Quantized Massive MU-MIMO-OFDM Uplink
Journal article, 2016

Coarse quantization at the base station (BS) of a massive multi-user (MU) multiple-input multiple-output (MIMO) wireless system promises significant power and cost savings. Coarse quantization also enables significant reductions of the raw analog-to-digital converter data that must be transferred from a spatially separated antenna array to the baseband processing unit. The theoretical limits as well as practical transceiver algorithms for such quantized MU-MIMO systems operating over frequency-flat, narrowband channels have been studied extensively. However, the practically relevant scenario where such communication systems operate over frequency-selective, wideband channels is less well understood. This paper investigates the uplink performance of a quantized massive MU-MIMO system that deploys orthogonal frequency-division multiplexing (OFDM) for wideband communication. We propose new algorithms for quantized maximum a posteriori channel estimation and data detection, and we study the associated performance/quantization tradeoffs. Our results demonstrate that coarse quantization (e.g., four to six bits, depending on the ratio between the number of BS antennas and the number of users) in massive MU-MIMO-OFDM systems entails virtually no performance loss compared with the infinite-precision case at no additional cost in terms of baseband processing complexity.

maximum a-posteriori (MAP) channel estimation

minimum mean-square error (MMSE) data detection

frequency-selective channels

Analog-to-digital conversion

forward-backward splitting (FBS)

convex optimization

orthogonal frequency-division multiplexing (OFDM)

massive multi-user multiple-input multiple-output (MU-MIMO)



Christoph Studer

Cornell University

Giuseppe Durisi

Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems

IEEE Transactions on Communications

0090-6778 (ISSN)

Vol. 64 6 2387-2399

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Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering



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