text: abstract—in this work, spatial diversity techniques in the area
  of multiple-input multiple-output (mimo) diffusion-based molecular communications (dbmc) are investigated. for transmitterside spatial coding, alamouti-type coding and repetition mimo
  coding are proposed and analyzed. at the receiver-side, selection
  diversity, equal-gain combining, and maximum-ratio combining
  are studied as combining strategies. throughout the numerical
  analysis, a symmetrical 2×2 mimo-dbmc system is assumed.
  furthermore, a trained artificial neural network is utilized to
  acquire the channel impulse responses. the numerical analysis
  demonstrates that it is possible to achieve a diversity gain in
  molecular communications. in addition, it is shown that for
  mimo-dbmc systems repetition mimo coding is superior to
  alamouti-type coding.
  index terms—molecular communication via diffusion,
  multiple-input multiple-output, spatial diversity, channel
  modeling, artificial neural network.