Nimisha Ghosh, Sanku Kumar Roy, T. Samanta, I. Banerjee
This paper deals with the movement pattern of mobile sinks in Wireless Sensor Network for efficient collection of information by the mobile sinks. We propose a path determination algorithm for the sinks to move in the network and cover the whole network area as much as possible. Multiple mobile sinks will move in their defined path based on the path determination algorithm to collect data from static sensor nodes. The performance of our proposed algorithm is studied based on the metric like energy consumption by the static sensor nodes and the mobile sinks as well as delay and network life time. Furthermore we have compared our algorithm with other existing algorithms and have found that the proposed algorithm gives better result in terms of energy consumption and network lifetime.
{"title":"Path Determination Algorithm of Mobile Sinks for Energy Efficient Data Collection and Optimal Coverage in Wireless Sensor Network","authors":"Nimisha Ghosh, Sanku Kumar Roy, T. Samanta, I. Banerjee","doi":"10.1109/ICIT.2014.35","DOIUrl":"https://doi.org/10.1109/ICIT.2014.35","url":null,"abstract":"This paper deals with the movement pattern of mobile sinks in Wireless Sensor Network for efficient collection of information by the mobile sinks. We propose a path determination algorithm for the sinks to move in the network and cover the whole network area as much as possible. Multiple mobile sinks will move in their defined path based on the path determination algorithm to collect data from static sensor nodes. The performance of our proposed algorithm is studied based on the metric like energy consumption by the static sensor nodes and the mobile sinks as well as delay and network life time. Furthermore we have compared our algorithm with other existing algorithms and have found that the proposed algorithm gives better result in terms of energy consumption and network lifetime.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"35 1","pages":"76-81"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74632406","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}
Janmenjoy Nayak, N. Sahoo, J. R. Swain, T. Dash, H. Behera
Polynomial Neural Network is a self-organizing network whose performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, a training algorithm for Polynomial Neural Network (PNN) based on Genetic Algorithm (GA) has been proposed for classification problems. A performance comparison of the proposed PNN-GA and Back Propagation based PNN (PNN-BP) has also been carried out by considering four popular datasets obtained from UCI machine learning repository. Experimental results show that the proposed PNN-GA outperforms PNN-BP for all the four datasets and thus may be applied as classification model in many real world problems.
{"title":"GA Based Polynomial Neural Network for Data Classification","authors":"Janmenjoy Nayak, N. Sahoo, J. R. Swain, T. Dash, H. Behera","doi":"10.1109/ICIT.2014.55","DOIUrl":"https://doi.org/10.1109/ICIT.2014.55","url":null,"abstract":"Polynomial Neural Network is a self-organizing network whose performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, a training algorithm for Polynomial Neural Network (PNN) based on Genetic Algorithm (GA) has been proposed for classification problems. A performance comparison of the proposed PNN-GA and Back Propagation based PNN (PNN-BP) has also been carried out by considering four popular datasets obtained from UCI machine learning repository. Experimental results show that the proposed PNN-GA outperforms PNN-BP for all the four datasets and thus may be applied as classification model in many real world problems.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"11 1","pages":"234-239"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76801060","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}
A Mobile Ad-Hoc Network is a set of wireless mobile nodes that communes with each other without using any dynamic infrastructure, access point or centralized supervision. In Mobile Ad-hoc network, due to mobility of nodes network topology commutes repeatedly and thus, routing process becomes a challenging task. A selection of routing protocols with varying network circumstances are analyzed and presents performance analysis of AODV, OLSR, ZRP, RAODV, AOMDV, DYMO and DSR Routing protocols in different mobility scenarios based on Random Waypoint mobility model in MANET with pause time. In this paper, an effort has been made to compare seven well known routing protocols AODV, RAODV, AOMDV, OLSR, DSR, DYMO and ZRP by using different performance metrics Packet Delivery Ratio, Average Jitter, Normalized Routing Load, First Packet Receive, Last Packet Receive, Total Packet Receive, Total Bytes Receive and Average End to End delay. The comparison has been done by using simulation tool NS-2.34 which is the main simulator, NAM (Network Animator) and MATLAB which is used for preparing the graphs from the trace files.
{"title":"Scenario-Based Performance Evaluation of Proactive, Reactive and Hybrid Routing Protocols in MANET Using Random Waypoint Model","authors":"B. S. Gouda, Debasis Patro, R. Shial","doi":"10.1109/ICIT.2014.40","DOIUrl":"https://doi.org/10.1109/ICIT.2014.40","url":null,"abstract":"A Mobile Ad-Hoc Network is a set of wireless mobile nodes that communes with each other without using any dynamic infrastructure, access point or centralized supervision. In Mobile Ad-hoc network, due to mobility of nodes network topology commutes repeatedly and thus, routing process becomes a challenging task. A selection of routing protocols with varying network circumstances are analyzed and presents performance analysis of AODV, OLSR, ZRP, RAODV, AOMDV, DYMO and DSR Routing protocols in different mobility scenarios based on Random Waypoint mobility model in MANET with pause time. In this paper, an effort has been made to compare seven well known routing protocols AODV, RAODV, AOMDV, OLSR, DSR, DYMO and ZRP by using different performance metrics Packet Delivery Ratio, Average Jitter, Normalized Routing Load, First Packet Receive, Last Packet Receive, Total Packet Receive, Total Bytes Receive and Average End to End delay. The comparison has been done by using simulation tool NS-2.34 which is the main simulator, NAM (Network Animator) and MATLAB which is used for preparing the graphs from the trace files.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"68 1","pages":"47-52"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79176065","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}
In this era of web applications, web shopping portals have become increasingly popular as they allow customers to buy products from home. These websites often request the customers to rate their products and write reviews, which helps the manufacturers to improve the quality of their products and other customers in choosing the right product or service. The rapid increase in the popularity of e-commerce has increased the number of customers in these type of web-shopping portals, leading to an enormous number of reviews for each product or service. Each of these reviews may describe the different features of the products. Hence, the customer has to go through a large number of reviews before s/he can arrive to a fully informed decision on whether to buy the product or not. In this paper, we describe a system, which automatically extracts the product features from the reviews and determines if they have been expressed in a positive or a negative way by the reviewers. The proposed algorithm works in two steps, viz feature extraction and polarity classification. We use association rule mining to identify the most characteristic features of a product. In the second step we develop a supervised machine learning algorithm based polarity classifier that determines the sentiment of the review sentences with respect to the prominent features. Our experiments on the benchmark reviews of five popular products show that our classifier is highly efficient and achieves an accuracy of 79.67%. We did not make use of any domain specific resources and tools, and thus our classifier is domain-independent, and can be used for the similar tasks in other domains.
{"title":"Feature Extraction and Opinion Mining in Online Product Reviews","authors":"Siddharth Aravindan, Asif Ekbal","doi":"10.1109/ICIT.2014.72","DOIUrl":"https://doi.org/10.1109/ICIT.2014.72","url":null,"abstract":"In this era of web applications, web shopping portals have become increasingly popular as they allow customers to buy products from home. These websites often request the customers to rate their products and write reviews, which helps the manufacturers to improve the quality of their products and other customers in choosing the right product or service. The rapid increase in the popularity of e-commerce has increased the number of customers in these type of web-shopping portals, leading to an enormous number of reviews for each product or service. Each of these reviews may describe the different features of the products. Hence, the customer has to go through a large number of reviews before s/he can arrive to a fully informed decision on whether to buy the product or not. In this paper, we describe a system, which automatically extracts the product features from the reviews and determines if they have been expressed in a positive or a negative way by the reviewers. The proposed algorithm works in two steps, viz feature extraction and polarity classification. We use association rule mining to identify the most characteristic features of a product. In the second step we develop a supervised machine learning algorithm based polarity classifier that determines the sentiment of the review sentences with respect to the prominent features. Our experiments on the benchmark reviews of five popular products show that our classifier is highly efficient and achieves an accuracy of 79.67%. We did not make use of any domain specific resources and tools, and thus our classifier is domain-independent, and can be used for the similar tasks in other domains.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"6 1","pages":"94-99"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79464727","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}
Jalal Syed, Ahmad, V. Reddy, J. Nehru, P. Radha, Krishna
The communication quality in multi-hop networks entirely depends on the selection of a multi-hop path from source to destination among the potential candidate paths. Finding a path with good throughput in multi hop MANETS (Mobile Ad Hoc Networks) is a critical job of QoS routing. Existing approaches finds the optimal path based on the best data rates among all links. However, other measures such as energy, delay and traffic intensity also impact in determining the optimal path, especially for multimedia traffic. In this paper, we present a model for optimal routing by considering the network route parameters namely distance, bandwidth, traffic intensity, queuing delay and energy utilization of the link. We use greedy approach for selecting a path in multi hop network. Our approach is useful in analyzing the candidate route weights and selects the optimal path from source to destination. In addition to finding best route, our protocol also ranks the candidate paths that enable alternative paths when there is a failure in the current path.
{"title":"An Improved QoS and Ranking Paths for Multimedia Traffic over MANETs","authors":"Jalal Syed, Ahmad, V. Reddy, J. Nehru, P. Radha, Krishna","doi":"10.1109/ICIT.2014.11","DOIUrl":"https://doi.org/10.1109/ICIT.2014.11","url":null,"abstract":"The communication quality in multi-hop networks entirely depends on the selection of a multi-hop path from source to destination among the potential candidate paths. Finding a path with good throughput in multi hop MANETS (Mobile Ad Hoc Networks) is a critical job of QoS routing. Existing approaches finds the optimal path based on the best data rates among all links. However, other measures such as energy, delay and traffic intensity also impact in determining the optimal path, especially for multimedia traffic. In this paper, we present a model for optimal routing by considering the network route parameters namely distance, bandwidth, traffic intensity, queuing delay and energy utilization of the link. We use greedy approach for selecting a path in multi hop network. Our approach is useful in analyzing the candidate route weights and selects the optimal path from source to destination. In addition to finding best route, our protocol also ranks the candidate paths that enable alternative paths when there is a failure in the current path.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"1 1","pages":"41-46"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80748504","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}
Since four decades, a sincere concern has aroused among managerial, professional, towards the satisfaction of teaching-learning objective in Academia. Huge span of time has already been spent revealing student's profile patterns using predictive modeling methods, however, very little effort is put up in identifying the causative features responsible for varied students' performances followed by decisive and remedial actions upon them. Data mining techniques can be used to understand the pitfalls arising in the teaching-learning professions. In machine learning feature selection or Attribute analysis is often treated as a preprocessing step. This paper proposes a framework for identify the most contributed attributes towards academia, for the performance of second year students of computer science and application course. An appropriate supervised machine learning model is applied upon our set of inherent attributes in order to arrive (NBC) at predictive scenarios for given pattern of external attributes. Thus, the model is able to extract the fitness procedure sequences of external effort put up by each student who is predicted in 'at-risk' category. The end-user can make use of these precedence relations to identify and resolve the most unfit governing factor for upgrading students' appraisals.
{"title":"Feature Extraction Model to Identify At -- Risk Level of Students in Academia","authors":"Mamta Singh, J. Singh, Arpana Rawal","doi":"10.1109/ICIT.2014.68","DOIUrl":"https://doi.org/10.1109/ICIT.2014.68","url":null,"abstract":"Since four decades, a sincere concern has aroused among managerial, professional, towards the satisfaction of teaching-learning objective in Academia. Huge span of time has already been spent revealing student's profile patterns using predictive modeling methods, however, very little effort is put up in identifying the causative features responsible for varied students' performances followed by decisive and remedial actions upon them. Data mining techniques can be used to understand the pitfalls arising in the teaching-learning professions. In machine learning feature selection or Attribute analysis is often treated as a preprocessing step. This paper proposes a framework for identify the most contributed attributes towards academia, for the performance of second year students of computer science and application course. An appropriate supervised machine learning model is applied upon our set of inherent attributes in order to arrive (NBC) at predictive scenarios for given pattern of external attributes. Thus, the model is able to extract the fitness procedure sequences of external effort put up by each student who is predicted in 'at-risk' category. The end-user can make use of these precedence relations to identify and resolve the most unfit governing factor for upgrading students' appraisals.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"31 1","pages":"221-227"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81651311","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}
Online frequency assignment for wireless cellular networks is one of the important research areas in recent time, where the geographical coverage area is divided into regular hexagonal regions called cells. Sequence of requests arrives over time to the cells that are headed by the base stations. Each of the requests is either a new call or a drop-call which is served by the base station by assigning the frequencies or releasing the frequencies respectively. In order to minimize the span of frequencies use to serve all the requests for new calls originating from same or neighboring cells, reassignment of the frequency of the dropped-call is done to an already existing call that uses the highest frequency. For χ-colorable networks, which are the generalization of the (3-colorable) cellular networks, we have suggested an efficient online algorithm for frequency reassignment, minimizing the span of frequency usages. The competitive ratio of the proposed online algorithm is (χ+1)/3, which is sharper than the competitive ratio (χ+1)/2 of existing similar problem without allowing reassignment of frequency. The optimality of the new algorithm is verified by finding the absolute lower and upper bounds of its competitive ratio for 3-colrable cellular network as a particular case when χ = 3.
{"title":"Online Frequency Reassignment for New and Drop Calls in Wireless Cellular Networks","authors":"Narayan Patra, B. Ray, S. P. Mohanty","doi":"10.1109/ICIT.2014.47","DOIUrl":"https://doi.org/10.1109/ICIT.2014.47","url":null,"abstract":"Online frequency assignment for wireless cellular networks is one of the important research areas in recent time, where the geographical coverage area is divided into regular hexagonal regions called cells. Sequence of requests arrives over time to the cells that are headed by the base stations. Each of the requests is either a new call or a drop-call which is served by the base station by assigning the frequencies or releasing the frequencies respectively. In order to minimize the span of frequencies use to serve all the requests for new calls originating from same or neighboring cells, reassignment of the frequency of the dropped-call is done to an already existing call that uses the highest frequency. For χ-colorable networks, which are the generalization of the (3-colorable) cellular networks, we have suggested an efficient online algorithm for frequency reassignment, minimizing the span of frequency usages. The competitive ratio of the proposed online algorithm is (χ+1)/3, which is sharper than the competitive ratio (χ+1)/2 of existing similar problem without allowing reassignment of frequency. The optimality of the new algorithm is verified by finding the absolute lower and upper bounds of its competitive ratio for 3-colrable cellular network as a particular case when χ = 3.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"34 1","pages":"137-141"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83988385","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 : 2014-12-01DOI: 10.1109/ICCITECHN.2014.7073143
T. Rahman, Mohammad Reduanul Haque, L. J. Rozario, Mohammad Shorif Uddin
Noise can be easily induced in images during acquisition and transmission. Therefore, it is a basic requirement to remove noise from an image while keeping its features intact for better understanding and recognition. Gaussian and impulse are two very common types of noise. Tremendous research initiatives are being taken for removing these noises. Previously, we developed a fuzzy filter that effectively removes high density impulse noise in images. In this paper, we proposed a modified fuzzy filter for reduction of Gaussian noise. Experimental result confirms the superiority of the proposed method compared to the conventional filters in terms of both denoising and details preservation.
{"title":"Gaussian noise reduction in digital images using a modified fuzzy filter","authors":"T. Rahman, Mohammad Reduanul Haque, L. J. Rozario, Mohammad Shorif Uddin","doi":"10.1109/ICCITECHN.2014.7073143","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2014.7073143","url":null,"abstract":"Noise can be easily induced in images during acquisition and transmission. Therefore, it is a basic requirement to remove noise from an image while keeping its features intact for better understanding and recognition. Gaussian and impulse are two very common types of noise. Tremendous research initiatives are being taken for removing these noises. Previously, we developed a fuzzy filter that effectively removes high density impulse noise in images. In this paper, we proposed a modified fuzzy filter for reduction of Gaussian noise. Experimental result confirms the superiority of the proposed method compared to the conventional filters in terms of both denoising and details preservation.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"2 1","pages":"217-222"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73900891","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 : 2014-12-01DOI: 10.1109/ICCITECHN.2014.7073071
N. Z. Zenia, Fariha Afsana, M. S. Kaiser, S. A. Mamun
In this paper, we present the performance evaluation of coded wireless ad-hoc network for emergency response communication. Due to the limited transmission range, a number of intermediate relaying nodes may exist between source and destination and these convey source transmission using hybrid Amplify-and-forward (AF)/Decode-and-forward (DF) protocol. All nodes contain single antenna and OFDM based Low Density Parity Check (LDPC) coded transmission is considered over Rician fading channel. The closed form bit-error-rate (BER) expression has been deduced for the proposed system. Performance evaluation reveals that BER of the LDPC coded ad-hoc network is better than that of non-coded ad-hoc network.
{"title":"Performance analysis of LDPC coded wireless ad-hoc network for emergency response communications","authors":"N. Z. Zenia, Fariha Afsana, M. S. Kaiser, S. A. Mamun","doi":"10.1109/ICCITECHN.2014.7073071","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2014.7073071","url":null,"abstract":"In this paper, we present the performance evaluation of coded wireless ad-hoc network for emergency response communication. Due to the limited transmission range, a number of intermediate relaying nodes may exist between source and destination and these convey source transmission using hybrid Amplify-and-forward (AF)/Decode-and-forward (DF) protocol. All nodes contain single antenna and OFDM based Low Density Parity Check (LDPC) coded transmission is considered over Rician fading channel. The closed form bit-error-rate (BER) expression has been deduced for the proposed system. Performance evaluation reveals that BER of the LDPC coded ad-hoc network is better than that of non-coded ad-hoc network.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"20 1","pages":"446-451"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84538761","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 : 2014-12-01DOI: 10.1109/ICCITECHN.2014.7073080
Tahsina Hashem, M. Islam
In modern wireless communication, multiple-input multiple-output (MIMO) system plays an important role as it improves channel capacity, range and reliability without requiring any additional bandwidth or transmit power. This research presents a detailed analysis of capacity performance of MIMO systems under four fading cases i.e. Gaussian, Weibull, Rayleigh and Nakagami-m fading in the low signal-to-noise ratio (SNR) regime. We first derive analytical expressions for the expectation of the trace of the complex channel matrix. Then we measure the low-SNR performance of MIMO system under four fading conditions with respect to minimum normalized energy per information bit and wideband slope. Also a comparative analysis has been performed between the channel capacity of spatial-multiplexing (SM) MIMO and Orthogonal Space Time block coded (OSTBC) MIMO system. Simulation results show that performance of the system depends on different criteria of MIMO fading channels. According to the capacity performance of MIMO system, four fading channels can be ordered as Gaussian, Nakagami-m, Rayleigh and Weibull fading channels respectively.
{"title":"Performance analysis of MIMO link under fading channels","authors":"Tahsina Hashem, M. Islam","doi":"10.1109/ICCITECHN.2014.7073080","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2014.7073080","url":null,"abstract":"In modern wireless communication, multiple-input multiple-output (MIMO) system plays an important role as it improves channel capacity, range and reliability without requiring any additional bandwidth or transmit power. This research presents a detailed analysis of capacity performance of MIMO systems under four fading cases i.e. Gaussian, Weibull, Rayleigh and Nakagami-m fading in the low signal-to-noise ratio (SNR) regime. We first derive analytical expressions for the expectation of the trace of the complex channel matrix. Then we measure the low-SNR performance of MIMO system under four fading conditions with respect to minimum normalized energy per information bit and wideband slope. Also a comparative analysis has been performed between the channel capacity of spatial-multiplexing (SM) MIMO and Orthogonal Space Time block coded (OSTBC) MIMO system. Simulation results show that performance of the system depends on different criteria of MIMO fading channels. According to the capacity performance of MIMO system, four fading channels can be ordered as Gaussian, Nakagami-m, Rayleigh and Weibull fading channels respectively.","PeriodicalId":6486,"journal":{"name":"2014 17th International Conference on Computer and Information Technology (ICCIT)","volume":"58 6 1","pages":"498-503"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84051570","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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