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Exploring frequency diversity with interference alignment in cognitive radio networks

机译:用认知无线电网络中的干扰对齐探索频率分集

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摘要

The available spectrum in cognitive radio networks is usually discontinuous but wide, which provides abundant frequency domain diversity. In this paper, we identify the opportunity of leveraging the newly-emerged technique interference alignment to exploit such diversity to support concurrent transmission and improve the network throughput in secondary networks. To enable interference alignment, independent-fading subcarriers should be grouped together to provide sufficient dimensions for intended signals and non-intended interferences at the receiver side. We formulate the subcarrier grouping problem for interference alignment to maximize the number of concurrent transmissions, and propose a greedy-based algorithm to solve it, which is proved to be optimal. Simulation results show that using the proposed scheme, the total throughput in cognitive radio networks can be greatly improved.
机译:认知无线电网络中的可用频谱通常是不连续但宽的,提供丰富的频域分集。 在本文中,我们确定了利用新出现的技术干扰对齐的机会,以利用这种多样性来支持并发传输,并提高二级网络中的网络吞吐量。 为了使干扰对准,应将独立的衰落子载波组合在一起,以提供用于预期信号的足够尺寸和接收器侧的非预期干扰。 我们制定用于干扰对齐的子载波分组问题,以最大化并发传输的数量,并提出基于贪婪的算法来解决,这被证明是最佳的。 仿真结果表明,使用所提出的方案,可以大大提高认知无线电网络中的总吞吐量。

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