Chapter 31: Hardware, Datasets, Simulation, and Evaluation

Learning Objectives

• Survey hardware platforms for RF imaging (mmWave, sub-6 GHz, SDR) and their trade-offs
• Identify standard datasets and generate synthetic data while avoiding the inverse crime
• Understand the CommIT simulator architecture and Monte Carlo methodology
• Apply image quality metrics (PSNR, SSIM, LPIPS), shape metrics (Chamfer, IoU), and detection metrics (ROC)
• Design reproducible experiments using open-source libraries (DeepInverse, ODL, Pyxu)