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Polarization-based Cross-tier Interference Alignment in Cognitive Heterogeneous Cellular Network

机译:认知异构蜂窝网络中基于极化的跨层干扰对准

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To eliminate the cross-tier interference and optimize the bit-error-rate performance of small cell for downlink underlay cognitive heterogeneous cellular network, a novel polarization-based cross-tier interference alignment scheme is proposed in this paper by exploiting the polarization resource of two-tier network. The transmitting and receiving polarization states of small cell are designed by interference alignment-like behaviors of the minimum total mean squared error optimization model under interference power constraint. An analytical and noncooperative closed form solution is provided for the model. Simulation results show the proposed scheme outperforms the existing schemes in bit-error-rate performance of small cell while keeping the maximum sum rate of overall system. And the tradeoff between bit-error-rate performances of macro cell and small cell is also evaluated.
机译:为了消除下行干扰的认知异质蜂窝网络的跨层干扰并优化小小区的误码率性能,本文提出了一种基于极化的跨层干扰对齐方案,该方法利用了两种极化资源。层网络。通过在干扰功率约束下最小总均方误差优化模型的类似干扰对准行为来设计小小区的发射和接收极化状态。为该模型提供了一种分析性和非合作性的封闭式解决方案。仿真结果表明,该方案在保持整个系统最大和速率的同时,在小小区误码率性能方面优于现有方案。并且还评估了宏小区和小型小区的误码率性能之间的折衷。

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