A New Approach to Linear Estimation Problem in Multi-user Massive MIMO Systems

A novel approach for solving linear estimation problem in multi-user massive MIMO systems is proposed. In this approach, the difficulty of matrix inversion is attributed to the incomplete definition of the dot product. The general definition of dot product implies that the columns of channel matrix are always orthogonal whereas, in practice, they may be not. If the latter information can be incorporated into dot product, then the unknowns can be directly computed from projections without inverting the channel matrix. By doing so, the proposed method is able to achieve an exact solution with a 25% reduction in computational complexity as compared to the QR method. Proposed method is stable, offers an extra flexibility of computing any single unknown, and can be implemented in just twelve lines of code

Implementation of a Scalable Matrix Inversion Architecture for Triangular Matrices

This paper presents an FPGA implementation of a novel snd Ihighl! scalable hardware architecture for inversion of triangiiliir matrices. An integral part of modern signal processing and communications applications involves manipulation of large matrices. Therefore, scalable and flexible hardware architectures are increasingly sought for. In this paper the traditional triangular shaped array architecture with n(n+l)/Z, where n being the number of inputs, communicating processors are mapped to a linear structure with only n processors. We show that the linear array structure avoids drawbacks such as nonscalability, large area and large power consumption. The implementation is based on a numerical stable recurrence algorithm which has excellent properties for hardware implementation. The implementation is the core processor in a smart antenna system