Estimation and Optimization for Molecular Communications with a Coexistence Constraint

Abstract : At present, molecular communications has largely been studied in isolation; that is, without the presence of any external biological systems. However, for applications in nanomedicine and advanced manufacturing, this assumption of isolation is unlikely to always hold. A key question is therefore how to design signaling strategies such that the desired information can be communicated, while not disrupting the function of the external biological system. In this paper, we study this problem by establishing a coexistence constraint based on the Kullback-Leibler divergence between the distribution of molecules on the surface of the biological system, with and without the presence of the molecular communication system. We then address the problem of how the transmitting device can estimate these distributions from local observations of its environment. Based on this, we optimize the modulation scheme used by the transmitter subject to the coexistence constraint. Trade-offs between the coexistence constraint, the probability of error, and the number of samples used to estimate distributions needed to compute the coexistence constraint are then studied numerically.
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Malcolm Egan, Valeria Loscri, Ido Nevat, Trung Duong, Marco Di Renzo. Estimation and Optimization for Molecular Communications with a Coexistence Constraint. ACM NanoCom 2019 - 6th ACM International Conference on Nanoscale Computing and Communication, Sep 2019, Dublin, Ireland. ⟨10.1145/nnnnnnn.nnnnnnn⟩. ⟨hal-02178421⟩

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