Reconstruction of Clipped Signals in Quantized Uplink Massive MIMO Systems
2020 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 68, no 5, p. 2891-2905, article id 8984303Article in journal (Refereed) Published
Abstract [en]
This paper considers the uplink of a single-cell multiuser massive multiple-input multiple-output system. Each receiver antenna of the base station (BS) is assumed to be equipped with a pair of analog-to-digital converters to quantize the real and imaginary part of the received signal. We propose a novel clipping-aware receiver (CA-MMSE), which performs minimum mean square error (MMSE) reconstruction only on the clipped received samples, while the granular samples are left unchanged after the quantization. On this basis, we present an iterative algorithm to implement the CA-MMSE receiver and derive a sufficient condition for its geometrical convergence to a fixed point. We show that as long as the number of BS antennas or the quantization resolution is sufficiently high, then, the performance of the CA-MMSE is as good as the optimal MMSE receiver which reconstructs all quantized received symbols. Additionally, we propose a novel Bussgang-based weighted zero-forcing (B-WZF) receiver which distinguishes the clipping and granular distortion and it is shown that as long as the received training symbols per antenna are correlated, the CA-MMSE brings significant improvements compared to conventional receivers in the literature while for users that do not experience deep large-scale fading the simpler B-WZF is near to the CA-MMSE for sufficiently high signal-to-noise ratio and quantization resolution. © 1972-2012 IEEE.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2020. Vol. 68, no 5, p. 2891-2905, article id 8984303
Keywords [en]
analog-to-digital converter (ADC), Bussgang's theorem, channel estimation, clipping, Massive multi-user multiple-input multiple-output (MIMO), minimum mean-square error (MMSE), signal reconstruction, Iterative methods, Mean square error, MIMO systems, Radio receivers, Receiving antennas, Scales (weighing instruments), Signal to noise ratio, User experience, Analog to digital converters, Geometrical convergence, High signal-to-noise ratio, Iterative algorithm, Minimum mean square error reconstruction, Multiple input multiple output system, Quantization resolution, Real and imaginary, Quantization (signal)
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:bth-19570DOI: 10.1109/TCOMM.2020.2971975ISI: 000536770300018Scopus ID: 2-s2.0-85085168705OAI: oai:DiVA.org:bth-19570DiVA, id: diva2:1435779
Funder
Vinnova2020-06-052020-06-052020-09-07Bibliographically approved