scholarly journals Comb Type Pilot Based Channel Estimation using Dft Based Interpolation for Spatial Modulated OFDM Systems

2021 ◽  
Vol 10 (5) ◽  
pp. 403-410
Author(s):  
Anetha Mary Soman ◽  
R Nakkeeran ◽  
Shinu Mathew John
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Urban Environments ◽  
Least Square ◽  
Spatial Modulation ◽  
Ofdm Systems ◽  
Least Square Estimator ◽  
Selective Channel ◽  
Project Model ◽  
Noise Error

An integration of Spatial Modulation with Orthogonal Frequency Division Multiplexing (SM OFDM) is a recently evolved transmission technique. In practical scenarios, channel estimation is significant for detecting transmitted data coherently. Impulse response based interpolation technique that provides channel frequency response estimate with reduction in noise error is proposed for comb type pilot based channel estimation of SM OFDM system along with 1D interpolation techniques under frequency selective channel. This scheme focus on carrying out smoothing and estimation in time domain and transforming output back to the frequency domain. BER performance is investigated for Rayleigh channel employing COST 207 project model on two test urban environments (Typical and Bad) for 4 and 16 QAM SM OFDM systems. Results show that the Least Square estimator with DFT interpolation performs finer compared to all one dimensional interpolation methods with less computational complexity by employing FFT algorithms.

PILOT-AIDED MULTIUSER CHANNEL ESTIMATION AND TRACKING IN MIMO-OFDM SYSTEMS

2007 ◽  
Vol 16 (03) ◽  
pp. 319-335 ◽  
Author(s):  
QINGHAI YANG ◽  
KYUNG SUP KWAK
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Least Square ◽  
Estimation Methods ◽  
Ofdm Systems ◽  
Estimation Algorithms ◽  
Channel Estimate ◽  
Multiuser Channel ◽  
Input Multiple Output

This paper addresses the pilot-aided multiuser least square (LS) channel estimation for the uplink of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. The systems under consideration allow all users use all available subcarriers independently and thus involve multiuser interference in the frequency domain. Direct application of the known pilot-aided single-user channel estimation methods to these systems is prohibited, requiring much more new investigations. The decentralized and centralized channel estimation algorithms are developed according to different multiuser scenarios. Optimal multiuser pilots are proposed, especially for centralized estimation methods with respect to the mean square error (MSE) of LS channel estimate. In addition, channel tracking algorithms are represented in terms of individual user's channels.

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.

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.

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 Adaptive Blind Channel Estimation for MIMO-OFDM Systems Based on PARAFAC

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Ruo-Nan Yang ◽  
Wei-Tao Zhang ◽  
Shun-Tian Lou
Keyword(s):  
Channel Estimation ◽  
Cost Function ◽  
Orthogonal Frequency Division Multiplexing ◽  
Weighted Least Squares ◽  
Estimation Method ◽  
Blind Channel Estimation ◽  
Ofdm Systems ◽  
Blind Channel ◽  
Mimo Ofdm ◽  
The Cost

In order to track the changing channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, it is prior to estimate channel impulse response adaptively. In this paper, we proposed an adaptive blind channel estimation method based on parallel factor analysis (PARAFAC). We used an exponential window to weight the past observations; thus, the cost function can be constructed via a weighted least squares criterion. The minimization of the cost function is equivalent to the decomposition of third-order tensor which consists of the weighted OFDM data symbols. To reduce the computational load, we adopt a recursive singular value decomposition method for tensor decomposition; then, the channel parameters can be estimated adaptively. Simulation results validate the effectiveness of the proposed algorithm under diverse signalling conditions.

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