11 research outputs found
Simplified Cooperative Detection for Multi-Receiver Molecular Communication
Diffusion-based molecular communication (MC) systems experience significant
reliability losses. To boost the reliability, an MC scheme where multiple
receivers (RXs) work cooperatively to decide the signal of a transmitter (TX)
by sending the same type of molecules to a fusion center (FC) is proposed in
this paper. The FC observes the total number of molecules received and compares
this number with a threshold to determine the TX's signal. The proposed scheme
is more bio-realistic and requires relatively low computational complexity
compared to existing cooperative schemes where the RXs send and the FC
recognizes different types of molecules. Asymmetric and symmetric topologies
are considered, and closed-form expressions are derived for the global error
probability for both topologies. Results show that the trade-off for simplified
computations leads to a slight reduction in error performance, compared to the
existing cooperative schemes.Comment: 5 pages, 4 figures, Will be presented as an invited paper at the 2017
IEEE Information Theory Workshop in November 2017 in Kaohsiung, Taiwa
Capacity of Molecular Channels with Imperfect Particle-Intensity Modulation and Detection
This work introduces the particle-intensity channel (PIC) as a model for
molecular communication systems and characterizes the properties of the optimal
input distribution and the capacity limits for this system. In the PIC, the
transmitter encodes information, in symbols of a given duration, based on the
number of particles released, and the receiver detects and decodes the message
based on the number of particles detected during the symbol interval. In this
channel, the transmitter may be unable to control precisely the number of
particles released, and the receiver may not detect all the particles that
arrive. We demonstrate that the optimal input distribution for this channel
always has mass points at zero and the maximum number of particles that can be
released. We then consider diffusive particle transport, derive the capacity
expression when the input distribution is binary, and show conditions under
which the binary input is capacity-achieving. In particular, we demonstrate
that when the transmitter cannot generate particles at a high rate, the optimal
input distribution is binary.Comment: Accepted at IEEE International Symposium on Information Theory (ISIT
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Maximum Likelihood Detection With Ligand Receptors for Diffusion-Based Molecular Communications in Internet of Bio-Nano Things.
Molecular Communication (MC) is a bio-inspired communication technique that uses molecules as a method of information transfer among nanoscale devices. MC receiver is an essential component having profound impact on the communication system performance. However, the interaction of the receiver with information bearing molecules has been usually oversimplified in modeling the reception process and developing signal detection techniques. In this paper, we focus on the signal detection problem of MC receivers employing receptor molecules to infer the transmitted messages encoded into the concentration of molecules, i.e., ligands. Exploiting the observable characteristics of ligand-receptor binding reaction, we first introduce a Maximum Likelihood (ML) detection method based on instantaneous receptor occupation ratio, as aligned with the current MC literature. Then, we propose a novel ML detection technique, which exploits the amount of time the receptors stay unbound in an observation time window. A comprehensive analysis is carried out to compare the performance of the detectors in terms of bit error probability. In evaluating the detection performance, emphasis is given to the receptor saturation problem resulting from the accumulation of messenger molecules at the receiver as a consequence of intersymbol interference. The results reveal that detection based on receptor unbound time is quite reliable even in saturation, whereas the reliability of detection based on receptor occupation ratio substantially decreases as the receiver gets saturated. Finally, we also discuss the potential methods of implementing the detectors
Capacities and Optimal Input Distributions for Particle-Intensity Channels
This work introduces the particle-intensity channel (PIC) as a model for
molecular communication systems and characterizes the capacity limits as well
as properties of the optimal (capacity-achieving) input distributions for such
channels. In the PIC, the transmitter encodes information, in symbols of a
given duration, based on the probability of particle release, and the receiver
detects and decodes the message based on the number of particles detected
during the symbol interval. In this channel, the transmitter may be unable to
control precisely the probability of particle release, and the receiver may not
detect all the particles that arrive. We model this channel using a
generalization of the binomial channel and show that the capacity-achieving
input distribution for this channel always has mass points at probabilities of
particle release of zero and one. To find the capacity-achieving input
distributions, we develop an efficient algorithm we call dynamic assignment
Blahut-Arimoto (DAB). For diffusive particle transport, we also derive the
conditions under which the input with two mass points is capacity-achieving.Comment: arXiv admin note: text overlap with arXiv:1705.0804