Pub Date : 2016-11-01DOI: 10.1109/CCINTELS.2016.7878196
G. Verma, Om Prakash Sahu
Selection of appropriate detection threshold (λ) is a very critical task in energy detection scheme based cognitive radio (CR) system. λ is mainly selected by using two principles called as constant detection rate (CDR) in which λ is calculated by taking fixed value of probability of detection (Pd) and constant false alarm rate (CFAR) in which λ is calculated by taking fixed value of probability of false alarm Pfa. The CDR principle is mostly adopted to sufficiently protect the primary users (PUs), but it lags in exploiting the best spectrum utilization opportunities mainly when CR user is located far away where chances of interfering a PU communication are least. This overprotective nature of CR in CDR principle leads to a decrease in its achievable throughput. To overcome it, this article proposes an approach in which the location information of PU is efficiently used to access the spectrum using “opportunistic spectrum access scheme under the CDR principle” and the “scheme of spectrum sharing”. Under the proposed approach, the CR achieves a significant gain in its throughput compared to the approach in which the CDR and CFAR principles are used blindly.
{"title":"Location based throughput gain in cognitive radio","authors":"G. Verma, Om Prakash Sahu","doi":"10.1109/CCINTELS.2016.7878196","DOIUrl":"https://doi.org/10.1109/CCINTELS.2016.7878196","url":null,"abstract":"Selection of appropriate detection threshold (λ) is a very critical task in energy detection scheme based cognitive radio (CR) system. λ is mainly selected by using two principles called as constant detection rate (CDR) in which λ is calculated by taking fixed value of probability of detection (Pd) and constant false alarm rate (CFAR) in which λ is calculated by taking fixed value of probability of false alarm Pfa. The CDR principle is mostly adopted to sufficiently protect the primary users (PUs), but it lags in exploiting the best spectrum utilization opportunities mainly when CR user is located far away where chances of interfering a PU communication are least. This overprotective nature of CR in CDR principle leads to a decrease in its achievable throughput. To overcome it, this article proposes an approach in which the location information of PU is efficiently used to access the spectrum using “opportunistic spectrum access scheme under the CDR principle” and the “scheme of spectrum sharing”. Under the proposed approach, the CR achieves a significant gain in its throughput compared to the approach in which the CDR and CFAR principles are used blindly.","PeriodicalId":158982,"journal":{"name":"2016 2nd International Conference on Communication Control and Intelligent Systems (CCIS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130048323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/CCINTELS.2016.7878192
S. Misra, Rakesh Kumar
Wireless sensor network (WSN) is a network which includes spatially distributed autonomous devices using sensors to monitor environmental or physical conditions. WSN is emerging as popular and essential ways of providing pervasive computing environments for numerous applications. The sensor nodes are constrained in terms of energy and therefore energy consumption and extending network lifetime is the most challenging task. A routing protocol in WSN is enhanced to hierarchical based routing protocol because of its energy-saving capability, network scalability and network topology stabilities. In this paper we have presented various clustering approaches used in WSN. Firstly, we have classified the protocol used in Wireless Sensor Network in the form of Protocol Operation (PO), Network Structure (NS) and Path Establishment (PE). Secondly, we have provided a broad overview of the cluster based routing protocol used in Wireless sensor network in the form of block cluster, chain cluster and grid cluster. We have also compared various clustering routing protocols based on different attributes and also discussed the various issues in these routing protocols.
{"title":"A literature survey on various clustering approaches in wireless sensor network","authors":"S. Misra, Rakesh Kumar","doi":"10.1109/CCINTELS.2016.7878192","DOIUrl":"https://doi.org/10.1109/CCINTELS.2016.7878192","url":null,"abstract":"Wireless sensor network (WSN) is a network which includes spatially distributed autonomous devices using sensors to monitor environmental or physical conditions. WSN is emerging as popular and essential ways of providing pervasive computing environments for numerous applications. The sensor nodes are constrained in terms of energy and therefore energy consumption and extending network lifetime is the most challenging task. A routing protocol in WSN is enhanced to hierarchical based routing protocol because of its energy-saving capability, network scalability and network topology stabilities. In this paper we have presented various clustering approaches used in WSN. Firstly, we have classified the protocol used in Wireless Sensor Network in the form of Protocol Operation (PO), Network Structure (NS) and Path Establishment (PE). Secondly, we have provided a broad overview of the cluster based routing protocol used in Wireless sensor network in the form of block cluster, chain cluster and grid cluster. We have also compared various clustering routing protocols based on different attributes and also discussed the various issues in these routing protocols.","PeriodicalId":158982,"journal":{"name":"2016 2nd International Conference on Communication Control and Intelligent Systems (CCIS)","volume":"53 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120817139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/CCINTELS.2016.7878189
Purnima K. Sharma, D. Sharma, P. C. Sau, A.K. Gupta
This paper deals with the radio propagation models predominantly used for the 4th Generation (4G) of cellular networks generally known as Long Term Evolution (LTE). It is necessary to study the radio wave propagation models at the development level of any wireless communication network or system. A comparative analysis is made among various radio propagation prediction models to assess the appropriate prediction model which can be helpful for LTE networks in a particular environment. In the analysis part; the mean, standard deviation and root mean square value are computed. In the evaluation Free space model predicts the minimum path loss and SUI model predicts the more path loss for the given values of frequency, base station antenna heights, and Mobile equipment antenna heights and transmitted power. Ericsson, winner II, Cost-231 and ECC models are showing better results when compared with the practical data obtained in the NCR region Delhi (INDIA). Among these models Ericsson model is showing least RMSE and standard deviation. From the analysis carried out in this paper, it is observed that the Ericsson path loss model is the best model for NCR region Delhi (INDIA). To acquire more accurate results in the existed Ericsson model some modifications are given using statistical measures.
{"title":"Comparative analysis of propagation models in LTE networks with spline interpolation","authors":"Purnima K. Sharma, D. Sharma, P. C. Sau, A.K. Gupta","doi":"10.1109/CCINTELS.2016.7878189","DOIUrl":"https://doi.org/10.1109/CCINTELS.2016.7878189","url":null,"abstract":"This paper deals with the radio propagation models predominantly used for the 4th Generation (4G) of cellular networks generally known as Long Term Evolution (LTE). It is necessary to study the radio wave propagation models at the development level of any wireless communication network or system. A comparative analysis is made among various radio propagation prediction models to assess the appropriate prediction model which can be helpful for LTE networks in a particular environment. In the analysis part; the mean, standard deviation and root mean square value are computed. In the evaluation Free space model predicts the minimum path loss and SUI model predicts the more path loss for the given values of frequency, base station antenna heights, and Mobile equipment antenna heights and transmitted power. Ericsson, winner II, Cost-231 and ECC models are showing better results when compared with the practical data obtained in the NCR region Delhi (INDIA). Among these models Ericsson model is showing least RMSE and standard deviation. From the analysis carried out in this paper, it is observed that the Ericsson path loss model is the best model for NCR region Delhi (INDIA). To acquire more accurate results in the existed Ericsson model some modifications are given using statistical measures.","PeriodicalId":158982,"journal":{"name":"2016 2nd International Conference on Communication Control and Intelligent Systems (CCIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124684241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/CCINTELS.2016.7878200
Dr. T. Satyasavithri, Hyderabad, S. Devi, J. Duryea, J. Boone, E. Pietka, M. Brown, L. Wilson, B. Doust, R. Gill, Changming Sun
Lung cancer is the foremost cause of death in many regions of the world. Early detection betters the chances of survival. PA chest radiography is the most commonly used diagnosis tool for detecting lung tumor, because it is cost effective and requires less radiation dose. Radiologists fail to detect nodule from PA chest radio graphs, at early stage because of complex anatomical structure present in radio graphs. Computer aided diagnosis systems are developed to assist radiologist in detecting tumor from radio graphs at early stage. Paper describes the algorithms to find potential nodule from Posterior and Anterior (PA) chest radio graphic images. In this paper two algorithms were proposed to detect tumor from PA chest radio graphs. In the first method tumor is separated from radio graphic image using different techniques like threshold, region growing and morphological operations and identified using geometrical features extracted from the segmented tumor. In second method tumor detected automatically with threshold and Circular Hough transform.
{"title":"Nodule detection from posterior and anterior chest radio graph using circular hough transform","authors":"Dr. T. Satyasavithri, Hyderabad, S. Devi, J. Duryea, J. Boone, E. Pietka, M. Brown, L. Wilson, B. Doust, R. Gill, Changming Sun","doi":"10.1109/CCINTELS.2016.7878200","DOIUrl":"https://doi.org/10.1109/CCINTELS.2016.7878200","url":null,"abstract":"Lung cancer is the foremost cause of death in many regions of the world. Early detection betters the chances of survival. PA chest radiography is the most commonly used diagnosis tool for detecting lung tumor, because it is cost effective and requires less radiation dose. Radiologists fail to detect nodule from PA chest radio graphs, at early stage because of complex anatomical structure present in radio graphs. Computer aided diagnosis systems are developed to assist radiologist in detecting tumor from radio graphs at early stage. Paper describes the algorithms to find potential nodule from Posterior and Anterior (PA) chest radio graphic images. In this paper two algorithms were proposed to detect tumor from PA chest radio graphs. In the first method tumor is separated from radio graphic image using different techniques like threshold, region growing and morphological operations and identified using geometrical features extracted from the segmented tumor. In second method tumor detected automatically with threshold and Circular Hough transform.","PeriodicalId":158982,"journal":{"name":"2016 2nd International Conference on Communication Control and Intelligent Systems (CCIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128195656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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