Fast Updating the STBC Decoder Matrices in the Uplink of a Massive MIMO System

Reducing computational complexity of the modern wireless communication systems such as massive Multiple-Input Multiple-Output (MIMO) configurations is of utmost interest. In this paper, we propose new algorithm that can be used to accelerate matrix inversion in the decoding of space-time block codes (STBC) in the uplink of dynamic massive MIMO systems. A multi-user system in which the base station is equipped with a large number of antennas and each user has two antennas is considered. In addition, users can enter or exit the system dynamically. For a given space-time block coding/decoding scheme the computational complexity of the receiver will be significantly reduced when a user is added to or removed from the system by employing the proposed method. In the proposed scheme, the matrix inversion for zero-forcing (ZF) as well as minimum mean square error (MMSE) decoding is derived from the inverse of a partitioned matrix and the Woodbury matrix identity. Furthermore, the suggested technique can be utilized when the number of users is fixed but the channel estimate changes for a particular user. The mathematical equations for updating the inverse of the decoding matrices are derived and its complexity is compared to the direct way of computing the inverse. Evaluations confirm the effectiveness of the proposed approach.

Energy Efficient Water-Filling Power Allocation with Cell Division for Massive MIMO Systems

In this paper, we consider the power allocation problem for the downlink of the massive multiple-input multiple-output (MIMO) systems. We propose a new scheme by exploiting the water-filling algorithm in a cell with two zones. It is allocated more power to the farther users, and also users with better channel conditions receive more power in each zone. The users with better channel gain have a higher priority than others in the energy efficiency (EE) point of view. Combining the water-filling and cell division techniques in the MIMO systems leads to a reach EE maximization. We also use standard interference function (SIF) to propose a new iterative algorithm for solving the optimization problem and obtain an efficient power allocation scheme. Simulation results show that the proposed algorithm outperforms other similar algorithms from the EE point of view.