Abstract-Traffic delay is one of the important metrics used for evaluating network performance. Delay and delay variation characteristics of IP packets transferred over multi-section networks can be derived, estimated or composed from component distributions of IP package delay in each network section. Approximate methods are needed in the cases of unknown or complicated delay distribution functions, which are unavailable or unusable in practice. The ITU-T has proposed a method for estimating IP packet delay variation. One of noticeable factors affecting the estimation accuracy is the packet delay population quantile which has not been adequately considered. The objective of this paper is to examine the optimal range of quantiles used for estimating the IP packet delay variation in the NGN (Next Generation Network) core networks. The paper is composed from the following ideas. Firstly, several concepts and mathematical formulas related to delay metrics based on probability and statistics theory are defined. The approximate method of ITU-T for estimating the IP packet delay variation in a multi-section network is revised. Then, another method based on convolution for composing the empirical IPTD distribution functions is proposed for the same target as the first one. Secondly, a number of test cases are implemented to measure the IP packet delay on several sections of an NGN core network. Sample data are used for computing and estimating the IP packet delay variation for multi-section networks by two methods with certain hypotheses. Finally, these methods are compared and evaluated both theoretically and empirically in regards to the estimation accuracy versus quantiles of the IP packet transfer delay. The best range of quantiles is determined to ensure the accuracy of the estimation method applied for the NGN core network.
Physical security is a potentially promising research direction for the fifth-generation and beyond networks. This paper investigates the physical layer security of massive multiple-input multipleoutput (MIMO) spatially-uncorrelated Rician fading channels in time-division duplex mode. Relying on the fact that the propagation channels need to be estimated in practice to detect the desired signals in the uplink and construct the precoding vectors in the downlink, an active attack on the pilot training phase is potentially harmful to the wireless networks. We demonstrate how a jammer can attack in the training phase of Massive MIMO with spatially-uncorrelated Rician fading channels and show the scheme for detecting the presence of a jammer. Based on the fundamental properties of Massive MIMO communication, the network can treat the jamming effects as additive white Gaussian noise. A threshold to detect the existence of the active jammer is, therefore, computed in closed-form expression with a sufficiently large number of antennas at the base station. The key merit of our proposed method is that it only requires partial channel information and two training time slots to detect the jammer activity. Numerical results manifest the effectiveness of our proposed active jamming detection over various system parameter settings. Furthermore, the benefits of the dominant line-of-sight (LoS) components have been testified. In particular, the detection probability is improved by about 1.5 times with the presence of the LoS components, while the false-alarm probability gets improved by more than ten folds.
We prose anew technique for the design of linear phase 2-D FIR filter subject to frequency mask constraints, wich can handle filters large enough for practical applications. The designed 2-D filters will admit a fast digital implementation. Moreover, we generalize the trigonometric Markow-Lukacs theorem to enable the 2-D filter specifications to be expressed as semi-definite constrants. As a result, the 2-D filter design problem is then posed as semi-definite program (SDP). In addition, we exploited convex duality to derive equivalent SDP formulation of reduced constraints. Design of 2-D rectangular-shaped filters illustrating the advantages of our method is presented.
Broadband Internet traffic is transported over the next generation core internetworks, which are composed of several IP/MPLS/GE network sections and transport multi-services. In practice, IP packet delay is normally measured in each separated network section but not over a whole internetwork. It is proved in the paper that packet delay distribution of Internet traffic component in core network sections can be approximately expressed as a shifted gamma distribution. Moreover a new explicit mathematical model based on shifted gamma distribution has also been proposed to compose delay distribution of Internet traffic packet transported over a core internetwork from component ones in each network section. It is resulted from this model that Internet packet delay over an internetwork inherits distribution properties from that over component networks. Other properties and parameters relationship of the model such as additive property of shape and location parameters, the relation between distribution lower moments and parameters, the dependence of distribution on parameters variation are also exposed in the paper. The proposed model of IP packet delay distributions has a certain scientific significance and plays an important role in practical performance analysis, network planning, designing and traffic engineering for improving the quality of service
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.