Pub Date : 2022-11-30DOI: 10.1109/LATINCOM56090.2022.10000572
Marcele O. K. Mendonça, P. Diniz, T. Ferreira
A severe drawback in broadband communications is the inter-symbol interference (ISI) originating from multipath fading, where one widely used solution is the orthogonal frequency-division multiplexing (OFDM) system. OFDM employs a block transmission, giving rise to inter-block interference (IBI) that can be remedied by using redundant elements. The standard solution is to insert a cyclic prefix (CP), whose length is equal to the channel order, and a set of pilots to estimate the channel, consuming, in part, the budgeting spectrum. This work proposes a machine learning (ML) based channel estimator for OFDM receivers operating with reduced redundancy and pilots. Our results confirm that the ML-designed receivers can achieve competitive bit-error-rate (BER) performance, opening new venues to improve spectrum utilization.
{"title":"Machine learning-based channel estimation for insufficient redundancy OFDM receivers using comb-type pilot arrangement","authors":"Marcele O. K. Mendonça, P. Diniz, T. Ferreira","doi":"10.1109/LATINCOM56090.2022.10000572","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000572","url":null,"abstract":"A severe drawback in broadband communications is the inter-symbol interference (ISI) originating from multipath fading, where one widely used solution is the orthogonal frequency-division multiplexing (OFDM) system. OFDM employs a block transmission, giving rise to inter-block interference (IBI) that can be remedied by using redundant elements. The standard solution is to insert a cyclic prefix (CP), whose length is equal to the channel order, and a set of pilots to estimate the channel, consuming, in part, the budgeting spectrum. This work proposes a machine learning (ML) based channel estimator for OFDM receivers operating with reduced redundancy and pilots. Our results confirm that the ML-designed receivers can achieve competitive bit-error-rate (BER) performance, opening new venues to improve spectrum utilization.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130310823","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 : 2022-11-30DOI: 10.1109/LATINCOM56090.2022.10000568
Rogério Pereira Junior, C. Rocha, B. Chang, D. L. Ruyet
Recently, a precoded discrete Fourier transform (DFT) filter bank system was proposed in order to obtain a scheme with better spectral localization, low peak-to-average power ratio (PAPR) and complex orthogonality. Such a scheme does not need to use Offset-Quadrature Amplitude Modulation and can be generalized by changing the waveform, while obtaining robustness in high mobility scenarios. Due to its complex orthogonality, most well-known methods of MIMO-OFDM transmission can be used efficiently. In this work, we will explore the generalization of this system using an iterative receiver and investigate the usage of multiple antennas in reception in high-spreading Doppler scenarios.
{"title":"IB-DFE receiver for generalized SIMO DFT precoded filter bank systems in doubly selective channels","authors":"Rogério Pereira Junior, C. Rocha, B. Chang, D. L. Ruyet","doi":"10.1109/LATINCOM56090.2022.10000568","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000568","url":null,"abstract":"Recently, a precoded discrete Fourier transform (DFT) filter bank system was proposed in order to obtain a scheme with better spectral localization, low peak-to-average power ratio (PAPR) and complex orthogonality. Such a scheme does not need to use Offset-Quadrature Amplitude Modulation and can be generalized by changing the waveform, while obtaining robustness in high mobility scenarios. Due to its complex orthogonality, most well-known methods of MIMO-OFDM transmission can be used efficiently. In this work, we will explore the generalization of this system using an iterative receiver and investigate the usage of multiple antennas in reception in high-spreading Doppler scenarios.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129660722","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 : 2022-11-30DOI: 10.1109/LATINCOM56090.2022.10000454
B. Lima, R. Dinis, D. B. D. Costa, M. Beko, Rodolfo Oliveira, R. Vigelis, M. Debbah
This paper investigates rate-splitting multiple access (RSMA) networks assisted by aerial intelligent reflecting surfaces (AIRS) and assuming a downlink multiple-input single-output (MISO) scenario (AIRS-RSMA) with imperfect successive interference cancelation (SIC). An optimization problem is formulated in order to maximize the total achievable rate by optimizing the transmit beamforming and common achievable rate of the users. By using approximation and transformation techniques, we convert the optimization problem into a semi-definite program (SDP) problem. To solve this problem, an algorithm based on alternating optimization (AO) is proposed to iteratively solve the transmit beamforming problem. Simulation results are provided to demonstrate the efficiency of the proposed method, in which it is revealed that the performance gains in terms of sum-rate of AIRS-RSMA networks with robust beamforming are significantly greater than the non-optimized AIRS-RSMA and conventional non-orthogonal multiple access (NOMA) schemes.
{"title":"Rate-Splitting Multiple Access Networks Assisted by Aerial Intelligent Reflecting Surfaces","authors":"B. Lima, R. Dinis, D. B. D. Costa, M. Beko, Rodolfo Oliveira, R. Vigelis, M. Debbah","doi":"10.1109/LATINCOM56090.2022.10000454","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000454","url":null,"abstract":"This paper investigates rate-splitting multiple access (RSMA) networks assisted by aerial intelligent reflecting surfaces (AIRS) and assuming a downlink multiple-input single-output (MISO) scenario (AIRS-RSMA) with imperfect successive interference cancelation (SIC). An optimization problem is formulated in order to maximize the total achievable rate by optimizing the transmit beamforming and common achievable rate of the users. By using approximation and transformation techniques, we convert the optimization problem into a semi-definite program (SDP) problem. To solve this problem, an algorithm based on alternating optimization (AO) is proposed to iteratively solve the transmit beamforming problem. Simulation results are provided to demonstrate the efficiency of the proposed method, in which it is revealed that the performance gains in terms of sum-rate of AIRS-RSMA networks with robust beamforming are significantly greater than the non-optimized AIRS-RSMA and conventional non-orthogonal multiple access (NOMA) schemes.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"EM-31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126527017","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 : 2022-11-30DOI: 10.1109/LATINCOM56090.2022.10000451
Antonio Rueda Hernández, L. Orozco-Barbosa, Ahmed Boujnoui, J. Camacho-Escoto, Javier Gomez
The IEEE802.11bc working group is currently working on the definition of the enhanced Broadcast Service (eBCS). This new service aims to provide the means to the distribution of local information, such as information announcements, sensor data and multimedia material to large number of users. Among the main challenges to be addressed towards the deployment of the eBCS standard, the Medium Access Mechanism (MAC) plays a major role. In this paper, we introduce Wireless Broadcast Access Protocol (WBAP), a novel MAC protocol addressing the major challenges required to the successful integration of broadcast services into the IEEE802.11 protocol stack. The paper includes a detailed description and a performance evaluation of our proposal. Our results show that WBAP is a promising solution to the deployment of the eBCS.
{"title":"WBAP: A Wireless Broadcast Access Protocol for the IEEE802.11bc Enhanced Broadcast Service","authors":"Antonio Rueda Hernández, L. Orozco-Barbosa, Ahmed Boujnoui, J. Camacho-Escoto, Javier Gomez","doi":"10.1109/LATINCOM56090.2022.10000451","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000451","url":null,"abstract":"The IEEE802.11bc working group is currently working on the definition of the enhanced Broadcast Service (eBCS). This new service aims to provide the means to the distribution of local information, such as information announcements, sensor data and multimedia material to large number of users. Among the main challenges to be addressed towards the deployment of the eBCS standard, the Medium Access Mechanism (MAC) plays a major role. In this paper, we introduce Wireless Broadcast Access Protocol (WBAP), a novel MAC protocol addressing the major challenges required to the successful integration of broadcast services into the IEEE802.11 protocol stack. The paper includes a detailed description and a performance evaluation of our proposal. Our results show that WBAP is a promising solution to the deployment of the eBCS.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131676564","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 : 2022-11-30DOI: 10.1109/LATINCOM56090.2022.10000783
Daniel Suzuki, A. Oliveira, Luan Gonçalves, I. Correa, A. Klautau, Silvia Lins, Pedro Batista
Machine learning has become a powerful tool for improving vehicle-to-vehicle (V2V) communication systems, and in general requires large datasets for model training and assessment. However, creating large and realistic datasets using field measurements is challenging due to the large bandwidths involved and usage of multiple antennas. Simulations have been widely adopted to circumvent the relative high cost of measurement campaigns. This paper presents the development of a new public dataset for research within V2V scenarios, of machine learning algorithms that require the MIMO channel for simulation or emulation. The adopted methodology relies on realistic simulations of vehicles traffic in 3D virtual worlds. The paper also analyses the influence of key parameters in the ray-tracing simulation with respect to the tradeoff between accuracy and computational cost. Lastly, the paper discusses results of beam-selection for V2V using machine learning and the presented dataset.
{"title":"Ray-Tracing MIMO Channel Dataset for Machine Learning Applied to V2V Communication","authors":"Daniel Suzuki, A. Oliveira, Luan Gonçalves, I. Correa, A. Klautau, Silvia Lins, Pedro Batista","doi":"10.1109/LATINCOM56090.2022.10000783","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000783","url":null,"abstract":"Machine learning has become a powerful tool for improving vehicle-to-vehicle (V2V) communication systems, and in general requires large datasets for model training and assessment. However, creating large and realistic datasets using field measurements is challenging due to the large bandwidths involved and usage of multiple antennas. Simulations have been widely adopted to circumvent the relative high cost of measurement campaigns. This paper presents the development of a new public dataset for research within V2V scenarios, of machine learning algorithms that require the MIMO channel for simulation or emulation. The adopted methodology relies on realistic simulations of vehicles traffic in 3D virtual worlds. The paper also analyses the influence of key parameters in the ray-tracing simulation with respect to the tradeoff between accuracy and computational cost. Lastly, the paper discusses results of beam-selection for V2V using machine learning and the presented dataset.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128026049","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 : 2022-11-30DOI: 10.1109/latincom56090.2022.10000580
{"title":"LATINCOM 2022 Message from the TPC Chairs","authors":"","doi":"10.1109/latincom56090.2022.10000580","DOIUrl":"https://doi.org/10.1109/latincom56090.2022.10000580","url":null,"abstract":"","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131334736","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 : 2022-11-30DOI: 10.1109/LATINCOM56090.2022.10000496
J. Vieira, D. Passos
Performance estimation can be used to improve IEEE 802.11 networks. Not only can it be used when designing the network to find a suitable number of APs to cover an area, but it can also be applied to several performance-maintaining tasks, such as load-balancing and interference control. MAPE is a framework that can provide good throughput estimations in multi-hop IEEE 802.11 networks. However, dense, interference-prone scenarios have an inherently higher complexity due to the number of interactions between the transmitting nodes. Since the original proposal of MAPE does not consider the interference between concurrent transmissions, its accuracy tends to decrease in such scenarios. This work focuses on enhancing MAPE by proposing several changes that model extra network interactions to improve its accuracy in dense IEEE 802.11 networks while maintaining short execution times. The evaluation of this enhanced version, called E-AFTER, shows a 158% increase in correlation between the estimates and the actual network performance and the reduction of estimation error in comparison to the original MAPE.
{"title":"Estimating performance in dense IEEE 802.11 networks with E-AFTER","authors":"J. Vieira, D. Passos","doi":"10.1109/LATINCOM56090.2022.10000496","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000496","url":null,"abstract":"Performance estimation can be used to improve IEEE 802.11 networks. Not only can it be used when designing the network to find a suitable number of APs to cover an area, but it can also be applied to several performance-maintaining tasks, such as load-balancing and interference control. MAPE is a framework that can provide good throughput estimations in multi-hop IEEE 802.11 networks. However, dense, interference-prone scenarios have an inherently higher complexity due to the number of interactions between the transmitting nodes. Since the original proposal of MAPE does not consider the interference between concurrent transmissions, its accuracy tends to decrease in such scenarios. This work focuses on enhancing MAPE by proposing several changes that model extra network interactions to improve its accuracy in dense IEEE 802.11 networks while maintaining short execution times. The evaluation of this enhanced version, called E-AFTER, shows a 158% increase in correlation between the estimates and the actual network performance and the reduction of estimation error in comparison to the original MAPE.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133737304","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 : 2022-11-30DOI: 10.1109/LATINCOM56090.2022.10000517
N. C. Matson, J. Camp, D. Rajan
In this paper, we use the results of an in-field air-to-air (A2A) channel sounding experiment to build a model of the channel over the full range of azimuth and elevation angles. We use said model to analyze the effect antenna orientation and UAV relative position have on channel magnitude. First, we quantity the different ways in which the UAV body can alter the radiation pattern of a dipole antenna depending on whether the antenna is perpendicular or parallel to the body of the UAV. Then, we analyze the effect that change in the radiation pattern has on the cross-polarization discrimination (XPD). Finally, we calculate the overlapping index, a distance measure, between the distribution of channel magnitude in two symmetric regions of 3D space and observe that the two distributions are further apart when the receiver (Rx) is below the transmitter (Tx), suggesting an asymmetry in the way the Tx and Rx UAV body affect the channel.
{"title":"Effect of Antenna Orientation and UAV Position on UAV Communications in 3D Space","authors":"N. C. Matson, J. Camp, D. Rajan","doi":"10.1109/LATINCOM56090.2022.10000517","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000517","url":null,"abstract":"In this paper, we use the results of an in-field air-to-air (A2A) channel sounding experiment to build a model of the channel over the full range of azimuth and elevation angles. We use said model to analyze the effect antenna orientation and UAV relative position have on channel magnitude. First, we quantity the different ways in which the UAV body can alter the radiation pattern of a dipole antenna depending on whether the antenna is perpendicular or parallel to the body of the UAV. Then, we analyze the effect that change in the radiation pattern has on the cross-polarization discrimination (XPD). Finally, we calculate the overlapping index, a distance measure, between the distribution of channel magnitude in two symmetric regions of 3D space and observe that the two distributions are further apart when the receiver (Rx) is below the transmitter (Tx), suggesting an asymmetry in the way the Tx and Rx UAV body affect the channel.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130917129","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 : 2022-11-30DOI: 10.1109/LATINCOM56090.2022.10000431
Farimasadat Miri, Alireza A. Namanloo, A. M. Souza, R. Pazzi
Location prediction is essential for location-based applications such as route recommendation systems, resource allocation optimization in congested areas, congestion avoidance, traffic management, just to mention a few. Knowing approximate vehicle locations can enhance our ability to better manage and prepare the existing mobile edge computing resources in a Vehicular ad hoc network. In this paper, we focus on a graph neural network model to estimate vehicle locations in a timely manner. We first model the vehicle locations based on events that happen between different regions of an area and the car itself. Leveraging our event-based model, we introduce Temporal Location Prediction (TLP) to capture essential features from each node, edges, and neighboring nodes to achieve timely location prediction. Afterwards, instead of using GPS coordinates as input, we demonstrate a new data structure to feed Bidirectional LSTM (BiLSTM) and LSTM for vehicle location prediction in different time intervals. Thus, our main contribution is a network model that utilizes a Temporal Graph neural network for dynamic location prediction. We explain the advantages and disadvantages of each model and how we can improve them. Our experiments on a real dataset show that our model (TLP) outperforms LSTM and BiLSTM in short-term prediction, considering the same scenario and conditions.
{"title":"A Novel Short-term Vehicle Location Prediction using Temporal Graph Neural Networks","authors":"Farimasadat Miri, Alireza A. Namanloo, A. M. Souza, R. Pazzi","doi":"10.1109/LATINCOM56090.2022.10000431","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000431","url":null,"abstract":"Location prediction is essential for location-based applications such as route recommendation systems, resource allocation optimization in congested areas, congestion avoidance, traffic management, just to mention a few. Knowing approximate vehicle locations can enhance our ability to better manage and prepare the existing mobile edge computing resources in a Vehicular ad hoc network. In this paper, we focus on a graph neural network model to estimate vehicle locations in a timely manner. We first model the vehicle locations based on events that happen between different regions of an area and the car itself. Leveraging our event-based model, we introduce Temporal Location Prediction (TLP) to capture essential features from each node, edges, and neighboring nodes to achieve timely location prediction. Afterwards, instead of using GPS coordinates as input, we demonstrate a new data structure to feed Bidirectional LSTM (BiLSTM) and LSTM for vehicle location prediction in different time intervals. Thus, our main contribution is a network model that utilizes a Temporal Graph neural network for dynamic location prediction. We explain the advantages and disadvantages of each model and how we can improve them. Our experiments on a real dataset show that our model (TLP) outperforms LSTM and BiLSTM in short-term prediction, considering the same scenario and conditions.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114356342","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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