3,352 research outputs found
New summation inequalities and their applications to discrete-time delay systems
This paper provides new summation inequalities in both single and double
forms to be used in stability analysis of discrete-time systems with
time-varying delays. The potential capability of the newly derived inequalities
is demonstrated by establishing less conservative stability conditions for a
class of linear discrete-time systems with an interval time-varying delay in
the framework of linear matrix inequalities. The effectiveness and least
conservativeness of the derived stability conditions are shown by academic and
practical examples.Comment: 15 pages, 01 figur
Missing links of the protein Nα-terminal acetylation machinery in plants
Protein N-terminal acetylation (Nt-acetylation) is the transfer of acetyl group from acetyl
coenzyme A (Ac-CoA) to the alpha amino acid of a protein. Since it has been discovered
more than fifty years ago, Nt-acetylation is known to be one of the most common protein
modifications in eukaryotes, occurring on approximately 50-70% of yeast soluble protein
and about 80-90% of human protein. However, the exact biological role has remained
enigmatic for majority of affected proteins, and only for a small number of proteins, Ntacetyation
was linked to various features of protein such as localization, stability and
interaction. Nt-acetylation in yeast and in human is thoroughly investigated with the
identification of five (NatA-NatE) and six (NatA-NatF) Nα-acetyltransferase (NAT) types,
respectively. In contrast, the knowledge of Nt-acetylation in plants was vacant for many
years. The first Arabidopsis NAT, AtNatC was identified in 2003, and very recently three
more NATs (NatA, NatB and NatE) were described by Iwona Stephan. In this study, we
identified two NATs (NatD and NatF) that are still missing in plants. AtNatD/AtNaa40p is
conserved from yeast with respect to acetylation of protein histone H4. The lack of Nterminal
serine acetylation increases the overall positive charge of H4 N-tail which causes
the minor phenotypes observed in atnaa40 mutant. The acetylation of N-terminal serine of
histone H4 might also involve in DNA double-strand break response. Besides, the
subcellular localization to cytoplasm and nucleus suggests a lysine acetyltransferase
activity of AtNaa40p towards histones. AtNatF/AtNaa60 unusually localizes to plasma
membrane and to the tonoplast. The sensitivity of atnaa60 mutant to salt tress during
germination stage appears to be related to the localization, and indicating the involvement
of AtNaa60p in salt stress or osmotic stress response. Like hNaa60p, AtNaa60 is believed
to acetylate a large number of proteins according to the NBD-Cl fluorescent assay.
AtNaa60p acetylates methione and serine starting peptides in vitro.
In addition, numerous proteins are found N-terminally acetylated in chloroplasts, both
chloroplast-encoded and nuclear-encoded proteins. In silico study reveals eight putative
plastidic NATs of which seven localize to the chloroplasts when they are transiently
expressed with EYFP in Arabidopsis protoplasts. Three proteins (At2g39000, At1g24040
and At2g06025) acetylate plenty of Escherichia coli proteins, their substrate specificities
are strongly correlated to chlotoplast transit peptide (cTP) cleavage sites. Four other
proteins (At4g19984, At1g26220, At1g32070 and At4g28030) are possibly true NATs
since they possess the conserved Ac-CoA binding motif. Our results, together with other
studies on acetylation in chloroplast, propose the connection between Nt-acetylation of
chloroplastic proteins and drought stress
On the existence and exponential attractivity of a unique positive almost periodic solution to an impulsive hematopoiesis model with delays
In this paper, a generalized model of hematopoiesis with delays and impulses
is considered. By employing the contraction mapping principle and a novel type
of impulsive delay inequality, we prove the existence of a unique positive
almost periodic solution of the model. It is also proved that, under the
proposed conditions in this paper, the unique positive almost periodic solution
is globally exponentially attractive. A numerical example is given to
illustrate the effectiveness of the obtained results.Comment: Accepted for publication in AM
Large-Scale-Fading Decoding in Cellular Massive MIMO Systems with Spatially Correlated Channels
Massive multiple-input--multiple-output (MIMO) systems can suffer from
coherent intercell interference due to the phenomenon of pilot contamination.
This paper investigates a two-layer decoding method that mitigates both
coherent and non-coherent interference in multi-cell Massive MIMO. To this end,
each base station (BS) first estimates the channels to intra-cell users using
either minimum mean-squared error (MMSE) or element-wise MMSE (EW-MMSE)
estimation based on uplink pilots. The estimates are used for local decoding on
each BS followed by a second decoding layer where the BSs cooperate to mitigate
inter-cell interference. An uplink achievable spectral efficiency (SE)
expression is computed for arbitrary two-layer decoding schemes. A closed-form
expression is then obtained for correlated Rayleigh fading, maximum-ratio
combining, and the proposed large-scale fading decoding (LSFD) in the second
layer. We also formulate a sum SE maximization problem with both the data power
and LSFD vectors as optimization variables. Since this is an NP-hard problem,
we develop a low-complexity algorithm based on the weighted MMSE approach to
obtain a local optimum. The numerical results show that both data power control
and LSFD improves the sum SE performance over single-layer decoding multi-cell
Massive MIMO systems.Comment: 17 pages; 10 figures; Accepted for publication in IEEE Transactions
on Communication
Sum Spectral Efficiency Maximization in Massive MIMO Systems: Benefits from Deep Learning
This paper investigates the joint data and pilot power optimization for
maximum sum spectral efficiency (SE) in multi-cell Massive MIMO systems, which
is a non-convex problem. We first propose a new optimization algorithm,
inspired by the weighted minimum mean square error (MMSE) approach, to obtain a
stationary point in polynomial time. We then use this algorithm together with
deep learning to train a convolutional neural network to perform the joint data
and pilot power control in sub-millisecond runtime, making it suitable for
online optimization in real multi-cell Massive MIMO systems. The numerical
result demonstrates that the solution obtained by the neural network is
less than the stationary point for four-cell systems, while the sum SE loss is
in a nine-cell system.Comment: 4 figures, 1 table. Accepted by ICC 2019. arXiv admin note: text
overlap with arXiv:1901.0362
Joint Pilot Design and Uplink Power Allocation in Multi-Cell Massive MIMO Systems
This paper considers pilot design to mitigate pilot contamination and provide
good service for everyone in multi-cell Massive multiple input multiple output
(MIMO) systems. Instead of modeling the pilot design as a combinatorial
assignment problem, as in prior works, we express the pilot signals using a
pilot basis and treat the associated power coefficients as continuous
optimization variables. We compute a lower bound on the uplink capacity for
Rayleigh fading channels with maximum ratio detection that applies with
arbitrary pilot signals. We further formulate the max-min fairness problem
under power budget constraints, with the pilot signals and data powers as
optimization variables. Because this optimization problem is non-deterministic
polynomial-time hard due to signomial constraints, we then propose an algorithm
to obtain a local optimum with polynomial complexity. Our framework serves as a
benchmark for pilot design in scenarios with either ideal or non-ideal
hardware. Numerical results manifest that the proposed optimization algorithms
are close to the optimal solution obtained by exhaustive search for different
pilot assignments and the new pilot structure and optimization bring large
gains over the state-of-the-art suboptimal pilot design.Comment: 16 pages, 8 figures. Accepted to publish at IEEE Transactions on
Wireless Communication
Joint Power Allocation and User Association Optimization for Massive MIMO Systems
This paper investigates the joint power allocation and user association
problem in multi-cell Massive MIMO (multiple-input multiple-output) downlink
(DL) systems. The target is to minimize the total transmit power consumption
when each user is served by an optimized subset of the base stations (BSs),
using non-coherent joint transmission. We first derive a lower bound on the
ergodic spectral efficiency (SE), which is applicable for any channel
distribution and precoding scheme. Closed-form expressions are obtained for
Rayleigh fading channels with either maximum ratio transmission (MRT) or zero
forcing (ZF) precoding. From these bounds, we further formulate the DL power
minimization problems with fixed SE constraints for the users. These problems
are proved to be solvable as linear programs, giving the optimal power
allocation and BS-user association with low complexity. Furthermore, we
formulate a max-min fairness problem which maximizes the worst SE among the
users, and we show that it can be solved as a quasi-linear program. Simulations
manifest that the proposed methods provide good SE for the users using less
transmit power than in small-scale systems and the optimal user association can
effectively balance the load between BSs when needed. Even though our framework
allows the joint transmission from multiple BSs, there is an overwhelming
probability that only one BS is associated with each user at the optimal
solution.Comment: 16 pages, 12 figures, Accepted by IEEE Trans. Wireless Commu
- …