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arXiv 1604.01469cs.ITmath.IT
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网络MIMO系统的随机分析

A Stochastic Analysis of Network MIMO Systems

Kianoush Hosseini, Wei Yu, Raviraj S. Adve

摘要:

本文通过对网络多输入多输出(MIMO)系统下行链路的统计分析,量化了协作通信的优点和局限性。我们考虑一个理想化的模型,其中多天线基站(BS)分布根据一个齐次泊松点过程和合作,形成不相交的集群。我们假设,完美的信道状态信息(CSI)是在合作BS没有任何开销。多个单天线用户使用迫零波束成形服务,在波束之间具有相等的功率分配。对于这样一个系统,我们得到易于处理的,但准确的,近似的信号功率和集群间干扰功率分布,并推导出一个计算效率高的表达可实现的每BS遍历和速率使用工具从随机几何。该表达式允许我们获得最佳加载因子,即,调度用户的数量和BS天线的数量之间的比率,其最大化每BS遍历和速率。此外,它使我们能够量化的网络MIMO系统的性能改善的合作集群大小的函数。我们表明,在集群内的BS的分布式集执行迫零,网络MIMO系统引入了惩罚接收信号功率。随着不可避免的集群外干扰,我们表明,每BS遍历和速率的网络MIMO系统不接近一个孤立的小区,即使在不切实际的大集群大小。然而,与不协调的单小区处理相比,网络MIMO即使在相对适度的簇大小下也确实提供了显著的速率改进。

英文摘要:

This paper quantifies the benefits and limitations of cooperative communications by providing a statistical analysis of the downlink in network multiple-input multiple-output (MIMO) systems. We consider an idealized model where the multiple-antenna base-stations (BSs) are distributed according to a homogeneous Poisson point process and cooperate by forming disjoint clusters. We assume that perfect channel state information (CSI) is available at the cooperating BSs without any overhead. Multiple single-antenna users are served using zero-forcing beamforming with equal power allocation across the beams. For such a system, we obtain tractable, but accurate, approximations of the signal power and inter-cluster interference power distributions and derive a computationally efficient expression for the achievable per-BS ergodic sum rate using tools from stochastic geometry. This expression allows us to obtain the optimal loading factor, i.e., the ratio between the number of scheduled users and the number of BS antennas, that maximizes the per-BS ergodic sum rate. Further, it allows us to quantify the performance improvement of network MIMO systems as a function of the cooperating cluster size. We show that to perform zero-forcing across the distributed set of BSs within the cluster, the network MIMO system introduces a penalty in received signal power. Along with the inevitable out-of-cluster interference, we show that the per-BS ergodic sum rate of a network MIMO system does not approach that of an isolated cell even at unrealistically large cluster sizes. Nevertheless, network MIMO does provide significant rate improvement as compared to uncoordinated single-cell processing even at relatively modest cluster sizes.

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