In multiple access molecular diffusive communications, many nano-machines exchange information and fuse data through a common Diffusive Molecular Communication (DMC) channel. Hence, there is Multiple-Access Interference (MAI), which should be sufficiently mitigated so as to achieve reliable communications. In this paper, we propose a novel low-complexity detection scheme, namely Equal-Gain Combining with Interference Mitigation (EGC-IM), for signal detection in the Molecular Type Hopping assisted Molecular Shift Keying (MTH-MoSK) DMC systems. By removing a number of entries from each row of the detection matrix formed during detection, the EGC-IM scheme shows its potential to significantly mitigate MAI and hence, outperform the conventional EGC scheme. Furthermore, the EGC-IM scheme has lower complexity than the conventional EGC scheme and therefore, it is beneficial for practical implementation.
Robust Neural Network based Multiuser Detector in MC-CDMA for Multiple Access Interference Mitigation
