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دانشگاه صنعتي اصفهاندانشكده برق و كامپيوتر

Cognitive Radio: ارائه کننده

محسن نادرطهرانی

درس در تحقيقي مقاله ارائهافزاری “ نرم ” رادیو

امیدی: جواد محمد دکتر مدرسبهار 1385-1386نيمسال

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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 Opportunistic Access in Fading Environments

passive primary receiver detection

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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

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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.

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Introduction : cognitive radio

Cooperative functionalities Spectrum sensing & spectrum sharing Spectrum management & spectrum

mobility with all layers

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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

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Cognitive radio: cognitive capabilities

Cognitive capabilities :

Real time interaction with its environment Determine appropriate communication parameters Adopt to dynamic radio environment

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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

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Cognitive radio : reconfigurability

reconfigurability : Capability of adjusting operating parameters

for transmission Operating frequency Modulation

User requirements Channel condition

Transmission power

Communication technology

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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

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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

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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

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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

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Physical Architecture of the Cognitive Radio

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Dynamic Range Reduction for ADC

Notch filter Phase array antenna

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Modulation• Physical Layer: OFDM

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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

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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.

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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.

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Collaborative Spectrum Sensing for OpportunisticAccess in Fading Environments

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Fading environment

Log-normal Shadowing Rayleigh Fading

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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

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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

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Probabilities of detection and false-alarm

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COLLABORATIVE SPECTRUM SENSING UNDERSPATIALLY-CORRELATED SHADOWING

shadowing correlation would degrade performance of collaborative sensing when collaborating users are close

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Question ?

How valid is the passive primary receiver assumption?

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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

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LO Leakage Table Over the years, improvements have been made to receiver

architectures, resulting in reduced LO leakage power.

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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

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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.

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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

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Integration time vs. probability of error

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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

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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

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EXPERIMENTAL RESULTS

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Refrence [1]Software Define Radio Course Dr. Omidi.M.J. [2]Detecting primary receivers for cognitive radio applications Wild, 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

  

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