432 research outputs found
Frequency Synchronization for Uplink Massive MIMO Systems
In this paper, we propose a frequency synchronization scheme for multiuser
orthogonal frequency division multiplexing (OFDM) uplink with a large-scale
uniform linear array (ULA) at base station (BS) by exploiting the angle
information of users. Considering that the incident signal at BS from each user
can be restricted within a certain angular spread, the proposed scheme could
perform carrier frequency offset (CFO) estimation for each user individually
through a \textit{joint spatial-frequency alignment} procedure and can be
completed efficiently with the aided of fast Fourier transform (FFT). A
multi-branch receive beamforming is further designed to yield an equivalent
single user transmission model for which the conventional single-user channel
estimation and data detection can be carried out. To make the study complete,
the theoretical performance analysis of the CFO estimation is also conducted.
We further develop a user grouping scheme to deal with the unexpected scenarios
that some users may not be separated well from the spatial domain. Finally,
various numerical results are provided to verify the proposed studies
Beamspace Channel Estimation in mmWave Systems via Cosparse Image Reconstruction Technique
This paper considers the beamspace channel estimation problem in 3D lens
antenna array under a millimeter-wave communication system. We analyze the
focusing capability of the 3D lens antenna array and the sparsity of the
beamspace channel response matrix. Considering the analysis, we observe that
the channel matrix can be treated as a 2D natural image; that is, the channel
is sparse, and the changes between adjacent elements are subtle. Thus, for the
channel estimation, we incorporate an image reconstruction technique called
sparse non-informative parameter estimator-based cosparse analysis AMP for
imaging (SCAMPI) algorithm. The SCAMPI algorithm is faster and more accurate
than earlier algorithms such as orthogonal matching pursuit and support
detection algorithms. To further improve the SCAMPI algorithm, we model the
channel distribution as a generic Gaussian mixture (GM) probability and embed
the expectation maximization learning algorithm into the SCAMPI algorithm to
learn the parameters in the GM probability. We show that the GM probability
outperforms the common uniform distribution used in image reconstruction. We
also propose a phase-shifter-reduced selection network structure to decrease
the power consumption of the system and prove that the SCAMPI algorithm is
robust even if the number of phase shifters is reduced by 10%
Could robots be regarded as humans in future?
With the overwhelming advances in Artificial Intelligence (AI), brain science
and neuroscience, robots are developing towards a direction of much more
human-like and human-friendly. We can't help but wonder whether robots could be
regarded as humans in future? In this article, we propose a novel perspective
to analyze the essential difference between humans and robots, that is based on
their respective living spaces, particularly the independent and intrinsic
thinking space. We finally come to the conclusion that, only when robots own
the independent and intrinsic thinking space as humans, could they have the
prerequisites to be regarded as humans.Comment: 4 pages, 1 tabl
Robust Beamforming for Physical Layer Security in BDMA Massive MIMO
In this paper, we design robust beamforming to guarantee the physical layer
security for a multiuser beam division multiple access (BDMA) massive
multiple-input multiple-output (MIMO) system, when the channel estimation
errors are taken into consideration. With the aid of artificial noise (AN), the
proposed design are formulated as minimizing the transmit power of the base
station (BS), while providing legal users and the eavesdropper (Eve) with
different signal-to-interference-plus-noise ratio (SINR). It is strictly proved
that, under BDMA massive MIMO scheme, the initial non-convex optimization can
be equivalently converted to a convex semi-definite programming (SDP) problem
and the optimal rank-one beamforming solutions can be guaranteed. In stead of
directly resorting to the convex tool, we make one step further by deriving the
optimal beamforming direction and the optimal beamforming power allocation in
closed-form, which greatly reduces the computational complexity and makes the
proposed design practical for real world applications. Simulation results are
then provided to verify the efficiency of the proposed algorithm
Channel Estimation for TDD/FDD Massive MIMO Systems with Channel Covariance Computing
In this paper, we propose a new channel estimation scheme for TDD/FDD massive
MIMO systems by reconstructing uplink/downlink channel covariance matrices
(CCMs) with the aid of array signal processing techniques. Specifically, the
angle information and power angular spectrum (PAS) of each multi-path channel
is extracted from the instantaneous uplink channel state information (CSI).
Then, the uplink CCM is reconstructed and can be used to improve the uplink
channel estimation without any additional training cost. In virtue of angle
reciprocity as well as PAS reciprocity between uplink and downlink channels,
the downlink CCM could also be inferred with a similar approach even for FDD
massive MIMO systems. Then, the downlink instantaneous CSI can be obtained by
training towards the dominant eigen-directions of each user. The proposed
strategy is applicable for any kind of PAS distributions and array geometries.
Numerical results are provided to demonstrate the superiority of the proposed
methods over the existing ones.Comment: 30 pages, 11 figure
Spatial- and Frequency-Wideband Effects in Millimeter-Wave Massive MIMO Systems
When there are a large number of antennas in massive MIMO systems, the
transmitted wideband signal will be sensitive to the physical propagation delay
of electromagnetic waves across the large array aperture, which is called the
spatial-wideband effect. In this scenario, transceiver design is different from
most of the existing works, which presume that the bandwidth of the transmitted
signals is not that wide, ignore the spatial-wideband effect, and only address
the frequency selectivity. In this paper, we investigate spatial- and
frequency-wideband effects, called dual-wideband effects, in massive MIMO
systems from array signal processing point of view. Taking mmWave-band
communications as an example, we describe the transmission process to address
the dual-wideband effects. By exploiting the channel sparsity in the angle
domain and the delay domain, we develop the efficient uplink and downlink
channel estimation strategies that require much less amount of training
overhead and cause no pilot contamination. Thanks to the array signal
processing techniques, the proposed channel estimation is suitable for both TDD
and FDD massive MIMO systems. Numerical examples demonstrate that the proposed
transmission design for massive MIMO systems can effectively deal with the
dual-wideband effects.Comment: 13 pages, 10 figures. Index terms: Massive MIMO, mmWave, array signal
processing, wideband, spatial-wideband, beam squint, angle reciprocity, delay
reciprocity. Submitted to IEEE Transactions on Signal Processin
Time Varying Channel Tracking with Spatial and Temporal BEM for Massive MIMO Systems
In this paper, we propose a channel tracking method for massive multi-input
and multi-output systems under both time-varying and spatial-varying
circumstance. Exploiting the characteristics of massive antenna array, a
spatial-temporal basis expansion model is designed to reduce the effective
dimensions of up-link and down-link channel, which decomposes channel state
information into the time-varying spatial information and gain information. We
firstly model the users movements as a one-order unknown Markov process, which
is blindly learned by the expectation and maximization (EM) approach. Then, the
up-link time varying spatial information can be blindly tracked by Taylor
series expansion of the steering vector, while the rest up-link channel gain
information can be trained by only a few pilot symbols. Due to angle
reciprocity (spatial reciprocity), the spatial information of the down-link
channel can be immediately obtained from the up-link counterpart, which greatly
reduces the complexity of down-link channel tracking. Various numerical results
are provided to demonstrate the effectiveness of the proposed method
Beam Tracking for UAV Mounted SatCom on-the-Move with Massive Antenna Array
Unmanned aerial vehicle (UAV)-satellite communication has drawn dramatic
attention for its potential to build the integrated space-air-ground network
and the seamless wide-area coverage. The key challenge to UAV-satellite
communication is its unstable beam pointing due to the UAV navigation, which is
a typical SatCom on-the-move scenario. In this paper, we propose a blind beam
tracking approach for Ka-band UAVsatellite communication system, where UAV is
equipped with a large-scale antenna array. The effects of UAV navigation are
firstly released through the mechanical adjustment, which could approximately
point the beam towards the target satellite through beam stabilization and
dynamic isolation. Specially, the attitude information can be realtimely
derived from data fusion of lowcost sensors. Then, the precision of the beam
pointing is blindly refined through electrically adjusting the weight of the
massive antennas, where an array structure based simultaneous perturbation
algorithm is designed. Simulation results are provided to demonstrate the
superiority of the proposed method over the existing ones
Enhancing Physical Layer Security in Dual-Hop Multiuser Transmission
In this paper, we consider the Physical Layer Security(PLS) problem in
orthogonal frequency division multiple access (OFDMA) based dual-hop system
which consists of multiple users, multiple amplify and forward relays, and an
eavesdropper. The aim is to enhance PLS of the entire system by maximizing sum
secrecy rate of secret users through optimal resource allocation under various
practical constraints. Specifically, the sub-carrier allocation to different
users, the relay assignments, and the power loading over different sub-carriers
at transmitting nodes are optimized. The joint optimization problem is modeled
as a mixed binary integer programming problem subject to exclusive sub-carrier
allocation and separate power budget constraints at each node. A joint
optimization solution is obtained through Lagrangian dual decomposition where
KKT conditions are exploited to find the optimal power allocation at base
station. Further, to reduce the complexity, a sub-optimal scheme is presented
where the optimal power allocation is derived under fixed sub-carrier-relay
assignment. Simulation results are also provided to validate the performance of
proposed schemes
Anisotropic Superconductivity of Ca1-xLaxFeAs2 (x ~ 0.18) Single Crystal
Anisotropic superconducting properties including the upper critical field
Hc2, thermal activation energy U0, and critical current density Jc are
systematically studied in a large Ca1-xLaxFeAs2 single crystal (x ~ 0.18). The
obtained Hc2 bears a moderate anisotropy gamma of approximately 2-4.2, located
between those of '122' Ba1-xKxFe2As2 (1 < gamma < 2) and '1111' NdFeAsO1-xFx (5
< gamma < 9.2). Both the magnitude of U0 and its field dependence are very
similar to those of NdFeAsO1-xFx, also indicating anisotropic
superconductivity. Moreover, high and anisotropic Jc's exceeding 10^5 A/cm2
have been calculated from the magnetization hysteresis loops, indicating the
existence of strong bulk-dominated pinning in the present superconducting
material.Comment: Appl. Phys. Express (2014
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