MMSE Criterion Research Articles

Are There Differences in Screening MMSE Interview Durations Between Subjects Who Maintain Severity and Subjects Who Drop Below Screening Inclusionary MMSE Thresholds at Baseline? An Exploratory Analysis.

AbstractBackgroundWe have previously identified a large proportion of subjects (> 10%) entering clinical trials in early Alzheimer’s disease to possibly suffer from Baseline inflation (Kott, 2023). Without useful predictive markers, the identification of these subjects happens only when these subjects are already randomized into the trial. Our prior analyses showed an almost linear relationship between MMSE interview duration and MMSE total score (Kott, 2022). To be able to identify possible subjects with MMSE score inflation at Screening, we wanted to test the hypothesis that those subjects with likely inflated MMSE scores had significantly longer scale administration times, possibly corresponding to increased symptom severity below the MMSE inclusionary threshold.MethodData from 6,922 subjects were pooled from 6 early AD clinical trials. We restricted the analysis to interviews between 3 and 30 minutes long, shorter interviews are technically not possible and longer interviews likely indicate user error. This decreased the sample to 6,717 subjects. Subjects were dichotomized into subjects meeting Screening MMSE criteria at Baseline and subjects who dropped below the Screening MMSE criteria at Baseline. A generalized linear model was fitted to the data with the Screening MMSE duration used as the predicted variable and type of subject (drops below criteria yes/no) as the predictor variable correcting for the MMSE score at Screening.Result937 subjects no longer met MMSE inclusion criteria at Baseline. For those subjects, MMSE interview duration increased significantly (∼40 seconds).ConclusionOur post‐hoc analysis found significantly longer Screening MMSE interview durations in subjects who no longer met MMSE inclusion cutoffs at Baseline. The increase was consistent with our hypothesis and likely reflects that these subjects had their Screening MMSE scores inflated in order to meet inclusion criteria. We suggest including prolonged MMSE durations in analytical programs as a marker of possible MMSE score inflation alongside other markers, like MMSE vs ADAS‐Cog discordance. We plan additional analyses to better understand this problem.

BASELINE DATA OF A 3-YEAR RANDOMIZED CONTROLLED TRIAL ASSESSING THE EFFECTS OF THE REDUCTION OF ANTIHYPERTENSIVE TREATMENT IN NURSING HOME RESIDENTS >80 YO. THE RETREAT FRAIL TRIAL

Objective: Although the benefits of blood pressure (BP) lowering treatments in patients over 80 years with preserved functional status have been shown, the benefits in treated hypertensive patients of this age-group with several co-morbidities and loss of functionality, remain controversial: data from observational studies show rather inverse relationships between BP and prognosis, whereas there is a total lack of interventional trials in these subjects. Design and method: RETREAT FRAIL is a multicenter randomized controlled trial aiming to evaluate the effect of the step-down of antihypertensive medications on all-cause mortality (mean follow-up, 36 months) in nursing home (NHs) residents over 80 years, treated with >1 antihypertensive drug and presenting an SBP<130 mmHg. The only clinical exclusion criterion was an estimated life expectancy <3 months. Enrolled patients were randomized into one of the 2 groups: treatment step-down or control group. In both groups, the follow-up is performed in the NHs every 2 months, including a comprehensive geriatric assessment every 6 months. Results: Between April 2019 and July 2022, 1048 patients (842 women), mean age 90±5, from 108 NHs were randomized (528 step-down and 520 controls). They were receiving at mean 9.4±3.4 different medications including 2.5±0.7 antihypertensive medications. Mean SBP: 118±11mmHg, DBP: 65±10 mmHg and HR: 71±12 bpm. Based on ADL, MMSE, and mobility criteria, 52% had severe loss of autonomy, 32 % partial loss of functionality and autonomy and 16% had preserved autonomy and functionality. No differences were observed for all these parameters between the 2 randomization groups. The 3-year follow-up of this trial will be completed June 2024. Conclusions: Despite the difficulties in NHs dramatically aggravated during the COVID-19 pandemic, we were able to complete the enrolment of the residents and to respect the follow-up protocol. RETREAT FRAIL will be the first randomized trial to provide information concerning the long-term effects of a progressive standardized down-titration of the BP lowering treatment in very old frail patient i.e. those who have so far been completely excluded from clinical trials.

Discrete MMSE Precoding for Multiuser MIMO Systems With PSK Modulation

We propose an optimal MMSE precoding technique using quantized signals with constant envelope. Unlike the existing MMSE design that relies on 1-bit resolution, the proposed approach employs uniform phase quantization and the bounding step in the branch-and-bound method is different in terms of considering the most restrictive relaxation of the nonconvex problem, which is then utilized for a suboptimal design also. We also propose robust MMSE designs where we exploit second order statistics of a channel state information mismatch. Moreover, unlike prior studies, we propose three different soft detection methods and an iterative detection and decoding scheme that allow the utilization of channel coding in conjunction with low-resolution precoding. Besides an exact approach for computing the extrinsic information, we propose two approximations with reduced computational complexity. Numerical simulations show that utilizing the MMSE criterion instead of the established maximum-minimum distance to the decision threshold yields a lower bit-error-rate in many scenarios. Furthermore, when using the MMSE criterion, a smaller number of bound evaluations in the branch-and-bound method is required for low and medium SNR. Finally, results based on an LDPC block code indicate that the proposed receive processing schemes yield a lower bit-error-rate compared to the conventional design.

MIMO-OFDM channel estimation based on minimum error entropy criterion under non-Gaussian environment

ABSTRACT Using the orthogonal frequency division multiplexing (OFDM) technique, a multiple-input multiple-output (MIMO) system can provide high spectral efficiency and high data transmission over a fading channel. To achieve the best performance in a MIMO-OFDM system, high accuracy in channel estimation is a very important factor which leads to appropriate receiver design. Therefore, in the most channel estimation algorithms, the mean square error (MSE) is the main criterion for noise minimisation which is robust in the case of Gaussian noise. However, in telecommunication systems which do not have noise with Gaussian distribution, the MSE criterion is not appropriate. So as to tackle this problem, a robust adaptive filtering algorithm was proposed using minimum error entropy (MEE) criterion and improved least square (ILS) approach which by far is better than MMSE criterion to robust channel estimation. In this work, impulsive noise is used for non-Gaussian environment simulation. Furthermore, MEE is employed to attenuate the impulsive noise, and ILS is adopted to reduce LS estimation variance. Compared to the MSE-based algorithms, simulation results indicate that the proposed method outperforms the channel estimation in a non-Gaussian environment.

AGMC-Based Robust Cubature Kalman Filter for SINS/GNSS Integrated Navigation System With Unknown Noise Statistics

A new robust cubature Kalman filter is proposed using adaptive generalized maximum correntropy (AGMC) criterion rather than the conventional MMSE criterion in this paper. In the proposed method, the adaptive generalized maximum correntropy (AGMC) criterion is firstly constructed from an adaptive forgetting correntropy based cost function, which is rather robust with respect to the process uncertainty and non-Gaussian noise. On this basis, a new robust cubature Kalman filter is further derived, where the predicted state vector and received measurements are processed simultaneously based on the regression form derived via the statistical linearization approach. An adaptive forgetting scheme is then proposed in combination with the AGMC-CKF to update the parameters of the AGMC adaptively in real time. Taking advantage of the AGMC, the unknown noise statistics caused by the process uncertainty and non-Gaussian noise can be effectively suppressed. Simulations and car-mounted experiments demonstrate that the proposed filter is superior in terms of estimation accuracy and robustness as compared with the related state-of-art methods.

Minimum-Bit-Error Rate Tuning for PDNP Detection

A dominant impediment in magnetic recording is pattern-dependent media noise, and its impact will only grow more severe as areal densities increase. A widely used strategy for mitigating media noise in a trellis-based detector is pattern-dependent noise prediction (PDNP); in this approach, each bit pattern (which determines a trellis branch) will have its own set of branch metric parameters (including the signal levels, noise predictor coefficients, and residual variances). Because the number of states grows exponentially with the number of tracks being detected, a multitrack detector has far more parameters than a single-track detector. In this article, we propose the adaptive minimum-bit-error rate (AMBER) algorithm for adapting these pattern-dependent multitrack detector parameters with the aim of minimizing BER. Numerical results for a 2-D-PDNP multitrack detector based on a quasi-micromagnetic simulated channel show that, when compared to a conventional MMSE criterion, the AMBER algorithm decreases the BER by 17%.

On the MMSE‐based multiuser millimeter wave MIMO hybrid precoding design

SummaryA hybrid MMSE‐based precoder and combiner design with low complexity is studied in this paper for both the downlink and uplink multiuser millimeter wave MIMO systems. At first, according to the underlying channel knowledge, the phases of the RF precoder and combiner are manipulated by using the MMSE criterion. On the basis of the MMSE‐based analog precoder design, the MMSE‐based digital baseband precoder can be readily derived. Thus, this method combines the advantage of using the MMSE precoding and phase extraction technique to obtain a reasonable solution. The proposed hybrid precoding design will be examined in both the uplink and downlink multiuser MIMO systems. Numerical results are presented to show that the proposed MMSE‐based hybrid precoding design is capable of attaining superior performance in terms of both the spectral efficiency and energy efficiency over the existing designs. Moreover, we will show that the MMSE‐based design can be readily extended to the multiuser millimeter wave MISO systems when only statistical channel state information is available.

Design of QAM-FBMC Waveforms Considering MMSE Receiver

Due to its high spectral confinement characteristics and spectral efficiency, QAM-FBMC is considered a candidate waveform to replace CP-OFDM. QAM-FBMC has inevitable non-orthogonality both in time and frequency, and the system and filter must be well-designed to minimize the interferences. However, existing QAM-FBMC studies utilize a matched filter as the receiver filter, which is not suitable for a non-orthogonal system. Therefore, in this paper, we design the prototype filters considering the MMSE criterion, and propose a system providing the highest SINR in QAM-FBMC which cannot avoid non-orthogonality. In addition, we confirm that the proposed filters show best performance at target SNR than the reference filters.

A Communication Method between High-speed UUV and Distributed Intelligent Nodes

In this paper, a doppler distortion compensation method for underwater transmission of OFDM (Orthogonal Frequency Division Multiplexing) signals is proposed, which is used to realize real-time underwater acoustic communication between high-speed UUV (Unmanned Underwater Vehicle) and intelligent nodes. The method decomposes channel variations based on a functions with a set of known equations. OFDM symbol reconstruction is performed after the Taylor(T) FFT (Fast Fourier Transformation) process. We design an adaptive stochastic gradient descent algorithm based on MMSE criterion to learn the combiner weights for differentially coherent detection, thereby achieving adaptive channel equalization in the underwater acoustic channel. Comprehensive data and experimental data from the recent mobile acoustic communication delta are used to demonstrate the feasibility of this approach. The method can realize high-speed underwater acoustic communication, provide data sample basis for long-term big data analysis, and realize real-time communication result analysis.

Monopulse angle measurement with mainlobe interference based on the auxiliary array

When there is sidelobe interference in the array pattern, adaptive monopulse angle measurement can suppress interference and improve the accuracy of angle measurement. However, when the interference occurs in the mainlobe, the angle measurement performance will be seriously deteriorated. This problem can be solved well with the monopulse angle measurement algorithm based on auxiliary array. Here, auxiliary array radars are added to the main radar to extend the aperture of the array, and using the MSINR criterion or MMSE criterion to suppress the mainlobe interference, a good measurement accuracy can be obtained. The effectiveness of the method is proved by computer simulation.

Distributed Precoding Systems in Multi-Gateway Multibeam Satellites: Regularization and Coarse Beamforming

This paper deals with the problem of beamformer design in a multibeam satellite, which is shared by several clusters of terminals, each served by an earth station, or gateway. Each gateway precodes the symbols addressed to its respective users; the design follows an MMSE criterion, and a judiciously chosen regularization factor accounts for the presence of mutually interfering clusters, extending more classical results applicable to the case of a single centralized station. More importantly, channel statistics can be used instead of instantaneous channel state information, avoiding the exchange of information among gateways through backhaul links. The on-board satellite beamforming weights are designed to exploit the degrees of freedom of the satellite antennas to minimize the noise impact and the interference to some specific users. On-ground beamforming results are provided as a reference to compare the joint performance of MMSE precoders and on-board beamforming network. A non-adaptive design complements the results and makes them more amenable to practical use by designing a coarse beamforming network.

Research on the Pre-coding Technology of Broadcast Stage in Multi-user MIMO System

For the poor transmission reliability of data, this paper focuses on the precoding techniques of the multi-user MIMO system in the broadcast phase in, and the single-user MIMO and multi-user MIMO precoding techniques have been studied. In the multi-user MIMO system, BD-MMSE-VP coding algorithm is proposed to improve the BER performance of the system by using the MMSE criterion to optimize the perturbation vector, and the system uses QR technique to decompose BD channel matrix. Simulation results verify the effective of the proposed precoding algorithm.

A Time-Domain Channel Estimation Method for MIMO-OFDM Systems with Low-Precision Quantization

Considering the cost and power consumption problems of the high-speed wireless communication receiver for high-precision quantization, this paper discusses the time-domain channel estimation for MIMO-OFDM systems with low-precision quantization. The low-precision quantization affects the performance of the system, however, by selecting the appropriate training sequence information, introducing the feedback dither control signal and using the optimized channel estimation algorithm, even with such low-precision (e.g., 1---3 bits) quantization, also can be obtained the performance of comparable the full precision MMSE criterion. Thereby reducing the complexity of the subsequent signal processing, cutting down the cost and power consumption, and effectively reducing the effect of low-precision quantization on the system performance. Theoretical analysis and simulation results show that this method has the characteristics of the fast convergence rate, higher estimation accuracy. Implement the receiver of the low cost, low power consumption and higher transmission efficiency of the system.

Adaptive joint sparse recovery algorithm based on Tabu Search

This paper introduces a novel metaheuristic methodology to address the Multiple Measurement Vectors problem using a well-known greedy search strategy. A modified version of Tabu Search algorithm is utilized to determine a precise estimation of row support and then joint sparse samples are reconstructed using MMSE criterion. The proposed approach is more robust to the sparsity order variations and noise uncertainty, in comparison with the conventional MMV problem solvers. Furthermore, to avoid wastage of the sampling resources and reduce the implementation costs, a two-step joint sparse recovery framework is developed which the first step predicts and adjusts the optimum sampling rate and the second one reconstructs signal vectors applying obtained sampling rate. Numerical simulations demonstrate the superiority of proposed technique for both improving the performance and reducing the computational complexity and sampling costs.

Joint Tx/Rx MMSE Filtering for Single-Carrier MIMO Eigenmode Transmission Using Iterative Interference Cancellation

SUMMARY In this paper, we propose a new joint transmit and receive spatial/frequency-domain filtering for single-carrier (SC) multipleinput multiple-output (MIMO) eigenmode transmission using iterative interference cancellation (IC). Iterative IC is introduced to a previously proposed joint transmit and receive spatial/frequency-domain filtering based on minimum mean square error criterion (called joint Tx/Rx MMSE filtering) to reduce the residual inter-symbol interference (ISI) after the Rx filtering. The optimal Tx/Rx filters are derived based on the MMSE criterion taking into account the iterative IC. The superiority of our proposed

Generalized Precoder Designs Based on Weighted MMSE Criterion for Energy Harvesting Constrained MIMO Channels

This paper studies precoder designs for simultaneous wireless information and power transfer (SWIPT) in multi-input multi-output (MIMO) channels, where a transmitter sends information to information decoding (ID) users while satisfying the minimum energy requirement of energy harvesting users. In contrast to the previous designs focused only on maximum information rate (MIR), we propose a more general and simpler solution using the weighted minimum mean squared error (WMMSE) criterion. To solve the SWIPT-WMMSE problem which is generally non-convex, we suggest two different design schemes, separate and joint designs. Interestingly, it is shown that the joint design achieves optimal performance with a single initial point and a few iterations, while the separate design needs a large number of iterations and initial points to approach the optimum. Based on the observation, we propose a simple closed-form solution, which is shown to achieve near optimal performance with reduced complexity. The derived solution can be adopted in various pragmatic applications of MIMO communications, such as the MMSE, quality-of-service, equal error designs, as well as the MIR by adjusting the weight matrix. We also confirm that our design strategies are a great use for managing co-channel interference in multiple ID-user scenarios. Finally, simulation results demonstrate the efficiency of the proposed MIMO-SWIPT framework.

Research on the Iterative Stopping Criterion Based on Linear Turbo Equalization

Although turbo equalization has superior performance, the data processing delay produced by large iterations has become its major drawback for real-time situations. Based on the MMSE criterion, the normal-probability-plot (NPP) of linear equalizer’s extrinsic information is studied in this paper, with the conclusion of the extrinsic information’s approximate Gaussian distribution obtained. In various conditions, the iterative number can be controlled dynamically based on the extrinsic information statistics. The simulation results approves that the technique is able to make delay dwindle largely with small performance degradation.

A Modified DFE-MMSE Equalization Algorithm

In wireless communication, inter symbol interference (ISI) and signal distortion are often caused by the frequency deviation and time offset of wireless channel. To eliminate or reduce ISI, people proposed the channel equalization technology. However, traditional decision feedback equalization algorithm based on MMSE criterion equalizer (DFE-MMSE) often introduces the error diffusion which degrades the performance of the equalizer in iterative system. In this paper, we propose an improved DFE-MMSE algorithm to reduce the error diffusion and improve the performance of iterative equalization, with a correction factor. Simulation results show that our algorithm achieves better bit error rate, which makes it competent in more practical cases.

State dimension reduction and analysis of quantized estimation systems

The problem of state dimension reduction and quantizer design under communication constraints is discussed for state estimation in quantized linear systems. Subject to the limited signal power, number and bandwidth of the parallel channels, a differential pulse code modulation (DPCM)-like structure is adopted to generate the quantized innovations as the transmitted signals, and the multi-level quantized Kalman filter (MLQ-KF) is used to serve as the pre- and post-filters. The dimension reduction matrix and quantizer are designed jointly under the MMSE criterion of estimation at the channel receiver. To demonstrate the validity of state estimation under the adopted framework, the state estimability based on quantized innovations is analyzed by using information theoretic method. This leads to a sufficient and necessary condition of a certain estimability Gramian matrix having full rank. The quantized Gramian is proved to converge to that of the original unquantized system when the quantization intervals turn to zero. Our work also provides an auxiliary analytic support for the estimation under 1-bit quantization. Simulations show that under communication constraints, the estimation performance is satisfactory when the designed dimension reduction method and quantizer are applied. The analytic conclusion of estimability is also verified by illustrative simulations.

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.