Wireless channel test-bed for DSRC applications using USRP software defined radio

2013 ◽  
Author(s):  
Arun Kumar ◽  
Sima Noghanian
Keyword(s):  
Software Defined Radio ◽  
Wireless Channel ◽  
Test Bed

scholarly journals Intelligent Non-Contact Sensing for Connected Health Using Software Defined Radio Technology

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1558
Author(s):  
Muhammad Bilal Khan ◽  
Mubashir Rehman ◽  
Ali Mustafa ◽  
Raza Ali Shah ◽  
Xiaodong Yang
Keyword(s):  
Psychological Health ◽  
Software Defined Radio ◽  
Orthogonal Frequency Division Multiplexing ◽  
Additive White Gaussian Noise ◽  
Vital Signs ◽  
Wireless Channel ◽  
Machine Learning Algorithms ◽  
Breathing Patterns ◽  
Connected Health ◽  
Innovative Solution

The unpredictable situation from the Coronavirus (COVID-19) globally and the severity of the third wave has resulted in the entire world being quarantined from one another again. Self-quarantine is the only existing solution to stop the spread of the virus when vaccination is under trials. Due to COVID-19, individuals may have difficulties in breathing and may experience cognitive impairment, which results in physical and psychological health issues. Healthcare professionals are doing their best to treat the patients at risk to their health. It is important to develop innovative solutions to provide non-contact and remote assistance to reduce the spread of the virus and to provide better care to patients. In addition, such assistance is important for elderly and those that are already sick in order to provide timely medical assistance and to reduce false alarm/visits to the hospitals. This research aims to provide an innovative solution by remotely monitoring vital signs such as breathing and other connected health during the quarantine. We develop an innovative solution for connected health using software-defined radio (SDR) technology and artificial intelligence (AI). The channel frequency response (CFR) is used to extract the fine-grained wireless channel state information (WCSI) by using the multi-carrier orthogonal frequency division multiplexing (OFDM) technique. The design was validated by simulated channels by analyzing CFR for ideal, additive white gaussian noise (AWGN), fading, and dispersive channels. Finally, various breathing experiments are conducted and the results are illustrated as having classification accuracy of 99.3% for four different breathing patterns using machine learning algorithms. This platform allows medical professionals and caretakers to remotely monitor individuals in a non-contact manner. The developed platform is suitable for both COVID-19 and non-COVID-19 scenarios.

scholarly journals Non-Contact Sensing Testbed for Post-Surgery Monitoring by Exploiting Artificial-Intelligence

2020 ◽  
Vol 10 (14) ◽  
pp. 4886 ◽  
Author(s):  
Mohammed Ali Mohammed Al-hababi ◽  
Muhammad Bilal Khan ◽  
Fadi Al-Turjman ◽  
Nan Zhao ◽  
Xiaodong Yang
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Software Defined Radio ◽  
Orthogonal Frequency Division Multiplexing ◽  
Nearest Neighbor ◽  
Wireless Channel ◽  
Weight Lifting ◽  
K Nearest Neighbor ◽  
Post Surgery ◽  
Contact Sensing

Non-contact health care monitoring is a unique feature in the emerging 5G networks that is achieved by exploiting artificial intelligence (AI). The ratio of the number of health care problems and patients is increasing exponentially and creating burgeoning data. The integration of AI and Internet of things (IoT) systems enables us to increase the huge volume of data to be generated. The approach by which AI is applied to the IoT systems enhances the intelligence of the health care system. In post-surgery monitoring of the patient, timely consultation is essential before further loss. Unfortunately, even after the advice of the doctor to the patient, he/she may forget to perform the activity in the correct way, which may lead to complications in recovery. In this research, the idea is to design a non-contact sensing testbed using AI for the classification of post-surgery activities. Universal software-defined radio peripheral (USRP) is utilized to collect the data of spinal cord operated patients during weight lifting activity. The wireless channel state information (WCSI) is extracted by using orthogonal frequency division multiplexing (OFDM) technique. AI applies machine learning to classify the correct and wrong way of weight lifting activity that was considered for experimental analysis. The accuracy achieved by the proposed testbed by using a fine K-nearest neighbor (FKNN) algorithm is 99.6%.

scholarly journals A COTS RF/Optical Software Defined Radio for the Integrated Radio and Optical Communications Test Bed

2016 ◽  
Author(s):  
Jennifer Nappier ◽  
Daniel Zeleznikar ◽  
Adam Wroblewski ◽  
Roger Tokars ◽  
Bryan Schoenholz ◽  
...  
Keyword(s):  
Optical Communications ◽  
Software Defined Radio ◽  
Test Bed

Multiband OFDM for Cognitive Radio – A Way for Cyclostationary Detection and Interference Cancellation

2016 ◽  
Vol 6 (4) ◽  
pp. 1702
Author(s):  
Avila J ◽  
Thenmozhi K
Keyword(s):  
Cognitive Radio ◽  
Interference Cancellation ◽  
Software Defined Radio ◽  
Test Bed ◽  
Radio System ◽  
Labview Software ◽  
Free Spectrum ◽  
Wireless Environment ◽  
Cyclostationary Detection ◽  
Hardware Test

With the tremendous growth in wireless technology there has been a shortage in the spectrum utilized for certain applications while some spectrum remains idle. To overcome this problem and for the efficient utilization of the spectrum cognitive radio is the suitable solution.Multiband OFDM can be easily modeled as cognitive radio, a technology that is employed for utilizing the available spectrum in the most efficient way. Since sensing of the free spectrum for detecting the arrival of the primary users is the foremost job of cognitive, here cyclostationary based spectrum sensing is carried out. Its performance is investigated using universal software defined radio peripheral (USRP) kit which is the hardware test bed for the cognitive radio system. Results are shown using Labview software. Further to mitigate the interference between the primary and cognitive users a modified intrusion elimination (AIC) algorithm had been proposed which in turn ensures the coexistence of both the users in the same wireless environment.

scholarly journals Implementation of PCC-OFDM on a software-defined radio testbed

2017 ◽  
Vol 5 (2) ◽  
pp. 17
Author(s):  
Gayathri Kongara ◽  
Jean Armstrong
Keyword(s):  
Carrier Frequency ◽  
Software Defined Radio ◽  
Orthogonal Frequency Division Multiplexing ◽  
Carrier Frequency Offset ◽  
Frequency Offset ◽  
Wireless Channel ◽  
Error Performance ◽  
Hardware Platform ◽  
Field Programmable ◽  
Comparative Results

A software-defined radio implementation of polynomial cancellation coded orthogonal frequency division multiplexing (PCC-OFDM) on a field programmable gate array (FPGA) based hardware platform is presented in this paper. Previous publications on PCC-OFDM have demonstrated that, in comparison to normal cyclic prefix based OFDM, it is robust in the presence of many impairments including carrier frequency offset, multipath distortion and phase noise. The error performance of the two multicarrier techniques is compared on a practical wireless channel under common channel impairments such as carrier frequency offset, multipath and noise. Based on the comparative results obtained on the hardware platform, the properties of PCC-OFDM make it a suitable candidate for consideration in future G applications requiring robust performance in asynchronous environments with minimal out of band spectral emissions.

scholarly journals A Low-Cost Software Defined Radio Based Cognitive Radio Test-Bed for LTE Networks

2018 ◽  
Vol 7 (3.1) ◽  
pp. 51
Author(s):  
Kolluru Suresh Babu ◽  
Srikanth Vemuru
Keyword(s):  
Cognitive Radio ◽  
Software Defined Radio ◽  
Experimental Validation ◽  
Low Cost ◽  
Spectrum Management ◽  
Test Bed ◽  
Lte Networks ◽  
Lte Advanced ◽  
Integrated Software ◽  
Secondary Link

In this work, we present a low-cost implementation of a Cognitive Radio (CR) test-bed for LTE and LTE-Advanced (LTE-A) Networks. The test-bed setup is implemented using highly integrated Software Defined Radio (SDR) platforms which are well suited for wireless communication. Each transceiver can be configured to work as a primary (resp. secondary) eNodeB or a primary (resp. secondary) user in a Heterogeneous Cognitive Radio framework. In this context, we study the problem of spectrum management in an LTE based heterogeneous network and propose simple distributed algorithms which the secondary eNodeB can employ to efficiently manage the spectral opportunities that arise in such a network. Experimental validation show significant improvement in the secondary link throughput.  

scholarly journals Industrial wireless channel measurements in a 2.4 GHz ISM radio band using a low-cost SDR-based channel sounder

2020 ◽  
Vol 9 (1) ◽  
pp. E1-1-E1-25
Author(s):  
Grzegorz Korzeniewski ◽  
◽  
Roberto Carrasco Álvarez ◽  
Keyword(s):  
Software Defined Radio ◽  
Communication Systems ◽  
Multipath Propagation ◽  
Low Cost ◽  
Wireless Channel ◽  
Channel Measurements ◽  
Channel Sounding ◽  
Channel Sounder ◽  
Radio Band ◽  
Mathematical Foundations

Industrial wireless channel is a challenge for the design of communication systems, due to non-Line-of-Sight transmission, caused by the presence of many highly reflective obstacles, and machines in operation, which are a source of the increased noise level. The main effect, which must be analyzed, is multipath propagation. In this article, a low-cost sounding system is proposed, based on Software Defined Radio (SDR) equipment, with the intention of making sounding devices more accessible to a larger group of researchers. Likewise, the mathematical foundations and the software/hardware implementation of the wireless channel sounding system are presented, and the solutions to mitigate the synchronization issues and SDR limitations are also introduced. The performance of the proposed sounder is validated through a measurement campaign in an industrial workshop, considering the 2.4 GHz Industrial, Scientific, Medical (ISM) band. Channel sounding measurements corroborate the accuracy of the results, which converge with the channel mathematical models proposed for several industrial environments and reported in the state-of-the-art literature. In this sense, the proposed channel sounder can be used to investigate the wireless propagation environments.

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