Explore MATLAB source code curated for "MIMO系统" with clean implementations, documentation, and examples.
Simulation program for wireless communication MIMO systems, featuring comprehensive documentation and source code with detailed explanations of signal processing algorithms and antenna configuration implementations.
Simulation of a 4x4 MIMO system model, presenting the transmission characteristics with code implementation insights.
Simulation of MIMO systems including space-time coding and multi-user MIMO implementations with algorithmic explanations
A comprehensive resource featuring classical channel models with MATLAB implementations, specifically focused on MIMO (Multiple-Input Multiple-Output) systems, including detailed algorithm explanations and key function descriptions.
This simulation investigates multi-user detection in MIMO systems, covering configurations with 1 transmitter and 4 receivers (1x4), 2x4, 3x4, and 4x4 antenna setups, and includes corresponding bit error rate (BER) performance curves. The implementation involves signal processing algorithms and detection techniques commonly used in MIMO communications.
System Identification and Adaptive Control - Recursive Least Squares Parameter Estimation for MIMO Systems (This program is designed for 2-input 2-output systems with implementation of RLS algorithm and real-time parameter updating)
This program provides implementations of V-BLAST MIMO system detection algorithms supporting various modulation schemes, including Zero-Forcing (ZF), Minimum Mean Square Error (MMSE), Maximum Likelihood (ML), and Serial Interference Cancellation (SIC) detection algorithms. Excellent resource for beginners with comprehensive code examples and detailed documentation.
Simulation of MIMO System Channel Capacity under AWGN Conditions with Implementation for Performance Analysis
Original MATLAB code for channel estimation in MIMO systems, featuring implementation details and algorithm explanations
Application Context: Applied to signal detection at the receiver end of communication MIMO systems. For received signals, detection and estimation are required to determine the estimated values of transmitted source symbols and compute error probabilities. Key Technologies: ZF detection algorithm and MMSE detection algorithm, implemented with matrix inversion and optimization techniques to enhance signal recovery accuracy.