Lattice-reduction-aided semidefinite relaxation detection algorithms for multiple-input multipleoutput systems

Multiple-input multiple-output (MIMO) system is considered to be one of the key technologies of long-term evolution, since it achieves requirements of high throughput and spectral efficiency. The semidefinite relaxation (SDR) detection for MIMO systems is an attractive alternative to the optimum maximum likelihood (ML) decoding because it is very computationally efficient. In the case of the binary phase shift keying and four quadrature amplitude modulation constellations, the block error rate (BLER) performance of SDR detection is fairly close to the optimum BLER performance. However, for high-order modulation systems, their BLER performance is still unsatisfactory compared with the ML decoding. Lattice reduction technology can transform a matrix into a new equivalent one with more orthogonal and shorter basis vectors. It has been combined with linear decoders to improve their BLER performance. Inspired by this, the authors proposed two lattice-reduction-aided MIMO detection algorithms based on SDR. Simulation results demonstrate that they can provide near-optimum BLER performance with polynomial time complexity.