text: In this paper, we design a drug release mechanism for dynamic time division multiple access (TDMA)-based molecular communication via diffusion (MCvD). In the proposed scheme, the communication frame is divided into several time slots over each of which a transmitter nanomachine is scheduled to convey its information by releasing the molecules into the medium. To optimize the number of released molecules and the time duration of each time slot (symbol duration), we formulate a multi-objective optimization problem whose objective functions are the bit error rate (BER) of each transmitter nanomachine. Based on the number of released molecules and symbol durations, we consider four cases, namely: "static-time static-number of molecules" (STSN), "static-time dynamic-number of molecules" (STDN), "dynamic-time static-number of molecules" (DTSN), and "dynamic-time dynamic-number of molecules" (DTDN). We consider three types of medium in which the molecules are propagated, namely: "mild diffusive environment" (MDE), "moderate diffusive environment" (MODE), and "severe diffusive environment" (SDE). For the channel model, we consider a 3-dimensional (3D) diffusive environment, such as blood, with drift in three directions. Simulation results show that the STSN approach is the least complex one with BER around @math , but, the DTDN is the most complex scenario with the BER around @math .
  @cite_24: Molecular communication is a new nano-scale communication paradigm that enables nanomachines to communicate with each other by emitting molecules to their surrounding environment. Nanonetworks are also envisioned to be composed of a number of nanomachines with molecular communication capability that are deployed in an environment to share specific molecular information such as odor, flavour, light, or any chemical state. In this paper, using the principles of natural ligand-receptor binding mechanisms in biology, we first derive a capacity expression for single molecular channel in which a single Transmitter Nanomachine (TN) communicates with a single Receiver Nanomachine (RN). Then, we investigate the capacity of the molecular multiple-access channel in which multiple TNs communicate with a single RN. Numerical results reveal that high molecular communication capacities can be attainable for the single and multiple-access molecular channels.
  @cite_10: Currently, communication between nanomachines is an important topic for the development of novel devices. To implement a nanocommunication system, diffusion-based molecular communication is considered as a promising bio-inspired approach. Various technical issues about molecular communications, including channel capacity, noise and interference, and modulation and coding, have been studied in the literature, while the resource allocation problem among multiple nanomachines has not been well investigated, which is a very important issue since all the nanomachines share the same propagation medium. Considering the limited computation capability of nanomachines and the expensive information exchange cost among them, in this paper, we propose a game-theoretic framework for distributed resource allocation in nanoscale molecular communication systems. We first analyze the inter-symbol and inter-user interference, as well as bit error rate performance, in the molecular communication system. Based on the interference analysis, we formulate the resource allocation problem as a non-cooperative molecule emission control game, where the Nash equilibrium is found and proved to be unique. In order to improve the system efficiency while guaranteeing fairness, we further model the resource allocation problem using a cooperative game based on the Nash bargaining solution, which is proved to be proportionally fair. Simulation results show that the Nash bargaining solution can effectively ensure fairness among multiple nanomachines while achieving comparable social welfare performance with the centralized scheme.
  @cite_23: This paper proposes and evaluates Neuronal TDMA, a TDMA-based signaling protocol framework for molecular communication, which utilizes neurons as a primary component to build in-body sensor-actuator networks (IBSANs). Neuronal TDMA leverages an evolutionary multiobjective optimization algorithm (EMOA) that optimizes the signaling schedule for nanomachines in IBSANs. The proposed EMOA uses a population of solution candidates, each of which represents a particular signaling schedule, and evolves them via several operators such as selection, crossover, mutation and offspring size adjustment. The evolution process is performed to seek Pareto-optimal signaling schedules subject to given constraints. Simulation results verify that the proposed EMOA efficiently obtains quality solutions. It outperforms several conventional EMOAs.
summary: Researchers study the TDMA optimization in neuron-based MC, which employs neurons to communicate and built in-body sensor-actuator networks (IBSANs) @cite_23 . They use an evolutionary multi-objective optimization algorithm to design the TDMA schedule. The resource allocation in MC has already studied for two transmitter nodes in @cite_10 where the authors propose a game-theoretic framework and study Bit Error Rate (BER) of such a system. In addition, the investigation of the channel capacity for multiple-access channels, which employs the principles of natural ligand-receptor is studied in @cite_24 . Furthermore, the researchers have found a high capacity in Single-input Single-output (SISO) and Multi-input Single-output (MISO)-based MC system @cite_24 . The investigation of more than two transmitter nodes in multiple access channel in existing works has not been considered yet. In addition, TDMA in Molecular Communication via Diffusion (MCvD) system has not been studied in the existing works on MC. The optimization of symbol durations and the number of released molecules by each transmitter node is also not considered in the existing works.