Fractionally Spaced Constant Modulus Blind Equalization Algorithm
Fractionally spaced constant modulus blind equalization algorithm designed for SIMO systems, delivering superior performance with efficient signal recovery capabilities
Explore MATLAB source code curated for "性能" with clean implementations, documentation, and examples.
Fractionally spaced constant modulus blind equalization algorithm designed for SIMO systems, delivering superior performance with efficient signal recovery capabilities
CDMA system simulation program with validated performance analysis under various environmental conditions, featuring customizable parameters for signal processing and interference studies
This source code implements a comprehensive simulation of OFDM communication system performance. The simulation supports multiple modulation schemes including BPSK, QPSK, MSK, and QAM, and models both AWGN and Rayleigh channels. Additionally, it includes a specialized simulation for IEEE802.11a-compliant OFDM systems with pilot insertion for enhanced performance. The code structure implements key OFDM components such as IFFT/FFT operations, cyclic prefix addition/removal, and channel equalization algorithms.
Performance comparison through simulation of convolutional code encoding and Viterbi decoding algorithms, with code implementation insights
MATLAB simulation program for LDPC code performance evaluation (BPSK modulation, AWGN channel)
The cubic spline algorithm demonstrates excellent performance in both image encoding and decoding operations, although its computational intensity reduces overall efficiency. We propose a fast algorithm that maintains quality while optimizing processing speed through improved interpolation calculations and boundary condition handling.
This coding scheme has been adopted in the DVB-S2 standard. The MATLAB program is designed to investigate the performance of LDPC codes through simulation and analysis of key parameters like bit error rate and signal-to-noise ratio.
QPSO significantly outperforms basic PSO in global search performance while achieving faster convergence speeds, making it ideal for complex optimization problems.
An improved Particle Swarm Optimization (PSO) algorithm based on hybrid strategies, implemented through two core source files: the main execution program (hpso.m) and parameter configuration module (hPSOoptions.m). The codebase features clean architecture with modular design, facilitating straightforward customization and performance enhancements. Experimental results demonstrate significant improvements over Standard PSO (SPSO) in optimization efficiency.
A BPSK performance simulation system implemented using MATLAB/Simulink with AWGN channel modeling. After running the simulation, users can observe the signal-to-noise ratio gain achieved through BPSK modulation and demodulation processes.