Resource Allocation in OFDM-Based Cooperative Cognitive Radio Networks with Two-Way Amplify-and-Forward Relay

2015 ◽  
Author(s):  
Lijie Wang ◽  
Yi Tang ◽  
Wenfeng Luo ◽  
Weitao Sun
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Amplify And Forward ◽  
Cooperative Cognitive Radio Networks

scholarly journals Full-Duplex Amplify-and-Forward Relay Selection in Cooperative Cognitive Radio Networks

2019 ◽  
Vol 68 (6) ◽  
pp. 6142-6146 ◽  
Author(s):  
Bakhtiar Ali ◽  
Jawad Mirza ◽  
Juping Zhang ◽  
Gan Zheng ◽  
Saqib Saleem ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Relay Selection ◽  
Radio Networks ◽  
Full Duplex ◽  
Amplify And Forward ◽  
Cooperative Cognitive Radio Networks

scholarly journals Optimizing Cooperative Cognitive Radio Networks with Opportunistic Access

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Ammar Zafar ◽  
Mohamed-Slim Alouini ◽  
Yunfei Chen ◽  
Redha M. Radaydeh
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Symbol Error Rate ◽  
Radio Networks ◽  
Optimal Resource Allocation ◽  
Cooperative Cognitive Radio Networks ◽  
Nonconvex Functions ◽  
Opportunistic Access ◽  
Optimal Resource

Optimal resource allocation for cooperative cognitive radio networks with opportunistic access to the licensed spectrum is studied. Resource allocation is based on minimizing the symbol error rate at the receiver. Both the cases of all-participate relaying and selective relaying are considered. The objective function is derived and the constraints are detailed for both scenarios. It is then shown that the objective functions and the constraints are nonlinear and nonconvex functions of the parameters of interest, that is, source and relay powers, symbol time, and sensing time. Therefore, it is difficult to obtain closed-form solutions for the optimal resource allocation. The optimization problem is then solved using numerical techniques. Numerical results show that the all-participate system provides better performance than its selection counterpart, at the cost of greater resources.

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