Pub Date : 2022-11-30DOI: 10.1109/LATINCOM56090.2022.10000445
G. Camilo, G. Rebello, Lucas Airam C. de Souza, M. Potop-Butucaru, M. Amorim, M. Campista, Henrique M. K. Costa
Payment channel networks (PCN) offer a fast, secure, and distributed alternative payment method while avoiding slow consensus mechanisms of blockchains. Nonetheless, the PCN topology directly influences the performance, cost, and payment success rate. This paper 1 analyzes the evolution of the Lightning Network topology, which is currently the leading payment channel network. We reconstruct the network graph using real data from a set of channel announcement messages collected between January 2020 and August 2021. Our analysis uses typical graph metrics, such as transitivity, diameter, and degree centrality, to evaluate the state and evolution of the network. The results show a strong trend in resource and connectivity centralization. Only 0.38% of nodes concentrate 50% of the network capacity, exposing a vulnerability to targeted attacks. As with the Bitcoin cryptocurrency, the centralization of the Lightning PCN directly contrasts with the original goal of a fully-decentralized network. Moreover, the low network transitivity compromises channel rebalancing techniques, which contribute to the stability of the system. This trend evidences the need for new attachment policies prioritizing greater network decentralization and robustness.
{"title":"Topological Evolution Analysis of Payment Channels in the Lightning Network","authors":"G. Camilo, G. Rebello, Lucas Airam C. de Souza, M. Potop-Butucaru, M. Amorim, M. Campista, Henrique M. K. Costa","doi":"10.1109/LATINCOM56090.2022.10000445","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000445","url":null,"abstract":"Payment channel networks (PCN) offer a fast, secure, and distributed alternative payment method while avoiding slow consensus mechanisms of blockchains. Nonetheless, the PCN topology directly influences the performance, cost, and payment success rate. This paper 1 analyzes the evolution of the Lightning Network topology, which is currently the leading payment channel network. We reconstruct the network graph using real data from a set of channel announcement messages collected between January 2020 and August 2021. Our analysis uses typical graph metrics, such as transitivity, diameter, and degree centrality, to evaluate the state and evolution of the network. The results show a strong trend in resource and connectivity centralization. Only 0.38% of nodes concentrate 50% of the network capacity, exposing a vulnerability to targeted attacks. As with the Bitcoin cryptocurrency, the centralization of the Lightning PCN directly contrasts with the original goal of a fully-decentralized network. Moreover, the low network transitivity compromises channel rebalancing techniques, which contribute to the stability of the system. This trend evidences the need for new attachment policies prioritizing greater network decentralization and robustness.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"44 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":"129527165","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/LATINCOM56090.2022.10000429
L. A. D. Lima, G. S. Pavani
Space division multiplexing (SDM) allows for capacity expansion in the Elastic Optical Network (EON) by providing different spatial paths in the same link for the lightpaths. Thus, in addition to the Routing and Spectrum Assignment (RSA) problem, the Space sub-problem must be tackled during the allocation of resources in an SDM-EON environment. In this work, we propose a fully distributed provisioning algorithm based on the Ant Colony optimization (ACO) metaheuristics with a crankback mechanism to solve the Routing, Space, and Spectrum Assignment (RSSA) problem. The proposed algorithm can mitigate the blocking by taking into consideration the fragmentation caused by the dynamic establishment and release of lightpaths. The obtained simulation results demonstrate the effectiveness of the proposed approach when compared to fragmentation-aware algorithms that rely on the OSPF-TE protocol to gather the network state information while maintaining much lower levels of control overhead.
{"title":"Fragmentation-aware Routing, Space, and Spectrum Assignment using Ant Colony Optimization","authors":"L. A. D. Lima, G. S. Pavani","doi":"10.1109/LATINCOM56090.2022.10000429","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000429","url":null,"abstract":"Space division multiplexing (SDM) allows for capacity expansion in the Elastic Optical Network (EON) by providing different spatial paths in the same link for the lightpaths. Thus, in addition to the Routing and Spectrum Assignment (RSA) problem, the Space sub-problem must be tackled during the allocation of resources in an SDM-EON environment. In this work, we propose a fully distributed provisioning algorithm based on the Ant Colony optimization (ACO) metaheuristics with a crankback mechanism to solve the Routing, Space, and Spectrum Assignment (RSSA) problem. The proposed algorithm can mitigate the blocking by taking into consideration the fragmentation caused by the dynamic establishment and release of lightpaths. The obtained simulation results demonstrate the effectiveness of the proposed approach when compared to fragmentation-aware algorithms that rely on the OSPF-TE protocol to gather the network state information while maintaining much lower levels of control overhead.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"23 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":"130169831","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/LATINCOM56090.2022.10000511
Martín Randall, P. Belzarena, Federico Larroca, P. Casas
The increased sophistication of mobile networks such as 5G and beyond, and the plethora of devices and novel use cases to be supported by these networks, make of the already complex problem of resource allocation in wireless networks a paramount challenge. We address the specific problem of user association, a largely explored yet open resource allocation problem in wireless systems. We introduce GROWS, a deep reinforcement learning (DRL) driven approach to efficiently assign mobile users to base stations, which combines a well-known extension of Deep Q Networks (DQNs) with Graph Neural Networks (GNNs) to better model the function of expected rewards. We show how GROWS can learn a user association policy which improves over currently applied assignation heuristics, as well as compared against more traditional Q-learning approaches, improving utility by more than 10%, while reducing user rejections up to 20%.
{"title":"Deep Reinforcement Learning and Graph Neural Networks for Efficient Resource Allocation in 5G Networks","authors":"Martín Randall, P. Belzarena, Federico Larroca, P. Casas","doi":"10.1109/LATINCOM56090.2022.10000511","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000511","url":null,"abstract":"The increased sophistication of mobile networks such as 5G and beyond, and the plethora of devices and novel use cases to be supported by these networks, make of the already complex problem of resource allocation in wireless networks a paramount challenge. We address the specific problem of user association, a largely explored yet open resource allocation problem in wireless systems. We introduce GROWS, a deep reinforcement learning (DRL) driven approach to efficiently assign mobile users to base stations, which combines a well-known extension of Deep Q Networks (DQNs) with Graph Neural Networks (GNNs) to better model the function of expected rewards. We show how GROWS can learn a user association policy which improves over currently applied assignation heuristics, as well as compared against more traditional Q-learning approaches, improving utility by more than 10%, while reducing user rejections up to 20%.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"24 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":"123314869","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/LATINCOM56090.2022.10000560
Toluwaleke Olutayo, B. Champagne
In this paper, we investigate the use of model-based neural networks for Massive Multiple-Input Multiple-Output (MMIMO) detection. Recently, a new M-MIMO detection architecture called LcgNet [1] was obtained by unfolding an iterative conjugate gradient descent algorithm into a layer-wise network and introducing additional trainable parameters. Herein, we extend this approach by introducing a preconditioner aimed at improving the spectrum of the filter matrix used in the uplink MIMO detector. Specifically, the preconditioning scheme reduces the eigenvalue spread of the filter matrix, thus resulting in better convergence of the conjugate gradient algorithm. The proposed extension of LcgNet with preconditioning, referred to as PrLcgNet, is evaluated by means of simulations over M-MIMO uncorrelated Rayleigh fading channels and correlated fading channels. Compared to the original LcgNet, Pr-LcgNet exhibits faster convergence and lower residual error in the training phase, while achieving comparable bit error rate (BER) performance using fewer layers.
{"title":"Learned Preconditioned Conjugate Gradient Descent for Massive MIMO Detection","authors":"Toluwaleke Olutayo, B. Champagne","doi":"10.1109/LATINCOM56090.2022.10000560","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000560","url":null,"abstract":"In this paper, we investigate the use of model-based neural networks for Massive Multiple-Input Multiple-Output (MMIMO) detection. Recently, a new M-MIMO detection architecture called LcgNet [1] was obtained by unfolding an iterative conjugate gradient descent algorithm into a layer-wise network and introducing additional trainable parameters. Herein, we extend this approach by introducing a preconditioner aimed at improving the spectrum of the filter matrix used in the uplink MIMO detector. Specifically, the preconditioning scheme reduces the eigenvalue spread of the filter matrix, thus resulting in better convergence of the conjugate gradient algorithm. The proposed extension of LcgNet with preconditioning, referred to as PrLcgNet, is evaluated by means of simulations over M-MIMO uncorrelated Rayleigh fading channels and correlated fading channels. Compared to the original LcgNet, Pr-LcgNet exhibits faster convergence and lower residual error in the training phase, while achieving comparable bit error rate (BER) performance using fewer layers.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"28 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":"121108208","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/LATINCOM56090.2022.10000585
Subhi M. Alrubei, E. Ball, J. Rigelsford
Blockchain is a technology that could help secure Internet of Things (IoT) systems and allow for easy interactions and communications among IoT devices without compromising their security. However, many nodes in IoT blockchain platforms lack adequate security at the hardware level; this is an important security aspect that can enhance both node security and overall trust in the platform. In this paper, we evaluate the viability of integrating a hardware secure module (HSM) and a hardware wallet (HW) into IoT blockchain applications. We provide a performance evaluation regarding the energy consumption of nodes that are equipped with HSM and HW and conduct security analyses. Finally, we discuss an example application, namely, secure community energy trading based on the deployment of an honesty-based distributed proof of authority (HDPoA) consensus algorithm where all nodes are equipped with an HSM and HW.
{"title":"Adding Hardware Security into IoT-Blockchain Platforms","authors":"Subhi M. Alrubei, E. Ball, J. Rigelsford","doi":"10.1109/LATINCOM56090.2022.10000585","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000585","url":null,"abstract":"Blockchain is a technology that could help secure Internet of Things (IoT) systems and allow for easy interactions and communications among IoT devices without compromising their security. However, many nodes in IoT blockchain platforms lack adequate security at the hardware level; this is an important security aspect that can enhance both node security and overall trust in the platform. In this paper, we evaluate the viability of integrating a hardware secure module (HSM) and a hardware wallet (HW) into IoT blockchain applications. We provide a performance evaluation regarding the energy consumption of nodes that are equipped with HSM and HW and conduct security analyses. Finally, we discuss an example application, namely, secure community energy trading based on the deployment of an honesty-based distributed proof of authority (HDPoA) consensus algorithm where all nodes are equipped with an HSM and HW.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"23 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":"121697271","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/LATINCOM56090.2022.10000583
A. Famili, A. Stavrou, Haining Wang, J. Park
Drones must operate permanently or temporarily autonomously for many applications. They rely on access to location services upon obtaining navigation commands and continually thereafter to enable completely or partially autonomous flight. Global Positioning System (GPS) is not always available, can be spoofed or jammed, and is particularly error-prone in indoor and underground settings. In this article, we present SPIN (Sensor Placement for Indoor Navigation of Drones), a sensor-assisted ranging system for drones that performs in GPS-deficient situations. SPIN employs a novel optimization technique for the deployment of indoor sensors in three-dimensional spaces. SPIN utilizes advancements in Evolutionary Algorithms to compute the smallest number of sensors and their ideal placement in order to minimize deployment costs and localization errors. This challenge is classified as NP-Hard and belongs to the class of Mixed Integer Programming (MIP) problems. SPIN can provide numerous optimal sensor configurations that decrease the number of deployed sensors, enabling autonomous navigation of drones in inside environments at a low cost.
{"title":"SPIN: Sensor Placement for Indoor Navigation of Drones","authors":"A. Famili, A. Stavrou, Haining Wang, J. Park","doi":"10.1109/LATINCOM56090.2022.10000583","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000583","url":null,"abstract":"Drones must operate permanently or temporarily autonomously for many applications. They rely on access to location services upon obtaining navigation commands and continually thereafter to enable completely or partially autonomous flight. Global Positioning System (GPS) is not always available, can be spoofed or jammed, and is particularly error-prone in indoor and underground settings. In this article, we present SPIN (Sensor Placement for Indoor Navigation of Drones), a sensor-assisted ranging system for drones that performs in GPS-deficient situations. SPIN employs a novel optimization technique for the deployment of indoor sensors in three-dimensional spaces. SPIN utilizes advancements in Evolutionary Algorithms to compute the smallest number of sensors and their ideal placement in order to minimize deployment costs and localization errors. This challenge is classified as NP-Hard and belongs to the class of Mixed Integer Programming (MIP) problems. SPIN can provide numerous optimal sensor configurations that decrease the number of deployed sensors, enabling autonomous navigation of drones in inside environments at a low cost.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"4 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":"124894882","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/LATINCOM56090.2022.10000456
Tiago Bornia De Castro, N. Fernandes
In smart grids, smart meters replace traditional meters, enabling near real-time communication between customers and companies. The metering data serves for billing, monitoring, and service delivery. However, the interception of a third malicious entity, or the data misuse by the utility could expose customer privacy. The solutions in the literature to protect the privacy of end-users discuss techniques such as data aggregation, homomorphic encryption, and the use of pseudonyms. However, they don’t solve the problem of the curious utility. In this article, we propose the UPriv-AC, a meter data privacy protection mechanism with blind signature and data aggregation. The blind signature allows a certified registry of consumption per user, but preventing the utility from mapping the certified pseudonyms to their respective meters. The proposed aggregation, performed by the meters in a decentralized way, protects users’ privacy from curious aggregators and the user’s identification through the network interface. Hence, our mechanism allows a proper network monitoring, but stopping the utility from building consumer profiles that could reveal users habits and possessions. We analyzed our proposal in comparison with others in the literature. The blind signature proved to be more secure and with 50% lower CPU usage than the partially homomorphic encryption.
{"title":"UPriv-AC: A Privacy-Preserving Mechanism for Smart Metering Against Curious Utility","authors":"Tiago Bornia De Castro, N. Fernandes","doi":"10.1109/LATINCOM56090.2022.10000456","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000456","url":null,"abstract":"In smart grids, smart meters replace traditional meters, enabling near real-time communication between customers and companies. The metering data serves for billing, monitoring, and service delivery. However, the interception of a third malicious entity, or the data misuse by the utility could expose customer privacy. The solutions in the literature to protect the privacy of end-users discuss techniques such as data aggregation, homomorphic encryption, and the use of pseudonyms. However, they don’t solve the problem of the curious utility. In this article, we propose the UPriv-AC, a meter data privacy protection mechanism with blind signature and data aggregation. The blind signature allows a certified registry of consumption per user, but preventing the utility from mapping the certified pseudonyms to their respective meters. The proposed aggregation, performed by the meters in a decentralized way, protects users’ privacy from curious aggregators and the user’s identification through the network interface. Hence, our mechanism allows a proper network monitoring, but stopping the utility from building consumer profiles that could reveal users habits and possessions. We analyzed our proposal in comparison with others in the literature. The blind signature proved to be more secure and with 50% lower CPU usage than the partially homomorphic encryption.","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":"127829786","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/LATINCOM56090.2022.10000493
R. Reyes, T. Bauschert
The performance of optimization algorithms for traffic restoration in communication networks is dependent on the characteristics of the problem instance. There is no known best algorithm that performs well for all instance realizations of any given traffic restoration problem. In this paper we argue that for a given problem instance, optimum or near-optimum performance can be attained through algorithm selection (AS). The objective is to select from a set of candidate algorithms, the one that performs best for the problem instance. For that, AS is formulated as a learning problem where a Machine-learning algorithm learns the relation between the instance properties and the performance of the candidate algorithms. As case study, the approach is applied for traffic restoration in IP-Optical networks. In these networks, optical failures may affect multiple IP links simultaneously. As a result, the IP layer has to perform traffic restoration by rerouting the affected IP flows. This can be carried out by a hyperheuristic method that performs traffic engineering to minimize the spare capacity utilized for traffic protection. The approach applies AS to choose the best algorithm from a set of heuristics for IP traffic rerouting. Results on selected scenarios show that AS predicts with high precision the heuristic that requires minimum spare capacity.
{"title":"Traffic Restoration in Communication Networks by Meta-Learning Inspired Algorithm Selection: A Case Study for IP-Optical SDN Networks","authors":"R. Reyes, T. Bauschert","doi":"10.1109/LATINCOM56090.2022.10000493","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000493","url":null,"abstract":"The performance of optimization algorithms for traffic restoration in communication networks is dependent on the characteristics of the problem instance. There is no known best algorithm that performs well for all instance realizations of any given traffic restoration problem. In this paper we argue that for a given problem instance, optimum or near-optimum performance can be attained through algorithm selection (AS). The objective is to select from a set of candidate algorithms, the one that performs best for the problem instance. For that, AS is formulated as a learning problem where a Machine-learning algorithm learns the relation between the instance properties and the performance of the candidate algorithms. As case study, the approach is applied for traffic restoration in IP-Optical networks. In these networks, optical failures may affect multiple IP links simultaneously. As a result, the IP layer has to perform traffic restoration by rerouting the affected IP flows. This can be carried out by a hyperheuristic method that performs traffic engineering to minimize the spare capacity utilized for traffic protection. The approach applies AS to choose the best algorithm from a set of heuristics for IP traffic rerouting. Results on selected scenarios show that AS predicts with high precision the heuristic that requires minimum spare capacity.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"247 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":"134272380","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/LATINCOM56090.2022.10000428
Ronakraj Gosalia, R. Malaney, R. Aguinaldo, J. Green, M. Clampin
Highly-accurate time synchronization between satellites provides for a plethora of fundamental physics investigations as well as providing for a range of enhanced-engineering applications. However, current state-of-the-art synchronization techniques in space are limited by the Standard Quantum Limit (SQL), thereby limiting progress. Squeezed light, however, offers a pathway to overcome the SQL — an example of the ‘quantum advantage’ offered by non-classical states of light. Here we investigate, for the first time, the practicality of achieving such a quantum advantage between low-Earth-orbit satellites. Among other deployed-platform issues, we pay particular attention to the impact photon loss and pointing error have on the transmitted squeezing level. A key finding of our work is the identification of the conditions under which quantum enhancement, via squeezed light alone, can deliver a factor of two improvement in timing resolution between two satellites. Our work, for the first time, sets the baseline for quantum timing enhancements in satellite networks achievable with current technology. We discuss how advanced quantum techniques beyond squeezed light could improve upon the results presented here.
{"title":"Beyond the Standard Quantum Limit in the Synchronization of Low-Earth-Orbit Satellites","authors":"Ronakraj Gosalia, R. Malaney, R. Aguinaldo, J. Green, M. Clampin","doi":"10.1109/LATINCOM56090.2022.10000428","DOIUrl":"https://doi.org/10.1109/LATINCOM56090.2022.10000428","url":null,"abstract":"Highly-accurate time synchronization between satellites provides for a plethora of fundamental physics investigations as well as providing for a range of enhanced-engineering applications. However, current state-of-the-art synchronization techniques in space are limited by the Standard Quantum Limit (SQL), thereby limiting progress. Squeezed light, however, offers a pathway to overcome the SQL — an example of the ‘quantum advantage’ offered by non-classical states of light. Here we investigate, for the first time, the practicality of achieving such a quantum advantage between low-Earth-orbit satellites. Among other deployed-platform issues, we pay particular attention to the impact photon loss and pointing error have on the transmitted squeezing level. A key finding of our work is the identification of the conditions under which quantum enhancement, via squeezed light alone, can deliver a factor of two improvement in timing resolution between two satellites. Our work, for the first time, sets the baseline for quantum timing enhancements in satellite networks achievable with current technology. We discuss how advanced quantum techniques beyond squeezed light could improve upon the results presented here.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"44 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":"116176066","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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