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Les communications sans fil prennent une place prépondérante dans la société de l’information. Les besoins toujours croissants de débit, de qualité et de couverture réseau imposent de revoir entièrement les modèles techniques et économiques des outils actuels. INTELSIG, service de Traitement du Signal de l’ULg et son partenaire, la grande école d’ingénieurs française SUPELEC (Ecole supérieure d’électricité) nous en diront plus sur la radio-logicielle (Software-defined radio), une des technologies retenues pour apporter une solution à toutes ces contraintes.
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Parole d’expert
Ir Jonathan PISANE, Doctorant ULg - INTELSIG Ir Sylvain AZARIAN, Ingénieur de Recherche - SUPELEC
Software Defined Radio : enjeux et perspectives
Avec le soutien de :
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 1
Sylvain AZARIAN - Supélec Jonathan PISANE – Ulg / INTELSIG - Supélec
Software Defined Radio : Challenges and Opportunities
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 2
Talk outline
• Part I – Introduction to SDR – Need for new system architectures – SDR as a potential solution – Basics to understand how it works – Demos
• Part II – SDR in OUFTI-1 Satellite • Part III – Radar applications
– What is radar ? – “Active” and “passive” radars – Using passive radar techniques to collect RCS
• Introduction to J. Pisane PhD work • System presentation • Live demo • Results
• Part IV– Challenges – Balancing technical constraints – Possible issues – Consumer Electronics and product life-cycle
• Part V – Future mobile Networks – Quick presentation on active research topics for future mobile networks
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 3
Part I
1 – Introduction to Software Defined Radio
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 4
Communication system
Osc.
Modulator
time
0 1 0 1 ….. 1
Message A
Osc.
Demodulator
time
0 1 0 1 ….. 1 Message A
A communication system takes input message A at transmitter side and delivers it at receiver side. On transmit side, a modulator is used to “encode” the information to be transmitted by the carrier. This information is then “extracted” using a demodulator at the receiver. This message can be analogical (voice, image) or digital (data).
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 5
Frequency allocation plan (USA)
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 6
Spectrum allocation… spectrum saturation
Currently, spectrum is allocated on a « per usage » basis. Ideal for broadcasting systems, this scheme is no longer efficient when spectrum is saturated and new « point to point » communication is required.
Dynamic spectrum Access is a possible solution to this saturation. New allocation rules… new techniques… new challenges
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 7
The limits of « classical hardware design »
One technology => one chip
• GSM • GPRS • UMTS • 4G • WiFi • BlueTooth • WiMAX • …
Does not fit !
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 8
Lack of space for new wideband telecoms
HF VHF
Allocated band : not available
Need for more throughput => need for more bandwidth … where ????
One solution : “bandwidth aggregation” • Design modulations and RF chains able to transmit on sparse spectrum
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 9
Stacking RF technologies – Cell. phones
RF modules – Nokia X6 • Phone CDMA • WiFi • BlueTooth • GPS
• Close in frequency, but completely different systems ►one chip by function ► cost and battery life…
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 10
Stacking RF technologies – Broadcast radio receivers
One sub-circuit by modulation type… Adding a new modulation means redesigning the hardware
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 11
Using applications to replace hardware
SDR technologies bring a new approach to have ‘one hardware for all’
• Wide bandwidth • High resolution AD & DA converters • Sample signals from 1µVolt to 50 mVolt with constant linearity… • Tunable power, tunable gain, … • Unlimited speed to main application..
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 12
Sampling signal to process it by software
0010101010101000 0111010101111010 0100010010001001 … 0100010011011100
Sampling clock (defines the “zoom level” on the incoming signal)
RF signal Continuously varying voltage from the antenna
Bit stream
Analog to digital converter (ADC) : at each ‘top’ given by sampling clock, a ‘picture’ of the incoming signal is taken and delivered as a binary word.
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 13
Basic SDR system architecture
CPUADCDAC
Software Defined Radio equipment : • Antenna and basic filtering, • Analog to Digital conversion, • CPU + applications.
Digital world Analog world
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 14
Communication system - Modulation Signal modulation involves changes made to sine waves in order to encode information. The mathematical equation representing a sine wave is as follows:
We see we have two “variables” we can use separately : amplitude and angle. Each modulation technique (AM,FM,…) uses a different scheme to change these variable depending on the information to send. In a digital communication system, the information transmitted is called the baseband.
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 15
Modulation – one example ASK (OOK) – Amplitude Shift Keying – playing with amplitude
In this modulation scheme, we change Ac depending on the bit value to transmit. We can use two levels or “on off keying” (OOK).
Modulator
Osc. time
Demodulation is quite easy but this method is very sensitive to parasites.
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 16
Quick introduction to the theory… why I & Q ? Signal spaces and basis functions
Basis : Two orthogonal functions chosen as basis set : sine and cosine.
Signal space : Let’s define our message M(t) as a two-dimension vector M(t)={x(t) ; y(t) } We can represent our message on a 2D plane using Cartesian or polar coordinates.
M(t) M(t) Q
I
In our signal space, we have the horizontal axis called “I” (in phase) and vertical axis called “Q” (in quadrature). We can also use complex numbers to represent our messages : M(t) = S.ejɸ
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 17
Digital modulation
0 1 0 1 ….. 1
Using a predefined “dictionary” (constellation), each sub-block of bits is mapped in IQ plane :
Ex: QAM16
The corresponding I and Q values are then used to generate baseband “time” signal. Of course the “dictionary” must be shared by transmitter and receiver…
One can imagine a complete set of constellations to map bits to symbols :
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 18
Digital transmitter architecture Back to our RF chain…
“Polar modulator”, quite complex to realize in hardware because requires evaluation of :
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 19
Digital transmitter architecture Quadrature modulator
Quadrature modulator is the most common design used in digital communications. To increase communication throughput, this scheme can also be parallelized on multiple frequencies simultaneously. OFDM uses multiple carriers, carefully chosen, to transmit bursts of data.
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 20
Digital receiver architecture Quadrature receiver
Minimalistic architecture for quadrature signals recovery: Incoming signal is “projected” (multiplied) with our two basis functions (sin & cos) to retrieve projections over I and Q axis in our signal space.
CPU
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 21
Introducing demo #1 – SDR Dongle from Microsat
USB bridge
Analog to Digital converter
RF Tuner
RF amplifier
Antenna socket
No signal processing is done ‘aboard’ : Samples are sent to host PC via USB and need to be processed to extract information.
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 22
HDSDR : Software Defined Receiver application
Waterfall display
frequency
time
spectrum display
Zoom area
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 23
Demo #1 : Ingredients
• See it working…
easySDR USB dongle From microsat
PC
WinRAD : Multimode SDR decoding freeware
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 24
Part II
2 - SDR In OUFTI-1 Satellite
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 25
MS Thesis A. Dedave • Implementation of FM, AX.25 and D-STAR radiocommunication protocols on SDR • Feasibility study for future nanosats
• Develop SDR experience @ULg – Montefiore
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 26
Analog RF front-end: Rx
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 27
Analog RF front-end: Tx
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 28
Digital back-end: Tx & Rx
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 29
Application (1): D-STAR – Rx & Tx
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 30
Application (2): AX.25
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 31
MS Thesis A. Dedave: Demos
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 32
Part III
3 - Radar applications
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 33
Definition and application
Military air surveillance (surveillance and tracking ) maritime surveillance battlefield surveillance missile seeker guidance & interception imagery
Civilian air traffic control (ATC) maritime navigation control collision avoidance satellites tracking road traffic control & ERP archaeological & geologic research
RADAR = RAdio Detection And Ranging
transmit & receive E.M. waves
detect the target
provide localization (range, angle, velocity)
can provide classification, identification of target
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 34
Radar in the day to day life Air Traffic Control and
monitoring Weather Radar
http://www.meteox.com/h.aspx?r=&jaar=-3&soort=loop1uur
Maritime Surveillance
Radar Presence Detection (Domotic)
Road Traffic Control
360km
200 to 400km
10 to 40km
10 to 30 m
200 to 400km
10 to 40 m
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 35
Less popular but so useful… Fighter control radar AWACS
Early Warning Surveillance
Imaging & remote Sensing from the earth
Air Defence Radar
Through the wall radar
50 to 140km
> 400km
700 to 1000 km
200 to 400 km
1 to 10 m
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 36
Radars you haven’t imagined…
Very Long range skywaves radar
Passive Radar
1000 to 3000 km
1 to 80 km
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 37
Radar principle Peak power : Pe (~ 1 kW à 1 MW ) Average power : Pm (~ 100 W à 10 kW )
Dt - Pulse delay, used to retreive the range D Dt = 2D/c
Tr - Pulse period (~100 ms à 10 ms )
t - Pulse duration (~1 à 100 ms)
Emitted signals
Received
The antenna beam is narrow and scanning all directions
This allows for measuring the target direction
1 to 3°
Scanning 10rpm
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 38
Passive radar
Passive radar relies on existing transmitters (donors). By processing reflected and direct path signal, it is possible to compute target position and speed. For this specific application, SDR offers the possibility to receive any type of donor.
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 39
Introduction to J. Pisane PhD work SN533, A320
transponder on
? Unknown aircraft transponder off
Goal of Ph. D. thesis: Identify the ?’s
?
SN533, A320
Radar
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 40
Introduction to J. Pisane PhD work
Receiver 2 Emitters of opportunity
Receiver 3
Receiver 1
GSM
DVB-T
• Operate at "low frequencies" (<1GHz) • Data = RCS of targets • No image reconstruction
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 41
Using passive radar techniques to collect RCS System overview
USB or remote
Network (direct or Internet)
Network (direct or Internet)
Donor(VOR, FM station, …)
Donor(VOR, FM station, …)
Geo databaseDonors & Receivers
Software Defined Receiver
Software Defined Receiver
SDR controller
ADSB-B decoderKinetic SBS-1
ADSB Receiver
Apache Tomcatsupervision
MySQL
remote
Central systemData collection / storage / analysis
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 42
RCS Data collection: System overview
Position given by ADSB receiver
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 43
RCS Data collection: System overview
Software Defined Receiver
Receiver tuned on a “quiet” area of the spectrum to have good SNR
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 44
RCS Data collection: System overview
Old samples New samples
Decimation
shift
We keep around
1second of signal
FFT
Samples
Axe
YFrequency (FFT bin)
‘Direct Path’ signal : spectrum of original transmitted signal
‘Echo path’ : same signal delayed and
shifted (Doppler effect)
SNR !
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 45
RCS Data collection: System overview
Live demo ! (if it works )
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 46
Typical spectrogram
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 47
Recovered RCS of plane
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 48
Part IV
4 - Software Defined Radio: challenges
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 49
Market driven by « Consumer Electronics »
Each iPhone® gives $300 operational profit… More than 8MILLIONS units sold in 2010 => 300x8000000 = 240 Million$
Current designs are “Keep it simple, Keep it low cost” new models every 6 month, design driven by marketing team
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 50
Balancing a set of constraints
Wideband signals => Wide bandwidth
High frequency => High sampling rate
Huge amount of data to process in real-time
System design is complex
=
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 51
Processing power
• SDR system to process WiFi signals • One channel is 22MHz wide, sampled at 44 MSPS at 16 bits (I
and Q) gives : – 44M * 4 bytes / seconds ➜ 176 MBytes/seconds
➜ Too much data to be processed by a « PC » processor ➜ Specific pre-processing hardware required (FPGA, DSP…) ➜ Such system require hardware + software + radio engineers to work
together
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 52
Analog front-ends must be designed with care Effect of imperfections on transmitted symbols
Any difference with ideal characteristic will degrade RF signal generation and… make signal demodulation more difficult.
Imperfection
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 53
Part V
5 – Research at Alcatel Lucent Chair in Flexible Radio @ Supélec
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 54
« Small cells » as a solution to densification
• Many small, low-cost, low-power BSs (50 to 150 meter range) as additional capacity/coverage layer under a macro cell deployment
• Use existing backhaul infrastructure • Collocated with existing street furniture (in-street cabinets/telephone booth, lamp posts,
etc.) ➜ no cell site acquisition • Self-organizing/maintaining (plug & play) ➜ no planning
Current mobile networks cannot follow customer bandwidth requirements… need for new network solutions
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 55
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 56
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 57
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 58
Software Defined Radio: Enjeux et perspectives – Sylvain AZARIAN et Jonathan PISANE 59
Future of mobile networks – ALU Chaire @ Supélec
We dream to have…
The challenges we have to face…