Exploiting Diversity in One-Shot Molecular Timing Channels via Order Statistics

Abstract

We study diversity in one-shot communication over molecular timing channels. We consider a channel model where the transmitter simultaneously releases a large number of information particles, while the information is encoded in the time of release. The receiver decodes the information based on the random time of arrival of the information particles. The random propagation is characterized by the general class of right-sided unimodal densities. We characterize the asymptotic exponential decrease rate of the probability of error as a function of the number of released particles, and denote this quantity as the system diversity gain. Four types of detectors are considered: the maximum-likelihood (ML) detector, a linear detector, a detector that is based on the first arrival (FA) among all the transmitted particles, and a detector based on the last arrival (LA). When the density characterizing the random propagation is supported over a large interval, we show that the simple FA detector achieves a diversity gain very close to that of the ML detector. On the other hand, when the density characterizing the random propagation is supported over a small interval, we show that the simple LA detector achieves a diversity gain very close to that of the ML detector.The authors are with the

Transmitter and Receiver Architectures for Molecular Communications: A Survey on Physical Design With Modulation, Coding, and Detection Techniques

“…However, the ML detection still performs significantly better than the FA for high values of M . The detection based on the order statistics has been extended in the same authors' later work [208], where they consider also the detection based on the last arrival (LA) time. Defining a system diversity gain as the asymptotic exponential decrease rate of error probability with the increased number of released particles, they showed that the diversity gain of the LA detector approaches to that of computationally expensive ML detector.…”

Molecular Information Delivery in Porous Media

“…IV. We note that a similar definition of α was studied in [11] for timing channels, but our method for evaluating α is different from [11].…”

“…1) Assuming that the number of molecules arrived can be approximated as a Gaussian random variable (RV), we present numerical results for different performance metrics, i.e., throughput, mutual information, and error probability, for the channel using fully resolved computational fluid dynamics results for the breakthrough curves. We also numerically evaluate the diversity gain that is defined (as in [11]) as the exponential decrease rate of the probability of error as the number of released molecules increases. 2) Using numerical results, we investigate the differences in channel characteristics and performance metrics between a PM and diffusive FS channel with flow.…”

Towards High Data-Rate Diffusive Molecular Communications: Performance Enhancement Strategies

“…These low rates might be acceptable for some applications where the information to be transmitted is limited and the design goals target low-complexity and low energy consumption. Several examples to these applications are one-shot DiMC or DiMC with very long symbol durations [6], [7], anomaly detection [8], [9], entity localization [10], [11], bio-sensing applications, etc. On the other hand, at both micro-and macro-scales, employing DiMC for digital communication links naturally elicits interest in increasing data rates.…”