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Low-Complexity Adaptive Signal Detection for Mobile Molecular Communication.
IEEE Transactions on NanoBioscience ( IF 3.7 ) Pub Date : 2020-01-09 , DOI: 10.1109/tnb.2020.2965168
Xiaodong Mu , Hao Yan , Bin Li , Manhua Liu , Ruifeng Zheng , Yan Li , Lin Lin

Currently, most of the researches in molecular communication (MC) domain focus on the static MC scenarios. However, some envisioned important MC applications require mobile MC system. The investigation on mobile MC, especially the signal detection of mobile MC is limited. This work considers the problem of signal detection for mobile MC scenarios where the receiver nano-machine performs random movement. Due to the random movement of the receiver, the channel impulse response (CIR) changes over time which makes the received signal stochastic and complicated. This further complicates the signal detection in mobile MC and leads to that the state-of-the-art signal detection schemes for static MC scenarios fail for the mobile MC scenarios. To solve this issue, an adaptive detection scheme has been proposed by our group previously, based on dynamic estimation of the stochastically varying distance between the transmitter and receiver and the reconstruction of CIR in each interval. However, its computational complexity is high. Limited capability of current nanomachines desire low-complexity detection algorithm. In this work, we further propose an adaptive detection scheme for mobile MC with a low computational complexity by utilizing the local convex property of the CIR. With on-off keying (OOK) modulation, the signal of symbol "1" presents local convex property while that of symbol "0" presents local concave property. The convexity extent varies with the stochastic distance. A simple indicator, local maximum convexity is proposed which adapts to the stochastic distance. By comparing the adaptive indicator with an adaptive threshold within each symbol interval, the signal is detected without the need to estimate the stochastically changing distance or to reconstruct the CIR. Therefore, the computational load is effectively reduced. Numerical simulations are performed to evaluate the proposed scheme. The results show that the proposed scheme achieves good detection accuracy with low computational complexity and it could be a promising detection scheme for mobile MC scenarios.

中文翻译:

用于移动分子通信的低复杂度自适应信号检测。

当前,在分子通信(MC)领域的大多数研究都集中在静态MC场景上。但是,一些预想的重要MC应用程序需要移动MC系统。对移动MC的研究尤其是对移动MC信号检测的研究是有限的。这项工作考虑了接收器纳米机执行随机运动的移动MC场景的信号检测问题。由于接收器的随机运动,信道脉冲响应(CIR)随时间变化,这使接收信号变得随机且复杂。这进一步使移动MC场景中的信号检测复杂化,并导致针对静态MC场景的最新信号检测方案在移动MC场景中失效。为了解决这个问题,我们小组先前提出了一种自适应检测方案,基于对发射机和接收机之间随机变化距离的动态估计以及每个间隔中CIR的重建。但是,其计算复杂度很高。当前的纳米机器能力有限,需要低复杂度的检测算法。在这项工作中,我们进一步利用CIR的局部凸性为移动MC提出了一种自适应检测方案,具有较低的计算复杂度。使用开关键控(OOK)调制时,符号“ 1”的信号呈现局部凸形,而符号“ 0”的信号呈现局部凹形。凸度随随机距离而变化。提出了一种简单的指标,即局部最大凸度,它适应于随机距离。通过将自适应指示符与每个符号间隔内的自适应阈值进行比较,无需估计随机变化的距离或重建CIR即可检测到信号。因此,有效地减少了计算负荷。进行数值模拟以评估所提出的方案。结果表明,该方案具有良好的检测精度和较低的计算复杂度,对于移动MC场景可能是一种很有前途的检测方案。
更新日期:2020-04-16
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