Molecular communication (MC) is envisioned to realize nanotheranostics as an emerging diagnostic tool to improve existing treatment modalities. Phase separation (PS) is a complex time-dependent process responsible for discrimination of two independent phases from a single homogeneous mixture. Recently, PS was revealed to be the fundamental mechanism behind formation and organization of the living cells. Inspired by PS mechanisms in nature, we establish a novel modulation scheme for MC which encodes the information in the dispersion of molecules diffusing in the environment. Hence, the diffusion distribution can be considered as carriers of molecules. To evaluate the performance of this communication scheme, a dual-carrier diffusion-division modulation (DDM) is adopted where each carrier can be effectively modeled by superposition of multiple independent phases. We derive the theoretical bit error rate (BER) of the proposed DDM scheme which is validated by particle-based simulation (PBS). Furthermore, performance of the multi-carrier DDM scheme is compared to the well-known on-off keying (OOK) modulation scheme (as the most relevant benchmark) and pulse-position modulation (PPM) scheme. It is shown that performance of the DDM-based MC system can be boosted by increasing the transmission power and/or using multiple carriers. Interestingly, the proposed DDM is a covert modulation scheme since any other receiver cannot decode the transmitted signal by just counting the number of received molecules unless having the shared key. Moreover, the DDM scheme requires a receiver that exploits the displacement distribution of the molecules inside the receiver to infer about the tranmitted bit. We strongly believe that this concept will introduce novel types of communication schemes more compatible with biological microenvironments. Also, this work establishes the foundation for more complex orthogonal multi-carrier DDM schemes which can potentially unlock novel cellular sensing mechanisms in biology.

Channel modeling is a challenging vital step towards the development of diffusion-based molecular communication networks (DMCNs). Analytical approaches for diffusion channel modeling are limited to simple and specific geometries and boundary conditions. Also, simulation- and experiment-driven methods are very time-consuming and computationally complex. In this paper, the channel model for DMCN employing the fundamental concentration Green's function (CGF) is characterized. A general homogeneous boundary condition framework is considered that includes any linear reaction systems at the boundaries in the environment. To obtain the CGF for a general DMCN including multiple transmitters, receivers, and other objects with arbitrary geometries and boundary conditions, a semi-analytical method (SAM) is proposed. The CGF linear integral equation (CLIE) is analytically derived. By employing the numerical method of moments, the problem of CGF derivation from CLIE is transformed into an inverse matrix problem. Moreover, a sequential SAM is proposed that converts the inversion problem of a large matrix into multiple smaller matrices reducing the computational complexity. Particle-based simulator confirms the results obtained from the proposed SAM. The convergence and run time for the proposed method are examined. Further, the error probability of a simple diffusion-based molecular communication system is analyzed and examined using the proposed method.

Diffusion-based molecular communication (DMC) is one of the most promising approaches for realizing nano-scale communications for healthcare applications. The DMC systems in in-vivo environments may encounter biological entities that release molecules identical to the molecules used for signaling as part of their functionality. Such entities in the environment act as external noise sources from the DMC system's perspective. In this paper, the release of molecules by external bio-inspired noise sources is particularly modeled as a compound Poisson process. The impact of compound Poisson noise sources (CPNSs) on the performance of a point-to-point DMC system is investigated. To this end, the noise from the CPNS observed at the receiver is characterized. Considering a simple on-off keying modulation and formulating symbol-by-symbol maximum likelihood (ML) detector, the performance of the DMC system in the presence of the CPNS is analyzed. For the special case of CPNS in a high-rate regime, the noise received from the CPNS is approximated as a Poisson process whose rate is normally distributed. In this case, it is proved that a simple single-threshold detector is an optimal ML detector. Our results reveal that in general, adopting the conventional simple homogeneous Poisson noise model may lead to overly optimistic performance predictions, if a CPNS is present.