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.

Improving Space-Time-Frequency MIMO-OFDM with ICI Self-Cancellation Scheme using Least Square Error Estimator

2015 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
Nur Farahiah Ibrahim ◽  
Zahari Abu Bakar ◽  
Azlina Idris
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Symbol Error Rate ◽  
Space Time ◽  
Least Square ◽  
Error Estimator ◽  
Frequency Diversity ◽  
Time Frequency ◽  
Mimo Ofdm ◽  
Subcarrier Mapping

Channel estimation techniques for Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) based on comb type pilot arrangement with least-square error (LSE) estimator was investigated with space-time-frequency (STF) diversity implementation. The frequency offset in OFDM effected its performance. This was mitigated with the implementation of the presented inter-carrier interference self-cancellation (ICI-SC) techniques and different space-time subcarrier mapping. STF block coding in the system exploits the spatial, temporal and frequency diversity to improve performance. Estimated channel was fed into a decoder which combined the STF decoding together with the estimated channel coefficients using LSE estimator for equalization. The performance of the system was compared by measuring the symbol error rate with a PSK-16 and PSK-32. The results show that subcarrier mapping together with ICI-SC were able to increase the system performance. Introduction of channel estimation was also able to estimate the channel coefficient at only 5dB difference with a perfectly known channel.

Joint Channel Estimation and Data Detection for STBC MIMO-OFDM Wireless Communication System

2015 ◽  
Vol 24 (04) ◽  
pp. 1550059 ◽  
Author(s):  
Gajanan R. Patil ◽  
Vishwanath K. Kokate
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Data Detection ◽  
Channel Estimate ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Mimo Ofdm ◽  
The Cost ◽  
Joint Channel

This paper presents a joint channel estimation and data detection technique for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Initial estimate of the channel is obtained using semi-blind channel estimation (SBCE). The whitening rotation (WR)-based orthogonal pilot maximum likelihood (OPML) method is used to obtain the channel estimate. The estimate is further enhanced by extracting information through the received data symbols. The performance of the proposed estimator is studied under various channel models. The simulation study shows that this approach gives better performance over training-based channel estimation (TBCE) and OPML SBCE methods but at the cost of higher computational complexity.

scholarly journals A Comprehensive Performance Analysis of MIMO-OFDM Technology Using Different MIMO Configurations and M-QAM Modulation Schemes for LTE Cellular Network

2018 ◽  
Vol 12 (4) ◽  
pp. 118 ◽  
Author(s):  
Jobaida Akhtar ◽  
Mohammad Istiaque Reja ◽  
Md. Al Amin ◽  
Md. Sahidur Rahman
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Frequency Synchronization ◽  
Antenna Diversity ◽  
Qam Modulation ◽  
Mimo Ofdm ◽  
Modulation Schemes ◽  
Ber Performance

MIMO-OFDM (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) uses multiple antennas at transmitter and receiver side to facilitate high throughput performance without needing additional bandwidth or transmission power. But frequency synchronization, Inter Carrier Interference (ICI) minimization and antenna diversity are the main challenges for MIMO-OFDM wireless technology. In this paper, a MIMO-OFDM hybrid model is designed with proper frequency synchronization and antenna diversity that minimizes ICI with improved signal strength. Using the model a comprehensive analysis in terms of Bit Error Rate (BER) performance with respect to Signal to Noise Ratio (SNR) and Bit Rate for different M-ary QAM modulation schemes and different MIMO configurations are presented over Rayleigh fading and AWGN channel. After an extensive analysis, it is found that the propose OFDM scheme shows better Bit Error rate (BER) performance for 64-QAM than any other M-ary QAM modulation schemes and the optimum MIMO configuration for this good quality performance is found to be 3×2 configuration.

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.

scholarly journals Performance Enhancement of MIMO-OFDM using Redundant Residue Number System

2018 ◽  
Vol 8 (5) ◽  
pp. 3902
Author(s):  
M. I. Youssef ◽  
A. E. Emam ◽  
M. Abd Elghany
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Error Detection ◽  
Orthogonal Frequency Division Multiplexing ◽  
Number System ◽  
Residue Number System ◽  
Error Detection And Correction ◽  
Residue Number ◽  
Mimo Ofdm ◽  
Redundant Residue Number System

Telecommunication industry requires high capacity networks with high data rates which are achieved through utilization of Multiple-Input-Multiple-Output (MIMO) communication along with Orthogonal Frequency Division Multiplexing (OFDM) system. Still, the communication channel suffers from noise, interference or distortion due to hardware design limitations, and channel environment, and to combat these challenges, and achieve enhanced performance; various error control techniques are implemented to enable the receiver to detect any possible received errors and correct it and thus; for a certain transmitted signal power the system would have lower Bit Error Rate (BER). The provided research focuses on Redundant Residue Number System (RRNS) coding as a Forward Error Correction (FEC) scheme that improves the performance of MIMO-OFDM based wireless communications in comparison with current methods as Low-Density Parity Check (LDPC) coders at the transmitter side or equalizers at receiver side. The Bit Error Rate (BER) performance over the system was measured using MATLAB tool for different simulated channel conditions, including the effect of signal amplitude reduction and multipath delay spreading. Simulation results had shown that RRNS coding scheme provides an enhancement in system performance over conventional error detection and correction coding schemes by utilizing the distinct features of Residue Number System (RNS).

scholarly journals Distributed Structured Compressive Sensing-Based Time-Frequency Joint Channel Estimation for Massive MIMO-OFDM Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Wenjie Zhang ◽  
Hui Li ◽  
Rong Jin ◽  
Shanlin Wei ◽  
Wei Cheng ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Channel Estimation ◽  
Massive Mimo ◽  
Orthogonal Frequency Division Multiplexing ◽  
Spectrum Efficiency ◽  
Ofdm Systems ◽  
Time Frequency ◽  
Common Support ◽  
Mimo Ofdm ◽  
Joint Channel

In massive multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, accurate channel state information (CSI) is essential to realize system performance gains such as high spectrum and energy efficiency. However, high-dimensional CSI acquisition requires prohibitively high pilot overhead, which leads to a significant reduction in spectrum efficiency and energy efficiency. In this paper, we propose a more efficient time-frequency joint channel estimation scheme for massive MIMO-OFDM systems to resolve those problems. First, partial channel common support (PCCS) is obtained by using time-domain training. Second, utilizing the spatiotemporal common sparse property of the MIMO channels and the obtained PCCS information, we propose the priori-information aided distributed structured sparsity adaptive matching pursuit (PA-DS-SAMP) algorithm to achieve accurate channel estimation in frequency domain. Third, through performance analysis of the proposed algorithm, two signal power reference thresholds are given, which can ensure that the signal can be recovered accurately under power-limited noise and accurately recovered according to probability under Gaussian noise. Finally, pilot design, computational complexity, spectrum efficiency, and energy efficiency are discussed as well. Simulation results show that the proposed method achieves higher channel estimation accuracy while requiring lower pilot sequence overhead compared with other methods.

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 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.

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