Explore MATLAB source code curated for "多天线" with clean implementations, documentation, and examples.
Comparative simulation of channel capacity between MIMO (Multiple-Input Multiple-Output) and single-antenna systems, including algorithm implementations and performance analysis with executable code examples
Multi-antenna cognitive radio systems offer not only traditional resources (frequency, time, and code domains) but also spatial domain resources compared to single-antenna systems. This paper investigates game theory-based resource allocation in limited-feedback cognitive MIMO systems, focusing on the distribution of transmission power, spatial resources (via beamforming), and feedback rates. Using limited feedback channels to transmit quantized Channel State Information (CSI), we explore several optimization problems including: 1) Joint power allocation and beamforming optimization (implementable through iterative algorithms like gradient descent or convex optimization solvers such as CVX), 2) Feedback rate control for secondary users (cognitive/unlicensed users) using dynamic programming or threshold-based algorithms, and 3) Joint power allocation and feedback rate control (solvable via Lagrange multiplier methods or heuristic approaches). The research introduces implementation frameworks for adaptive resource allocation in cognitive radio networks.
A simulation program for space-time coding in wireless communication systems, featuring multi-antenna transmission and reception with fading channel modeling capabilities.
This MATLAB program simulates a multi-antenna multi-relay dual-hop amplify-and-forward relaying system operating over Nakagami-m fading channels. The function outputs the outage probability, which is calculated using signal-to-noise ratio (SNR) threshold comparisons and stochastic channel modeling. The implementation includes matrix operations for channel coefficient generation and relay signal processing.