This paper studies the Rake receiver for the direct sequence ultra-wideband (DS-UWB) system. SRake receiver and PRake receiver are employed to receive the UWB signal in the indoor dense multi-path UWB channel (IEEE **...
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ISBN:
(纸本)9781479948116
This paper studies the Rake receiver for the direct sequence ultra-wideband (DS-UWB) system. SRake receiver and PRake receiver are employed to receive the UWB signal in the indoor dense multi-path UWB channel (IEEE ***3a). In order to study how to improve the performance of receivers, different order of Gaussian pulses are discussed firstly. And then, the ml estimation algorithm is used to get the channel timing delay and the weighted value of the Rake receiver. The effect of the performance influenced by different assisted-pilot numbers is discussed with different SNR. Finally, the influence of different branch numbers of the SRake receiver and PRake receiver are given. The simulation results show that the fifth order Gaussian pulse could achieve better performance for the SRake considering the limits of FCC, while the waveforms will not affect the performance greatly for the PRAke receiver. Furthermore, more numbers of assisted-pilot and branches of receiver will improve the system performance. All of these results provide a basis for Rake receiver design of DS-UWB system.
This paper studies the Rake receiver for the direct sequence ultra-wideband(DS-UWB) *** receiver and PRake receiver are employed to receive the UWB signal in the indoor dense multi-path UWB channel(IEEE ***3a).In orde...
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ISBN:
(纸本)9781479948109
This paper studies the Rake receiver for the direct sequence ultra-wideband(DS-UWB) *** receiver and PRake receiver are employed to receive the UWB signal in the indoor dense multi-path UWB channel(IEEE ***3a).In order to study how to improve the performance of receivers,different order of Gaussian pulses are discussed *** then,the ml estimation algorithm is used to get the channel timing delay and the weighted value of the Rake *** effect of the performance influenced by different assisted-pilot numbers is discussed with different ***,the influence of different branch numbers of the SRake receiver and PRake receiver are *** simulation results show that the fifth order Gaussian pulse could achieve better performance for the SRake considering the limits of FCC,while the waveforms will not affect the performance greatly for the PRAke ***,more numbers of assisted-pilot and branches of receiver will improve the system *** of these results provide a basis for Rake receiver design of DS-UWB system.
The nonlinear distortion caused by power amplifier (PA) nonlinearity distorts the constellation and degrades the bit error rate (BER) performance of 60 GHz millimeter wave (mmWave) wireless local area network (WLAN) e...
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ISBN:
(纸本)9781467304375;9781467304368
The nonlinear distortion caused by power amplifier (PA) nonlinearity distorts the constellation and degrades the bit error rate (BER) performance of 60 GHz millimeter wave (mmWave) wireless local area network (WLAN) easily, due to the huge bandwidth and high equivalent isotropic radiated power (EIRP), especially for quadrature amplitude modulation (QAM) signals. This paper aims at data-aided (DA) distorted constellation (DC) estimation and demodulation to resist PA nonlinearity. A maximum likelihood (ml) estimation algorithm is proposed, and the corresponding Cramer-Rao lower bounds (CRLBs) are computed. Furthermore, we implement the demodulation based on the DC rather than the standard constellation (SC). Simulation results indicate that the means of the estimated parameters are unbiased and the mean square errors (MSEs) approach the CRLBs. Meanwhile, the proposed DC demodulation with PA nonlinearity achieves BER performance close to the ideal PA case, and evidently outperforms the traditional SC demodulation especially in the high-code-rate or uncoded case.
A reduced complexity Maximum-Likelihood (ml) detection algorithm is proposed for the multiple-input multiple-output orthogonal frequency division multiple (MIMO-OFDM) systems. The proposed detection algorithm combines...
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ISBN:
(纸本)9781612846835;9781612846828
A reduced complexity Maximum-Likelihood (ml) detection algorithm is proposed for the multiple-input multiple-output orthogonal frequency division multiple (MIMO-OFDM) systems. The proposed detection algorithm combines the ml algorithm and the QR algorithm. In the detection process, the first T signals are detected by the ml algorithm and the last Nt-T signals are detected by QR algorithm where T is a parameter and Nt is the number of transmitter antennas. From the simulation results, compared with the traditional ml algorithm, the computational complexity of the proposed algorithm with 4 transmitter antennas, 4 receiver antennas and T=3 is reduced by 95% at the expense of about 1.3dB signal-to-noise-ratio (SNR) degradation for bit error rate (BER) at 10(-3). Therefore, the proposed detection algorithm can be used in the practical MIMO-OFDM systems requiring very low complexity.
With the rapid development of Internet, many network applications (e.g., P2P) use dynamic ports and encryption technology, which makes the traditional port and payload-based classification methods ineffective. Hence, ...
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With the rapid development of Internet, many network applications (e.g., P2P) use dynamic ports and encryption technology, which makes the traditional port and payload-based classification methods ineffective. Hence, it is important and necessary to find the more effective ones. Currently the machine learning (ml) techniques provide a promising alternative one for IP traffic classification. In this work, we use the ml-based classification method to identify the classes of the unknown flows using the payload-independent statistical features such as packet-length and arrival-interval. In order to improve the efficiency of the classification methods, the feature reduction techniques are further adopted to refine the selected features for attaining a best group of features. Finally we compare and evaluate the ml classification algorithms based on the BRASIL data source in terms of the three metrics such as overall accuracy, average precision and average recall. Our experiments show that the decision-tree algorithm is the best ml one for IP traffic classification and is able to construct the real-time classification system.
A novel DWPM (Discrete Wavelet Packet Modulation) system with blind channel identification based on Maximum Likelihood (ml) algorithm is studied for multipath fading channel. The Channel State Information (CSI) is obt...
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A novel DWPM (Discrete Wavelet Packet Modulation) system with blind channel identification based on Maximum Likelihood (ml) algorithm is studied for multipath fading channel. The Channel State Information (CSI) is obtained with blind channel identification method and inter-symbol interference is suppressed by H over-bar matrix based on ZF (Zero Forcing) algorithm. Finally, the demodulated symbols are detected by ml algorithm. The performance of the system under the multipath fading channel is analyzed by simulation. The simulation results show the performance of the system is better than that of the traditional OFDM system.
The authors show that the conditional entropy maximisation algorithm is a generalised version of the maximum likelihood algorithm for positron emission tomography (PET). Promising properties of the conditional entropy...
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The authors show that the conditional entropy maximisation algorithm is a generalised version of the maximum likelihood algorithm for positron emission tomography (PET). Promising properties of the conditional entropy maximisation algorithm are as follows: an assumption is made that the entropy of the information content of the data should be maximised;it is a consistent way of selecting an image from the very many images that fit the measurement data;this approach takes care of the positivity of the reconstructed image pixels, since entropy does not exist for negative image pixel values;and inclusion of prior distribution knowledge in the reconstruction process is possible. Simulated experiments performed on a PET system have shown that the quality of the reconstructed image using the entropy maximisation method is good. A Gibbs distribution is used to incorporate prior knowledge into the reconstruction process. The mean squared error (MSE) of the reconstructed images shows a sharp new dip, confirming improved image reconstruction. The entropy maximisation method is an alternative approach to maximum likelihood (ml) and maximum a posteriori (MAP) methodologies.
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