Maximizing Energy Efficiency in the Vector Precoded MU-MISO Downlink by Selective Perturbation

We propose an energy-efficient vector perturbation (VP) technique for the downlink of multiuser multiple-input-single-output (MU-MISO) systems. In contrast to conventional VP where the search for perturbation vectors involves all users´ symbols, here, the perturbation is applied to a subset of the transmitted symbols. This, therefore, introduces a performance-complexity tradeoff, where the complexity is greatly reduced compared to VP by limiting the dimensions of the sphere search, at the expense of a performance penalty compared to VP. By changing the size of the subset of perturbed users, the aforementioned tradeoff can be controlled to maximize energy efficiency. We further propose three distinct criteria for selecting which users´ symbols to perturb, each of which yields a different performance-complexity tradeoff. The presented analytical and simulation results show that partially perturbing the data provides a favorable tradeoff, particularly at low-power transmission where the power consumption associated with the signal processing becomes dominant. In fact, it is shown that diversity close to the one for conventional VP can be achieved at energy efficiency levels improved by up to 300% compared to VP.