We consider the downlink of a cooperative cellular communications system, where several base-stations around each mobile cooperate and perform zero-forcing to reduce the received interference at the mobile. We derive closed-form expressions for the asymptotic performance of the network as the number of antennas per base station grows large. These expressions capture the trade off between various system parameters, and characterize the joint effect of noise and interference (where either noise or interference is asymptotically dominant and where both are asymptotically relevant). The asymptotic results are verified using Monte Carlo simulations, which indicate that they are useful even when the number of antennas per base station is only moderately large. Additionally, we show that when the number of antennas per base station grows large, power allocation can be optimized locally at each base station. We hence present a power allocation algorithm that achieves near optimal performance while significantly reducing the coordination overhead between base stations. The presented analysis is significantly more challenging than the uplink analysis, due to the dependence between beamforming vectors of nearby base stations. This statistical dependence is handled by introducing novel bounds on marked shot-noise point processes with dependent marks, which are also useful in other contexts.

翻译：我们考虑一个合作式蜂窝通信系统的下行链路，其中每个移动台周围的多个基站相互协作，并采用迫零（zero-forcing）方法以减少移动台端接收到的干扰。我们推导出当每基站天线数趋于无穷大时网络渐近性能的闭式表达式。这些表达式刻画了各系统参数之间的权衡关系，并描述了噪声与干扰的联合效应（包括噪声或干扰分别渐近占优的情形以及两者均渐近相关的情形）。通过蒙特卡洛仿真验证了渐近结果的准确性，表明即使每基站天线数仅为中等规模时，该结果仍具有实用价值。此外，我们证明当每基站天线数足够大时，功率分配可在各基站本地优化。据此提出一种功率分配算法，在显著降低基站间协调开销的同时实现接近最优的性能。由于相邻基站的波束赋形向量存在依赖性，本文的分析远比上行链路分析更具挑战性。这种统计依赖性通过引入标记相关雪噪点过程的新型界值来处理，该界值在其他场景中同样具有应用价值。