Abstract—Generalized space shift keying (GSSK) has recently
attracted much interest in the study of emerging massive MIMO
systems. The maximum likelihood (ML) detection of GSSK can
be posed as a 0-1 quadratic program with an equality constraint.
The penalty function method is a common way to transform a
constrained programming into an unconstrained one. However,
determining an ideal penalty factor is not a trivial problem and
has not been addressed adequately. In this letter, we prove a
lemma to show that the ML detection of GSSK can be converted
into an equivalent 0-1 quadratic program if the penalty factor
is greater than a small constant. Based on the proposed lemma,
we also present an algorithm to determine the penalty factor and
finally recover the transmitted signals of GSSK. Simulation results
substantiate the performance of the proposed detector.
