Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323783
Yendoutie Nakorgou, Antoine Gnansounou, A. Kora, Mbemba Hydara
The most common used terms by telecommunication actors especially those in the mobile network sector are coverage, signal strength, quality of service etc. These related terms are major source of concern not only for regulators, operators, mobile service providers, but also users of the networks. To verify compliance of mobile networks specifications, measurement campaigns are often carried out and the most used method of which is drive test. This method is considered expensive because of the license software used, including logistics and personnel. Several alternative solutions have been developed but these involve mainly smartphone users. Information collection by these solutions are made from mobile phones, centralized and processed. However, the major obstacles in these solutions are reluctance of users, impact on user equipment and reliability of the results. The objective of this research is to evaluate reliability of these measurement solutions and compared them with drive test. The study further explore the impact of these measurements on the integration of collection applications on the users' phones.
{"title":"Accurate radio coverage assessment methods: Investigation of mobile networks based on subscribers mobile phones","authors":"Yendoutie Nakorgou, Antoine Gnansounou, A. Kora, Mbemba Hydara","doi":"10.23919/ICACT.2018.8323783","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323783","url":null,"abstract":"The most common used terms by telecommunication actors especially those in the mobile network sector are coverage, signal strength, quality of service etc. These related terms are major source of concern not only for regulators, operators, mobile service providers, but also users of the networks. To verify compliance of mobile networks specifications, measurement campaigns are often carried out and the most used method of which is drive test. This method is considered expensive because of the license software used, including logistics and personnel. Several alternative solutions have been developed but these involve mainly smartphone users. Information collection by these solutions are made from mobile phones, centralized and processed. However, the major obstacles in these solutions are reluctance of users, impact on user equipment and reliability of the results. The objective of this research is to evaluate reliability of these measurement solutions and compared them with drive test. The study further explore the impact of these measurements on the integration of collection applications on the users' phones.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125435879","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 : 2018-02-01DOI: 10.23919/ICACT.2018.8323651
Bhuridech Sudsee, Chanwit Kaewkasi
The advancement of storage technologies and the fast-growing number of generated data have made the world moved into the Big Data era. In this past, we had many data mining tools but they are inadequate to process Data-Intensive Scalable Computing workloads. The Apache Spark framework is a popular tool designed for Big Data processing. It leverages in-memory processing techniques that make Spark up to 100 times faster than Hadoop. Testing this kind of Big Data program is time consuming. Unfortunately, developers lack a proper testing framework, which cloud help assure quality of their data-intensive processing programs, while saving development time. We propose Distributed Test Checkpointing (DTC) for Apache Spark, DTC applies unit testing to the Big Data software development life cycle and reduce time spent for each testing loop with checkpoint. From the experimental results, we found that in the subsequence rounds of unit testing, DTC dramatically speed the testing time up to 450–500% faster. In case of storage, DTC can cut unnecessary data off and make the storage 19.7 times saver than the original checkpoint of Spark.
{"title":"A productivity improvement of distributed software testing using checkpoint","authors":"Bhuridech Sudsee, Chanwit Kaewkasi","doi":"10.23919/ICACT.2018.8323651","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323651","url":null,"abstract":"The advancement of storage technologies and the fast-growing number of generated data have made the world moved into the Big Data era. In this past, we had many data mining tools but they are inadequate to process Data-Intensive Scalable Computing workloads. The Apache Spark framework is a popular tool designed for Big Data processing. It leverages in-memory processing techniques that make Spark up to 100 times faster than Hadoop. Testing this kind of Big Data program is time consuming. Unfortunately, developers lack a proper testing framework, which cloud help assure quality of their data-intensive processing programs, while saving development time. We propose Distributed Test Checkpointing (DTC) for Apache Spark, DTC applies unit testing to the Big Data software development life cycle and reduce time spent for each testing loop with checkpoint. From the experimental results, we found that in the subsequence rounds of unit testing, DTC dramatically speed the testing time up to 450–500% faster. In case of storage, DTC can cut unnecessary data off and make the storage 19.7 times saver than the original checkpoint of Spark.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123696624","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 : 2018-02-01DOI: 10.23919/ICACT.2018.8323833
Sang Kwon Kim, Deokkyu Jung, Sang-Yun Lee, Sun-Joong Kim
As the number of successful global open source software have been increased recently, a research and development software funded by the government has been directed to distribute open source. In this way, we want to represent open source website for Open Smart Broadcast Platform as part of the open smart broadcast research. This website is easy to utilize for those who want to develop smart media platform. Through the website, users can easily download the source and feedback the result.
{"title":"A study on the establishment of open source website for open smart broadcast platform","authors":"Sang Kwon Kim, Deokkyu Jung, Sang-Yun Lee, Sun-Joong Kim","doi":"10.23919/ICACT.2018.8323833","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323833","url":null,"abstract":"As the number of successful global open source software have been increased recently, a research and development software funded by the government has been directed to distribute open source. In this way, we want to represent open source website for Open Smart Broadcast Platform as part of the open smart broadcast research. This website is easy to utilize for those who want to develop smart media platform. Through the website, users can easily download the source and feedback the result.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114353299","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 : 2018-02-01DOI: 10.23919/ICACT.2018.8323919
Shi Li, Inshil Doh, K. Chae
A content delivery network (CDN), as a distributed network architecture, enhances efficient delivery of content. The interconnection of different CDNs (CDNi) further improves efficiency and the experience of end users. As another distributed network with high availability and high performance, a peer-to-peer (P2P) network can provide efficient resource sharing. To combine the advantages of the two networks, we propose a hybrid CDNi-P2P architecture, along with trust management models to achieve more efficient content delivery. In CDNi-P2P architecture, end users can obtain the requested content from the nearest CDN edge server, and can also share these contents with other users in the same domain as a P2P network. After the transactions, users can rate each other based on the reputation evaluation method adopted in the system. For some mobile users, they can move among different domains and share the contents who have with the end users in different system. In general, different systems adopt different reputation evaluation standards. This leads to disparate trust values for mobile users in different systems. Based on the architecture, we propose two trust models to solve this problem: a local trust model and a cross-domain trust model. To evaluate reputation more effectively and accurately, we also propose a search algorithm for the trust model called the non-redundant indirect trust search algorithm (NRIT-SA). Using the proposed trust models, a mobile user can transform his/her local trust into mobile trust in a new domain. We thus avoid disparate trust values for a single user in different domains and improve the availability of the content possessed by mobile users as they move among different domains. The result of the performance analysis shows that when there is a high connectivity degree of users in the system, the calculation time of the proposed NRIT-SA tends to be stable. And depending on the comparison result with the full search algorithm, NRIT-SA shows more efficient calculation performance and more reliable result.
{"title":"NRIT: Non-redundant indirect trust search algorithm for a cross-domain based CDNi-P2P architecture","authors":"Shi Li, Inshil Doh, K. Chae","doi":"10.23919/ICACT.2018.8323919","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323919","url":null,"abstract":"A content delivery network (CDN), as a distributed network architecture, enhances efficient delivery of content. The interconnection of different CDNs (CDNi) further improves efficiency and the experience of end users. As another distributed network with high availability and high performance, a peer-to-peer (P2P) network can provide efficient resource sharing. To combine the advantages of the two networks, we propose a hybrid CDNi-P2P architecture, along with trust management models to achieve more efficient content delivery. In CDNi-P2P architecture, end users can obtain the requested content from the nearest CDN edge server, and can also share these contents with other users in the same domain as a P2P network. After the transactions, users can rate each other based on the reputation evaluation method adopted in the system. For some mobile users, they can move among different domains and share the contents who have with the end users in different system. In general, different systems adopt different reputation evaluation standards. This leads to disparate trust values for mobile users in different systems. Based on the architecture, we propose two trust models to solve this problem: a local trust model and a cross-domain trust model. To evaluate reputation more effectively and accurately, we also propose a search algorithm for the trust model called the non-redundant indirect trust search algorithm (NRIT-SA). Using the proposed trust models, a mobile user can transform his/her local trust into mobile trust in a new domain. We thus avoid disparate trust values for a single user in different domains and improve the availability of the content possessed by mobile users as they move among different domains. The result of the performance analysis shows that when there is a high connectivity degree of users in the system, the calculation time of the proposed NRIT-SA tends to be stable. And depending on the comparison result with the full search algorithm, NRIT-SA shows more efficient calculation performance and more reliable result.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114482173","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 : 2018-02-01DOI: 10.23919/ICACT.2018.8323881
Fuching Tsai, En-Cih Chang, Da-Yu Kao
The ubiquity of instant messaging (IM) apps on smart phones have provided criminals to communicate with channels which are difficult to decode. Investigators and analysts are increasingly experiencing large data sets when conducting cybercrime investigations. Call record analysis is one of the critical criminal investigation strategies for law enforcement agencies (LEAs). The aim of this paper is to investigate cybercriminals through network forensics and sniffing techniques. The main difficulty of retrieving valuable information from specific IM apps is how to recognize the criminal' IP address records on the Interne t. This paper proposes a packet filter framework to WhatsApp communication patterns from huge collections of network packets in order to locate criminal's identity more effectively. A rule extraction method in sniffing packets is proposed to retrieve relevant attributes from high dimensional analysis regarding to geolocation and pivot table. The results can support LEAs in discovering criminal communication payloads, as well as facilitating the effectiveness of modern call record analysis. It will be helpful for LEAs to prosecute cybercriminals and bring them to justice.
{"title":"WhatsApp network forensics: Discovering the communication payloads behind cybercriminals","authors":"Fuching Tsai, En-Cih Chang, Da-Yu Kao","doi":"10.23919/ICACT.2018.8323881","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323881","url":null,"abstract":"The ubiquity of instant messaging (IM) apps on smart phones have provided criminals to communicate with channels which are difficult to decode. Investigators and analysts are increasingly experiencing large data sets when conducting cybercrime investigations. Call record analysis is one of the critical criminal investigation strategies for law enforcement agencies (LEAs). The aim of this paper is to investigate cybercriminals through network forensics and sniffing techniques. The main difficulty of retrieving valuable information from specific IM apps is how to recognize the criminal' IP address records on the Interne t. This paper proposes a packet filter framework to WhatsApp communication patterns from huge collections of network packets in order to locate criminal's identity more effectively. A rule extraction method in sniffing packets is proposed to retrieve relevant attributes from high dimensional analysis regarding to geolocation and pivot table. The results can support LEAs in discovering criminal communication payloads, as well as facilitating the effectiveness of modern call record analysis. It will be helpful for LEAs to prosecute cybercriminals and bring them to justice.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123912572","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 : 2018-02-01DOI: 10.23919/ICACT.2018.8323807
A. Diop, S. Meza, M. Gordan, A. Vlaicu
Video surveillance is one of the key components in todays' public security. The possibility to identify abnormal events in such sequences is a difficult problem in computer vision with the aim of providing automatic means of analysis. The use of Latent Dirichlet Allocation (LDA) provided encouraging results for topic classification in text documents and extensions to the video range have already been presented in the literature. The paper approaches video sequence classification considering the extension of the LDA model by building a vocabulary based on motion information “words” that are used to isolate events/topics present in the video. The implementation is tested on the PETS datasets and results are compared with state of the art.
{"title":"LDA based classification of video surveillance sequences using motion information","authors":"A. Diop, S. Meza, M. Gordan, A. Vlaicu","doi":"10.23919/ICACT.2018.8323807","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323807","url":null,"abstract":"Video surveillance is one of the key components in todays' public security. The possibility to identify abnormal events in such sequences is a difficult problem in computer vision with the aim of providing automatic means of analysis. The use of Latent Dirichlet Allocation (LDA) provided encouraging results for topic classification in text documents and extensions to the video range have already been presented in the literature. The paper approaches video sequence classification considering the extension of the LDA model by building a vocabulary based on motion information “words” that are used to isolate events/topics present in the video. The implementation is tested on the PETS datasets and results are compared with state of the art.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115537912","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 : 2018-02-01DOI: 10.23919/ICACT.2018.8323751
B. Oh, Junhyeok Lee
This paper proposes architecture to recognize scene images based on an ensemble of two convolution neural networks. A convolution neural network is used to train massive scene images, and the other convolution neural network is used to extract objects from the scene images. The object lists are stored according to scene classes, and used as a clue to decide the top-1 and top-5 classes during scene image recognition stage.
{"title":"A case study on scene recognition using an ensemble convolution neural network","authors":"B. Oh, Junhyeok Lee","doi":"10.23919/ICACT.2018.8323751","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323751","url":null,"abstract":"This paper proposes architecture to recognize scene images based on an ensemble of two convolution neural networks. A convolution neural network is used to train massive scene images, and the other convolution neural network is used to extract objects from the scene images. The object lists are stored according to scene classes, and used as a clue to decide the top-1 and top-5 classes during scene image recognition stage.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122682688","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 : 2018-02-01DOI: 10.23919/ICACT.2018.8323887
Wook Hyun, Changkyu Lee, Shin-Gak Kang, Juyoung Park
On providing multimedia stream over a mesh-based overlay network, the starting point of buffermap is determined through negotiation with other peers. When it boots up, it does not have a starting point of its buffermap, and it can determine this value only by negotiations with other arbitrary peer. If it selects a bad start point, the peer cannot receive stream data because other peer's buffermap may not have a fragment that it needs in some time. There are some jitters in processing media for presentation and network delivery, and it accumulates over timer. This leads to the peer lag behind of actual stream. Hence, it is crucial to adjust the start point of buffermap appropriately during streaming. This paper describes how the problematic situation can be happen, and how to adapt the buffermap for stable multimedia streaming service over a mesh-based overlay network.
{"title":"Buffermap adaptation method for MP2P multimedia streaming protocol","authors":"Wook Hyun, Changkyu Lee, Shin-Gak Kang, Juyoung Park","doi":"10.23919/ICACT.2018.8323887","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323887","url":null,"abstract":"On providing multimedia stream over a mesh-based overlay network, the starting point of buffermap is determined through negotiation with other peers. When it boots up, it does not have a starting point of its buffermap, and it can determine this value only by negotiations with other arbitrary peer. If it selects a bad start point, the peer cannot receive stream data because other peer's buffermap may not have a fragment that it needs in some time. There are some jitters in processing media for presentation and network delivery, and it accumulates over timer. This leads to the peer lag behind of actual stream. Hence, it is crucial to adjust the start point of buffermap appropriately during streaming. This paper describes how the problematic situation can be happen, and how to adapt the buffermap for stable multimedia streaming service over a mesh-based overlay network.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129100280","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 : 2018-02-01DOI: 10.23919/ICACT.2018.8323635
Nicolas Bersano, Horacio Sanson
This work focuses on the potential of artificial neural networks to classify biological signals in a healthcare setting, specifically in the estimation of blood pressure from photoplethysmography signal readings obtained via medical devices. This signal is known to have valuable cardiovascular information and has been related to heart rate and blood pressure pulsewave. Among the literature there have been attempts to correlate this signal directly to a single blood pressure value and/or classify it into one of the blood pressure clinical states (e.g. Hypotension, Normal, Pre Hypertension, Stage 1 Hypertension, Stage 2 Hypertension). We propose models based on artificial neural networks that achieve similar performance to those in previous works, without needing engineered nor demographic features. These models are capable of learning how to extract descriptive features from only the raw photoplethysmography signals, and use them for classification into a blood pressure class. Test results are promising and validate the usefulness of artificial neural network architectures for this task.
{"title":"Non-invasive blood pressure estimation from photoplethysmography signals using artificial neural networks","authors":"Nicolas Bersano, Horacio Sanson","doi":"10.23919/ICACT.2018.8323635","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323635","url":null,"abstract":"This work focuses on the potential of artificial neural networks to classify biological signals in a healthcare setting, specifically in the estimation of blood pressure from photoplethysmography signal readings obtained via medical devices. This signal is known to have valuable cardiovascular information and has been related to heart rate and blood pressure pulsewave. Among the literature there have been attempts to correlate this signal directly to a single blood pressure value and/or classify it into one of the blood pressure clinical states (e.g. Hypotension, Normal, Pre Hypertension, Stage 1 Hypertension, Stage 2 Hypertension). We propose models based on artificial neural networks that achieve similar performance to those in previous works, without needing engineered nor demographic features. These models are capable of learning how to extract descriptive features from only the raw photoplethysmography signals, and use them for classification into a blood pressure class. Test results are promising and validate the usefulness of artificial neural network architectures for this task.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"77 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121028935","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 : 2018-02-01DOI: 10.23919/ICACT.2018.8323781
Wuttipan Duangsri, M. Somrobru, N. Sutthisangiam
Co-channel interference cancellation method are investigated for cooperative communication employing a decode-and-forward protocol when the base station is disturbed by the co-channel interference (CCI). In order to solve such interference problem, the beamforming method with the appropriate weight estimation for a smart antenna at the base station will be employed. We can also control the transmitted power at the interfering source, and maintain nearly a full diversity gain compared with the existing decode-and-forward cooperative communication. The network performance can be enhanced by the proposed power adaptive at the interference source by the quality of channel criterion and signal combining method. The maximum ratio combining (MRC) and the cooperative maximum ration combining (C-MRC) are used to combine the received signals arrived at the base station to achieve the minimum probability of error based on the experimental results from simulations. The results show proposed method in C-MRC systems had the lower probability of error than MRC because the effect of three gain factors: the antenna array gain obtained from the beamforming algorithm, the power gain of the proposed power adaptive strategy, and the diversity gain obtained from a signal combining of received signals from the relay.
{"title":"Performance enhancement for co-channel interference cancellation with smart antenna and power adaptive in cooperative communication","authors":"Wuttipan Duangsri, M. Somrobru, N. Sutthisangiam","doi":"10.23919/ICACT.2018.8323781","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323781","url":null,"abstract":"Co-channel interference cancellation method are investigated for cooperative communication employing a decode-and-forward protocol when the base station is disturbed by the co-channel interference (CCI). In order to solve such interference problem, the beamforming method with the appropriate weight estimation for a smart antenna at the base station will be employed. We can also control the transmitted power at the interfering source, and maintain nearly a full diversity gain compared with the existing decode-and-forward cooperative communication. The network performance can be enhanced by the proposed power adaptive at the interference source by the quality of channel criterion and signal combining method. The maximum ratio combining (MRC) and the cooperative maximum ration combining (C-MRC) are used to combine the received signals arrived at the base station to achieve the minimum probability of error based on the experimental results from simulations. The results show proposed method in C-MRC systems had the lower probability of error than MRC because the effect of three gain factors: the antenna array gain obtained from the beamforming algorithm, the power gain of the proposed power adaptive strategy, and the diversity gain obtained from a signal combining of received signals from the relay.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117123460","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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