MMSE Algorithm Research Articles

Data detection method for uplink massive MIMO systems based on the long recurrence enlarged conjugate gradient

<p>Although the mean square error (MMSE) approach is recognized to be near optimal for uplinking large-scale multiple-input-multiple-output (MIMO) systems, there are certain difficulties in the procedure related to matrix inversion. The long recurrence enlarged conjugate gradient (LRE-CG) approach is proposed in this study as a way to iteratively realize the MMMS algorithm while avoiding the complications of matrix inversion. In addition, a diagonal-approximate starting solution to the LRE-CG approach was used to speed up the conversion rate and reduce the complications required. It has been discovered that the LRE-CG-based approach has the ability to significantly reduce computational complexity. By comparing simulation results, it is clear that this new methodology surpasses well-established wayslike the Neumann series approximation-based method and the Gauss-Siedel iterative method. With a small number of iterations, the suggested approach achieves near-optimal performance of a standard MMSE algorithm.</p>

MIMO Semi-blind Channel Estimation by using Tikhonov Regularized MMSE and MAP Algorithms with Householder Transformation based QR Decomposition

MIMO Semi-blind Channel Estimation by using Tikhonov Regularized MMSE and MAP Algorithms with Householder Transformation based QR Decomposition

Performance Analysis of Compressive Sensing based LS and MMSE Channel Estimation Algorithm

In this paper, the optimality of Compressive Sensing based Least Square (LS-CS) and Compressive Sensing based Minimum Mean Square (MMSE-CS) channel estimation algorithms in Multi Input Multi Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system is investigated for a sparse communication channel. The performance of LS, MMSE, LS-CS and MMSE-CS channel estimation algorithms in terms of sparsity of the channel, compressive sensing and mathematical complexity is investigated and analyzed so that optimum ranges can be recommended.

Two-Stage Method for Joint Estimation of Information Symbols and Channel Frequency Response in OFDM Communication Systems

The optimal and quasi-optimal algorithms of two-stage joint estimation of information symbols and frequency response (FR) of multibeam channels in OFDM-based communication systems have been synthesized. They involve the calculation of a posteriori probability density of estimated processes. At the first stage, the recurrent calculation of joint a posteriori distributions of information symbols and the frequency response is performed from two sides of the measurement vector. At the second stage, a posteriori distributions are combined on each of subcarriers that are obtained as a result of the first stage estimation. Based on the obtained a posteriori distributions, estimates of the information symbol and channel FR are determined by the criteria of a posteriori probability maximum and the average mean squared error minimum, respectively. The performance of synthesized algorithms similar to the well-known MMSE algorithm involves the need of knowledge of statistical properties of communication channel. The device implementing the optimal algorithm is multichannel, each channel of which is matched with the corresponding value of symbol from the modulation constellation. The quasi-optimal algorithm was obtained by using the Gaussian approximation of a posteriori probability density. It should be noted that this algorithm preserves its multichannel structure. The approbation of the presented algorithm was conducted using the computer-aided statistical simulation for different parameters of multibeam communication channels and the comparison of the obtained results with the results obtained by the MMSE and LS algorithms. The simulation results showed that the error probability decreases by about 2 times with a maximum signal propagation delay of 100 μs.

Research on sparse channel estimation algorithm based on MIMO OFDM system

In the application of MIMO OFDM system, the traditional pilot-assisted channel estimation algorithm, such as LS, MMSE algorithm, does not take advantage of the characteristics of channel sparsity, which results in the reduction of spectrum utilization due to the use of a large number of pilots. Under the premise of compressed sensing, this paper uses channel sparsity to study the AMP channel estimation algorithm based on MIMO OFDM system, and introduces the principles and steps of the AMP algorithm in detail. Through theoretical analysis and simulation, it is shown that the AMP channel estimation algorithm proposed in this paper has a significant improvement in spectrum utilization and estimation performance compared with the traditional method, which is more effective and greatly reduces the calculation time.

Detection Algorithm of Compressed Sensing Signal in Generalized Spatial Modulation System

For the generalized spatial modulation in the underdetermined system with the number of transmitting antennas larger than the number of receiving antennas, the activation of the antenna is small and inaccurate. The traditional MMSE algorithm and the ZF algorithm still perform the pseudo-inverse operation on the entire channel matrix, which results in a large number of redundancy. Although the ML algorithm has the best detection performance, the complexity is difficult to meet the actual requirements. In this paper, for the sparse characteristics of generalized spatial modulation signals, a detection algorithm is improved based on the compressed sensing recovery algorithm SWOMP. The algorithm first selects multiple or one active antenna sequences conforming to the spatial modulation to form an index set according to the situation, and then uses the backtracking principle to select the atomic column according to the threshold, rejects the unreliable sequence, and finally uses the minimum mean square error algorithm to detect the modulation symbol according to the activated antenna index. The pseudo-inverse operation of the entire channel matrix is avoided, and the bit error rate is lower than the ZF algorithm, the MMSE algorithm and the OMP algorithm, and the performance of the proposed algorithm is closer to the ML algorithm, which is a better way that balance between complexity and detection performance.

Image Transmission with Joint Time Reversal and OFDM in Underwater Acoustic Environment

The development of technology and applications in the underwater acoustic field are a challenge for researchers. The OFDM system is an interesting research topic to date because of its high-rate and high-quality wireless capabilities. In a multipath environment, OFDM can reduce the effect of multipath fading by converting frequency selective channel to a flat subchannels parallel collection of frequency. Time reversal with its spatial and temporal focal properties is a technique that can be relied upon in reducing channel fading and intersymbol interference which causes distortion in the received signal. In this paper, we present a study of transmitting images in underwater acoustic environments using a combined time reversal and OFDM (TR-OFDM) technique. The estimation technique based on the MMSE algorithm is used in the image restoration process. The simulation results show that transmitting image with the TR-OFDM system has superior performance compared to traditional OFDM system. With BPSK modulation and MMSE estimation technique, the BER obtained by TR-OFDM is 10−3 at SNR 8.2 dB. Modulation schemes such as M-PSK and M-QAM are also presented in this paper. BPSK modulation is proven to have the best performance on SNR 20 dB with zero resulting error.

Effective Transmission Method With Adaptive Nonstationary Channel Equalization for Hypersonic Reentry Communications

The reentry plasma sheath propagation environment is nonstationary and has high-dynamic characteristics. The communication signal suffers serious parasitic modulation effect since the time-varying degree of the channel is on the same order as the telemetry symbol rate. This paper proposes an effective transmission scheme to cancel the plasma sheath channel (PSC) distortion by utilizing the short spreading and adaptive nonstationary channel equalization technology. The proposed scheme spreads the telemetry signal and inserts a small number of pilot signals to determine whether the nonstationary state of the channel is changed by the channel amplitude attention value of the pilot signals. A novel adaptive nonstationary stochastic gradient recursive minimum mean square error (NSGR–MMSE) algorithm is then proposed to estimate the other channel response values in each current state. Finally, the channel equalization is performed to mitigate the damage from the parasitic modulation effect. The proposed method can accommodate the nonstationary characteristics of the channel and the small-scale channel distortion simultaneously with small bandwidth efficiency scarification and minimal algorithm complexity cost. The simulation results show that the proposed transmission scheme can ensure reliable communication under two typical reentry PSC models. Furthermore, the performance of the proposed adaptive NSGR–MMSE algorithm is improved by at least 3 dB versus the classic MMSE algorithm under the effective transmission scheme.

High-Efficiency Expectation Propagation Detector for High-Order Massive MIMO Systems

Multiple-inputs multiple-outputs (MIMO) technology, including massive MIMO, plays an important role in modern wireless communication systems. Massive MIMO systems with high-order modulation can promote spectrum efficiency. The algorithm complexity and detection performance are the main challenges for the massive MIMO system. Thus, the low complexity and high-performance MIMO detector is important for the practical massive MIMO application. The Expectation Propagation (EP) detector outperforms many conventional detectors in high-order massive MIMO scenarios. However, its complexity increases exponentially with the number of sending antennas and the modulation order. In this paper, we propose a novel information updating scheme for EP MIMO detection algorithm to achieve high performance with low complexity. The high-efficiency EP detector is based on the expectation propagation algorithm with the jointed scheme of successive updating, sorting updating and sphere search aided algorithm. Numerical results show the high-efficiency EP detector reduces over 85% complexity of the original EP detector for the scenario $N_{t}=N_{r}=20$ with 64-QAM modulation, and the gain on complexity becomes more evident with the increase of antenna scale and the modulation order. The high-efficiency EP detector can outperform the original EP detector in different high-order massive scenarios. Compared with MMSE algorithm, the proposed scheme can get huge performance gain with 1.5 times complexity for high-order massive MIMO systems.

Compressive Sensing-Based Channel Estimation for FBMC-OQAM System Under Doubly Selective Channels

Filter-bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) has been considered as an alternative scheme to orthogonal frequency division multiplexing (OFDM). However, the traditional channel estimation techniques of the OFDM cannot be directly applied to the FBMC-OQAM system because of the real-field orthogonality of the FBMC-OQAM signals. Although traditional channel estimation techniques, such as least square (LS) and minimum mean square error (MMSE), are widely applied to the FBMC-OQAM system via canceling the intrinsic imaginary interference from adjacent data symbols, the LS algorithm is subject to noise enhancement and it results in large mean square error (MSE), while the mmse algorithm needs to know the statistical information of channel in advance. Due to sparsity of the wireless channel, channel estimation is investigated as a compressive sensing (CS) problem. In this paper, we first introduce the coding method to cancel intrinsic imaginary interference for the FBMC-OQAM system. Then, a novel sparse adaptive subspace pursuit (SASP) method is proposed to improve the accuracy of LS channel estimation. Finally, we develop two distinctive algorithms, namely, auxiliary pilot (AP) SASP and coding-SASP, to estimate channel frequency respond (CFR) in the FBMC-OQAM system. The simulation results show that the AP-SASP and coding-SASP algorithms can offer a low complexity and fewer measurements compared with conventional orthogonal matching pursuit (OMP) and regularized OMP (ROMP) methods. Moreover, the proposed AP-SASP and coding-SASP algorithms have a better bit error ratio (BER) performance than the conventional OMP and ROMP methods for FBMC system in the doubly selective channels.

CRS-aided MMSE algorithm for LTE Downlink

MMSE algorithm has good performance in an ideal situation, but channel information is required. In order to improve the practicality of the MMSE algorithm, in this paper, a method that estimates channel information through CRS (Cell-specific Reference Signal) is proposed in LTE system. In the simulation, MMSE algorithm, ML algorithm and LS algorithm are compared in the LTE system under the same simulation conditions. Simulation results show that CRS-aided MMSE algorithm outperforms ML algorithm and LS algorithm.

LTE-Advanced 환경에서 D2D 통신을 위한 송수신 기법

We treat device-to-device direct communication (D2D) by reusing cellular uplink resources in LTE-Advanced systems. Conventional schemes assume that D2D transmitter employs SC-FDMA scheme for the date transmission. In the conventional schemes, however, it is very difficult to reduce the interference between the users, D2D communication cannot be used when the interference caused by cellular uplink signal is high. In this paper, we propose D2D transmission scheme which employes MC-CDMA technology and D2D detection scheme which uses MMSE algorithm to reduce interference from the cellular uplink signal. Therefore, in the proposed scheme the D2D communication becomes possible even in the high interference scenario. Through simulation, we show that the proposed scheme has better BER performance than the conventional scheme.

A Novel Channel Estimation Method Based on Power-Delay Profile

Considering the physical layer specification of the IEEE802.11 protocol as background, a novel LSE (least square estimation) algorithm based on power-delay profile of wireless channel is proposed. In multi-path time-variant channel, receiver carries out a primary MMSE estimation using training symbols and pilots of OFDM symbol firstly. Then the channel impulse response is obtained from frequency response estimated by MMSE. Finally, LSE algorithm is applied to revise the channel impulse response according to the power-delay profile. The LSE algorithm can reduce the noise level of MMSE estimation in time-domain which is equivalent to increasing the SNR to the output of 2-D wiener filter. Simulation results confirm that the proposed LSE algorithm gains a better performance in contrast to MMSE algorithm. As the Doppler frequency shift increases, LSE outperforms more significantly than MMSE algorithm.

LMS Blind Adaptive Multiuser Detection for Underwater Acoustic Communication with MMSE and MOE Criteria

In order to solve detection of multi-user detection in underwater acoustic communication networks, blind adaptive multiuser detection method using LMS algorithm was proposed to solve the MAI problem of multi-user detection in underwater acoustic communication channel when users increase. Two type simulations were executed, including synchronous and asynchronous multi-user simulation analysis, to verify the validity of LMS multi-user detection algorithm and inspection machine. The verification of the effectiveness of the MMSE and MOE algorithm for LMS multi-user detection algorithm was done by simulation.

基于FPGA的LTE系统信道估计算法 研究与设计

本论文从实现的角度对LTE系统信道估计算法进行了研究，对LS、MMSE等常用的信道估计算法进行了分析和MATLAB仿真；详细介绍了采用数字化后的MMSE算法实现的信道估计器电路结构，依照3GPP物理层标准，实现了基于FPGA的TD-LTE系统上行的信道估计算法电路。仿真结果表明，所提出的数字化MMSE算法模型系统在系统复杂度和信道估计效果上都较为优化。 From the point of view of implementation, channel estimation of LTE uplink is studied in the paper. Firstly, LS, MMSE and other commonly used channel estimation algorithm are analyzed and simulated by MATLAB. Secondly, channel estimator circuit structure adopting digital MMSE algorithm is described in detail. Then, in accordance with the 3GPP physical layer standards, based on FPGA, digital channel estimation algorithm of TD-LTE uplink system is implemented. The simulation results illustrate that the digital MMSE algorithm model system is optimal in both the complexity of the system and channel estimation effect.

Development and Performance Evaluation of MMSE MacroDiversity Reception System With Delay Difference Correction

We have been developing a minimum-mean-square-error macrodiversity (MMSE-MD) reception system using distributed remote antennas and radio-on-fiber (RoF) links for use in live broadcasts of road races. The system selects remote antennas with good signal quality and combines their signals based on the MMSE algorithm to combat both small-scale and large-scale fading. For the system to be feasible, we have to consider propagation delay differences among diversity branches due to the RoF links and radio propagation. This paper describes a practical delay difference correction (DDC) technique that can keep signal continuity in any situation, the hardware implementation of an MMSE-MD receiver embodying the technique, and indoor and outdoor performance evaluations. Our prototype receiver perfectly corrected the propagation delay differences among diversity branches without losing signal continuity and maintained MD reception without signal outage across a wide area on an actual road-race course.

Study of BLAST Signal Detection Algorithm in LTE System

BLAST can achieve high speed data communication. Its signal detection directly affects performance of BLAST receiver. This paper introduced several signal detection algorithmsZF algorithm, MMSE algorithm, ZF-SIC algorithm and MMSE-SIC algorithm. The simulation results show that the traditional ZF algorithm has the worst performance, the traditional MMSE algorithm and the ZF-SIC algorithm is similar, but with the increase of the SNR, the performance of ZF-SIC algorithm is better than MMSE algorithm. MMSE-SIC algorithm has the best detection performance in these detection algorithms.

Improved Algorithm Based on the DFT Transform Channel Estimation and Threshold Filtering

In channel estimation, the complexity of the DFT-based channel estimation algorithm is lower than the MMSE algorithm, and the DFT-based algorithm performs better than the LS algorithm. However, due to that the traditional algorithms simply considered all the samples to be useful channel impulse response, ignoried the effect of noise. Therefore, the algorithm could be improved. This paper presents an improved algorithm based on twice noise estimation theory. The algorithm uses the sequence of points other than the cyclic prefix length to estimate the noise variance firstly, and then use the estimated noise variance to distinguish the noise samples within the cyclic prefix length. The computation of the new noise variance and noise mean through the new noise points as a threshold filters the impulse response of the channel in time domain and eliminates the impact of noise on the system further. The simulation result shows that the improved algorithm performs better than the traditional algorithm.

An Improved Channel Estimation Method for LTE Uplink

As users of the increasing demand for multimedia services, 3GPP long term evolution system proposed the Long Term Evolution, LTE. LTE is the most important improvements with a new air interface technology to provide users with higher peak rates. Accurate channel estimation is to ensure the transmission quality of LTE system and the key to its advantages. In pursuit of lower bit error rate (BER), this paper based on pilot signals TDD LTE system on the uplink channel estimation algorithm. Use LS algorithm, MMSE algorithm and svd algorithm. Based on these three improved svd algorithm, it gave the simulation results.

Channel Estimation Study for Block - Pilot Insertion in OFDM Systems Under Slowly Time Varying Conditions

In this paper, we propose a study of performance of the channel estimation using LS, MMSE, LMMSE and Lr-LMMSE algorithms in OFDM (Orthogonal Frequency Division Multiplexing) system which, as known suffers from the time variation of the channel under high mobility conditions, using block pilot insertion. The loss of sub channel orthogonality leads to inter-carrier interference (ICI). Using many algorithms for channel estimation, we will show that, for a 16- QAM modulation, the LMMSE algorithm performs well to achieve this estimation but when the SNR (Signal Noise Rate) is high, the four algorithms (LS, MMSE, LMMSE and Lr-LMMSE) perform similarly, this is not always the case for another scheme of modulation. We will improve also the mean squared error for these algorithms. It will be illustrious in this paper that the LMMSE algorithm performs well with the block- pilot insertion as well as its low rank version which behave very good even when the size of FFT is very high.