In this paper, we present a new precoding technique using rotation transformations for closed loop multiple-input multiple-output (MIMO) wireless systems, which does not require the singular value decomposition (SVD) operation of the channel transfer matrix and allows a simple maximum-likelihood (ML) decoding at the receiver. We divide the precoding process into two steps: orthogonalization transformation which induces orthogonality between transmitted signals and beamforming transformation which achieves diversity gain. In the proposed method, we utilize a design criterion based on the minimum Euclidean distance between the received signals and then the vector orthogonalization is connected to the vector-norm maximization. In this paper, we focus on spatial multiplexing systems transmitting two independent data streams. Compared with the SVD based schemes, the proposed approach maintains a low complexity by relying only on three different kinds of rotation matrices for both the orthogonalization and beamforming transformation. Simulation results confirm that the proposed two step precoding achieves the better performance than the conventional SVD based MIMO precodings with reduced complexity.
- Closed-loop systems
- MIMO systems
- Maximum likelihood detection (MLD)
- Space division multiplexing (SDM)
ASJC Scopus subject areas
- Electrical and Electronic Engineering