Browsing by Author "Amanna, Ashwin E."

Now showing 1 - 9 of 9
  • Thumbnail Image
    Automatic Modulation Classification Using Grey Relational Analysis
    Price, Matthew (Virginia Tech, 2011-04-25)
    One component of wireless communications of increasing necessity in both civilian and military applications is the process of automatic modulation classification. Modulation of a detected signal of unknown origin requiring interpretation must first be determined before the signal can be demodulated. This thesis presents a novel architecture for a modulation classifier that determines the most likely modulation using Grey Relational Analysis with the extraction and combination of multiple signal features. An evaluation of data preprocessing methods is conducted and performance of the classifier is investigated with the addition of each new signal feature used for classification.
  • Thumbnail Image
    Calibration of Snowmaking Equipment for Efficient Use on Virginia's Smart Road
    Shea, Edward (Virginia Tech, 1999-08-04)
    Virginia's Smart Road, to be completed by early 2000, is a test bed for numerous research activities including snow and ice control, remote sensor testing, snow removal management, safety and human factors, and vehicle dynamics. An all-weather testing system will feature 75 automated snowmaking towers. In order to provide timely and repeatable weather scenarios, equipment operators will need to understand fully the limitations and capabilities of the snowmaking system. The research presented herein addresses the hydraulic and hydrologic variables and design methodology to implement efficient snowmaking at a transportation research facility. Design variables include nozzle configuration, water pressure and flowrate, compressed air pressure and flowrate, tower orientation, snow inducer concentration, water and compressed air temperature, and ambient weather conditions. Testing and data collection was performed at the Snow Economics, Inc. research and development site at Seven Springs Mountain Resort in Champion, PA. The results of this work will be used to guide the operators of the Smart Road on the most efficient use of the snowmaking equipment.
  • Thumbnail Image
    Cognitive radio engine parametric optimization utilizing Taguchi analysis
    Amanna, Ashwin E.; Ali, Daniel; Gadhiok, Manik; Price, Matthew; Reed, Jeffrey H. (2012-01-09)
    Cognitive radio (CR) engines often contain multiple system parameters that require careful tuning to obtain favorable overall performance. This aspect is a crucial element in the design cycle yet is often addressed with ad hoc methods. Efficient methodologies are required in order to make the best use of limited manpower, resources, and time. Statistical methods for approaching parameter tuning exist that provide formalized processes to avoid inefficient ad hoc methods. These methods also apply toward overall system performance testing. This article explores the use of the Taguchi method and orthogonal testing arrays as a tool for identifying favorable genetic algorithm (GA) parameter settings utilized within a hybrid case base reasoning/genetic algorithm CR engine realized in simulation. This method utilizes a small number of test cases compared to traditional design of experiments that rely on full factorial combinations of system parameters. Background on the Taguchi method, its drawbacks and limitations, past efforts in GA parameter tuning, and the use of GA within CR are overviewed. Multiple CR metrics are aggregated into a single figure-of-merit for quantification of performance. Desirability functions are utilized as a tool for identifying ideal settings from multiple responses. Kiviat graphs visualize overall CR performance. The Taguchi method analysis yields a predicted best combination of GA parameters from nine test cases. A confirmation experiment utilizing the predicted best settings is compared against the predicted mean, and desirability. Results show that the predicted performance falls within 1.5% of the confirmation experiment based on 9 test cases as opposed to the 81 test cases required for a full factorial design of experiments analysis.
  • Thumbnail Image
    Hybrid Experiential-Heuristic Cognitive Radio Engine Architecture and Implementation
    Amanna, Ashwin E.; Ali, Daniel; Fitch, David Gonzalez; Reed, Jeffrey H. (Hindawi, 2012-05-16)
    The concept of cognitive radio (CR) focuses on devices that can sense their environment, adapt configuration parameters, and learn from past behaviors. Architectures tend towards simplified decision-making algorithms inspired by human cognition. Initial works defined cognitive engines (CEs) founded on heuristics, such as genetic algorithms (GAs), and case-based reasoning (CBR) experiential learning algorithms. This hybrid architecture enables both long-term learning, faster decisions based on past experience, and capability to still adapt to new environments. This paper details an autonomous implementation of a hybrid CBR-GA CE architecture on a universal serial radio peripheral (USRP) software-defined radio focused on link adaptation. Details include overall process flow, case base structure/retrieval method, estimation approach within the GA, and hardware-software lessons learned. Unique solutions to realizing the concept include mechanisms for combining vector distance and past fitness into an aggregate quantification of similarity. Over-the-air performance under several interference conditions is measured using signal-to-noise ratio, packet error rate, spectral efficiency, and throughput as observable metrics. Results indicate that the CE is successfully able to autonomously change transmit power, modulation/coding, and packet size to maintain the link while a non-cognitive approach loses connectivity. Solutions to existing shortcomings are proposed for improving case-base searching and performance estimation methods.
  • Thumbnail Image
    Implementation and Analysis of Wireless Local Area Networks for High-Mobility Telematics
    Aziz, Farhan Muhammad (Virginia Tech, 2003-05-30)
    Wireless networks provide communications to fixed, portable and mobile users and offer substantial flexibility to both end-users and service providers. Current cellular/PCS networks do not offer cost effective high data rate services for applications, such as, telematics, traffic surveillance and rescue operations. This research studies the feasibility and behavior of outdoor implementation of low-cost wireless LANs used for high mobility telematics and traffic surveillance. A multi-hop experimental wireless data network is designed and tested for this purpose. Outdoor field measurements show the wireless coverage and throughput patterns for static and mobile users. The results suggest that multi-hop wireless LANs can be used for high mobility applications if some protocols are improved.
  • Thumbnail Image
    A novel OFDM Blind Equalizer: Analysis and Implementation
    Gonzalez Fitch, David E. (Virginia Tech, 2012-07-13)
    Link adaptation is important to guarantee robust and reliable wireless communications with- out wasting valuable radio resources. This technique has become more feasible with the recent appearance of Software Defined Radios (SDRs), which allow easy reconfiguration of their parameters via software. As the environment changes over time, the transmitter needs to be able to effectively estimate its performance under different radio input parameters to be able to find a close to optimal solution. In most wireless communications, an equalizer is implemented at the receiver to estimate the channel impulse response. This estimate can be fed back to the transmitter via a feedback channel, which can in turn help generate a sub-optimal transmission solution for the current situation. In this thesis, a link adaptation method is proposed that uses Orthogonal Frequency-Division Multiplexing (OFDM) in conjunction with blind channel estimation. With the use of OFDM, it can be assumed that the frequency fading at each subcarrier is approximately flat. In addition, under the assumption that the channel is quasi-stationary, the Bit Error Rate (BER) at each subcarrier can be estimated by using the well-known BER formulas for an Additive White Gaussian Noise (AWGN) channel. However, the effect of imperfect channel estimation must also be taken into account. A novel OFDM blind channel estimator is developed. Finally, both simulations and real over-the-air results are presented.
  • Thumbnail Image
    Optical method of recording electrical activity in isolated rabbit hearts
    Amanna, Ashwin E. (Virginia Tech, 1993-12-01)
    A recently developed optical method utilizes a single, implantable, optical fiber to record electrical activity from isolated hearts stained with voltage-sensitive dyes. This optical technique generates recordings of transmembrane potential from excitable myocardial tissue, and remain free from stimulus artifacts that accompany electro stimulation and hinder all standard electrode recording methods during the application of high-voltage electrical shocks. The fiber optic system uses a l00J,lm diameter core fiber which can record from epicardial surface, internal mid-myocardium, or endocardial surfaces. The stained tissue is excited through the fiber and the resulting fluorescence is transmitted through the same fiber to a photomultiplier tube. Changes in fluorescence accompanying normal cardiac action potentials usually range from 1-5%. Substantive motion related signals accompany normal beating hearts, drowning out the actual signal that corresponds to change in membrane potential. When added to the nutrient solution of the heart, an excitation / contraction decoupler restricts motion and reduces the motion related signal making it easier to isolate the true membrane potential signal.
  • Thumbnail Image
    Scalable Parameter Management using Casebased Reasoning for Cognitive Radio Applications
    Ali, Daniel Ray (Virginia Tech, 2012-05-01)
    Cognitive radios have applied various forms of artificial intelligence (AI) to wireless systems in order to solve the complex problems presented by proper link management, network traffic balance, and system efficiency. Casebased reasoning (CBR) has seen attention as a prospective avenue for storing and organizing past information in order to allow the cognitive engine to learn from previous experience. CBR uses past information and observed outcomes to form empirical relationships that may be difficult to model apriori. As wireless systems become more complex and more tightly time constrained, scalability becomes an apparent concern to store large amounts of information over multiple dimensions. This thesis presents a renewed look at an abstract application of CBR to CR. By appropriately designing a case structure with useful information both to the cognitive entity as well as the underlying similarity relationships between cases, an accurate problem description can be developed and indexed. By separating the components of a case from the parameters that are meaningful to similarity, the situation can be quickly identified and queried given proper design. A data structure with this in mind is presented that orders cases in terms of general placement in Euclidean space, but does not require the discrete calculation of distance between the query case and all cases stored. By grouping possible similarity dimension values into distinct partitions called "similarity buckets", a data structure is developed with constant (O(1)) access time, which is an improvement of several orders of magnitude over traditional linear approaches (O(n)).
  • Thumbnail Image
    System and method for heterogenous spectrum sharing between commercial cellular operators and legacy incumbent users in wireless networks
    (United States Patent and Trademark Office, 2016-12-06)
    Described herein are systems and methods for telecommunications spectrum sharing between multiple heterogeneous users, which leverage a hybrid approach that includes both distributed spectrum sharing, spectrum-sensing, and use of geo-reference databases.