  Generalized quadrature spatial modulation (GQSM) schemes are known to achieve
high energy- and spectral- efficiencies by modulating information both in
transmitted symbols and in coded combinatorial activations of subsets of
multiple transmit antennas. A challenge of the approach is, however, the
decoding complexity which scales with the efficiency of the scheme. In order to
circumvent this bottleneck and enable high-performance and feasible GQSM in
massive multiple-input multiple-output (mMIMO) scenarios, we propose a novel
decoding algorithm which enjoys a complexity order that is independent of the
combinatorial factor. This remarkable feature of the proposed decoder is a
consequence of a novel vectorized Gaussian belief propagation (GaBP) algorithm,
here contributed, whose message passing (MP) rules leverage both pilot symbols
and the unit vector decomposition (UVD) of the GQSM signal structure. The
effectiveness of the proposed UVD-GaBP method is illustrated via computer
simulations including numerical results for systems of a size never before
reported in related literature (up to 32 transmit antennas), which demonstrates
the potential of the approach in paving the way towards high energy and
spectral efficiency for wireless systems in a truly mMIMO setting.
