Pub Date : 2021-11-11DOI: 10.1109/cits52676.2021.9618426
Kamil Sert, C. F. Bazlamaçci
String matching is about finding all occurrences of a string within a given text. String matching algorithms have important roles in various real world areas such as web and security applications. In this work, we are interested in solving regular expression matching hence a more general form of string matching problem targeting especially the field of network intrusion detection systems (NIDS). In our work, we enhance a non-deterministic finite automata (NFA) based method on FPGA considerably. We propose to use a matching structure that processes two consecutive characters instead of one in order to yield better memory utilization and provide a novel mapping of this new architecture onto FPGA. The amount of digital circuitry needed to represent the NFA is reduced due to having less number of states and less number of LUTs in the devised 2-character regex matching process. An evaluation study is performed using the well-known Snort rule set and a sizable performance improvement is demonstrated.
{"title":"NFA Based Regular Expression Matching on FPGA","authors":"Kamil Sert, C. F. Bazlamaçci","doi":"10.1109/cits52676.2021.9618426","DOIUrl":"https://doi.org/10.1109/cits52676.2021.9618426","url":null,"abstract":"String matching is about finding all occurrences of a string within a given text. String matching algorithms have important roles in various real world areas such as web and security applications. In this work, we are interested in solving regular expression matching hence a more general form of string matching problem targeting especially the field of network intrusion detection systems (NIDS). In our work, we enhance a non-deterministic finite automata (NFA) based method on FPGA considerably. We propose to use a matching structure that processes two consecutive characters instead of one in order to yield better memory utilization and provide a novel mapping of this new architecture onto FPGA. The amount of digital circuitry needed to represent the NFA is reduced due to having less number of states and less number of LUTs in the devised 2-character regex matching process. An evaluation study is performed using the well-known Snort rule set and a sizable performance improvement is demonstrated.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126307220","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 : 2021-11-11DOI: 10.1109/cits52676.2021.9618157
Jagdeep Singh, M. Obaidat, S. K. Dhurandher
As a key enabling technology for pervasive computing, Opportunity Network has recently attracted a great deal of research work in machine learning domain. In this paper, we present a new opportunistic network routing strategy that tries to send messages to a destination location area rather than a single node. To improve routing in Opportunistic networks, we apply cascade learning (a type of integration-based machine learning). We demonstrate that the proposed Cascade Learning based Routing Protocol (CLRP), outperforms existing machine learning-based protocols LOOP and MLProph on various performance metrics, including delivery probability and average latency, using real data mobility traces in simulation.
{"title":"Location based Routing in Opportunistic Networks using Cascade Learning","authors":"Jagdeep Singh, M. Obaidat, S. K. Dhurandher","doi":"10.1109/cits52676.2021.9618157","DOIUrl":"https://doi.org/10.1109/cits52676.2021.9618157","url":null,"abstract":"As a key enabling technology for pervasive computing, Opportunity Network has recently attracted a great deal of research work in machine learning domain. In this paper, we present a new opportunistic network routing strategy that tries to send messages to a destination location area rather than a single node. To improve routing in Opportunistic networks, we apply cascade learning (a type of integration-based machine learning). We demonstrate that the proposed Cascade Learning based Routing Protocol (CLRP), outperforms existing machine learning-based protocols LOOP and MLProph on various performance metrics, including delivery probability and average latency, using real data mobility traces in simulation.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125777467","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 : 2021-11-11DOI: 10.1109/cits52676.2021.9618475
Taissir Y. Elganimi, Nura K. Daghari, Khaled Maaiuf Rabie
Reconfigurable intelligent surface (RIS)-assisted multiuser millimeter-wave (mmWave) wireless systems have emerged as cost-effective and energy-efficient wireless solutions for the future 6G communications. In this paper, RIS-assisted energy-efficient hybrid precoding schemes are introduced as a promising technology that can achieve a transmission in an intelligent way. In addition, an RIS-assisted machine learning (ML) inspired energy-efficient hybrid precoding scheme that requires low-cost and energy-efficient switches and inverters is considered, where the adaptive cross entropy (ACE) optimization algorithm is employed to find the corresponding optimal precoding weights. Besides, imperfect channel state information (CSI) in both the source-to-RIS channel and RIS-to-destination channel links is assumed to be known. Extensive simulations have been conducted to evaluate the effect of imperfect CSI on the achievable sum-rate and the energy efficiency of the proposed RIS-assisted hybrid precoding schemes. Additionally, the performance of the proposed hybrid precoders is compared to that of the conventional hybrid precoding schemes. The results reveal that the proposed hybrid precoding architectures outperform the conventional schemes with large number of reflecting elements, and the performance is significantly degraded in the presence of imperfect CSI.
{"title":"Impact of Channel Imperfection on the Performance of RIS-Assisted Energy-Efficient Hybrid Precoding","authors":"Taissir Y. Elganimi, Nura K. Daghari, Khaled Maaiuf Rabie","doi":"10.1109/cits52676.2021.9618475","DOIUrl":"https://doi.org/10.1109/cits52676.2021.9618475","url":null,"abstract":"Reconfigurable intelligent surface (RIS)-assisted multiuser millimeter-wave (mmWave) wireless systems have emerged as cost-effective and energy-efficient wireless solutions for the future 6G communications. In this paper, RIS-assisted energy-efficient hybrid precoding schemes are introduced as a promising technology that can achieve a transmission in an intelligent way. In addition, an RIS-assisted machine learning (ML) inspired energy-efficient hybrid precoding scheme that requires low-cost and energy-efficient switches and inverters is considered, where the adaptive cross entropy (ACE) optimization algorithm is employed to find the corresponding optimal precoding weights. Besides, imperfect channel state information (CSI) in both the source-to-RIS channel and RIS-to-destination channel links is assumed to be known. Extensive simulations have been conducted to evaluate the effect of imperfect CSI on the achievable sum-rate and the energy efficiency of the proposed RIS-assisted hybrid precoding schemes. Additionally, the performance of the proposed hybrid precoders is compared to that of the conventional hybrid precoding schemes. The results reveal that the proposed hybrid precoding architectures outperform the conventional schemes with large number of reflecting elements, and the performance is significantly degraded in the presence of imperfect CSI.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122470576","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 : 2021-11-11DOI: 10.1109/cits52676.2021.9618277
M. Obaidat, S. Dwivedi, Ruhul Amin, K. Hsiao
The upcoming industry is continuously changing, and the current systems and technologies are not suitable in their present form. They need to upgrade to solve the complex problems that are faced by the different applications. The healthcare industry is one of them. In the current healthcare industries, the patient’s information is stored in the central cloud servers, and the third party (TP) is required to share these details among the service providers. As a result, sharing information without adopting TP in a distributed manner is a challenging task. The distributed ledger technology blockchain has the potential to resolve the problems mentioned above. The blockchain provides the immutability, transparency, and traceability of records where the records are distributed among the many nodes. This article first presents the various problems of the current electronic medical record (EMR) system, discusses the importance of blockchain in EMR systems, and finally summarizes the existing approaches with their future scopes. Based on it, this paper proposed a novel architecture for a blockchain-enabled secure sharing of health records. In addition to it, possible research directions with the relevant security attacks for blockchain systems are also highlighted in the paper.
{"title":"Blockchain Enabled Electronics Medical System Proposed Framework with Research Directions","authors":"M. Obaidat, S. Dwivedi, Ruhul Amin, K. Hsiao","doi":"10.1109/cits52676.2021.9618277","DOIUrl":"https://doi.org/10.1109/cits52676.2021.9618277","url":null,"abstract":"The upcoming industry is continuously changing, and the current systems and technologies are not suitable in their present form. They need to upgrade to solve the complex problems that are faced by the different applications. The healthcare industry is one of them. In the current healthcare industries, the patient’s information is stored in the central cloud servers, and the third party (TP) is required to share these details among the service providers. As a result, sharing information without adopting TP in a distributed manner is a challenging task. The distributed ledger technology blockchain has the potential to resolve the problems mentioned above. The blockchain provides the immutability, transparency, and traceability of records where the records are distributed among the many nodes. This article first presents the various problems of the current electronic medical record (EMR) system, discusses the importance of blockchain in EMR systems, and finally summarizes the existing approaches with their future scopes. Based on it, this paper proposed a novel architecture for a blockchain-enabled secure sharing of health records. In addition to it, possible research directions with the relevant security attacks for blockchain systems are also highlighted in the paper.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122476074","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 : 2021-11-11DOI: 10.1109/cits52676.2021.9618301
Savira Rohwinasakti, Budhi Irawan, C. Setianingsih
In 2018, the everyday client of online transportation administrations is up to 8 million clients/day in the Southeast Asian locale. Indonesia is the biggest country in utilizing the administrations contrasted with other Southeast Asian nations. The clients present their reactions to the administrations given by online transportation specialist co-ops through different media through the Instagram remarks segment. The responses submitted have additionally differed, so they likewise contained opinions that communicated their sentiments about specific administrations. In this manner, an opinion investigation framework was made utilizing the K-Nearest Neighbor strategy to decide clients' reactions to the administrations given, the degree of fulfillment, and assist clients with picking the best administrations. This examination shows that the proposed method can characterize client assessment with 94.4% accuracy, and for recall and precision, the F1 Score has the same result, 94.4%. This infers that from assessment results, the proposed calculation performs well to dissect opinion consequently.
{"title":"Sentiment Analysis on Online Transportation Service Products Using K-Nearest Neighbor Method","authors":"Savira Rohwinasakti, Budhi Irawan, C. Setianingsih","doi":"10.1109/cits52676.2021.9618301","DOIUrl":"https://doi.org/10.1109/cits52676.2021.9618301","url":null,"abstract":"In 2018, the everyday client of online transportation administrations is up to 8 million clients/day in the Southeast Asian locale. Indonesia is the biggest country in utilizing the administrations contrasted with other Southeast Asian nations. The clients present their reactions to the administrations given by online transportation specialist co-ops through different media through the Instagram remarks segment. The responses submitted have additionally differed, so they likewise contained opinions that communicated their sentiments about specific administrations. In this manner, an opinion investigation framework was made utilizing the K-Nearest Neighbor strategy to decide clients' reactions to the administrations given, the degree of fulfillment, and assist clients with picking the best administrations. This examination shows that the proposed method can characterize client assessment with 94.4% accuracy, and for recall and precision, the F1 Score has the same result, 94.4%. This infers that from assessment results, the proposed calculation performs well to dissect opinion consequently.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131709991","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 : 2021-11-11DOI: 10.1109/CITS52676.2021.9618507
Clemens Klöck
In this document a new FIR filter design algorithm is proposed. The algorithm gives the designer a set of filters which differ in the approximation of the ideal filter characteristic and the number of none-zero elements. The designer can choose a filter based on proposed filter selection criteria which filter is suitable for the tradeoff between approximation as well as processing power and storage capacity.
{"title":"FIR Filter Design Method Based on LASSO to Adjust the Number of Non-zero Coefficients","authors":"Clemens Klöck","doi":"10.1109/CITS52676.2021.9618507","DOIUrl":"https://doi.org/10.1109/CITS52676.2021.9618507","url":null,"abstract":"In this document a new FIR filter design algorithm is proposed. The algorithm gives the designer a set of filters which differ in the approximation of the ideal filter characteristic and the number of none-zero elements. The designer can choose a filter based on proposed filter selection criteria which filter is suitable for the tradeoff between approximation as well as processing power and storage capacity.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116948061","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 : 2021-11-11DOI: 10.1109/cits52676.2021.9618231
Alper Saylam, Nur Kelesoglu, Rifat Orhan Çikmazel, Mert Nakıp, V. Rodoplu
We develop an algorithm called "Dynamic Positioning Interval based on Reciprocal Forecasting Error (DPIRFE)" for energy-efficient mobile Internet of Things (IoT) Indoor Positioning (IP). In contrast with existing IP algorithms, DPIRFE forecasts the future trajectory of a mobile IoT device by using machine learning and dynamically adjusts the positioning interval based on the reciprocal instantaneous forecasting error, thereby dynamically trading off transmit energy consumption against forecasting error. We compare the performance of DPIRFE with respect to the total transmit energy consumption and the average forecasting error against Constant Positioning Interval (CPI) and Positioning Interval based on Displacement (PID) algorithms. Our results show that DPI-RFE significantly outperforms both of these benchmark algorithms with respect to transmit energy consumption while achieving a competitive average forecasting error performance. These results open the way to the design of machine learning based trajectory forecasting algorithms that can be utilized for energy-efficient positioning in next-generation wireless networks.
{"title":"Dynamic Positioning Interval Based On Reciprocal Forecasting Error (DPI-RFE) Algorithm for Energy-Efficient Mobile IoT Indoor Positioning","authors":"Alper Saylam, Nur Kelesoglu, Rifat Orhan Çikmazel, Mert Nakıp, V. Rodoplu","doi":"10.1109/cits52676.2021.9618231","DOIUrl":"https://doi.org/10.1109/cits52676.2021.9618231","url":null,"abstract":"We develop an algorithm called \"Dynamic Positioning Interval based on Reciprocal Forecasting Error (DPIRFE)\" for energy-efficient mobile Internet of Things (IoT) Indoor Positioning (IP). In contrast with existing IP algorithms, DPIRFE forecasts the future trajectory of a mobile IoT device by using machine learning and dynamically adjusts the positioning interval based on the reciprocal instantaneous forecasting error, thereby dynamically trading off transmit energy consumption against forecasting error. We compare the performance of DPIRFE with respect to the total transmit energy consumption and the average forecasting error against Constant Positioning Interval (CPI) and Positioning Interval based on Displacement (PID) algorithms. Our results show that DPI-RFE significantly outperforms both of these benchmark algorithms with respect to transmit energy consumption while achieving a competitive average forecasting error performance. These results open the way to the design of machine learning based trajectory forecasting algorithms that can be utilized for energy-efficient positioning in next-generation wireless networks.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132865487","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 : 2021-11-11DOI: 10.1109/cits52676.2021.9618005
Dhairya Jadav, M. Obaidat, S. Tanwar, Rajesh Gupta, K. Hsiao
Blockchain is a prevalent technology whose applications are aimed towards security, privacy, traceability and trust. One such application is autonomous vehicles (AVs). The biggest concern of AVs is their safety. A malicious AV can cause accidents that may be life-threatening. We have proposed a blockchain and ensemble learning-based system to classify the vehicles as malicious to address the aforementioned safety issue. Smart contracts for AVs transaction verification have been designed to count the number of malicious activities performed by any AV. Finally, results show that the proposed model achieved the goal of this paper with an accuracy of 97.5 %.
{"title":"Amalgamation of Blockchain and AI to Classify Malicious Behavior of Autonomous Vehicles","authors":"Dhairya Jadav, M. Obaidat, S. Tanwar, Rajesh Gupta, K. Hsiao","doi":"10.1109/cits52676.2021.9618005","DOIUrl":"https://doi.org/10.1109/cits52676.2021.9618005","url":null,"abstract":"Blockchain is a prevalent technology whose applications are aimed towards security, privacy, traceability and trust. One such application is autonomous vehicles (AVs). The biggest concern of AVs is their safety. A malicious AV can cause accidents that may be life-threatening. We have proposed a blockchain and ensemble learning-based system to classify the vehicles as malicious to address the aforementioned safety issue. Smart contracts for AVs transaction verification have been designed to count the number of malicious activities performed by any AV. Finally, results show that the proposed model achieved the goal of this paper with an accuracy of 97.5 %.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130732920","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 : 2021-11-11DOI: 10.1109/cits52676.2021.9618520
T. Zhou, Shiru Gao, Yuanhao Mei, Ling Wang
Emotion recognition plays an important role in the fields of medical care, education, services, and public safety. In the video, the emotion could be recognized through facial expressions and body postures. In this paper, we proposed the ER-FLS (Emotion Recognition based on Facial Landmark and Skeleton) Model, which could recognize emotions through the combination of the skeleton and facial landmarks. The model has a lightweight network structure and could focus on the key areas of face and skeleton landmarks with an attention mechanism. By calculating the similarity between global and local features, and update the weights, the recognition accuracy could be enhanced. The experimental analysis proved that the ER-FLS Model achieves 90.63% accuracy of emotional recognition.
{"title":"Facial Expressions and Body Postures Emotion Recognition based on Convolutional Attention Network","authors":"T. Zhou, Shiru Gao, Yuanhao Mei, Ling Wang","doi":"10.1109/cits52676.2021.9618520","DOIUrl":"https://doi.org/10.1109/cits52676.2021.9618520","url":null,"abstract":"Emotion recognition plays an important role in the fields of medical care, education, services, and public safety. In the video, the emotion could be recognized through facial expressions and body postures. In this paper, we proposed the ER-FLS (Emotion Recognition based on Facial Landmark and Skeleton) Model, which could recognize emotions through the combination of the skeleton and facial landmarks. The model has a lightweight network structure and could focus on the key areas of face and skeleton landmarks with an attention mechanism. By calculating the similarity between global and local features, and update the weights, the recognition accuracy could be enhanced. The experimental analysis proved that the ER-FLS Model achieves 90.63% accuracy of emotional recognition.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126864462","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 : 2021-11-11DOI: 10.1109/cits52676.2021.9618360
Subhankar Ghosh, M. Obaidat, D. De, K. Hsiao
The number of wireless network devices has grown exponentially over the few last decades. Properly allocating the right spectrum of these large number of devices is one of the biggest challenges for future networks. In this article, we have described the method of spectrum allocation based on Stackelberg game and coalition formation game. The Stackelberg game is used to assign the spectrum to devices connected with small cell base station (SBS), and the coalition formation game is used to allocate the spectrum between device-to-device (D2D) communication devices. Two utility functions have been proposed and through these functions the network operator assigns the required spectrum to the devices. In SCHOOL, we have calculated the signal to interference plus noise ratio (SINR) and spectral efficiency (SE) of the network and compared it with the previous networks. The proposed SCHOOL has generated ~ 2% - 8% more SINR than existing network.
无线网络设备的数量在过去几十年里呈指数级增长。如何正确分配这些大量设备的频谱是未来网络面临的最大挑战之一。在本文中，我们描述了基于Stackelberg博弈和联盟形成博弈的频谱分配方法。采用Stackelberg博弈对连接SBS (small cell base station)的设备分配频谱，采用联盟形成博弈对D2D (device-to-device)通信设备分配频谱。提出了两个实用函数，通过这些函数，网络运营商将所需的频谱分配给设备。在SCHOOL中，我们计算了网络的信噪比(SINR)和频谱效率(SE)，并与之前的网络进行了比较。拟议的学校比现有网络产生约2% - 8%的信噪比。
{"title":"SCHOOL: Spectrum Allocation for D2D Communication Enabled HetNet using Stackelberg and Coalition Formation Game","authors":"Subhankar Ghosh, M. Obaidat, D. De, K. Hsiao","doi":"10.1109/cits52676.2021.9618360","DOIUrl":"https://doi.org/10.1109/cits52676.2021.9618360","url":null,"abstract":"The number of wireless network devices has grown exponentially over the few last decades. Properly allocating the right spectrum of these large number of devices is one of the biggest challenges for future networks. In this article, we have described the method of spectrum allocation based on Stackelberg game and coalition formation game. The Stackelberg game is used to assign the spectrum to devices connected with small cell base station (SBS), and the coalition formation game is used to allocate the spectrum between device-to-device (D2D) communication devices. Two utility functions have been proposed and through these functions the network operator assigns the required spectrum to the devices. In SCHOOL, we have calculated the signal to interference plus noise ratio (SINR) and spectral efficiency (SE) of the network and compared it with the previous networks. The proposed SCHOOL has generated ~ 2% - 8% more SINR than existing network.","PeriodicalId":211570,"journal":{"name":"2021 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125375323","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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