Efficient Optimal Joint Channel Estimation and Data Detection for Massive MIMO Systems

In this paper, we propose an efficient optimal joint channel estimation and data detection algorithm for massive MIMO wireless systems. Our algorithm is optimal in terms of the generalized likelihood ratio test (GLRT). For massive MIMO systems, we show that the expected complexity of our algorithm grows polynomially in the channel coherence time. Simulation results demonstrate significant performance gains of our algorithm compared with suboptimal non-coherent detection algorithms. To the best of our knowledge, this is the first algorithm which efficiently achieves GLRT-optimal non-coherent detections for massive MIMO systems with general constellations.Comment: 5 pages, 4 figures, Conferenc

Adaptive Beamforming for High Bit Rate Services in the FDD Mode of UTRA

Most time-reference beamforming algorithms suffer from severe beampattern distortion effects when applied to high bit rate services in WCDMA, causing serious performance degradation in terms of output BER, especially at high input SINR levels. These shortcomings are essentially caused by the uplink multiplexing of the traffic channel, which is seen by the base station as a powerful interfering source coming from the direction of arrival of the desired user. In this paper, a semi-blind beamforming technique is proposed as a valid solution to overcome this effect. The suggested scheme resorts to a conditional maximum likelihood approach to the underlying estimation problem and is designed to operate in an iterative fashion.Peer ReviewedPostprint (published version

Accounting for risk of non linear portfolios: a novel Fourier approach

The presence of non linear instruments is responsible for the emergence of non Gaussian features in the price changes distribution of realistic portfolios, even for Normally distributed risk factors. This is especially true for the benchmark Delta Gamma Normal model, which in general exhibits exponentially damped power law tails. We show how the knowledge of the model characteristic function leads to Fourier representations for two standard risk measures, the Value at Risk and the Expected Shortfall, and for their sensitivities with respect to the model parameters. We detail the numerical implementation of our formulae and we emphasizes the reliability and efficiency of our results in comparison with Monte Carlo simulation.Comment: 10 pages, 12 figures. Final version accepted for publication on Eur. Phys. J.

Measures and dynamics of entangled states

We develop an original approach for the quantitative characterisation of the entanglement properties of, possibly mixed, bi- and multipartite quantum states of arbitrary finite dimension. Particular emphasis is given to the derivation of reliable estimates which allow for an efficient evaluation of a specific entanglement measure, concurrence, for further implementation in the monitoring of the time evolution of multipartite entanglement under incoherent environment coupling. The flexibility of the technical machinery established here is illustrated by its implementation for different, realistic experimental scenarios.Comment: Physics Reports, in pres