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：本文考虑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协同工作并执行迫零处理，以减少移动台处接收到的干扰。我们推导了当每个基站的天线数量趋于无穷时网络渐近性能的闭式表达式。这些表达式刻画了各种系统参数之间的权衡，并表征了噪声与干扰的联合效应（其中噪声或干扰分别渐近主导，以及两者均渐近相关）。通过蒙特卡洛仿真验证了渐近结果，表明即使每个基站的天线数量仅为中等规模，这些结果仍具有实用性。此外，我们证明当每个基站的天线数量趋于无穷时，可以在每个基站本地优化功率分配。因此，我们提出一种功率分配算法，该算法在显著降低基站间协调开销的同时，实现了接近最优的性能。由于邻近基站的波束赋形向量存在依赖性，本文的分析相比上行链路分析更具挑战性。这种统计依赖性通过引入带相关标记的标记散弹噪声点过程的新边界来处理，该边界在其他场景中同样具有适用性。