Constant Modulus Algorithms via Low-Rank Approximation

We present a novel convex-optimization-based approach to the solutions of a family of problems involving constant modulus signals. The family of problems includes the constant modulus and the constrained constant modulus, as well as the modified constant modulus and the constrained modified constant modulus. The usefulness of the proposed solutions is demonstrated for the tasks of blind beamforming and blind multiuser detection. The performance of these solutions, as we demonstrate by simulated data, is superior to existing methods.This work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216

Efficient blind decoding of orthogonal space-time block codes over time-selective fading channels

In this paper, we consider efficient blind decoder design for orthogonal space-time block codes (OSTBCs). A general decision rule for blind OSTBC decoding is derived assuming a quasi-static flat multiple-input multiple-output (MIMO) Rayleigh fading channel. We use the linear dispersion representation of OSTBCs to derive a blind decoder that results in a quadratic minimization problem, which can be solved efficiently by semidefinite relaxation, sphere decoding or successive interference cancellation. To resolve phase ambiguity problems inherent in blind detectors, rather than using pilot symbols that results in a bandwidth loss, we propose novel totally blind decoders using dual constellations or a superimposed training scheme. To alleviate the computational burden, a minimum mean-squareerror (MMSE) channel estimator is also proposed to track the time-varying channel without using the blind decoder