One-Bit Sigma-Delta MIMO Precoding

Coarsely quantized MIMO signalling methods have gained popularity in the recent developments of massive MIMO as they open up opportunities for massive MIMO implementation using cheap and power-efficient radio-frequency front-ends. This paper presents a new one-bit MIMO precoding approach using spati...

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Published in:IEEE journal of selected topics in signal processing Vol. 13; no. 5; pp. 1046 - 1061
Main Authors: Shao, Mingjie, Ma, Wing-Kin, Li, Qiang, Swindlehurst, A. Lee
Format: Journal Article
Language:English
Published: New York IEEE 01.09.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1932-4553, 1941-0484
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Abstract Coarsely quantized MIMO signalling methods have gained popularity in the recent developments of massive MIMO as they open up opportunities for massive MIMO implementation using cheap and power-efficient radio-frequency front-ends. This paper presents a new one-bit MIMO precoding approach using spatial Sigma-Delta (<inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula>) modulation. In previous one-bit MIMO precoding research, one mainly focuses on using optimization to tackle the difficult binary signal optimization problem that arises from the precoding design. Our approach attempts a different route. Assuming angular MIMO channels, we apply <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> modulation-a classical concept in analog-to-digital conversion of temporal signals-in space. The resulting <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding approach has two main advantages: First, we no longer need to deal with binary optimization in <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding design. Particularly, the binary signal restriction is replaced by peak signal amplitude constraints. Second, the impact of the quantization error can be well controlled via modulator design and under appropriate operating conditions. Through symbol error probability analysis, we reveal that the very large number of antennas in massive MIMO provides favorable operating conditions for <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding. In addition, we develop a new <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> modulation architecture that is capable of adapting the channel to achieve nearly zero quantization error for a targeted user. Furthermore, we consider multi-user <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding using the zero-forcing and symbol-level precoding schemes. These two <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding schemes perform considerably better than their direct one-bit quantized counterparts, as simulation results show.
AbstractList Coarsely quantized MIMO signalling methods have gained popularity in the recent developments of massive MIMO as they open up opportunities for massive MIMO implementation using cheap and power-efficient radio-frequency front-ends. This paper presents a new one-bit MIMO precoding approach using spatial Sigma-Delta ([Formula Omitted]) modulation. In previous one-bit MIMO precoding research, one mainly focuses on using optimization to tackle the difficult binary signal optimization problem that arises from the precoding design. Our approach attempts a different route. Assuming angular MIMO channels, we apply [Formula Omitted] modulation—a classical concept in analog-to-digital conversion of temporal signals—in space. The resulting [Formula Omitted] precoding approach has two main advantages: First, we no longer need to deal with binary optimization in [Formula Omitted] precoding design. Particularly, the binary signal restriction is replaced by peak signal amplitude constraints. Second, the impact of the quantization error can be well controlled via modulator design and under appropriate operating conditions. Through symbol error probability analysis, we reveal that the very large number of antennas in massive MIMO provides favorable operating conditions for [Formula Omitted] precoding. In addition, we develop a new [Formula Omitted] modulation architecture that is capable of adapting the channel to achieve nearly zero quantization error for a targeted user. Furthermore, we consider multi-user [Formula Omitted] precoding using the zero-forcing and symbol-level precoding schemes. These two [Formula Omitted] precoding schemes perform considerably better than their direct one-bit quantized counterparts, as simulation results show.
Coarsely quantized MIMO signalling methods have gained popularity in the recent developments of massive MIMO as they open up opportunities for massive MIMO implementation using cheap and power-efficient radio-frequency front-ends. This paper presents a new one-bit MIMO precoding approach using spatial Sigma-Delta (<inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula>) modulation. In previous one-bit MIMO precoding research, one mainly focuses on using optimization to tackle the difficult binary signal optimization problem that arises from the precoding design. Our approach attempts a different route. Assuming angular MIMO channels, we apply <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> modulation-a classical concept in analog-to-digital conversion of temporal signals-in space. The resulting <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding approach has two main advantages: First, we no longer need to deal with binary optimization in <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding design. Particularly, the binary signal restriction is replaced by peak signal amplitude constraints. Second, the impact of the quantization error can be well controlled via modulator design and under appropriate operating conditions. Through symbol error probability analysis, we reveal that the very large number of antennas in massive MIMO provides favorable operating conditions for <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding. In addition, we develop a new <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> modulation architecture that is capable of adapting the channel to achieve nearly zero quantization error for a targeted user. Furthermore, we consider multi-user <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding using the zero-forcing and symbol-level precoding schemes. These two <inline-formula><tex-math notation="LaTeX">\Sigma \Delta</tex-math></inline-formula> precoding schemes perform considerably better than their direct one-bit quantized counterparts, as simulation results show.
Author Ma, Wing-Kin
Li, Qiang
Shao, Mingjie
Swindlehurst, A. Lee
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Cites_doi 10.1109/SPAWC.2017.8227757
10.1007/s10107-015-0946-6
10.1109/ICASSP.2018.8461642
10.1109/JETCAS.2017.2772191
10.1109/ISCAS.1992.230265
10.1109/NRC.2004.1316400
10.1109/18.59924
10.1109/ICASSP.2018.8462190
10.1109/TSP.2011.2109954
10.1109/TCOMM.2017.2723000
10.1109/ICASSP.2017.7953405
10.1109/82.476175
10.1137/080716542
10.1109/TWC.2018.2868369
10.1109/TSP.2017.2706179
10.1109/TSP.2017.2715006
10.1109/TSP.2019.2937280
10.1109/LCOMM.2015.2494600
10.1109/TWC.2018.2873386
10.1109/79.482138
10.1109/GlobalSIP.2018.8646546
10.1109/LWC.2017.2787159
10.1109/TWC.2016.2585640
10.1109/TCOMM.2016.2545666
10.1109/JSTSP.2018.2823267
10.1109/TAP.2013.2241719
10.1109/TSP.2008.924638
10.1109/NDS.2017.8070633
10.1109/LWC.2017.2740386
10.1109/ACSSC.2016.7869149
10.1109/TWC.2018.2827028
10.1137/1.9781611974997
10.1109/TWC.2017.2691318
10.1109/ICECS.2009.5410815
10.2140/pjm.1958.8.171
10.1109/LCOMM.2017.2687871
10.1109/TWC.2016.2619343
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References ref35
ref13
ref12
bertsekas (ref43) 2003
ref37
ref15
ref36
ref14
ref31
ref30
ref33
ref11
nesterov (ref38) 0; 269
ref32
ref10
barac (ref21) 2016
ref2
ref1
ref39
ref17
ref16
ref19
ref18
beck (ref40) 2017; 25
ref24
ref23
ref26
ref25
ref42
ref41
corey (ref20) 0
ref28
proakis (ref34) 2001
ref27
ref29
nikoofard (ref22) 0
ref8
ref7
ref9
ref4
ref3
ref6
ref5
References_xml – ident: ref30
  doi: 10.1109/SPAWC.2017.8227757
– start-page: 301
  year: 0
  ident: ref22
  article-title: Low-complexity N-port ADCs using 2-D sigma-delta noise-shaping for N-element array receivers
  publication-title: Proc Int Midwest Symp Circuits Syst
– ident: ref42
  doi: 10.1007/s10107-015-0946-6
– ident: ref31
  doi: 10.1109/ICASSP.2018.8461642
– ident: ref11
  doi: 10.1109/JETCAS.2017.2772191
– ident: ref33
  doi: 10.1109/ISCAS.1992.230265
– ident: ref27
  doi: 10.1109/NRC.2004.1316400
– year: 2016
  ident: ref21
  article-title: Spatial sigma-delta modulation in a massive MIMO cellular system
– ident: ref32
  doi: 10.1109/18.59924
– ident: ref35
  doi: 10.1109/ICASSP.2018.8462190
– ident: ref24
  doi: 10.1109/TSP.2011.2109954
– ident: ref12
  doi: 10.1109/TCOMM.2017.2723000
– ident: ref13
  doi: 10.1109/ICASSP.2017.7953405
– ident: ref26
  doi: 10.1109/82.476175
– ident: ref39
  doi: 10.1137/080716542
– ident: ref16
  doi: 10.1109/TWC.2018.2868369
– ident: ref4
  doi: 10.1109/TSP.2017.2706179
– year: 2003
  ident: ref43
  publication-title: Convex Analysis and Optimization
– ident: ref9
  doi: 10.1109/TSP.2017.2715006
– ident: ref18
  doi: 10.1109/TSP.2019.2937280
– ident: ref1
  doi: 10.1109/LCOMM.2015.2494600
– ident: ref15
  doi: 10.1109/TWC.2018.2873386
– ident: ref19
  doi: 10.1109/79.482138
– ident: ref37
  doi: 10.1109/GlobalSIP.2018.8646546
– ident: ref6
  doi: 10.1109/LWC.2017.2787159
– ident: ref25
  doi: 10.1109/TWC.2016.2585640
– ident: ref2
  doi: 10.1109/TCOMM.2016.2545666
– year: 2001
  ident: ref34
  publication-title: Digital Communications
– ident: ref17
  doi: 10.1109/JSTSP.2018.2823267
– ident: ref28
  doi: 10.1109/TAP.2013.2241719
– ident: ref36
  doi: 10.1109/TSP.2008.924638
– ident: ref23
  doi: 10.1109/NDS.2017.8070633
– ident: ref14
  doi: 10.1109/LWC.2017.2740386
– ident: ref29
  doi: 10.1109/ACSSC.2016.7869149
– year: 0
  ident: ref20
  article-title: Spatial sigma-delta signal acquisition for wideband beamforming arrays
  publication-title: Proc Int ITG Workshop Smart Antennas
– volume: 269
  start-page: 543
  year: 0
  ident: ref38
  article-title: A method for unconstrained convex minimization problem with the rate of convergence $\mathcal {O}(1/k^2)$
  publication-title: Doklady an USSR
– ident: ref7
  doi: 10.1109/TWC.2018.2827028
– volume: 25
  year: 2017
  ident: ref40
  publication-title: First Order Optimization Method
  doi: 10.1137/1.9781611974997
– ident: ref5
  doi: 10.1109/TWC.2017.2691318
– ident: ref8
  doi: 10.1109/ICECS.2009.5410815
– ident: ref41
  doi: 10.2140/pjm.1958.8.171
– ident: ref10
  doi: 10.1109/LCOMM.2017.2687871
– ident: ref3
  doi: 10.1109/TWC.2016.2619343
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SubjectTerms Analog to digital conversion
Antenna arrays
Design optimization
Error analysis
Massive MIMO
Measurement
MIMO communication
MIMO precoder design
Modulation
one-bit MIMO
Optimization
Precoding
Quantization (signal)
Sigma-Delta modulation
Title One-Bit Sigma-Delta MIMO Precoding
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