Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Efficient and reliable por allocation algorithm in cognitive radio (CR) networks is a challenging problem. Traditional water-filling algorithm is inefficient for CR networks due to the interaction with primary users. ,  consider reliability/availability of subcarriers or primary user activity for por allocation.  model this aspect mathematically with a risk-return model by defining a general rate loss function.  then propose optimal and suboptimal algorithms to allocate por under a fixed por budget for such a system with linear rate loss. These algorithms as  will see allocate more por to more reliable subcarriers in a water-filling fashion with different water levels.  compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. Finally,  discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them.
['Ziaul Hasan', 'Ekram Hossain', 'Charles L. Despins', 'Vijay K. Bhargava']
I am writing a research paper on a idea Power Allocation for Cognitive Radios Based on Primary User Activity in an OFDM System
[{"from": "human", "value": "I am writing a research paper on a idea Power Allocation for Cognitive Radios Based on Primary User Activity in an OFDM System"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Efficient and reliable por allocation algorithm in cognitive radio (CR) networks is a challenging problem. Traditional water-filling algorithm is inefficient for CR networks due to the interaction with primary users. ,  consider reliability/availability of subcarriers or primary user activity for por allocation.  model this aspect mathematically with a risk-return model by defining a general rate loss function.  then propose optimal and suboptimal algorithms to allocate por under a fixed por budget for such a system with linear rate loss. These algorithms as  will see allocate more por to more reliable subcarriers in a water-filling fashion with different water levels.  compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. Finally,  discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them."}]