Analyzing Large-Scale Multiuser Molecular Communication via 3D Stochastic Geometry

arXiv admin note: text overlap with arXiv:1605.08311arXiv admin note: text overlap with arXiv:1605.08311Information delivery using chemical molecules is an integral part of biology at multiple distance scales and has attracted recent interest in bioengineering and communication theory. Potential applications include cooperative networks with a large number of simple devices that could be randomly located (e.g., due to mobility). This paper presents the first tractable analytical model for the collective signal strength due to randomly-placed transmitters in a three-dimensional (3D) large-scale molecular communication system, either with or without degradation in the propagation environment. Transmitter locations in an unbounded and homogeneous fluid are modelled as a homogeneous Poisson point process. By applying stochastic geometry, analytical expressions are derived for the expected number of molecules absorbed by a fully-absorbing receiver or observed by a passive receiver. The bit error probability is derived under ON/OFF keying and either a constant or adaptive decision threshold. Results reveal that the combined signal strength increases proportionately with the transmitter density, and the minimum bit error probability can be improved by introducing molecule degradation. Furthermore, the analysis of the system can be generalized to other receiver designs and other performance characteristics in large-scale molecular communication systems

MmWave MU-MIMO for Aerial Networks

Millimeter wave offers high bandwidth for air-to-air (A2A) communication. In this paper, we evaluate the rate performance of a multiuser MIMO (MU-MIMO) configuration where several aircraft communicate with a central hub. We consider a hybrid subarray architecture, single path channels, and realistic atmospheric attenuation effects. We propose a mathematical framework for the analysis of millimeter wave (mmWave) MU-MIMO networks. Via Monte Carlo simulation, we demonstrate that mmWave is a promising technology for delivering gigabit connectivity in next-generation aerial networks.Comment: 5 pages, 4 figures, accepted at ISWCS Special Session 7: Vehicle-to-Everything (V2X) Communications. Small correction to equation (9) that I noticed after publication. Code available at: https://github.com/travisCuvelier/mmWaveAerialNetwork

Channel Modeling for Diffusive Molecular Communication - A Tutorial Review

Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications such as sensing of target substances in biotechnology, smart drug delivery in medicine, and monitoring of oil pipelines or chemical reactors in industrial settings. As for any other kind of communication, simple yet sufficiently accurate channel models are needed for the design, analysis, and efficient operation of MC systems. In this paper, we provide a tutorial review on mathematical channel modeling for diffusive MC systems. The considered end-to-end MC channel models incorporate the effects of the release mechanism, the MC environment, and the reception mechanism on the observed information molecules. Thereby, the various existing models for the different components of an MC system are presented under a common framework and the underlying biological, chemical, and physical phenomena are discussed. Deterministic models characterizing the expected number of molecules observed at the receiver and statistical models characterizing the actual number of observed molecules are developed. In addition, we provide channel models for time-varying MC systems with moving transmitters and receivers, which are relevant for advanced applications such as smart drug delivery with mobile nanomachines. For complex scenarios, where simple MC channel models cannot be obtained from first principles, we investigate simulation-driven and experimentally-driven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems.Comment: 40 pages; 23 figures, 2 tables; this paper is submitted to the Proceedings of IEE