Part 4: Near-Field, XL-MIMO, and Hardware-Aware Design
Chapter 18: XL-MIMO Channel Estimation
Research~260 min
Learning Objectives
- Define a visibility region (VR) as the subset of array elements illuminated by a user and explain why XL-MIMO arrays induce spatial non-stationarity
- Model the VR binary mask with a 2D Markov random field prior and connect the MRF parameters to physical cluster sizes
- Derive a message-passing / variational inference procedure for MAP VR detection from noisy pilot observations
- Decompose XL-MIMO channel estimation into subarray-level operations and analyze the complexity reduction
- Exploit the spherical wavefront structure to build a polar-domain dictionary for near-field sparse channel estimation
- Combine VR detection and channel estimation into a joint EM procedure and quantify performance vs pilot overhead
- Relate VR mismatch penalties to classical pilot contamination (Ch. 3) and contrast with far-field stationary models
Sections
Prerequisites
Near-field communications: Fraunhofer distance, spherical wavefront (MIMO Ch. 17)Channel estimation and pilot design: LS, MMSE, pilot contamination (MIMO Ch. 3)Spatial correlation and one-ring model (MIMO Ch. 2)Sparse recovery: compressed sensing, basis pursuit, OMP (FSI Ch. 12)Markov random fields and graphical models (probability background)EM algorithm and variational inference (estimation background)
💬 Discussion
Loading discussions...