本文研究了在系统和速率一定的条件下有着高斯噪声的衰落MIMO广播信道和功率最小化问题.该问题通常存在于无线通信系统动态资源分配中,是和功率约束下衰落MIMO下行链路和速率最大化的互补问题.首先利用MIMO MAC和MIMO BC的对偶性,将问题描述和转化为凸最优化问题,在此基础上,利用子梯度法和二分法,设计了相应的快速迭代的多用户注水算法,用于计算基站的发射功率.理论分析和数值仿真结果表明,该算法全局有效地收敛于最小的和功率.
In this paper, we consider the problem of minimizing sum power under the constraint of a sum rate in fading Gaussian multiple input multiple output(MIMO) broadcast channel( BC ) with additive Gaussian noise. This problem arises frequently in dynamic resource allocation of wireless communication systems. It is the complementary problem to sum rate maximization with a sum power constraint for fading MIMO downlink. We first formulate the equivalent convex optimization problem using the duality between the MIMO multi-access channel(MAC) and the MIMO BC. Then we derive a simple and fast iterative water-filling algorithrns based on the subgradient and bisection methods that compute sum power of the transmitter. Theory analysis and numerical simulations show that the proposed algorithm converges to the minimum sum power globally and efficiently.