IEEE Trans Nanobioscience. 2021 Oct;20(4):416-425. doi: 10.1109/TNB.2021.3077297. Epub 2021 Sep 30.
Molecular communication, as an emerging research direction, has emerged in the field of communication, which usually combined with nanotechnology and bio-related knowledge. In the direction of communication channel research, the most widespread model for a molecular communication channel is the diffusion-based channel, where the information-carrying molecules propagate randomly in the medium based on Brownian motion. Multi-input multi-output (MIMO) technology is often used to improve communication quality in the traditional communication field. Compared with the SISO model, which only has inter-symbol interference (ISI) as the interference source, the interference in MIMO communication model includes ISI as well as inter-link interference (ILI), which emerges when receiver receive other transmitters' molecules. In this paper, MIMO communication models are built, based on diffusion channel, CSK, probabilistic theory, considered with ISI and ILI, to establish the calculation formula of related bit error rate, And the influence of relevant parameters in the model on bit error rate is studied. Then, SISO and SIMO models will be built to compare with MIMO models. Last, self-adaptive dual threshold algorithm is proposed to reduce BER of the 2×2 MIMO system. Simulation results show that the proposed algorithm has better performance on reducing BER than other approaches.
分子通信作为一个新兴的研究方向,出现在通信领域,通常结合纳米技术和生物相关知识。在通信信道研究方向中,最广泛的分子通信信道模型是基于扩散的信道,其中携带信息的分子基于布朗运动在介质中随机传播。多输入多输出(MIMO)技术常用于提高传统通信领域的通信质量。与只有符号间干扰(ISI)作为干扰源的 SISO 模型相比,MIMO 通信模型中的干扰包括 ISI 以及当接收器接收其他发射器的分子时出现的链路间干扰(ILI)。在本文中,基于扩散信道、CSK、概率理论,考虑 ISI 和 ILI,建立了相关误码率的计算公式,并研究了模型中相关参数对误码率的影响。然后,建立 SISO 和 SIMO 模型来与 MIMO 模型进行比较。最后,提出了自适应双门限算法来降低 2×2 MIMO 系统的误码率。仿真结果表明,与其他方法相比,所提出的算法在降低误码率方面具有更好的性能。