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Neural embedded smart link generation scheme for heterogeneous network

机译:异构网络的神经嵌入式智能链路生成方案

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摘要

The Long Term Evolution (LTE) network is a very much popular network in heterogeneous network. Heterogeneous networks provide maximum data rate by integrating various technologies and channels, based on appropriate network selection. For the sensible data transmission in the LTE network, noise plays an vital role as channel is a free space. The minimum noise channel selection is a decision of present and previous status of network channel. Proposed scheme develop neural network model, which will act as a smart link generation scheme for computing minimum noise channel path for sensible data transmission. Hence, proposed scheme will improve performance of the network. Result indicates that, proposed scheme improves throughput and system reliability. Proposed scheme is also reduces packet loss rate and energy consumption in contrast with conventional techniques.
机译:长期演进(LTE)网络是异构网络中非常流行的网络。异构网络根据适当的网络选择,通过集成各种技术和渠道来提供最大的数据速率。对于LTE网络中的合理数据传输,由于信道是自由空间,因此噪声起着至关重要的作用。最小噪声通道选择是网络通道当前和先前状态的决定。提出的方案开发了神经网络模型,它将作为一种智能链路生成方案,用于计算最小噪声通道路径以进行合理的数据传输。因此,提出的方案将改善网络的性能。结果表明,该方案提高了吞吐量和系统可靠性。与常规技术相比,提出的方案还降低了分组丢失率和能量消耗。

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