Dataset for the paper “Quantum Search-Aided Multi-User Detection of IDMA-Assisted Multi-Layered Video Streaming“.

Panagiotis Botsinis, Yongkai Huo, Dimitrios Alanis, Zunaira Babar, Soon Xin Ng, Lajos Hanzo.
IEEE Access (accepted). Results may reproduced using MATLAB and GLE.

Abstract: Moore’s law is expected to lead to the gates of the quantum world in 2017. Therefore, the emerging quantum computing research is expected to give rise to novel quantum search algorithms, which may replace the currently used classical ones in wireless communications, leading to performance improvements and complexity reduction. In this treatise we demonstrate the benefits of Quantum-assisted Multi-User Detection (QMUD) in the uplink of a multi-user system, where the reference user conveys a multi-layered video stream to the base station, while using adaptive modulation and different rates per video layer. This is the first study, where a QMUD is employed in a video
application. The QMUD does not treat the rest of the users as interference, but rather detects the signals transmitted by all the users. We have evaluated the system’s performance both in terms of its Bit Error Ratio (BER) and Peak Signal-to-Noise
Ratio (PSNR) versus the channel’s Signal-to-Noise Ratio (SNR), while quantifying the complexity reduction achieved by using the QMUD instead of the optimal classical Maximum A Posteriori Probability (MAP) MUD. The effect of the number of users on the system’s performance is also quantified.

Acknowledgements: The financial support of the European Research Council under the Advanced Fellow Grant, that of the Royal Society’s Wolfson Research Merit Award and that of the Engineering and Physical Sciences Research Council under Grant EP/L018659/1 is gratefully acknowledged. The use of the IRIDIS High Performance Computing Facility at the University of Southampton is also acknowledged.

Each folder corresponds to a figure in the manuscript.