Pub Date : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9652981
Farah Arabian, M. Rice
This paper examines the relationship between polarization diversity combining and equalization in the context of aeronautical mobile telemetry (AMT). The receive antennas currently used in AMT combine the linear polarizations using a 90° hybrid coupler to synthesize circularly polarized signals. Maximum likelihood (ML) polarization combining is developed for this application. Computer simulation results show that equalizing an ML combined channel achieves a lower bit error rate than equalizing circularly combined signals. The performance improvement is achieved at the cost of estimating the channel.
{"title":"Polarization Combining and Equalization for Aeronautical Mobile Telemetry","authors":"Farah Arabian, M. Rice","doi":"10.1109/MILCOM52596.2021.9652981","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9652981","url":null,"abstract":"This paper examines the relationship between polarization diversity combining and equalization in the context of aeronautical mobile telemetry (AMT). The receive antennas currently used in AMT combine the linear polarizations using a 90° hybrid coupler to synthesize circularly polarized signals. Maximum likelihood (ML) polarization combining is developed for this application. Computer simulation results show that equalizing an ML combined channel achieves a lower bit error rate than equalizing circularly combined signals. The performance improvement is achieved at the cost of estimating the channel.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130734873","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 : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9653046
Xavier Leturc, Elie Janin, C. Martret
In this paper, we present results coming from the Multi bAnd Efficient Networks for Ad hoc communications (MAENA) project. We present a distributed dynamic channel assignment (DDCA) algorithm for military clustered ad hoc networks that has been designed during the project. To design the proposed algorithm, we start from an existing algorithm called greedy based dynamic channel assignment (GBDCA). We first identify the main drawbacks of this algorithm, and then we propose modifications to alleviate these drawbacks yielding the proposed GBDCA++ solution. We also explain how to implement the GBDCA++ algorithm in a military waveform developed in the MAENA project. Finally, we show the superiority of GBDCA++ over GBDCA by providing high fidelity simulation results obtained using the simulator developed within the framework of the MAENA project.
{"title":"Distributed Dynamic Channel Assignment in Military Ad Hoc Networks within the MAENA Project: New Algorithm and High Fidelity Simulation Results","authors":"Xavier Leturc, Elie Janin, C. Martret","doi":"10.1109/MILCOM52596.2021.9653046","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9653046","url":null,"abstract":"In this paper, we present results coming from the Multi bAnd Efficient Networks for Ad hoc communications (MAENA) project. We present a distributed dynamic channel assignment (DDCA) algorithm for military clustered ad hoc networks that has been designed during the project. To design the proposed algorithm, we start from an existing algorithm called greedy based dynamic channel assignment (GBDCA). We first identify the main drawbacks of this algorithm, and then we propose modifications to alleviate these drawbacks yielding the proposed GBDCA++ solution. We also explain how to implement the GBDCA++ algorithm in a military waveform developed in the MAENA project. Finally, we show the superiority of GBDCA++ over GBDCA by providing high fidelity simulation results obtained using the simulator developed within the framework of the MAENA project.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116939652","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 : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9653072
Wenhan Zhang, M. Krunz, G. Ditzler
Deep neural networks (DNNs) have recently been applied in the classification of radio frequency (RF) signals. One use case of interest relates to the discernment between different wireless technologies that share the spectrum. Although highly accurate DNN classifiers have been proposed, preliminary research points to the vulnerability of these classifiers to adversarial machine learning (AML) attacks. In one such attack, a surrogate DNN model is trained by the attacker to produce intelligently crafted low-power “perturbations” that degrade the classification accuracy of the legitimate classifier. In this paper, we design four DNN-based classifiers for the identification of Wi-Fi, 5G NR-Unlicensed (NR-U), and LTE LAA transmissions over the 5 GHz UNII bands. Our DNN models include both convolutional neural networks (CNNs) as well as several recurrent neural networks (RNNs) models, particularly LSTM and Bidirectional LSTM (BiLSTM) networks. We demonstrate the high classification accuracy of these models under “benign” (non-adversarial) noise. We then study the efficacy of these classifiers under AML-based perturbations. Specifically, we use the fast gradient sign method (FGSM) to generate adversarial perturbations. Different attack scenarios are studied, depending on how much information the attacker has about the defender's classifier. In one extreme scenario, called “white-box” attack, the attacker has full knowledge of the defender's DNN, including its hyperparameters, its training dataset, and even the seeds used to train the network. This attack is shown to significantly degrade the classification accuracy even when the FGSM-based perturbations are low power, i.e., the received SNR is relatively high. We then consider more realistic attack scenarios, where the attacker has partial or no knowledge of the defender's classifier. Even under limited knowledge, adversarial perturbations can still lead to significant reduction in the classification accuracy, relative to classification under AWGN with the same SNR level.
{"title":"Intelligent Jamming of Deep Neural Network Based Signal Classification for Shared Spectrum","authors":"Wenhan Zhang, M. Krunz, G. Ditzler","doi":"10.1109/MILCOM52596.2021.9653072","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9653072","url":null,"abstract":"Deep neural networks (DNNs) have recently been applied in the classification of radio frequency (RF) signals. One use case of interest relates to the discernment between different wireless technologies that share the spectrum. Although highly accurate DNN classifiers have been proposed, preliminary research points to the vulnerability of these classifiers to adversarial machine learning (AML) attacks. In one such attack, a surrogate DNN model is trained by the attacker to produce intelligently crafted low-power “perturbations” that degrade the classification accuracy of the legitimate classifier. In this paper, we design four DNN-based classifiers for the identification of Wi-Fi, 5G NR-Unlicensed (NR-U), and LTE LAA transmissions over the 5 GHz UNII bands. Our DNN models include both convolutional neural networks (CNNs) as well as several recurrent neural networks (RNNs) models, particularly LSTM and Bidirectional LSTM (BiLSTM) networks. We demonstrate the high classification accuracy of these models under “benign” (non-adversarial) noise. We then study the efficacy of these classifiers under AML-based perturbations. Specifically, we use the fast gradient sign method (FGSM) to generate adversarial perturbations. Different attack scenarios are studied, depending on how much information the attacker has about the defender's classifier. In one extreme scenario, called “white-box” attack, the attacker has full knowledge of the defender's DNN, including its hyperparameters, its training dataset, and even the seeds used to train the network. This attack is shown to significantly degrade the classification accuracy even when the FGSM-based perturbations are low power, i.e., the received SNR is relatively high. We then consider more realistic attack scenarios, where the attacker has partial or no knowledge of the defender's classifier. Even under limited knowledge, adversarial perturbations can still lead to significant reduction in the classification accuracy, relative to classification under AWGN with the same SNR level.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128193018","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 : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9653084
Caleb Bowers, J. Macker, Jeffery W. Weston, B. Adamson
As autonomous systems, sensors, and heterogeneous wireless platforms become increasingly interconnected and networked at the tactical edge, the performance of event-driven data sharing amongst groups of nodes becomes more central to effective operations. Event-driven architectures (EDA) are a means to better manage these events and distribute them across a network. The unique deployment constraints and group messaging requirements of tactical networks, however, create technical challenges for current state-of-the-art EDA solutions that often rely on excessive EDA management traffic and depend on unicast transport protocols. To examine group-centric EDA enhancements, we present an evaluation of multicast transport and forwarding technologies using the Zero Message Queuing (ZMQ) EDA socket library in emulated tactical network environments. Using ZMQ to generate group-based messages overtop a multicast transport layer coupled with efficient multicast packet forwarding techniques, we observe improved EDA message delivery and a reduction in overall network traffic load. While this is an initial study, our early results motivate continued work and enhancements to both the underlying network transport and EDA application design.
{"title":"Multicast Enhancements to Event-Driven Tactical Networking","authors":"Caleb Bowers, J. Macker, Jeffery W. Weston, B. Adamson","doi":"10.1109/MILCOM52596.2021.9653084","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9653084","url":null,"abstract":"As autonomous systems, sensors, and heterogeneous wireless platforms become increasingly interconnected and networked at the tactical edge, the performance of event-driven data sharing amongst groups of nodes becomes more central to effective operations. Event-driven architectures (EDA) are a means to better manage these events and distribute them across a network. The unique deployment constraints and group messaging requirements of tactical networks, however, create technical challenges for current state-of-the-art EDA solutions that often rely on excessive EDA management traffic and depend on unicast transport protocols. To examine group-centric EDA enhancements, we present an evaluation of multicast transport and forwarding technologies using the Zero Message Queuing (ZMQ) EDA socket library in emulated tactical network environments. Using ZMQ to generate group-based messages overtop a multicast transport layer coupled with efficient multicast packet forwarding techniques, we observe improved EDA message delivery and a reduction in overall network traffic load. While this is an initial study, our early results motivate continued work and enhancements to both the underlying network transport and EDA application design.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133932102","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 : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9652948
Saeed Kaviani, Bo Ryu, E. Ahmed, Kevin Larson, Anh-Ngoc Le, Alex Yahja, J. H. Kim
Highly dynamic mobile ad-hoc networks (MANETs) remain as one of the most challenging environments to develop and deploy robust, efficient, and scalable routing protocols. In this paper, we present DeepCQ+ routing protocol which, in a novel manner, integrates emerging multi-agent deep reinforcement learning (MADRL) techniques into existing Q-learning-based routing protocols and their variants, and achieves persistently higher performance across a wide range of topology and mobility configurations. While keeping the overall protocol structure of the Q-learning-based routing protocols, DeepCQ+ replaces statically configured parameterized thresholds and hand-written rules with carefully designed MADRL agents such that no configuration of such parameters is required a priori. Extensive simulation shows that DeepCQ+ yields significantly increased end-to-end throughput with lower overhead and no apparent degradation of end-to-end delays (hop counts) compared to its Q-learning-based counterparts. Qualitatively, and perhaps more significantly, DeepCQ+ maintains remarkably similar performance gains under many scenarios that it was not trained for in terms of network sizes, mobility conditions, and traffic dynamics. To the best of our knowledge, this is the first successful application of the MADRL framework for the MANET routing problem that demonstrates a high degree of scalability and robustness even under the environments that are outside the trained range of scenarios. This implies that our MARL-based DeepCQ+ design solution significantly improves the performance of Q-learning-based CQ+ baseline approach for comparison and increases its practicality and explainability because the real-world MANET environment will likely vary outside the trained range of MANET scenarios. Additional techniques to further increase the gains in performance and scalability are discussed.
{"title":"DeepCQ+: Robust and Scalable Routing with Multi-Agent Deep Reinforcement Learning for Highly Dynamic Networks","authors":"Saeed Kaviani, Bo Ryu, E. Ahmed, Kevin Larson, Anh-Ngoc Le, Alex Yahja, J. H. Kim","doi":"10.1109/MILCOM52596.2021.9652948","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9652948","url":null,"abstract":"Highly dynamic mobile ad-hoc networks (MANETs) remain as one of the most challenging environments to develop and deploy robust, efficient, and scalable routing protocols. In this paper, we present DeepCQ+ routing protocol which, in a novel manner, integrates emerging multi-agent deep reinforcement learning (MADRL) techniques into existing Q-learning-based routing protocols and their variants, and achieves persistently higher performance across a wide range of topology and mobility configurations. While keeping the overall protocol structure of the Q-learning-based routing protocols, DeepCQ+ replaces statically configured parameterized thresholds and hand-written rules with carefully designed MADRL agents such that no configuration of such parameters is required a priori. Extensive simulation shows that DeepCQ+ yields significantly increased end-to-end throughput with lower overhead and no apparent degradation of end-to-end delays (hop counts) compared to its Q-learning-based counterparts. Qualitatively, and perhaps more significantly, DeepCQ+ maintains remarkably similar performance gains under many scenarios that it was not trained for in terms of network sizes, mobility conditions, and traffic dynamics. To the best of our knowledge, this is the first successful application of the MADRL framework for the MANET routing problem that demonstrates a high degree of scalability and robustness even under the environments that are outside the trained range of scenarios. This implies that our MARL-based DeepCQ+ design solution significantly improves the performance of Q-learning-based CQ+ baseline approach for comparison and increases its practicality and explainability because the real-world MANET environment will likely vary outside the trained range of MANET scenarios. Additional techniques to further increase the gains in performance and scalability are discussed.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123854387","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 : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9653022
Frederick M. Chache, Sean Maxon, R. Narayanan, Ramesh Bharadwaj
To be useful, wireless sensor networks (WSNs) must be relied upon even when dispersed across environments that lack consistent internet access. To this end, we propose a mesh network architecture based on the Better Approach to Mobile Ad-hoc Networking (B.A.T.M.A.N.) algorithm in conjunction with the long range, low power communication protocol, LoRa, to transmit messages. Adaptations including methods of time synchronization, slotted ALOHA transmission and Quality of Service (QoS) considerations with a network-traffic-aware data routing protocol for a multi-source/multi-sink network configuration have been implemented. With this solution, nodes can create an ad-hoc network, sharing internet access and greatly expanding the network coverage without the need for any additional infrastructure. Our QoS-aware routing metrics have been tested in simulation and show performance improvements over traditional B.A.T.M.A.N. destination routing algorithms in these low data rate systems.
{"title":"QoS Extension to a B.A.T.M.A.N. based LoRa Mesh Network","authors":"Frederick M. Chache, Sean Maxon, R. Narayanan, Ramesh Bharadwaj","doi":"10.1109/MILCOM52596.2021.9653022","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9653022","url":null,"abstract":"To be useful, wireless sensor networks (WSNs) must be relied upon even when dispersed across environments that lack consistent internet access. To this end, we propose a mesh network architecture based on the Better Approach to Mobile Ad-hoc Networking (B.A.T.M.A.N.) algorithm in conjunction with the long range, low power communication protocol, LoRa, to transmit messages. Adaptations including methods of time synchronization, slotted ALOHA transmission and Quality of Service (QoS) considerations with a network-traffic-aware data routing protocol for a multi-source/multi-sink network configuration have been implemented. With this solution, nodes can create an ad-hoc network, sharing internet access and greatly expanding the network coverage without the need for any additional infrastructure. Our QoS-aware routing metrics have been tested in simulation and show performance improvements over traditional B.A.T.M.A.N. destination routing algorithms in these low data rate systems.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121204507","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 : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9652992
Stefan Weithoffer, Rami Klaimi, C. A. Nour
The complexity involved to blindly detect the channel code parameters in the case of their imperfect knowledge is generally measured in terms of the minimum number of frames that an eavesdropper needs to observe for successful detection, adding an additional layer of privacy. In this work, starting from a defined almost regular interleaver for Turbo codes, we propose methods to construct a larger set of distinct interleavers that increases the minimum number of observations by a factor equal to the size of the constructed set. Furthermore, the generated sets of interleavers can be described by defining only a small number of parameters and are shown to achieve a comparable error correcting performance to base interleavers. To validate the proposed implementation-friendly method, an application example for information frame sizes $mathrm{K}=128$ bits and $mathrm{K}=512$ bits is provided for the construction of two sets of 8192 interleavers, prohibitively increasing detection complexity by state-of-the-art methods.
{"title":"Mitigating Blind Detection Through Protograph Based Interleaving for Turbo Codes","authors":"Stefan Weithoffer, Rami Klaimi, C. A. Nour","doi":"10.1109/MILCOM52596.2021.9652992","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9652992","url":null,"abstract":"The complexity involved to blindly detect the channel code parameters in the case of their imperfect knowledge is generally measured in terms of the minimum number of frames that an eavesdropper needs to observe for successful detection, adding an additional layer of privacy. In this work, starting from a defined almost regular interleaver for Turbo codes, we propose methods to construct a larger set of distinct interleavers that increases the minimum number of observations by a factor equal to the size of the constructed set. Furthermore, the generated sets of interleavers can be described by defining only a small number of parameters and are shown to achieve a comparable error correcting performance to base interleavers. To validate the proposed implementation-friendly method, an application example for information frame sizes $mathrm{K}=128$ bits and $mathrm{K}=512$ bits is provided for the construction of two sets of 8192 interleavers, prohibitively increasing detection complexity by state-of-the-art methods.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127565168","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 : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9653004
M. Rupar, Erlend Larsen, H. B. Saglam, Ruben Bascuñana Blasco, Julian A. Savin, Nadine Brueck
As information technology advances, the need for distributed communications on the battlefield continues to grow. Moreover, NATO activities are multi-nation engagements, and necessitate communications between member countries and from the theater of operations back to command centers. The NATO Information Systems Technology (IST) 172 research task group is investigating non-satellite and non-high frequency (HF) technologies for beyond line-of-sight (BLOS) communications, creating links between disparate battlefield nodes. The study is examining existing and emerging capabilities within the NATO member nations, and considering their applicability to two representative communications scenarios. Range extension, ease of interoperability between member nations, frequency coordination considerations and existing radio hardware are all to be included in the analysis.
{"title":"Airborne Beyond Line of Sight Communication Networks","authors":"M. Rupar, Erlend Larsen, H. B. Saglam, Ruben Bascuñana Blasco, Julian A. Savin, Nadine Brueck","doi":"10.1109/MILCOM52596.2021.9653004","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9653004","url":null,"abstract":"As information technology advances, the need for distributed communications on the battlefield continues to grow. Moreover, NATO activities are multi-nation engagements, and necessitate communications between member countries and from the theater of operations back to command centers. The NATO Information Systems Technology (IST) 172 research task group is investigating non-satellite and non-high frequency (HF) technologies for beyond line-of-sight (BLOS) communications, creating links between disparate battlefield nodes. The study is examining existing and emerging capabilities within the NATO member nations, and considering their applicability to two representative communications scenarios. Range extension, ease of interoperability between member nations, frequency coordination considerations and existing radio hardware are all to be included in the analysis.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127568916","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 : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9652930
P. Montezuma, R. Madeira, Hugo Serra, P. Viegas, R. Dinis, J. Oliveira, João Guerreiro
Uplink high throughput is essential to assure good situational awareness in Unmanned Aerial Vehicles (UAVs) mission. For that purpose larger bandwidths should be combined with the maximum possible spectral efficiency at the uplink. This leads to the use of multilevel broadband modulations with high Peak-to-Average Power Ratio (PAPR) values that may compromise the power amplification efficiency of current amplification technologies. High efficiency can be assured in these links with a new amplification scheme based on the Quantized Digital Amplification (QDA) technique that combines broadband support with both low complexity and high energy efficiency of signal power amplification stage. Spectral efficiency is also assured due to the QDA capacity to deal efficiently with multilevel modulations with high PAPRs, commonly used to assure high spectral efficiencies. The several cases analyzed here show the effectiveness and the robustness of the new technique to support efficiently the signal amplification in these links.
{"title":"Quantized Digital Amplification with combination over the air - Achieving maximum efficiency on communication links between long range UAVs and satellites","authors":"P. Montezuma, R. Madeira, Hugo Serra, P. Viegas, R. Dinis, J. Oliveira, João Guerreiro","doi":"10.1109/MILCOM52596.2021.9652930","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9652930","url":null,"abstract":"Uplink high throughput is essential to assure good situational awareness in Unmanned Aerial Vehicles (UAVs) mission. For that purpose larger bandwidths should be combined with the maximum possible spectral efficiency at the uplink. This leads to the use of multilevel broadband modulations with high Peak-to-Average Power Ratio (PAPR) values that may compromise the power amplification efficiency of current amplification technologies. High efficiency can be assured in these links with a new amplification scheme based on the Quantized Digital Amplification (QDA) technique that combines broadband support with both low complexity and high energy efficiency of signal power amplification stage. Spectral efficiency is also assured due to the QDA capacity to deal efficiently with multilevel modulations with high PAPRs, commonly used to assure high spectral efficiencies. The several cases analyzed here show the effectiveness and the robustness of the new technique to support efficiently the signal amplification in these links.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125640384","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 : 2021-11-29DOI: 10.1109/MILCOM52596.2021.9652924
G. Elmasry, P. Corwin
Tactical network architects are exploring ways to leverage 5G capabilities in military communications. 5G offers many capabilities that can benefit tactical networks to include directionality, dynamic spectrum management, abundant bandwidth and low latency. There are different areas of 5G that are considered by the tactical community such as security enhancements, interfacing 5G technologies with existing tactical links and waveforms, developing new MIMO antennas that meet tactical requirements, enhancing 5G spectrum emission to meet EW requirements and exploring how to adapt an open architecture for tactical 5G. This paper approaches the adaptation of 5G to tactical networks from the high-level operational views leading to a proposed lab architecture that is specific for a vertical tactical 5G solution. This is a top-down study that exposes the pros and cons of following a vertical path for tactical 5G. Vertical 5G here means the augmentation of 5G standards (e.g., 3GPP) for an open-architecture-based, tactical-specific 5G solution that can eventually lead to the full utilization of 5G capabilities within tactical networks.
{"title":"Operational Views of Vertical Tactical 5G","authors":"G. Elmasry, P. Corwin","doi":"10.1109/MILCOM52596.2021.9652924","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9652924","url":null,"abstract":"Tactical network architects are exploring ways to leverage 5G capabilities in military communications. 5G offers many capabilities that can benefit tactical networks to include directionality, dynamic spectrum management, abundant bandwidth and low latency. There are different areas of 5G that are considered by the tactical community such as security enhancements, interfacing 5G technologies with existing tactical links and waveforms, developing new MIMO antennas that meet tactical requirements, enhancing 5G spectrum emission to meet EW requirements and exploring how to adapt an open architecture for tactical 5G. This paper approaches the adaptation of 5G to tactical networks from the high-level operational views leading to a proposed lab architecture that is specific for a vertical tactical 5G solution. This is a top-down study that exposes the pros and cons of following a vertical path for tactical 5G. Vertical 5G here means the augmentation of 5G standards (e.g., 3GPP) for an open-architecture-based, tactical-specific 5G solution that can eventually lead to the full utilization of 5G capabilities within tactical networks.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126543889","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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