Joint Parameter Optimization for Perpetual Nanonetworks and Maximum Network Capacity

2019

IET signal process.

In this study, the authors propose a novel component‐wise variable step‐size diffusion least mean square (CWVSS‐DLMS) algorithm for distributed estimation. Different from the traditional variable step‐size DLMS (VSS‐DLMS) algorithms in which the updating of all components in the weight vector are the same, the step sizes vary from each other on all components at each iteration in the CWVSS‐DLMS algorithm. After deriving the CWVSS‐DLMS algorithm, they perform theoretical analysis in terms of mean stability and mean‐square behaviour. They have also compared the performance of the CWVSS‐DLMS algorithm with several other DLMS algorithms through numerical simulations in both stationary and non‐stationary environments. Simulation results show that the performance of the CWVSS‐DLMS algorithm is more outstanding than the fixed step‐size DLMS algorithm, several non‐component‐wise VSS‐DLMS algorithms and existing component‐wise VSS‐DLMS algorithms in balancing high convergence rates and low steady‐state misadjustment. Moreover, they have investigated the performance of the CWVSS‐DLMS algorithm for estimating sparse parameter in a distributed way. Simulation results show that the CWVSS‐DLMS algorithm can yield satisfying performance in sparsely distributed estimation regardless of the degree of sparsity in the real parameter.

Section: Performance Analysismentioning

confidence: 55%

Component‐wise variable step‐size diffusion least mean square algorithm for distributed estimation

Huang

2019

IET signal process.

“…where y = p or y = d stands for the calculation of one probing packet and one data packet, respectively. W y refers to the coding weight, which is adaptive to different coding algorithms or parameter optimizations [26].…”

Section: Energy Consumption In Pulse-based Nanonetwork Communicationmentioning

confidence: 99%

“…In Fig. 8, the energy consumption of E ECP in (26) and other error control techniques are shown as a function of the data packet size N d bits . As shown in the figure, the trend for all error control strategies are very similar to that of the delay shown in Fig.…”

Section: E Energy Consumptionmentioning

confidence: 99%

ECP: A Probing-Based Error Control Strategy for THz-Based Nanonetworks With Energy Harvesting

Han

2019

IEEE Access

Self Cite

Nanonetworks are comprised of the nano-sized communication devices that can perform simple tasks, such as computation, data storage, and actuation at the nanoscale. However, the error-prone wireless links as a result of severe path loss in the terahertz band (0.1-10.0 THz) and very limited energy storage capacity in nanodevices are challenging the communication in the nanonetworks. Therefore, efficient and effective error control protocols are necessary for the nanonetworks in the THz band. In this paper, first, a novel error control strategy with probing (ECP) mechanism for the nanonetworks powered by energy harvesting is proposed. In particular, each data packet will be transmitted only after the successful communication of one probing packet. Second, the energy state model by considering the energy harvestingconsumption process is presented based on the extended Markov chain approach. Moreover, a probabilistic analysis of the overall network traffic and multiuser interference is used by the proposed energy state model to capture the dynamic network behavior. Third, the impact of the different packets energy of consumption on a state transition and the state probability distribution of nanonodes based on the above-mentioned model is comprehensively investigated. Finally, the performance of the ECP mechanism and the other four different error control strategies, namely, Automatic Repeat reQuest (ARQ), Forward Error Correction (FEC), Error Prevention Codes (EPC) and a hybrid EPC, in terms of the end-to-end successful packet delivery probability, end-to-end packet delay, achievable throughput, and energy consumption are investigated and evaluated. The results show that the proposed ECP mechanism can maximize the end-to-end successful data packet delivery probability than the other four error control schemes, increase the achievable throughput compared with ARQ and EPC schemes, and outperform the ARQ and FEC schemes in terms of energy utilization. INDEX TERMS Nanonetworks, error control, energy harvesting, probing mechanism, Markov chain. The associate editor coordinating the review of this manuscript and approving it for publication was Petros Nicopolitidis. many unprecedented applications. For example, there are many direct applications of nanotechnology in the biomedical field (e.g., drug delivery systems and cancer detection), in the environmental field (e.g., plants monitoring systems and biodegradation) and in the military field (e.g., biological, chemical defenses and nano-functionalized equipments) [1], [3]. To realize these applications and guarantee their performance, the energy consumption, data processing and communication problems in the nanodevices are required to be considered comprehensively. Recently, THz band has been recommended as the frequency band of communication for nanodevices due to the 25616 2169-3536 2019 IEEE. Translations and content mining are permitted for academic research only.

“…come true [10,11,12]. In the past years, some attempts have been made for nano-networks in the design of nano-components [10,13,14,15], physical layer models [16,17,18], communication protocols [19,20,21,22] and other applications [5,6,23].…”

Section: Introductionmentioning

confidence: 99%

Slot Self-Allocation Based MAC Protocol for Energy Harvesting Nano-Networks

Wang

2019

Sensors

Self Cite

Nano-networks are composed of interconnected nano-nodes and can enable unprecedented applications in various fields. Due to the peculiarities of nano-networks, such as high density, extremely limited energy and computational resources, traditional carrier-sensing based Media Access Control (MAC) protocols are not suitable for nano-networks. In this paper, a Slot Self-Allocation based MAC protocol (SSA-MAC) is proposed for energy harvesting nano-networks. Two transmission schemes for centralized and distributed nano-networks are designed, respectively. In centralized nano-networks, nano-nodes can only send packets to the nano-controller in their Self-Allocation Slots (SASs), while, in distributed nano-networks, nano-nodes can only receive packets from surrounding nano-nodes in their SASs. Extensive simulations were conducted to compare the proposed SSA-MAC with PHysical LAyer aware MAC (PHLAME), Receiver-Initiated Harvesting-aware MAC (RIH-MAC) and Energy Efficient Wireless NanoSensor Network MAC (EEWNSN). From the results, it can be concluded that the proposed SSA-MAC achieves better performance and can reduce the collision probability, while improving the energy efficiency of nano-networks.