Channel estimation in MIMO-OFDM spatial multiplexing using Least Square method

2011 ◽  
Author(s):  
Risanuri Hidayat ◽  
Anggun Fitrian Isnawati ◽  
Budi Setiyanto
Keyword(s):  
Channel Estimation ◽  
Least Square Method ◽  
Spatial Multiplexing ◽  
Least Square ◽  
Mimo Ofdm

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 Channel Estimation in MIMO-OFDM System

2014 ◽  
Vol 14 (2) ◽  
pp. 97-102
Author(s):  
SR Aryal ◽  
H Dhungana
Keyword(s):  
Channel Estimation ◽  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Multipath Fading ◽  
Spatial Multiplexing ◽  
Diversity Gain ◽  
Estimation Methods ◽  
Mean Square ◽  
Ofdm System ◽  
Mimo Ofdm

There are no limit of human desire, so day by day we need much higher data speed to facilitate our need but every physical resource like frequency band, transmit signal strength are finite. Within the given limited resource, higher data speed is accomplished by new proficiency called Multiple Input Multiple Output (MIMO), Orthogonal Frequency Division Multiplexing (OFDM) system. MIMO-OFDM fulfills the high data rate requirement through spatial multiplexing gain and improved link reliability due to antenna diversity gain. With this technique, both interference reduction and maximum diversity gain are achieved by increasing number of antennae on either side. Received signal in MIMO-OFDM system is usually distorted by multipath fading. In order to recover the transmitted signal correctly, channel effect must be estimated and repaired at receiver. In this paper the performance evaluating parameter mean square error and symbol error rate of least square error, minimum mean square error and DFT based channel estimation methods are estimated and appropriate solution is recommended. Furthermore, comparison among their characteristics is simulated in MATLAB and useful conclusion is delineated. DOI: http://dx.doi.org/10.3126/njst.v14i2.10421   Nepal Journal of Science and Technology Vol. 14, No. 2 (2013) 97-102

Performance of Pilot-Aided 3D- OFDM Channel Estimation using Different Antenna Configurations

2017 ◽  
Vol 8 (1) ◽  
pp. 77
Author(s):  
Dinesh N. Bhange ◽  
Chandrashekhar G. Dethe
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Rayleigh Fading ◽  
Minimum Mean Square Error ◽  
Vertical Direction ◽  
Performance Comparison ◽  
Least Square ◽  
Digital Video Broadcasting ◽  
Video Broadcasting ◽  
Mimo Ofdm

<p>This paper aims, a 3D-Pilot Aided Multi-Input Multi-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) Channel Estimation (CE) for Digital Video Broadcasting -T2 (DVB-T2)for the 5 different proposed block and comb pilot patterns model and performed on different antenna configuration. The effects of multi-transceiver antenna on channel estimation are addressed with different pilot position in frequency, time and the vertical direction of spatial domain framing. This paper first focus on designing of 5- different proposed spatial correlated pilot pattern model with optimization of pilot overhead. Then it demonstrates the performance comparison of Least Square (LS) &amp;Linear Minimum Mean Square Error (LMMSE), two linear channel estimators for 3D-Pilot Aided patterns on different antenna configurations in terms of Bit Error Rate. The simulation results are shown for Rayleigh fading noise channel environments. Also, 3x4 MIMO configuration is recommended as the most suitable configuration in this noise channel environments.</p>

scholarly journals Channel estimation for intelligent reflecting surface aided multi-user MISO terahertz system

2020 ◽  
Vol 13 (2) ◽  
pp. 51-60
Author(s):  
Wenjie Chen ◽  
Zhi Chen ◽  
Xinying Ma
Keyword(s):  
Channel Estimation ◽  
Least Square Method ◽  
Estimation Problem ◽  
Least Square ◽  
Single Output ◽  
Main Challenge ◽  
Estimation Scheme ◽  
Promising Application ◽  
Stage 1 ◽  
Reflecting Surface

Intelligent reflecting surface (IRS) is considered as a promising application in terahertz (THz) communications since it is able to enhance the THz communication with no additional power consumptions. In this letter, we consider the channel estimation problem for an IRS-aided THz multi-user multi-input single-output (MISO) system with lens antenna array. The main challenge of the problem is that we need to estimate multiple channels and some of the channels are cascaded. To deal with the problem, we propose a two-stage channel estimation scheme, where we set different IRS modes to estimate different channels for each stage. In stage 1, we set the IRS to an absorbing mode and estimate the channel without IRS. Removing the influence of the prior estimated channel, in stage 2, we estimate the channel with IRS by setting the IRS to a perfect reflecting mode. And we decompose the total channel estimation problem into a series of independent problems, where we estimate each independent channel component with a least square method.

scholarly journals Forward and backward RLS-DDCE processing in MIMO-OFDM spatial multiplexing receivers

2010 ◽  
Vol 8 ◽  
pp. 101-107
Author(s):  
M. Muxfeldt ◽  
P. Beinschob ◽  
U. Zölzer
Keyword(s):  
Channel Estimation ◽  
Ldpc Code ◽  
Error Rates ◽  
Spatial Multiplexing ◽  
Recursive Least Squares ◽  
Likelihood Ratios ◽  
Novel Approach ◽  
Turbo Principle ◽  
Channel Information ◽  
Mimo Ofdm

Abstract. In this paper we present a novel approach in frequency domain channel estimation technique. Our proposal is based on the recursive least squares (RLS) algorithm combined with the decision making process called decision directed channel estimation (RLS-DDCE). The novelty and key concept of this technique is the block-wise causal and anti-causal RLS processing that yields two independent processing of RLS along with the associated decisions. Due to the implemented low density parity check (LDPC) code the receiver operates with soft information, which enables us to introduce a new modification of the Turbo principle as well as simple addition of the a-posteriori log-likelihood ratios (LLRs). Although the computational complexity is increased by both of our approaches, the latter is relatively less complex than the earlier. Simulation results show that these implementations outperform the simple RLS-DDCE algorithm and yield lower bit error rates (BER) and more accurate channel information.

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