Applying the Riemann geometric machinery of volume estimates in terms of curvature, bounds for the minimal distance of packings/codes in the Grassmann and Stiefel manifolds will be derived and analyzed. In the context of space time block codes this leads to a monotonically increasing minimal distance lower bound as a function of the block length. This advocates large block lengths for the code design. Index Terms-Sphere packings, space-time codes, Gilbert-Varshamov/Hamming bounds, Stiefel/Grassmann manifold2) At first sight the proposition seems obvious, but one has to take into account that d V is expressed in terms of Φ, Ψ ∈ V k,n , while r V is expressed in terms of the space of tangents and these two spaces are linked by the matrix exponential which can not be written in closed form compare Appendix B. Furthermore unlike d V , r V is NOT induced by (geodesics with respect to) the seemingly canonical embedding V k,n ⊂ n×k , compare Appendix A-I.2

A theorem about local in time existence of spacelike foliations with prescribed mean curvature in cosmological spacetimes will be proved. The time function of the foliation is geometrically defined and fixes the diffeomorphism invariance inherent in general foliations of spacetimes. Moreover, in contrast to the situation of the more special constant mean curvature foliations, which play an important role in global analysis of spacetimes, this theorem overcomes the existence problem arising from topological restrictions for surfaces of constant mean curvature.

A theorem about local in time existence of spacelike foliations with prescribed mean curvature in cosmological spacetimes will be proved. The time function of the foliation is geometrically defined and fixes the diffeomorphism invariance inherent in general foliations of spacetimes. Moreover, in contrast to the situation of the more special constant mean curvature foliations, which play an important role in global analysis of spacetimes, this theorem overcomes the existence problem arising from topological restrictions for surfaces of constant mean curvature

Abstract-In this work, the geometric relation between space time block code design for the coherent channel and its noncoherent counterpart is exploited to get an analogue of the information theoretic inequality I(X; S) ≤ I((X, H); S) in terms of diversity. It provides a lower bound on the performance of non-coherent codes when used in coherent scenarios. This leads in turn to a code design decomposition result splitting coherent code design into two complexity reduced sub tasks. Moreover a geometrical criterion for high performance space time code design is derived.

It is well known, that the Alamouti scheme is the only space-time code from orthogonal design achieving the capacity of a multiple-input multiple-output (MIMO) wireless communication system with n_T=2 transmit antennas and n_R=1 receive antenna. In this work, we propose the n-times stacked Alamouti scheme for n_T=2n transmit antennas and show that this scheme achieves the capacity in the case of n_R=1 receive antenna. This result may regarded as an extension of the Alamouti case. For the more general case of more than one receive antenna, we show that if the number of transmit antennas is higher than the number of receive antennas we achieve a high portion of the capacity with this scheme. Further, we show that the MIMO capacity is at most twice the rate achieved with the proposed scheme for all SNR. We derive lower and upper bounds for the rate achieved with this scheme and compare it with upper and lower bounds for the capacity. In addition to the capacity analysis based on the assumption of a coherent channel, we analyze the error rate performance of the stacked OSTBC with the optimal ML detector and with the suboptimal lattice-reduction (LR) aided zero-forcing detector. We compare the error rate performance of the stacked OSTBC with spatial multiplexing (SM) and full-diversity achieving schemes. Finally, we illustrate the theoretical results by numerical simulations.Comment: IEEE Transactions on Signal Processing, accepte