Performance Analysis of Spectrum Sensing with Multiple Status Changes in Primary User Traffic

  title={Performance Analysis of Spectrum Sensing with Multiple Status Changes in Primary User Traffic},
  author={Liang Tang and Yunfei Chen and Evor L. Hines and Mohamed-Slim Alouini},
  journal={IEEE Communications Letters},
In this letter, the impact of primary user traffic with multiple status changes on the spectrum sensing performance is analyzed. Closed-form expressions for the probabilities of false alarm and detection are derived. Numerical results show that the multiple status changes of the primary user cause considerable degradation in the sensing performance. This degradation depends on the number of changes, the primary user traffic model, the primary user traffic intensity and the signal-to-noise ratio… 

Figures from this paper

Periodic Spectrum Sensing With Non-Continuous Primary User Transmissions

A thorough study of spectrum sensing performance in cognitive radio (CR) scenarios where the primary user (PU) transmission is not continuous is presented and a comprehensive analytical framework is derived which accounts for detector performance, presence of noise and fading, PU temporal statistics, and periodic sensing.

Analyzing the Performance of Spectrum Sensing in Cognitive Radio Systems With Dynamic PU Activity

This letter model the PU activity using a two-state Markov chain and derive analytical expressions for the probabilities of detection and false alarm that explicitly consider the changes in the PU signal that may occur during the sensing interval by the SU.

Energy detection of random arrival and departure of primary user signals in Cognitive Radio systems

An analytical forms are derived for both the detection and false alarm probabilities, using the Bayesian-based ED scheme, assuming random arrival and departure of the primary user signal during the secondary user's sensing period.

Energy detection based spectrum sensing with random arrival and departure of primary user's signal

To improve the robustness of the detection performance against random signal arrival and departure, a Bayesian-based ED scheme is proposed, and simulation results are presented to validate the analytic study, and show the performance gain of the proposed Bayesian approach.

Sensing-Throughput Tradeoff in Cognitive Radio With Random Arrivals and Departures of Multiple Primary Users

Results show that, though the increase in the number of PUs reduces the optimal sensing time for SU, the opportunity to find a vacant PU channel reduces simultaneously, in turn, reducing SU throughput.

Spectrum Sensing Techniques Based on Last Status Change Point Estimation for Dynamic Primary User in Additive Laplacian Noise

A real time scenario of dynamic primary user (PU) is considered in additive Laplacian noise and it is found that the considered system outperforms the conventional schemes.

A New Spectrum Sensing Strategy for Dynamic Primary Users in Cognitive Radio

Simulations indicate that the proposed sensing strategy provides an improvement in terms of probability of detection for all the considered spectrum sensing methods.

A New Adaptive Sensing Scheme for Low SNR and Random Arrival of PU Environment

Numerical results show that the optimal scheme significantly increases SU utility while avoiding interference to PU in the adverse environment, and it reduces detection difficulty and computational complexity.

The impacts of user dynamics on energy-based opportunistic cooperative spectrum sensing in Cognitive Radio Networks over log-normal shadowed Rayleigh fading channels

  • Chihkai ChenK. Yao
  • Computer Science
    2013 International Conference on Computing, Networking and Communications (ICNC)
  • 2013
Close form expressions for the dynamic performance of distributed energy-based cooperative spectrum sensing are derived and provide a feasible framework to apply optimization techniques for system design parameters to efficiently guarantee the global optimality without computationally costly exhaustive search.

A New Method of Spectrum Sensing in Cognitive Radio for Dynamic and Randomly Modelled Primary Users

In this study, a new spectrum sensing method for cognitive radio (CR) is proposed for primary user (PU) signals which are modelled as random with unknown power. It is also assumed that, being



Analysis of effect of primary user traffic on spectrum sensing performance

Numerical results show that the performance of spectrum sensing can be significantly degraded if the primary user channel state changes frequently, and that collaborative spectrum sensing is effective in alleviating the deleterious effect caused by thePrimary user traffic.

Probability-based periodic spectrum sensing during secondary communication

A probability model regarding the appearance of the primary user at any sample of a CR user frame is established by utilizing the statistical characteristics of the licensed channel occupancy and it is shown that such a probability-based spectrum sensing scheme has nearly optimal performance.

Sensing-throughput tradeoff for cognitive radio networks: A multiple-channel scenario

This paper investigates the design of the optimal spectrum sensing time and power allocation schemes so as to maximize the aggregate ergodic throughput of the cognitive radio network to guarantee the quality of service (QoS) of the primary users (PUs) without exceeding the power limit of the secondary transmitter.

Traffic Pattern Prediction and Performance Investigation for Cognitive Radio Systems

  • Xiukui LiS. Zekavat
  • Computer Science, Business
    2008 IEEE Wireless Communications and Networking Conference
  • 2008
An algorithm for the prediction of call arrival rate is proposed which exploits the periodicity of the traffic process and an approach for call holding time estimation is presented.

An adaptive sensing period algorithm in cognitive radio networks

  • Hongyan LiHongliang Fu
  • Computer Science, Business
    2009 IEEE International Conference on Communications Technology and Applications
  • 2009
An adaptive sensing period algorithm is proposed to realize the automatic adjusting of sensing periods based on the channel-usage model of licensed users and it is demonstrated that the proposed algorithm always has steady performance, regardless of the number of channels sensed.

Performance of collaborative spectrum sensing for cognitive radio in the presence of gaussian channel estimation errors

Numerical results show that the probability of missed opportunity decreases as the estimation error decreases, and also show that in the presence of noise, there exists a threshold phenomenon for the noise level.

Optimization of Spectrum Sensing for Opportunistic Spectrum Access in Cognitive Radio Networks

  • A. GhasemiE. Sousa
  • Business
    2007 4th IEEE Consumer Communications and Networking Conference
  • 2007
In the context of spectrum sensing, sensing time may be fine- tuned to enhance the secondary users' perceived quality-of- service (QoS) as long as the regulatory constraint for the protection of the primary users against harmful interference is satisfied.

Improved Energy Detectors for Cognitive Radios With Randomly Arriving or Departing Primary Users

New and improved energy detectors for cognitive radios are derived by considering the effect of the primary user traffic on spectrum sensing, which shows that the new energy detector outperforms the conventional energy detector in all the cases examined.

How Often and How Long Should a Cognitive Radio Sense the Spectrum?

  • N. MoayeriHui Guo
  • Computer Science
    2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN)
  • 2010
Numerical results are presented that show the behavior of the maximum profit of the secondary user, its throughput, and the resulting level of interference to the primary users as functions of various network parameters.

Deriving Call Holding Time Distribution in Cellular Network from Empirical Data

Summary The call holding time distribution in cellular systems is one of the main parameters that are used to study and analyze several system performance measures. Several statistical distributions