  Spatial Modulation (SM) is a recently developed low-complexity Multiple-Input
Multiple-Output scheme that uses antenna indices and a conventional signal set
to convey information. It has been shown that the Maximum-Likelihood (ML)
detection in an SM system involves joint detection of the transmit antenna
index and the transmitted symbol, and hence, the ML search complexity grows
linearly with the number of transmit antennas and the size of the signal set.
In this paper, we show that the ML search complexity in an SM system becomes
independent of the constellation size when the signal set employed is a square-
or a rectangular-QAM. Further, we show that Sphere Decoding (SD) algorithms
become essential in SM systems only when the number of transmit antennas is
large and not necessarily when the employed signal set is large. We propose a
novel {\em hard-limiting} enabled sphere decoding detector whose complexity is
lesser than that of the existing detector and a generalized detection scheme
for SM systems with {\em arbitrary} number of transmit antennas. We support our
claims with simulation results that the proposed detectors are ML-optimal and
offer a significantly reduced complexity.
