Knowledge-Driven Wireless Networks Design Cognitive Radios requires New Networking Solution  Knowledge-driven Networking (goes beyond “cognitive networking”,

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Presentation transcript:

Knowledge-Driven Wireless Networks Design Cognitive Radios requires New Networking Solution  Knowledge-driven Networking (goes beyond “cognitive networking”, which just puts current Passive MAC, Network and Transport Protocols on top of Cognitive Radio, thereby neglecting the users’ a bility to influence the network) Plato formulated knowledge as "justified true belief". Knowledge acquisition involves complex cognitivecognitive processes: sensing, learning, communication, association and reasoning. [Wikipedia]

(Dynamic) Environment Information Knowledge-driven Decision Making Wireless User Manager / Leader (optional, e.g. BS) Actions Rules {Complete/Incomplete} Negotiation messages Resource Negotiation { Explicit/Implicit } { Myopic, Foresighted, etc. } {Fairness/Efficiency} Knowledge-Driven Wireless Networks Design Cognition/Sensing Learning

Autonomous wireless user Network Coordinator Autonomous wireless user Centralized negotiationDecentralized negotiation Private information Public information Negotiation messages /actions Negotiation messages /actions Information Flow source channel state channel state Network

Information Horizon : hop number : information from nodes in hop Knowledge-driven Decision Making Autonomous Wireless User Learning Determining value of Cognition /Sensing Adapting Information horizon Public information We can evaluate the value of by the expected utility improvement given the information

Knowledge-driven Communication Dynamic Environment (source/channel characteristics, other users, etc.) Cognition /Sensing Exchange Information (cross-layer) Sense Information (cross-layer) Learning Memory (information history) Determine Value of Information Interactive Learning from “environment” Determine Value of Learning Knowledge-driven Decision Making Resource Negotiation Of Spectrum Access Strategies/Policies Knowledge Accumulation Knowledge Formation Knowledge-driven Networking using optimized cross-layer action Knowledge-driven Utility Evaluation Autonomous Wireless User Interference Explicit control messages Negotiation messages Actions Through its actions and negotiation messages, a user will teach/influence the behavior of other users

Why and how? Users can influence and negotiate the rules (e. g. fairness, taxation, service provided etc.), therefore, the rul es should take into consideration user’s ability to strategically influence the network performance Mechanism Design [1, 2, 3]123 Coalition Theory Bargaining Theory [4, 5]45 Passive Resource Allocation (e.g e) Current Rules Game theoretic resource management rules design and analysis (centralized/distributed) … Knowledge-Driven Wireless Networks Design

Knowledge-driven Networking (user-side) How? Model wireless users as agents that can learn their environment (not only source and channel conditions, but also other users behaviors!) Proactive Cross-layer Design [6,7]67 Interactive Learning [8]8 Behavior Analysis & Forecasting [9,10,11]91011 Strategic Information Exchange [12,13]1213 Passive Cross-layer Adaptation Current Knowledge-Driven Wireless Networks Design