1 research outputs found
Signal Shaping for Generalized Spatial Modulation and Generalized Quadrature Spatial Modulation
This paper investigates generic signal shaping methods for
multiple-data-stream generalized spatial modulation (GenSM) and generalized
quadrature spatial modulation (GenQSM) based on the maximizing the minimum
Euclidean distance (MMED) criterion. Three cases with different channel state
information at the transmitter (CSIT) are considered, including no CSIT,
statistical CSIT and perfect CSIT. A unified optimization problem is formulated
to find the optimal transmit vector set under size, power and sparsity
constraints. We propose an optimization-based signal shaping (OBSS) approach by
solving the formulated problem directly and a codebook-based signal shaping
(CBSS) approach by finding sub-optimal solutions in discrete space. In the OBSS
approach, we reformulate the original problem to optimize the signal
constellations used for each transmit antenna combination (TAC). Both the size
and entry of all signal constellations are optimized. Specifically, we suggest
the use of a recursive design for size optimization. The entry optimization is
formulated as a non-convex large-scale quadratically constrained quadratic
programming (QCQP) problem and can be solved by existing optimization
techniques with rather high complexity. To reduce the complexity, we propose
the CBSS approach using a codebook generated by quadrature amplitude modulation
(QAM) symbols and a low-complexity selection algorithm to choose the optimal
transmit vector set. Simulation results show that the OBSS approach exhibits
the optimal performance in comparison with existing benchmarks. However, the
OBSS approach is impractical for large-size signal shaping and adaptive signal
shaping with instantaneous CSIT due to the demand of high computational
complexity. As a low-complexity approach, CBSS shows comparable performance and
can be easily implemented in large-size systems.Comment: Summited to IEEE TW