2014 11-06 melian
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Cogni7ve(Radio(in(HF(Communica7ons(Laura(Melián(Gu7érrez(
lmelian@ide7c.eu(
IDeTIC(Universidad(de(Las(Palmas(de(Gran(Canaria,(Spain(
Rennes,(6th(November(2014(
Outline(
• IDeTIC:(A(li/le(bit(about(us.((• Communica7ons(in(the(HF(band(• Cogni7ve(Radio(in(HF(communica7ons(
– Using(wideband(HF(receivers(for(spectrum(sensing(– Learning(with(Hidden(Markov(Models(– Decision(making(for(dynamic(spectrum(access(
• Conclusion(
1(
IDeTIC(
• Research(Ins7tute(within(ULPGC(
Research(ins7tute(within(Universidad(de(Las(Palmas(
de(Gran(Canaria(
2(
www.ide7c.eu(
Around 65 people
! Staff((PhD):(((( ( ( ( (29(! Staff((no(PhD): (((((( ( ( (((8(! Hired((no(permanent(staff):( (16(! MSc(students: ( ( ( (((6(! BSc(students:( ( ( ( (((3(
… and 12 external collaborators
IDeTIC:(Academic(ac7vi7es(
3(
Expert'course'on'aeronau.cal'and'airport'
management'
PhD'program'on''Communica.ons'Systems'
Short'course'on'“the'port'city”'
Master'on'home'automa.on,'
architecture'and'sustainable'for'
tourism'
Expert'course'on'IT'and'tourism'
Master'on'IT'solu.ons'for'the'environment'and'welfare'
IDeTIC:(Research(fields(
4(
RF'Systems'&'Radar'
Sensor'networking,'SmartSpaces'&'IoT'
Automa.c'geoloca.on'of'wildfires'
Mari.me'communica.ons'&'
surveillance'
Wireless'Photonics'&'InKhome'
Services'
IT'applied'to'Social'Sciences'
Space'&'AircraL'Electronics'
Biometrics'&'Signal'Processing'
66%
91%
57%
67%87%
50%
77%
66%
91%
57%
67%87%
50%
77%
HF(Communica7ons(• Research(line(between(IDeTIC((ULPGC)(
and(GAPS((UPM).(
• LongWdistance(HF(communica7ons(
• HFDVL(System((HF(Data+Voice(Link):(– Based( on( SoZware( Radio( with(
mul7carrier(modula7ons.(– Digital( interac7ve( voice( and( highW
data(rate(transmissions.((– Operates( wi th( commerc ia l(
transceivers.(– SISO( &( SIMO( (up( to( 4( Rx)(
configura7ons.(
• Three(configura7ons(in(data(transmission:(– File(transfer(– Short(message((SMS)(– HFMail( 5(
[EXAMPLE , ]
HFDVL:(Real(Tests(
6(
Tests done by the Spanish Department of Defense
Arnomendi ship (60 days) Flight from Manas to Zaragoza (14 h) Hercules C-130 airplane
Canary(Islands
6021 Km
7950'Km 3864'Km
HFSA_IDeTIC_F1_V01(Database(
Spectrum(ac7vity(in(the(14(MHz(amateur(band.(
• Power(measurements(in(the(frequency(domain.(• 600(kHz(bandwidth((200(channels(simultaneously):(amateur(band(and(other(sta7ons.(
• Dura7on:(10(minutes.(• Weekdays(&(Weekends.(• Each(sample(represents(a(3kHz(channel(in(2(seconds.(
7(
Yagiantenna
Broad-band HF transceiver
Spectrum powermeasurement
AgilentVector Signal Analyzer
PC with: System Vue and
VSA software
HFSA_IDeTIC_F1_V01(Database(
Spectrum(ac7vity(in(the(14(MHz(amateur(band.(
8(
Cogni7ve(Radio(in(the(HF(band(
• Challenges(to(face(in(this(environment(– There(is(no(coordina7on(among(users.(
• Frequency(alloca7on(per(country.(• TransWhorizon(behaviour.(
– Use(of(wideband(receivers:(• The(dynamic(range(of(the(received(power(is(wider(than(cellular(environments.(
• Strongly(affected(by(narrowband(interference.(
9(
Outline(
10(
Learning/(Knowledge(extrac7on(
Spectrum(sensing(
Wireless(receiver(
Decision(making(
Wireless(transmi/er(
Frequency'spectrum'
Transmit) Observe)
NBI(in(wideband(HF(receivers(
11(
NBI(in(wideband(HF(receivers(
12(
NBI(in(wideband(HF(receivers(
Wideband(HF(transceiver(–(Receiver(diagram(block(
13(
�������� ADC
BW = 1.0 MHz112 MHz
122.7 MHz
82-109 MHz
BW 1 MHz10.7 MHz
Image-rejection Filter 3-30MHz
Band Pass Filters 3-30MHz RF Amp
≤ 20 dB
DDS
Low Pass10.7 MHz
AGC
≤ 75 dB
RS232
���
µControllerCARDS12
�������� ADC
BW = 1.0 MHz112 MHz
BW = 1.0 MHz112 MHz
122.7 MHz
82-109 MHz
BW 1 MHz10.7 MHzBW 1 MHz10.7 MHz
Image-rejection Filter 3-30MHzImage-rejection Filter 3-30MHz
Band Pass Filters 3-30MHz
Band Pass Filters 3-30MHz RF Amp
≤ 20 dB≤ 20 dB
DDS
Low Pass10.7 MHz
AGC
≤ 75 dB
RS232
���
µControllerCARDS12
We(must(detect(and(mi7gate(in(the(analog(domain(
NBI(detec7on(in(wideband(HF(receivers(
14(
Our(proposal(based(on(Compressive(Sensing(for(NBI(detec7on((((
((A(parallel(system(to(the(wideband(receiver(with:((W(Detec7on(phase((W(Mi7ga7on(block(
ADC(with(fs(<<(fNyq(
15(
NBI(detec7on(in(wideband(HF(receivers(
Linear(Measurement(Process(
Φ(M x N transforma7on(
(M < N)(
x =(Original(Signal((N(samples)(
y =(Compressive(Measurements((M(measurements)(
y = Φ x "Basics(of(Compressive(Sensing:(
16(
NBI(detec7on(in(wideband(HF(receivers(
y = Φ x "Basics(of(Compressive(Sensing:(
x = Ψ s "Sparse(Signal(
Fourier(basis(
Compressible(Signal(
17(
NBI(detec7on(in(wideband(HF(receivers(
y =(Compressive(Measurements ( ( (K =(Sparsity(level)(
Φ =(Measurement(Matrix " " " "s =(Sparse(Signal("
x =(Original(Signal( ( ( ( ( ( (Ψ =(Sparsity(Basis("
NBI(detec7on(in(wideband(HF(receivers(
18(
Our(proposal(based(on(Compressive(Sensing(for(NBI(detec7on(((((
Unpublished(Results(
Outline(
19(
Learning/(Knowledge(extrac7on(
Spectrum(sensing(
Wireless(receiver(
Decision(making(
Wireless(transmi/er(
Frequency'spectrum'
Transmit) Observe)
Hidden(Markov(Model(
20(
Hidden'Markov'Model'Doubly( embedded( stochas7c( process( with( an( underlying(stochas7c(process(that(is(not(observable((it(is(hidden),(but(it(can(only( be( observed( through( another( set( of( stochas7c( processes(that(produce(the(sequence(of(observa7ons.(
...
Box 1 Box 2 Box N
Hidden(Markov(Model(
• The(three(basic(problems(of(HMM(– The(evalua7on(problem:( ((
(Forward(step(of(ForwardWBackward(procedure(– The(decoding(problem:((
(Viterbi(algorithm(– The(learning(problem:((
(BaumWWelch(method(
21(
Data(segmenta7on(
22(
2 s. 1 minute
1 0 0 ... ... ... ...1 1 1 1 1 1 1 1 1 1 00 0 0 0 0 0 0 0 0 0
3 12 3 ... 1
10 minutes
HF(Spectrum(Ac7vity(Predic7on(
• Main(model:((Ergodic(HMM((10(minutes(sequences(
• 3(submodels:((LeZWright(HMM((Observa7on(symbols(for(1((minute(
23(
HMM1 HMM2 HMM3
1 2 3 4 39 40... 38
HF(Spectrum(Ac7vity(Predic7on(
Submodel 1λ1 = (A1,B1,π1)
Submodel 2λ2 = (A2,B2,π2)
Submodel 3λ3 = (A3,B3,π3)
P(OT|λ2) P(OT|λ3)P(OT|λ1)
B’11 B’22 B’33
High-level model
New definition of the high-level model:
Previous detected states
High-level modelλ = (A,B’,π)
max(P(OT+1|λ))
Predicted state
B’11 0 00 B’22 00 0 B’33
B’ =
OT
Observations
t (min)TT-1
Submodels
t (min)T-1 TT-2
... ST
24(
HF(Spectrum(Ac7vity(Predic7on(
1 2 3 4 5 6 7 84
6
8
10
12
14
16
Acquired knowledge (min.)
Aver
age
erro
r rat
e (%
)
Global performanceNormal activityHigh activity
25(
Outline(
26(
Learning/(Knowledge(extrac7on(
Spectrum(sensing(
Wireless(receiver(
Decision(making(
Wireless(transmi/er(
Frequency'spectrum'
Transmit) Observe)
Joint(work(at(Supélec(
Decision(making(with(UCB(
Upper(Confidence(Bound((UCB)(algorithm(to(provide(HF(secondary(users(with(dynamic(access(to(the(spectrum.(
27(Joint(work(at(Supélec(
Exploita7on( Explora7on(
Decision(making(with(UCB(
28(Joint(work(at(Supélec(
Unpublished(Results(
Conclusion(
The(applica7on(of(Cogni7ve(Radio(to(HF(communica7ons(might(be(feasible(
(• Both( Learning(with(HMM(and(decision(making(with(UCB(can(help(secondary(HF(users(to(avoid(collisions(with(other(users.(
• A(compressive(detector(can(be(used(in(wideband(HF(receivers(to(detect(NBI.(
29(
Thank(you(for(your(a/en7on!(
Cogni7ve(Radio(in(HF(Communica7ons(Laura(Melián(Gu7érrez(
lmelian@ide7c.eu(
IDeTIC(Universidad(de(Las(Palmas(de(Gran(Canaria,(Spain(
Rennes,(6th(November(2014(
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