Explore MATLAB source code curated for "mmse" with clean implementations, documentation, and examples.
MATLAB code for graduation project implementing VBLAST decoding algorithms including Zero Forcing (ZF), Minimum Mean Square Error (MMSE), QR decomposition, ZF with Interference Cancellation (ZF_IC), and MMSE with Interference Cancellation (MMSE+IC), featuring performance comparison and implementation analysis
This study compares the SER (Symbol Error Rate) and BER (Bit Error Rate) performance of MLSE (Maximum Likelihood Sequence Estimation) equalization and MMSE (Minimum Mean Square Error) frequency-domain equalization for BPSK, QPSK, 8PSK, and 16QAM modulation techniques under known channel conditions, with implementation insights and algorithm explanations.
Students and professionals in communication engineering know that signal processing algorithm implementation can be quite complex. This resource provides essential adaptive signal processing algorithms including LMS (Least Mean Squares), RLS (Recursive Least Squares), and MMSE (Minimum Mean Square Error) with practical implementation insights to facilitate easier coding and application.
Channel estimation simulation implementing multiple methods: linear interpolation, MMSE (Minimum Mean Square Error), 1-dimensional MMSE, and 2-dimensional MMSE with algorithm comparisons and performance analysis
Comprehensive simulation of OFDM channel estimation techniques including Least Squares (LS) and Minimum Mean Square Error (MMSE) algorithms with complete MATLAB implementation
Comprehensive overview of ZF, MMSE, QPSK, 16-QAM, MIMO 2x2/4x4, and V-BLAST technologies with signal processing implementations
A comprehensive comparison of multiuser detection algorithms including Decorrelation, MMSE (Minimum Mean Square Error), SIC (Successive Interference Cancellation), and PIC (Parallel Interference Cancellation), featuring implementation approaches and performance analysis
A comprehensive analysis of Zero-Forcing (ZF) and Minimum Mean Square Error (MMSE) pre-equalization linear precoding methods, including performance comparison and implementation considerations.
This primary simulation code, titled "Comparison of Equalization Schemes," implements modular functions to calculate bit error rates (BER) for various equalizer types. The implementation includes Time Domain Equalizers (TDE) employing Minimum Mean Square Error (MMSE) and Zero Forcing (ZF) algorithms, Time Domain Decision Feedback Equalizers (DF_TDE), and Linear Frequency Domain Equalizers (FDE) with MMSE/ZF variants. Each function incorporates channel modeling with QPSK modulation over tapped-delay-line channels with additive white Gaussian noise.
MATLAB code implementation of Minimum Mean Square Error (MMSE) equalization for Orthogonal Frequency Division Multiplexing (OFDM) systems, including detailed algorithm description and practical application examples