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dc.contributor.authorGuo, Shuaishuai
dc.contributor.authorZhang, Haixia
dc.contributor.authorZhang, Peng
dc.contributor.authorDang, Shuping
dc.contributor.authorCong, Liang
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2019-12-29T13:41:45Z
dc.date.available2019-12-29T13:41:45Z
dc.date.issued2019-01-27
dc.identifier.urihttp://hdl.handle.net/10754/660858
dc.description.abstractThis 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.
dc.publisherarXiv
dc.relation.urlhttps://arxiv.org/pdf/1901.09318
dc.rightsArchived with thanks to arXiv
dc.titleSignal Shaping for Generalized Spatial Modulation and Generalized Quadrature Spatial Modulation
dc.typePreprint
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.eprint.versionPre-print
dc.contributor.institutionShandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China,250061
dc.contributor.institutionSchool of Computer Engineering, Weifang University, Weifang 261061, China
dc.identifier.arxivid1901.09318
kaust.personGuo, Shuaishuai
kaust.personDang, Shuping
kaust.personAlouini, Mohamed-Slim
dc.versionv1
refterms.dateFOA2019-12-29T13:42:22Z


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