Shlezinger, N;
Eldar, YC;
Rodrigues, MRD;
(2019)
Asymptotic Task-Based Quantization With Application to Massive MIMO.
In: Sanei, Saeid and Hanzo, Lajos, (eds.)
Proceedings of the 44th International Conference on Acoustics, Speech and Signal Processing (ICASSP-2019).
(pp. pp. 3995-4012).
IEEE Xplore: New York, USA.
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Abstract
Quantizers take part in nearly every digital signal processing system that operates on physical signals. They are commonly designed to accurately represent the underlying signal, regardless of the specific task to be performed on the quantized data. In systems working with high-dimensional signals, such as massive multiple-input multiple-output (MIMO) systems, it is beneficial to utilize low-resolution quantizers, due to cost, power, and memory constraints. In this paper, we study quantization of high-dimensional inputs, aiming at improving performance under resolution constraints by accounting for the system task in the quantizers design. We focus on the task of recovering a desired signal statistically related to the high-dimensional input, and analyze two quantization approaches. We, first, consider vector quantization, which is typically computationally infeasible, and characterize the optimal performance achievable with this approach. Next, we focus on practical systems that utilize hardware-limited scalar uniform analog-to-digital converters (ADCs), and design a task-based quantizer under this model. The resulting system accounts for the task by linearly combining the observed signal into a lower dimension prior to quantization. We then apply our proposed technique to channel estimation in massive MIMO networks. Our results demonstrate that a system utilizing low-resolution scalar ADCs can approach the optimal channel estimation performance by properly accounting for the task in the system design.
| Type: | Proceedings paper |
|---|---|
| Title: | Asymptotic Task-Based Quantization With Application to Massive MIMO |
| Event: | 44th International Conference on Acoustics, Speech and Signal Processing (ICASSP-2019), 12-17 May 2019, Brighton, UK |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/TSP.2019.2923149 |
| Publisher version: | https://doi.org/10.1109/TSP.2019.2923149 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Massive MIMO, quantization, hybrid receivers |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10079523 |
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