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دانشگاه صنعتي اصفهان دانشكده برق و كامپيوتر Cognitive Radio ارائه کننده : محسن نادرطهرانی PowerPoint Presentation
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دانشگاه صنعتي اصفهان دانشكده برق و كامپيوتر Cognitive Radio ارائه کننده : محسن نادرطهرانی

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دانشگاه صنعتي اصفهان دانشكده برق و كامپيوتر Cognitive Radio ارائه کننده : محسن نادرطهرانی - PowerPoint PPT Presentation


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دانشگاه صنعتي اصفهان دانشكده برق و كامپيوتر Cognitive Radio ارائه کننده : محسن نادرطهرانی ارائه مقاله تحقيقي در درس “ رادیو نرم افزاری ” مدرس: دکتر محمد جواد امیدی نيمسال بهار 1386-1385. Agenda. Introduction Cognitive radio cognitive capabilities reconfigurability

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دانشگاه صنعتي اصفهان دانشكده برق و كامپيوتر Cognitive Radio ارائه کننده : محسن نادرطهرانی


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    1. دانشگاه صنعتي اصفهان دانشكده برق و كامپيوتر Cognitive Radio ارائه کننده : محسن نادرطهرانی ارائه مقاله تحقيقي در درس “ رادیو نرم افزاری ” مدرس: دکتر محمد جواد امیدی نيمسال بهار 1386-1385

    2. Agenda • Introduction • Cognitive radio • cognitive capabilities • reconfigurability • Spectrum sensing • Spectrum management • Spectrum mobility • Spectrum sharing • Physical Layer • TESTBED ARCHITECTURE AND IMPLEMENTATION • Collaborative Spectrum Sensing for OpportunisticAccess in FadingEnvironments • passive primary receiver detection

    3. Cognitive radio • Today’s wireless networks are characterized by a fixed spectrum assignment policy. • The limited available spectrum and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically

    4. Cognitive radio definition • Cognitive radio systems offer the opportunity to improve spectrum utilization by detecting unoccupied spectrum bands and adapting the transmission to those bands while avoiding the interference to primary users. • A Cognitive Radio (CR) is an SDR that additionally senses its environment, tracks changes and reacts upon its findings.

    5. Introduction : cognitive radio • Cooperative functionalities • Spectrum sensing & spectrum sharing • Spectrum management & spectrum mobility with all layers

    6. Cognitive radio • Cognitive capabilities • Capture information from radio environment • Temporal & spatial variations in radio environment • Interference avoidance • Reconfigurability • Dynamically programmed according to radio environment • Different transmission access technique

    7. Cognitive radio: cognitive capabilities Cognitive capabilities : • Real time interaction with its environment • Determine appropriate communication parameters • Adopt to dynamic radio environment

    8. Cognitive radio: cognitive capabilities • Spectrum sensing • Monitoring available spectrum bands • Capture their information • Detects the spectrum holes • Spectrum analysis • Estimating the characteristics of spectrum holes • Spectrum decision • Determining the data rate • Transmission mode • Bandwidth of transmission • Choosing spectrum band • Spectrum characteristics • User requirement

    9. Cognitive radio : reconfigurability • reconfigurability : Capability of adjusting operating parameters for transmission • Operating frequency • Modulation • User requirements • Channel condition • Transmission power • Communication technology

    10. Spectrum sensing • Adopt to its environment by detecting spectrum holes • Detect the primary users receiving data • Hard to have a direct measurements of a channel between primary receiver & transmitter • Primary transmitter detection • Matched filter detection • Energy detection • Cyclostationary feature detection • Cooperative detection • Interference-based detection

    11. Spectrum management • Spectrum sensing • Spectrum analysis • Operating frequency • Bandwidth • Interference level • Path loss • Wireless link error • Modulation scheme • Interference level • Link layer delay • Different protocols at different spectrum bands, different packet transmission delay • Holding time • Spectrum decision • QoS requirements • Spectrum characteristics

    12. Spectrum mobility: spectrum handoff • Spectrum mobility • Channel condition becomes worse • Primary user appears • Protocols of different layer of the network • Adopt to the channel parameters of operating frequency • Transparent to spectrum handoff and its associated latency • Shifting from one mode of operation to another • Smoothly • As soon as possible

    13. Spectrum sharing • Spectrum sharing process • Spectrum sensing • Spectrum allocation • Spectrum access • Transmitter-receiver handshake • Spectrum mobility • Spectrum sharing techniques • Architecture assumption • Centralized • Distributed • Spectrum allocation behavior • Cooperative • Non-cooperative • Spectrum access technique • Overlay • The FCC has legalized this type of sharing in the 5GHz band and is considering whether to allow it in theTV broadcast bands • underlay

    14. Physical Architecture of the Cognitive Radio

    15. Dynamic Range Reduction for ADC • Notch filter • Phase array antenna

    16. bit sequence 1 d (l) 1 . n n . o Cod o . i i s s r r e m e . v v . n n ) . o o T 1 c c x (t) F d (l) l l RF F . r a ( RF- e r i . l D/A Cod l . T a e Mod. r F s - a D m o p I . - x (t) t - . MT o l . t - e l l 1 l d(l) a a i N r . r a . e Cod p . s m Modulation • Physical Layer: OFDM • Transmitter structure and spectrum

    17. OFDM challenges • co-channel and adjacent channel interferers • There are several spectrum shaping techniques that could be used to improve OFDM spectral leakage: • Introducing guard bands • Windowing • Power control per sub-carrier

    18. TESTBED ARCHITECTURE AND IMPLEMENTATION • Berkeley Emulation Engine 2 (BEE2), which is a generic,multi-purpose, FPGA based, emulation platform for computationally intensive applications. • Each BEE2 can connect to 18 front-end boards via multi-gigabit interfaces. • The BEE2 consists of 5 Vertex-2 Pro 70 FPGAs. • Each FPGA can be connected to 4GB of memory with a raw memory throughput of 12.8Gps • All computation FPGAs are connected to the control FPGA via 20 Gbps links.

    19. Modular front-end system • The analog/baseband board contains the filters, ADC/DAC chips and a Xilinx Vertex-II Pro FPGA • Digital-to-analog conversion is performed by a 14-bit DAC running up to 128MHz while analog-to-digital conversion is performed by a 12-bit ADC running up to 64MHz. • The FPGA performs data processing and control, and supports 4 optical 1.25 Gbs links for transmitting and receiving data to/from BEE2 • A separate RF modem module connects to the baseband board. • The RF frequency is fully programmable in the entire 80MHz ISM band.

    20. Collaborative Spectrum Sensing for OpportunisticAccess in Fading Environments

    21. Fading environment • Log-normal Shadowing • Rayleigh Fading

    22. Collaborative Spectrum Sensing • In order to improve performance of spectrum sensing, we allow different secondary users to collaborate by sharing their information. • In order to minimize the communication overhead, users only share their final 1-bit decisions (H0 or H1) rather than their decision statistics • Let n denote the number of users collaborating. For simplicity we assume that all n users experience independent and identically distributed (iid) fading/shadowing with same average SNR • A secondary user receives decisions from n−1 other users and decides H1 if any of the total n individual decisions is H1. This fusion rule is known as the OR-rule or 1-out-of-nrule

    23. Probabilities of detection and false-alarm • Probabilities of detection and false-alarm for the collaborative scheme (denoted by Qd and Qf respectively) may be written as follows : • where Pd and Pf are the individual probabilities of detection and false-alarm • This collaborative scheme increases probability of detection as well as probability of false-alarm

    24. Probabilities of detection and false-alarm

    25. COLLABORATIVE SPECTRUM SENSING UNDERSPATIALLY-CORRELATED SHADOWING • shadowing correlation would degrade performance of collaborative sensing when collaborating users are close

    26. Question ? • How valid is the passive primary receiver assumption?

    27. LO Leakage • We explore the possibility of detecting primary receivers by exploiting the local oscillator (LO) leakage power emitted by the RF front end of primary receivers • Modern day radio receivers are based to a large extent on the superheterodyne receiver architecture invented by Edwin Armstrong in 1918

    28. LO Leakage Table • Over the years, improvements have been made to receiver architectures, resulting in reduced LO leakage power.

    29. Detection of LO Leakage • Detecting this leakage power directly with a CR would be impractical for two reasons. • Firstly, it would be difficult for the receive circuitry of the CR to detect the LO leakage over larger distances. • The second reason that it would be impractical to detect the LO leakage directly is that the LO leakage power is very variable, depending on the receiver model and year

    30. Sensor Node • We propose to build tiny, low cost sensor nodes that would be mounted close to the primary receivers • The node would first detect the LO leakage to determine which channel the receiver was tuned to. • It would then relay this information to the CR through a separate control channel using a fixed power level.

    31. Sensor Architectire • Several detection schemes exist to detect low energy signals. • Regardless of the detection scheme, the front-end architecture of the node will be the same

    32. Integration time vs. probability of error

    33. PERFORMANCE IMPROVEMENTS • There is no guarantee that a channel will be available • Assumption • Density of the primary receivers: D/km2 • Number of channels: M • Interference Radius of CR: R • All of the channels are equally likely to be used at any instance of time and the receivers are uniformly distributed

    34. At a receiver density of 10,000/km2 and an interference radius of 250m the probability is 0.99 that at least one channel is available

    35. EXPERIMENTAL RESULTS

    36. Refrence • [1]Software Define Radio Course Dr. Omidi.M.J. • [2]Detecting primary receivers for cognitive radio applicationsWild, B.; Ramchandran, • [3] Physical layer design issues unique to cognitive radio systems Cabric, D.   Brodersen, R • [4]Some physical layer issues of wide-band cognitive radio systems Haiyun Tang • [5]Collaborative spectrum sensing for opportunistic access in fading environmentsGhasemi, A.; Sousa, E.S. • [6] Device-centric spectrum management Haitao Zheng   Lili Cao • [7]Cognitive radio for flexible mobile multimedia communications Mitola, J., • [8]Cognitive radio: brain-empowered wireless communications Haykin, S. • [9]Cognitive Radio An Integrated Agent Architecture for Software Defined Radio Dissertation Doctor of Technology Joseph Mitola III

    37. THANK YOU