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Optimized Time Splitting to Maximize Rate in An Interference Alignment Based Network *

机译:优化的时间分割以最大化基于干扰对准的网络中的速率 *

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In this paper, considering an interference alignment (IA) based network, a time splitting scheme for transmitting training and data symbols is optimized. The time allocated to transmit training symbols will affect the precision of channel estimation (CE) and thus the achievable rate as well as the duration for data symbol transmission. With the least square (LS) CE algorithm, the lower bound of achievable rate is carefully derived. Then we formulate an optimization problem to maximize the lower bound of achievable rate by optimizing the time splitting factor (TSF) . The existence of optimum is first proven. Then, regarding the complexity of solution, Taylor expansion is adopted to find the approximated optimal TSF. Numerical results are presented to validate the correctness and efficiency of the proposed scheme.
机译:在本文中,考虑到基于干扰对准(IA)的网络,优化了用于传输训练和数据符号的时间分割方案。分配用于传输训练符号的时间将影响信道估计(CE)的精度,从而影响可达到的速率以及数据符号传输的持续时间。使用最小二乘(LS)CE算法,可以仔细得出可实现速率的下限。然后,我们提出了一个优化问题,通过优化时间分割因子(TSF)来最大化可实现速率的下限。最优的存在首先被证明。然后,关于解的复杂性,采用泰勒展开法来找到近似的最佳TSF。数值结果表明了所提方案的正确性和有效性。

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