Search

Simultaneous wireless information power transfer with power splitting is a new technology for energy harvesting that splits the received signal into two streams with adjustable power levels for information decoding and energy saving. Traditionally, decode and forward (DF) and amplify and forward (AF) schemes are used for energy harvesting in three‐step two‐way relay networks (TWRNs). In this paper, piece‐wise and forward (PF) scheme are applied with power splitting for energy harvesting in TWRNs. In PF, the received signal from each source at relay is compared to an adaptive threshold, if the signal strength is above the threshold, the relay functions similar to DF scheme, otherwise, the relay transmits a particular combination of its received signals from the sources. Next, the outage performance of PF protocol in a three‐step TWRN is studied and optimal lossless energy saving (OLES) method are presented to minimise the outage probability by computing the optimum power splitting ratio. The simulation and analytical results indicate that the outage probability of PF can be significantly improved using OLES technique in comparison with other related relaying schemes. The results show that the outage probability of PF‐OLES is 13, 3, and 5dB$5\nobreakspace \text{dB}$ lower than AF‐OLES, DF‐OLES, and DAPS [1], respectively. [ABSTRACT FROM AUTHOR]

Abstract Molecular Communication via Diffusion (MCvD) is a promising paradigm which enables nano-machines to communicate with each other. However, the reliability of existing communication systems degrades rapidly as the distance between the transmitters and the receivers grows. To solve this issue, relaying schemes must be implemented in practice. In this paper, we study two relaying schemes: In the first case, the relay node decodes the incoming signal symbol and forwards it to the receiver using a different types of molecules. Then, the receiver detects the information bits by only considering the molecules from the relay node. In the second case, the receiver considers both types of molecules sent from the transmitter and the relay node. Closed-form expression for the end-to-end bit error probability of the these two schemes are derived. Also, we obtain optimal relay location for both schemes. Moreover, we study the optimal threshold, concentration, baud-rate and timing offset to mitigate the overall Inter-Symbol Interference(ISI) and obtain maximum throughput in the relay network. [ABSTRACT FROM AUTHOR]

Abstract In diffusion-based molecular communication simple modulation techniques based on the concentration, type, or released time of molecules are commonly used. However, random delay of the diffused molecules in environment can cause some strong inter-symbol interference (ISI) among consecutive symbols. Due to the limited computational capabilities of nano-machines, sophisticated modulation and coding schemes cannot be used to resolve this issue. In this paper, we propose several new, yet simple, ISI-resistant coding schemes for diffusion-based communications over a one-dimensional noiseless channel. These schemes map the information bits into variable length codewords and place time-gaps between the consecutive codewords to mitigate ISI issue. Our analytical and simulation results indicate that the proposed schemes provide superior performances in terms of probability of error and throughput compared to the existing schemes. [ABSTRACT FROM AUTHOR]

Bounds on the capacity of wireless networks often rely on simplifying assumptions and are given in terms of coarse network parameters, such as the number of nodes. While useful due to their simplicity, such bounds can significantly overestimate the achievable capacity in real-world situations, ignoring actual network topology and traffic patterns. The results of this paper improve such analytical results on network capacity in several ways. At the heart of our methodology lies the concept of transmission arenas, which indicates the presence of active transmissions near any given location in the network. This novel space-based approach is well-suited to untangle the interactions of simultaneous transmissions. Avoiding a graph-based model of the network, it opens new avenues of studying capacities. For homogeneous networks, we recover classical bounds. However, our methodology applies to arbitrary networks and can, thus, inform placing and activating of nodes also in the presence of clustering. Our method works with all classical channel models and dimensions. It provides bounds on the transport capacity which involve only high-level knowledge of node locations, such as the length of Euclidean minimum spanning tree. As an additional novelty, we establish bounds on wireless unicast and multicast capacities. [ABSTRACT FROM PUBLISHER]

We study the dynamics of network selection in heterogeneous wireless networks based on client-side control. Clients in such networks selfishly select the best radio access technology (RAT) that maximizes their own throughputs. We study two general classes of throughput models that capture the basic properties of random access (e.g., Wi-Fi) and scheduled access (e.g., WiMAX, LTE, and 3G) networks. Formulating the problem as a non-cooperative game, we study its existence of equilibria, convergence time, efficiency, and practicality. Our results reveal that: 1) single-class RAT selection games converge to Nash equilibria, while an improvement path can be repeated infinitely with a mixture of classes; 2) we provide tight bounds on the convergence time of these games; 3) we analyze the Pareto-efficiency of the Nash equilibria of these games, deriving the conditions under which Nash equilibria are Pareto-optimal, and quantifying the distance of equilibria with respect to the set of Pareto-dominant points when the conditions are not satisfied; and 4) with extensive measurement-driven simulations, we show that RAT selection games converge to Nash equilibria in a small number of steps, and are amenable to practical implementation. We also investigate the impact of noisy throughput estimates, and propose solutions to handle them. [ABSTRACT FROM PUBLISHER]

Communication security of wireless sensor networks is achieved using cryptographic keys assigned to the nodes. Due to resource constraints in such networks, random key pre-distribution schemes are of high interest. Although in most of these schemes no location information is considered, there are scenarios that location information can be obtained by nodes after their deployment. In this paper, we propose a novel probabilistic key pre-distribution scheme, for large-scale wireless sensor networks which utilizes location information in order to improve the performance of random key pre-distribution substantially. In order to apply the location information of the nodes in key distribution process, we partition the network into some regions and use graph coloring techniques to efficiently assign the random keys. The proposed scheme has a superior scalability by supporting larger number of nodes and also increasing the probability of existence of a shared exclusive key among the nearby nodes, i.e., the probability of having an isolated node is significantly reduced in comparison with the existing random key pre-distribution schemes. Our simulation results verify these terms. [ABSTRACT FROM AUTHOR]

Cognitive Radio (CR) is an adaptive, intelligent radio technology that can automatically detects available channels in a wireless spectrum and change transmission parameters to allow more concurrent wireless communications in a given spectrum band at a location. Physical layer attack is a common attack in these networks which can degrade the performance of cognitive radio networks severely. In this attack, the attacker mimics the signals of the Primary Users (PU) to mislead the cognitive users about the existence of the primary users. Two physical layer attack approaches are studied in this paper. First, we have considered the case that the cognitive users are united against the attacker to maximize the network total throughput. Second, we have studied the case that the cognitive users are selfish but have a common attacker. In both cases, we have assumed that the cognitive network employs carrier sense multiple access with collision avoidance (CSMA/CA) to prevent collisions. We use the game theory approach to model the optimization problem and then try to solve it. Some simulations are conducted to evaluate the cognitive network performances. [ABSTRACT FROM AUTHOR]

In this paper, we explore fundamental limitations of the benefit of network coding in multihop wireless networks. We study two well-accepted scenarios in the field: single multicast session and multiple unicast sessions. We assume arbitrary but fixed topology and traffic patterns for the wireless network. We prove that the gain of network coding in terms of throughput and energy saving of a single multicast session is at most a constant factor. Also, we present a lower bound on the average number of transmissions of multiple unicast sessions under any arbitrary network coding. We identify scenarios under which network coding provides no gain at all, in the sense that there exists a simple flow scheme that achieves the same performance. Moreover, we prove that the gain of network coding in terms of the maximum transport capacity is bounded by a constant factor of at most $(\pi)$ in any arbitrary wireless network under all traditional Gaussian channel models. As a corollary, we find that the gain of network coding on the throughput of large homogeneous wireless networks is asymptotically bounded by a constant. Furthermore, we establish theorems which relate a network coding scheme to a simple routing scheme for multiple unicast sessions. The theorems can be used as criteria for evaluating the potential gain of network coding in a given wired or wireless network. Based on these criteria, we find more scenarios where network coding has no gain on throughput or energy saving. [ABSTRACT FROM AUTHOR]

The monitoring of epileptic seizures is mainly done by means of electroencephalogram (EEG) monitoring. Although this method is accurate, it is not comfortable for the patient as the EEG-electrodes have to be attached to the scalp which hampers the patient's movement. This makes long-term home monitoring not feasible. In this paper, the aim is to propose a seizure detection system based on accelerometry for the detection of epileptic seizure. The used sensors are wireless, which can improve quality of life for the patients. In this system, three 2D accelerometer sensors are positioned on the right arm, left arm, and left thigh of an epileptic patient. Datasets from three patients suffering from severe epilepsy are used in this paper for the development of an automatic detection algorithm. This monitoring system is based on Wireless Sensor Networks and can determine the location of the patient when a seizure is detected and then send an alarm to hospital staff or the patient's relatives. Our wireless sensor nodes are MICAz Motes developed by Crossbow Technology. The proposed system can be used for patients living in a clinical environment or at their home, where they do only their daily routines. The analysis of the recorded data is done by an Artificial Neural Network and K Nearest-Neighbor to recognize seizure movements from normal movements. The results show that K Nearest Neighbor performs better than Artificial Neural Network for detecting these seizures. The results also show that if at least 50% of the signal consists of seizure samples, we can detect the seizure accurately. In addition, there is no need for training the algorithm for each new patient.