Direction of arrival estimation in the presence of distributed noise sources: Cumulant based approach

In the past few years there have been attempts to develop subspace methods for DoA (direction of arrival) estimation using a fourth?order cumulant which is known to de?emphasize Gaussian background noise. To gauge the relative performance of the cumulant MUSIC (MUltiple SIgnal Classification) (c?MUSIC) and the standard MUSIC, based on the covariance function, an extensive numerical study has been carried out, where a narrow?band signal source has been considered and Gaussian noise sources, which produce a spatially correlated background noise, have been distributed. These simulations indicate that, even though the cumulant approach is capable of de?emphasizing the Gaussian noise, both bias and variance of the DoA estimates are higher than those for MUSIC. To achieve comparable results the cumulant approach requires much larger data, three to ten times that for MUSIC, depending upon the number of sources and how close they are. This is attributed to the fact that in the estimation of the cumulant, an average of a product of four random variables is needed to make an evaluation. Therefore, compared to those in the evaluation of the covariance function, there are more cross terms which do not go to zero unless the data length is very large. It is felt that these cross terms contribute to the large bias and variance observed in c?MUSIC. However, the ability to de?emphasize Gaussian noise, white or colored, is of great significance since the standard MUSIC fails when there is colored background noise. Through simulation it is shown that c?MUSIC does yield good results, but only at the cost of more data.

Smart applications for energy harvested WSNs

A Wireless Sensor Network (WSN) powered using harvested energies is limited in its operation by instantaneous power. Since energy availability can be different across nodes in the network, network setup and collaboration is a non trivial task. At the same time, in the event of excess energy, exciting node collaboration possibilities exist; often not feasible with battery driven sensor networks. Operations such as sensing, computation, storage and communication are required to achieve the common goal for any sensor network. In this paper, we design and implement a smart application that uses a Decision Engine, and morphs itself into an energy matched application. The results are based on measurements using IRIS motes running on solar energy. We have done away with batteries; instead used low leakage super capacitors to store harvested energy. The Decision Engine utilizes two pieces of data to provide its recommendations. Firstly, a history based energy prediction model assists the engine with information about in-coming energy. The second input is the energy cost database for operations. The energy driven Decision Engine calculates the energy budgets and recommends the best possible set of operations. Under excess energy condition, the Decision Engine, promiscuously sniffs the neighborhood looking for all possible data from neighbors. This data includes neighbor's energy level and sensor data. Equipped with this data, nodes establish detailed data correlation and thus enhance collaboration such as filling up data gaps on behalf of nodes hibernating under low energy conditions. The results are encouraging. Node and network life time of the sensor nodes running the smart application is found to be significantly higher compared to the base application.

Localized data gathering paradigms for small and marginal farm lands in Semi-Arid region – Issues and Concerns

In this work we explore the application of wireless sensor technologies for the benefit of small and marginal farmers in semi-arid regions. The focus in this paper is to discuss the merits and demerits of data gathering & relay paradigms that collect localized data over a wide area. The data gathered includes soil moisture, temperature, pressure, rain data and humidity. The challenge to technology intervention comes mainly due to two reasons: (a) Farmers in general are interested in crop yield specific to their piece of land. This is because soil texture can vary rapidly over small regions. (b) Due to a high run-off, the soil moisture retention can vary from region to region depending on the topology of the farm. Both these reasons alter the needs drastically. Additionally, small and marginal farms can be sandwiched between rich farm lands. The village has very little access to grid power. Power cuts can extend up to 12 hours in a day and upto 3 or 4 days during some months in the year. In this paper, we discuss 3 technology paradigms for data relaying. These include Wi-Fi (Wireless Fidelity), GPRS (General Packet Radio Service) and DTN (Delay and Disruption Tolerant Network) technologies. We detail the merits and demerits of each of these solutions and provide our final recommendations. The project site is a village called Chennakesavapura in the state of Karnataka, India.

Simulation Blocks for TOSSIM-T2"

We develop several hardware and software simulation blocks for the TinyOS-2 (TOSSIM-T2) simulator. The choice of simulated hardware platform is the popular MICA2 mote. While the hardware simulation elements comprise of radio and external flash memory, the software blocks include an environment noise model, packet delivery model and an energy estimator block for the complete system. The hardware radio block uses the software environment noise model to sample the noise floor.The packet delivery model is built by establishing the SNR-PRR curve for the MICA2 system. The energy estimator block models energy consumption by Micro Controller Unit(MCU), Radio,LEDs, and external flash memory. Using the manufacturer’s data sheets we provide an estimate of the energy consumed by the hardware during transmission, reception and also track several of the MCUs states with the associated energy consumption. To study the effectiveness of this work, we take a case study of a paper presented in [1]. We obtain three sets of results for energy consumption through mathematical analysis, simulation using the blocks built into PowerTossim-T2 and finally laboratory measurements. Since there is a significant match between these result sets, we propose our blocks for T2 community to effectively test their application energy requirements and node life times.

Eye-View: A retinal image capture system

This paper presents a low cost but high resolution retinal image acquisition system of the human eye. The images acquired by a CMOS image sensor are communicated through the Universal Serial Bus (USB) interface to a personal computer for viewing and further processing. The image acquisition time was estimated to be 2.5 seconds. This system can also be used in telemedicine applications.

Counter-free input-determined timed automata

We identify a class of timed automata, which we call counter-free input-determined automata, which characterize the class of timed languages definable by several timed temporal logics in the literature, including MTL. We make use of this characterization to show that MTL+Past satisfies an “ultimate stability” property with respect to periodic sequences of timed words. Our results hold for both the pointwise and continuous semantics. Along the way we generalize the result of McNaughton-Papert to show a counter-free automata characterization of FO-definable finitely varying functions.

On continuous timed automata with input-determined guards

We consider a general class of timed automata parameterized by a set of “input-determined” operators, in a continuous time setting. We show that for any such set of operators, we have a monadic second order logic characterization of the class of timed languages accepted by the corresponding class of automata. Further, we consider natural timed temporal logics based on these operators, and show that they are expressively equivalent to the first-order fragment of the corresponding MSO logics. As a corollary of these general results we obtain an expressive completeness result for the continuous version of MTL.

Topological analysis of general linear networks

A new method of network analysis, a generalization in several different senses of existing methods and applicable to all networks for which a branch-admittance (or impedance) matrix can be formed, is presented. The treatment of network determinants is very general and essentially four terminal rather than three terminal, and leads to simple expressions based on trees of a simple graph associated with the network and matrix, and involving products of low-order, usually(2 times 2)determinants of tree-branch admittances, in addition to tree-branch products as in existing methods. By comparison with existing methods, the total number of trees and of tree pairs is usually considerably reduced, and this fact, together with an easy method of tree-pair sign determination which is also presented, makes the new method simpler in general. The method can be very easily adapted, by the use of infinite parameters, to accommodate ideal transformers, operational amplifiers, and other forms of network constraint; in fact, is thought to be applicable to all linear networks.