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首页> 外文期刊>IEEE transactions on wireless communications >Analytical framework for multiuser uplink MIMO space-time scheduling design with convex utility functions
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Analytical framework for multiuser uplink MIMO space-time scheduling design with convex utility functions

机译：具有凸效用函数的多用户上行MIMO空时调度设计分析框架

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摘要

In this paper, we derive a novel analytical framework for designing optimal multiple-input multiple-output (MIMO) uplink space-time scheduling algorithms with respect to general convex utility functions. The novel approach we take is to discretize the search space and apply integer-programming techniques. We assume that mobile terminal has nT transmit antennas while the base station has nR receive antennas. With multiple antennas at the transmitter and the receiver, joint beam-forming has to be considered. In order that our proposed framework is practicable and can be implemented with a reasonable cost in a real environment, we impose a linear spatial processing constraint at the physical layer of the base station. We apply the framework to two commonly used system utility functions, namely, maximal throughput and proportional fair. We devise an optimal scheduling algorithm based on our framework as a performance reference and observe that transmit antennas and receive antennas have different roles in the system performance. On the other hand, we study how far we are from the optimal performance on a widely used heuristic called the greedy algorithm in 3G1x and Universal Mobile Terrestrial Service (UMTS) systems. We found that it is optimal when nR=1 but there is quite a large performance penalty when nR>1 compared with the optimal reference. We further propose another heuristic algorithm [called the genetic algorithm(GA)] and found that the GA is quite promising in terms of performance complexity tradeoff, especially for large K (number of mobile users), nT, and nR.
机译：在本文中，我们推导了一种新颖的分析框架，用于针对一般凸效用函数设计最佳多输入多输出（MIMO）上行链路时空调度算法。我们采用的新颖方法是离散化搜索空间并应用整数编程技术。我们假设移动终端具有nT个发射天线，而基站具有nR个接收天线。在发射机和接收机处有多个天线时，必须考虑联合波束成形。为了使我们提出的框架可行并且可以在实际环境中以合理的成本实施，我们在基站的物理层施加了线性空间处理约束。我们将该框架应用于两个常用的系统实用程序功能，即最大吞吐量和比例公平。我们设计了一个基于我们的框架作为性能参考的最佳调度算法，并观察到发射天线和接收天线在系统性能中具有不同的作用。另一方面，我们研究了在3G1x和通用移动地面服务（UMTS）系统中被广泛使用的名为贪婪算法的启发式算法与最佳性能的差距。我们发现，当nR = 1时是最佳选择，但与最佳参考值相比，当nR> 1时会有相当大的性能损失。我们进一步提出了另一种启发式算法[称为遗传算法（GA）]，发现GA在性能复杂度的权衡方面非常有前途，特别是对于大K（移动用户数量），nT和nR。

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