Pub Date : 2020-02-01DOI: 10.1109/NCC48643.2020.9056029
S. Manna, Jessy Rimaya Khonglah, A. Mukherjee, G. Saha
Kernelized graph-based learning methods have gained popularity because of its better performances in the clustering task. But in high dimensional data, there exist many redundant features which may degrade the clustering performances. To solve this issue, we propose a novel multi-view kernelized graph-based clustering (MVKGC) framework for high dimensional data that performs the clustering task while reducing the dimensionality of the data. The proposed method also uses multiple views which help to improve the clustering performances by providing different partial information of a given data set. The extensive experiments of the proposed method on different real-world benchmark data sets show a better and efficient performance of the proposed method than other existing methods.
{"title":"Kernelized Graph-based Multi-view Clustering on High Dimensional Data","authors":"S. Manna, Jessy Rimaya Khonglah, A. Mukherjee, G. Saha","doi":"10.1109/NCC48643.2020.9056029","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9056029","url":null,"abstract":"Kernelized graph-based learning methods have gained popularity because of its better performances in the clustering task. But in high dimensional data, there exist many redundant features which may degrade the clustering performances. To solve this issue, we propose a novel multi-view kernelized graph-based clustering (MVKGC) framework for high dimensional data that performs the clustering task while reducing the dimensionality of the data. The proposed method also uses multiple views which help to improve the clustering performances by providing different partial information of a given data set. The extensive experiments of the proposed method on different real-world benchmark data sets show a better and efficient performance of the proposed method than other existing methods.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130138731","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 : 2020-02-01DOI: 10.1109/NCC48643.2020.9056088
Vikram Singh, Suraj Srivastava, A. Jagannatham
This work proposes symbol and block level adaptive channel estimation schemes, based on the least mean squares (LMS) and block-LMS (BLMS) approaches, respectively, for multiuser-MIMO (MU-MIMO) systems. The proposed schemes do not require knowledge of the first and second order statistics of the time-varying MU-MIMO channel, while also having a lower computational complexity in comparison to the Kalman filter based channel estimation approaches present in the existing literature. Another important aspect of the proposed MU-MIMO framework is that channel estimation is carried out at the base station (BS), which simplifies the receiver architecture. Analytical expressions are derived for the error covariance matrix at each time instant and the asymptotic mean square error (MSE) of the proposed LMS and BLMS frameworks. Further, a superimposed pilot (SIP) framework for MU-MIMO channel estimation been developed, which transmits data symbols to a group of selected users during the training phase, thus leading to a significant improvement in the sum-rate performance. Simulation results are presented to demonstrate the improved sum-rate and MSE performance of the proposed schemes and also to verify the analytical results.
{"title":"Superimposed Pilots based Adaptive Time-Selective Channel Estimation in MU-MIMO Systems","authors":"Vikram Singh, Suraj Srivastava, A. Jagannatham","doi":"10.1109/NCC48643.2020.9056088","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9056088","url":null,"abstract":"This work proposes symbol and block level adaptive channel estimation schemes, based on the least mean squares (LMS) and block-LMS (BLMS) approaches, respectively, for multiuser-MIMO (MU-MIMO) systems. The proposed schemes do not require knowledge of the first and second order statistics of the time-varying MU-MIMO channel, while also having a lower computational complexity in comparison to the Kalman filter based channel estimation approaches present in the existing literature. Another important aspect of the proposed MU-MIMO framework is that channel estimation is carried out at the base station (BS), which simplifies the receiver architecture. Analytical expressions are derived for the error covariance matrix at each time instant and the asymptotic mean square error (MSE) of the proposed LMS and BLMS frameworks. Further, a superimposed pilot (SIP) framework for MU-MIMO channel estimation been developed, which transmits data symbols to a group of selected users during the training phase, thus leading to a significant improvement in the sum-rate performance. Simulation results are presented to demonstrate the improved sum-rate and MSE performance of the proposed schemes and also to verify the analytical results.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127606814","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 : 2020-02-01DOI: 10.1109/NCC48643.2020.9056093
Suraj Srivastava, Manoj P. Suradkar, A. Jagannatham
This work presents affine precoded superimposed pilot-based sparse channel estimation in orthogonal space-time block coded (OSTBC) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. A pilot-based block sparse Bayesian learning (P-BSBL) technique is developed initially, which leverages the sparsity as well as the spatial correlation of the MIMO channel for improved estimation. Subsequently, a data aided-BSBL (D-BSBL) technique is presented for joint maximum likelihood (ML) decoding of the symbols and sparse channel estimation, which is shown to lead to a further improvement in the accuracy of the estimated channel. In addition to a significant decrease in the mean squared error (MSE) of estimation, the proposed schemes are also shown to lead to a substantial increase in spectral efficiency over the existing schemes. Moreover, they are also applicable in ill-posed CSI estimation scenarios, where conventional approaches fail due to a large delay spread. The Bayesian Cramér-Rao bounds are derived to analytically benchmark the estimation performance followed by simulation results that show the improved performance of the proposed techniques.
{"title":"BSBL-based Block-Sparse Channel Estimation for Affine Precoded OSTBC MIMO-OFDM Systems","authors":"Suraj Srivastava, Manoj P. Suradkar, A. Jagannatham","doi":"10.1109/NCC48643.2020.9056093","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9056093","url":null,"abstract":"This work presents affine precoded superimposed pilot-based sparse channel estimation in orthogonal space-time block coded (OSTBC) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. A pilot-based block sparse Bayesian learning (P-BSBL) technique is developed initially, which leverages the sparsity as well as the spatial correlation of the MIMO channel for improved estimation. Subsequently, a data aided-BSBL (D-BSBL) technique is presented for joint maximum likelihood (ML) decoding of the symbols and sparse channel estimation, which is shown to lead to a further improvement in the accuracy of the estimated channel. In addition to a significant decrease in the mean squared error (MSE) of estimation, the proposed schemes are also shown to lead to a substantial increase in spectral efficiency over the existing schemes. Moreover, they are also applicable in ill-posed CSI estimation scenarios, where conventional approaches fail due to a large delay spread. The Bayesian Cramér-Rao bounds are derived to analytically benchmark the estimation performance followed by simulation results that show the improved performance of the proposed techniques.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125778277","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 : 2020-02-01DOI: 10.1109/NCC48643.2020.9056040
Sapta Girish Neelam, P. R. Sahu
Orthogonal time frequency space (OTFS) modulation, which was proposed recently is a two dimensional modulation technique designed in the delay-Doppler (DD) domain unlike OFDM which was designed in the time-frequency (TF) domain. It is suited for doubly dispersive fading wireless channels. Some transformations are done at the transmitter and receiver of the conventional multicarrier modulation. In this paper, we pre- distort frequency dependent transmitter (Tx) IQ imbalance (IQI) and power amplifier (PA) nonlinearity in two steps. The bit error rate performance analysis of OTFS in the presence of receiver (Rx) IQI along with residual Tx IQI is analyzed. We develop an input-output relation of OTFS in the DD domain, with impairments in the presence of time varying (TV) channel. A message passing algorithm is used to detect the OTFS signal with impairments. We show that compensating IQI at the Tx and PA non-linearity has improved the BER performance.
{"title":"Error performance of OTFS in the presence of IQI and PA Nonlinearity","authors":"Sapta Girish Neelam, P. R. Sahu","doi":"10.1109/NCC48643.2020.9056040","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9056040","url":null,"abstract":"Orthogonal time frequency space (OTFS) modulation, which was proposed recently is a two dimensional modulation technique designed in the delay-Doppler (DD) domain unlike OFDM which was designed in the time-frequency (TF) domain. It is suited for doubly dispersive fading wireless channels. Some transformations are done at the transmitter and receiver of the conventional multicarrier modulation. In this paper, we pre- distort frequency dependent transmitter (Tx) IQ imbalance (IQI) and power amplifier (PA) nonlinearity in two steps. The bit error rate performance analysis of OTFS in the presence of receiver (Rx) IQI along with residual Tx IQI is analyzed. We develop an input-output relation of OTFS in the DD domain, with impairments in the presence of time varying (TV) channel. A message passing algorithm is used to detect the OTFS signal with impairments. We show that compensating IQI at the Tx and PA non-linearity has improved the BER performance.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128102553","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 : 2020-02-01DOI: 10.1109/NCC48643.2020.9055993
Sridhar Chintala, Jaisingh Thangaraj
Ocular Artifacts (OAs) have a significant impact on the performance of Electroencephalogram (EEG) activities in the frontal region because of its higher amplitude. In this paper, Robust Variable Forgetting Factor (RVFF) and Recursive Least Square (RLS) based RVFF-RLS algorithm is implemented for removal of OAs from the raw EEG signal. Reference signals such as horizontal electro-oculogram and vertical electro-oculogram are recorded and then processed through the finite impulse response filter, whose coefficients are adaptively updated using the RVFF-RLS algorithm. Thereafter, obtained signals are subsequently subtracted from the raw EEG signal to obtain an EEG signal, which is free from OAs. The performance of proposed technique is compared with conventional techniques such as numerical variable forgetting factor RLS, fixed step size normalized least mean squares, fixed forgetting factor- RLS. The proposed technique shows least mean square error under a dynamic environment.
{"title":"Ocular Artifact Elimination from EEG signals using RVFF-RLS Adaptive Algorithm","authors":"Sridhar Chintala, Jaisingh Thangaraj","doi":"10.1109/NCC48643.2020.9055993","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9055993","url":null,"abstract":"Ocular Artifacts (OAs) have a significant impact on the performance of Electroencephalogram (EEG) activities in the frontal region because of its higher amplitude. In this paper, Robust Variable Forgetting Factor (RVFF) and Recursive Least Square (RLS) based RVFF-RLS algorithm is implemented for removal of OAs from the raw EEG signal. Reference signals such as horizontal electro-oculogram and vertical electro-oculogram are recorded and then processed through the finite impulse response filter, whose coefficients are adaptively updated using the RVFF-RLS algorithm. Thereafter, obtained signals are subsequently subtracted from the raw EEG signal to obtain an EEG signal, which is free from OAs. The performance of proposed technique is compared with conventional techniques such as numerical variable forgetting factor RLS, fixed step size normalized least mean squares, fixed forgetting factor- RLS. The proposed technique shows least mean square error under a dynamic environment.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133604420","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 : 2020-02-01DOI: 10.1109/NCC48643.2020.9056021
Prateek Yadav, Subrat Kar
We investigate the impact of the content popularity of video streams in a local region and its impact on the CDN deployment cost. We have gathered real-world data from four popular classroom video streaming sites and analyzed the content caching to optimize the CDN deployment. Our traces contain metadata of around 31 thousand educational videos and approximately 100 million views in the education category of YouTube. From this analysis, we assert that region based content (e.g., NPTEL, India) follows Zipf law with low popularity exponent, and it is the region-based content popularity which most significantly impacts the CDN deployment cost.
{"title":"Evaluating the Impact of Region Based Content Popularity of Videos on the Cost of CDN Deployment","authors":"Prateek Yadav, Subrat Kar","doi":"10.1109/NCC48643.2020.9056021","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9056021","url":null,"abstract":"We investigate the impact of the content popularity of video streams in a local region and its impact on the CDN deployment cost. We have gathered real-world data from four popular classroom video streaming sites and analyzed the content caching to optimize the CDN deployment. Our traces contain metadata of around 31 thousand educational videos and approximately 100 million views in the education category of YouTube. From this analysis, we assert that region based content (e.g., NPTEL, India) follows Zipf law with low popularity exponent, and it is the region-based content popularity which most significantly impacts the CDN deployment cost.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131560493","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 : 2020-02-01DOI: 10.1109/NCC48643.2020.9055990
H. Dutta, Debajit Sarma, M. Bhuyan, R. Laskar
The ability to discern the shape of hands can be a vital issue in improving the performance of hand gesture recognition. Segmentation itself is a very challenging problem having various constraints like illumination variation, complex background etc. The objective of the paper is to incorporate the perception of semantic segmentation into a classification problem and make use of the deep neural models to achieve improved results. This paper utilizes the UNET architecture to obtain the semantically segmented mask of the input, which is then given to a VGG16 model for classification. Here the top classifier layer of the VGG16 model is replaced with a classifier designed specifically for classifying the gestures at hand. The Brazilian Sign Language database used in the paper contains about 9600 images. Data augmentation process is used in preprocessing to generate sufficient number of training images for the aforementioned CNN-based models. A significant and improved average recognition rate of 98.97% is achieved through inherent feature learning capability of CNN and refined segmentation for 34 classes.
{"title":"Semantic Segmentation based Hand Gesture Recognition using Deep Neural Networks","authors":"H. Dutta, Debajit Sarma, M. Bhuyan, R. Laskar","doi":"10.1109/NCC48643.2020.9055990","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9055990","url":null,"abstract":"The ability to discern the shape of hands can be a vital issue in improving the performance of hand gesture recognition. Segmentation itself is a very challenging problem having various constraints like illumination variation, complex background etc. The objective of the paper is to incorporate the perception of semantic segmentation into a classification problem and make use of the deep neural models to achieve improved results. This paper utilizes the UNET architecture to obtain the semantically segmented mask of the input, which is then given to a VGG16 model for classification. Here the top classifier layer of the VGG16 model is replaced with a classifier designed specifically for classifying the gestures at hand. The Brazilian Sign Language database used in the paper contains about 9600 images. Data augmentation process is used in preprocessing to generate sufficient number of training images for the aforementioned CNN-based models. A significant and improved average recognition rate of 98.97% is achieved through inherent feature learning capability of CNN and refined segmentation for 34 classes.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134310264","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 : 2020-02-01DOI: 10.1109/NCC48643.2020.9056034
Brijesh Soni, Dhaval K. Patel, Y. Guan, Sumei Sun, Yoong Choon Chang, J. Lim
In this paper, we investigate the outage analysis of Millimeter wave (mmWave) non-orthogonal multiple access (NOMA) based cooperative relaying system. We consider that the source communicates with user equipment with the aid of decode and forward relay using power domain downlink NOMA, and by sending messages in two time slots. Moreover, the α-η-κ -µ fading channel is considered between source, relay and user equipment, which is recently proposed in literature as a good fit model for mmWave communication. To this end, we derive the analytical expression for outage probability in terms of channel fading parameters. In order to gain insights at high SNR, asymptotic analysis for outage probability is carried out. Furthermore, analysis of achievable sum rate is also studied. Findings suggest that the considered channel model provides comparative diversity gain than the other fading channels. Proposed analytical expressions are verified by Monte Carlo simulations. We observe that at high SNR, diversity order depends only on the number of the scattered clusters and on the non linearity of the medium i.e. diversity order is αµ/2.
{"title":"Performance Analysis of NOMA aided Cooperative Relaying over α-η-κ-µ Fading Channels","authors":"Brijesh Soni, Dhaval K. Patel, Y. Guan, Sumei Sun, Yoong Choon Chang, J. Lim","doi":"10.1109/NCC48643.2020.9056034","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9056034","url":null,"abstract":"In this paper, we investigate the outage analysis of Millimeter wave (mmWave) non-orthogonal multiple access (NOMA) based cooperative relaying system. We consider that the source communicates with user equipment with the aid of decode and forward relay using power domain downlink NOMA, and by sending messages in two time slots. Moreover, the α-η-κ -µ fading channel is considered between source, relay and user equipment, which is recently proposed in literature as a good fit model for mmWave communication. To this end, we derive the analytical expression for outage probability in terms of channel fading parameters. In order to gain insights at high SNR, asymptotic analysis for outage probability is carried out. Furthermore, analysis of achievable sum rate is also studied. Findings suggest that the considered channel model provides comparative diversity gain than the other fading channels. Proposed analytical expressions are verified by Monte Carlo simulations. We observe that at high SNR, diversity order depends only on the number of the scattered clusters and on the non linearity of the medium i.e. diversity order is αµ/2.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133195741","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 : 2020-02-01DOI: 10.1109/NCC48643.2020.9056007
S. Thakallapalli, Sudarsana Reddy Kadiri, S. Gangashetty
In this paper, we present a multispeaker localization method using the time delay estimates obtained from the spectral features derived from the single frequency filter (SFF) representation. The mixture signals are transformed into SFF domain from which the temporal envelopes are extracted at each frequency. Subsequently, the spectral features such as mean and variance of temporal envelopes across frequencies are correlated for extracting the time delay estimates. Since these features emphasize the high SNR regions of the mixtures, correlation of the corresponding features across the channels leads to robust delay estimates in real acoustic environments. We study the efficacy of the developed approach by comparing its performance with the existing correlation based time delay estimation techniques. Both, a standard data set recorded in real-room acoustic environments and simulated data set are used for evaluations. It is observed that the localization performance of the proposed algorithm closely matches the performance of a state-of-the-art correlation approach and outperforms other approaches.
{"title":"Spectral Features derived from Single Frequency Filter for Multispeaker Localization","authors":"S. Thakallapalli, Sudarsana Reddy Kadiri, S. Gangashetty","doi":"10.1109/NCC48643.2020.9056007","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9056007","url":null,"abstract":"In this paper, we present a multispeaker localization method using the time delay estimates obtained from the spectral features derived from the single frequency filter (SFF) representation. The mixture signals are transformed into SFF domain from which the temporal envelopes are extracted at each frequency. Subsequently, the spectral features such as mean and variance of temporal envelopes across frequencies are correlated for extracting the time delay estimates. Since these features emphasize the high SNR regions of the mixtures, correlation of the corresponding features across the channels leads to robust delay estimates in real acoustic environments. We study the efficacy of the developed approach by comparing its performance with the existing correlation based time delay estimation techniques. Both, a standard data set recorded in real-room acoustic environments and simulated data set are used for evaluations. It is observed that the localization performance of the proposed algorithm closely matches the performance of a state-of-the-art correlation approach and outperforms other approaches.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114966218","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 : 2020-02-01DOI: 10.1109/NCC48643.2020.9056036
H. Sahu, P. R. Sahu, Jeevan Mishra
A cooperative communication system with space shift keying (SSK) modulation and simultaneous wireless information and power transfer (SWIPT) scheme is analyzed over Rayleigh fading channel. SSK is a simple modulation technique that enhances data rate, minimize inter-channel interference, inter-antenna synchronization, and number of radio frequency chains whereas SWIPT extends battery life at the relays. Average bit error probability (ABEP) using partial relay selection and generalised selection combining (GSC) schemes at the receiver are investigated for Rayleigh fading channels. ABEP expression is derived with single amplify and forward (AF) relay selection, from multiple relays, and using selection combining of signals from multiple antennas. Numerical and computer simulation results are presented with the discussion.
{"title":"ABEP of SSK with SWIPT at Relay and Generalised Selection Combining at the Destination over Rayleigh Fading","authors":"H. Sahu, P. R. Sahu, Jeevan Mishra","doi":"10.1109/NCC48643.2020.9056036","DOIUrl":"https://doi.org/10.1109/NCC48643.2020.9056036","url":null,"abstract":"A cooperative communication system with space shift keying (SSK) modulation and simultaneous wireless information and power transfer (SWIPT) scheme is analyzed over Rayleigh fading channel. SSK is a simple modulation technique that enhances data rate, minimize inter-channel interference, inter-antenna synchronization, and number of radio frequency chains whereas SWIPT extends battery life at the relays. Average bit error probability (ABEP) using partial relay selection and generalised selection combining (GSC) schemes at the receiver are investigated for Rayleigh fading channels. ABEP expression is derived with single amplify and forward (AF) relay selection, from multiple relays, and using selection combining of signals from multiple antennas. Numerical and computer simulation results are presented with the discussion.","PeriodicalId":183772,"journal":{"name":"2020 National Conference on Communications (NCC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121226514","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：