Dynamic Carrier Allocation for Cognitive Radio Networks

Cognitive radios have been introduced as a dynamic way to share the frequency spectrum within wireless networks. After sensing its environment to discover the available frequency resources, a cognitive network allocates the locally available carriers among its nodes, under the constraint of negligible interference on licensed operators. The allocation, based on partial knowledge of the network parameters, must be optimized in order to provide maximum rates in the cognitive network. In addition, having a stable allocation reduces the control traffic inherent in dynamic networks. This paper presents a new and fast iterative way to allocate the available carriers, that reduces the control traffic and provides fairness at the same time. Using the properties of a proportionally fair objective function, we fasten the optimum search in the space of possible allocations, and reach that optimum with no approximation. Numerical results show that the proposed iterative algorithm is less complex than an analytical solution in usual dynamic carrier allocation scenarios.