LTE-Advanced网络的节能下行调度

H. Mahdavi-Doost, N. Prasad, S. Rangarajan
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引用次数: 10

摘要

LTE-Advanced (LTE-A)蜂窝网络的特点是使用基于OFDM的多址(OFDMA)和多天线(MIMO)技术。从Andrews-Zhang的开创性工作开始,已经提出了几种在此类网络上寻求利用多通道,多用户和空间多样性的子帧调度算法。工业界和学术界最近的兴趣是将能源效率纳入此类算法的设计中。在本文中,我们制定了一个单细胞下行链路调度问题,该问题利用了所有关键特征,并对传输参数的选择实施了所有主要强制约束。为了适应能源效率的考虑,还对通道集施加了线性成本约束。我们证明了所得到的问题等价于一个组合拍卖问题,具有分数次加性(但不一定是次模性)的估值和对被拍卖物品的线性约束。具有次模估值且没有任何附加约束的组合拍卖问题,可以用经典贪心算法近似求解。对于当前的问题,我们提出了一种基于确定性乘法更新的算法。后一种算法足够简单,可以在子帧调度的精细时间尺度(1ms)内实现。我们严格地建立了算法的近似保证,并通过仿真对其性能进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy efficient downlink scheduling in LTE-Advanced networks
LTE-Advanced (LTE-A) cellular networks are characterized by their use of OFDM based multiple access (OFDMA) and multi-antenna (MIMO) techniques. Starting from the seminal work of Andrews-Zhang, several algorithms for subframe scheduling over such networks, that seek to exploit multi-channel, multi-user and spatial diversity, have been proposed. Recent interest in both industry and academia is to incorporate energy efficiency in the design of such algorithms. In this paper, we formulate a single-cell downlink scheduling problem that exploits all key features and enforces all the main mandatory constraints on the choice of transmission parameters. Linear cost constraints on the set of channels are also imposed in order to accommodate energy efficiency considerations. We show that the resulting problem is equivalent to a combinatorial auction problem with fractionally sub-additive (but not necessarily submodular) valuations and linear constraints on the items being auctioned. The combinatorial auction problem with submodular valuations and without any additional constraints, can be approximately solved using the classical greedy algorithm. For the problem at hand, we instead propose a deterministic multiplicative updates based algorithm. The latter algorithm is simple enough to be implemented in the fine time-scale (1 ms) of subframe scheduling. We rigorously establish the approximation guarantee of our proposed algorithm and evaluate its performance via simulations.
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