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Sum capacity maximization for MIMO-OFDMA based cognitive radio networks

机译:基于MIMO-OFDMA的认知无线电网络的总容量最大化

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摘要

In the opportunistic Cognitive Radio (CR) networks, the secondary users' (SU) capacity is limited due to the need to avoid the primary users' (PUs) bands. The combination of the Multiple-Input Multiple-Output (MIMO) structure with the orthogonal frequency division multiplexing (OFDM) structure is a very promising candidate which can compensate for such a shortage of capacity increasing the spectral efficiency. In this paper, a MIMO-OFDMA structure is proposed for the multiple access in multi-user CR networks. Furthermore, in order to achieve the maximum capacity in this structure, the resource allocation problem including proper allocation of sub-carriers to users and proper power allocation is investigated. To this aim, an efficient algorithm for the resource allocation is introduced. Furthermore, an alternative sub-optimal algorithm is obtained with lower complexity and very good performance. The performance of the suggested algorithms is investigated in a realistic scenario using LTE (Long Term Evolution) parameters with Spatial Channel Propagation Model (3GPP SCM). Simulation results verify the enhancement and efficiency of the proposed algorithms compared to the conventional ones applied in CR networks.
机译:在机会认知无线电(CR)网络中,由于需要避开主要用户(PU)频段,因此限制了次要用户(SU)的容量。多输入多输出(MIMO)结构与正交频分多路复用(OFDM)结构的组合是一个很有前途的候选方案,它可以弥补这种容量不足的问题,从而提高频谱效率。本文提出了一种MIMO-OFDMA结构,用于多用户CR网络中的多址接入。此外,为了在该结构中实现最大容量,研究了资源分配问题,包括向用户适当分配子载波以及适当地进行功率分配。为此,介绍了一种有效的资源分配算法。此外,以较低的复杂度和非常好的性能获得了替代的次优算法。在实际场景中,使用带有空间信道传播模型(3GPP SCM)的LTE(长期演进)参数来研究建议算法的性能。仿真结果验证了所提出算法与CR网络中常规算法相比的增强和效率。

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