Echo Return Loss Enhancement

In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%, and 16% using Periodic, Sequential, Stochastic, and M-max PU NVLLMS algorithms respectively, compared to that used by a full update method which  is very important, especially in the application of mobile communication since the power consumption must be considered. In addition, the average ERLE and average Mean Square Error (MSE) for M-max PU NVLLMS are better than other proposed algorithms.  

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