14 research outputs found
Capacity of SIMO and MISO Phase-Noise Channels with Common/Separate Oscillators
In multiple antenna systems, phase noise due to instabilities of the
radio-frequency (RF) oscillators, acts differently depending on whether the RF
circuitries connected to each antenna are driven by separate (independent)
local oscillators (SLO) or by a common local oscillator (CLO). In this paper,
we investigate the high-SNR capacity of single-input multiple-output (SIMO) and
multiple-output single-input (MISO) phase-noise channels for both the CLO and
the SLO configurations.
Our results show that the first-order term in the high-SNR capacity expansion
is the same for all scenarios (SIMO/MISO and SLO/CLO), and equal to , where stands for the SNR. On the contrary, the second-order
term, which we refer to as phase-noise number, turns out to be
scenario-dependent. For the SIMO case, the SLO configuration provides a
diversity gain, resulting in a larger phase-noise number than for the CLO
configuration. For the case of Wiener phase noise, a diversity gain of at least
can be achieved, where is the number of receive antennas. For
the MISO, the CLO configuration yields a higher phase-noise number than the SLO
configuration. This is because with the CLO configuration one can obtain a
coherent-combining gain through maximum ratio transmission (a.k.a. conjugate
beamforming). This gain is unattainable with the SLO configuration.Comment: IEEE Transactions on Communication
Receiver Algorithm based on Differential Signaling for SIMO Phase Noise Channels with Common and Separate Oscillator Configurations
In this paper, a receiver algorithm consisting of differential transmission
and a two-stage detection for a single-input multiple-output (SIMO) phase-noise
channels is studied. Specifically, the phases of the QAM modulated data symbols
are manipulated before transmission in order to make them more immune to the
random rotational effects of phase noise. At the receiver, a two-stage detector
is implemented, which first detects the amplitude of the transmitted symbols
from a nonlinear combination of the received signal amplitudes. Then in the
second stage, the detector performs phase detection. The studied signaling
method does not require transmission of any known symbols that act as pilots.
Furthermore, no phase noise estimator (or a tracker) is needed at the receiver
to compensate the effect of phase noise. This considerably reduces the
complexity of the receiver structure. Moreover, it is observed that the studied
algorithm can be used for the setups where a common local oscillator or
separate independent oscillators drive the radio-frequency circuitries
connected to each antenna. Due to the differential encoding/decoding of the
phase, weighted averaging can be employed at a multi-antenna receiver, allowing
for phase noise suppression to leverage the large number of antennas. Hence, we
observe that the performance improves by increasing the number of antennas,
especially in the separate oscillator case. Further increasing the number of
receive antennas results in a performance error floor, which is a function of
the quality of the oscillator at the transmitter.Comment: IEEE GLOBECOM 201
Distributed Massive MIMO via all-Digital Radio Over Fiber
A crucial challenge in the implementation of distributed massive multiple-input multiple-output (MIMO) architectures is to provide phase coherence while, at the same time, limit the complexity of the remote-radio heads (RRHs), which is important for cost-efficient scalability. To address this challenge, we present in this paper a phase-coherent distributed MIMO architecture, based on off-the-shelf, low-cost components. In the proposed architecture, up- and down-conversion are carried out at the central unit (CU). The RRHs are connected to the CU by means of optical fibers carrying oversampled radio-frequency (RF) 1-bit signals. In the downlink, the 1-bit signal is generated via sigma-delta modulation. At the RRH, the RF signal is recovered from the 1-bit signal through a bandpass filter and a power amplifier, and then fed to an antenna. In the uplink, the 1-bit signal is generated by a comparator whose inputs are the low-noise-amplified received RF signal and a suitably designed dither signal. The performance of the proposed architecture is evaluated with satisfactory results both via simulation and measurements from a testbed
On the Capacity of the Wiener Phase-Noise Channel: Bounds and Capacity Achieving Distributions
In this paper, the capacity of the additive white Gaussian noise (AWGN)
channel, affected by time-varying Wiener phase noise is investigated. Tight
upper and lower bounds on the capacity of this channel are developed. The upper
bound is obtained by using the duality approach, and considering a specific
distribution over the output of the channel. In order to lower-bound the
capacity, first a family of capacity-achieving input distributions is found by
solving a functional optimization of the channel mutual information. Then,
lower bounds on the capacity are obtained by drawing samples from the proposed
distributions through Monte-Carlo simulations. The proposed capacity-achieving
input distributions are circularly symmetric, non-Gaussian, and the input
amplitudes are correlated over time. The evaluated capacity bounds are tight
for a wide range of signal-to-noise-ratio (SNR) values, and thus they can be
used to quantify the capacity. Specifically, the bounds follow the well-known
AWGN capacity curve at low SNR, while at high SNR, they coincide with the
high-SNR capacity result available in the literature for the phase-noise
channel.Comment: IEEE Transactions on Communications, 201
Massive MU-MIMO-OFDM Uplink with Hardware Impairments: Modeling and Analysis
We study the impact of hardware impairments at the base station (BS) of an
orthogonal frequency-division multiplexing (OFDM)-based massive multiuser (MU)
multiple-input multiple-output (MIMO) uplink system. We leverage Bussgang's
theorem to develop accurate models for the distortions caused by nonlinear
low-noise amplifiers, local oscillators with phase noise, and oversampling
finite-resolution analog-to-digital converters. By combining the individual
effects of these hardware models, we obtain a composite model for the BS-side
distortion caused by nonideal hardware that takes into account its inherent
correlation in time, frequency, and across antennas. We use this composite
model to analyze the impact of BS-side hardware impairments on the performance
of realistic massive MU-MIMO-OFDM uplink systems
ML Detection in Phase Noise Impaired SIMO Channels with Uplink Training
The problem of maximum likelihood (ML) detection in training-assisted
single-input multiple-output (SIMO) systems with phase noise impairments is
studied for two different scenarios, i.e. the case when the channel is
deterministic and known (constant channel) and the case when the channel is
stochastic and unknown (fading channel). Further, two different operations with
respect to the phase noise sources are considered, namely, the case of
identical phase noise sources and the case of independent phase noise sources
over the antennas. In all scenarios the optimal detector is derived for a very
general parametrization of the phase noise distribution. Further, a high
signal-to-noise-ratio (SNR) analysis is performed to show that
symbol-error-rate (SER) floors appear in all cases. The SER floor in the case
of identical phase noise sources (for both constant and fading channels) is
independent of the number of antenna elements. In contrast, the SER floor in
the case of independent phase noise sources is reduced when increasing the
number of antenna elements (for both constant and fading channels). Finally,
the system model is extended to multiple data channel uses and it is shown that
the conclusions are valid for these setups, as well.Comment: (To appear in IEEE Transactions on Communications, 2015), Contains
additional material (Appendix B. T-slot Detectors