Journal articles: 'Minimum Mean Squared Error (MMSE)'

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Namba, Akio. "PMSE PERFORMANCE OF THE BIASED ESTIMATORS IN A LINEAR REGRESSION MODEL WHEN RELEVANT REGRESSORS ARE OMITTED." Econometric Theory 18, no. 5 (July 17, 2002): 1086–98. http://dx.doi.org/10.1017/s0266466602185033.

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In this paper, we consider a linear regression model when relevant regressors are omitted. We derive the explicit formulae for the predictive mean squared errors (PMSEs) of the Stein-rule (SR) estimator, the positive-part Stein-rule (PSR) estimator, the minimum mean squared error (MMSE) estimator, and the adjusted minimum mean squared error (AMMSE) estimator. It is shown analytically that the PSR estimator dominates the SR estimator in terms of PMSE even when there are omitted relevant regressors. Also, our numerical results show that the PSR estimator and the AMMSE estimator have much smaller PMSEs than the ordinary least squares estimator even when the relevant regressors are omitted.

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Batra, Deepak, Sanjay Sharma, and Amit Kumar Kohli. "Improved Parameter Estimation for First-Order Markov Process." Research Letters in Signal Processing 2009 (2009): 1–2. http://dx.doi.org/10.1155/2009/186250.

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This correspondence presents a linear transformation, which is used to estimate correlation coefficient of first-order Markov process. It outperforms zero-forcing (ZF), minimum mean-squared error (MMSE), and whitened least-squares (WTLSs) estimators by controlling output noise variance at the cost of increased computational complexity.

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Matsumoto, Tad, and Aihua Hong. "On the MMSE Criterion for Space-Time Coded Signaling in the Presence of Unknown Interference." Research Letters in Communications 2007 (2007): 1–3. http://dx.doi.org/10.1155/2007/83283.

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The primary goal of this letter is to provide comparative assessments to the two cases where different criteria are used in joint over antenna minimum mean squared error (JA-MMSE) spatial filtering for space-time coded systems in the presence of unknown interference. It is shown that additional constraints to preserve the space-time coded signal structure in JA-MMSE spatial filtering place floor in bit error rate (BER) performance, while imposing no additional constraint places no error floor.

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YANG, Janghoon. "Analysis on Sum Rate of Random Beamforming with Minimum Mean Squared Error (MMSE) Receive Beamforming." IEICE Transactions on Communications E95.B, no. 9 (2012): 3033–37. http://dx.doi.org/10.1587/transcom.e95.b.3033.

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Dubey, Neha, and Ankit Pandit. "A Comprehensive Review on Channel Estimation in OFDM System." SMART MOVES JOURNAL IJOSCIENCE 5, no. 3 (March 28, 2019): 6. http://dx.doi.org/10.24113/ijoscience.v5i3.201.

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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.

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Mvodo Martin Paulin, Zanga, Koko Same Louis Christian, and Essiben Dikoundou Jean-François. "Linear precoder optimization of spectral efficiency of time division duplex hyper MIMO system with pilot contamination." Indonesian Journal of Electrical Engineering and Computer Science 29, no. 3 (March 1, 2023): 1520. http://dx.doi.org/10.11591/ijeecs.v29.i3.pp1520-1528.

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Our work is developed in context of studing Massive MIMO in a 5G context. The aim is to optimize spectral efficiency of several users hyper MIMO system during Uplink communication in a multi-cell contaminated pilot environment, using a new type of precoders called single cell-minimum mean square eroor (S-MMSE) and multicell-minimum mean square eroor (MMMSE). Indeed, we address two key and well-known issues of massive multiuser MIMO (MU-MIMO) environments in a test-driven development (TDD) operation scheme, namely acquisition of uplink channel state information (UL) and optimisation of the bit stream per unit frequency, the spectral efficiency (SE). From a practical point of view, these two notions are inclusively linked. Indeed, a very good channel estimation leads to a better spectral efficiency. In our approcah, we derive from the minimum mean square error estimator (MMSE) to two new types of precoders that can operate in a multicell environment with a contaminated pilot sequence, namely the SMMSE and the M-MMSE. A comparative study performance of these classical precoders such as regulated zero forcing (RZF), ZF (Zero Forcing) and MR (Minimum Ratio) encountered in multi-antenna processing shows an improvement of nearly 51% in terms of system gain and spectral efficiency.

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Akande, Damilare O., Zachaeus K. Adeyemo, Olakunle O. Arowolo, Olasunkanmi F. Oseni, and Oluwole O. Obanisola. "Hybridization of zero forcing-minimum mean square error equalizer in multiple input multiple output system." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 2 (May 1, 2022): 836. http://dx.doi.org/10.11591/ijeecs.v26.i2.pp836-845.

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Transmission of high data rate over multipath environment is associated with many wireless applications. However, this transmission results in high delay which leads to ISI distortion and causes high error. The existing LE in MIMO systems such as ZF equalizer used in addressing this problem reduces the ISI distortion completely but results in noise amplification. Likewise, MMSE equalizer only reduces the noise but cannot eliminate ISI. Therefore, this paper proposed a hybrid LE for Wi-Fi over Weibull fading channel. The hybridized ZF-MMSE equalizer was developed using conventional ZF and MMSE equalizers. Digital transmitted signal propagated over Weibull fading channel is received at the receiver through multiple antennas and then combined using MRC. The combined signal is then equalized using hybrid ZF-MMSE to eliminate both the ISI and the amplified noise. The developed model was simulated in MATLAB software environment and evaluation was performed using BER and Pout. The results obtained revealed that the hybrid ZF-MMSE equalizer gave better performance over existing equalizers in a MIMO system. Therefore, the proposed equalizer will help improve the performance of the Wi-Fi technology.

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Alqatawneh, Ali, Luae Al-Tarawneh, and Ziyad Almajali. "Indexed-channel estimation under frequency and time-selective fading channels in high-mobility systems." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 3 (June 1, 2023): 2865. http://dx.doi.org/10.11591/ijece.v13i3.pp2865-2875.

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Index modulation (IM) techniques have been employed in different communication systems to improve bandwidth efficiency by carrying additional information bits. In high-mobility communication systems and under both time-selective and frequency-selective fading channels with Doppler spread, channel variations can be tracked by employing pilot-aided channel estimation with minimum mean-squared error estimation. However, inserting pilot symbols among information symbols reduces the system's spectral efficiency in pilot-aided channel estimation schemes. We propose pilot-aided channel estimation with zero-pilot symbols and an energy detection scheme to tackle this issue. Part of the information bit-stream is conveyed by the indices of zero-pilot symbols leading to an increase in the system's spectral efficiency. We used an energy detector at the receiver to detect the transmitted zero-pilot symbols. This paper examines the impacts of diversity order on the zero-pilot symbol detection error probability and the mean-squared of error estimation. The impacts of pilot symbols number and the zero-pilot symbol number on the mean-squared error of the minimum mean-squared error (MMSE) estimator and the system error performance are also investigated in this paper.

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Li, Jiao Jun, An Zhi Chen, Ting Zhang, and Li Yun Su. "The Simulation Analysis of Channel Estimation Based on LS and MMSE Alrorithms." Advanced Materials Research 765-767 (September 2013): 2781–84. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.2781.

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Due to the complex propagation caused by the multipath effect, the time-varying characteristics, the frequency selective fading and other factors of the wireless communication, consequently, the channel estimation is an important component in the receiving system with high performance. In this paper, comparisons with regard to the mean-square error and bit error rate are made in the WPDM-CDMA system based on two typical channel estimation algorithms, including the least squares error (LS) algorithm and the minimum mean-square error (MMSE) algorithm.

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Kadhim, Dheyaa Jasim, Muna Hadi Saleh, and Sadiq Jassim Abou-Loukh. "Evaluation of massive multiple-input multiple-output communication performance under a proposed improved minimum mean squared error precoding." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 2 (June 1, 2023): 984. http://dx.doi.org/10.11591/ijai.v12.i2.pp984-994.

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The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy- issue efficiency strategy is known as minimum mean squared error (MMSE) implementation degrades the performance of a downlink massive MIMO energy-efficiency scheme, so some improvements are adding for this precoding scheme to improve its workthat is called our proposal solution as a proposed improved MMSE precoder (PIMP). The energy efficiency (EE) study has also taken into mind drastically lowering radiated power while maintaining high throughput and minimizing interference issues. We further find the tradeoff between spectral efficiency (SE) and EE although they coincide at the beginning but later their interests become conflicting and divergent then leading EE to decrease so gradually while SE continues increasing logarithmically. The results achieved that for a single-cellular massive MU-MIMO downlink model, our PIMP scheme is the appropriate scenario to achieve higher precoding performance system. Furthermore, both maximum ratio transmission (MRT) and PIMP are suitable for performance improvement in massive MIMO results of EE and SE. So, the main contribution comes with this work that highest EE and SE are belong to use a PIMP which performs better appreciably than MRT at bigger ratio of number of antennas to the number of the users.

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Alzamil, A. A. "Assessment of Uplink Massive MIMO in Scattering Environment." Engineering, Technology & Applied Science Research 10, no. 5 (October 26, 2020): 6290–93. http://dx.doi.org/10.48084/etasr.3743.

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This paper investigates the performance of massive MIMO systems under the effect of multipath propagation environment. Linear Minimum Mean Squared Error (MMSE) is considered to assess the performance of BPBK/OFDM based uplink massive MIMO transmission. Bit Error Rate (BER) and channel capacity in Non Line Of Site (NLOS) multipath fading environment are presented. The results show a correlation between the number of antennas and the performance of the system.

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Jeong, Jae Jin. "A Minimum Mean-Square-Error (MMSE) Decoder for Quasi-Orthogonal Space–Time Block Code." Electronics 8, no. 7 (June 27, 2019): 732. http://dx.doi.org/10.3390/electronics8070732.

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The quasi-orthogonal space–time block code (QO-STBC) was introduced to achieve a full transmission rate for the four antennas system. In this paper, a decoding method for the QO-STBC is proposed to improve the bit-error-rate (BER) and to solve a rank-deficient problem. The proposed algorithm is based on the minimum mean-square-error (MMSE) technique. To overcome the implementation problem from the MMSE, an estimation method of the noise variance is developed in this paper. The proposed algorithm is implemented without matrix inversion, therefore, the proposed algorithm achieves a better BER than the conventional algorithms, as it has a low computational complexity. The simulation results show the low BER of the proposed algorithm in a Rayleigh fading channel.

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Morsy, T., J. Götze, and H. Nassar. "Convex programming for detection in structured communication problems." Advances in Radio Science 8 (December 22, 2010): 307–12. http://dx.doi.org/10.5194/ars-8-307-2010.

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Abstract. The generalized Minimum Mean Squared Error (GMMSE) detector has a bit error rate performance, which is similar to the MMSE detector. The advantage of the GMMSE detector is that it does not require the knowledge of the noise power. However, the computational complexity of the GMMSE detector is significantly higher than the computational complexity of the MMSE detector. In this paper, the complexity of the GMMSE detector is reduced by taking into account the structure of the system matrix (Toeplitz). Furthermore, by using circular approximation of the structured system matrix an approximate GMMSE detector is presented, whose computational complexity is only slightly higher than MMSE, i.e.~only an iterative gradient descent algorithm based on the inversion of diagonal matrices is additionally required.

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Costa, Bruno Felipe, and Taufik Abrão. "MIMO Precoding for Correlated Fading Channels." Journal of Circuits, Systems and Computers 25, no. 05 (February 25, 2016): 1650041. http://dx.doi.org/10.1142/s0218126616500419.

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This contribution proposes a precoder-decoder design aiming to improve the performance of multiple-input–multiple-output (MIMO) detectors under correlated fading channels. The MIMO detection principle namely minimum mean squared error (MMSE) detector is analyzed under such channel condition. The proposed approach deploys the channel state information (CSI) aiming to estimate the level of spatial correlation channel, namely normalized correlation index [Formula: see text] and uses this information to improve the MIMO system performance. Furthermore, the impact of the [Formula: see text] estimation errors on the performance, as well the performance degradation for different levels of correlation have been analyzed and compared with the classical MMSE-MIMO detector operating under uncorrelated channels and perfect channel estimation.

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Chen, Hsiao-Hwa, and Zhi-Qiang Liu. "Asynchronous block-based minimum mean square error (B-MMSE) CDMA multi-user detection." International Journal of Communication Systems 11, no. 6 (November 1998): 395–401. http://dx.doi.org/10.1002/(sici)1099-1131(199811/12)11:6<395::aid-dac381>3.0.co;2-y.

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Shatti, Ahmed Hussein, and Ehab AbdulRazzaq Hussein. "Low-complex Bayesian estimator for imperfect channels in massive muti-input multi-output system." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (December 1, 2022): 6261. http://dx.doi.org/10.11591/ijece.v12i6.pp6261-6271.

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Motivated by the fact that the complexity of the computations is one of the main challenges in large multiple input multiple output systems, known as massive multiple-input multiple-output (MIMO) systems, this article proposes a low-complex minimum mean squared error (MMSE) Bayesian channel estimator for uplink channels of such systems. First, we have discussed the necessity of the covariance information for the MMSE estimator and how their imperfection knowledge can affect its accuracy. Then, two reduction phases in dimension and floating-point operations have been suggested to reduce its complexity: in phase 1, eigenstructure reduction for channel covariance matrices is implemented based on some truncation rules, while in phase 2, arithmetic operations reduction for matrix multiplications in the MMSE equation is followed. The proposed procedure has significantly reduced the complexity of the MMSE estimator to the first order O(M), which is less than that required for the conventional MMSE with O(M3) in terms of matrix dimension. It has been shown that the estimated channels using our proposed procedure are asymptotically aligned and serve the same quality as the full-rank estimated channels. Our results are validated by averaging the normalized mean squared error (NMSE) over a length of 500 sample realizations through a Monte Carlo simulation using MATLAB R2020a.

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Soubhi Hussein, Yaseein, Mohamad Yusoff Alias, Ayad A. Abdulkafi, Nazaruddin Omar, and Mohd Kamarulzamin Bin Salleh. "Expectation-maximization-based channel estimation algorithm for OFDM visible light communication systems." International Journal of Engineering & Technology 7, no. 4 (September 24, 2018): 2638. http://dx.doi.org/10.14419/ijet.v7i4.15994.

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The tremendous growth of indoor communication requires increased capacity and appropriate quality of services. Visible light communica-tion (VLC) is a green technology that shows great promise in terms of its ability to meet the demand for communication services. Orthogo-nal frequency division multiplexing (OFDM) enables VLC to provide a higher data rate and to combat inter-symbol interference. However, an accurate and efficient channel estimation method is needed for coherent demodulation at the receiver end of an OFDM system. In this paper, a new algorithm for OFDM-based VLC systems is proposed. The algorithm is based on expectation maximization and is called the expectation maximization for visible light communication (EM-VLC) algorithm. The algorithm is implemented to find the maximum-likelihood (ML) estimation of the channel impulse response and to find unknown parameters. In addition, a low-rank minimum mean square error (lr-MMSE) estimator algorithm is developed and its performance is compared with least squares (LS) and minimum mean square error (MMSE) estimators. The proposed EM-VLC algorithm improves the performance of OFDM VLC systems by significantly reducing the bit error rate (BER) and consequently increasing system throughput. The simulation results demonstrate that the EM-VLC algorithm outper-forms the three channel estimation algorithms, LS, MMSE and lr-MMSE.

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Wang, Xianan, Xiaoxiang Wang, Wenrong Gong, and Zijia Huang. "Generalized Block-Diagonalization Schemes for MIMO Relay Broadcasting Systems." International Journal of Digital Multimedia Broadcasting 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/305846.

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We propose two generalized block-diagonalization (BD) schemes for multiple-input multiple-output (MIMO) relay broadcasting systems with no channel state information (CSI) at base station. We first introduce a generalized zero forcing (ZF) scheme that reduces the complexity of the traditional BD scheme. Then the optimal power loading matrix for the proposed scheme is analyzed and the closed-form solution is derived. Furthermore, an enhanced scheme is proposed by employing the minimum-mean-squared-error (MMSE) criterion. Simulation results show that the proposed generalized MMSE scheme outperforms the other schemes and the optimal power loading scheme improves the sum-rate performance efficiently.

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Huang, Wei, and Yibin Zheng. "MMSE Reconstruction for 3D Freehand Ultrasound Imaging." International Journal of Biomedical Imaging 2008 (2008): 1–8. http://dx.doi.org/10.1155/2008/274164.

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The reconstruction of 3D ultrasound (US) images from mechanically registered, but otherwise irregularly positioned, B-scan slices is of great interest in image guided therapy procedures. Conventional 3D ultrasound algorithms have low computational complexity, but the reconstructed volume suffers from severe speckle contamination. Furthermore, the current method cannot reconstruct uniform high-resolution data from several low-resolution B-scans. In this paper, the minimum mean-squared error (MMSE) method is applied to 3D ultrasound reconstruction. Data redundancies due to overlapping samples as well as correlation of the target and speckle are naturally accounted for in the MMSE reconstruction algorithm. Thus, the reconstruction process unifies the interpolation and spatial compounding. Simulation results for synthetic US images are presented to demonstrate the excellent reconstruction.

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Patra, Jyoti P., and Poonam Singh. "Improved Signal Detection Techniques for QOSTBC System in Fast Fading Channel." Journal of Telecommunications and Information Technology 1 (March 31, 2020): 6–12. http://dx.doi.org/10.26636/jtit.2020.138019.

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Most existing quasi-orthogonal space time Block coding (QO-STBC) schemes have been developed relying on the assumption that the channel is at or remains static during the length of the code word symbol periods to achieve an optimal antenna diversity gain. However, in time-selective fading channels, this assumption does not hold and causes intertransmit-antenna-interferences (ITAI). Therefore, the simple pairwise maximum likelihood decoding scheme is not sufficient to recover original transmitted signals at the receiver side. To avoid the interferences, we have analyzed several signal detection schemes, namely zero forcing (ZF), two-step zero forcing (TS-ZF), minimum mean square error (MMSE), zero forcing - interference cancelation - decision feedback equalizer (ZF-IC-DFE) and minimum mean square error - interference cancelation { decision feedback equalizer (MMSE-IC-DFE). We have proposed two efficient iterative signal detection schemes, namely zero forcing - iterative interference cancelation - zero forcing { decision feedback equalization (ZF-IIC-ZF-DFE) and minimum mean square error - parallel interference cancelation - zero forcing – decision feedback equalization (MMSE-IIC-ZF-DFE). The simulation results show that these two proposed detection schemes significantly outperform all conventional methods for QOSTBC system over time selective channel.

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Hsiao-Hwa Chen and Zhi-Qiang Liu. "Zero-insertion adaptive minimum mean-square error (MMSE) receiver for asynchronous CDMA multiuser detection." IEEE Transactions on Vehicular Technology 50, no. 2 (March 2001): 557–69. http://dx.doi.org/10.1109/25.923067.

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Yu, F., J. W. Tao, and Y. M. Yang. "Robust air velocity estimation based on iterative implementation of Minimum Mean-Square Error (MMSE)." Aerospace Science and Technology 41 (February 2015): 167–74. http://dx.doi.org/10.1016/j.ast.2014.12.021.

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Alghoniemy, Masoud. "Regularized MIMO Decoders." Journal of Communications Software and Systems 5, no. 4 (December 20, 2010): 149. http://dx.doi.org/10.24138/jcomss.v5i4.201.

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In the Multi Input Multi Output (MIMO) antenna system, it is known that the Linear Minimum Mean Squared Error (MMSE) receiver is equivalent to Tikhonov regularization.Given that, we develop a family of generalized receivers based on regularization with different penalty functions that penalize the received symbols outside the convex hull of the modulating constellation. For illustration purposes we consider two types of penalty functions, the deadzone and infinity norm penalty functions. The proposed decoders have low complexity and can be implemented efficiently using convex optimization algorithms. Simulation results show that the proposed receivers outperform the MMSE receiver by as high as 5-dB at low Signal to Noise Ratio (SNR).

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Li, Ming, Xiafei Tang, Qichun Zhang, and Yiqun Zou. "Non-Gaussian Pseudolinear Kalman Filtering-Based Target Motion Analysis with State Constraints." Applied Sciences 12, no. 19 (October 4, 2022): 9975. http://dx.doi.org/10.3390/app12199975.

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For the bearing-only target motion analysis (TMA), the pseudolinear Kalman filter (PLKF) solves the complex nonlinear estimation of the motion model parameters but suffers serious bias problems. The pseudolinear Kalman filter under the minimum mean square error framework (PL-MMSE) has a more accurate tracking ability and higher stability compared to the PLKF. Since the bearing signals are corrupted by non-Gaussian noise in practice, we reconstruct the PL-MMSE under Gaussian mixture noise. If some prior information, such as state constraints, is available, the performance of the PL-MMSE can be further improved by incorporating state constraints in the filtering process. In this paper, the mean square and estimation projection methods are used to incorporate PL-MMSE with linear constraints, respectively. Then, the linear approximation and second-order approximation methods are applied to merge PL-MMSE with nonlinear constraints, respectively. Simulation results demonstrate that the constrained PL-MMSE algorithms result in lower mean square errors and bias norms, which demonstrates the superiority of the constrained algorithms.

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Swapna, Sonti. "Channel Estimation for MIMO Systems." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (January 31, 2022): 201–4. http://dx.doi.org/10.22214/ijraset.2022.39776.

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Abstract: A combination of multiple-input multiple-output (MIMO) systems and orthogonal frequency division multiplexing (OFDM) technologies can be employed in modern wireless communication systems to achieve high data rates and improved spectrum efficiency. For multiple input multiple output (MIMO) systems, this paper provides a Rayleigh fading channel estimation technique based on pilot carriers. The channel is estimated using traditional Least Square (LS) and Minimum Mean Square (MMSE) estimation techniques. The MIMO-OFDM system's performance is measured using the Bit Error Rate (BER) and Mean Square Error (MSE) levels. Keywords: MIMO, MMSE, Channel estimation, BER, OFDM

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Fan, Yu. "Study on Cooperative Multipoint Communication Precoding Algorithm under SLNR-MMSE Framework." Advances in Multimedia 2022 (July 31, 2022): 1–10. http://dx.doi.org/10.1155/2022/9457248.

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With the rapid growth of demand for wireless data services and the continuous introduction of new air interface technologies, mobile communication systems continue to face new challenges in supporting high-speed multimedia service transmission and achieving seamless coverage. In order to meet the requirements of the IMS system in terms of bandwidth, peak rate, communication throughput, etc., multiantenna enhancement technology and cooperative multipoint transmission technology have become research hotspots as key technologies. In the study of multiuser system, this paper focuses on the precoding technology based on noncode book, based on the minimum mean square error criterion and the maximum letter leakage noise ratio criterion, studies the precoding technology of different multiuser systems, expounds the collaborative multipoint transmission system, and makes a basic classification. The signal leakage-to-noise ratio precoding algorithm and the minimum mean square error precoding algorithm are analyzed in detail. In view of the shortcomings of these two algorithms, this paper takes the minimum sum of the total mean square error of the system as the optimization goal of the combinations of precoding and power allocation. The precoding algorithm of SLNR-MMSE is proposed. The simulation analysis shows that the proposed algorithm has certain advantages over other algorithms in terms of bit error rate and system capacity. It shows that this study is important for optimizing collaborative multipoint communication system.

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Gashtasbi, Ali, Mário Marques da Silva, Rui Dinis, and João Guerreiro. "On the Performance of LDPC-Coded Large Intelligent Antenna System." Applied Sciences 13, no. 8 (April 10, 2023): 4738. http://dx.doi.org/10.3390/app13084738.

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This article studies Large Intelligent Systems (LIS) along with Single Carrier with Frequency Domain Equalization (SC-FDE), utilizing Low-Density Parity-Check (LDPC). Four different receivers are studied in the scenarios described above, namely Equal Gain Combining (EGC), Maximum Ratio Combining (MRC), Zero Forcing (ZF), and Minimum Mean Squared Error (MMSE). The results of this article show that the use of LDPC codes leads to an improvement of performance by about 2 dB for a 4X25 LIS system and by 3 dB for a 4X225 LIS system, as compared to similar systems without LDPC codes. Moreover, for all simulations, the MMSE receiver achieves the best overall performance, while EGC performs the worst.

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Alqatawneh, Ali. "Orthogonal frequency division multiplexing system with an indexed-pilot channel estimation." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 2 (May 1, 2022): 808. http://dx.doi.org/10.11591/ijeecs.v26.i2.pp808-818.

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In this paper, we examine an orthogonal frequency division multiplexing (OFDM) system under imperfect channel conditions and pilot-insertion- based channel estimation. However, unlike conventional pilot-insertion-based channel estimation, some inserted pilot symbols are set to zero where the index of the zero-pilot symbols is employed to transmit extra data bits. In this paper, we employ a minimum mean squared error (MMSE) to detect transmitted pilot symbols; these symbols are then used to estimate channel coefficients. Furthermore, the impact of zero-pilot symbols on the mean-squared error of channel estimation and on system error performance is examined. Our findings show that the index of zero-pilot symbols can be used to improve system throughput by carrying extra information bits without harming channel estimation accuracy or degrading system error performance. Simulation results show that, at a high signal-to-noise ratio, the bit error rate for data bits transmitted via zero-pilot symbols index selection is lower than that of data bits transmitted over data subcarriers.

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Adebanjo, Ibukunoluwa Adetutu, Yekeen Olajide Olasoji, and Micheal Olorunfunmi Kolawole. "Space-Time Trellis Coding with Equalization." European Journal of Engineering Research and Science 4, no. 9 (September 27, 2019): 207–11. http://dx.doi.org/10.24018/ejers.2019.4.9.1412.

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As we are entering the 5G era, high demand is made of wireless communication. Consistent effort has been ongoing in multiple-input multiple-output (MIMO) systems, which provide correlation on temporal and spatial domain, to meet the high throughput demand. To handle the characteristic nature of wireless channel effectively and improve the system performance, this paper considers the combination of diversity and equalization. Space-Time trellis code is combined with single-carrier modulation using two-choice equalization techniques, namely: minimum mean squared error (MMSE) equalizer and orthogonal triangular (QR) detection. MMSE gives an optimal balance between noise enhancement and net inter-symbol interference (ISI) in the transmitted signal. Use of these equalizers provides the platform of investigating the bit error rate (BER) and the pairwise error probability (PEP) at the receiver, as well as the effect of cyclic prefix reduction on the receivers. It was found that the MMSE receiver outperforms the QR receiver in terms of BER, while in terms of PEP; the QR receiver outperforms the MMSE receiver. When a cyclic prefix reduction test was carried out on both receivers, it yields a significant reduction in BER of both receivers but has no significant effect on the overall performance.

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Adebanjo, Ibukunoluwa Adetutu, Yekeen Olajide Olasoji, and Micheal Olorunfunmi Kolawole. "Space-Time Trellis Coding with Equalization." European Journal of Engineering and Technology Research 4, no. 9 (September 27, 2019): 207–11. http://dx.doi.org/10.24018/ejeng.2019.4.9.1412.

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As we are entering the 5G era, high demand is made of wireless communication. Consistent effort has been ongoing in multiple-input multiple-output (MIMO) systems, which provide correlation on temporal and spatial domain, to meet the high throughput demand. To handle the characteristic nature of wireless channel effectively and improve the system performance, this paper considers the combination of diversity and equalization. Space-Time trellis code is combined with single-carrier modulation using two-choice equalization techniques, namely: minimum mean squared error (MMSE) equalizer and orthogonal triangular (QR) detection. MMSE gives an optimal balance between noise enhancement and net inter-symbol interference (ISI) in the transmitted signal. Use of these equalizers provides the platform of investigating the bit error rate (BER) and the pairwise error probability (PEP) at the receiver, as well as the effect of cyclic prefix reduction on the receivers. It was found that the MMSE receiver outperforms the QR receiver in terms of BER, while in terms of PEP; the QR receiver outperforms the MMSE receiver. When a cyclic prefix reduction test was carried out on both receivers, it yields a significant reduction in BER of both receivers but has no significant effect on the overall performance.

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Shin, Vladimir, Georgy Shevlyakov, Woohyun Jeong, and Yoonsoo Kim. "Closed-Form Distance Estimators under Kalman Filtering Framework with Application to Object Tracking." Mathematical Problems in Engineering 2020 (August 20, 2020): 1–16. http://dx.doi.org/10.1155/2020/9141735.

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In this paper, the minimum mean square error (MMSE) estimation problem for calculation of distances between two signals via the Kalman filtering framework is considered. The developed algorithm includes two stages: the Kalman estimate of a state vector computed at the first stage is nonlinearly transformed at the second stage based on a distance function and the MMSE criterion. In general, the most challenging aspect of application of the distance estimator is calculation of the multivariate Gaussian integral. However, it can be successfully overcome for the specific metrics between two points in line, between point and line, between point and plane, and others. In these cases, the MMSE estimator is defined by an analytical closed-form expression. We derive the exact closed-form bilinear and quadratic MMSE estimators that can be effectively applied for calculation of an inner product, squared norm, and Euclidean distance. A novel low-complexity suboptimal estimator for special composite functions of linear, bilinear, and quadratic forms is proposed. Radar range-angle responses are described by the functions. The proposed estimators are validated through a series of experiments using real models and metrics. Experimental results show that the MMSE estimators outperform existing estimators that calculate distance and angle in nonoptimal manner.

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Özyurt, Serdar, Mustafa Öztürk, and Enver Çavuş. "Low-Complexity MIMO MMSE Receiver with Performance Enhancement via Coordinate Interleaving." Journal of Circuits, Systems and Computers 29, no. 14 (June 10, 2020): 2050231. http://dx.doi.org/10.1142/s021812662050231x.

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Multiple-input multiple-output (MIMO) Minimum mean-square error (MMSE) receivers are widely adopted in the latest communication standards and reducing the complexity of these receivers while preserving the error performance is highly desirable. In this work, we study the error performance and implementation complexity of MIMO MMSE receivers when combined with a coordinate interleaved signal space diversity (SSD) technique. Contrary to the well-known trade-off between the error performance and implementation complexity, the proposed system leads to a considerably simplified MIMO MMSE receiver with significant performance gains when compared to the original MIMO MMSE receiver. Unlike the standard MIMO MMSE receiver, the proposed coordinate interleaved technique induces a block diagonal transmit correlation matrix providing both performance enhancement and complexity reduction. The results show that the error performance can be improved more than 10[Formula: see text]dB with up to 71% computational complexity reduction. The complexity comparison between the original and proposed approaches is also verified by means of field-programmable gate array (FPGA) implementation.

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Yin, Zhendong, Xu Jiang, Zhilu Wu, and Xiaohui Liu. "A Hybrid Multiuser Detector Based on MMSE and AFSA for TDRS System Forward Link." Scientific World Journal 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/620617.

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This study mainly focuses on multiuser detection in tracking and data relay satellite (TDRS) system forward link. Minimum mean square error (MMSE) is a low complexity multiuser detection method, but MMSE detector cannot achieve satisfactory bit error ratio and near-far resistance, whereas artificial fish swarm algorithm (AFSA) is expert in optimization and it can realize the global convergence efficiently. Therefore, a hybrid multiuser detector based on MMSE and AFSA (MMSE-AFSA) is proposed in this paper. The result of MMSE and its modified formations are used as the initial values of artificial fishes to accelerate the speed of global convergence and reduce the iteration times for AFSA. The simulation results show that the bit error ratio and near-far resistance performances of the proposed detector are much better, compared with MF, DEC, and MMSE, and are quite close to OMD. Furthermore, the proposed MMSE-AFSA detector also has a large system capacity.

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CHEN, YING, ZHI-CHENG JI, and CHUN-JIAN HUA. "EFFICIENT STATISTICAL MODELING OF WAVELET COEFFICIENTS FOR IMAGE DENOISING." International Journal of Wavelets, Multiresolution and Information Processing 07, no. 05 (September 2009): 629–41. http://dx.doi.org/10.1142/s0219691309003136.

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Statistical modeling of wavelet coefficients is a critical issue in wavelet domain signal processing. By analyzing the defects of other existing methods, and exploiting the local dependency of wavelet coefficients, an efficient statistical model is proposed. Improved variance estimation of the local wavelet coefficients can be obtained using the new model. Then we apply an approximate minimum mean squared error (MMSE) estimation procedure to restore the wavelet image coefficients. The modeling process is computational cost saving, and the denoising experiments show the algorithm outperforms other approaches in peak-signal-to-noise ratio (PSNR).

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35

Rubio, Lorenzo, Rafael P. Torres, Vicent M. Rodrigo Peñarrocha, Jesús R. Pérez, Herman Fernández, Jose-Maria Molina-Garcia-Pardo, and Juan Reig. "Contribution to the Channel Path Loss and Time-Dispersion Characterization in an Office Environment at 26 GHz." Electronics 8, no. 11 (November 1, 2019): 1261. http://dx.doi.org/10.3390/electronics8111261.

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In this paper, path loss and time-dispersion results of the propagation channel in a typical office environment are reported. The results were derived from a channel measurement campaign carried out at 26 GHz in line-of-sight (LOS) and obstructed-LOS (OLOS) conditions. The parameters of both the floating-intercept (FI) and close-in (CI) free space reference distance path loss models were derived using the minimum-mean-squared-error (MMSE). The time-dispersion characteristics of the propagation channel were analyzed through the root-mean-squared (rms) delay-spread and the coherence bandwidth. The results reported here provide better knowledge of the propagation channel features and can be also used to design and evaluate the performance of the next fifth-generation (5G) networks in indoor office environments at the potential 26 GHz frequency band.

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Bao, Xiuwen, Ming Jiang, Wenhao Fang, and Chunming Zhao. "PCQNet: A Trainable Feedback Scheme of Precoder for the Uplink Multi-User MIMO Systems." Entropy 24, no. 8 (August 2, 2022): 1066. http://dx.doi.org/10.3390/e24081066.

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Multi-user multiple-input multiple-output (MU-MIMO) technology can significantly improve the spectral and energy efficiencies of wireless networks. In the uplink MU-MIMO systems, the optimal precoder design at the base station utilizes the Lagrange multipliers method and the centralized iterative algorithm to minimize the mean squared error (MSE) of all users under the power constraint. The precoding matrices need to be fed back to the user equipment to explore the potential benefits of the joint transceiver design. We propose a CNN-based compression network named PCQNet to minimize the feedback overhead. We first illustrate the effect of the trainable compression ratios and feedback bits on the MSE between the original precoding matrices and the recovered ones. We then evaluate the block error rates as the performance measure of the centralized implementation with an optimal minimum mean-squared error (MMSE) transceiver. Numerical results show that the proposed PCQNet achieves near-optimal performance compared with other quantized feedback schemes and significantly reduces the feedback overhead with negligible performance degradation.

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Illangakoon, Chathura, and Pradeepa Yahampath. "On Achievable Distortion in Sending Gaussian Sources over a Bandwidth-Matched Gaussian MAC with No Transmitter CSI." Entropy 21, no. 10 (October 11, 2019): 992. http://dx.doi.org/10.3390/e21100992.

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This paper investigates the minimum mean square error (MMSE) of communicating a pair of Gaussian sources over a a bandwidth-matched Gaussian multiple-access channel with block Rayleigh fading in the absence of channel state information (CSI) at the transmitters. The achievable MMSE is not known. To this end, we derive several upper-bounds to the minimum achievable average MMSE as a function of the transmitter powers, the average channel fading power-to-noise ratio, and the correlation coefficient of the two sources. To derive nontrivial upper bounds which improve on those of separate source-channel coding and uncoded transmission, we incorporate ideas from joint source-channel coding and hybrid digital–analog coding to construct specific coding schemes for which the achievable MMSE can be determined.

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Zhang, Zhengzhen, Chao Dong, and Qian Wan. "Iterative Intercell Interference Cancellation in MIMO Multicell Networks." Wireless Communications and Mobile Computing 2018 (September 27, 2018): 1–8. http://dx.doi.org/10.1155/2018/3526906.

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An iterative intercell interference cancellation algorithm is introduced to improve the receiver performance of uplink transmission in multicell networks. At first, the uplink signal detection is performed independently in each cell according to minimum mean squared error (MMSE) criterion. Subsequently, the detection results are applied to reconstruct the transmit signals of different users and cancel their interference to neighboring cells. With the help of reconstruction results, the MMSE detection matrix of each cell is updated. The channel responses of both efficient and interference links are estimated with the help of pilots. The pilot allocation parameter is introduced to indicate the quality of channel estimation. The simulation results indicate that intercell interference can be greatly mitigated by the proposed algorithm with a moderate number of receiver antennas at the base station.

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Dalton, Lori A., and Edward R. Dougherty. "Bayesian Minimum Mean-Square Error Estimation for Classification Error—Part I: Definition and the Bayesian MMSE Error Estimator for Discrete Classification." IEEE Transactions on Signal Processing 59, no. 1 (January 2011): 115–29. http://dx.doi.org/10.1109/tsp.2010.2084572.

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Kittisuwan, P., and C. Chinrungrueng. "Differential Form of Bivariate MMSE Estimator Based on Gaussian Noise." Journal of Circuits, Systems and Computers 26, no. 01 (October 4, 2016): 1750008. http://dx.doi.org/10.1142/s0218126617500086.

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In fact, the noise signal is an important problem in signal, circuits and systems. The minimum mean square error (MMSE) estimation technique is useful in several additive white Gaussian noise (AWGN) reduction methods. Original form of MMSE estimator is the integral form. Unfortunately, integral form of MMSE estimator cannot be obtained in simple form for any interesting peaked, heavy-tailed densities (also known as super-Gaussian densities). In this work, we proposed a differential form of bivariate MMSE estimator. The development depends on bivariate Taylor series. The proposed estimator requires no integration. In fact, the derivation is an extension of the existing results for differential form of univariate MMSE estimator.

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Huang, Cheng Ti, Ruey Wen Liu, Hou Jun Wang, and Cheng Lin Yang. "An Autocorrelation-Based Interference Rejection Signal Detection Scheme." Advanced Materials Research 271-273 (July 2011): 833–38. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.833.

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This presentation proposed an autocorrelation-based signal detection scheme to get a better resulting. The signal detection scheme is combined by Autocorrelation Filter and an improved linear Minimum Mean Square Error (MMSE) estimator. The Autocorrelation Filter is used to reject the interference, and the improved linear MMSE estimator is used to get the least error. Both two methods are based on the non-overlapping property of the signals in autocorrelation domain. The theory consequence and Simulation results indicate that this signal detection scheme can achieve a high detection quality.

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Diana, D. C., and R. Hema. "Swarm Intelligence Based MMSE Frequency Domain Equalization for MIMO Systems." ECTI Transactions on Electrical Engineering, Electronics, and Communications 21, no. 2 (June 27, 2023): 249824. http://dx.doi.org/10.37936/ecti-eec.2023212.249824.

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The automatic upgradation of equalizer weights in channel equalization demands a low-complexity, highly accurate estimation of recovery at the minimum possible time. The low-complexity frequency domain equalization improves the minimum mean square error (MMSE) of the equalization process. Adding the superiority of particle swarm optimization (PSO) to the equalizer coefficient selection process enhances the MMSE. This work proposes frequency-domain channel equalization along with a modified PSO (MPSO) as an adaptive algorithm for equalizer weight selection in MIMO systems. The simulation results validate the performance with the time domain linear and decision feedback equalizer structures for BPSK and QAM systems. The parameters are carefully selected by analyzing MMSE thoroughly under timevarying channel conditions.

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Zhai, Kai, Zheng Ma, and Xianfu Lei. "Accurate Performance Analysis of Coded Large-Scale Multiuser MIMO Systems with MMSE Receivers." Sensors 19, no. 13 (June 28, 2019): 2884. http://dx.doi.org/10.3390/s19132884.

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In this paper, we estimate the uplink performance of large-scale multi-user multiple-input multiple-output (MIMO) networks. By applying minimum-mean-square-error (MMSE) detection, a novel statistical distribution of the signal-to-interference-plus-noise ratio (SINR) for any user is derived, for path loss, shadowing and Rayleigh fading. Suppose that the channel state information is perfectly known at the base station. Then, we derive the analytical expressions for the pairwise error probability (PEP) of the massive multiuser MMSE–MIMO systems, based on which we further obtain the upper bound of the bit error rate (BER). The analytical results are validated successfully through simulations for all cases.

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Lakshmi, Dr M. Vijaya. "Deep Learning Aided 5G Channel Estimation." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (June 30, 2023): 3821–26. http://dx.doi.org/10.22214/ijraset.2023.54202.

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Abstract: Wireless communications involves the transfer of voiceand data without a cable or wires. It uses orthogonal frequencydivision multiplexing, also known as a multicarrier transmission technique. In multiple input multiple output (MIMO) wireless communication (4G and 5G technologies), channel estimation is crucial. Multiple antennas are used at both the transmit and receive sides ofa MIMO system to increase spectral efficiency and reliability. In 5G channel estimation is performed to improve the accuracy of the received signal. Least-squares estimation is a cheap method with relatively large channel estimationerrors, but it is supported in this work by using a new channel estimation method that leverages deep learning. LS (least squares) and MMSE (minimum mean squared error) are two popular traditional approaches to channel estimation, but deep learning provides much more accurate results than previous channel estimation methods.

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Kittisuwan, Pichid. "Simple Form of MMSE Estimator for Super-Gaussian Prior Densities." Fluctuation and Noise Letters 14, no. 03 (June 29, 2015): 1550025. http://dx.doi.org/10.1142/s021947751550025x.

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The denoising method that become popular in recent years for additive white Gaussian noise (AWGN) are Bayesian estimation techniques e.g., maximum a posteriori (MAP) and minimum mean square error (MMSE). In super-Gaussian prior densities, it is well known that the MMSE estimator in such a case has a complicated form. In this work, we derive the MMSE estimation with Taylor series. We show that the proposed estimator also leads to a simple formula. An extension of this estimator to Pearson type VII prior density is also offered. The experimental result shows that the proposed estimator to the original MMSE nonlinearity is reasonably good.

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Hu, Chia-Chang, and Chi-Tsung Wang. "PCA-Combined Receive Antenna Selection for MMSE V-BLAST in Correlated Channels." ISRN Signal Processing 2011 (February 6, 2011): 1–3. http://dx.doi.org/10.5402/2011/384162.

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A computationally efficient receive antenna subset selection in conjunction with the principal component analysis (PCA) is proposed for the minimum mean square error (MMSE) V-BLAST systems in correlated channels. This proposed PCA-combined antenna subset selection is capable of sustaining system performance and reducing complexity burden in signal processing and hardware cost.

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Wong, Kah Jing, Filbert Juwono, and Regina Reine. "Deep Learning for Channel Estimation and Signal Detection in OFDM-Based Communication Systems." ELKHA 14, no. 1 (April 20, 2022): 52. http://dx.doi.org/10.26418/elkha.v14i1.53962.

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The goal of 6G communication networks requires higher transmission speeds, tremendous data processing, and low-latency communication. Orthogonal frequency-division multiplexing (OFDM), which is widely utilized in 5G communication systems, may be a viable alternative for 6G. It significantly reduces inter symbol interference (ISI) in the frequency-selective fading environment. Channel estimation is critical in OFDM to optimize system performance. Deep learning has been employed as an appealing alternative for channel estimation and signal detection in OFDM-based communication systems due to its better potential for feature learning and representation. In this study, we examine the deep neural network (DNN) layers created from long-short term memory (LSTM) for detecting the signals by learning the received signal as well as channel information. We investigate the performance of the system under various conditions. The simulation results show that the signal bit error (SER) is equivalent to and better than that of the minimum mean squared error (MMSE) and least square (LS) methods.

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Zhao, Gaoli, Jianping Wang, Wei Chen, and Junping Song. "A Novel Signal Detection Algorithm for Underwater MIMO-OFDM Systems Based on Generalized MMSE." Journal of Sensors 2019 (November 12, 2019): 1–10. http://dx.doi.org/10.1155/2019/2603051.

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The MIMO-OFDM system fully exploits the advantages of MIMO and OFDM, effectively resisting the channel multipath fading and inter-symbol interference while increasing the data transmission rate. Studies show that it is the principal technical mean for building underwater acoustic networks (UANs) of high performance. As the core, a signal detection algorithm determines the performance and complexity of the MIMO-OFDM system. However, low computational complexity and high performance cannot be achieved simultaneously, especially for UANs with a narrow bandwidth and limited data rate. This paper presents a novel signal detection algorithm based on generalized MMSE. First, we propose a model for the underwater MIMO-OFDM system. Second, we design a signal coding method based on STBC (space-time block coding). Third, we realize the detection algorithm namely GMMSE (generalized minimum mean square error). Finally, we perform a comparison of the algorithm with ZF (Zero Forcing), MMSE (minimum mean square error), and ML (Maximum Likelihood) in terms of the BER (bit error rate) and the CC (computational complexity). The simulation results show that the BER of GMMSE is the lowest one and the CC close to that of ZF, which achieves a tradeoff between the complexity and performance. This work provides essential theoretical and technical support for implementing UANs of high performance.

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Sur, Samarendra Nath, Rabindranath Bera, Akash Kumar Bhoi, Mahaboob Shaik, and Gonçalo Marques. "Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems." Information 11, no. 6 (June 4, 2020): 301. http://dx.doi.org/10.3390/info11060301.

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Massive multi-input-multi-output (MIMO) systems are the future of the communication system. The proper design of the MIMO system needs an appropriate choice of detection algorithms. At the same time, Lattice reduction (LR)-aided equalizers have been well investigated for MIMO systems. Many studies have been carried out over the Korkine–Zolotareff (KZ) and Lenstra–Lenstra–Lovász (LLL) algorithms. This paper presents an analysis of the channel capacity of the massive MIMO system. The mathematical calculations included in this paper correspond to the channel correlation effect on the channel capacity. Besides, the achievable gain over the linear receiver is also highlighted. In this study, all the calculations were further verified through the simulated results. The simulated results show the performance comparison between zero forcing (ZF), minimum mean squared error (MMSE), integer forcing (IF) receivers with log-likelihood ratio (LLR)-ZF, LLR-MMSE, KZ-ZF, and KZ-MMSE. The main objective of this work is to show that, when a lattice reduction algorithm is combined with the convention linear MIMO receiver, it improves the capacity tremendously. The same is proven here, as the KZ-MMSE receiver outperforms its counterparts in a significant margin.

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Tiwari, Keerti, Davinder S. Saini, and Sunil V. Bhooshan. "ASEP of MIMO System with MMSE-OSIC Detection over Weibull-Gamma Fading Channel Subject to AWGGN." Journal of Computer Networks and Communications 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/7918456.

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Ordered successive interference cancellation (OSIC) is adopted with minimum mean square error (MMSE) detection to enhance the multiple-input multiple-output (MIMO) system performance. The optimum detection technique improves the error rate performance but increases system complexity. Therefore, MMSE-OSIC detection is used which reduces error rate compared to traditional MMSE with low complexity. The system performance is analyzed in composite fading environment that includes multipath and shadowing effects known as Weibull-Gamma (WG) fading. Along with the composite fading, a generalized noise that is additive white generalized Gaussian noise (AWGGN) is considered to show the impact of wireless scenario. This noise model includes various forms of noise as special cases such as impulsive, Gamma, Laplacian, Gaussian, and uniform. Consequently, generalizedQ-function is used to model noise. The average symbol error probability (ASEP) of MIMO system is computed for 16-quadrature amplitude modulation (16-QAM) using MMSE-OSIC detection in WG fading perturbed by AWGGN. Analytical expressions are given in terms of Fox-H function (FHF). These expressions demonstrate the best fit to simulation results.

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Journal articles on the topic 'Minimum Mean Squared Error (MMSE)'

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