Diffusion-Based Molecular Communication With Limited Molecule Production Rate

Abstract

This paper studies the impact of a transmitter's molecule generation process on the capacity of a concentration based Molecular Communication (MC) system. Constraints caused by the molecule generation process affect the availability of the molecules at the transmitter. The transmitter has a storage of molecules, and should decide whether to release or save the currently produced molecules. As a result, the MC system has conceptual connections with energy harvesting systems. In this paper, we consider two scenarios on the propagation channel. The first scenario assumes a channel with no Inter-symbol Interference (ISI), i.e., a memoryless channel. We derive bounds on the capacity of the MC system in this scenario. The second scenario assumes the MC network with ISI, in which the output of the channel depends on the history of released molecules in the pervious time-slots. Based on the assumptions that either the transmitter or the receiver knows the channel statistics, we compute a lower bound on the channel capacity. 1 Index Terms-Molecular communication (MC) network, Channel Capacity, inter-symbol interference (ISI).

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

“…However, at dimensions in question, without any replenishment, these reservoirs will inevitably deplete, rendering the nanomachine functionally useless in terms of MC. Moreover, the replenishment rate of transmitter reservoirs has a direct effect on achievable communication rates [16], [17]. Possible theoretically proposed scenarios for reservoir replenishment include local synthesis of IMs, e.g., use of genetically engineered bacteria whose genes are regulated to produce the desired transmitter proteins [18], as well as employment of transmitter harvesting methods [19].…”

Universal Transceivers: Opportunities and Future Directions for the Internet of Everything (IoE)

“…On the molecular level, energy-aware algorithms can be used for efficient coordination and movement EH nanonetworks, e.g., engineered bacteria tracking and eliminating harmful targets in the human body (Islam et al, 2020). Since the molecules harvested for energy generation can also transport information, the EH process directly governs data transmissions (Bafghi et al, 2018). Other approaches, such as feedback control, are also promising for energy-aware MC, especially in diffusion-based information transfer (Musa et al, 2020).…”

On the IID Capacity-Achieving Input for Binding Channels With Multiple Ligand Receptors

“…In addition, considering that the molecule generator in the source has a limited productivity, the concentrations is hence assumed to satisfy an average constraintc ∈ [c L , c H ]. Note that this assumption has been adopted in the previous works [13] and [27] to make the model more realistic.…”

“…As an upper bound of the channel capacity C defined in (13), C FB can be used to evaluate the tightness of C IID approximating to the channel capacity C. It can be concluded that C IID provides a tight lower bound of C.…”

“…However, these previous works on the channel capacity analysis of the ligand-binding process or the binding channels only considered a peak constraint on the channel input, which implies the ligand concentration can be chosen arbitrarily in a closed range. Whereas, due to the finite reaction rate and limited storage space, most ligand generators, including living cells and synthetic nano-machines,have limited productivity and hence can not continuously transmit ligands in high concentrations [13]. Therefore, an average constraint on the input should be considered, which will lead to some novel characteristics on the capacity-achieving distribution.…”