scholarly journals A Novel LS/LMMSE Based PSO Approach for 3D-Channel Estimation in Rayleigh Fading

2018 ◽  
Vol 7 (4) ◽  
pp. 117-123
Author(s):  
D. N. Bhange ◽  
C. Dethe
Keyword(s):  
Channel Estimation ◽  
Bit Error Rate ◽  
Error Rate ◽  
Orthogonal Frequency Division Multiplexing ◽  
Transmission Rate ◽  
Least Square ◽  
High Signal ◽  
Mean Square ◽  
Ofdm Systems ◽  
Channel Parameters

A high transmission rate can be obtained using Multi Input Multi Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) model. The most commonly used 3D-pilot aided channel estimation (PACE) techniques are Least Square (LS) and Least Minimum Mean Square (LMMSE) error. Both of the methods suffer from high mean square error and computational complexity. The LS is quite simple and LMMSE being superior in performance to LS providing low Bit Error Rate (BER) at high Signal to Noise ratio (SNR). Artificial Intelligence when combined with these two methods produces remarkable results by reducing the error between transmission and reception of data signal. The essence of LS and LMMSE is used priory to estimate the channel parameters. The bit error so obtained is compared and the least bit error value is fine-tuned using particle swarm optimization (PSO) to obtained better channel parameters and improved BER. The channel parameter corresponding to the low value of bit error rate obtained from LS/LMMSE is also used for particle initialization. Thus, the particles advance from the obtained channel parameters and are processed to find a better solution against the lowest bit error value obtained by LS/LMMSE. If the particles fail to do so, then the bit error value obtained by LS/LMMSE is finally considered. It has emerged from the simulated results that the performance of the proposed system is better than the LS/LMMSE estimations. The performance of OFDM systems using proposed technique can be observed from the imitation and relative results.

scholarly journals A Comprehensive Review on Channel Estimation in OFDM System

2019 ◽  
Vol 5 (3) ◽  
pp. 6 ◽  
Author(s):  
Neha Dubey ◽  
Ankit Pandit
Keyword(s):  
Channel Estimation ◽  
Mean Square Error ◽  
Orthogonal Frequency Division Multiplexing ◽  
Transmission Rate ◽  
Minimum Mean Square Error ◽  
Estimation Method ◽  
Least Square ◽  
Estimation Methods ◽  
Mean Square ◽  
Mimo Ofdm

In wireless communication, orthogonal frequency division multiplexing (OFDM) plays a major role because of its high transmission rate. Channel estimation and tracking have many different techniques available in OFDM systems. Among them, the most important techniques are least square (LS) and minimum mean square error (MMSE). In least square channel estimation method, the process is simple but the major drawback is it has very high mean square error. Whereas, the performance of MMSE is superior to LS in low SNR, its main problem is it has high computational complexity. If the error is reduced to a very low value, then an exact signal will be received. In this paper an extensive review on different channel estimation methods used in MIMO-OFDM like pilot based, least square (LS) and minimum mean square error method (MMSE) and least minimum mean square error (LMMSE) methods and also other channel estimation methods used in MIMO-OFDM are discussed.

scholarly journals Channel Estimation and Data Detection Using Machine Learning for MIMO 5G Communication Systems in Fading Channel

Technologies ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 72 ◽  
Author(s):  
Sumitra Motade ◽  
Anju Kulkarni
Keyword(s):  
Channel Estimation ◽  
Bit Error Rate ◽  
Error Rate ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Symbol Error Rate ◽  
Base Station ◽  
Data Detection ◽  
Ofdm Systems ◽  
K Nearest Neighbor

In multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems, multi-user detection (MUD) algorithms play an important role in reducing the effect of multi-access interference (MAI). A combination of the estimation of channel and multi-user detection is proposed for eliminating various interferences and reduce the bit error rate (BER). First, a novel sparse based k-nearest neighbor classifier is proposed to estimate the unknown activity factor at a high data rate. The active users are continuously detected and their data are decoded at the base station (BS) receiver. The activity detection considers both the pilot and data symbols. Second, an optimal pilot allocation method is suggested to select the minimum mutual coherence in the measurement matrix for optimal pilot placement. The suggested algorithm for designing pilot patterns significantly improves the results in terms of mean square error (MSE), symbol error rate (SER) and bit error rate for channel detection. An optimal pilot placement reduces the computational complexity and maximizes the accuracy of the system. The performance of the channel estimation (CE) and MUD for the proposed scheme was good as it provided significant results, which were validated through simulations.

scholarly journals Performance Enhancement of Coherent Optical OFDM System Using LMS Algorithm

2020 ◽  
Vol 1 ◽  
pp. 1-5
Author(s):  
Manisha Bharti
Keyword(s):  
Phase Noise ◽  
Bit Error Rate ◽  
Error Rate ◽  
Orthogonal Frequency Division Multiplexing ◽  
Performance Enhancement ◽  
Lms Algorithm ◽  
Frame Structure ◽  
Least Mean Square ◽  
Ofdm Systems ◽  
Ofdm System

Instability of the local oscillator causes phase noise – a phenomenon that is a disadvantage and is considered to be a major obstacle in the functioning of coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. An attempt has been made in this paper to reduce the effects of common phase errors generated by phase noise. In this paper, a least mean square (LMS) based algorithm is proposed for estimation of phase noise. Using this proposed algorithm, the major problem of phase ambiguity caused by cycle slip is avoided and the bit error rate is greatly improved. Further, there is no requirement for modifying the frame structure of OFDM using this algorithm. A CO-OFDM system with the 8-PSK technique is used to implement the algorithm concerned. Furthermore, the algorithm, using the 8-PSK modulation technique, is analyzed and compared with the existing QPSK technique and with other algorithms. The investigations reveal that 8-PSK outperforms existing LMS algorithms using other techniques and significantly reduces the bit error rate.

scholarly journals Smoothing techniques for decision-directed MIMO OFDM channel estimation

2011 ◽  
Vol 9 ◽  
pp. 139-143
Author(s):  
P. Beinschob ◽  
U. Zölzer
Keyword(s):  
Channel Estimation ◽  
Bit Error Rate ◽  
Error Rate ◽  
Error Propagation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mimo Systems ◽  
Smoothing Techniques ◽  
Time Frequency ◽  
Channel Estimate ◽  
Mimo Ofdm

Abstract. With the purpose of supplying the demand of faster and more reliable communication, multiple-input multiple-output (MIMO) systems in conjunction with Orthogonal Frequency Division Multiplexing (OFDM) are subject of extensive research. Successful Decoding requires an accurate channel estimate at the receiver, which is gained either by evaluation of reference symbols which requires designated resources in the transmit signal or decision-directed approaches. The latter offers a convenient way to maximize bandwidth efficiency, but it suffers from error propagation due to the dependency between the decoding of the current data symbol and the calculation of the next channel estimate. In our contribution we consider linear smoothing techniques to mitigate error propagation by the introduction of backward dependencies in the decision-based channel estimation. Designed as a post-processing step, frame repeat requests can be lowered by applying this technique if the data is insensitive to latency. The problem of high memory requirements of FIR smoothing in the context of MIMO-OFDM is addressed with an recursive approach that acquires minimal resources with virtual no performance loss. Channel estimate normalized mean square error and bit error rate (BER) performance evaluations are presented. For reference, a median filtering technique is presented that operates on the MIMO time-frequency grids of channel coefficients to reduce the peak-like outliers produced by wrong decisions due to unsuccessful decoding. Performance in terms of Bit Error Rate is compared to the proposed smoothing techniques.

scholarly journals Precoding Aided Data Correlation Scheme for Channel Estimation Technique in MIMO-OFDM System

2021 ◽  
Vol 16 ◽  
pp. 146-154
Author(s):  
Sidramayya S. Matad ◽  
Ramesha K.
Keyword(s):  
Channel Estimation ◽  
Mean Square Error ◽  
Orthogonal Frequency Division Multiplexing ◽  
Transmission Rate ◽  
Multiple Input Multiple Output ◽  
Blind Channel Estimation ◽  
Mean Square ◽  
Estimation Technique ◽  
Blind Channel ◽  
Mimo Ofdm

Channel estimation is considered as an important phase in Multiple Input Multiple Output – Orthogonal Frequency Division Multiplexing (MIMO-OFDM) networks which can enhances the performance significantly. Channel estimation widely classified as pilot based, blind and semi-blind channel estimation. The pilot-based channel estimation decreases the data transmission rate and spectral efficiency. To overcome these issues of existing schemes, we present a novel blind channel estimation technique. According to proposed scheme, we transmit the data in a block-wise manner. The proposed scheme uses precoding technique to establish the correlation between these blocks. Further, we use channel correlation to solve the diagonal uncertainty of correlation matrix which helps to improve the system performance. We present a comparative analysis study which shows that proposed approach can achieve better performance in terms of Normalized Mean Square Error (NMSE) and Mean Square Error (MSE) when compared with existing techniques.

scholarly journals Channel Estimation Based on Statistical Frames and Confidence Level in OFDM Systems

2018 ◽  
Vol 8 (9) ◽  
pp. 1607 ◽  
Author(s):  
Xiao Zhou ◽  
Chengyou Wang ◽  
Ruiguang Tang ◽  
Mingtong Zhang
Keyword(s):  
Channel Estimation ◽  
Mean Square Error ◽  
Confidence Level ◽  
Orthogonal Frequency Division Multiplexing ◽  
Minimum Mean Square Error ◽  
Estimation Method ◽  
Least Square ◽  
Estimation Methods ◽  
Mean Square ◽  
Inverse Operation

Channel estimation is an important module for improving the performance of the orthogonal frequency division multiplexing (OFDM) system. The pilot-based least square (LS) algorithm can improve the channel estimation accuracy and the symbol error rate (SER) performance of the communication system. In pilot-based channel estimation, a certain number of pilots are inserted at fixed intervals between OFDM symbols to estimate the initial channel information, and channel estimation results can be obtained by one-dimensional linear interpolation. The minimum mean square error (MMSE) and linear minimum mean square error (LMMSE) algorithms involve the inverse operation of the channel matrix. If the number of subcarriers increases, the dimension of the matrix becomes large. Therefore, the inverse operation is more complex. To overcome the disadvantages of the conventional channel estimation methods, this paper proposes a novel OFDM channel estimation method based on statistical frames and the confidence level. The noise variance in the estimated channel impulse response (CIR) can be largely reduced under statistical frames and the confidence level; therefore, it reduces the computational complexity and improves the accuracy of channel estimation. Simulation results verify the effectiveness of the proposed channel estimation method based on the confidence level in time-varying dynamic wireless channels.

scholarly journals Variable Is Better Than Invariable: Sparse VSS-NLMS Algorithms with Application to Adaptive MIMO Channel Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Guan Gui ◽  
Zhang-xin Chen ◽  
Li Xu ◽  
Qun Wan ◽  
Jiyan Huang ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Computational Cost ◽  
Mimo Channel ◽  
Variable Step Size ◽  
Mean Square ◽  
Ofdm Systems ◽  
Step Size ◽  
Estimation Performance

Channel estimation problem is one of the key technical issues in sparse frequency-selective fading multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) scheme. To estimate sparse MIMO channels, sparseinvariable step-size normalized least mean square(ISS-NLMS) algorithms were applied to adaptive sparse channel estimation (ACSE). It is well known that step-size is a critical parameter which controls three aspects: algorithm stability, estimation performance, and computational cost. However, traditional methods are vulnerable to cause estimation performance loss because ISS cannot balance the three aspects simultaneously. In this paper, we propose two stablesparse variable step-sizeNLMS (VSS-NLMS) algorithms to improve the accuracy of MIMO channel estimators. First, ASCE is formulated in MIMO-OFDM systems. Second, different sparse penalties are introduced to VSS-NLMS algorithm for ASCE. In addition, difference between sparse ISS-NLMS algorithms and sparse VSS-NLMS ones is explained and their lower bounds are also derived. At last, to verify the effectiveness of the proposed algorithms for ASCE, several selected simulation results are shown to prove that the proposed sparse VSS-NLMS algorithms can achieve better estimation performance than the conventional methods via mean square error (MSE) and bit error rate (BER) metrics.

scholarly journals Performance Evaluation of OFDM System using Pseudo-Pilots with Particle Swarm & Moth Flame (Hybrid) Optimization

2019 ◽  
Vol 8 (9S) ◽  
pp. 127-130
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Transmission Rate ◽  
Signal To Noise Ratio ◽  
Particle Swarm ◽  
Least Square ◽  
Coherent Detection ◽  
Receiver Design ◽  
Recursive Least Square ◽  
High Data

This paper is focused on the advanced signal processing techniques for the multi-carrier modulation especially on the orthogonal frequency division multiplexing (OFDM). OFDM has high data rate and robust against the frequency selective multi-path channels. Channel estimation is crucial for the receiver design in coherent detection. In this paper we are investigating and examining the pilot aided system for channel estimation and its special effects on the performance of the OFDM based system. In this paper new technique is proposed which make use of conventional Least Square (LS) and Recursive Least Square (RLS) hybridization techniques for the channel estimation afterwards we apply Particle Swarm Optimization (PSO) and Hybrid PSO (PSO+ Moth Flame Optimization(MFO)) optimization for obtaining more optimize techniques. In the proposed system, to estimate channel impulse response we are using pseudo-pilots instead to pilots as it is useful to overcome the pilot overhead and decrease the complexity by using pseudo random symbol (PRS). The performance of the proposed techniques and the weighted scheme are compared and verified using computerized simulation carried out using Matrix Laboratory (MATLAB) software. It is demonstrated on the basis of graph between BER and signal to Noise Ratio (Eb/NO), that the proposed technique reduces the execution time and increase the transmission rate with low or zero overhead.

scholarly journals SLM Technique to Reduce PAPR and Improve BER in OFDM Systems

2021 ◽  
Vol 9 (VI) ◽  
pp. 5138-5143
Author(s):  
N. Sai Santhosh
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
Rate Distortion ◽  
Estimation Accuracy ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Ofdm Systems ◽  
Time Frequency

Through the combined use of multiple input, multiple output, and orthogonal frequency division multiplexing technologies, mankind has achieved a huge leap in the data rate of gigabit per second with the birth of 5G wireless technology. With frequency selective fading, multiple (OFDM MIMO) is possible. One of its most important performance concerns is PAPR (Peak-to-Average Power Ratio), which renders OFDM particularly vulnerable to harmonic distortion, reducing channel estimation accuracy and resulting in a lower bit error rate (BER). We propose a selective codeword shift mapping method for the MIMO-OFDM system (SCS-SLM). It lowers the PAPR and causes the power amplifier to operate in the non-linear area, resulting in intermodulation between sub-carriers, signal constellation, bit error rate distortion, as well as enhanced system performance. Furthermore, employing space-time-frequency block code (STFBC OFDM) orthogonal frequency division multiplexing might improve BER performance. This paper mentions a useful strategy for minimizing the PAPR, which is Selective Mapping. In addition, the bit error rate performance and, as a result, the process complexity for this system is discussed. In addition to the above-mentioned analysis, a thorough analysis of the mutual independence of the alternative OFDM signals generated using this technique is also discussed. Furthermore, this new approach has the important benefit of removing the extra bits on the side of the transmitted OFDM signal.

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