Chapter Summary
Chapter Summary
Key Points
- 1.
The cascaded channel model. For a BS with antennas, an RIS with elements, and a UE with antennas, the effective end-to-end channel is , a matrix linear in the RIS phase vector . The Khatri-Rao identity is the workhorse that every optimization algorithm exploits.
- 2.
Rank and keyhole. The rank of is bounded by . Pure LoS on both hops gives a rank-1 cascade β the RIS keyhole, which eliminates multi-stream multiplexing regardless of BS or UE antenna count. Rich scattering on either (or both) sides is required for multi-stream operation.
- 3.
LoS RIS phases are a spatial sawtooth. Under LoS on both hops, the optimal RIS phase is a linear (for planar arrays, bilinear) function of element index: , where are determined by the BS and UE directions. This is the phased-array "generalized reflection" pattern.
- 4.
Cascaded Rayleigh has fatter tails. For small , cascaded Rayleigh fading yields higher outage probability than direct Rayleigh of the same mean SNR. At , the CLT approximates the cascaded distribution back to Gaussian, and the "keyhole penalty" in outage vanishes. Another reason to design with hundreds of elements.
- 5.
Near-field at sub-THz is the rule, not the exception. The Fraunhofer distance can exceed a kilometer for 1-m apertures at 140 GHz. Inside , wavefront curvature across the aperture enables distance-specific focusing and adds extra degrees of freedom absent in the far-field. Near-field modeling is essential for sub-THz RIS design; it is the technical foundation of the array-fed RIS architecture (Chapter 11).
Looking Ahead
We now have the full signal model in hand. Chapter 4 attacks the first practical question the model raises: how does the system estimate and in the first place, given that the RIS is passive and cannot transmit pilots? The answer β ON/OFF switching patterns, DFT codebooks, and compressed sensing β sets up the optimization chapters 5β8, which finally exploit the cascaded model to design and jointly.