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Communications and Mobile Computing (CMC), 2010 International Conference on

Date 12-14 April 2010

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Displaying Results 1 - 25 of 123
  • [Front cover - Vol 3]

    Page(s): C1
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  • [Title Page i - Volume 3]

    Page(s): i
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  • [Title page iii - Volume 3]

    Page(s): iii
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  • [Copyright notice - Volume 3]

    Page(s): iv
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  • Table of contents - Volume 3

    Page(s): v - xiii
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  • Preface - Volume 3

    Page(s): xiv
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  • Conference Committee - Volume 3

    Page(s): xv
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  • Technical Program Committee - Volume 3

    Page(s): xvi - xx
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  • list-reviewer

    Page(s): xxi - xxii
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  • Analysis and Improvements of the Constant Modulus Algorithm

    Page(s): 3 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (278 KB) |  | HTML iconHTML  

    In this paper, we study a widely used blind equalization algorithm-constant modulus algorithm (CMA), by introducing several methods which can improve its convergence or complexity performance. Moreover, we discuss the pros and cons of every method. View full abstract»

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  • Blind Identification and Digital Compensation of Memory Nonlinearities for Multiband Systems

    Page(s): 7 - 11
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (312 KB) |  | HTML iconHTML  

    Memory nonlinearities exist in electronic devices or transmission links. A blind identification method is proposed to estimate the Volterra inverse of memory nonlinearities for multiband system by minimizing the strong out-of-band spurs above the preset threshold based on domain transformation and spur classification. The inverse model is employed to recover the noisy sampled signal or improve the spurious-free dynamic range of memory nonlinear system by applying post-distortion or pre-distortion compensation. It can also used as multiband digital filter with varying intermediate frequency or bandwidth. In time-varying system, the filter coefficients can be updated adaptively by iterate search. The experiment results demonstrate the effectiveness. View full abstract»

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  • Blind Identification of Weak Nonlinear System Based on Normalized Kurtosis

    Page(s): 12 - 16
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (292 KB) |  | HTML iconHTML  

    This paper studies normalized kurtosis and its application in weak nonlinear system identification. According to the definition of normalized kurtosis and its properties, the memory effect and nonlinear order influences on normalized kurtosis are derived theoretically, and simulation results are given. Accordingly, this paper proposes a method in weak nonlinear system identification by using normalized kurtosis variation with varying system characteristics. Finally, this paper describes the potential advantage of proposed method. View full abstract»

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  • Blind Multiuser Detection Based on Nonlinear Power Estimation

    Page(s): 17 - 20
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (297 KB) |  | HTML iconHTML  

    A nonlinear parameter estimation algorithm is proposed to improve the blind multiuser detection based on power estimation (Kalman-P). In view of the estimation error of power of the desired user, the nonlinear mu-law compression function in communication theory is applied in our proposed algorithm. Computer simulations show that the new detection scheme has better performance in signal-to-interference ratio (SIR) than the Kalman-P. View full abstract»

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  • Fast Blind Channel Estimation Based on Discrete Hilbert Transform in OFDM System

    Page(s): 21 - 23
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (253 KB) |  | HTML iconHTML  

    We propose a novel blind channel estimation method for OFDM systems, the proposed method is based on the relation between amplitude and phase of analytic signal, and estimate the phase-frequency response basing on the estimation of amplitude-frequency response. In particular, the proposed method achieves accurate channel estimation and fast convergence. View full abstract»

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  • Improved Channel Optimized Image Coding Based on More Rational Source Model

    Page(s): 24 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (239 KB) |  | HTML iconHTML  

    Joint source channel coding (JSCC) has been proved a promising scheme for image communication in varying channel because of the properties of graceful degradation/improvement with limited coding delay and complexity, especially the combination of wavelet transform and JSCC is an easy way to achieve high-powered channel optimized image coding. For the purpose of attaining better performance, the source statistical characteristics including the intra-subband correlation of wavelet transform coefficients are considered, and then a Markov source modeling method capable of reserving and characterizing the correlation is developed, furthermore the utilization of the residual redundancy is also demonstrated within three referenced channel optimized image coders with fixed rate. Simulations show that the source model is more rational for wavelet transformed images and the improved channel optimized image coders utilizing the residual source redundancy performs better with no or negligible extra expense of bits and coding complexity. View full abstract»

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  • Iterative LDPC-Hadamard Code-Aided Carrier Phase Synchronization at Extremely Low SNR

    Page(s): 30 - 34
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (320 KB) |  | HTML iconHTML  

    In this paper, we consider a method of code-aided carrier phase synchronization at extremely low signal-to-noise values based on LDPC-Hadamard code. This system comprises a low-rate LDPC-Hadamard code that is close to Shannon limit at extremely low SNR values and an EM-based carrier phase synchronizer that makes use of the posterior probabilities of the data symbols, provided by the iterative decoder. Simulations show that the proposed synchronizer can achieve a bit-error-rate (BER) performance of 10-5 at Es/No=-10 dB, and has negligible BER performance degradation as compared to the ideally synchronized system. Through analysis and simulation, we show that our strategies are very effective at extremely low SNR values. View full abstract»

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  • Low Complexity Hybrid Algorithm for Crosstalk Cancellation

    Page(s): 35 - 39
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (252 KB) |  | HTML iconHTML  

    Crosstalk is the major limiting issue in VDSL2 system. A low complexity hybrid algorithm based on diagonal splitting precoder and iterative waterfilling algorithm is proposed in this paper. In this algorithm, crosstalk is mitigated by DS precoder firstly, and discrete iterative waterfilling is then chosen for power allocation. Computer simulation results based on measured data verify that the performance of the new method is almost the same as the optimal hybrid algorithm when the QoS requirements are met, but the new algorithm dramatically reduces the computational complexity. View full abstract»

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  • Method and Application of Image Clearness in Bad Weather

    Page(s): 40 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (538 KB) |  | HTML iconHTML  

    Aiming at degraded phenomena of images taken in bad weather, in this paper, a new entirely self - adapting method of image clearness is proposed on the basis of an atmospheric scattering model. First, under the gray distributing characteristics of a degraded image, we can get the optimal normal distribution. Second, the gray mean of the sky distribution can be obtained according to the optimal normal distribution. At the same time, to use the gray histogram segments this original image, and we can obtain the iso-depth neighborhoods. Last, employing the model lists equations, and the values of normalized radiance can be gotten. Thereby, the overcast of degraded images can be cleared. Experiments show the method can effectively improve degraded images in bad weather. View full abstract»

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  • New Bounds on the Average Error Probability of M-ary Orthogonal Signaling with a Large M on Rayleigh Fading Channels

    Page(s): 45 - 49
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (264 KB) |  | HTML iconHTML  

    The average symbol error probability (SEP) of M-ary orthogonal signaling with a large M is evaluated using new upper bounds. Based on the relation of the Gaussian Q-function and its square, new upper bounds on the SEP on the Rayleigh fading channels are developed, where single-integral forms are derived. Numerical results are presented to illustrate the value of the upper bound and validate the bound-based evaluation of receiver performance. View full abstract»

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  • New Classes of Binary Array Set with Zero-Correlation Zone

    Page(s): 50 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (284 KB) |  | HTML iconHTML  

    Based on the perfect binary array and the orthogonal matrix, new classes of binary array set with zero-correlation zone are presented. The set sizes of the proposed array sets are showed to be close to the theoretical upper bound. View full abstract»

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  • On Denoising of Spread Spectrum Communication for Wireless Location

    Page(s): 56 - 62
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (287 KB) |  | HTML iconHTML  

    Wireless location by spread spectrum communication can be severely corrupted by noise. Narrowband noise is the most effective interference that can make measurement signal undetected. In this paper, an adaptive wavelet filter is presented to suppress single and multiple narrowband interferences with additive white Gaussian noise that interferes with spread spectrum signals. The filter uses combinations of Gaussian wavelets with optimal time-frequency localization and computational efficiency for real-time denoising. The performance of the wavelet filter has been evaluated by experiments with spread spectrum communication system. Experimental results demonstrate that the proposed wavelet filter mitigates the narrowband noise in accordance with the corrupted frequency contents, and improves signal to noise ratio (SNR) for peak detection leading to higher accuracy of timing measurement for real-time wireless location. View full abstract»

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  • Plume Source Localizing in Different Distributions and Noise Types Based on WSN

    Page(s): 63 - 66
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (289 KB) |  | HTML iconHTML  

    Accidental gas leaks from unknown sites will cause the serious environmental pollution. One of the efficient methods to solve the problem is tracking and locating the plume source position. This paper presents a wireless sensor network installed with the gas sensor to on-line monitor the environment and estimate the location of a gas source based on the concentration readings at the wireless sensor nodes. Nonlinear Least Squares Method (NLS) was proposed for localization. The effect of the estimation error, with different distributions of the sensor nodes, different sensor number and different types of the back ground noises, is researched by simulations. The simulation results show that when the number of the nodes is more, the effect of the different distributions is not distinct. While the number of the nodes is less, the estimation error under the uniform distribution is more stable than under the random distribution. The suitable deployed method is discussed based on the simulation results. We also discussed the impact of the different noise types to the estimation error. View full abstract»

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  • QR Decomposition-Based Semi-Blind MIMO Channel Estimation

    Page(s): 67 - 71
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (593 KB) |  | HTML iconHTML  

    A novel algorithm is proposed and studied for QR decomposition-based scheme in the context of semi-blind Multi-Input Multi-Output (MIMO) channel estimation. Specifically, the flat-fading MIMO channel matrix H can be decomposed as a down-triangular matrix R and a unitary rotation matrix Q. The matrix R is estimated blindly from only received data by using Cholesky decomposition while the optimum rotation matrix Q is estimated exclusively from training samples based on OPML (Orthogonal Pilot ML Estimator) techniques. Significant estimation gains can be achieved by estimation of such optimum rotation matrices which are parameterized a fewer number of parameters. Furthermore, this semi-blind scheme is shown to be very efficient when the number of receive antennas is greater than the number of transmit antennas, with a low computational cost. Simulation results confirm that the presented estimation based on estimating only the Q matrix from training sequences can perform more efficiently than estimating H directly from the pilot data, and an additional about 4 dB in performance gain would result when exploit 1000 transmitted symbols over Rayleigh fading channels. View full abstract»

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  • Robust Novel EM-Based Direction-of-Arrival Estimation Technique for Wideband Source Signals

    Page(s): 72 - 76
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (206 KB) |  | HTML iconHTML  

    Direction-of-arrival (DOA) estimation for wideband source signals using near-field acoustic sensor networks has been drawing a lot of research interest recently. A wide variety of DOA estimation approaches are based on the predominant maximum-likelihood objective. In this paper, we would like to tackle with the DOA estimation problem based on the realistic assumption where the sources are corrupted by spatially non-white noises. We explore the respective limitations of two popular DOA methods for solving this problem, namely the SC-ML and AC-ML algorithms, and design a new expectation maximization (EM) algorithm. Through Monte Carlo simulations, it is demonstrated that our proposed EM algorithm outperforms the SC-ML and AC-ML methods in terms of the DOA accuracy. View full abstract»

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  • Signal Filtering Based on Wavelet Transform and its Application in Ground Penetrating Radar

    Page(s): 77 - 81
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (334 KB) |  | HTML iconHTML  

    Towards wavelet transforms part characters in time domain and frequency domain, a practical GPR signal processing method is proposed. Based on continuous wavelet transform, the main component of echo signal is extracted by energy analysis. Through scaled decomposition and frequency filtering, the disturbed component is eliminated. The SNR of reconstructed echo signal is improved. The experiments of real data indicate it improves the processing performance of underground target detecting than continuous wavelet transform. View full abstract»

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