A Joint Sensing-Time Adaption and Data Transmission Scheme in Cognitive Radio Networks

2011 ◽  
Author(s):  
Wenshan Yin ◽  
Pinyi Ren ◽  
Chao Zhang
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Data Transmission ◽  
Radio Networks ◽  
Transmission Scheme ◽  
Sensing Time

scholarly journals Efficient Approximations for Optimization of N-Out-of-K Rule for Heterogeneous Cognitive Radio Networks

2021 ◽  
Vol 11 (7) ◽  
pp. 3083
Author(s):  
Youheng Tan ◽  
Xiaojun Jing
Keyword(s):  
Cognitive Radio ◽  
Computational Complexity ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Closed Form Expression ◽  
Sampling Point ◽  
Mutual Cooperation ◽  
Communication Time ◽  
Sensing Time

Spectrum sensing (SS) has attracted much attention due to its important role in the improvement of spectrum efficiency. However, the limited sensing time leads to an insufficient sampling point due to the tradeoff between sensing time and communication time. Although the sensing performance of cooperative spectrum sensing (CSS) is greatly improved by mutual cooperation between cognitive nodes, it is at the expense of computational complexity. In this paper, efficient approximations of the N-out-of-K rule-based CSS scheme under heterogeneous cognitive radio networks are provided to obtain the closed-form expression of the sensing threshold at the fusion center (FC), where the false alarm probability and its corresponding detection probability are approximated by the Poisson distribution. The computational complexity required to obtain the optimal sensing threshold at the FC has greatly decreased and theoretical derivations state that the approximation error is negligible. The simulations validate the effectiveness of the proposed scheme.

scholarly journals Traffic Based Optimization of Spectrum Sensing in Cognitive Radio Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Changhua Yao ◽  
Qihui Wu ◽  
Linfang Zhou
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Concave Function ◽  
Radio Networks ◽  
Data Traffic ◽  
Time Value ◽  
Achievable Throughput ◽  
Special Case ◽  
Sensing Time

We propose a more practical spectrum sensing optimization problem in cognitive radio networks (CRN), by considering the data traffic of second user (SU). Compared with most existing work, we do not assume that SU always has packets to transmit; instead, we use the actual data transmitted per second rather than the channel capacity as the achievable throughput, to reformulate the Sensing-Throughput Tradeoff problem. We mathematically analyze the problem of optimal sensing time to maximize the achievable throughput, based on the data traffic of SU. Our model is more general because the traditional Sensing-Throughput Tradeoff model can be seen as a special case of our model. We also prove that the throughput is a concave function of sensing time and there is only one optimal sensing time value which is determined by the data traffic. Simulation results show that the proposed approach outperforms existing methods.

Sign in / Sign up

Export Citation Format

Share Document