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 $1\%$ less than the stationary point for four-cell systems, while the sum SE loss is $2\%$ 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