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Energy and Spectrum Efficient Transmission Techniques Under QoS Constraints Toward Green Heterogeneous Networks

机译:QoS约束下面向绿色异构网络的能量和频谱高效传输技术

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© 2015 IEEE. This paper proposes a joint energy efficiency (EE) and spectrum efficiency (SE) tradeoff analysis as a multi-objective optimization problem (MOP) in the uplink of multi-user multi-carrier two-tier orthogonal frequency division multiplexing access heterogeneous networks subject to users' maximum transmission power and minimum rate constraints. The proposed MOP is modeled such that the network providers can dynamically tune the tradeoff parameters to switch between different communication scenarios with diverse design requirements. In order to find its Pareto optimal solution, the MOP is transformed, using a weighted sum method, into a single-objective optimization problem (SOP), which itself can further be transformed from a fractional form, by exploiting fractional programming, into a subtractive form. Since the formulated SOP is hard to solve due to the combinatorial channel allocation indicators, we reformulate the SOP into a better tractable problem by relaxing the combinatorial indicators using the idea of time-sharing. We then prove that this reformulated SOP is strictly quasi-concave with respect to the transmission power and the subcarrier allocation indicator. We then propose an iterative two-layer distributed framework to achieve an upper bound Pareto optimal solution of the original proposed MOP. The numerical simulations demonstrate the effectiveness of our proposed two-layer framework achieving an upper bound Pareto optimal solution, which is very close to an optimal solution, with fast convergence, lower and acceptable polynomial complexity, and balanced EE-SE tradeoff.
机译:©2015 IEEE。本文提出了一种联合能量效率(EE)和频谱效率(SE)的权衡分析方法,作为多目标多载波两层正交频分复用接入异构网络在上行链路下的多目标优化问题(MOP)。用户的最大传输功率和最小速率限制。对提出的MOP进行建模,以便网络提供商可以动态调整权衡参数,以在具有不同设计要求的不同通信场景之间切换。为了找到其Pareto最优解,使用加权和方法将MOP转换为单目标优化问题(SOP),可以通过分数编程将其本身从分数形式进一步转换为减法形式。形成。由于组合渠道分配指标导致制定的SOP难以解决,因此我们通过使用分时的想法来放松组合指标,从而将SOP重新制定为更好解决的问题。然后,我们证明,就传输功率和子载波分配指标而言,重新制定的SOP严格是准凹的。然后,我们提出了一个迭代的两层分布式框架,以实现原始提出的MOP的上限Pareto最优解。数值模拟表明,我们提出的两层框架可实现帕累托最优解的上限,该解非常接近于最优解,具有快速收敛,较低且可接受的多项式复杂度以及平衡的EE-SE权衡的优点。

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