Pub Date : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631755
Ran Sun, H. Habuchi, Y. Kozawa
As typical binary modulation schemes for the intensity modulation / direct detection (IM/DD) optical wireless communication, on-off keying (OOK) and binary pulse position modulation (BPPM) are well known. Although OOK has higher transmission efficiency than BPPM, BPPM is superior to OOK in terms of communication reliability. It is expected to create a better modulation scheme by fusing OOK and PPM. In this paper, an optical wireless turbo coded system using a new signalling scheme called hybrid PPM-OOK signalling (HPOS) is proposed. The information bit stream of the turbo coded system is represented by PPM signalling and the parity bit streams are indicated by OOK signalling. The decision for OOK is optimized via the PPM signal. The proposed system is evaluated through computer simulation in optical wireless channel. The effective information rate performances (i.e. channel capacity) of the proposed system are compared with those of the conventional OOK turbo coded system and BPPM turbo coded system. As results, the proposed system outperforms the conventional OOK system and BPPM system.
{"title":"Proposal of Optical Wireless Turbo Coded System with Hybrid PPM-OOK Signalling","authors":"Ran Sun, H. Habuchi, Y. Kozawa","doi":"10.1109/ICSPCS.2018.8631755","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631755","url":null,"abstract":"As typical binary modulation schemes for the intensity modulation / direct detection (IM/DD) optical wireless communication, on-off keying (OOK) and binary pulse position modulation (BPPM) are well known. Although OOK has higher transmission efficiency than BPPM, BPPM is superior to OOK in terms of communication reliability. It is expected to create a better modulation scheme by fusing OOK and PPM. In this paper, an optical wireless turbo coded system using a new signalling scheme called hybrid PPM-OOK signalling (HPOS) is proposed. The information bit stream of the turbo coded system is represented by PPM signalling and the parity bit streams are indicated by OOK signalling. The decision for OOK is optimized via the PPM signal. The proposed system is evaluated through computer simulation in optical wireless channel. The effective information rate performances (i.e. channel capacity) of the proposed system are compared with those of the conventional OOK turbo coded system and BPPM turbo coded system. As results, the proposed system outperforms the conventional OOK system and BPPM system.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133278412","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}
Waveforms classification is an important task in many applications such as disease diagnosis, earthquake prediction and speech recognition. In this paper, a sparse representation based method is proposed for waveforms classification. Firstly, K singular value decomposition (K-SVD) method is applied to each class of training samples to obtain a corresponding dictionary. Then, for a test sample, it is sparsely represented and reconstructed by each dictionary respectively, and assign it to the class with the smallest reconstruction error. To verify the classification ability of the proposed method, two experiments on both simulated and real-world data sets are conducted. The final experimental results demonstrate that our proposed method can obtain a good performance in terms of the classification accuracy and noise tolerance.
{"title":"Sparse Representation for Waveforms Classification","authors":"Shanzhu Xiao, Bendong Zhao, Huan-zhang Lu, Dongya Wu","doi":"10.1109/ICSPCS.2018.8631717","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631717","url":null,"abstract":"Waveforms classification is an important task in many applications such as disease diagnosis, earthquake prediction and speech recognition. In this paper, a sparse representation based method is proposed for waveforms classification. Firstly, K singular value decomposition (K-SVD) method is applied to each class of training samples to obtain a corresponding dictionary. Then, for a test sample, it is sparsely represented and reconstructed by each dictionary respectively, and assign it to the class with the smallest reconstruction error. To verify the classification ability of the proposed method, two experiments on both simulated and real-world data sets are conducted. The final experimental results demonstrate that our proposed method can obtain a good performance in terms of the classification accuracy and noise tolerance.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116509385","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 : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631723
Ryohei Iwasaki, K. Ohuchi
An orthogonal frequency division multiplexing (OFDM) signal has the drawback of a high peak-to-average power ratio (PAPR). A precoding method is proposed for PAPR reduction. In this method, a low PAPR signal is generated through multiplication by a matrix generated from a certain sequence and data symbol vector. The PAPR reduction achieved by this method is constant even when we use another matrix generated by a different parameter. The partial transmit sequences (PTS) method is another PAPR reduction method. In the PTS method, subcarriers that constitute an OFDM signal are partitioned into clusters. Then, the time-domain signals of each cluster are individually given phase rotations, and we select the OFDM signal with the lowest PAPR. This method does not cause a non-linear distortion because of linear processing. Numerous clusters and phase rotations are required, and the calculation burden becomes enormous to increase the PAPR reduction. In this paper, we show how both methods can be combined for the purpose of further reducing the PAPR. This paper shows that the PAPR reduction of the proposed method is better than that of the PTS or precoding methods separately. We also show that the proposed method can increase the PAPR reduction by increasing the number of candidate signals, as in the PTS method. Moreover, the proposed method can greatly reduce the number of candidate signals needed to achieve the same reduction.
{"title":"PAPR Reduction in OFDM Signal by Combining Partial Transmit Sequences with Precoding Matrix","authors":"Ryohei Iwasaki, K. Ohuchi","doi":"10.1109/ICSPCS.2018.8631723","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631723","url":null,"abstract":"An orthogonal frequency division multiplexing (OFDM) signal has the drawback of a high peak-to-average power ratio (PAPR). A precoding method is proposed for PAPR reduction. In this method, a low PAPR signal is generated through multiplication by a matrix generated from a certain sequence and data symbol vector. The PAPR reduction achieved by this method is constant even when we use another matrix generated by a different parameter. The partial transmit sequences (PTS) method is another PAPR reduction method. In the PTS method, subcarriers that constitute an OFDM signal are partitioned into clusters. Then, the time-domain signals of each cluster are individually given phase rotations, and we select the OFDM signal with the lowest PAPR. This method does not cause a non-linear distortion because of linear processing. Numerous clusters and phase rotations are required, and the calculation burden becomes enormous to increase the PAPR reduction. In this paper, we show how both methods can be combined for the purpose of further reducing the PAPR. This paper shows that the PAPR reduction of the proposed method is better than that of the PTS or precoding methods separately. We also show that the proposed method can increase the PAPR reduction by increasing the number of candidate signals, as in the PTS method. Moreover, the proposed method can greatly reduce the number of candidate signals needed to achieve the same reduction.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124945366","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 : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631753
Himanshu Soni, Alice P. Bates, R. Kennedy
In this work, we propose a method for the derivation of prolate spheroidal wave functions (PSWFs) and Slepian functions on continuous and disjoint intervals on the real number line. The proposed method uses Fourier series to obtain a closed-form approximation for Slepian functions on the real line. With this closed-form expression, Slepian functions can be evaluated at arbitrary points in the region of interest with high accuracy. The conventional method uses properties of the Slepian concentration problem to evaluate PSWFs on finite number of points in an interval. The conventional method is computationally expensive and does not allow for easy storage. By approximating an interval containing regions of interest as periodic, we express the Slepian concentration problem as a finite dimensional problem using the Fourier series domain. Solutions to the Slepian concentration problem in this form are Fourier series coefficients corresponding to the Slepian functions. Reconstruction in Fourier series basis, scaling and subsequent truncation provides the closed-form expression for the Slepian problem. Upon comparison with PSWFs obtained by the conventional method, we find negligible difference.
{"title":"Efficient Computation of Slepian Functions on the Real Line","authors":"Himanshu Soni, Alice P. Bates, R. Kennedy","doi":"10.1109/ICSPCS.2018.8631753","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631753","url":null,"abstract":"In this work, we propose a method for the derivation of prolate spheroidal wave functions (PSWFs) and Slepian functions on continuous and disjoint intervals on the real number line. The proposed method uses Fourier series to obtain a closed-form approximation for Slepian functions on the real line. With this closed-form expression, Slepian functions can be evaluated at arbitrary points in the region of interest with high accuracy. The conventional method uses properties of the Slepian concentration problem to evaluate PSWFs on finite number of points in an interval. The conventional method is computationally expensive and does not allow for easy storage. By approximating an interval containing regions of interest as periodic, we express the Slepian concentration problem as a finite dimensional problem using the Fourier series domain. Solutions to the Slepian concentration problem in this form are Fourier series coefficients corresponding to the Slepian functions. Reconstruction in Fourier series basis, scaling and subsequent truncation provides the closed-form expression for the Slepian problem. Upon comparison with PSWFs obtained by the conventional method, we find negligible difference.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"332 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122841945","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 : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631787
O. Oyerinde
Multiuser detection schemes are essential in any multiuser user access technology. Their importance cannot be over emphasized in a non-orthogonal multiple access (NOMA) system, a multiuser access technology that has been proposed for the fifth generation (5G) wireless networks. This paper proposed a multiuser detection (MUD) scheme, named the modified subspace pursuit (SP)-based MUD, for use in uplink grant free NOMA systems. In developing the scheme, temporary correlation of active user sets between adjacent time slots together with side information, a-priori knowledge of the active user support set's estimate, are exploited. The proposed MUD performs signal detection in a continuous time slots while user activities changes within a transmission frame in contrast to the traditional orthogonal matching pursuit (OMP)-based MUD that performs similar detection with the assumption that user activity remains unchanged within a whole frame. Computer simulation results show that the proposed modified SP-based MUD achieves better performance in comparison with the performances of the traditional OMP-based MUD and its variant, the computational efficient OMP-based MUD considered in this paper.
{"title":"Multiuser Detector for Uplink Grant Free NOMA Systems Based on Modified Subspace Pursuit Algorithm","authors":"O. Oyerinde","doi":"10.1109/ICSPCS.2018.8631787","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631787","url":null,"abstract":"Multiuser detection schemes are essential in any multiuser user access technology. Their importance cannot be over emphasized in a non-orthogonal multiple access (NOMA) system, a multiuser access technology that has been proposed for the fifth generation (5G) wireless networks. This paper proposed a multiuser detection (MUD) scheme, named the modified subspace pursuit (SP)-based MUD, for use in uplink grant free NOMA systems. In developing the scheme, temporary correlation of active user sets between adjacent time slots together with side information, a-priori knowledge of the active user support set's estimate, are exploited. The proposed MUD performs signal detection in a continuous time slots while user activities changes within a transmission frame in contrast to the traditional orthogonal matching pursuit (OMP)-based MUD that performs similar detection with the assumption that user activity remains unchanged within a whole frame. Computer simulation results show that the proposed modified SP-based MUD achieves better performance in comparison with the performances of the traditional OMP-based MUD and its variant, the computational efficient OMP-based MUD considered in this paper.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132517013","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 : 2018-12-01DOI: 10.1109/ICSPCS.2018.8631764
Timothy Roberts, K. Paliwal
Current Time-Scale Modification algorithms scale all frequencies by the same amount. This paper presents an efficient method and implementation for time scaling of arbitrary frequency regions, called Frequency Dependent Time-Scale Modification. This is achieved by creating a composite frequency spectrum frame before using traditional frequency domain time-scaling methods. Testing was undertaken with results presented from varied processing of 3 files. Links to and description of a MATLAB implementation are provided. Availability: A MATLAB software implementation can be found on Github at github.com/zygurt/TSM.
{"title":"Frequency Dependent Time-Scale Modification","authors":"Timothy Roberts, K. Paliwal","doi":"10.1109/ICSPCS.2018.8631764","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631764","url":null,"abstract":"Current Time-Scale Modification algorithms scale all frequencies by the same amount. This paper presents an efficient method and implementation for time scaling of arbitrary frequency regions, called Frequency Dependent Time-Scale Modification. This is achieved by creating a composite frequency spectrum frame before using traditional frequency domain time-scaling methods. Testing was undertaken with results presented from varied processing of 3 files. Links to and description of a MATLAB implementation are provided. Availability: A MATLAB software implementation can be found on Github at github.com/zygurt/TSM.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"254 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126263042","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 : 2018-10-15DOI: 10.1109/ICSPCS.2018.8631781
Michaela Novosadová, P. Rajmic
Used in the paper is an overcomplete piecewise-polynomial image model incorporating sparsity. The paper shows that using such a model, the edges in the image can be resolved robustly with respect to noise. Two variants of the proposed approach are both shown to be superior to the use of the classic edge detecting kernels. The proposed method is in turn also suitable for image segmentation.
{"title":"Image Edges Resolved Well When Using an Overcomplete Piecewise-Polynomial Model","authors":"Michaela Novosadová, P. Rajmic","doi":"10.1109/ICSPCS.2018.8631781","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631781","url":null,"abstract":"Used in the paper is an overcomplete piecewise-polynomial image model incorporating sparsity. The paper shows that using such a model, the edges in the image can be resolved robustly with respect to noise. Two variants of the proposed approach are both shown to be superior to the use of the classic edge detecting kernels. The proposed method is in turn also suitable for image segmentation.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127244709","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 : 2018-07-10DOI: 10.1109/ICSPCS.2018.8631749
I. Shakeel, I. Ahmad, Hajime Suzuki
One of the challenges often faced with wireless communication systems is its limited range and data-rate. Distributed Transmit Beamforming (DTB) techniques are being developed to address these two issues to provide reliable connectivity from power-limited distributed users. This paper proposes an adaptive Low Density Parity Check (LDPC) coding scheme for the DTB system. The proposed scheme constructs powerful LDPC codes with varying code-rates and block-lengths. This feature of the proposed scheme allows the DTB system to optimise its system resources, improve throughput and communicate reliably under large variation of different channel environments. The performance of some of the codes constructed using the proposed scheme is evaluated and compared with the uncoded and other coded-DTB systems. The results obtained show large gains over the compared systems. The results also show that coding applied to the DTB system drastically reduces the minimum number of distributed transmit nodes required to achieve a target error-rate with the same energy per information bit to noise power spectral density (Eb/N0).
{"title":"Construction of Adaptive Short LDPC Codes for Distributed Transmit Beamforming","authors":"I. Shakeel, I. Ahmad, Hajime Suzuki","doi":"10.1109/ICSPCS.2018.8631749","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631749","url":null,"abstract":"One of the challenges often faced with wireless communication systems is its limited range and data-rate. Distributed Transmit Beamforming (DTB) techniques are being developed to address these two issues to provide reliable connectivity from power-limited distributed users. This paper proposes an adaptive Low Density Parity Check (LDPC) coding scheme for the DTB system. The proposed scheme constructs powerful LDPC codes with varying code-rates and block-lengths. This feature of the proposed scheme allows the DTB system to optimise its system resources, improve throughput and communicate reliably under large variation of different channel environments. The performance of some of the codes constructed using the proposed scheme is evaluated and compared with the uncoded and other coded-DTB systems. The results obtained show large gains over the compared systems. The results also show that coding applied to the DTB system drastically reduces the minimum number of distributed transmit nodes required to achieve a target error-rate with the same energy per information bit to noise power spectral density (Eb/N0).","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132684440","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 : 2018-06-01DOI: 10.1109/ICSPCS.2018.8631773
Nazreen P.M., A. Ramakrishnan
In this work, we propose the use of dropout as a Bayesian estimator for increasing the generalizability of a deep neural network (DNN) for speech enhancement. By using Monte Carlo (MC) dropout, we explore whether the DNN can accomplish better enhancement in unseen noisy conditions. Two DNNs are trained on speech corrupted with five different noises at three SNRs, one using conventional dropout and other with MC dropout and tested on speech with unseen noises. Speech samples are obtained from the TIMIT database and noises from NOISEX-92. In another experiment, we train five DNN models separately on speech corrupted with five different noises, at three SNRs. The model precision estimated using MC dropout is used as a proxy for squared error to dynamically select the best of the DNN models based on their performance on each frame of test data. The first set of experiments aims at improving the performance of an existing DNN with conventional dropout for unseen noises, by replacing the conventional dropout with MC dropout. The second set of experiments aims at finding an optimal way of choosing the best DNN model for de-noising when multiple noise-specific DNN models are available, for unseen noisy conditions.
{"title":"DNN Based Speech Enhancement for Unseen Noises Using Monte Carlo Dropout","authors":"Nazreen P.M., A. Ramakrishnan","doi":"10.1109/ICSPCS.2018.8631773","DOIUrl":"https://doi.org/10.1109/ICSPCS.2018.8631773","url":null,"abstract":"In this work, we propose the use of dropout as a Bayesian estimator for increasing the generalizability of a deep neural network (DNN) for speech enhancement. By using Monte Carlo (MC) dropout, we explore whether the DNN can accomplish better enhancement in unseen noisy conditions. Two DNNs are trained on speech corrupted with five different noises at three SNRs, one using conventional dropout and other with MC dropout and tested on speech with unseen noises. Speech samples are obtained from the TIMIT database and noises from NOISEX-92. In another experiment, we train five DNN models separately on speech corrupted with five different noises, at three SNRs. The model precision estimated using MC dropout is used as a proxy for squared error to dynamically select the best of the DNN models based on their performance on each frame of test data. The first set of experiments aims at improving the performance of an existing DNN with conventional dropout for unseen noises, by replacing the conventional dropout with MC dropout. The second set of experiments aims at finding an optimal way of choosing the best DNN model for de-noising when multiple noise-specific DNN models are available, for unseen noisy conditions.","PeriodicalId":179948,"journal":{"name":"2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127269372","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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