scholarly journals Cognitive engine implementation for wireless multicarrier transceivers

2007 ◽  
Vol 7 (9) ◽  
pp. 1129-1142 ◽  
Author(s):  
Tim R. Newman ◽  
Brett A. Barker ◽  
Alexander M. Wyglinski ◽  
Arvin Agah ◽  
Joseph B. Evans ◽  
...  
Keyword(s):  
Cognitive Engine ◽  
Multicarrier Transceivers

Cognitive engine based on binary ant colony simulated annealing algorithm

2013 ◽  
Vol 32 (12) ◽  
pp. 3478-3481
Author(s):  
Ling XIA ◽  
Wen-jiang FENG
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Ant Colony ◽  
Cognitive Engine ◽  
Annealing Algorithm

Secure Intelligent Radio for Trains (SIRT)

2017 ◽  
Author(s):  
K. R. Damindra S. Bandara ◽  
Satish Kolli ◽  
Duminda Wijesekara
Keyword(s):  
Critical Infrastructure ◽  
Adaptive Modulation ◽  
Radio Spectrum ◽  
Spectrum Management ◽  
Worker Safety ◽  
Radio Noise ◽  
Radio Communication ◽  
Radio System ◽  
Cognitive Engine ◽  
Prototype Development

American Railroads are planning to complete implementing their Positive Train Control (PTC) systems by 2020. Safety objectives of PTC are to avoid inter-train collisions, train derailments and ensuring railroad worker safety. Under published specifications of I-ETMS (the PTC system developed by Class I freight railroads), the on-board PTC controller communicates with two networks; namely, the Signaling network and the Wayside Interface Unit network to gather navigational information such as the positions of other trains, the status of critical infrastructure (such as switches) and any hazardous conditions that may affect the train path. By design, PTC systems are predicated on having a reliable radio network operating in reserved radio spectrum, although the PTC system itself is designed to be a real-time fail safe distributed control systems. Secure Intelligent Radio for Trains (SIRT) is an intelligent radio that is customized to train operations with the aim of improving the reliability and security of the radio communication network. SIRT has two tiers. The upper tier has the Master Cognitive Engine (MCE) which communicates with other SIRT nodes to obtain signaling and wayside device information. To do so, the MCE communicates with cognitive engines at the lower tier of SIRT; namely the Cryptographic Cognitive Engine (CCE) (that provide cryptographic security and threat detection) and the Spectrum Management Cognitive Engine (SCE) (that uses spectrum monitoring, frequency hopping and adaptive modulation to ensure the reliability of the radio communication medium). We presented the architecture and the prototype development of the CCE in [1]. This paper presents the design of the MCE and the SCE. We are currently developing a prototype of the SCE and the MCE and testing the performance of our cognitive radio system under varying radio noise conditions. Our experiments show that SIRT dynamically switches modulation schemes in response to radio noise and switches channels in response to channel jamming.

Implementation and On-Orbit Testing Results of a Space Communications Cognitive Engine

2018 ◽  
Vol 4 (4) ◽  
pp. 825-842 ◽  
Author(s):  
Timothy M. Hackett ◽  
Sven G. Bilen ◽  
Paulo Victor Rodrigues Ferreira ◽  
Alexander M. Wyglinski ◽  
Richard C. Reinhart ◽  
...  
Keyword(s):  
Space Communications ◽  
Cognitive Engine

scholarly journals Cognitive Radio Transceivers: RF, Spectrum Sensing, and Learning Algorithms Review

2014 ◽  
Vol 2014 ◽  
pp. 1-21 ◽  
Author(s):  
Lise Safatly ◽  
Mario Bkassiny ◽  
Mohammed Al-Husseini ◽  
Ali El-Hajj
Keyword(s):  
Spectrum Sensing ◽  
Model Uncertainty ◽  
Unsupervised Classification ◽  
Machine Learning Techniques ◽  
Classification Algorithms ◽  
Cognitive Engine ◽  
Uwb Antennas ◽  
Hardware Impairments ◽  
Learning Techniques ◽  
Reconfigurable Radio

A cognitive transceiver is required to opportunistically use vacant spectrum resources licensed to primary users. Thus, it relies on a complete adaptive behavior composed of: reconfigurable radio frequency (RF) parts, enhanced spectrum sensing algorithms, and sophisticated machine learning techniques. In this paper, we present a review of the recent advances in CR transceivers hardware design and algorithms. For the RF part, three types of antennas are presented: UWB antennas, frequency-reconfigurable/tunable antennas, and UWB antennas with reconfigurable band notches. The main challenges faced by the design of the other RF blocks are also discussed. Sophisticated spectrum sensing algorithms that overcome main sensing challenges such as model uncertainty, hardware impairments, and wideband sensing are highlighted. The cognitive engine features are discussed. Moreover, we study unsupervised classification algorithms and a reinforcement learning (RL) algorithm that has been proposed to perform decision-making in CR networks.

A Self-Learning Method for Cognitive Engine Based on CBR and Simulated Annealing

2012 ◽  
Vol 457-458 ◽  
pp. 1586-1594
Author(s):  
Yi Jing Liu ◽  
Li Ya Chai ◽  
Jing Min Liu ◽  
Bo Wen Li
Keyword(s):  
Simulated Annealing ◽  
Learning Method ◽  
Cognitive Engine ◽  
Self Learning

A Multiple Objective Fitness Function Design Scheme for GA-Based Cognitive Engines

2015 ◽  
Vol 764-765 ◽  
pp. 444-447
Author(s):  
Keun Hong Chae ◽  
Hua Ping Liu ◽  
Seok Ho Yoon
Keyword(s):  
Genetic Algorithm ◽  
Parameter Optimization ◽  
Fitness Function ◽  
Multiple Objective ◽  
Cognitive Engine ◽  
Fitness Functions ◽  
Design Scheme ◽  
Transmission Parameter ◽  
Function Design ◽  
Single Objective

In this paper, we propose a multiple objective fitness function for cognitive engines by using the genetic algorithm (GA). Specifically, we propose four single objective fitness functions, and finally, we propose a multiple objective fitness function based on the single objective fitness functions for transmission parameter optimization. Numerical results demonstrate that we can obtain transmission parameter sets optimized for given transmission scenarios with the GA-based cognitive engine incorporating the proposed objective fitness function.

scholarly journals Hybrid cognitive engine for radio systems adaptation

Kahn at Penn ◽  
2017 ◽  
Author(s):  
Ismail AlQerm ◽  
Basem Shihada
Keyword(s):  
Cognitive Engine ◽  
Radio Systems

Design and implementation of a patient-specific cognitive engine for robotic needle insertion

2016 ◽  
Author(s):  
Xiaoyu Tan ◽  
Chin-Boon Chng ◽  
Bin Duan ◽  
Yvonne Ho ◽  
Rong Wen ◽  
...  
Keyword(s):  
Needle Insertion ◽  
Patient Specific ◽  
Cognitive Engine ◽  
Design And Implementation

scholarly journals DSP implementation of a bit loading algorithm for adaptive wireless multicarrier transceivers

2007 ◽  
Vol 7 (9) ◽  
pp. 1117-1128 ◽  
Author(s):  
Martin Cudnoch ◽  
Alexander M. Wyglinski ◽  
Fabrice Labeau
Keyword(s):  
Bit Loading ◽  
Dsp Implementation ◽  
Multicarrier Transceivers
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