1,785 research outputs found
The Distributed MIMO Scenario: Can Ideal ADCs Be Replaced by Low-resolution ADCs?
This letter considers the architecture of distributed antenna system, which
is made up of a massive number of single-antenna remote radio heads (RRHs),
some with full-resolution but others with low-resolution analog-to-digital
converter (ADC) receivers. This architecture is greatly motivated by its high
energy efficiency and low-cost implementation. We derive the worst-case uplink
spectral efficiency (SE) of the system assuming a frequency-flat channel and
maximum-ratio combining (MRC), and reveal that the SE increases as the number
of quantization bits for the low-resolution ADCs increases, and the SE
converges as the number of RRHs with low-resolution ADCs grows. Our results
furthermore demonstrate that a great improvement can be obtained by adding a
majority of RRHs with low-resolution ADC receivers, if sufficient quantization
precision and an acceptable proportion of high-to-low resolution RRHs are used.Comment: 4 pages, to be published in IEEE Wireless Communications Letter
Bayes-Optimal Joint Channel-and-Data Estimation for Massive MIMO with Low-Precision ADCs
This paper considers a multiple-input multiple-output (MIMO) receiver with
very low-precision analog-to-digital convertors (ADCs) with the goal of
developing massive MIMO antenna systems that require minimal cost and power.
Previous studies demonstrated that the training duration should be {\em
relatively long} to obtain acceptable channel state information. To address
this requirement, we adopt a joint channel-and-data (JCD) estimation method
based on Bayes-optimal inference. This method yields minimal mean square errors
with respect to the channels and payload data. We develop a Bayes-optimal JCD
estimator using a recent technique based on approximate message passing. We
then present an analytical framework to study the theoretical performance of
the estimator in the large-system limit. Simulation results confirm our
analytical results, which allow the efficient evaluation of the performance of
quantized massive MIMO systems and provide insights into effective system
design.Comment: accepted in IEEE Transactions on Signal Processin
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