A simplified iterative water-filling algorithm for per-user power allocation in multiuser MMSE-precoded MIMO systems

In this paper, we deal with a per-user power allocation problem in multiuser multiple input multiple output (MU-MIMO) systems based on minimum mean square error (MMSE) precoding. The MMSE-precoding technique provides a reasonable performance due to minimization of a composite interference-plus-noise power through allowing inter-user interference as well as the higher capacity with multiuser spatial multiplexing. The technique also has a reasonable computational complexity with linear transmit processing. The problem of optimizing per-user power allocation under inter-stream interference is not convex. Hence, we invoke some iterative approaches. In this paper, we propose a simplified iterative water-filling (SIWF) algorithm for per-user optimum power allocation in multiuser MMSE-precoded MIMO systems, in order to maximize the downlink sum capacity. This technique can reduce greatly the computational complexity for the iterative water-filling process through accelerating the iteration process, as compared with the existing modified iterative water-filling (MIWF) algorithm without any performance loss. In the proposed algorithm, hot the taxation and interference terms are updated at every iteration of the inner loop of iterative water-filling. In addition, per-user power levels at every iteration for the inner loop are normalized so that the total transmit power constraint could be satisfied, prior to the next iteration. From computer simulations and complexity analyses, we show that the proposed algorithm has much lower complexity but the same capacity, as compared with the original NHWF algorithm.