Chapter Summary

Chapter Summary

Key Points

• 1.

  RIS-ISAC enables simultaneous comm and sensing from one panel. A RIS reshapes both the communication path (BS→UE via RIS) and the sensing path (BS→target→BS via RIS). Single waveform, single hardware, two services — the 6G ISAC vision.

• 2.

  Sensing SNR scales as $N^4$, twice the rate of comm's $N^2$. The round-trip radar path passes through the RIS twice; coherent combining on each hop gives $N^2$ amplitude (power = squared), total $N^4$ sensing SNR gain. RIS is disproportionately more valuable for sensing than for communication — at $N = 256$, sensing gain is $\sim 96$ dB vs. communication gain of $\sim 48$ dB.

• 3.

  The Pareto frontier trades comm vs. sensing via tradeoff parameter $\lambda$. Scalarized problem $\max (1-\lambda) R_{\text{comm}} + \lambda R_{\text{sens}}$ over $(\mathbf{W}, \boldsymbol{\Phi})$. $\lambda$ sweeps from 0 (comm-only) to 1 (sensing-only). The RIS-aided frontier is a convex outward expansion of the no-RIS frontier.

• 4.

  The CommIT RIS-ISAC framework (Caire, Liu, Atzeni 2023). SDR lift of both $\mathbf{W}$ and $\boldsymbol{\Phi}$ gives a tight convex relaxation. For rank-1 radar targets + $K \leq N_t$ users, SDR is exactly tight (no gap). For higher rank, Gaussian randomization extracts $< 1$ dB optimality gap. Warm-start AO refinement gives deployment-grade solutions in real time.

• 5.

  Target deployments: automotive V2X, smart-city sensing, industrial safety. The RIS dual-function paradigm works best when (a) comm users and radar targets coexist in the coverage area, (b) moderate mobility, and (c) a single panel can geometrically see both. Emerging 6G deployments are natural fits.