662 research outputs found
A Mixed-ADC Receiver Architecture for Massive MIMO Systems
Motivated by the demand for energy-efficient communication solutions in the
next generation cellular network, a mixed-ADC receiver architecture for massive
multiple input multiple output (MIMO) systems is proposed, which differs from
previous works in that herein one-bit analog-to-digital converters (ADCs)
partially replace the conventionally assumed high-resolution ADCs. The
information-theoretic tool of generalized mutual information (GMI) is exploited
to analyze the achievable data rates of the proposed system architecture and an
array of analytical results of engineering interest are obtained. For
deterministic single input multiple output (SIMO) channels, a closed-form
expression of the GMI is derived, based on which the linear combiner is
optimized. Then, the asymptotic behaviors of the GMI in both low and high SNR
regimes are explored, and the analytical results suggest a plausible ADC
assignment scheme. Finally, the analytical framework is applied to the
multi-user access scenario, and the corresponding numerical results demonstrate
that the mixed system architecture with a relatively small number of
high-resolution ADCs is able to achieve a large fraction of the channel
capacity without output quantization.Comment: 5 pages, 5 figures, to appear in IEEE Information Theory Workshop
(ITW2015
On Low-Resolution ADCs in Practical 5G Millimeter-Wave Massive MIMO Systems
Nowadays, millimeter-wave (mmWave) massive multiple-input multiple-output
(MIMO) systems is a favorable candidate for the fifth generation (5G) cellular
systems. However, a key challenge is the high power consumption imposed by its
numerous radio frequency (RF) chains, which may be mitigated by opting for
low-resolution analog-to-digital converters (ADCs), whilst tolerating a
moderate performance loss. In this article, we discuss several important issues
based on the most recent research on mmWave massive MIMO systems relying on
low-resolution ADCs. We discuss the key transceiver design challenges including
channel estimation, signal detector, channel information feedback and transmit
precoding. Furthermore, we introduce a mixed-ADC architecture as an alternative
technique of improving the overall system performance. Finally, the associated
challenges and potential implementations of the practical 5G mmWave massive
MIMO system {with ADC quantizers} are discussed.Comment: to appear in IEEE Communications Magazin
Spectral Efficiency of Mixed-ADC Massive MIMO
We study the spectral efficiency (SE) of a mixed-ADC massive MIMO system in
which K single-antenna users communicate with a base station (BS) equipped with
M antennas connected to N high-resolution ADCs and M-N one-bit ADCs. This
architecture has been proposed as an approach for realizing massive MIMO
systems with reasonable power consumption. First, we investigate the
effectiveness of mixed-ADC architectures in overcoming the channel estimation
error caused by coarse quantization. For the channel estimation phase, we study
to what extent one can combat the SE loss by exploiting just N << M pairs of
high-resolution ADCs. We extend the round-robin training scheme for mixed-ADC
systems to include both high-resolution and one-bit quantized observations.
Then, we analyze the impact of the resulting channel estimation error in the
data detection phase. We consider random high-resolution ADC assignment and
also analyze a simple antenna selection scheme to increase the SE. Analytical
expressions are derived for the SE for maximum ratio combining (MRC) and
numerical results are presented for zero-forcing (ZF) detection. Performance
comparisons are made against systems with uniform ADC resolution and against
mixed-ADC systems without round-robin training to illustrate under what
conditions each approach provides the greatest benefit.Comment: To appear in IEEE Transactions on Signal Processin
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
Spectral Efficiency of One-Bit Sigma-Delta Massive MIMO
We examine the uplink spectral efficiency of a massive MIMO base station employing a one-bit Sigma-Delta ( \Sigma \Delta ) sampling scheme implemented in the spatial rather than the temporal domain. Using spatial rather than temporal oversampling, and feedback of the quantization error between adjacent antennas, the method shapes the spatial spectrum of the quantization noise away from an angular sector where the signals of interest are assumed to lie. It is shown that, while a direct Bussgang analysis of the \Sigma \Delta approach is not suitable, an alternative equivalent linear model can be formulated to facilitate an analysis of the system performance. The theoretical properties of the spatial quantization noise power spectrum are derived for the \Sigma \Delta array, as well as an expression for the spectral efficiency of maximum ratio combining (MRC). Simulations verify the theoretical results and illustrate the significant performance gains offered by the \Sigma \Delta approach for both MRC and zero-forcing receivers
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