Power control in cognitive radio systems based on spectrum sensing side information
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POWER CONTROL IN COGNITIVE RADIO SYSTEMS BASED ON SPECTRUM SENSING SIDE INFORMATION. Karama Hamdi, Wei Zhang, and Khaled Ben Letaief The Hong Kong University of Science and Technology Communications, 2007. ICC '07. IEEE International Conference. Outline. Introduction System Model

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POWER CONTROL IN COGNITIVE RADIO SYSTEMS BASED ON SPECTRUM SENSING SIDE INFORMATION

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Power control in cognitive radio systems based on spectrum sensing side information

POWER CONTROL IN COGNITIVE RADIO SYSTEMS BASED ON SPECTRUM SENSING SIDE INFORMATION

Karama Hamdi, Wei Zhang, and Khaled Ben Letaief

The Hong Kong University of Science and Technology

Communications, 2007. ICC '07. IEEE International Conference


Outline

Outline

  • Introduction

  • System Model

  • Power Control Based on Spectrum Sensing Side Information

  • Numerical Result

  • Conclusion

  • Comments


Introduction

Introduction

  • Cellular network bands are overloaded in most parts of the world but amateur radio or paging frequencies are not.

  • Some important abilities should be provided by the cognitive radio [5]

    • spectrum sensing, dynamic frequency selection, transmit power control

  • Challenging problem

    • The interference which occurs when a cognitive radio accesses a licensed band but fails to notice the presence of the licensed user.

[5] S. Haykin, “Cognitive radio: brain-empowered wireless communications,” IEEE J. Sel. Areas in Commun., vol. 23, pp. 201–220, Feb. 2005.


Introduction cont d

Introduction (cont’d)

  • In [8], A power control rule was presented to allow cognitive radios to adjust their transmit powers in order to guarantee a QoS to the primary system

    • Base on the locations of the licensed user

  • In this paper, we present a power control approach in cognitive radio systems base on spectrum sensing side information

    • To mitigate the interference to the primary user due to the presence of cognitive radios


Introduction cont d1

Introduction (cont’d)

  • This approach consists of two steps

    • the shortest distance between a licensed receiver and a cognitive radio is derived from the spectrum sensing side information

    • the transmit power of the cognitive radio is determined based on this shortest distance to guarantee a quality of service for the licensed user


System model

System Model

Decodable region

Primary transmitter

Primary receiver

Cognitive radio

Protection region

PTx’s transmit power: Qp

CR’s transmit power: Qc

Δ (dB): the signal attenuation of the distance Rd

μ (dB): the margin of protection


System model cont d

System Model (cont’d)

  • In the secondary system,

    • A cognitive radio is considered to work in the same frequency band as the primary system

    • “Listening before accessing”

  • Let d (m) denote the distance between the primary transmitter and the cognitive radio

    • Computing d will be a challenging problem

  • QoS of the primary receiver

    • Limit the transmit power Qc of the cognitive radio


System model cont d1

System Model (cont’d)

  • The worst case scenario

    • The primary receiver is located on the crossing point between the boundary of the protection region and the line from the primary transmitter to the cognitive radio

    • can guarantee a good QoS for the primary receiver in operation at any location inside the protection region

  • The transmit power of the cognitive radio

    • inflicts tolerable interference on the primary receiver

    • depends on the SNR loss (μ+ψ) in dB

    • The SNR loss due to the distance d is give by η =ψ+Δ

  • The transmit power control problem is essentially converted to

    • The problem of evaluating the SNR loss η due to d for a given μ and Δ


Power control based on spectrum sensing side information

Power Control Based on Spectrum Sensing Side Information

  • Firstly propose an idea of determining the distance dbetween the primary transmitter and the cognitive radio from spectrum sensing

  • The transmit power of the cognitive radio can be controlled based on the distance d in order to guarantee a QoS to the primary receiver


Power control based on spectrum sensing side information cont d

Power Control Based on Spectrum Sensing Side Information (cont’d)

  • Spectrum Sensing Side Information

    • T: the observation time,

    • x(t): the received signal at the cognitive radio

    • s(t): the transmitted signal from the primary transmitter

    • n(t): the zero-mean additive white Gauassian noise (AWGN) with variance σ2

    • h: the Rayleigh fading channel coefficient

  • The instantaneous SNR is defined as


  • Power control based on spectrum sensing side information cont d1

    Power Control Based on Spectrum Sensing Side Information (cont’d)

    • The energy of the received signal, denoted by Y, is collected in a fixed bandwidth W

    • and a time slot duration T and then compared with a pre-designed threshold λ

    • If Y > λ then the cognitive radio assumes that the primary system is in operation, i.e., H1. Otherwise, it assumes H0.


    Power control based on spectrum sensing side information cont d2

    Power Control Based on Spectrum Sensing Side Information (cont’d)

    • The average probability of false alarm, detection and missing of energy detection over Rayleigh fading channels can be given by, respectively [11]

    False alarm

    :denotes the average SNR at the cognitive radio

    Eγ[.]: the expectation over the random variable γ which is Rayleigh distributed.

    Γ: the gamma function

    Detection

    Missing Detection

    [11] A. Ghasemi and E. S. Sousa, “Collaborative spectrum sensing for opportunistic access in fading environments,” (DySPAN’05),


    Power control based on spectrum sensing side information cont d3

    Power Control Based on Spectrum Sensing Side Information (cont’d)

    1. This figure show that when the average SNR increases the probability of missing becomes smaller

    2. For a specified average SNR, a larger Pf will result in the decrease of Pm because of the decrease of the threshold used in energy detection


    Power control based on spectrum sensing side information cont d4

    Power Control Based on Spectrum Sensing Side Information (cont’d)

    • The path loss due to the distance d can be given by

    We can obtain a relationship between Pm and d (or η) for the given Qp/σ2 and α.

    It is obvious that the distance d (or η) can decided by Pm


    Power control based on spectrum sensing side information cont d5

    Power Control Based on Spectrum Sensing Side Information (cont’d)

    Numerical results demonstrate that when the cognitive radio is far from the primary transmitter, a high probability of missing is obtained.

    For a fixed distance d, A higher transmit SNR can get a better sensing performance, i.e. a lower Pm, because the received SNR is enhanced.


    Power control based on spectrum sensing side information cont d6

    Power Control Based on Spectrum Sensing Side Information (cont’d)

    • The probability of missing Pmcan be calculated as follows

    Let,

    Yi denotes the energy collected by the cognitive radio in the time slot i.

    Once Pm is determined, d (or η) can be obtained from the previous formula


    Power control based on spectrum sensing side information cont d7

    Power Control Based on Spectrum Sensing Side Information (cont’d)

    • Transmit Power Control for Cognitive Radio

    decodability SNR

    SINR

    where Qp‘ and Qc‘ denote the received signal power from the primary transmitter and the cognitive radio, respectively

    α and μ are constants

    It can be seen from the above formula, that the value of the allowable Qc depends on the SNR loss ψ


    Power control based on spectrum sensing side information cont d8

    Power Control Based on Spectrum Sensing Side Information (cont’d)

    • In this work, we consider the worst case that the primary receiver is located at the closet point to the cognitive radio. (fig 1.)

      • where Qcmax denote the maximum value of Qc in dB

      • d has been derived from the spectrum sensing side information previously


    Power control based on spectrum sensing side information cont d9

    Power Control Based on Spectrum Sensing Side Information (cont’d)

    • Proposed Power Control Algorithm:

      • Step1: Calculate the Pm (probability of missing)

      • Step2: Derive d or η

      • Step3: Calculate Qcmax


    Numerical results

    Numerical Results

    This shows the proportional relationship between Pm and the SNR loss due to the distance d.


    Numerical results cont d

    Numerical Results (cont’d)

    It demonstrates that the allowable transmit power of the cognitive radio can be increased when a heavy SNR loss occurs between the cognitive radio and the primary receiver


    Conclusion

    Conclusion

    • Develop a power control approach which intelligently adjusts the transmit power of the cognitive radio

      • while maintaining a QoS for the primary user

    • The transmit power is controlled by the spectrum sensing side information

      • the probability of missing which actually includes the implicit location information of the primary user.


    Comments

    Comments

    • Only use the sensing information to make the power control decision.

    • Evaluating the distance as an important parameter to make the decision

    • Consider the worst case, rather than find out a general solution.

      • Performance consideration


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