Interference alignment with frequency-clustering for efficient resource allocation in cognitive radio networks

Abstract

In this paper, the problem of resource allocation in overloaded orthogonal frequency division multiplexing (OFDM) based multiple-input multiple-output (MIMO) cognitive radio (CR) system is considered. The objective is to allocate the different subcarrier and distribute the available user power in order to maximize the CR system throughput. The interference induced to the primary system should not be harmful and hence, should not exceed the prescribed limit. Interference alignment (IA) technique is employed in order to achieve an efficient use of the available radio resources. Without affecting the quality of service of the primary system, IA enables the secondary users to share the available spectrum which increases the CR system degrees-of-freedom. Due to IA feasibility condition, the spectrum sharing with perfect IA is restricted to a certain number of user per subcarrier. Accordingly, the resource management problem is formulated as a mixed-integer optimization problem which is considered as an NP-hard problem. To reduce the computational complexity of the problem, a two-phase efficient sub-optimal algorithm is proposed. Frequency-clustering is performed in the first phase to the overcome IA feasibility conditions while the power is distributed among subcarriers in the second phase. Simulations show that IA technique achieves a significant sum-rate increase of CR systems compared with the traditional CR systems that use orthogonal multiple access transmission techniques.