Pub Date : 2017-03-01DOI: 10.1109/ICSCN.2017.8085701
Karthik N, V. S. Ananthanarayana
A wireless sensor network (WSN) is a conglomeration of scattered self organized sensor nodes to agreeably monitor the physical and surrounding conditions. These sensor nodes are equipped with limited resources such as memory, processing capability, battery power and transceiver for monitoring, processing and communicating the observed phenomena to make critical decisions with respect to collected data. Evaluating the trustworthiness of data is a primary preprocessing process of event detection in WSN. The trustworthy data which is free from data fault, inaccuracy and inconsistency is used to identify the interesting events and critical decision making in WSN. In this paper, we present our current work on data trust model that focuses on data fault detection, data reconstruction, data quality estimation for reliable event detection in WSN. The aim of this paper is to propose a novel data trust model for harsh environment of WSN to identify the events and strange environmental data behavior. This proposed framework combines different data processing methods through data correlation techniques to mitigate the data security risks of pervasive environments.
{"title":"Data trust model for event detection in wireless sensor networks using data correlation techniques","authors":"Karthik N, V. S. Ananthanarayana","doi":"10.1109/ICSCN.2017.8085701","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085701","url":null,"abstract":"A wireless sensor network (WSN) is a conglomeration of scattered self organized sensor nodes to agreeably monitor the physical and surrounding conditions. These sensor nodes are equipped with limited resources such as memory, processing capability, battery power and transceiver for monitoring, processing and communicating the observed phenomena to make critical decisions with respect to collected data. Evaluating the trustworthiness of data is a primary preprocessing process of event detection in WSN. The trustworthy data which is free from data fault, inaccuracy and inconsistency is used to identify the interesting events and critical decision making in WSN. In this paper, we present our current work on data trust model that focuses on data fault detection, data reconstruction, data quality estimation for reliable event detection in WSN. The aim of this paper is to propose a novel data trust model for harsh environment of WSN to identify the events and strange environmental data behavior. This proposed framework combines different data processing methods through data correlation techniques to mitigate the data security risks of pervasive environments.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"407 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127983345","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085648
J JENCY RUBIA, G. Kumar
The vital element of the DSP processor is Multiplier unit. The main objectives of the DSP processor are speed, power, delay and area. These goals have been realized with fixed-width multiplier whose output bits equal to input bits. The fixed-width multiplier implemented DSP processors can be applied for audio signal processing, video signal processing, VLSI signal processing, speech recognition, digital communication, medical imaging, MRI, MP3 and so on. Many researchers are optimizing, the performance of the multiplication process. In this review paper, the technologies to achieve the objectives of the DSP processor have been studied. And also the most recent developments in the multiplier circuit have been discussed. In this paper, first, the brief background of the fixed-width multiplier is outlined. Then, several multiplier architectures proposed for MAC (multiplier-accumulator) presented, narrating their functioning principles and key features. To provide a perception into future research directions, open research issues are discussed at the completion of this paper.
{"title":"A survey paper on modern technologies in fixed-width multiplier","authors":"J JENCY RUBIA, G. Kumar","doi":"10.1109/ICSCN.2017.8085648","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085648","url":null,"abstract":"The vital element of the DSP processor is Multiplier unit. The main objectives of the DSP processor are speed, power, delay and area. These goals have been realized with fixed-width multiplier whose output bits equal to input bits. The fixed-width multiplier implemented DSP processors can be applied for audio signal processing, video signal processing, VLSI signal processing, speech recognition, digital communication, medical imaging, MRI, MP3 and so on. Many researchers are optimizing, the performance of the multiplication process. In this review paper, the technologies to achieve the objectives of the DSP processor have been studied. And also the most recent developments in the multiplier circuit have been discussed. In this paper, first, the brief background of the fixed-width multiplier is outlined. Then, several multiplier architectures proposed for MAC (multiplier-accumulator) presented, narrating their functioning principles and key features. To provide a perception into future research directions, open research issues are discussed at the completion of this paper.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117102567","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085658
L. Chandiea, K. Anusudha
The need in today's wireless applications is to design antennas that are compact, robust and effortless to integrate with RF circuit components. Microstrip patch antenna is one such type which satisfies these requirements. But the two main performance parameters of an antenna namely the gain and the bandwidth are near to the ground for patch antennas. Usually the gain range of a patch antenna is 1–2dB. Most straightforward approach of increasing these factors involves the use of low dielectric substrate with increased thickness, but this inevitably leads to generation of surface waves. As a result, sensible substrate thickness has to be employed. In this paper pentagon shaped patch antenna with metamaterial on the substrate for multiband application is proposed. The analysis is done using Ansoft HFSS software version 15.0. The performance parameters analysed are bandwidth, gain and return loss. The proposed antenna design covers UWB range, C, X, Ku, K, Ka and a portion of V band.
{"title":"Design of pentagon shaped microstrip patch antennawith metamaterialfor multiband application","authors":"L. Chandiea, K. Anusudha","doi":"10.1109/ICSCN.2017.8085658","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085658","url":null,"abstract":"The need in today's wireless applications is to design antennas that are compact, robust and effortless to integrate with RF circuit components. Microstrip patch antenna is one such type which satisfies these requirements. But the two main performance parameters of an antenna namely the gain and the bandwidth are near to the ground for patch antennas. Usually the gain range of a patch antenna is 1–2dB. Most straightforward approach of increasing these factors involves the use of low dielectric substrate with increased thickness, but this inevitably leads to generation of surface waves. As a result, sensible substrate thickness has to be employed. In this paper pentagon shaped patch antenna with metamaterial on the substrate for multiband application is proposed. The analysis is done using Ansoft HFSS software version 15.0. The performance parameters analysed are bandwidth, gain and return loss. The proposed antenna design covers UWB range, C, X, Ku, K, Ka and a portion of V band.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122294100","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085710
R. Anandha Sree, A. Kavitha
This work has focused on the possibilities of classifying vowels ‘a’, ‘e’, ‘i’, ‘o’, ‘u’ from EEG signals, that has been derived while imagining the vowels, with minimum input features. The EEG signals have been acquired from 5 subjects while imagining and uttering the vowels during a well defined experimental protocol, have been processed and segmented using established signal processing routines. The signals have been segmented under various sub-band frequencies and subjected to Db4 Discrete Wavelet Transform. The various conventional and derived energy based features have been acquired from the sub-band frequency signals, trained and tested using Deep Belief Networks for classifying the imagined vowels. The experiments have been repeated on various electrode combinations. Results obtained from all sub-band frequency based features have shown a good classification accuracy. Further, classification protocol employing features that have been derived from each sub-band frequency has shown that the theta and gamma band frequency features have been more effective with a vowel classification accuracy ranging between 75–100%.
{"title":"Vowel classification from imagined speech using sub-band EEG frequencies and deep belief networks","authors":"R. Anandha Sree, A. Kavitha","doi":"10.1109/ICSCN.2017.8085710","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085710","url":null,"abstract":"This work has focused on the possibilities of classifying vowels ‘a’, ‘e’, ‘i’, ‘o’, ‘u’ from EEG signals, that has been derived while imagining the vowels, with minimum input features. The EEG signals have been acquired from 5 subjects while imagining and uttering the vowels during a well defined experimental protocol, have been processed and segmented using established signal processing routines. The signals have been segmented under various sub-band frequencies and subjected to Db4 Discrete Wavelet Transform. The various conventional and derived energy based features have been acquired from the sub-band frequency signals, trained and tested using Deep Belief Networks for classifying the imagined vowels. The experiments have been repeated on various electrode combinations. Results obtained from all sub-band frequency based features have shown a good classification accuracy. Further, classification protocol employing features that have been derived from each sub-band frequency has shown that the theta and gamma band frequency features have been more effective with a vowel classification accuracy ranging between 75–100%.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132268727","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085738
Minnu Anthrayose, T. Sridarshini, S. Gandhi
Photonic crystal is a dielectric with periodic modulation of refractive index of constituent elements which results in photonic band-gap effect which is unique property of Photonic crystal. Such Band gap effect helps to analyse the optical performance of Photonic crystals. This paper deals with Photonic Band gap (PBG) calculations for two dimensional Photonic crystals and the effect of size that is radius of silicon pillar on PBG. Plane Wave Expansion (PWE) method is used for obtaining band structure.
{"title":"Performance analysis and characterization of 2D photonic crystals — An analytical approach","authors":"Minnu Anthrayose, T. Sridarshini, S. Gandhi","doi":"10.1109/ICSCN.2017.8085738","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085738","url":null,"abstract":"Photonic crystal is a dielectric with periodic modulation of refractive index of constituent elements which results in photonic band-gap effect which is unique property of Photonic crystal. Such Band gap effect helps to analyse the optical performance of Photonic crystals. This paper deals with Photonic Band gap (PBG) calculations for two dimensional Photonic crystals and the effect of size that is radius of silicon pillar on PBG. Plane Wave Expansion (PWE) method is used for obtaining band structure.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132761928","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085690
Dr. B. Vinayagasundaram, R. J. Aarthi, N. Abirami
The key interest of machine learning is conventionally training the machine from data that have underlying distribution such as data should have predetermined distribution. Such a constraint on the problem area leads to the technique for development of learning algorithms with notionally verifiable performance accuracy. However, real-world problems are not able to fit smartly into such restricted model. Class imbalance problem can occur due to tilted distribution of class data. Data streaming from non-stationary distribution with more uncertainty in real-time applications, resulting in the concept drift problem. In this methodology, it is proposed to extend the Extreme Learning Machine (ELM) algorithm for effectively handling the class imbalance problem and concept drift in datasets. This proposal has higher level of prediction accuracy and performance compared to Support Vector Machine (SVM) and Support Vector Data Description.
机器学习的主要兴趣是传统地从具有底层分布的数据中训练机器，例如应该具有预定分布的数据。这种对问题区域的约束导致了具有概念上可验证性能准确性的学习算法的开发技术。然而，现实世界的问题并不能很好地适应这种受限制的模型。班级数据的倾斜分布会导致班级不平衡问题。数据流是非平稳分布，在实时应用中具有更多的不确定性，导致概念漂移问题。在该方法中，提出了扩展极限学习机(ELM)算法以有效处理数据集中的类不平衡问题和概念漂移问题。与支持向量机(SVM)和支持向量数据描述(Support Vector Data Description)相比，该方法具有更高的预测精度和性能。
{"title":"Online extreme learning machine for handling concept drift and class imbalance problem","authors":"Dr. B. Vinayagasundaram, R. J. Aarthi, N. Abirami","doi":"10.1109/ICSCN.2017.8085690","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085690","url":null,"abstract":"The key interest of machine learning is conventionally training the machine from data that have underlying distribution such as data should have predetermined distribution. Such a constraint on the problem area leads to the technique for development of learning algorithms with notionally verifiable performance accuracy. However, real-world problems are not able to fit smartly into such restricted model. Class imbalance problem can occur due to tilted distribution of class data. Data streaming from non-stationary distribution with more uncertainty in real-time applications, resulting in the concept drift problem. In this methodology, it is proposed to extend the Extreme Learning Machine (ELM) algorithm for effectively handling the class imbalance problem and concept drift in datasets. This proposal has higher level of prediction accuracy and performance compared to Support Vector Machine (SVM) and Support Vector Data Description.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"2021 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133001641","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085647
P. Rakesh, S. Priyanka, T. Kumar
This paper presents speech enhancement using fixed and adaptive beamforming techniques to improve quality of speech signal in noisy environment. Microphone arrays provide a means of enhancing a desired signal in the presence of corrupting noise sources using spatial filtering. In this paper, Delay and Sum Beamformer (DSB) and Generalized Side lobe Canceller (GSC) beamformer are implemented using microphone array and their performance are evaluated by considering various noises under different SNR levels. Enhanced speech characteristics are represented in time domain and frequency domain. The interference is nullified and the beamformer is steered towards desired direction using spatial response. An enhanced speech with improved SNR is achieved by generalized side lobe canceller with Least Mean Square (LMS) algorithm than Delay and Sum beamformer.
{"title":"Performance evaluation of beamforming techniques for speech enhancement","authors":"P. Rakesh, S. Priyanka, T. Kumar","doi":"10.1109/ICSCN.2017.8085647","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085647","url":null,"abstract":"This paper presents speech enhancement using fixed and adaptive beamforming techniques to improve quality of speech signal in noisy environment. Microphone arrays provide a means of enhancing a desired signal in the presence of corrupting noise sources using spatial filtering. In this paper, Delay and Sum Beamformer (DSB) and Generalized Side lobe Canceller (GSC) beamformer are implemented using microphone array and their performance are evaluated by considering various noises under different SNR levels. Enhanced speech characteristics are represented in time domain and frequency domain. The interference is nullified and the beamformer is steered towards desired direction using spatial response. An enhanced speech with improved SNR is achieved by generalized side lobe canceller with Least Mean Square (LMS) algorithm than Delay and Sum beamformer.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"416 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121821291","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085704
B. Bharathi, G. Sridevi, G. J. Varshitha
Tamil is one of the oldest languages of the world with a rich collection of literature. The state of Tamil Nadu in India and Sri Lanka have vast populations of indigenous Tamil speakers. The Thirukkural is a classical Tamil Sangam Literature, penned by the famous Tamil poet, Thiruvalluvar. Kural is a very short Tamil Poetic form consisting of two lines. Thirukkural contains many important messages, speaking about the moral and ethical values to be followed by everyone. Up to now, speech Recognition has not been applied to this literature. This paper proposes a system which will recognize and retrieve the meaning of Thirukkural from speech utterances. This is achieved by extracting the MFCC feature vectors from the input speech (kural) and building the acoustic models by using Gaussian Mixture Model(GMM). This speaker independent system aims to convert the input speech Thirukkural into text and display the meaning in Tamil along with the chapter number, name and kural number. The system will also synthesize the meaning of the Thirukkural(text to speech). This will be useful to students and visually challenged people to learn Thirukkural in an interactive way. This will be a great help in encouraging more people to take an interest in and learn the Thirukkural. Experiments were conducted by collecting the corpus from 25 people (2000 kural samples) for one chapter of Thirukkural named “Seynandri Aridhal”. The performance of the system was evaluated by building models for different mixture components and retrieving the meaning. It was found to give 100 % accurate results for 128 mixture component models.
{"title":"Recognising and retrieving the meaning of Thirukkural from speech utterances","authors":"B. Bharathi, G. Sridevi, G. J. Varshitha","doi":"10.1109/ICSCN.2017.8085704","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085704","url":null,"abstract":"Tamil is one of the oldest languages of the world with a rich collection of literature. The state of Tamil Nadu in India and Sri Lanka have vast populations of indigenous Tamil speakers. The Thirukkural is a classical Tamil Sangam Literature, penned by the famous Tamil poet, Thiruvalluvar. Kural is a very short Tamil Poetic form consisting of two lines. Thirukkural contains many important messages, speaking about the moral and ethical values to be followed by everyone. Up to now, speech Recognition has not been applied to this literature. This paper proposes a system which will recognize and retrieve the meaning of Thirukkural from speech utterances. This is achieved by extracting the MFCC feature vectors from the input speech (kural) and building the acoustic models by using Gaussian Mixture Model(GMM). This speaker independent system aims to convert the input speech Thirukkural into text and display the meaning in Tamil along with the chapter number, name and kural number. The system will also synthesize the meaning of the Thirukkural(text to speech). This will be useful to students and visually challenged people to learn Thirukkural in an interactive way. This will be a great help in encouraging more people to take an interest in and learn the Thirukkural. Experiments were conducted by collecting the corpus from 25 people (2000 kural samples) for one chapter of Thirukkural named “Seynandri Aridhal”. The performance of the system was evaluated by building models for different mixture components and retrieving the meaning. It was found to give 100 % accurate results for 128 mixture component models.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117221347","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085733
S. Thilagavathi, D. Venkatesh
In this paper, an Ultra Wideband (UWB) Monopole antenna is proposed for several applications. The size of the antenna is 55mm × 35mm × 1.7mm with dual F-slots in its ground plane and three different pairs of rectangular slots in its upper patch. In order for the antenna to resonate at multiple frequencies or to attain wide impedance bandwidth, the relative lengths, heights and positions of the slots are tuned to the required resonant frequency. The simulation results are obtained using the tool Advanced Design System 2014 (ADS 2014). The −10 dB impedance bandwidth obtained by the proposed antenna at two resonant frequencies 2.5 GHz and 4.9 GHz are 683 MHz (2.280 GHz to 2.963 GHz) and 4.352 GHz (4.667 GHz to 9.019 GHz) respectively. The maximum gain of 3.1 dBi at 2.5 GHz and 2.26 dBi at 5 GHz are also achieved. The antenna will operate for 2.4 GHz ISM band, Bluetooth & Zigbee applications, IEEE 802.11 WiMAX at 5.5 GHz, WLAN (5 GHz) applications of IEEE 802.11a, IEEE 802.11n & IEEE 802.11ac and also covers the part of 4–8 GHz (C-band) satellite frequency band.
{"title":"Design of compact dual F-slots UWB monopole antenna for wireless devices","authors":"S. Thilagavathi, D. Venkatesh","doi":"10.1109/ICSCN.2017.8085733","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085733","url":null,"abstract":"In this paper, an Ultra Wideband (UWB) Monopole antenna is proposed for several applications. The size of the antenna is 55mm × 35mm × 1.7mm with dual F-slots in its ground plane and three different pairs of rectangular slots in its upper patch. In order for the antenna to resonate at multiple frequencies or to attain wide impedance bandwidth, the relative lengths, heights and positions of the slots are tuned to the required resonant frequency. The simulation results are obtained using the tool Advanced Design System 2014 (ADS 2014). The −10 dB impedance bandwidth obtained by the proposed antenna at two resonant frequencies 2.5 GHz and 4.9 GHz are 683 MHz (2.280 GHz to 2.963 GHz) and 4.352 GHz (4.667 GHz to 9.019 GHz) respectively. The maximum gain of 3.1 dBi at 2.5 GHz and 2.26 dBi at 5 GHz are also achieved. The antenna will operate for 2.4 GHz ISM band, Bluetooth & Zigbee applications, IEEE 802.11 WiMAX at 5.5 GHz, WLAN (5 GHz) applications of IEEE 802.11a, IEEE 802.11n & IEEE 802.11ac and also covers the part of 4–8 GHz (C-band) satellite frequency band.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121198667","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 : 2017-03-01DOI: 10.1109/ICSCN.2017.8085644
Prasad Rayi, M. Prasad
Massive-Multi Input and Multi Output (MIMO) antenna system is considered as the key technology to improve both spectral efficiency (SE) and energy efficiency (EE) for 5G systems. Where pilot contamination and inter-cell interference have been considered as basic limiting factors to achieve high data rate. These parameters will saturate the SE and truncate to a constant value. In this work, we explore the effective evaluation of SE and EE of the M-MIMO antenna system with optimal users. In this work, we basically considered linear processing algorithms such as zero-forcing (ZF), maximum ratio combing (MRC) and minimum mean square error (MMSE) for the analysis SE for the both single and multi-cell scenario in M-MIMO systems. In this paper, we provide a platform to improve the SE and EE with a variation of base station (BS) antennas M and pilot reuse factor λ. We also derived the explicit and exact expressions for the analysis of SE and EE with perfect and imperfect channel state information (CSI). Which are very tight and tractable approximations in the prospective of realistic system scenario. We mainly focused on the asymptotic limit of SE and also obtain optimal user terminals K. It has been noticed that the SE performance greatly depends on the receiving combined scheme. We compared the simulation results for SE based the parameters such as varying antennas at the BS M, optimal UTs K and finally pilot reuse factors λ=4 and λ=7. Here, the simulation results of the BS antennas per-user (M/K) and optimal users K, highly depend on the receive technique and the BS antennas M. We also demonstrated the simulation results with the variation of per-user SE versus the BS antennas. The simulation results were performed by using Matlab 2015b.
{"title":"Enhancement of spectral and energy efficiency in massive MIMO systems with linear schemes","authors":"Prasad Rayi, M. Prasad","doi":"10.1109/ICSCN.2017.8085644","DOIUrl":"https://doi.org/10.1109/ICSCN.2017.8085644","url":null,"abstract":"Massive-Multi Input and Multi Output (MIMO) antenna system is considered as the key technology to improve both spectral efficiency (SE) and energy efficiency (EE) for 5G systems. Where pilot contamination and inter-cell interference have been considered as basic limiting factors to achieve high data rate. These parameters will saturate the SE and truncate to a constant value. In this work, we explore the effective evaluation of SE and EE of the M-MIMO antenna system with optimal users. In this work, we basically considered linear processing algorithms such as zero-forcing (ZF), maximum ratio combing (MRC) and minimum mean square error (MMSE) for the analysis SE for the both single and multi-cell scenario in M-MIMO systems. In this paper, we provide a platform to improve the SE and EE with a variation of base station (BS) antennas M and pilot reuse factor λ. We also derived the explicit and exact expressions for the analysis of SE and EE with perfect and imperfect channel state information (CSI). Which are very tight and tractable approximations in the prospective of realistic system scenario. We mainly focused on the asymptotic limit of SE and also obtain optimal user terminals K. It has been noticed that the SE performance greatly depends on the receiving combined scheme. We compared the simulation results for SE based the parameters such as varying antennas at the BS M, optimal UTs K and finally pilot reuse factors λ=4 and λ=7. Here, the simulation results of the BS antennas per-user (M/K) and optimal users K, highly depend on the receive technique and the BS antennas M. We also demonstrated the simulation results with the variation of per-user SE versus the BS antennas. The simulation results were performed by using Matlab 2015b.","PeriodicalId":383458,"journal":{"name":"2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN)","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121156520","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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