In this paper, assuming multi-antenna transmitter and receivers, we consider multicast beamformer design for the weighted max-min-fairness (WMMF) problem in a multi-stream multi-group communication setup. Unlike the single-stream scenario, the WMMF objective in this setup is not equivalent to maximizing the minimum weighted SINR due to the summation over the rates of multiple streams. Therefore, the non-convex problem at hand is first approximated with a convex one and then solved using Karush-Kuhn-Tucker (KKT) conditions. Then, a practically appealing closed-form solution is derived, as a function of dual variables, for both transmit and receive beamformers. Finally, we use an iterative solution based on the sub-gradient method to solve for the mutually coupled and interdependent dual variables. The proposed solution does not rely on generic solvers and does not require any bisection loop for finding the achievable rate of various streams. As a result, it significantly outperforms the state-of-art in terms of computational cost and convergence speed.
翻译:在本文中,假设多ANETNA发射机和接收机,我们假设在多流多组通信设置中考虑加权最大公平(WMMF)问题的多播波形设计。与单一流情景不同,WMMF在这种设置中的目标并不等于由于对多流速度的比较而使最低加权SINR最大化。因此,手头的非吞吐器问题首先与一个连接器相近,然后使用Karush-Kuhn-Tucker (KKTT) 的条件加以解决。然后,作为一种双重变量的功能,为传输和接收光流得出一个实际具有吸引力的封闭式解决方案。最后,我们使用基于分位法的迭代解决方案来解决相互配合和相互依存的双重变量。拟议解决方案并不依赖通用求解器,而且不需要任何两部分循环来寻找各种流的可实现速度。结果,它大大超出了计算成本和速度方面的最新水平。