Abstract
In this paper, we propose an energy-efficient interference alignment (IA) based resource management algorithm for multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) cognitive radio (CR) systems. The proposed algorithm provides the secondary users (SUs) with the opportunity for underlay sharing of the primary system spectrum. The proposed algorithm ensures the quality-of-service (QoS) of the primary system by guaranteeing the minimum transmission rate. The problem is formulated as a mixed-integer non-convex optimization problem, in which the objective is to maximize the energy efficiency, and the constraints are the per-user power budget and QoS demand of the primary system. To tackle mixed-integer and non-convexity nature of the problem, we propose a sub-optimal energy-efficient algorithm through two successive steps. The first step schedules the subcarriers among the SUs based on IA while the second step iteratively allocates the power based on Dinkelbach’s scheme. Simulations reveal that the proposed algorithm achieves significant improvement in the energy efficiency compared to the traditional spectrum-efficient algorithm.
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© 2015 Institute for Computer Science, Social Informatics and Telecommunications Engineering
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El-Absi, M., Ali, A., El-Hadidy, M., Kaiser, T. (2015). Energy-Efficient Resource Allocation Based on Interference Alignment in MIMO-OFDM Cognitive Radio Networks. In: Weichold, M., Hamdi, M., Shakir, M., Abdallah, M., Karagiannidis, G., Ismail, M. (eds) Cognitive Radio Oriented Wireless Networks. CrownCom 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 156. Springer, Cham. https://doi.org/10.1007/978-3-319-24540-9_44
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DOI: https://doi.org/10.1007/978-3-319-24540-9_44
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