Communications in Information and Systems
Volume 20 (2020)
Mathematical Engineering: A special issue at the occasion of the 85th birthday of Prof. Thomas Kailath
Guest Editors: Ali H. Sayed, Helmut Bölcskei, Patrick Dewilde, Vwani Roychowdhury, and Stephen Shing-Toung Yau
Task-based quantization with application to MIMO receivers
Pages: 131 – 162
Multiple-input multiple-output (MIMO) systems are required to communicate reliably at high spectral bands using a large number of antennas, while operating under strict power and cost constraints. In order to meet these constraints, future MIMO receivers are expected to operate with low resolution quantizers, namely, utilize a limited number of bits for representing their observed measurements, inherently distorting the digital representation of the acquired signals. The fact that MIMO receivers use their measurements for some task, such as symbol detection and channel estimation, other than recovering the underlying analog signal, indicates that the distortion induced by bit-constrained quantization can be reduced by designing the acquisition scheme in light of the system task, i.e., by task-based quantization. In this work we survey the theory and design approaches to task-based quantization, presenting model-aware designs as well as data-driven implementations. Such task-based quantizers are shown to notably outperform conventional approaches which the desired information from lowresolution measurements solely in the digital domain. Then, we show how one can implement a task-based bit-constrained MIMO receiver, presenting approaches ranging from conventional hybrid receiver architectures to structures exploiting the dynamic nature of metasurface antennas. This survey narrows the gap between theoretical task-based quantization and its implementation in practice, providing concrete algorithmic and hardware design principles for realizing task-based MIMO receivers.
This work received funding from the Benoziyo Endowment Fund for the Advancement of Science, the Estate of Olga Klein – Astrachan, the European Union’s Horizon 2020 research and innovation program under grant No. 646804-ERC-COGBNYQ, and the Israel Science Foundation under grant No. 0100101.
Received 7 February 2020
Published 19 November 2020