MIMO system capacity improvements using radio-over-fibre distributed antenna system technology

The effect of antenna separation in a 3×3 MIMO system using RoF DAS technology is investigated. Larger antenna separation is found to improve the throughput due to reduced channel correlation and improved SNR. © 2011 Optical Society of America.

MIMO System capacity improvements using radio-over-fibre distributed antenna system technology

The effect of antenna separation in a 3×3 MIMO system using RoF DAS technology is investigated. Larger antenna separation is found to improve the throughput due to reduced channel correlation and improved SNR. © OSA/OFC/NFOEC 2011.

Significant improvements in optical power budgets of real-time optical OFDM PON systems.

Based on a comprehensive theoretical optical orthogonal frequency division multiplexing (OOFDM) system model rigorously verified by comparing numerical results with end-to-end real-time experimental measurements at 11.25Gb/s, detailed explorations are undertaken, for the first time, of the impacts of various physical factors on the OOFDM system performance over directly modulated DFB laser (DML)-based, intensity modulation and direct detection (IMDD), single-mode fibre (SMF) systems without in-line optical amplification and chromatic dispersion compensation. It is shown that the low extinction ratio (ER) of the DML modulated OOFDM signal is the predominant factor limiting the maximum achievable optical power budget, and the subcarrier intermixing effect associated with square-law photon detection in the receiver reduces the optical power budget by at least 1dB. Results also indicate that, immediately after the DML in the transmitter, the insertion of a 0.02nm bandwidth optical Gaussian bandpass filter with a 0.01nm wavelength offset with respect to the optical carrier wavelength can enhance the OOFDM signal ER by approximately 1.24dB, thus resulting in a 7dB optical power budget improvement at a total channel BER of 1 × 10(-3).

Uncertainty management for on-line optimisation of a POMDP-based large-scale spoken dialogue system

The optimization of dialogue policies using reinforcement learning (RL) is now an accepted part of the state of the art in spoken dialogue systems (SDS). Yet, it is still the case that the commonly used training algorithms for SDS require a large number of dialogues and hence most systems still rely on artificial data generated by a user simulator. Optimization is therefore performed off-line before releasing the system to real users. Gaussian Processes (GP) for RL have recently been applied to dialogue systems. One advantage of GP is that they compute an explicit measure of uncertainty in the value function estimates computed during learning. In this paper, a class of novel learning strategies is described which use uncertainty to control exploration on-line. Comparisons between several exploration schemes show that significant improvements to learning speed can be obtained and that rapid and safe online optimisation is possible, even on a complex task. Copyright © 2011 ISCA.