Cognitive Radio Networks

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Presentation transcript:

Cognitive Radio Networks Mo Dong

Presentation Outline Introduction Definition Cognitive radio network architecture Dynamic Spectrum Access in CRN

Introduction 1

Why cognitive radio? Pros: Effectively controls interferenc Simple to design hardware Cons: Utilization of 0.5% in the 3-4 GHz And 0.3% in 4-5 GHz Multiple allocation over all of the band A crisis of spectrum availability

A new approach to spectrum licensing is needed Spectrum hole A new approach to spectrum licensing is needed

Definition 2

Cognitive radio : “cognitive Radio” was first introduced by J.Mitola : An intelligent wireless communication system that is aware of its surrounding environment (i.e., outside world), and uses the methodology of understanding-by-building to learn from the environment and adapt its internal states to statistical variations in the incoming RF stimuli by making corresponding changes in certain operating parameters (e.g., transmit-power, carrierfrequency, and modulation strategy) in real-time, with two primary objectives in mind: · highly reliable communications whenever and wherever needed; · efficient utilization of the radio spectrum.

Cognitive radio : FCC definition : A ‘‘Cognitive Radio’’ is a radio that can change its transmitter parameters (So must be Reconfigurable) based on interaction with the environment in which it operates. (So must have some capabilities such as sensing)

Cognitive radio network architecture 3

Components of CRN Primary network Secondary network Primary users: Primary users have the license to operate in certain spectrum bands Primary base station: Controls the access of primary users to spectrum Secondary network Secondary users: Secondary users have no licensed bands assigned to them. Secondary base-station: A fixed infrastructure component with cognitive radio capabilities and provides single hop connection to secondary users. Spectrum broker : Scheduling server shares the spectrum resources between different cognitive radio networks.

Network access types CR Network Access: CRs can access their own base station on both licensed and unlicensed spectrum bands CR Ad Hoc Access: CRs can communicate with other CRs through an ad hoc connection on both licensed and unlicensed spectrum bands. Primary Network Access : CRs can access primary base station through the licensed bands.

Dynamic Spectrum Access in CR 4

Dynamic Spectrum Access HOW TO REALIZE CR Capacity Mobility Connectivity Dynamic Spectrum Access

Dynamic Spectrum Access Opportunistic Access Model Collaborative Access Model SU is like a smart mice. They sniff around and if there is no PU, they will seize the day SU and PU agree on the use of spectrum and they can temporarily forget that they are naturally mutual exclusive and achieve a win-win state.

Dynamic Spectrum Access Opportunistic Access Model sensing access evict

Dynamic Spectrum Access Collaborative Access Model Contact with DCN Choose the channel wanted Reach Agreement on a common behalf Use it until time expire or PU change its mind

Dynamic Spectrum Access Collaborative Opportunistic Pros: Efficiency, Easy for infrastructure Hard in theory Cons: Need across layer design to be realized Pros: Quick, adaptive, Hard in theory Cons: Cannot make money Hard to implement

Dynamic Spectrum Access Collaborative Opportunistic Pros: Efficiency, Easy for infrastructure Hard in theory Cons: Need across layer design to be realized Pros: Quick, adaptive, Hard in theory Cons: Cannot make money Hard to implement Channel Mobility

Dynamic Spectrum Access Game Model Auction Model Contract Model ⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯

Game Models The behavior of the cognitive radios in dynamic spectrum access networks can be modeled as a dynamic spectrum sharing game (DSSG).

Game Models Non-cooperative DSSG without centralized control The focus is on distributed design and cooperation simulation. Cooperative DSSG users do enforceable spectrum sharing through centralized authorities. Nash bargaining Solution plays an important role in cooperative games. Negotiated or leasing-based dynamic spectrum sharing This scenario can be modeled as multiplayer non- cooperative game with incomplete information. Auction theory is applied to formulate and analyze the interactions.

Auction Model Auction-Based Spectrum Sharing Game VCG is usually used to achieve socially optimal solution It may not be suitable for spectrum sharing because of the temperature-constraint, information overhead and computational burden. Two other auctions are generally used: SINR Auction: charging secondary users according to their received signal-to-interference-plus-noise ratio. Power Auction: charging secondary users based on their received power

My Work Opportunistic Spectrum Access to 3G Wireless CDMA Networks for Cognitive Radio Double Auction for Spectrum Resource Allocation using Coalitional Game Approach Recently ⋯⋯

References [1] I. Akyildiz, W. Lee, M. Vuran, and S. Mohanty, “NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey,” Computer Networks, vol. 50, no. 13, pp. 2127–2159, 2006. [2] L. Hu, V. Iversen, and L. Dittmann, “Survey of PHY and LINK Layer Functions of Cognitive Radio Networks for Opportunistic Spectrum Sharing,” Communications and Networking in China, pp. 10–24, 2009. [3] Y. Xiao and F. Hu, Cognitive radio networks. Auerbach Publications, 2008. [4] I. Akyildiz, W. Lee, M. Vuran, and S. Mohanty, “A survey on spectrum management in cognitive radio networks,” IEEECommunications Magazine, vol. 46, no. 4, pp. 40–48, 2008. [5] Y. Yi, J. Zhang, Q. Zhang, T. Jiang, and J. Zhang, “Cooperative Communication- Aware Spectrum Leasing in Cognitive Radio Networks,” in 2010 IEEE Symposium on New Frontiers in Dynamic Spectrum, 2010, pp. 1–11. [6] Z. Ji and K. Liu, “Cognitive radios for dynamic spectrum access-dynamic spectrum sharing: A game theoretical overview,” IEEE Communications Magazine, vol. 45, no. 5, pp. 88–94, 2007. [7] L. Chen, S. Iellamo, M. Coupechoux, P. Godlewski, P. da Vinci, and I. Milan, “An Auction Framework for Spectrum Allocation with Interference Constraint in Cognitive Radio Networks.”