研究目的
To improve the data rate in diffusion-based molecular communication by proposing a novel multiple-input multiple-output (MIMO) design that utilizes multiple molecular emitters at the transmitter and multiple molecular detectors at the receiver, and to develop detection algorithms specific to molecular MIMO systems.
研究成果
The proposed MIMO system for molecular communication significantly improves data rates by addressing interlink interference (ILI) and intersymbol interference (ISI). The developed detection algorithms, especially adaptive thresholding and practical zero forcing, show promising performance in terms of bit error rate (BER). The world's first molecular MIMO testbed demonstrates the feasibility of the proposed concept, achieving transmission rates 1.7 times higher than molecular SISO systems.
研究不足
The study assumes that the receiver has incomplete information regarding the system and the channel state, preferring low complexity symbol detection methods. The practicality of acquiring instantaneous channel state information for the Genie-aided zero forcing algorithm is not feasible in molecular communications.
1:Experimental Design and Method Selection:
The study proposes a MIMO system for molecular communication, utilizing particle-based simulators to model the channel's impulse response and to determine interlink interference (ILI) and intersymbol interference (ISI). Four detection algorithms are proposed and evaluated.
2:Sample Selection and Data Sources:
The study uses simulations to generate channel statistics, with 5000 molecules per antenna emitted and 500 simulations carried out for each parameter set.
3:List of Experimental Equipment and Materials:
The study involves a tabletop molecular MIMO testbed with chemical sensors and spray nozzles for emission and detection of molecules.
4:Experimental Procedures and Operational Workflow:
The transmitter releases molecules into the medium, which propagate via diffusion. The receiver counts the number of received molecules during a symbol slot. The proposed detection algorithms are applied to demodulate the signal.
5:Data Analysis Methods:
The study uses nonlinear curve fitting on simulation data to model the channel's impulse response and analyzes system performance in terms of bit error rate (BER) and signal-to-interference ratio (SIR).
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