2,839 research outputs found
Uplink Performance of Time-Reversal MRC in Massive MIMO Systems Subject to Phase Noise
Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an
excess of base station (BS) antennas (Massive MIMO) offer unprecedented
multiplexing gains and radiated energy efficiency. Oscillator phase noise is
introduced in the transmitter and receiver radio frequency chains and severely
degrades the performance of communication systems. We study the effect of
oscillator phase noise in frequency-selective Massive MIMO systems with
imperfect channel state information (CSI). In particular, we consider two
distinct operation modes, namely when the phase noise processes at the BS
antennas are identical (synchronous operation) and when they are independent
(non-synchronous operation). We analyze a linear and low-complexity
time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both
operation modes we derive a lower bound on the sum-capacity and we compare
their performance. Based on the derived achievable sum-rates, we show that with
the proposed receive processing an array gain is achievable. Due
to the phase noise drift the estimated effective channel becomes progressively
outdated. Therefore, phase noise effectively limits the length of the interval
used for data transmission and the number of scheduled users. The derived
achievable rates provide insights into the optimum choice of the data interval
length and the number of scheduled users.Comment: 13 pages, 6 figures, 2 tables, IEEE Transactions on Wireless
Communications (accepted
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
On the Outage Probability of the Full-Duplex Interference-Limited Relay Channel
In this paper, we study the performance, in terms of the asymptotic error
probability, of a user which communicates with a destination with the aid of a
full-duplex in-band relay. We consider that the network is
interference-limited, and interfering users are distributed as a Poisson point
process. In this case, the asymptotic error probability is upper bounded by the
outage probability (OP). We investigate the outage behavior for well-known
cooperative schemes, namely, decode-and-forward (DF) and compress-and-forward
(CF) considering fading and path loss. For DF we determine the exact OP and
develop upper bounds which are tight in typical operating conditions. Also, we
find the correlation coefficient between source and relay signals which
minimizes the OP when the density of interferers is small. For CF, the
achievable rates are determined by the spatial correlation of the
interferences, and a straightforward analysis isn't possible. To handle this
issue, we show the rate with correlated noises is at most one bit worse than
with uncorrelated noises, and thus find an upper bound on the performance of
CF. These results are useful to evaluate the performance and to optimize
relaying schemes in the context of full-duplex wireless networks.Comment: 30 pages, 4 figures. Final version. To appear in IEEE JSAC Special
Issue on Full-duplex Wireless Communications and Networks, 201
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
Hardware Impairments in Large-scale MISO Systems: Energy Efficiency, Estimation, and Capacity Limits
The use of large-scale antenna arrays has the potential to bring substantial
improvements in energy efficiency and/or spectral efficiency to future wireless
systems, due to the greatly improved spatial beamforming resolution. Recent
asymptotic results show that by increasing the number of antennas one can
achieve a large array gain and at the same time naturally decorrelate the user
channels; thus, the available energy can be focused very accurately at the
intended destinations without causing much inter-user interference. Since these
results rely on asymptotics, it is important to investigate whether the
conventional system models are still reasonable in the asymptotic regimes. This
paper analyzes the fundamental limits of large-scale multiple-input
single-output (MISO) communication systems using a generalized system model
that accounts for transceiver hardware impairments. As opposed to the case of
ideal hardware, we show that these practical impairments create finite ceilings
on the estimation accuracy and capacity of large-scale MISO systems.
Surprisingly, the performance is only limited by the hardware at the
single-antenna user terminal, while the impact of impairments at the
large-scale array vanishes asymptotically. Furthermore, we show that an
arbitrarily high energy efficiency can be achieved by reducing the power while
increasing the number of antennas.Comment: Published at International Conference on Digital Signal Processing
(DSP 2013), 6 pages, 5 figure
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