Location Assisted Subcarrier and Power Allocation in Underlay Mobile Cognitive Radio Networks

In this paper we perform subcarrier and power allocation for the downlink transmission in a cognitive radio network by exploiting the location information of mobile secondary users. A mixed integer nonlinear problem is formulated which maximizes the aggregate capacity of the secondary network, subject to the constrained interference at the primary user and the maximum transmit power limit of the secondary base station. To solve the formulated problem, an optimal subcarrier allocation is first obtained based on a practical assumption, followed by an optimal power allocation achieved using standard optimization methods. The proposed solution can facilitate to reduce latency and provide high speed communication of big data for mobile secondary users since speed, direction and location are all taken into account for effective allocation of resources. Simulation results verify our design intentions and confirm the efficiency of the proposed resource allocation strategy. © 2018 IEEE

Location assisted subcarrier and power allocation in underlay mobile cognitive radio networks

In this paper we perform subcarrier and power allocation for the downlink transmission in a cognitive radio network by exploiting the location information of mobile secondary users. A mixed integer nonlinear problem is formulated which maximizes the aggregate capacity of the secondary network, subject to the constrained interference at the primary user and the maximum transmit power limit of the secondary base station. To solve the formulated problem, an optimal subcarrier allocation is first obtained based on a practical assumption, followed by an optimal power allocation achieved using standard optimization methods. The proposed solution can facilitate to reduce latency and provide high speed communication of big data for mobile secondary users since speed, direction and location are all taken into account for effective allocation of resources. Simulation results verify our design intentions and confirm the efficiency of the proposed resource allocation strategy