A Semidefinite Relaxation Approach to Efficient Soft Demodulation of MIMO 16-QAM

Three computationally-efficient list-based soft MIMO demodulators are developed, each of which generates its list using the randomization procedure associated with the semidefinite relaxation (SDR) of a particular hard demodulation problem. The structure of this SDR depends on the signaling scheme, and we will focus on 16-QAM signaling. The key step in the development of the first two demodulators is the derivation of polynomial expressions for the extrinsic information provided by the decoder. These expressions enable this information to be incorporated into the SDR framework. The resulting “List-SDR” demodulators require one semidefinite program (SDP) to be solved at each demodulation-decoding iteration. In the proposed “Single-SDR” demodulator this requirement is reduced to one SDP per channel use by deriving an approximation of the randomization procedure used by the List-SDR demodulator and showing that this approximation enables the decoupling of the processing of the channel measurement from that of the extrinsic information from the decoder. Simulation results show that the proposed demodulators provide considerable reductions in computational cost over several existing soft demodulators, and that these reductions are obtained without incurring a substantial degradation in performance.