Ikuo Oka

Error probability for digital transmission over nonlinear channels with application to TCM

The computation of upper and lower bounds to error probability in digital transmission over nonlinear channels with a finite memory is considered. By using orthogonal Volterra series, the authors derive a canonical representation for discrete nonlinear systems, based on a linear convolutional code and a memoryless mapper. This representation shows that finite-memory, discrete nonlinear systems can be analyzed in much the same way as TCM (trellis-coded modulation) schemes. In particular, TCM over nonlinear channels can be analyzed. A technique is derived that expresses an upper bound to error probability based on the computation of the transfer of a state diagram with N branches, and whose branch labels are matrices rather than scalars. Some examples of its application are given. In particular, error bounds are derived for nonlinear TCM schemes and for TCM schemes operating on nonlinear channels. >

Experiment on Regional Broadband Network Using Free-Space-Optical Communication Systems

The transmission of a free-space optical (FSO) beam through the atmosphere is influenced by several factors: chief among them are weather conditions such as fog, rain, and snow. In the design of FSO communication systems, it is necessary to determine the weather dependence of the system and derive a relation between the weather parameters and performance of the FSO communication systems. From our experiments, we have established that the link-operating rate, which is an important parameter for overall FSO-communication-system performance, cannot be estimated using the cumulative-distribution probability of the visibility data. A technique of estimating short-term FSO-link performance characteristics is required. Using this approach, a method for approximating an FSO link-operating rate is proposed for the western Kanto area in Japan, where the link-performance deterioration is mostly a result of rain. The method is based on the analysis of short-term recorded rain intensity and visibility data. The estimated FSO link-operating rate is shown to have a good conformance with the experimental measured result.

A global message network employing low Earth-orbiting satellites

A global message communication network for low-density traffic, using satellites at low altitudes, is described. This network affords around-the-clock service to any part of the globe, including the polar regions. Such a network can accommodate static and mobile user terminals simultaneously. The oblate globe is modeled as a regular polyhedron with 12 facets for setting up the orbits. Satellites are positioned uniformly in low-altitude symmetrical orbits. The symmetrical orbits are those whose axes are symmetrical in the three-dimensional space. The authors study the coverage aspects of the 6-orbit scheme and the 10-orbit scheme, each with satellites deployed at an altitude of 5000 km. At this altitude, the terrestrial user terminals can access satellites at a grazing angle of 45 degrees . The method of access over the crosslinks is the slotted ALOHA scheme. For low-density traffic, the downlink and uplink throughput rates are estimated. Simulation results agree with these analytical estimates for low values of network offered load. >

A general orthogonal modulation model for software radios

In this letter, a general orthogonal-modulation model to develop new modulations and to identify some widely used modulation schemes is proposed. Based on this general framework, an optimum scheme for non-Gaussian channels under a given set of constraints can be derived. In software radios, the modulation should be changed by tracking this optimum scheme. The proposed model is based on orthonormal vectors, which are obtained by multidimensional rotations. Several widely used modulation schemes are renamed by their consecutive multidimensional rotation angles within the proposed framework. New modulation examples in continuous-wave interference and impulse interference channels are given to illustrate the corresponding local optima.

Towards real-time processing for application identification of encrypted traffic

Application identification in the middle is one of key challenges for network operators to manage application based traffic and policy controls in the Internet. However, it is becoming harder according to the increase of end-to-end encrypted traffic in which we hardly read application specific information from packets. We previously proposed a method to identify the application of traffic whenever the traffic is encrypted or not. Our method gives a significant accuracy of identification of encrypted traffic as high as the case when traffic is not encrypted, however, it requires an offline processing to obtain statistics of the whole of flows. A real-time identification is important, but the accuracy is a problem due to unstable information of flow statistics. In this paper we therefore propose an approach to improve the accuracy of identification when we identify the encrypted traffic in real-time. We first clarify the sufficient number of packets required for accurate identification, and then the method to infer the statistics to improve the accuracy even when the obtained number of packets is smaller than the one required. Experimental results have shown that the proposed approach achieves the high accuracy almost the same as in offline method.

Exact analysis of bit error probability for 4-state soft decision Viterbi decoding

Although Viterbi decoding is widely used in practical systems, only a few studies have been made for the exact error performance. We already proposed analytical technique for a 2-state soft decision Viterbi decoding. In this paper, this technique is extended to bit error probability for 4-state soft decision Viterbi decoding. This employs an iterative calculation of probability density function (PDF) of the path metrics.

Comparisons of Machine Learning Algorithms for Application Identification of Encrypted Traffic

Application identification assists network operators effectively on many tasks regarding network management such as controlling bandwidth or securing traffic from others. However, encryption is one of the factors to make application identification difficult, because it is so hard to infer the original (unencrypted) packets from encrypted packets. As a result, the accuracy of application identification is getting worse as the increase of encrypted traffic. In this paper, we propose a method to increase the accuracy of application identification whatever the traffic is encrypted or not. We propose EFM (Estimated Features Method) and investigate how three different supervised machine learning algorithms (Support Vector Machine, Naaive Bayes Kernel Estimation, and C4.5 decision tree) affect the accuracy of identification. Our results show that EFM using SVM is able to provide overall accuracy 97.2% for encrypted traffic.

Identification of Different TCP Versions Based on Cluster Analysis

When multiple flows using different versions of Transmission Control Protocol (TCP) exist together on a network, they seriously affect each other. One method to overcome this problem is to control such flows individually by identifying the TCP versions of each flow. Thus, for this process, it is necessary to identify online which TCP version is used in each flow. In this paper, we first focus on a method for controlling the congestion window (cwnd) in different versions of TCP. We find out characteristic values using this method and then propose a method to identify flow by using the characteristics. We show that any 2 out of 14 TCP versions that are implemented in Linux can be identified by using our proposed method.

Application identification from encrypted traffic based on characteristic changes by encryption

Application identification is paid much attention by network operators to manage application based traffic control in the Internet. However, encryption is one of the factors to make application identification difficult, because it is so hard to infer the original (unencrypted) packets from encrypted packets. Therefore the accuracy of application identification is getting worse as the increase of encrypted traffic. In this paper, the changes in traffic features due to encryption are analyzed, and two methods are developed that can be used with an existing method for identifying applications from encrypted traffic. Experimental results show that these methods improve identification accuracy up to 28.5% for encrypted traffic compared to existing methods. Moreover, identification using the best combination of flow features enables high accuracy with less computation due to the elimination of features that do not flow a Gaussian distribution and thus degrade accuracy.

Interference Immunity Effects in CPSK Systems with Hard-Limiting Transponders

Transmission characteristics are described for M-ary coherent phase-shift keyed (CPSK) systems with N-stage hard-limiting transponders where noise and multiple continuous wave (CW) interference sources are additively combined in each link. A general expression for the probability density function of the composite phase at the final link is derived; the overall error probability is then obtained from this general expression. Comparisons with N-cascaded linear amplifier systems clearly show the noise and interference immunity that result from the use of bandpass hard limiters (BPHLs). The BPHL systems error probability improvement versus interference sources is shown to be much larger than the improvement versus noise.