Pub Date : 2020-07-01DOI: 10.1109/SPCOM50965.2020.9179543
Akash Agarwal, A. Jagannatham
This work considers a finite blocklength (FBL) non-orthogonal multiple access (NOMA)-based joint one-way and two-way relaying aided communication scheme wherein two source nodes share a single decode-and-forward (DF) relay to exchange their information as well as transmit it to the respective destination nodes over a finite number of channel uses. Novel closed-form expressions have been obtained for the end-to-end block error rate (BLER) at all the nodes and also the net throughput of the system. Furthermore, an asymptotic end-to-end BLER floor has also been obtained for all the nodes at high transmit signal to noise power ratio (SNR). Simulation results are presented to authenticate the analytical results derived and demonstrate the efficacy of the proposed scheme.
{"title":"NOMA-based Joint One-Way and Two-Way Relaying Aided Finite Blocklength Communication","authors":"Akash Agarwal, A. Jagannatham","doi":"10.1109/SPCOM50965.2020.9179543","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179543","url":null,"abstract":"This work considers a finite blocklength (FBL) non-orthogonal multiple access (NOMA)-based joint one-way and two-way relaying aided communication scheme wherein two source nodes share a single decode-and-forward (DF) relay to exchange their information as well as transmit it to the respective destination nodes over a finite number of channel uses. Novel closed-form expressions have been obtained for the end-to-end block error rate (BLER) at all the nodes and also the net throughput of the system. Furthermore, an asymptotic end-to-end BLER floor has also been obtained for all the nodes at high transmit signal to noise power ratio (SNR). Simulation results are presented to authenticate the analytical results derived and demonstrate the efficacy of the proposed scheme.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130062019","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 : 2020-07-01DOI: 10.1109/SPCOM50965.2020.9179556
Balasubramanyam Appina
We propose a complete blind no-reference (NR) image quality assessment algorithm for assessing the perceptual quality of natural stereoscopic (S3D) images. Towards this end, we have generated an intermediate image from the left and right views, and hypothesize that the perceived quality of the S3D view close to that cyclopean image. We perform multi-steerable decomposition on cyclopean images and we compute the naturalness image quality evaluator (NIQE) score [1] and entropy score from each subband. Finally, the primitive quality scores of steerable subbands are pooled to obtain the overall perceptual quality score of an S3D image. The proposed algorithm is evaluated on the LIVE Phase I [2] and LIVE Phase II [3] stereoscopic image datasets and demonstrates its robust performance on both the datasets and across distortions. The proposed algorithm, which is a ‘complete blind’ model (neither requires pristine S3D images nor requires training on human opinion scores), is called the Multi-Orient NIQE based 3D image quality evaluator (MO-NIQE).
{"title":"A ‘Complete Blind’ No-Reference Stereoscopic Image Quality Assessment Algorithm","authors":"Balasubramanyam Appina","doi":"10.1109/SPCOM50965.2020.9179556","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179556","url":null,"abstract":"We propose a complete blind no-reference (NR) image quality assessment algorithm for assessing the perceptual quality of natural stereoscopic (S3D) images. Towards this end, we have generated an intermediate image from the left and right views, and hypothesize that the perceived quality of the S3D view close to that cyclopean image. We perform multi-steerable decomposition on cyclopean images and we compute the naturalness image quality evaluator (NIQE) score [1] and entropy score from each subband. Finally, the primitive quality scores of steerable subbands are pooled to obtain the overall perceptual quality score of an S3D image. The proposed algorithm is evaluated on the LIVE Phase I [2] and LIVE Phase II [3] stereoscopic image datasets and demonstrates its robust performance on both the datasets and across distortions. The proposed algorithm, which is a ‘complete blind’ model (neither requires pristine S3D images nor requires training on human opinion scores), is called the Multi-Orient NIQE based 3D image quality evaluator (MO-NIQE).","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123550399","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 : 2020-07-01DOI: 10.1109/spcom50965.2020.9179616
{"title":"SPCOM 2020 Cover Page","authors":"","doi":"10.1109/spcom50965.2020.9179616","DOIUrl":"https://doi.org/10.1109/spcom50965.2020.9179616","url":null,"abstract":"","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"18 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125632001","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 : 2020-07-01DOI: 10.1109/SPCOM50965.2020.9179550
P. Jain, K. Gurugubelli, A. Vuppala
Language Identification (LID) is an integral part of multilingual speech systems. There are various conditions under which the performance of LID systems are sub-optimal, such as short duration, noise, channel variation, and so on. There has been effort to improve performance under these conditions, but the impact of speaker emotion variation on the performance of LID systems has not been studied. It is observed that the performance of LID systems degrade in the presence of emotional mismatch between train and test conditions. To that effect, we investigated adaptation approaches for improving the performance of LID systems by incorporating emotional utterances in form of adaptation dataset. Hence, we studied a prosody modification technique called Flexible Analysis Synthesis Tool (FAST) to vary the emotional characteristics of an utterance in order to improve the performance, but the results were inconsistent and not satisfactory. In this work, we propose a combination of Recurrent Convolutional Neural Network (RCNN) based architecture with multi stage training methodology, which outperformed state-ofart LID systems such as i-vectors, time delay neural network, long short term memory, and deep neural network x-vector.
{"title":"Towards Emotion Independent Language Identification System","authors":"P. Jain, K. Gurugubelli, A. Vuppala","doi":"10.1109/SPCOM50965.2020.9179550","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179550","url":null,"abstract":"Language Identification (LID) is an integral part of multilingual speech systems. There are various conditions under which the performance of LID systems are sub-optimal, such as short duration, noise, channel variation, and so on. There has been effort to improve performance under these conditions, but the impact of speaker emotion variation on the performance of LID systems has not been studied. It is observed that the performance of LID systems degrade in the presence of emotional mismatch between train and test conditions. To that effect, we investigated adaptation approaches for improving the performance of LID systems by incorporating emotional utterances in form of adaptation dataset. Hence, we studied a prosody modification technique called Flexible Analysis Synthesis Tool (FAST) to vary the emotional characteristics of an utterance in order to improve the performance, but the results were inconsistent and not satisfactory. In this work, we propose a combination of Recurrent Convolutional Neural Network (RCNN) based architecture with multi stage training methodology, which outperformed state-ofart LID systems such as i-vectors, time delay neural network, long short term memory, and deep neural network x-vector.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121190203","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 : 2020-07-01DOI: 10.1109/SPCOM50965.2020.9179529
P. VijithKumarK., B. K. Rai, T. Jacob
The notion of coded caching was introduced by Maddah-Ali and Niesen when they demonstrated the utility of coding in caching systems. Since their seminal work, several schemes have been proposed to characterize optimal memory rate tradeoff to the caching problems. In this paper, we consider the (4, 5) cache network where the server has four files, each of size F bits, and five users are connected to the server through a common shared link. We consider the demands where each file in the server is requested by at least one user. For this cache network, we derive an improved lower bound for the small cache region, where the cache size in the range of $displaystyle frac{1}{5}F$ bits to $displaystyle frac{4}{5}F$ bits. We also introduce a new caching scheme to achieve the memory rate pair $left(displaystyle frac{61}{20},frac{1}{4}right)$. We then derive a new lower bound for the cache region where cache size in the range of $displaystyle frac{61}{20}F$ bits to $displaystyle frac{16}{5}F$ bits to prove the optimality of the proposed scheme.
{"title":"Towards the Exact Memory Rate Tradeoff for the (4,5) Cache Network","authors":"P. VijithKumarK., B. K. Rai, T. Jacob","doi":"10.1109/SPCOM50965.2020.9179529","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179529","url":null,"abstract":"The notion of coded caching was introduced by Maddah-Ali and Niesen when they demonstrated the utility of coding in caching systems. Since their seminal work, several schemes have been proposed to characterize optimal memory rate tradeoff to the caching problems. In this paper, we consider the (4, 5) cache network where the server has four files, each of size F bits, and five users are connected to the server through a common shared link. We consider the demands where each file in the server is requested by at least one user. For this cache network, we derive an improved lower bound for the small cache region, where the cache size in the range of $displaystyle frac{1}{5}F$ bits to $displaystyle frac{4}{5}F$ bits. We also introduce a new caching scheme to achieve the memory rate pair $left(displaystyle frac{61}{20},frac{1}{4}right)$. We then derive a new lower bound for the cache region where cache size in the range of $displaystyle frac{61}{20}F$ bits to $displaystyle frac{16}{5}F$ bits to prove the optimality of the proposed scheme.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124062742","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 : 2020-07-01DOI: 10.1109/SPCOM50965.2020.9179509
Apoorva Chawla, R. Singh, Adarsh Patel, A. Jagannatham
This paper considers a distributed detection framework for millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) wireless sensor networks (WSNs). A hybrid combining based low complexity fusion rule is derived at the fusion center (FC) that also incorporates the local probabilities of detection and false alarm of the individual sensor nodes, thus making it suitable for practical scenarios. Closed-form expressions for the probabilities of detection and false alarm are evaluated to characterize the system performance. Moreover, a deflection coefficient maximization based framework is also developed to determine the signaling matrix that further improves the detection performance of the proposed scheme. Finally, simulation results are presented to demonstrate the performance of the proposed detector and to corroborate the analytical results.
{"title":"Distributed Detection in Millimeter Wave Massive MIMO Wireless Sensor Networks","authors":"Apoorva Chawla, R. Singh, Adarsh Patel, A. Jagannatham","doi":"10.1109/SPCOM50965.2020.9179509","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179509","url":null,"abstract":"This paper considers a distributed detection framework for millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) wireless sensor networks (WSNs). A hybrid combining based low complexity fusion rule is derived at the fusion center (FC) that also incorporates the local probabilities of detection and false alarm of the individual sensor nodes, thus making it suitable for practical scenarios. Closed-form expressions for the probabilities of detection and false alarm are evaluated to characterize the system performance. Moreover, a deflection coefficient maximization based framework is also developed to determine the signaling matrix that further improves the detection performance of the proposed scheme. Finally, simulation results are presented to demonstrate the performance of the proposed detector and to corroborate the analytical results.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127600669","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 : 2020-07-01DOI: 10.1109/SPCOM50965.2020.9179624
G. Ananthi
This paper deals with Simultaneous Extreme Ultra-Violet Information and Power Transfer system (SEUVIPT) for energy harvesting in 6G Mobile networks. The proposed SEUVIPT system consists of EUV photo Light Emitting Diode (LED) at the transmitter and EUV photo detector at the receiver in a high vacuum atmospheric EUV channel. The energy harvesting optimization problem has been formulated for the proposed model using information rate and signal to noise ratio. Power splitting protocol is used for energy harvesting and information transmission. The energy harvesting maximization problem is non-convex. It is converted into convex and an expression for the optimal energy harvesting is derived for the proposed model. Simulation results show that the proposed model increases the harvested energy in SEUVIPT effectively.
{"title":"Simultaneous Extreme Ultraviolet Information and Power Transfer(SEUVIPT)","authors":"G. Ananthi","doi":"10.1109/SPCOM50965.2020.9179624","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179624","url":null,"abstract":"This paper deals with Simultaneous Extreme Ultra-Violet Information and Power Transfer system (SEUVIPT) for energy harvesting in 6G Mobile networks. The proposed SEUVIPT system consists of EUV photo Light Emitting Diode (LED) at the transmitter and EUV photo detector at the receiver in a high vacuum atmospheric EUV channel. The energy harvesting optimization problem has been formulated for the proposed model using information rate and signal to noise ratio. Power splitting protocol is used for energy harvesting and information transmission. The energy harvesting maximization problem is non-convex. It is converted into convex and an expression for the optimal energy harvesting is derived for the proposed model. Simulation results show that the proposed model increases the harvested energy in SEUVIPT effectively.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131627510","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 : 2020-07-01DOI: 10.1109/SPCOM50965.2020.9179507
Satish Kumar Suman, Aniket Dhok, Swapnil Bhole
With the advent of modern smartphones, AR, VR services and advancement in display resolution of mobile devices coupled with real-time streaming services, the demand for highresolution video has boomed. To fulfill this requirement, a variety of Adaptive Bit-Rate Streaming methods for Video-on-Demand applications are employed. However, the use of multi-pass encoding in the aforementioned methods renders them obsolete when it comes to real-time video streaming due to latency restrictions. In this work, we bypass the conventional multiple-encoding used in Video-on-Demand applications and present a novel machinelearning-based approach that estimates the optimal video resolution for a given content at a particular bit-rate for ultra low latency applications. A new feature that captures temporal as well as spatial correlation in video sequence has been used to train the Deep Neural Network (DNN) model. A python-based testbed is designed to evaluate the proposed scheme. Experiment results corroborate the viability and effectiveness of the proposed method for real-time mobile video streaming applications.
{"title":"DNNStream: Deep-learning based Content Adaptive Real-time Streaming","authors":"Satish Kumar Suman, Aniket Dhok, Swapnil Bhole","doi":"10.1109/SPCOM50965.2020.9179507","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179507","url":null,"abstract":"With the advent of modern smartphones, AR, VR services and advancement in display resolution of mobile devices coupled with real-time streaming services, the demand for highresolution video has boomed. To fulfill this requirement, a variety of Adaptive Bit-Rate Streaming methods for Video-on-Demand applications are employed. However, the use of multi-pass encoding in the aforementioned methods renders them obsolete when it comes to real-time video streaming due to latency restrictions. In this work, we bypass the conventional multiple-encoding used in Video-on-Demand applications and present a novel machinelearning-based approach that estimates the optimal video resolution for a given content at a particular bit-rate for ultra low latency applications. A new feature that captures temporal as well as spatial correlation in video sequence has been used to train the Deep Neural Network (DNN) model. A python-based testbed is designed to evaluate the proposed scheme. Experiment results corroborate the viability and effectiveness of the proposed method for real-time mobile video streaming applications.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133485418","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 : 2020-07-01DOI: 10.1109/spcom50965.2020.9179538
{"title":"SPCOM 2020 Copyright Page","authors":"","doi":"10.1109/spcom50965.2020.9179538","DOIUrl":"https://doi.org/10.1109/spcom50965.2020.9179538","url":null,"abstract":"","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129064406","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 : 2020-07-01DOI: 10.1109/SPCOM50965.2020.9179521
Reena Sahu, Kanchan K. Chaurasia, Abhishek K. Gupta
In this paper, we focus on the performance of a broadcast network (single frequency network) including TV broadcasting networks. Since all transmitters in a broadcast network are transmitting the same signal, received signals from multiple transmitters from a certain connectivity region around the user can be combined to improve the coverage at this user. Using tools from stochastic geometry, we provide an analytical framework to derive the SINR and rate coverage of a typical receiver located at the origin. We also validate our analysis via numerical results. We show that rate coverage is affected by the size of the connectivity region and there exists an optimal size of connectivity region that maximizes the rate coverage.
{"title":"SINR and Rate Coverage of Broadcast Networks using Stochastic Geometry","authors":"Reena Sahu, Kanchan K. Chaurasia, Abhishek K. Gupta","doi":"10.1109/SPCOM50965.2020.9179521","DOIUrl":"https://doi.org/10.1109/SPCOM50965.2020.9179521","url":null,"abstract":"In this paper, we focus on the performance of a broadcast network (single frequency network) including TV broadcasting networks. Since all transmitters in a broadcast network are transmitting the same signal, received signals from multiple transmitters from a certain connectivity region around the user can be combined to improve the coverage at this user. Using tools from stochastic geometry, we provide an analytical framework to derive the SINR and rate coverage of a typical receiver located at the origin. We also validate our analysis via numerical results. We show that rate coverage is affected by the size of the connectivity region and there exists an optimal size of connectivity region that maximizes the rate coverage.","PeriodicalId":208527,"journal":{"name":"2020 International Conference on Signal Processing and Communications (SPCOM)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130224591","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：