Symbol Synchronization for Diffusive Molecular Communication Systems

Symbol synchronization refers to the estimation of the start of a symbol interval and is needed for reliable detection. In this paper, we develop a symbol synchronization framework for molecular communication (MC) systems where we consider some practical challenges which have not been addressed in the literature yet. In particular, we take into account that in MC systems, the transmitter may not be equipped with an internal clock and may not be able to emit molecules with a fixed release frequency. Such restrictions hold for practical nanotransmitters, e.g. modified cells, where the lengths of the symbol intervals may vary due to the inherent randomness in the availability of food and energy for molecule generation, the process for molecule production, and the release process. To address this issue, we propose to employ two types of molecules, one for synchronization and one for data transmission. We derive the optimal maximum likelihood (ML) symbol synchronization scheme as a performance upper bound. Since ML synchronization entails high complexity, we also propose two low-complexity synchronization schemes, namely a peak observation-based scheme and a threshold-trigger scheme, which are suitable for MC systems with limited computational capabilities. Our simulation results reveal the effectiveness of the proposed synchronization~schemes and suggest that the end-to-end performance of MC systems significantly depends on the accuracy of symbol synchronization.Comment: This paper has been accepted for presentation at IEEE International Conference on Communications (ICC) 201

Diffusive Mobile Molecular Communications Over Time-Variant Channels

This letter introduces a formalism for modeling time-variant channels for diffusive molecular communication systems. In particular, we consider a fluid environment where one transmitter nano-machine and one receiver nano-machine are subjected to Brownian motion in addition to the diffusive motion of the information molecules used for communication. Due to the stochastic movements of the transmitter and receiver nano-machines, the statistics of the channel impulse response change over time. We show that the time-variant behaviour of the channel can be accurately captured by appropriately modifying the diffusion coefficient of the information molecules. Furthermore, we derive an analytical expression for evaluation of the expected error probability of a simple detector for the considered system. The accuracy of the proposed analytical expression is verified via particle-based simulation of the Brownian motion.Comment: 4 pages, 3 figures, 1 table. Accepted for publication in IEEE Communications Letters (Author's comment: Manuscript submitted Jan. 19, 2017; revised Feb. 20, 2017; accepted Feb. 22, 2017

Amplify-and-Forward Relaying in Two-Hop Diffusion-Based Molecular Communication Networks

This paper studies a three-node network in which an intermediate nano-transceiver, acting as a relay, is placed between a nano-transmitter and a nano-receiver to improve the range of diffusion-based molecular communication. Motivated by the relaying protocols used in traditional wireless communication systems, we study amplify-and-forward (AF) relaying with fixed and variable amplification factor for use in molecular communication systems. To this end, we derive a closed-form expression for the expected end-to-end error probability. Furthermore, we derive a closed-form expression for the optimal amplification factor at the relay node for minimization of an approximation of the expected error probability of the network. Our analytical and simulation results show the potential of AF relaying to improve the overall performance of nano-networks.Comment: 7 pages, 6 figures, 1 table. Submitted to the 2015 IEEE Global Communications Conference (GLOBECOM) on April 15, 201

Channel Estimation for Diffusive Molecular Communications

In molecular communication (MC) systems, the \textit{expected} number of molecules observed at the receiver over time after the instantaneous release of molecules by the transmitter is referred to as the channel impulse response (CIR). Knowledge of the CIR is needed for the design of detection and equalization schemes. In this paper, we present a training-based CIR estimation framework for MC systems which aims at estimating the CIR based on the \textit{observed} number of molecules at the receiver due to emission of a \textit{sequence} of known numbers of molecules by the transmitter. Thereby, we distinguish two scenarios depending on whether or not statistical channel knowledge is available. In particular, we derive maximum likelihood (ML) and least sum of square errors (LSSE) estimators which do not require any knowledge of the channel statistics. For the case, when statistical channel knowledge is available, the corresponding maximum a posteriori (MAP) and linear minimum mean square error (LMMSE) estimators are provided. As performance bound, we derive the classical Cramer Rao (CR) lower bound, valid for any unbiased estimator, which does not exploit statistical channel knowledge, and the Bayesian CR lower bound, valid for any unbiased estimator, which exploits statistical channel knowledge. Finally, we propose optimal and suboptimal training sequence designs for the considered MC system. Simulation results confirm the analysis and compare the performance of the proposed estimation techniques with the respective CR lower bounds.Comment: to be appeared in IEEE Transactions on Communications. arXiv admin note: text overlap with arXiv:1510.0861