Riemannian-Optimization-Based Hybrid Precoder for Spatial Modulation Aided Millimeter Wave MIMO - Chen, Hong-Yunn; Chou, Cheng-Fu; Golubchik, Leana (IEEE Vehicular Technology Conference, 2019)
The millimeter wave (mmWave) technology is considered as the potential candidate for high speed telecommunications service in 5G wireless communication, as it offers a ten times larger spectrum than existing cellular systems. The generalized spatial modulation (GenSM) aided millimeter wave multiple input multiple-output (mm-wave MIMO) concept have attracted substantial research interest, as it could lead to significant performance enhancement of mm-wave MIMO while maintaining the antennas with reduced number of active chains. However, current solvers either get stuck in a local minimum or have much computational complexity of GenSM-aided mm-wave MIMO schemes because the non-convex nature of the hybrid precoding design incurs significant performance degradation. To address this problem, we employ the Riemannian Optimization (RO) algorithms for the design of a hybrid precoder for GenSM-aided mm-wave MIMOs in order to enhance the spectral efficiency (SE). That is, we first re-design the hybrid precoding structures, i.e., by integrating the RF chain power constraints into the objective function; this allows the original optimized problem with constraints to be transformed into an unconstrained optimization problem on a nonlinear search space. Next, by considering the characteristics of a digital precoder, we are able to construct a proper manifold, in which we could effectively apply the RO iterative gradient descent method for computing a better solution. Our simulation results show that the proposed RO-based hybrid precoder is able to (a) outperform traditional GenSM-aided mm-wave MIMOs schemes, and (b) achieve comparable SE performance, when compared with modern mm-wave MIMO schemes.