centre for development of advanced computing software defined radio & cognitive radio:...
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Centre for Development of Advanced ComputingCentre for Development of Advanced Computing
Software Defined Radio & Cognitive
Radio: Implementation
Initiatives
KRISHNA KUMAR S.KRISHNA KUMAR S.Centre for Development of Advanced Computing
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C-DAC
A National Centre of Excellence and premier R & D institution
under DIT, MCIT, Govt. of India
involved in the design, development and deployment of Electronics & IT- based
solutions for human advancement
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10 Locations
14 Centres 3000
members
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TETRA
VoIP
Digital Audio
Software Defined Radio Networking
TETRA-WiMax
MANET
CR
CNM
NG WF SDR
AM/FM Radios & Television
Alpha Numeric Information Displays
CCTV Cameras
Monitors
Direct Reception System
Multifunction mono/stereo Audio Consoles
CD Players
Equalizers
Monitoring Amplifiers
Digital Audio Work Stations
1990 2000 2010 2015
Broadcast & Communications @ C-DAC
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2004
2006
2007
2008
2009
2010/11
Study Repor
t
SDR Demos- 2 SCA WFS
C-DAC SDR
proposal
1st SDR Project
SDR PoC
DIT DIT DIT DIT2012
2012
2013
SDR Manpack
HandheldSDR-NC
C-DAC SDR-Demo DIT C-DACNAVY
CR
C-DAC SDR programme road map
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recent/current projects in SDR/CR
SDR for Naval Communication (DRDO)
SDR Manpack (DIT)
SDR Handheld (Core funding)
Cognitive Radio Networks (DIT)
jointly with IISc.
Next Generation Waveforms for SDR
Related projects
Mobile Adhoc NETworks (MANET)
Autonomic Network Management Systems (ANMS)
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Demonstrated re-configurablity with two SCA compliant waveforms
o TETRA UHF band & Militaryo Legacy FM Radio (VHF band) Clear Mode
the PoC SDR lab model
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SDR manpack: product perspective
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agenda
introduction SDR architecture SDR waveforms from SDR to CR Spectrum Sensing Engine application scenarios conclusions
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Software Defined Radio
a radio in which some or all of the radio’soperating functions are implemented
through modifiable software or firmware
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SDR Platform
Consists ofHardware,Firmware, Operating system Middleware
Takes different personalities, defined by the waveform that is loaded
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SDR platform architecture
LNA
IMGFILTER
MXR IFFILTER
AMP
AMP
RFFILTER
MXR
IFFILTER
DUPLEXEROR
T/R SW
ADC
DAC
FPGA
IF to 250MHz
12-16 BITS60-125MSPS
12-16 BITS200-1000MSPS
DSP+
GPP
MEM MEM
MMI
LO
LO
DDSSYNTH
LO
LO
FREQ STD
CLK
CLK
CLKCLK
CLK
CLK
CLK
CLK
ADC
CLK
12 BIT / 250MSPS
MXR IFFILTER
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RF transceiver
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Hopping Synthesizer
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Harmonic Filter Bank
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Baseband Boards
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agenda
introduction SDR architecture SDR waveforms from SDR to CR Spectrum Sensing Engine application scenarios conclusions
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Waveform: Definition
From http://www.wirelessinnovation.org/Introduction_to_SDR
The set of transformations applied to information to be transmitted and the corresponding set of transformations to convert received signals back to their information content.Representation of a signal in spaceThe representation of transmitted RF signal plus optional additional radio functions up to and including all network layers.
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Waveform
Can be visualized at different levels
ArchitectureConceptual entityDefines and abstracts the waveform functionsAlmost independent of the platform specifics
ImplementationPhysical realization of architecture Closely related to platform
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Waveform Architecture design
What it is?
What it is not?
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Technical Specification
s
Candidate Architecture
Architecture design process
SIMULATION
User behavioural
patterns
operational needs
Radio Standards
Final Architectur
e
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Waveform Implementation
Physical realization of architecture Closely related to platformImplementer should knowOverall platform architectureAvailability of Computing elements
• GPP, DSP, FPGAOther configurable resources
• clocks, vca, vco, tunable filters etc.
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Task Partitioning among CEs
GPP
Signaling and controlHigher layer and MAC functions
PHY Bit level processingSymbol rate processingSoft real-time numerically intensive tasks – e.g. channel estimation
Ideally all hard real time PHY functionsTasks best implemented using parallel architectureSymbol rate processing for wideband systems
DSP FPGA
RULES OF THUMB
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What devices in a given SDR?
Device architectures are being upgraded constantlyNew FPGAs realize DSP functions using specific architectures New DSPs use hardware accelerators to implement hard real time tasksGPP performance too scales up Blurred boundaries! Vanishing boundaries?Platform designer priorities do matter
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Portability & Re-configurability
Probably the most important features of SDRWaveform should be portable across platforms [a statement to be qualified]Waveform should be able to configure and control platform resourcesEnsured by proper design and implementation of Waveform and PlatformMay result in sub-optimal implementationbut that’s okay! in most cases
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Application Program Interfaces
Key enabler in ensuring portability & re-configurability
Abstracts low level functions
Platform provider to facilitate platform abstraction through APIs
Waveform implementer to use APIs to access platform features
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GPP & DSP APIs
GPP API calls are typically POSIX calls
DSP API calls are C-function callsAPI implemented as a libraryAPI to be used while building DSP image
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RF APIs
To abstract Radio functionsTuning LOConfigure Tx. DACConfigure AGC Etc.
API calls are pre-defined messages
Processed and executed by a dedicated controller
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FPGA: Wrapper
Equivalent of API for FPGA Wrapper defines the platform logic Waveform logic defines the (part of) PHY signal processing Waveform logic to be integrated with wrapper
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Waveform Logic
Waveform Logic
EMIF GlueEMIF Glue
SPI GlueSPI Glue
McBSP Glue
McBSP Glue
uPP GlueuPP Glue
ADC FIFOADC FIFO
DAC FIFODAC FIFO
UARTGlueUARTGlue
GPIO(Push
Buttons, LEDs, DIP Switches,
GPIO Headers)
GPIO(Push
Buttons, LEDs, DIP Switches,
GPIO Headers)
DSPDSP
ADCADC
DACDAC
RF ControlRF Control
UART PortUART Port
FPGA IO Ring
TOP module
SPI Signals
EMIF
McBSP
uPP
14 bit
16 bit
Interrupt 1Interrupt 2
FPGA: Architecture
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FPGA: model based design
To design waveform signal processing
Can be done in a graphical way
Designer need not no low-level architecture of the device
Can be used jointly with Matlab/Simulink or similar simulation environments
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FPGA: model based design tools
Xilinx - System GeneratorAltera - DSP BuilderActel - SynplifyLattice - ispLever DSP
Agilent system view – VHDL code generation
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FPGA: integration with wrapper
Combine the HDL source level
Combine the wrapper source with waveform netlist Similar to adding a library
Combine at bitmap level Wrapper logic implemented in advanceWaveform logic added using partial reconfiguration
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agenda
introduction SDR architecture SDR waveforms from SDR to CR Spectrum Sensing Engine application scenarios conclusions
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from SDR to CR
A natural evolution
CR, by nature, has to be an SDRbut,
an SDR with certain specific fetures.
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CR additional requirements
A truly wideband radio front end
Support for White/Gray space detectionSpectrum sensing - hardware & softwareGeo-location and Database
• IEEE 802.22
Dynamic Spectrum ManagementChannel & Bandwidth allocationRate adaptation & Tx power control
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from SDR to CR: concerns
Algorithm complexities – of course
A truly wideband radio front endTx side RF Power ampsRx side – wide band sensing
AD/DA conversion bottle-necks
Noise, sensitivity, interference protection, SFDR
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agenda
introduction SDR architecture SDR waveforms From SDR to CR Spectrum Sensing Engine – design & implementation application scenarios conclusions
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Primary Signal Details
Primary: Terrestrial analog TV txn in India
System: CCIR system B,G PAL
Bands: • Band II VHF: 174 to 225 MHz• Band IV UHF: 470 to 582 MHz
Channel BW: 8 MHz
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Requirements
Incumbent Detection Threshold: -94 dBm (measured at peak of sync)
Channel Detection Time: <=2 sec per channel
Detection Performance: Probability of Detection >=90% at False
Alarm rate of <= 10%
Guided by IEEE 802.22 WRAN WG interim recommendations
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Platform - Lyrtech SFF SDR
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From SS Algorithm to SS Engine (from “recipe” to “dish”)
Study of algorithmStudy of hardware architectureDesigning software architectureOptimal partitioning of algorithm Model based design / C-program developmentFixed point considerations
dynamic range, bit growth, over/under-run, truncation error
Defining and realizing interfacesDebugging, testing and optimization
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Detection Scheme
Pre-processing/Feature extraction stage Extracts the spectrum around the picture carrier
Energy Detection stage Computes the energy around the pictures carrier
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Pre-Processing
Decimating filter stages
5 5 5 2
Digital IF BW: 8MHz125 Msps
14 bits
to sensing algorithm BW: 100kHz
500 Ksps32 bits
DDS @ 30MHz
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Implementation
Implemented in the FPGA part (Virtex 4)Design using Simulink / System generator
Model based design approach
Fixed point implementationWord-length selection
bit growth truncation error resource utilization
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Energy Detection
N samples x B buffers
Gives the adavntage of averaging
Reduces the FFT implementation complexity
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Implementation
Implemented in the DSP (TMS320C64X)
Code developed in C language
Debugged using Code Composer Studio & XDS560 ICE
A fixed point implementation
Word-lengths selection
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User Interface
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Test Settings
Picture carrier: 67.25MHz
Channel Bandwidth: 8MHz
Video pattern: White
Sensing duration: 20.4 ms
Sampling rate: 125Msps
Ensemble size: 1e5
SNR values: -30dB, -27dB, -24dB
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PAPR for ATV
Courtesy: Martyn J. Horspool, Analog-to-digital Upgradeable Transmitters For the Worldwide Market, Harris Corporation
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Results
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Results
System meets the false alarm/miss detection performance at -27 dB SNR
Highly encouraging result
Enough margin to accommodate large scale fading
Caveat: This is only a lab measurement
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agenda
introduction SDR architecture SDR waveforms from SDR to CR Spectrum Sensing Engine application scenarios conclusions
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application areas
MilitaryPMR (public safety, police, paramilitary)Disaster managementCommercial Cellular (Base Stations)Rural broadband accessIEEE 802.22 system adaptaion
Tele-Medicine
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acknowledgements
Simon Zachariah
Beena K. T.S. Sagar
Chandra R. Murthy
Shine K. P.Satheesh Kumar S.