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 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.

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 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 Performance of Channel Estimation Technique in MIMO-OFDM System Using mPSK Modulation

2013 ◽  
Vol 1 (1) ◽  
Author(s):  
Musayyanah . ◽  
Yoedy Moegiharto ◽  
I Gede Puja Astawa
Keyword(s):  
Channel Estimation ◽  
System Performance ◽  
Orthogonal Frequency Division Multiplexing ◽  
Minimum Mean Square Error ◽  
Estimation Technique ◽  
Ofdm System ◽  
Rate Transmission ◽  
Mimo Ofdm ◽  
Ls Estimator ◽  
Pilot Channel

Multicarrier modulation technique as Orthogonal Frequency Division Multiplexing (OFDM) is able to vanishIntersymbol Interferences (ISI) caused by multipathchannel. Merging with multi- antenna transmission techniques such asMIMO become MIMO- OFDM system is able to improve (data rate transmission)the transmission of data and capacity of the system. Pilot channel estimation technique with the algorithm Linear Minimum Mean Square Error (LMMSE) with modulation m-PSK is applied in this study. The results obtained in the form of graphs BER against EbNo which shows that the system performance with LMMSEestimator has a different gain for QPSKmodulation better about 0.75 dB, for 8 PSKmodulation is about 1.5 dB and for 16 PSKmodulation around 1 dB compare to LS estimator. Number of the largest antenna both in the transmitter and receiver produce the best system performance. Observation for QPSKmodulation shows a scheme transmitter- receiver antenna 4x2 having gain approximately 9 dB better than the number of the lowest transmitter antenna(1x2). For scheme 4x4 shows gain around 8,5 dB than the number of the lowest receiver antenna.Keywords:MIMO, OFDM,LS, LMMSE, MPSK.

scholarly journals Model-based compressed sensing algorithms for MIMO- OFDM channel estimation

2018 ◽  
Vol 7 (2.4) ◽  
pp. 5
Author(s):  
P N. Jayanthi ◽  
S Ravishankar
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Orthogonal Frequency Division Multiplexing ◽  
Wireless Channel ◽  
Least Square ◽  
Modulation Scheme ◽  
Mean Square ◽  
Least Mean Square ◽  
Model Based ◽  
Mimo Ofdm

High data rates on the wireless channel can be achieved by combining orthogonal frequency division multiplexing (OFDM) with multiple input multiple output (MIMO) communication modulation scheme. MIMO-OFDM system impulse response of the channel is approximately sparse. Sparse channelestimation can be done using Compressive Sensing (CS) techniques. In this paper, a low complexity model based CoSaMp Compressive Sensing (CS) algorithm with conventional tools namely Least Square (LS) and Least Mean Square (LMS) are used for MIMO-OFDM channel estimation. Simulation results show amodel based CoSaMP for MIMO-OFDM channel estimation with LMS tool the Normalized Mean Square Error(NMSE)reduced by 34%with very reduced complexity.

An Improved SVD-LMMSE Channel Estimation Algorithm of LTE System

2013 ◽  
Vol 756-759 ◽  
pp. 862-866
Author(s):  
Yang Zhou ◽  
Hong Cheng Dong ◽  
Xiao Wen Li
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Least Square ◽  
Superior Performance ◽  
Estimation Algorithms ◽  
Dct Transform ◽  
Value Decomposition

This paper first introduces the MIMO-OFDM (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) system model, and then studies several classical channel estimation algorithms: LS (Least Square) algorithm, LMMSE (Liner Minimum Mean-Square Error) algorithms and SVD-LMMSE (Singular value decomposition) algorithm. Finally, based on the DCT transform domain channel estimation, the original SVD-LMMSE algorithm has been improved. Theoretical analysis and simulation results show that: The improved SVD-LMMSE algorithm not only can reduce the complexity of the implementation, but also has more superior performance.

A Two-Way Relay Channel Estimation Method Based on Sparsity Adaptive Matching Pursuit Algorithm

2012 ◽  
Vol 263-266 ◽  
pp. 1037-1042
Author(s):  
Ju Rong Wang ◽  
Jin He Zhou
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Prior Information ◽  
Matching Pursuit ◽  
Minimum Mean Square Error ◽  
Estimation Method ◽  
Reconstruction Algorithm ◽  
Least Square ◽  
Estimation Methods ◽  
Relay Channel

To solve the problem that many existing two-way relay channel (TWRC) estimation methods require the sparse degree of the channel as prior information, we introduced a novel iterative greedy reconstruction algorithm based on compressed sensing (CS), called the sparisty adaptive matching pursuit (SAMP) to reconstruct the channel impulse response under orthogonal frequency division multiplexing (OFDM) system. The most innovative feature of SAMP is its capability of channel reconstruction without prior information of the sparse degree. Under the same condition we compared the algorithm with the other channel estimation methods including conventional least square (LS) algorithm, minimum mean square error (MMSE) algorithm and a orthogonal matching pursuit (OMP) algorithm based on CS. Simulation results show that the proposed algorithm has a better estimation performance and the algorithm improves the utilization of communication resources such as spectrum and energy. Thus it is suitable for real application.

scholarly journals Analisa Simulasi Performansi Penggunaan Orthogonal Frequency Division Multiplexing Pada Sistem Digital Video Broadcasting-Terrestrial

2017 ◽  
Vol 3 (1) ◽  
pp. 65
Author(s):  
Dian Widi Astuti
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multipath Fading ◽  
Block Type ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Digital Video Broadcasting ◽  
Video Broadcasting ◽  
Guard Interval ◽  
Pilot Channel

Orthogonal Frequency Division Multiplexing (OFDM) merupakan suatu teknik transmisi yang menggunakan beberapa buah frekuensi pembawa (multicarrier) dalam satu saluran dimana setiap frekuensi pembawa tersebut saling orthogonal (tegak lurus). OFDM banyak dipakai untuk sistem komunikasi wireless mengingat kemampuan dari OFDM mengatasi multipath fading yang menyebabkan terjadinya intersymbol interference (ISI). Dampak dari ISI tersebut adalah penerima tidak dapat membaca sandi informasi dengan benar sehingga mengurangi performasi sistem komunikasi digital. Cara OFDM mengatasi ISI adalah dengan menggandakan simbol dan menambah simbol secara periodik yang digunakan sebagai guard interval. Penambahan dari guard band yang terlalu lebar bisa mengurangi throughput data yang dikirimkan. Fading juga menyebabkan amplitudo dan phasa berfluktuatif sehingga cara untuk mengatasinya adalah estimasi kanal (Channel Estimation) dengan menyisipkan simbol pilot pada pengiriman frame OFDM sehingga penerima dapat memperkirakan karakteristik kanal dan dapat mengembalikan data yang terkirim. CE terdiri atas comb-type pilot channel estimation dan block-type pilot channel estimation. DVB-T sebagai penyiaran televisi digital terestrial juga memakai OFDM dengan skema modulasi OFDM tambahan yaitu berupa pilot simbol atau yang lebih dikenal dengan estimasi kanal (Channel Estimation). Mengingat jumlah subcarrier dari DVB-T cukup besar jika dibandingkan dengan aplikasi lain yang menggunakan OFDM maka perlu dilakukan sebuah penelitian tentang analisa performasi penggunaan OFDM untuk sistem DVB-T terhadap perubahan guard interval, modulasi dan penggunaan kanal pada estimasi kanal tersebut.

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