Analog processing to enable scalable high-throughput mm-Wave wireless fiber systems

Sawaby, Mahmoud; Mamandipoor, Babak; Madhow, Upamanyu; Arbabian, Amin

doi:10.1109/acssc.2016.7869662

Cited by 10 publications

(2 citation statements)

References 17 publications

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“…The goal of our investigation of severely quantized LoS MIMO, therefore, is to examine how far we can push the paradigm of using larger available bandwidths (which limits the precision of available ADCs) to reduce the required constellation size (which potentially enables reduction in ADC precision). Our work also contrasts with recent efforts in the research literature based on analog-centric [8]- [11] or hybrid analog-digital [12]- [15] processing in an attempt to sidestep the ADC bottleneck.…”

Section: Related Workmentioning

confidence: 59%

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All-Digital LoS MIMO with Low-Precision Analog-to-Digital Conversion

Sezer¹,

Madhow²

2021

Preprint

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Line-of-sight (LoS) multi-input multi-output (MIMO) systems exhibit attractive scaling properties with increase in carrier frequency: for a fixed form factor and range, the spatial degrees of freedom increase quadratically for 2D arrays, in addition to the typically linear increase in available bandwidth.In this paper, we investigate whether modern all-digital baseband signal processing architectures can be devised for such regimes, given the difficulty of analog-to-digital conversion for large bandwidths. We propose low-precision quantizer designs and accompanying spatial demultiplexing algorithms, considering 2 × 2 LoS MIMO with QPSK for analytical insight, and 4 × 4 MIMO with QPSK and 16QAM for performance evaluation. Unlike prior work, channel state information is utilized only at the receiver (i.e., transmit precoding is not employed). We investigate quantizers with regular structure whose high-SNR mutual information approaches that of an unquantized system. We prove that amplitude-phase quantization is necessary to attain this benchmark; phase-only quantization falls short. We show that quantizers based on maximizing per-antenna output entropy perform better than standard Minimum Mean Squared Quantization Error (MMSQE) quantization. For spatial demultiplexing with severely quantized observations, we introduce the novel concept of virtual quantization which, combined with linear detection, provides reliable demodulation at significantly reduced complexity compared to maximum likelihood detection.

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Section: Related Workmentioning

confidence: 59%

“…An important direction for future research is to investigate quantization-constrained LoS MIMO is more complex settings, including understanding the impact of dispersion due to geometric misalignments and potential performance advantages of spatial oversampling [8], [14].…”

Section: Discussionmentioning

confidence: 99%