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Journal Article

Channel Estimation in OFDM Mobile Wireless Channel Using ZF, ZF-SIC, ZF-SIC-OO, MMSE, MMSE-SIC, MMSE-SIC-OO, LS & ALSMME Method

TL;DR: In this paper antenna 2x2 configuration is used and a Novel algorithm namely ALMMSE is proposed that reduce Bit Error Rate (BER) by using spatial multiplexing and Signal to Noise Ratio (SNR) curve of equalizer exceeds that of ZF, ZFSIC, ZF-SIC-OO, MMSE , MMSE-S IC, MMSA, ML, LS and AlMMSE equalizer.
Abstract: Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have emerged as wide application technology in wireless communication systems for increasing data rate and the system performance. The effect of fading & interference can be reduced to increase the capacity of the link. MIMO systems uses multiple (input) Transmit and multiple (output) Receive antennas which exploit the multipath propagation in the rich scattering environment. The matrix channel plays very pivotal role in the throughput of a MIMO link since the modulation, data rate, power allocation & the antenna weights are the various dependent parameters on the channel gain. When data rate is been transmitted at high bit rate, the channel impulse response can be extended over many symbol periods which leads to Inter-Symbol Interference (ISI). ISI always causing an issue for signal recovery in wireless communication. In order to reduce complexity of MIMO system, various detection algorithm such as Zero Forcing (Z
Citations
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Journal Article
TL;DR: In this paper antenna configuration is used and QPSK modulation is treated here for simulation purpose, and signal-noise ratio (SNR) curve of Constant modulus algorithm(CMA) equalizer exceeds that of ZF, MMSE and ML equalizer.
Abstract: Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing(OFDM) systems have recently emerged as key technology in wireless communication systems for increasing data rate and system performance. The effect of fading and interference can be combated to increase the capacity of the link. MIMO systems uses Multiple Transmit and Multiple Receive antennas which exploit the multipath propagation in rich scattering environment. The matrix channel plays a pivotal role in the throughput of a MIMO link since the modulation, data rate, power allocation and antenna weights are dependent on the channel gain. When data rate is transmitted at high bit rate, the channel impulse response can extend over many symbol periods which leads to Inter-Symbol Interference(ISI). ISI always caused an issue for signal recovery in wireless communication. In order to reduce the complexity of MIMO system, various detection algorithm such as Zero forcing(ZF), Minimum Mean Square Error(MMSE), Maximum Likelihood(ML) and a novel algorithm namely Constant Modulus Algorithm(CMA) are proposed that reduce bit error rate(BER) via spatial multiplexing. QPSK modulation is treated here for simulation purpose.Simulations are done by MatLab that shows BER vs. signal-noise ratio (SNR) curve of Constant modulus algorithm(CMA) equalizer exceeds that of ZF, MMSE and ML equalizer. In this paper antenna configuration is used.

2 citations

Proceedings ArticleDOI
12 Apr 2019
TL;DR: This work proposes and study a new method based on μ-Law companding type and Polar Codes to reduce PAPR values in a MIMO-OFDM system that operates with less complexity and outperforms the most well-known methods.
Abstract: MIMO-OFDM is a method adopted by new highspeed communications technologies such as IEEE802.11, IEEE 802.16 and 4G. Among the advantages of MIMO-OFDM, its ability to increase the transmission rate, and its adaptation to multipath channel with fading. Unfortunately the signals modulated by the OFDM technique generate high values of Peak-to-Average Power Ratio (PAPR). To solve this major drawback, several techniques have been proposed in literature. Among others, we find those that combine coding and companding. In this context we propose and study a new method based on μ-Law companding type and Polar Codes to reduce PAPR values in a MIMO-OFDM system. In order to evaluate the performances of our method in terms of PAPR and BER, several simulations are performed taking into consideration parameters related to coding and companding rates, and the number of sub carriers. The plotted curves show that the results are very significant; indeed, firstly our method achieves a gain of 8 dB in terms of PAPR by ensuring a good compromise in term of BER thanks to the use of the Polar Codes. Secondly our method operates with less complexity and outperforms the most well-known methods.

1 citations


Cites methods from "Channel Estimation in OFDM Mobile W..."

  • ...BER of MIMO OFDM FFT=256,R=1/2, μ=[10,10,150,255]....

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  • ...It is a promising technique to reduce the PAPR of the OFDM system used in the works [4-12]....

    [...]

  • ...In Fig 8 we compare our work with the PTS method with different sub-block values (2, 4 and 8) introduced in the article [10]....

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References
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Book
01 Jan 1986
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Abstract: Background and Overview. 1. Stochastic Processes and Models. 2. Wiener Filters. 3. Linear Prediction. 4. Method of Steepest Descent. 5. Least-Mean-Square Adaptive Filters. 6. Normalized Least-Mean-Square Adaptive Filters. 7. Transform-Domain and Sub-Band Adaptive Filters. 8. Method of Least Squares. 9. Recursive Least-Square Adaptive Filters. 10. Kalman Filters as the Unifying Bases for RLS Filters. 11. Square-Root Adaptive Filters. 12. Order-Recursive Adaptive Filters. 13. Finite-Precision Effects. 14. Tracking of Time-Varying Systems. 15. Adaptive Filters Using Infinite-Duration Impulse Response Structures. 16. Blind Deconvolution. 17. Back-Propagation Learning. Epilogue. Appendix A. Complex Variables. Appendix B. Differentiation with Respect to a Vector. Appendix C. Method of Lagrange Multipliers. Appendix D. Estimation Theory. Appendix E. Eigenanalysis. Appendix F. Rotations and Reflections. Appendix G. Complex Wishart Distribution. Glossary. Abbreviations. Principal Symbols. Bibliography. Index.

16,062 citations

Journal ArticleDOI
TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
Abstract: (1995). Fundamentals of Statistical Signal Processing: Estimation Theory. Technometrics: Vol. 37, No. 4, pp. 465-466.

14,342 citations

Journal ArticleDOI
TL;DR: The Fourier transform data communication system is described and the effects of linear channel distortion are investigated and a differential phase modulation scheme is presented that obviates any equalization.
Abstract: The Fourier transform data communication system is a realization of frequency-division multiplexing (FDM) in which discrete Fourier transforms are computed as part of the modulation and demodulation processes. In addition to eliminating the bunks of subcarrier oscillators and coherent demodulators usually required in FDM systems, a completely digital implementation can be built around a special-purpose computer performing the fast Fourier transform. In this paper, the system is described and the effects of linear channel distortion are investigated. Signal design criteria and equalization algorithms are derived and explained. A differential phase modulation scheme is presented that obviates any equalization.

2,507 citations

Journal ArticleDOI
TL;DR: It is shown, and confirmed by simulation, that to maintain signal-to-interference ratios of 20 dB or greater for the OFDM carriers, offset is limited to 4% or less of the intercarrier spacing.
Abstract: This paper discusses the effects of frequency offset on the performance of orthogonal frequency division multiplexing (OFDM) digital communications. The main problem with frequency offset is that it introduces interference among the multiplicity of carriers in the OFDM signal. It is shown, and confirmed by simulation, that to maintain signal-to-interference ratios of 20 dB or greater for the OFDM carriers, offset is limited to 4% or less of the intercarrier spacing. Next, the paper describes a technique to estimate frequency offset using a repeated data symbol. A maximum likelihood estimation (MLE) algorithm is derived and its performance computed and compared with simulation results. Since the intercarrier interference energy and signal energy both contribute coherently to the estimate, the algorithm generates extremely accurate estimates even when the offset is far too great to demodulate the data values. Also, the estimation error depends only on total symbol energy so it is insensitive to channel spreading and frequency selective fading. A strategy is described for initial acquisition in the event of uncertainty in the initial offset that exceeds 1/2 the carrier spacing, the limit of the MLE algorithm. >

2,475 citations

Proceedings ArticleDOI
25 Jul 1995
TL;DR: The authors present the MMSE and LS estimators and a method for modifications compromising between complexity and performance and the symbol error rate for a 18-QAM system is presented by means of simulation results.
Abstract: The use of multi-amplitude signaling schemes in wireless OFDM systems requires the tracking of the fading radio channel. The paper addresses channel estimation based on time-domain channel statistics. Using a general model for a slowly fading channel, the authors present the MMSE and LS estimators and a method for modifications compromising between complexity and performance. The symbol error rate for a 18-QAM system is presented by means of simulation results. Depending upon estimator complexity, up to 4 dB in SNR can be gained over the LS estimator.

1,647 citations