Ravi Tiwari

Performance analysis of patient monitoring system under different routing algorithm

For the sake of improving the overhead occurring due to control operations and to attain the reliable data signaling in the patient monitoring system based on ZigBee, we are focusing on the comparative performance evaluation of different routing algorithm in a wireless body area network (WBAN) using the OPNET simulation tool. WBAN contains the number of wireless mobile nodes forming an unpredictable topology and link instability that make routing a core issue. In this paper a comparative study of three routing algorithms named AODV, DSR, and OLSR has been done with increasing number of wireless nodes in WBAN on account of end to end delay, load, and throughput. Simulation results demonstrate that OLSR routing protocol outperforms among all protocols under an increasing number of node scenario.

Dynamic-Double-Threshold Energy Detection Scheme under Noise Varying Environment in Cognitive Radio System

cognitive radio, spectrum sensing is a key component for securing the licensed terminal from interference and detects the white spectrum hole to improve the spectrum efficiency. In the existing techniques, the noise uncertainty was either not considered or only detrimental effects are mitigated without much performance improvement. Therefore, a novel dynamic- double-threshold energy detection scheme is proposed under noise uncertainty, and its performance has been studied. Simulation analysis and results show that the proposed scheme improves the performance of detection for smaller values of false alarm probability. It is also found that the detection probability is reached at a satisfactory level, even under varying noise uncertainty.

Comparative performance evaluation of a new dynamic-double-threshold energy detection scheme with basic spectrum sensing techniques

Spectrum sensing is a primary requirement in cognitive radio systems. In order to improve the spectrum efficiency and facilitate the unlicensed mobile users to use the empty licensed radio frequency band of the electromagnetic spectrum, the spectrum sensing techniques should be more accurate and reliable. In this paper, the disadvantages of basic transmitter detection techniques are discussed, and an innovative, dynamic-double-threshold energy detection scheme is proposed, which overcome the lacunas of existing techniques. Simulation analysis and results show the comparison and performance improvement in terms of detection probability and false alarm probability.

Performance analysis of mobile patient network using AODV and DSR routing algorithms

In the case of medical applications, the main requirement is to improve the control overhead and to achieve the reliable data transmission. A ZigBee based mobile patient monitoring network model is proposed, and its performance improvement is analysed based on reduced delay and enhanced throughput. We are focusing on the separate and comparative performance evaluation of AODV and DSR routing protocol in a wireless body area network (WBAN). WBAN has numbered of the sensor nodes for collecting the physiological status of patients like ECG, temperature, Heartbeat, etc. Mobile sensor nodes forming an unpredictable topology and link instability that make routing protocols a core issue. In this paper, we considered one wireless network having the hospital care center who monitors mobile patient under AODV and DSR routing protocols, and transmits data to various nodes. Simulation has been performed using OPNET simulation tool, and the results demonstrate that the AODV routing protocol is best suited for medical monitoring system.

Sojourn time based maximum likelihood estimator for velocity estimation in HetNets

In this paper, we propose a sojourn time based maximum likelihood (ML) estimation technique for accurately estimating the velocity of mobile users in Heterogeneous Networks (HetNets). In such networks, base station (BS) density in a particular area is more compared to the traditional macrocell network for better quality of service. However, increase in BS density results in more frequent handovers, and thus causes handoff failures. To address these challenges, knowledge of mobile users velocity is a significant requirement. In this work, we develop a velocity estimation strategy based on sojourn time. Sojourn time is defined as the time span in which a user is served by one BS before it handed over to another BS for better services. The sojourn time method is used in this analysis as it considers both handover count and sojourn time information in estimating the user velocity. Here, we consider that BSs are randomly distributed by homogeneous Poisson point process (PPP), and their coverage is modeled by using Poisson-Voronoi tessellation. Using these statistics, we first derive the Cramer-Rao Lower Bound (CRLB) based on sojourn time and later we determine an ML estimator, which is asymptotically unbiased. We validate our approach by simulation in which we show the tight closeness of ML estimator asymptotic variance with CRLB. Also, we compare the proposed ML estimator with CRLB of velocity estimator based on sojourn time and handover count. Our results illustrate that proposed ML estimator based on sojourn time outperforms the CRLB based on handover count.

A ML detection for UWA communication with Nakagami fading and GG noise

In this paper, we propose a maximum likelihood (ML) detection technique for underwater acoustic (UWA) communication in oceanic medium. The multi-path fading and additive noise in UWA channel is modeled by Nakagami distribution and mixture of Generalized Gaussian (GG) distribution, respectively. In the system model, we also consider multiple receive antennas to take advantage of spatial diversity. In order to design an efficient and computationally inexpensive detector, we apply Expectation Maximization (EM) algorithm to decompose the additive noise distribution in terms of finite weighted Gaussian components. In this context, we propose decision boundary for ML detection of binary modulated signal. A discussion on variation in decision boundary under various signal to noise ratio (SNR) levels is also presented. Finally, we compare the performance of proposed ML detection technique with conventional maximal ratio combining (MRC) technique, and validate the proposed approach by showing improvement in performance.

Maximum likelihood estimator for velocity estimation in HetNets based on handoff count

In this paper, we propose a maximum likelihood based estimation technique for accurately estimating the velocity of mobile users in Heterogeneous networks (HetNets). In HetNets, base station (BS) density around a particular user is more compared to the traditional cellular network, resulting in frequent handoffs for a better quality of service. However, if the mobility management is not efficient, there is always a high probability of handover failures, unnecessary handoffs and call drops. The accurate estimation of the velocity of mobile users is one of the most challenging task in mobility management. The proposed velocity estimation strategy is based on handoff count which occurs during a predefined time span. Here we model densely deployed BSs using random waypoint process (RWP) and analyse the statistics of handover count as a function of velocity, BS density, and time span. Using these statistics we first derive the Cramer-Rao lower bound (CRLB) and later we determine a maximum likelihood estimator (MLE), which is an asymptotic unbiased estimator. We validate our approach by simulation which show the tight closeness of MLE asymptotic variance with CRLB. In addition, our result illustrates that velocity estimation error decreases with increase in BS density and time span of handover count measurements.

Performance Evaluation of Patient Monitoring System With Different Routing Protocols

In order to improve the control overhead and to achieve the reliable data transmission in the patient monitoring system based on ZigBee, here the concentration is given on the comparative performance evaluation of different routing algorithm in a wireless body area network (WBAN) using the OPNET simulation tools. WBAN contains the number of wireless mobile nodes forming an unpredictable topology and link instability that make routing a core issue. This paper provides a relative analysis of AODV, DSR, and OLSR routing protocols with increasing number of wireless nodes in WBAN on the basis of end to end delay, load, and throughput. Simulation results demonstrate that OLSR routing protocol is performing best amongst all protocols under an increasing number of node scenario. General Terms WBAN, Patient Monitoring, AODV, DSR, OLSR, OPNET.