Semidefinite Relaxation for Large Scale MIMO Detection

João Lucas Negrão, Alex Myamoto Mussi, Taufik Abrão

DOI: 10.14209/sbrt.2016.211

Evento: XXXIV Simpósio Brasileiro de Telecomunicações (SBrT2016)

Keywords: MIMO detection lattice reduction semi-definite relaxation convex optimization

Abstract

The semi-definite relaxation (SDR) is a high performance efficient approach to MIMO detection especially for low modulation orders. We focus on developing a computationally efficient approximation of the maximum likelihood detector (ML) algorithm based on semi-definite programming (SDP) for MQAM constellations. The detector is based on a convex relaxation of the ML problem. A comparative analysis including the performance-complexity trade-off of the SDR and the lattice reduction (LR) aided linear MIMO detectors considering high number of antennas is carried out aiming to demonstrate the effectiveness of the SDR-based conventional and large scale MIMO detector. SDR-MIMO detector can provide a close, and under high order antennas cases, a better performance than the LR-aided linear MIMO detectors.

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