Communication Principles Experiment_Fundamentals of MATLAB Simulation

To optimize communication system design, we must conduct in-depth research on statistical characteristics of received signals in wireless environments. The simulation scenario involves: multiple obstacles blocking the line-of-sight path between transmitter and receiver, large separation distance (exceeding 500 meters), substantial number of randomly distributed obstacles (N>50), uniform reflection signal strength at receiver (energy E=1), and 1GHz carrier frequency. Our MATLAB implementation will address the following aspects:

1. Phase distribution analysis of received sinusoidal waves: We'll generate multiple signal paths using random phase generation (rand function in MATLAB) and perform distribution fitting using fitdist to identify optimal probability distributions.

2. Statistical characterization of signal amplitude: The code will compute mean and variance through mean() and var() functions, then visualize the probability density function using histogram with 'pdf' normalization and fitting curves.

3. Rayleigh distribution investigation: We'll implement raylpdf function to plot PDF curves with parameter √(N·E), comparing theoretical expectations (σ√(π/2)) and variance (σ²(2-π/2)) with simulation results using analytical calculations.

4. Mobile receiver analysis: By fixing obstacle positions and simulating receiver motion at 1m/s and 10m/s velocities, we'll plot signal envelope variations over time using envelope detection algorithms. Comparative analysis of the curves will reveal velocity-dependent transmission characteristics, providing crucial data for communication system optimization.