Jems_Thesis

Experimental Investigation of Energy, Bandwidth and Modulation on Spectrum

Sensingby

Jems Pradhan

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Major Professor :Dr.Yanxiao Zhao Committee Members :Dr. Dimitrios E Anagnostou, Dr. Cassendra Degen

Master of Science in Electrical Engineering South Dakota School of Mines and Technology Rapid City, July 6, 2015

[email protected], July 6, 2015

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OUTLINE

• BACKGROUND

• Energy-and-Bandwidth Spectrum Sensing (EBSS)

• Two-Stage Spectrum Sensing• Conclusion • Future Work


Static and Dynamic Spectrum PolicySpectrum Sensing Methods

Experimental VerificationSensing performance comparison with energy detection

Theoretical Analysis Experimental Analysis


FREQUENCY

STATIC AND LIMITED

SPECTRUM SCARCITY


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Dynamic Spectrum Access

Dynamic Exclusive Use Model Open Sharing Mode Hierarchical Access

Model

Spectrum Property Rights

Dynamic Spectrum Allocation Spectrum Underlay Spectrum Overlay


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• Static Spectrum Access Policy results underutilization of available spectrum.

• Dynamic Spectrum Access(DSA) is a promising solution.

Frequency

Power

Time

BUSY IDLE BUSY IDLE BUSY

Secondary User(SU) can use this IDLE channel via Dynamic Spectrum Access

• Spectrum Sensing to detect the IDLE and BUSY channel.• Detect the incoming PU or SU occupied by SU in the idle channel.


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Spectrum Sensing Techniques:


• Energy Detection Method: widely used

• Other Sensing Methods:

• Matched Filter Detection

• Waveform Based Sensing

• Radio Identification Based Sensing

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Energy Detection Method:

ri= signal received by user Secondary User i ni = Additive White Gaussian Noise s= signal that Primary User transmits

λE= predefined Energy Threshold



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Frequency (Channel)

Ener

gy L

evel

-------------------------------------------

Signal

NoiseEnergy Threshold

PROBLEM STATEMENT

Drawback of Energy Detection Method: What if the noise has an energy level greater than λE ?

Noise but considered as signal according to energy detection

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Energy-and-Bandwidth Spectrum Sensing (EBSS):

λB = pre-defined bandwidth thresholdB = bandwidth of the received signal

• Energy of the received signal should be higher than the energy threshold .

• Bandwidth of the received signal should be higher than the bandwidth threshold.

(r > λE) AND (r > λB) =

False, if H0

True, if H1


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Principle of Energy Detection and EBSS

Frequency (Channel)

Ener

gy L

evel

Figure: Energy Detection Method

-------------------------------------------

Energy Threshold

False Alarm

Signal

Noise

Frequency (Channel)

Ener

gy L

evel

Figure: Energy-and Bandwidth Detection Method

-------------------------------------------

Energy Threshold

Signal

Noise

Noise


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SENSING PERFORMANCE


• Sensing Performance Metrics– Probability of false alarm: Channel sensed busy when no signal is present– Probability of miss detection: Channel sensed idle when signal is present

P1f is the Probability of False alarm for Energy Detection Method

P1m is the Probability of Miss Detection for Energy Detection Method

P1f = Pr(r > λE / H0)

P1m = Pr(r < λE / H1)

P2f is the Probability of False Alarm for EBSS

P2m is the Probability of Miss Detection for EBSS

P2f = Pr[(r > λE) AND (b> λB) / H0]

P2m = Pr{NOT[(r > λE) AND (b> λB)] / H1}

= Pr{[(r < λE) OR (b < λB)] / H1}

EXPERIMENTAL SETUP I


Figure: Schematic of USRP N200

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GNU Radio and USRP

• GNU Radio Software is a free and open source software for Software Defined Radio.

• USRP N200.

• Motherboard (XILINX Spartan 3A-DSP 1800).• Daughter board XCVR2450.• Operating frequency range of XCVR2450 2.4-2.5GHz and 4.95-5.85GHz

which is an ISM band.• Antenna used is the VERT2450 vertical antenna with dual band (2.4 -

2.5 and 4.9 - 5.9 GHz).


Received Signal LNA IF

DAUGHTER BOARD

ADC DDC

MOTHERBOARD

HOST COMPUTER GNU SOFTWARE


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EXPERIMENTAL RESULTS

Frequency (GHz)

Ener

gy le

vel (

dB)

Figure: USRP trying to receive 2.4 GHz Signal when no signal was sent from the transmitter .


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Frequency (GHz)

Ener

gy le

vel (

dB)

Figure: USRP Device receiving 2.4 GHz signal when 2.4 GHz was sent from the transmitter.


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Frequency (GHz)

Ener

gy le

vel (

dB)

Figure: USRP trying to receive 2.42 GHz Signal when no signal was sent from the transmitter .


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Frequency (GHz)

Ener

gy le

vel (

dB)



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Frequency (GHz)

Ener

gy le

vel (

dB)

Figure: USRP Device receiving 2.45 GHz signal when no signal was sent from the transmitter.


[email protected], July 6, 2015 21

Ener

gy le

vel (

dB)

Frequency (GHz)


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Frequency (GHz)

Ener

gy le

vel (

dB)

Figure: USRP Device receiving 5.1 GHz signal when no signal was sent from the transmitter.


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Frequency (GHz)

Ener

gy le

vel (

dB)

Figure: USRP Device receiving 5.1 GHz signal when 5.1 GHz signal was sent from the transmitter.



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Performance Evaluation using Probabilities of False Alarm and Miss Detection of theoretical and practical energy detection

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Performance Evaluation using Probabilities of False Alarm and Miss Detection


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• Theoretical analysis of Energy-and-Bandwidth Spectrum Sensing.

• Experimental Analysis of Energy-and-Bandwidth Spectrum Sensing.

• Analysis of Performance Metrics using Probability of False Alarm and Probability of Miss Detection.


Question : Is the signal detected is originated from a PU or an SU ?

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Two-Stage Spectrum Sensing Approach

• Utilizes Energy and Bandwidth of EBSS and also utilizes the Modulation to

distinguish channel from three states : H0(idle), H1(occupied by PU) and

H2(occupied by SU).

False, if H0

(r > λE) AND (b> λB) =

True, if H1 or H2

• H1 or H2 is detected based on the modulation scheme.

• PU and SU operate using different modulation scheme QPSK and BPSK respectively .

• SU with two demodulators to detect both QPSK and BPSK.


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Basic concept of MODULATION


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Mathematical model BPSK and QPSK

SBPSK (t) = m(t) cos(2πfct + θ)

Figure: Block Diagram of BPSK Modulator

SQPSK (t) = AcmI(t) cos(2πfct) + AcmQ(t) sin(2πfct)

Figure: Block Diagram of QPSK Modulator


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Square Law

Device

Band Pass Filter

Frequency Divider

Recovered Signal

Received Signal

Integrate and Dump

Circuit

Bit Sychronizer

m(t) cos(2πfct+θ)cos2(2πfct+θ) cos(4πfct+2θ) cos(2πfct+θ)

m(t) cos(2πfct+θ)

m(t) cos2(2πfct+θ)

Figure: Block Diagram of BPSK Carrier Recovery Circuit.

S(t) = Ac2[mI

2(t) cos2(2πfct)] – 2 Ac mI(t) cos(2πfct)* Ac mQ(t) sin (2πfct)* + Ac

2[mQ2(t) sin2(2πfct)]

S(t) = Ac mI(t) cos(2πfct)


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EXPERIMENTAL SETUP II

Figure: Experimental Setup to analyze the effects of different modulation scheme.


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Figure: PU and SU using different demodulation techniques.


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Figure: PU and SU using different demodulation techniques varying the data rate.


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• Analysis Based on packet by packet by considering frequency, data rate and modulation. SU uses BPSK and PU uses QPSK in all the experiments conducted hereafter.

Figure: A SU receiver (USRP N200) receiving BPSK signals at 2.47 GHz


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Figure: A PU receiver (USRP N200) receiving QPSK signals at 5.1 GHz


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Figure: SU receiving signals at 2.47 GHz modulated using BPSK when PUsending signals at 2.47001 GHz using QPSK


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Figure: An SU receiver receiving BPSK signals at 2.45 GHz when there is another SU transmitter at 2.45 GHz using BPSK.


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Figure: USRP N200 receiving signals at 2.47 GHz modulated using BPSKwhen there is another transmitter at 2.47 GHz using QPSK


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Figure: USRP N200 receiving signals at 2.49 GHz modulated using BPSKwhen there is a transmitter at 2.49 GHz using BPSK.

Figure: USRP N200 failing to receive signals at 2.49 GHz using QPSK whenthere is a transmitter at 2.49 GHz using BPSK


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PU Tx QPSK

Modulated

SU Tx BPSK

Modulated

SU Rx Equipped with

QPSK + BPSKDemodulators

Detected PU

Detected SU

Block Diagram of Proposed SU Receiver


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Figure: USRP N200 successfully receiving signals at 2.45GHz using QPSK when there is a PU transmitter receiver pair at 2.45 GHz using QPSK



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CONCLUSION

• A new approach of spectrum sensing EBSS is proposed and experimentally verified.

• Spectrum performance has been drastically improved using EBSS compared to traditional energy detection method.

• A new method is proposed to identify the PU and SU signal using Energy, Bandwidth and Modulation Sensing Approach.

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FUTURE WORK

• Sensing performance of EBSS will be analyzed theoretically.

• SU equipped with two demodulators and aware of the modulation implemented by PU and SU.

• Experiments are only conducted on ISM bands more experiments could be conducted on different frequency range.


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PUBLICATIONS• Zhao, Y., Pradhan, J., Huang, J., & Sun, H. (2014, October). Experimental

approach: energy-and-bandwidth spectrum sensing using GNU radio and USRP. In Proceedings of the 2014 Conference on Research in Adaptive and Convergent Systems (pp. 174-179). ACM.

• Zhao, Y., Pradhan, J., Huang, J., Luo, Y., & Pu, L. (2015). Joint energy-and-bandwidth spectrum sensing with GNU radio and USRP. ACM SIGAPP Applied Computing Review, 14(4), 40-49


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THANK YOU !!!



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