🤖 AI Summary
Existing analytical channel models for three-dimensional molecular communication with spherical absorbing receivers are restricted to one-dimensional or planar flow configurations, lacking a general and accurate solution for arbitrary uniform drift directions.
Method: This paper derives, for the first time, a closed-form analytical expression for the three-dimensional channel impulse response (CIR) of a spherical absorbing receiver under arbitrary drift directions. The core technique applies Girsanov’s theorem to perform a drift correction on the Brownian motion path measure, rigorously transforming the static absorption problem into an equivalent drifted-medium first-passage time problem.
Contribution/Results: The proposed method overcomes geometric and directional constraints, enabling precise modeling of molecular propagation under arbitrary flow fields. It supports rapid analytical computation of key performance metrics—including peak time and amplitude—thereby significantly reducing reliance on computationally intensive Monte Carlo simulations and providing a solid theoretical foundation for system design and optimization.
📝 Abstract
Accurate channel modeling for spherical absorbing receivers is fundamental to the design of realistic molecular multiple-input multiple-output (MIMO) systems. While advanced modulation schemes have been proposed to mitigate interference, determining the channel impulse response (CIR) under arbitrary flow directions remains a challenge; existing exact solutions are restricted to either 1-D/no-drift scenarios or planar receiver geometries. Addressing this gap, we derive the first exact analytical CIR for a spherical receiver in a 3-D molecular communication system with uniform drift in an arbitrary direction. Unlike prior approximations that ignore the angle between the drift and the transmission axis, our approach utilizes the Girsanov theorem to analytically transform the hitting-time distribution from a stationary medium to a drifted one. The proposed closed-form expression not only eliminates modeling errors inherent in previous approximations for off-axis receivers but also enables efficient parameter-space exploration of critical system metrics (e.g., peak time and amplitude), a task that would be computationally costly with pure simulation-based approaches.