Research Article
Energy-Efficient Resource Allocation Based on Interference Alignment in MIMO-OFDM Cognitive Radio Networks
@INPROCEEDINGS{10.1007/978-3-319-24540-9_44, author={Mohammed El-Absi and Ali Ali and Mohamed El-Hadidy and Thomas Kaiser}, title={Energy-Efficient Resource Allocation Based on Interference Alignment in MIMO-OFDM Cognitive Radio Networks}, proceedings={Cognitive Radio Oriented Wireless Networks. 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21--23, 2015, Revised Selected Papers}, proceedings_a={CROWNCOM}, year={2015}, month={10}, keywords={Cognitive radio Interference alignment Resource allocation Energy efficiency MIMO OFDM}, doi={10.1007/978-3-319-24540-9_44} }- Mohammed El-Absi
Ali Ali
Mohamed El-Hadidy
Thomas Kaiser
Year: 2015
Energy-Efficient Resource Allocation Based on Interference Alignment in MIMO-OFDM Cognitive Radio Networks
CROWNCOM
Springer
DOI: 10.1007/978-3-319-24540-9_44
Abstract
In this paper,we propose an energy-efficient interference alignment (IA) based resource management algorithm for multi-input multioutput (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-ofservice (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 tomaximize the energy efficiency, and the constraints are the per-user power budget andQoS 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.
