42638711
Hybrid DS/SFH Spread-Spectrum Multiple Access with Predetection Diversity and Coding for Indoor Radio
The authors derive close upper and lower bounds on the average bit error probability for hybrid direct-sequence/slow-frequency-hopped spread-spectrum multiple-access (DS/SFH-SSMA) systems with noncoherent DPSK demodulation, using predetection diversity (selection combining and equal gain combining) in conjunction with interleaved channel coding (Hamming
21925389
Downlink transmission of broadband OFCDM Systems-part II: effect of Doppler shift
The orthogonal frequency and code division multiplexing (OFCDM) system with 2-D spreading (time- and frequency-domain spreading) is becoming a promising candidate for future broadband wireless communication systems. OFCDM is more attractive than orthogonal frequency-division multiplexing (OFDM) both by introducing frequency-domain spreading for frequency diversity provision and time-domain spreading for flexible data rate provision. To provide high-speed mobile services, multicode transmission is employed in conjunction with OFCDM. In a Gaussian or flat-fading channel, multicode channels are orthogonal. However, in a realistic wireless channel, the orthogonality no longer maintains. Thus, multicode interference (MCI) is caused. This paper focuses on the investigation of the effect of Doppler shift on the downlink transmission of high-speed mobile OFCDM systems. A practical channel estimation algorithm based on a code-multiplexed pilot channel is employed to track the variations of fading channels. Hybrid MCI cancellation and minimum mean-square error (MMSE) detection proposed by the authors is employed as an efficient way to eliminate the MCI in the frequency domain. The system performance is analytically studied with imperfect channel estimation to show how it is affected by parameters such as the window size in the channel estimation, Doppler shift, the number of stages of the hybrid detection, the power ratio of pilot to data channels, spreading factor, and so on
16255139
Narrowband interference suppression in time-hopping impulse radio ultra-wideband communications
Ultra-wideband (UWB) technology has been considered an innovative solution for future short-range high-speed wireless communications. Interference suppression is important for the UWB devices to operate over spectrum occupied by narrowband systems. In this paper, the use of a notch filter in time-hopping impulse radio (TH-IR) for UWB communication is considered, where a Gaussian monopulse is employed with pulse position modulation. Lognormal channel fading is assumed, and a complete analytical framework is provided for the performance evaluation of using a transversal-type notch filter to reject narrowband interference (NBI). A closed-form expression of bit-error probability is derived, and the numerical results show that the use of a notch filter can improve the system performance significantly. Furthermore, a performance comparison between TH-IR and multicarrier code-division multiple-access (MC-CDMA) UWB systems is made under the conditions of the same transmit power, the same data rate, and the same bandwidth. It is shown that in the presence of NBI, the TH-IR system and MC-CDMA system achieve similar performance when both use a notch filter
7624272
PhyloMiner: A Tool for Evolutionary Data Analysis
Currently, phylogenetic tree techniques are being used in multiple areas, from tree of life problems to pathogen recognition to drug discovery. With all of these applications for phylogenetic tree techniques, methods are needed to exploit the knowledge modeled in phylogenetic trees more thoroughly. One such information point of interest is the behavior of frequent patterns in phylogenetic trees. While there are many techniques that look at maximal, consensus and super tree patterns, there are few techniques that look at frequent, but not maximal pattern. This demonstration paper presents PhyloMiner, a tool that automatically discovers frequent agreement subtrees from multiple phytogenies. It introduces this topic of frequent agreement subtrees and then concludes with describing the PhyloMiner tool that implements these concepts and is available freely on the World Wide Web
11520313
Linear Vertex Arboricity, Independence Number and Clique Cover Number
The linear vertex-arboricity of a graph G is defined to the minimum number of subsets into which the vertex-set G can be partitioned so that every subset induces a linear forest. In this paper, we give the upper and lower bounds for sum and product of linear vertex-arboricity with independence number and with clique cover number respectively. All of these bounds are sharp.
17168623
Traffic classification for application specific peering
Peer-to-Peer (P2P) applications [4], [6], [2], [3] have increased traffic significantly. We propose application specific peering that allows searches for a resource (using existing or modified P2P protocols) to be directed to a copy of resource on an ISP's network, using a novel technique that automatically classifies traffic (shown in Fig 1) as belonging to an ISP, its customers, peers, or their customers. We examined a large amount of traffic belonging to three popular P2P protocols and used a graph transformation to detect connected components. We partition traffic in each component into signaling and data sections based on request/response sizes of P2P protocols and extract high traffic volume (by bytes) entities by examining large connected components in the graph. We discuss the important components of our traffic classification system here. We analyzed router-level data from multiple Internet Gateway Routers (IGRs) across AT&T IP backbone using Cisco's NetFlow services. Note that statistics are from a subset of IGRs at some AT&T's peering links. They are not representative of overall traffic pattem on AT&T IP backbone. We examined DirectConnect[2], Gnutella[3], and FastTrack[4], extracting records that matched the default application ports (source or destina• tion, 411/412, 6346/6347, and 1214 (FastTrack) respectively), involving TCP traffic. Data was gathered over three separate months in 2001, each lasting 5-7 days. The number of netflow records varies from a low of 0.5M (DirectConnect) to a high
29712526
Three-sided side match finite-state vector quantization
Several low bit-rate still-image compression methods have been presented, such as SPHIT, hybrid VQ, and the Wu-Chen (see Proc. IEEE ICASSP, 1997) method. In particular, the image "Lena" can be compressed using less than 0.15 bpp at 31.4 dB or higher. These methods exercise the analysis techniques (wavelet or subband) before distributing the bit rate to each piece of an image, thus the dilemma between bit rate and distortion can be solved. In this paper, we propose a simple but comparable method that adopts the technique of side match VQ only. The side match vector quantization (SMVQ) is an effective VQ coding scheme at low bit-rate. The conventional side match (two-sided) VQ utilizes the codeword information of two neighboring blocks to predict the state codebook of an input vector. We propose a hierarchical three-sided side match finite-state vector quantization (HTSMVQ) method that can: (1) make the state codebook size as small as possible-the size is reduced to one if the prediction can perform perfectly; (2) improve the prediction quality for edge blocks; and (3) regularly refresh the codewords to alleviate the error propagation of side match. In the simulation results, the image "Lena" can be coded with a PSNR 34.682 dB at 0.25 bpp. It is better than SPIHT, EZW, FSSQ and hybrid VQ with 34.1, 33.17, 33.1, and 33.7 dB, respectively. At a bit rate lower than 0.15 bpp, only the enhanced version of EZW performs better than our method, at about 0.14 dB.
206541019
An online self-organizing neuro-fuzzy control for autonomous underwater vehicles
Controlling autonomous underwater vehicles (AUVs) in an uncertain and unstructured environment presents many challenging control problems. Model-based control strategies have been used with limited success. The paper presents an online self-organizing neuro-fuzzy control that serves as a better alternative control scheme in controlling AUVs. The proposed self-organizing neuro-fuzzy controller is a six-layer feedforward neural network that is capable of self-constructing and self-restructuring its internal node connectivity and learning the parameters of each node based on incoming training data. Computer simulations have been conducted to validate the performance of the proposed neuro-fuzzy controller and an experimental verification has been scheduled to verify if on ODIN, an autonomous underwater vehicle developed at the University of Hawaii.