Error control in bacterial quorum communications

Quorum sensing (QS) is used to describe the communication between bacterial cells, whereby a coordinated population response is controlled through the synthesis, accumulation and subsequent sensing of specific diffusible chemical signals called autoinducers, enabling a cluster of bacteria to regulate gene expression and behavior collectively and synchronously, and assess their own population. As a promising method of molecular communication (MC), bacterial populations can be programmed as bio-transceivers to establish information transmission using molecules. In this work, to investigate the key features for MC, a bacterial QS system is introduced, which contains two clusters of bacteria, specifically Vibrio fischeri, as the transmitter node and receiver node, and the diffusive channel. The transmitted information is represented by the concentration of autoinducers with on-off keying (OOK) modulation. In addition, to achieve better reliability and energy efficiency, different error control techniques, including forward error correction (FEC) and Automatic Repeat reQuest (ARQ) are taken into consideration. For FEC, this work presents a comparison of the performance of traditional Hamming codes, Minimum Energy Codes (MEC) and Luby Transform (LT) codes over the channel. In addition, it applied several ARQ protocols, namely Stop-N-Wait (SW-ARQ), Go-Back-N (GBN-ARQ), and Selective-Repeat (SR-ARQ) combined with error detection codes to achieve better reliability. Results show that both the FEC and ARQ techniques can enhance the channel reliability, and that ARQ can resolve the issue of out-of-sequence and duplicate packet delivery. Moreover, this work further addresses the question of optimal frame size for data communication in this channel capacity and energy constrained bacterial quorum communication system. A novel energy model which is constructed using the experimental validated synthetic logic gates has been proposed to help with the optimization process. The optimal fixed frame length is determined for a set of channel parameters by maximizing the throughput and energy efficiency matrix

Throughput and energy efficiency based packet size optimization of ARQ protocols in bacterial quorum communications

The discovery that bacteria use signalling molecules, which are released into the environment, to communicate with each other changed our general perception of organisms inhabiting the world. Nowadays, the term quorum sensing is used to describe the phenomenon whereby a coordinated population response is controlled by exchanging specific diffusible chemical signals called autoinducers, enabling a cluster of bacteria to regulate their gene expression and behaviour collectively and synchronously. Bacteria assess their own population and coordinate their actions through the synthesis, accumulation and subsequent sensing of autoinducers. In this work, a bacterial quorum communication system is introduced, which contains two clusters of bacteria, specifically Vibrio fischeri, a gram-negative marine bacterium, as the transmitter node and receiver node, and the diffusive channel. The transmitted information is encoded into the concentration of autoinducers, with binary representation, and then, it is divided into frames for transmission. Automatic Repeat reQuest protocols are applied to achieve better reliability. In addition, this paper addresses the question of optimal frame size for data communication in this channel capacity and energy constrained bacterial quorum communication system. The optimal fixed frame length is determined for a set of channel parameters by maximising the throughput and energy efficiency matrix

Channel Coding in Molecular Communication

This dissertation establishes and analyzes a complete molecular transmission system from a communication engineering perspective. Its focus is on diffusion-based molecular communication in an unbounded three-dimensional fluid medium. As a basis for the investigation of transmission algorithms, an equivalent discrete-time channel model (EDTCM) is developed and the characterization of the channel is described by an analytical derivation, a random walk based simulation, a trained artificial neural network (ANN), and a proof of concept testbed setup. The investigated transmission algorithms cover modulation schemes at the transmitter side, as well as channel equalizers and detectors at the receiver side. In addition to the evaluation of state-of-the-art techniques and the introduction of orthogonal frequency-division multiplexing (OFDM), the novel variable concentration shift keying (VCSK) modulation adapted to the diffusion-based transmission channel, the lowcomplex adaptive threshold detector (ATD) working without explicit channel knowledge, the low-complex soft-output piecewise linear detector (PLD), and the optimal a posteriori probability (APP) detector are of particular importance and treated. To improve the error-prone information transmission, block codes, convolutional codes, line codes, spreading codes and spatial codes are investigated. The analysis is carried out under various approaches of normalization and gains or losses compared to the uncoded transmission are highlighted. In addition to state-of-the-art forward error correction (FEC) codes, novel line codes adapted to the error statistics of the diffusion-based channel are proposed. Moreover, the turbo principle is introduced into the field of molecular communication, where extrinsic information is exchanged iteratively between detector and decoder. By means of an extrinsic information transfer (EXIT) chart analysis, the potential of the iterative processing is shown and the communication channel capacity is computed, which represents the theoretical performance limit for the system under investigation. In addition, the construction of an irregular convolutional code (IRCC) using the EXIT chart is presented and its performance capability is demonstrated. For the evaluation of all considered transmission algorithms the bit error rate (BER) performance is chosen. The BER is determined by means of Monte Carlo simulations and for some algorithms by theoretical derivation