WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Conference Object Citation - WoS: 3Citation - Scopus: 3Adaptive Resource Allocation for Sdma-Ofdma Systems With Genetic Algorithm(Institute of Electrical and Electronics Engineers Inc., 2009) Özbek, Berna; Özbek, Berna; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyIn this paper, we propose an adaptive resource allocation algorithm to maximize the sum data rate for spatial division multiplexing access (SDMA) orthogonal division multiple access (OFDMA) systems using genetic algorithm. We perform Zero forcing (ZF) beamforming at the transmitter constructing single and multiple beams for OFDMA systems with multiple transmit antennas. In order to reduce the complexity and convergence time of genetic algorithm (GA), we present an initial condition obtained by allocating the user to the subcarrier with maximum precoding gain. The proposed algorithm reduces the complexity without sacrificing the performance. We obtain the simulation results and compare them with the classical static and adaptive allocation methods. We show that the GA with the proposed initial condition increases the sum data rate compared to classical GA and reduces the convergence time significantly for SDMA-OFDMA systems.Conference Object Semi-Orthogonal User Selection for Miso Systems With Quantized Feedback(Institute of Electrical and Electronics Engineers Inc., 2008) Khanfir, Hajer; Özbek, Berna; Khanfir, Hajer; 03.05. Department of Electrical and Electronics Engineering; 01. Izmir Institute of Technology; 03. Faculty of EngineeringFor MISO multi-user downlink wireless communication system with precoding at the transmission, the channel state information at the transmitter can provide tremendous capacity gains. However, the amount of feedback data increases with the number of users in the cell and the number of transmit antennas. In this paper, we study on different algorithms and criteria in order to significantly reduce the amount of feedback data. We associate the classical norm criterion with a criterion based on the orthogonality between the user channels. Without cooperation between the users, we only allow users that are semi-orthogonal to feedback their channel information (CQI and CDI) to the base station. The feedback CDI is quantized using a local grassmanian packing. We show that the proposed combined criterion with a finite feedback rate gives better performance compared to the norm criterion. Furthermore we show that the performance is not affected by CQI quantization.