Capacity of molecular channels with imperfect particle-intensity modulation and detection

Abstract

Abstract-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.

Neural Network Detection of Data Sequences in Communication Systems

“…In our model it is assumed that the transmitter uses on-offkeying (OOK) modulation, where the transmission symbol set is S = {0, 1}, and the transmitter either transmits a pulse with a fixed intensity to represent the 1-bit or no pulse to represent the 0-bit. Note that OOK modulation has been considered in many previous works on optical and molecular communication and has been shown to be the optimal input distribution for a large class of Poisson channels [54]- [56]. Later in Section V-D, we extend the results to larger symbol sets by considering the general m level pulse amplitude modulation (m-PAM), where information is encoded in m amplitudes of the pulse transmissions.…”

Efficient Binomial Channel Capacity Computation with an Application to Molecular Communication

“…In [5] a channel is considered in which imperfect particleintensity modulation and detection is used for communication between a biological transmitter and receiver (e.g. cells).…”

“…As n increases, these two mass points move away from 0.5, and when they are far enough away, a new mass point is born at 0.5. The binomial channel has been considered recently as a model for molecular communication [5], [6], where typical values of n will be on the order of a thousand. In [7], values of the capacity of the binomial channel were obtained using the ellipsoid method [8].…”

“…However, the ellipsoid method is too slow for practical application when the value of n is large. This paper presents a more efficient approach to computing the capacity of the binomial channel and applies it to the molecular communication channel model of [5].…”

“…Section IV introduces a new method that applies Blahut-Arimoto to a finite support that is dynamically adjusted using Csiszár's Min-Max Capacity theorem. Section V applies this method to the molecular channel model of [5], and Section VI concludes the paper.…”