17 research outputs found
Soft metrics and their Performance Analysis for Optimal Data Detection in the Presence of Strong Oscillator Phase Noise
In this paper, we address the classical problem of maximum-likelihood (ML)
detection of data in the presence of random phase noise. We consider a system,
where the random phase noise affecting the received signal is first compensated
by a tracker/estimator. Then the phase error and its statistics are used for
deriving the ML detector. Specifically, we derive an ML detector based on a
Gaussian assumption for the phase error probability density function (PDF).
Further without making any assumptions on the phase error PDF, we show that the
actual ML detector can be reformulated as a weighted sum of central moments of
the phase error PDF. We present a simple approximation of this new ML rule
assuming that the phase error distribution is unknown. The ML detectors derived
are also the aposteriori probabilities of the transmitted symbols, and are
referred to as soft metrics. Then, using the detector developed based on
Gaussian phase error assumption, we derive the symbol error probability (SEP)
performance and error floor analytically for arbitrary constellations. Finally
we compare SEP performance of the various detectors/metrics in this work and
those from literature for different signal constellations, phase noise
scenarios and SNR values
Effect of Synchronizing Coordinated Base Stations on Phase Noise Estimation
In this paper, we study the problem of oscillator phase noise (PN) estimation
in coordinated multi-point (CoMP) transmission systems. Specifically, we
investigate the effect of phase synchronization between coordinated base
stations (BSs) on PN estimation at the user receiver (downlink channel). In
this respect, the Bayesian Cram\'er-Rao bound for PN estimation is derived
which is a function of the level of phase synchronization between the
coordinated BSs. Results show that quality of BS synchronization has a
significant effect on the PN estimation
On the Impact of Phase Noise in Communication Systems –- Performance Analysis and Algorithms
The mobile industry is preparing to scale up the network capacity by a factor of 1000x in order to cope with the staggering growth in mobile traffic. As a consequence, there is a tremendous pressure on the network infrastructure, where more cost-effective, flexible, high speed connectivity solutions are being sought for. In this regard, massive multiple-input multiple-output (MIMO) systems, and millimeter-wave communication systems are new physical layer technologies, which promise to facilitate the 1000 fold increase in network capacity. However, these technologies are extremely prone to hardware impairments like phase noise caused by noisy oscillators. Furthermore, wireless backhaul networks are an effective solution to transport data by using high-order signal constellations, which are also susceptible to phase noise impairments.
Analyzing the performance of wireless communication systems impaired by oscillator phase noise, and designing systems to operate efficiently in strong phase noise conditions are critical problems in communication theory. The criticality of these problems is accentuated with the growing interest in new physical layer technologies, and the deployment of wireless backhaul networks. This forms the main motivation for this thesis where we analyze the impact of phase noise on the system performance, and we also design algorithms in order to mitigate phase noise and its effects.
First, we address the problem of maximum a posteriori (MAP) detection of data in the presence of strong phase noise in single-antenna systems. This is achieved by designing a low-complexity joint phase-estimator data-detector. We show that the proposed method outperforms existing detectors, especially when high order signal constellations are used. Then, in order to further improve system performance, we consider the problem of optimizing signal constellations for transmission over channels impaired by phase noise. Specifically, we design signal constellations such that the error rate performance of the system is minimized, and the information rate of the system is maximized. We observe that these optimized constellations significantly improve the system performance, when compared to conventional constellations, and those proposed in the literature.
Next, we derive the MAP symbol detector for a MIMO system where each antenna at the transceiver has its own oscillator. We propose three suboptimal, low-complexity algorithms for approximately implementing the MAP symbol detector, which involve joint phase noise estimation and data detection. We observe that the proposed techniques significantly outperform the other algorithms in prior works. Finally, we study the impact of phase noise on the performance of a massive MIMO system, where we analyze both uplink and downlink performances. Based on rigorous analyses of the achievable rates, we provide interesting insights for the following question: how should oscillators be connected to the antennas at a base station, which employs a large number of antennas
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
Oscillator Phase Noise and Small-Scale Channel Fading in Higher Frequency Bands
This paper investigates the effect of oscillator phase noise and channel
variations due to fading on the performance of communication systems at
frequency bands higher than 10GHz. Phase noise and channel models are reviewed
and technology-dependent bounds on the phase noise quality of radio oscillators
are presented. Our study shows that, in general, both channel variations and
phase noise can have severe effects on the system performance at high
frequencies. Importantly, their relative severity depends on the application
scenario and system parameters such as center frequency and bandwidth. Channel
variations are seen to be more severe than phase noise when the relative
velocity between the transmitter and receiver is high. On the other hand,
performance degradation due to phase noise can be more severe when the center
frequency is increased and the bandwidth is kept a constant, or when
oscillators based on low power CMOS technology are used, as opposed to high
power GaN HEMT based oscillators.Comment: IEEE Global Telecommun. Conf. (GLOBECOM), Austin, TX, Dec. 201
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
Constellation Optimization in the Presence of Strong Phase Noise
In this paper, we address the problem of optimizing signal constellations for
strong phase noise. The problem is investigated by considering three
optimization formulations, which provide an analytical framework for
constellation design. In the first formulation, we seek to design
constellations that minimize the symbol error probability (SEP) for an
approximate ML detector in the presence of phase noise. In the second
formulation, we optimize constellations in terms of mutual information (MI) for
the effective discrete channel consisting of phase noise, additive white
Gaussian noise, and the approximate ML detector. To this end, we derive the MI
of this discrete channel. Finally, we optimize constellations in terms of the
MI for the phase noise channel. We give two analytical characterizations of the
MI of this channel, which are shown to be accurate for a wide range of
signal-to-noise ratios and phase noise variances. For each formulation, we
present a detailed analysis of the optimal constellations and their performance
in the presence of strong phase noise. We show that the optimal constellations
significantly outperform conventional constellations and those proposed in the
literature in terms of SEP, error floors, and MI.Comment: 10 page, 10 figures, Accepted to IEEE Trans. Commu
Calculation of the Performance of Communication Systems from Measured Oscillator Phase Noise
Oscillator phase noise (PN) is one of the major problems that affect the
performance of communication systems. In this paper, a direct connection
between oscillator measurements, in terms of measured single-side band PN
spectrum, and the optimal communication system performance, in terms of the
resulting error vector magnitude (EVM) due to PN, is mathematically derived and
analyzed. First, a statistical model of the PN, considering the effect of white
and colored noise sources, is derived. Then, we utilize this model to derive
the modified Bayesian Cramer-Rao bound on PN estimation, and use it to find an
EVM bound for the system performance. Based on our analysis, it is found that
the influence from different noise regions strongly depends on the
communication bandwidth, i.e., the symbol rate. For high symbol rate
communication systems, cumulative PN that appears near carrier is of relatively
low importance compared to the white PN far from carrier. Our results also show
that 1/f^3 noise is more predictable compared to 1/f^2 noise and in a fair
comparison it affects the performance less.Comment: Accepted in IEEE Transactions on Circuits and Systems-I: Regular
Paper