Leandros Tassiulas
John C. Malone Professor of Electrical EngineeringCards
About
Research
Publications
2026
Semantics-Aware Unified Terrestrial Non-Terrestrial 6G Networks
Delfani E, Mesodiakaki A, Tassiulas L, Pappas N. Semantics-Aware Unified Terrestrial Non-Terrestrial 6G Networks. IEEE Communications Magazine 2026, PP: 1-8. DOI: 10.1109/mcom.001.2500615.Peer-Reviewed Original ResearchSeamless networkNon-terrestrial networksAge of informationVolume of dataNetworks of low-earth-orbitEnergy consumptionSemantic metricsEfficient managementSemantics-awareSixth-generationNetwork of networksTransmission demandData communicationData exchangeNon-TerrestrialInformation handlingData generationNetworkMonitoring systemDestination monitoringInformationLow Earth orbitOperational requirementsIoTQuery5GC-Bench: A Framework for Stress-Testing and Benchmarking 5G Core VNFs
Panitsas I, Atalay T, Stojadinovic D, Stavrou A, Tassiulas L. 5GC-Bench: A Framework for Stress-Testing and Benchmarking 5G Core VNFs. 2026, 00: 1-6. DOI: 10.1109/wcnc65185.2026.11555639.Peer-Reviewed Original ResearchVirtual network functionsCloud-native designEnd-to-endUser planeG deploymentsRealistic workloadsService trafficNetwork functionsResource usageSynthetic workloadsModular frameworkLack visibilityResource demandsOpenAirInterfaceResource constraintsPerformance optimizationCapacity planningTrafficWorkloadArtifactsA Deep and Transfer Learning Approach for Handover Management in O-RAN
Panitsas I, Mudvari A, Maatouk A, Tassiulas L. A Deep and Transfer Learning Approach for Handover Management in O-RAN. 2026, 00: 1-6. DOI: 10.1109/wcnc65185.2026.11555653.Peer-Reviewed Original ResearchOpen Radio Access NetworkHandover algorithmHandover managementReal-world deploymentState-of-the-artTransfer learning approachLarge-scale networksHandover decisionAccess networksBase stationCellular networksHandover methodRetraining timeClassification accuracyLearning approachNear real-timeHandoverIntelligent controlAlgorithmHigher accuracyNetworkOpen problemsFlexible designXAppsAccuracyEditorial: Emerging optimization, learning and signal processing for next-generation wireless communications and networking
Kalogerias D, Liang L, Eisen M, Petropulu A, Tassiulas L. Editorial: Emerging optimization, learning and signal processing for next-generation wireless communications and networking. Frontiers In Signal Processing 2026, 6: 1827692. DOI: 10.3389/frsip.2026.1827692.Commentaries, Editorials and LettersRate-Fidelity Tradeoffs in All-Photonic and Memory-Equipped Quantum Switches
Promponas P, Bacciottini L, Polakos P, Vardoyan G, Towsley D, Tassiulas L. Rate-Fidelity Tradeoffs in All-Photonic and Memory-Equipped Quantum Switches. 2026, 00: 19-28. DOI: 10.1109/qcnc69040.2026.00013.Peer-Reviewed Original ResearchBell-state measurementNear-term devicesEntanglement switchPhotonic qubitsQuantum networksQuantum memoryQuantum switchQubitsOptical componentsNetwork-level performanceOperating regionMemoryless operatorDecoherenceGenerator switchingNumerical evaluationQuantumEntanglementSwitchingRating fidelityProtocol parametersHardwareTradeoffOperationMeasurementsBuilding blocksAn LLM agent-based framework for analytical characterization of Nash equilibria
Liu W, Zhou X, Wang X, Cheng Y, Ye L, Berry R, Tassiulas L, Huang J, Zhao J. An LLM agent-based framework for analytical characterization of Nash equilibria. Nexus 2026, 3: 100107. DOI: 10.1016/j.ynexs.2025.100107.Peer-Reviewed Original ResearchNash EquilibriaMulti-agent reasoningSymbolic code executionMachine-checked proofsClosed-form characterizationAgent-based frameworkFinancial marketsEquilibrium searchDynamic gameStatic gameClimate policyCode executionEconomic analysisStrategy generationCanonical modelPayoffEquilibrium derivationClosed-form solutionClosed-formAnalytical characterizationEquilibriaEquilibriumGameScalable pipelineStrategic systemsAGORAN: An agentic open marketplace for 6G RAN automation
Chatzistefanidis I, Nikaein N, Leone A, Maatouk A, Tassiulas L, Morabito R, Pitsiorlas I, Kountouris M. AGORAN: An agentic open marketplace for 6G RAN automation. Computer Networks 2026, 275: 111927. DOI: 10.1016/j.comnet.2025.111927.Peer-Reviewed Original ResearchService-level agreementsNext-generation mobile networksReal-time situational awarenessEnd-to-endAgent marketplaceMalicious behaviorMobile networksSlice controllerLanguage modelBroker agentAgent observationsReal-time incentivesLive demoTrust scoresNetwork functionsAgent messagesVehicle mobilitySituational awarenessService ownersRAN controllerMulti-objective optimizationVector databaseDecision qualityResource utilizationOpen marketplaceModeling RIS for Multi-User Resource Allocation Under Pricing-Aware Policies
Papadopoulos A, Lalas A, Votis K, Tassiulas L, Liaskos C. Modeling RIS for Multi-User Resource Allocation Under Pricing-Aware Policies. IEEE Access 2026, 14: 14766-14776. DOI: 10.1109/access.2026.3656715.Peer-Reviewed Original ResearchReconfigurable intelligent surfaceMulti-user resource allocationProgrammable wireless environmentsStochastic wireless channelsWireless environmentCodebook modelWireless channelScalable executionPolicy-AwareG networksIntelligent surfaceLarge-scale simulationsNetwork performanceReal-time useMulti-userHeterogeneous usersPerformance guaranteesMultiplexing schemeResource allocationPerformance objectivesAllocationUsersGuaranteesPerformanceAlgorithmTele-LLMs: A Series of Specialized Large Language Models for Telecommunications
Maatouk A, Ampudia K, Ying R, Tassiulas L. Tele-LLMs: A Series of Specialized Large Language Models for Telecommunications. IEEE Access 2026, 14: 86424-86441. DOI: 10.1109/access.2026.3698683.Peer-Reviewed Original ResearchLanguage modelNatural language processingDomain-specific specializationsGeneral-purpose modelTelecommunication domainQuestion-and-answerGeneral-purpose counterpartsTraining dataLanguage processingTelecommunications aspectsTraining techniquesTelecommunicationsDatasetComprehensive datasetEffective training techniquesMathematical representationLanguageDomainTaskLLMRepresentationRelevant sourcesModelTechnique
2025
Age Optimal Sampling for Unreliable Channels Under Unknown Channel Statistics
He H, Tang H, Pan J, Wang J, Song J, Tassiulas L. Age Optimal Sampling for Unreliable Channels Under Unknown Channel Statistics. IEEE Transactions On Mobile Computing 2025, 25: 7640-7656. DOI: 10.1109/tmc.2025.3646252.Peer-Reviewed Original ResearchOnline learning algorithmChannel statisticsLearning algorithmsOnline algorithmStochastic gradient descent algorithmUnknown channel statisticsError-prone channelsOptimal offline policyGradient descent algorithmTime average AoIStochastic approximation problemOffline policyUnreliable channelsDescent algorithmSuccessful transmissionStatus informationSampling policyThreshold structureAlgorithmSimulation resultsReceiverApproximation problemRandom delaysOptimal thresholdRobbins-Monro algorithm