Chapter Summary

Chapter Summary

Key Points

• 1.

  ISAC and coded caching are complementary. Caching reduces communication resource demand by factor $1 + K \mu$, freeing power and bandwidth for sensing.

• 2.

  Three-way tradeoff. The achievable $(R, \text{CRB}, M)$ region forms a convex surface. Pareto frontier parametrized by the sensing-power fraction $\rho$. Caching expands the frontier at every $\rho$.

• 3.

  Sensing outputs drive predictive caching. Prediction accuracy $\alpha \in [0, 1]$ yields expected delivery rate $(1 - \alpha) \cdot R_\text{MAN}$. Perfect prediction eliminates delivery; no prediction recovers MAN.

• 4.

  CommIT contribution (Zhou-Caire 2023) established predictive coded caching with sensing information — bridging the ISAC outputs → caching inputs feedback loop.

• 5.

  V2X / smart-city case studies show 3-10× bandwidth reduction from predictive caching, freeing resources for sensor-critical collision avoidance.

• 6.

  Open problems abound. Converse for the three-way region is unknown. Non-orthogonal resource allocation may improve rate. Multi-target / multi-cell ISAC with caching are active research.

• 7.

  Deployment on 6G horizon (2028-2030). Requires unified cross-layer scheduling, APIs in 3GPP Rel-19+, and integrated RF hardware. Major engineering work remains; research-practice gap is substantial.