基于LMS算法改进Cupo相位抖动补偿方法

为了增加FIR-ALE(Finite Impulse Response-Adaptive Linear Enhancer)相位噪声补偿系统的补偿能力,本文基于LMS算法对Cupo的FIR-ALE系统进行改进,并对8PSK调制方式下的信号进行了Matlab仿真,通过对信号功率谱、误比特率以及星座图的分析,对比了两种方法.仿真结果表明,改进后的系统对于幅度为5°、频率为120 Hz的相位抖动,能够将抖动衰减25 dB左右;对于幅度为15°、频率为25 Hz的相位抖动,改进后的LMS系统能将抖动衰减35 dB左右.而且,随着相位抖动幅度的增大,改进的LMS方法的补偿能力同Cupo的FIR-ALE方法比较,性能逐渐提高.     

Towards evolvable Internet architecture-design constraints and models analysis

There is a general consensus about the success of Internet architecture in academia and industry. However, with the development of diversified application, the existing Internet architecture is facing more and more challenges in scalability, security, mobility and performance. A novel evolvable Internet architecture framework is proposed in this paper to meet the continuous changing application requirements. The basic idea of evolvability is relaxing the constraints that limit the development of the architecture while adhering to the core design principles of the Internet. Three important design constraints used to ensure the construction of the evolvable architecture, including the evolvability constraint, the economic adaptability constraint and the manageability constraint, are comprehensively described. We consider that the evolvable architecture can be developed from the network layer under these design constraints. What＇s more, we believe that the address system is the foundation of the Internet. Therefore, we propose a general address platform which provides a more open and efficient network environment for the research and development of the evolvable architecture.     

Interactive Evolutionary Multi-Objective Optimization Algorithm Using Cone Dominance

As the number of objectives increases, the performance of the Pareto dominance-based Evolutionary Multi-objective Optimization (EMO) algorithms such as NSGA-II, SPEA2 severely deteriorates due to the drastic increase in the Pareto-incomparable solutions. We propose a sorting method which classifies these incomparable solutions into several ordered classes by using the decision maker's (DM) preference information. This is accomplished by designing an interactive evolutionary algorithm and constructing convex cones. This method allows the DMs to drive the search process toward a preferred region of the Pareto optimal front. The performance of the proposed algorithm is assessed for two, three, and four-objective knapsack problems. The results demonstrate the algorithm's ability to converge to the most preferred point. The evaluation and comparison of the results indicate that the proposed approach gives better solutions than that of NSGA-II. In addition, the approach is more efficient compared to NSGA-II in terms of the number of generations required to reach the preferred point.     

A Semi-Supervised WLAN Indoor Localization Method Based on 1-Graph Algorithm

For indoor location estimation based on received signal strength (RSS) in wireless local area networks (WLAN), in order to reduce the influence of noise on the positioning accuracy, a large number of RSS should be collected in offline phase. Therefore, collecting training data with positioning information is time consuming which becomes the bottleneck of WLAN indoor localization. In this paper, the traditional semi-supervised learning method based on k-NN and ε-NN graph for reducing collection workload of offline phase are analyzed, and the result shows that the k-NN or ε-NN graph are sensitive to data noise, which limit the performance of semi-supervised learning WLAN indoor localization system. Aiming at the above problem, it proposes a 1-graph-algorithm-based semi-supervised learning (LG-SSL) indoor localization method in which the graph is built by 1-norm algorithm. In our system, it firstly labels the unlabeled data using LG-SSL and labeled data to build the Radio Map in offline training phase, and then uses LG-SSL to estimate user’s location in online phase. Extensive experimental results show that, benefit from the robustness to noise and sparsity of 1-graph, LG-SSL exhibits superior performance by effectively reducing the collection workload in offline phase and improving localization accuracy in online phase.     

一种高效安全的EPS AKA协议

针对4G认证与密钥协商协议(EPS AKA)中存在的安全问题,提出了一种高效安全的改进协议(ES-AKA).该协议不仅能够抵抗重定向攻击和重放攻击,同时消除了密钥K泄露的安全隐患.安全性和协议性能分析表明:在更高的安全性能下,该协议降低了服务网络的存储空间和归属网络的计算量,有效减少了认证过程的比特通信量.     

Virtual screening of eighteen million compounds against dengue virus: Combined molecular docking and molecular dynamics simulations study

Dengue virus is a major issue of tropical and sub-tropical regions. Dengue virus has been the cause behind the major alarming epidemics in the history with mass causalities from the decades. Unavailability of on-shelf drugs for the prevention of further proliferation of virus inside the human body results in immense number of deaths each year. This issue necessitates the design of novel anti-dengue drug. The protease enzyme pathway is the critical target for drug design due to its significance in the replication, survival and other cellular activities of dengue virus. Therefore, approximately eighteen million compounds from the ZINC database have been virtually screened against nonstructural protein 3 (NS3). The incremental construction algorithm of Glide docking program has been used with its features high throughput virtual screening (HTVS), standard precision (SP), extra precision (XP) and in combination of Prime module, induced fit docking (IFD) approach has also been applied. Five top-ranked compounds were then selected from the IFD results with better predicted binding energies with the catalytic triad residues (His51, Asp75, and Ser135) that may act as potential inhibitors for the underlying target protease enzyme. The top-ranked compounds ZINC95518765, ZINC44921800, ZINC71917414, ZINC39500661, ZINC36681949 have shown the predicted binding energies of −7.55, −7.36, −8.04, −8.41, −9.18 kcal/mol, respectively, forming binding interactions with three catalytically important amino acids. Top-docking poses of compounds are then used in molecular dynamics (MD) simulations. In computational studies, our proposed compounds confirm promising results against all the four serotypes of dengue virus, strengthening the opportunity of these compounds to work as potential on-shelf drugs against dengue virus. Further experimentation on the proposed compounds can result in development of strong inhibitors.     

Structure based virtual screening-driven identification of monastrol as a potent urease inhibitor

Virtual screening uses computer based methods to discover new ligands on the basis of biological structures. Among all virtual screening methods structure based docking has received considerable attention. In an attempt to identify new ligands as urease inhibitors, structure-based virtual screening (SBVS) of an in-house database of 10,000 organic compounds was carried out. The X-ray crystallographic structure of Bacillus pasteurii (BP) in complex with acetohydroxamic acid (PDB Code 4UBP) was used as a protein structure. As a starting point, ~10,000 compounds of our in-house database were analyzed to check redundancy and the compounds found repeated were removed from the database. Finally 6993 compounds were docked into the active site of BP urease using GOLD and MOE-Dock software. A remarkable feature of this study was the identification of monastrol, a well-known KSP inhibitor already in clinical trials, as a novel urease inhibitor. The hits identified were further evaluated by molecular docking and on examination of the affinity predictions, twenty-seven analogs of monastrol were synthesized by a multicomponent Biginelli reaction followed by their in vitro screening as urease inhibitors. Finally twelve compounds were identified as new urease inhibitors. The excellent in vitro activity suggested that these compounds may serve as viable lead compounds for the treatment of urease related problems.     

A cross-layer TCP enhancement in QoS-aware mobile ad hoc networks

With the increase of multimedia traffic over the Internet, current network protocols are largely concerned with the QoS requirements of delay-sensitive applications. In Mobile Ad-hoc Networks (MANETs), the majority of protocols developed to date provide QoS mechanisms by assigning high priority to delay-sensitive applications. While today’s Internet traffic is still dominated by TCP-based applications, the negative effects of the IEEE 802.11e service differentiation scheme on TCP performance in the presence of high priority traffic have not been adequately addressed in the literature. In this paper we first evaluate the performance of TCP in 802.11e MANETs when competing with high priority VoIP traffic. We then propose a novel TCP-friendly scheme, called IEDCA, to improve IEEE 802.11e EDCA mechanism. Our simulation-based performance study demonstrates that our proposed scheme IEDCA not only improves the performance of TCP significantly, it also facilitates the voice traffic transmission.     

Femtocell based green power consumption methods for mobile network

This paper presents the analytical models of power consumption in macrocell, microcell, picocell and femtocell based networks. Five case studies are presented in this paper where macrocells, microcells, picocells and femtocells are deployed based on the number of mobile subscribers present in a region, mobile user traffic in that region and the area of the region where cellular coverage has to be provided. A comparative study is performed between the power consumption by the base stations in each of these five cases and that of the only macrocell based network. The simulation results demonstrate that using each of these five strategies the power consumption by the base stations can be minimized than that of only macrocell based network. Based on the power consumption by the base stations in these five schemes, we have categorized the networks into five classes, A, B, C, D and E, each of which contains cells of different types to reduce power consumption to achieve green cellular network.