• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.3
• /
• pp.1319-1335
• /
• 2017

This paper proposes an opportunistic reporting-based sensing-reporting-throughput optimization scheme that maximizes the spectral efficiency of secondary users (SUs) in cooperative cognitive radio networks with a soft combining rule. The performance of cooperative spectrum sensing depends on the sensing time, the reporting time of transmitting sensing results, and the fusion scheme. While longer sensing time and reporting time improve the sensing performance, this shortens the allowable data transmission time, which in turn degrades the spectral efficiency of SUs. The proposed scheme adopts an opportunistic reporting scheme to restrain the reporting overhead and it jointly controls the sensing-reporting overhead in order to increase the spectral efficiency of SUs. We show that there is a trade-off between the spectral efficiency of SUs and the overheads of cooperative spectrum sensing. The numerical results demonstrate that the proposed scheme significantly outperforms the conventional sensing-throughput optimization schemes when there are many SUs. Moreover, the numerical results show that the sensing-reporting time should be jointly optimized in order to maximize the spectral efficiency of SUs.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.4
• /
• pp.1208-1222
• /
• 2014

Due to the low utilization and scarcity of frequency spectrum in current spectrum allocation methodology, cognitive radio networks (CRNs) have been proposed as a promising method to solve the problem, of which spectrum sensing is an important technology to utilize the precious spectrum resources. In order to protect the primary user from being interfered, most of the related works focus only on the restriction of the missed detection probability, which may causes over-protection of the primary user. Thus the interference probability is defined and the interference-aware sensing model is introduced in this paper. The interference-aware sensing model takes the spatial conditions into consideration, and can further improve the network performance with good spectrum reuse opportunity. Meanwhile, as so many fading factors affect the spectrum channel, errors are inevitably exist in the reporting channel in cooperative sensing, which is improper to be ignored. Motivated by the above, in this paper, we study the throughput tradeoff for interference-aware cognitive radio networks over imperfect reporting channel. For the cooperative spectrum sensing, the K-out-of-N fusion rule is used. By jointly optimizing the sensing time and the parameter K value, the maximum throughput can be achieved. Theoretical analysis is given to prove the feasibility of the optimization and computer simulations also shows that the maximum throughput can be achieved when the sensing time and the parameter of K value are both optimized.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.1
• /
• pp.58-73
• /
• 2014

As is well known, cooperative sensing can significantly improve the sensing accuracy as compared to local sensing in cognitive radio networks (CRNs). However, a large number of cooperative secondary users (SUs) reporting their local detection results to the fusion center (FC) would cause much overhead, such as sensing delay and energy consumption. In this paper, we propose a fast cooperative sensing scheme, called double threshold fusion (DTF), to reduce the sensing overhead while satisfying a given sensing accuracy requirement. In DTF, FC respectively compares the number of successfully received local decisions and that of failed receptions with two different thresholds to make a final decision in each reporting sub-slot during a sensing process, where cooperative SUs sequentially report their local decisions in a selective fashion to reduce the reporting overhead. By jointly considering sequential detection and selective reporting techniques in DTF, the overhead of cooperative sensing can be significantly reduced. Besides, we study the performance optimization problems with different objectives for DTF and develop three optimum fusion rules accordingly. Simulation results reveal that DTF shows evident performance gains over an existing scheme.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.2
• /
• pp.253-263
• /
• 2015

Lately, spectrum sensing performance has been improved by using cooperate spectrum sensing which each results of sensing of several secondary users are reported to the fusion center. Using Cognitive Radio, secondary user is able to share a bandwidth allocated to primary user. In this paper, we propose a new decentralized cooperative spectrum sensing scheme which compensates the performance degradation of existing decentralized cooperative spectrum sensing considering the error probability of the channel which sensed result of the secondary user is delivered to the fusion center in decentralized cooperative spectrum sensing. In addition, a sensing threshold optimization of minimizing the error probability of decentralized cooperative spectrum sensing is introduced by deriving the equation and the optimal sensing threshold has been confirmed to maximize the decentralized cooperative spectrum sensing performance.