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Cooperative resource allocation in OFDM-based multicell cognitive radio systems

机译:基于OFDM的多小区认知无线电系统中的协作资源分配

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In this paper, we investigate the resource allocation problem for an orthogonal frequency division multiplexing (OFDM) based multicell cognitive radio (CR) system. Secondary users (SUs) served by the CR system distribute randomly in multiple cells and share radio spectrum with primary users (PUs) in a licensed system, where the interference introduced to the PUs must be kept below their tolerable thresholds. In our system model, SUs in different CR cells can transmit signals with the same OFDM subchannel, so cochannel interference among the SUs should also be considered. We propose an efficient algorithm, named as multi-level waterfilling (MLWF), to allocate power among OFDM subchannels for all CR cells by jointly considering transmission power and interference constraints. The MLWF always allocates much power to a subchannel which generates less interference to the PUs. Simulation results show that our proposed algorithm provides better performance than other existing ones. Moreover, the complexity of the MLWF is much lower than other representative algorithms.
机译:在本文中,我们研究了基于正交频分复用(OFDM)的多小区认知无线电(CR)系统的资源分配问题。由CR系统服务的辅助用户(SU)随机分布在多个小区中,并与许可系统中的主要用户(PU)共享无线电频谱,其中引入PU的干扰必须保持在其容许阈值以下。在我们的系统模型中,不同CR单元中的SU可以使用相同的OFDM子信道传输信号,因此SU之间也应考虑同信道干扰。我们提出一种有效的算法,称为多级注水(MLWF),通过共同考虑传输功率和干扰约束,为所有CR小区在OFDM子信道之间分配功率。 MLWF总是将大量功率分配给子信道,从而对PU产生更少的干扰。仿真结果表明,本文提出的算法具有比现有算法更好的性能。此外,MLWF的复杂度远低于其他代表性算法。

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