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This paper proposes two differential detection techniques for signal detection in mobile molecular communication (MMC) for targeted drug delivery (TDD) application. In MMC, a nano-transmitter and a nano-receiver are considered to be in Brownian motion in an extracellular fluid medium. Transmitter uses calcium molecules to communicate with the recei...
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... an MC system, nanomachines are the basic elements whose size can vary from nanometers to few micrometers [9]. These nanomachines can carry the drugs, which provide therapeutic actions in the human body during sickness. Drug carrying nanomachines used in TDD are shown in Fig. 1. These drugs must act on cells since the sickness is due to the disorder in cells. To increase the effectiveness of a therapeutic drug, it has to reach the target cell in the human body. In conventional drug delivery [10], such as oral ingestion and intravascular injection, the drug particles are distributed over the entire ...
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... 5). The differential detector calculates the difference between peaks of consecutive bits in a symbol shown in braces (0, 1), (2, 3), (4, 5)... (2L − 2, 2L − 1). If we denote maximum value of N Y total (i, k) by max(i, k) then detection rule of this detector is given by: ...
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... 5). The differential detector calculates the difference between peaks of consecutive bits in a symbol shown in braces (0, 1), (2, 3), (4, 5)... (2L − 2, 2L − 1). If we denote maximum value of N Y total (i, k) by max(i, k) then detection rule of this detector is given by: ...
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... can be observed that SSD performs better at larger bit durations because ISI reduces with an increase in bit duration. SBD and CDD perform better for small values of bit duration because they utilize ISI for detection of Bit-0 and their performance degrades with an increase in bit duration because the ISI reduces with an increase in bit duration. Fig. 10 shows the BER performance of all the detectors with SNR. The SNR has been defined in (25). As the SNR increases, BER for all detectors except SSD shows a decreasing trend. SSD does not exhibit a significant decrease in the BER. This is because an increase in SNR increases the amount of ISI also. For SBD, CDD, and MCD the BER decreases ...
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... can be observed from Fig. 4 that ISI decreases with time. As an example, during 0.5s -0.6s, ISI(i, t 2 ) < ISI(i, t 1 ). So, (40) gives a negative concentration difference for Bit-0. CDD eliminates the ISI if Bit-1 is received and utilizes the ISI signal to detect Bit-0. Thus, ISI is not detrimental in CDD. Further the residual ISI (plotted in Fig. 11) power is given by: Having this residual ISI power, MCD can provide accurate detection. As evident in Fig. 5 that difference between consecutive peaks (Peak 1 -Peak 2) in a symbol is positive if Bit-1 is received and the difference between consecutive peaks (Peak 5 -Peak 6) in a symbol is negative if Bit-0 is received. So, accurate ...
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... of concentration difference for static MC is studied and no coding was used. So, if consecutive bits [1 1] or [0 0] are received their difference is zero. Hence, coding the Bit-1 by symbol [1 0] and Bit-0 by symbol [0 1] is necessary to differentiate between Bit-1 and Bit-0. ISI power of the difference signal in MCD is calculated and plotted in Fig. 11 in a similar manner as CDD. The residual ISI power increases with an increase in SNR for the detectors CDD and MCD as shown in Fig. 11. As CDD utilizes the ISI to detect Bit-0 hence some amount of ISI power is desirable in CDD. For MCD, the ISI is detrimental. Despite of ISI, MCD gives a better BER performance at 70 dB and 80 dB SNR ...
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... difference is zero. Hence, coding the Bit-1 by symbol [1 0] and Bit-0 by symbol [0 1] is necessary to differentiate between Bit-1 and Bit-0. ISI power of the difference signal in MCD is calculated and plotted in Fig. 11 in a similar manner as CDD. The residual ISI power increases with an increase in SNR for the detectors CDD and MCD as shown in Fig. 11. As CDD utilizes the ISI to detect Bit-0 hence some amount of ISI power is desirable in CDD. For MCD, the ISI is detrimental. Despite of ISI, MCD gives a better BER performance at 70 dB and 80 dB SNR ...
Citations
... CDD has been a focus of MC research for more than ten years and early progress in applying MC in the context of CDD has been summarized in several survey papers [2], [3]. Most of the recent works on CDD in MC focus on the development of communication theoretical models to aid the design of efficient drug delivery systems [4], [5]. Besides, there are some works that consider the physics-based modeling of specific MC system components such as the Tx [6], [7]. ...
... First, we exploit data from experiments in which the CBD molecules are not embedded into PMPs, but released from a propylene glycol solution in the BNC fleece [13] to verify the proposed channel model (5) in isolation. In the considered scenario, the CBD molecules are released instantaneously in the BNC fleece, hence, the measured CBD concentration at the Rx corresponds to the channel impulse response in (5). ...
... First, we exploit data from experiments in which the CBD molecules are not embedded into PMPs, but released from a propylene glycol solution in the BNC fleece [13] to verify the proposed channel model (5) in isolation. In the considered scenario, the CBD molecules are released instantaneously in the BNC fleece, hence, the measured CBD concentration at the Rx corresponds to the channel impulse response in (5). Fig. 2 shows h(t) for D o = 7.3 · 10 −2 mm 2 h −1 along with the experimental data and we observe that the agreement is excellent (MSE = 1.6 · 10 −3 ). ...
Controlled drug delivery (CDD), the controlled release and delivery of therapeutic drugs inside the human body, is a promising approach to increase the efficacy of drug administration and reduce harmful side effects to the body. CDD has been a major research focus in the field of molecular communications (MC) with the goal to aid the design and optimization of CDD systems with communication theoretical analysis. However, the existing studies of CDD under the MC framework are purely theoretical, and the potential of MC for the development of practical CDD applications remains yet to be shown. This paper presents a step towards filling this research gap. Specifically, we present a novel MC-based model for a specific CDD system in which drugs are embedded into microparticles and released gradually towards the target site. It is demonstrated that the proposed model is able to faithfully reproduce experimental data. Furthermore, statistical analysis is conducted to explore the impact of the microparticle size on the drug release. The presented results reveal the sensitivity of the drug release to changes in the microparticle size. In this way, the proposed model can be used for the design of future microparticle-based CDD systems.
... These theoretical results provide the basis for optimizing design parameters for specific mobile molecular communication schemes, including the design of an optimized threshold [8], and evaluating the system performance in terms of the bit error rate [9] and achievable rate [10]. Also, transmission with a differential encoding [11] or by using different types of molecules [12] has been investigated and reception has been proposed exploiting multiple measurements over time [13] or using adaptive signal detection techniques [14]. These solutions for point-to-point connections facilitate cooperation among mobile nanomachines. ...
Nanomachines are envisioned for a variety of applications in the industry and health sectors operating as sensors and actuators. Considering their potential mobility, it is relevant to study the capability of nanomachines to cooperate in molecular communication scenarios. To this end, we provide new insights into the leader-follower dynamics when a mobile leader node moves randomly in three-dimensional space and emits molecules into a diffusive environment to send information about its position to a follower node. In this paper, we investigate the random distance between the two nodes due to decision errors at the follower and analyze an upper bound for the average distance as a function of time. Simulations are provided to validate our analytical results. Moreover, by comparing to the benchmark scenario of uncoordinated movement of leader and follower, we investigate for which parameters the follower can reliably follow the leader.
... These antennas are significantly smaller than typical antennas; they are made of graphene and can operate in the Terahertz frequency spectrum (Jornet & Akyildiz, 2014). The researchers are also investigating nanoscale transceiver design for IoNT domain that operates at higher frequencies (Shrivastava et al., 2020;Nafari & Jornet, 2017). ...
Over the last decade, the Internet of Things (IoT) domain has grown dramatically, from ultra-low-power hardware design to cloud-based solutions, and now, with the rise of 5G technology, a new horizon for edge computing on IoT devices will be introduced. A wide range of communication technologies has steadily evolved in recent years, representing a diverse range of domain areas and communication specifications. Because of the heterogeneity of technology and interconnectivity, the true realisation of the IoT ecosystem is currently hampered by multiple dynamic integration challenges. In this context, several emerging IoT domains necessitate a complete re-modeling, design, and standardisation from the ground up in order to achieve seamless IoT ecosystem integration. The Internet of Nano-Things (IoNT), Internet of Space-Things (IoST), Internet of Underwater-Things (IoUT) and Social Internet of Things (SIoT) are investigated in this paper with a broad future scope based on their integration and ability to source other IoT domains by highlighting their application domains, state-of-the-art research, and open challenges. To the best of our knowledge, there is little or no information on the current state of these ecosystems, which is the motivating factor behind this article. Finally, the paper summarises the integration of these ecosystems with current IoT domains and suggests future directions for overcoming the challenges.
... In [146], two transmission techniques based on CSK and Manchester coding were presented, where bit-1 and bit-0 were represented as symbol [1 0] and [0 1], respectively. Moreover, at the receiver, a concentration differencebased detection was proposed which used the maximum concentration difference within a bit-interval for detection of the transmitted bit using CSK. ...
... Using (15), the iltered signal in jth bit interval can be written as ϕ j ϕ j ϕ j = [ϕ 0 , ϕ 1 , · · · , ϕ P −1 ]. Based on this iltered signal, the slope vector s j s j s j and concentration difference [146] ...
... If channel model is not known then the adaptive threshold-based detection techniques used in [118] and [136] will not yield good performance because (6) can not be used for distance estimation. Therefore, to deal with unknown channel model, non-coherent detection techniques proposed in [145], [146], [119] can be considered. In [146], amplitude difference was used as the decision metric, whereas energy difference was used as the decision metric in [145]. ...
Recent studies have shown that designing communication systems at nanoscale and microscale for the Internet of Bio-Nano Things (IoBNT) applications is possible using Molecular Communication (MC), where two or multiple nodes communicate with each other by transmitting chemical molecules. The basic steps involved in MC are the transmission of molecules, propagation of molecules in the medium, and reception of the molecules at the receiver. Various transmission schemes, channel models, and detection techniques have been proposed for MC in recent years. This paper, therefore, presents an exhaustive review of the existing literature on detection techniques along with their transmission schemes under various MC setups. More specifically, for each setup, this survey includes the transmission and detection techniques under four different environments to support various IoBNT applications: (i) static transmitter and receiver in a pure-diffusive channel, (ii) static transmitter and receiver in a flow-induced diffusive channel, (iii) mobile transmitter and receiver in a pure-diffusive channel, (iv) mobile transmitter and receiver in a flow-induced diffusive channel. Also, performances and complexities of various detection schemes have been compared. Further, several challenges in detection and their possible solutions have been discussed under both static and mobile scenarios. Furthermore, some experimental works in MC are presented to show realistic transmission and detection procedures available in practice. Finally, future research directions and challenges in the practical design of the transmitter and receiver are described to realize MC for IoBNT health applications.
... II. PROPOSED NEURAL NETWORK BASED MMC SYSTEM Fig. 1(a) shows Tx and Rx in Brownian motion [11] in Extracellular Fluid (ECF). Radius of the Tx and the Rx are a t and a t respectively. ...
... Thus, the filtered signal in jth bit interval is φ j = [φ 0 , φ 1 , ..., φ P −1 ]. Slope vector s j = [s 0 , s 1 , ..., s P −2 ] where, s i = φ i+1 − φ i and concentration difference [11] vector ...
... Each BER value is obtained on a test data of 10000 bits. The signal-to-noise ratio (SNR) [11] is defined as: ...
This paper proposes a neural network (NN) detector for mobile molecular communication (MMC). The NN uses Broyden-Fletcher-Goldfarb-Shanno (BFGS), and Levenberg-Marquardt (LM) algorithms for optimization. In the proposed work, the received signal is filtered and three different techniques for supervised training and detection are used. The three different techniques are (a) the filtered signal, (b) slope values of the filtered signal, and (c) concentration difference values of the filtered signal within a bit interval. The trained NN is used for detecting the unknown bits for time-varying parameters such as the distance between transmitter (Tx) and receiver (Rx), noise, and the number of released molecules by the Tx. Bit error rate (BER) with the signal-to-noise ratio (SNR) is shown for different parameters such as coherence time of the channel, diffusion coefficient of the Tx, and the initial distance between the Tx and the Rx. Simulation results show that the BFGS algorithm trains the NN faster compared to the LM algorithm and the trained NN can perform well in a time-varying MMC environment.
In this work, a particle-based simulation of two differential detectors for a reactive receiver in mobile molecular communication (MMC) is presented. The received signal is filtered and used for detection. On-off keying (OOK) is used as the modulation in both schemes. The detector in first scheme finds two-time instants in the filtered signal to maximize absolute concentration difference within the same bit duration. Then the concentration difference is used as the decision metric. The second scheme uses Manchester coding at the transmitter where the bit-0 and bit-1 are represented as the symbol [0 1] and symbol [1 0] respectively. The difference between the peak values of filtered signals in successive bit durations is used as the decision metric. Correlation between the analytical signal and particle-based signal is also found. Further, the bit error rate (BER) of the proposed detection schemes is calculated using the analytical signal and validated using the particle-based signal. Simulation results show a good agreement between the BER obtained using the analytical signal and the particle-based signal.
