Explore MATLAB source code curated for "最小均方误差" with clean implementations, documentation, and examples.
This program implements and demonstrates the MMSE-Ordered SIC detection algorithm for digital communication systems, featuring detailed algorithm workflow and MATLAB implementation examples.
Implementation of MSE calculation for least squares algorithm, minimum mean square error algorithm, and related approaches with MATLAB code examples
A comparative analysis of decorrelation and minimum mean square error techniques versus conventional multiuser detectors, with implementation insights
Layered space-time codes employ three widely-used detection algorithms: Maximum Likelihood (ML) detection, Zero Forcing (ZF) detection, and Minimum Mean Squared Error (MMSE) detection. Each algorithm involves distinct computational approaches, including exhaustive search techniques, matrix inversion operations, and statistical noise compensation methods.
A MATLAB implementation for simulating the minimum mean square error between estimated channels and true channels obtained through channel estimation algorithms, featuring various estimation techniques and performance analysis.
Multiple signal detection algorithms for multi-antenna systems encompass Zero-Forcing (ZF), Minimum Mean Square Error (MMSE), Maximum Likelihood (ML), Enhanced Maximum Likelihood, and other advanced techniques.
MATLAB simulation of the Minimum Mean Square Error (MMSE) algorithm with code implementation details and performance analysis
In a DS-spread spectrum system with additive white Gaussian noise, a comprehensive performance comparison of conventional single-user detection, linear decorrelating multiuser detection, and minimum mean square error multiuser detection techniques
Updated complete version: Performance comparison between conventional single-user detection, linear decorrelating multiuser detection, and minimum mean square error multiuser detection in DS-spread spectrum systems with additive white Gaussian noise, including implementation insights and MATLAB code considerations.
MATLAB simulation and implementation of minimum mean square error (MMSE) signal-to-noise ratio (SNR) estimation algorithm with performance analysis