Power control is of paramount importance in combating the near-far problem and co-channel interference in a CDMA cellular system. Due to fast fading and ambient interference in a wireless channel, conventional fixed-s...Power control is of paramount importance in combating the near-far problem and co-channel interference in a CDMA cellular system. Due to fast fading and ambient interference in a wireless channel, conventional fixed-step power control schemes have difficulty in compensating for the fast fading channel dynamically and in a timely manner. To acquire flexible power regulation in order to maintain required transmission capacity under the given transmission quality requirement, we propose a hybrid power control scheme which makes full use of the simple fuzzy inference rule refined by an operator in the fuzzy control and prediction property from related previous results in Generalized Prediction Control (GPC). In implementation of this strategy, we classify the fading zone into three levels according to the signal-to-noise-rate (SNR) requirement. In each level the power compensation amount varies with fading gradient and the compensation scheme varies as well. The digital results show that adoption of the fuzzy-GPC power regulation scheme has acquired a reasonable performance improvement when compared with fixed-step and fuzzy schemes. According to theoretic analysis and simulation results, we can conclude that under a variational transmission environment, a flexible power regulation scheme such as fuzzy-GPC is easy to adapt to the environment and thus overcomes the near-far effect and multi-access interference effectively.展开更多
New industrial applications call for new methods and new ideas in signal analysis. Wavelet packets are new tools in industrial applications and they have just recently appeared in projects and patents. In training neu...New industrial applications call for new methods and new ideas in signal analysis. Wavelet packets are new tools in industrial applications and they have just recently appeared in projects and patents. In training neural networks, for the sake of dimensionality and of ratio of time, compact information is needed. This paper deals with simultaneous noise suppression and signal compression of quasi-harmonic signals. A quasi-harmonic signal is a signal with one dominant harmonic and some more sub harmonics in superposition. Such signals often occur in rail vehicle systems, in which noisy signals are present. Typically, they are signals which come from rail overhead power lines and are generated by intermodulation phenomena and radio interferences. An important task is to monitor and recognize them. This paper proposes an algorithm to differentiate discrete signals from their noisy observations using a library of nonorthonormal bases. The algorithm combines the shrinkage technique and techniques in regression analysis using Shannon Entropy function and Cross Entropy function to select the best discernable bases. Cosine and sine wavelet bases in wavelet packets are used. The algorithm is totally general and can be used in many industrial applications. The effectiveness of the proposed method consists of using as few as possible samples of the measured signal and in the meantime highlighting the difference between the noise and the desired signal. The problem is a difficult one, but well posed. In fact, compression reduces the level of the measured noise and undesired signals but introduces the well known compression noise. The goal is to extract a coherent signal from the measured signal which will be ＂well represented＂ by suitable waveforms and a noisy signal or incoherent signal which cannot be ＂compressed well＂ by the waveforms. Recursive residual iterations with cosine and sine bases allow the extraction of elements of the required signal and the noise. The algorithm that has been developed is utilized as a filter to extract features for training neural networks. It is currently integrated in the inferential modelling platform of the unit for Advanced Control and Simulation Solutions within ABB＇s industry division. An application using real measured data from an electrical railway line is presented to illustrate and analyze the effectiveness of the proposed method. Another industrial application in fault detection, in which coherent and incoherent signals are univocally visible, is also shown.展开更多
文摘Power control is of paramount importance in combating the near-far problem and co-channel interference in a CDMA cellular system. Due to fast fading and ambient interference in a wireless channel, conventional fixed-step power control schemes have difficulty in compensating for the fast fading channel dynamically and in a timely manner. To acquire flexible power regulation in order to maintain required transmission capacity under the given transmission quality requirement, we propose a hybrid power control scheme which makes full use of the simple fuzzy inference rule refined by an operator in the fuzzy control and prediction property from related previous results in Generalized Prediction Control (GPC). In implementation of this strategy, we classify the fading zone into three levels according to the signal-to-noise-rate (SNR) requirement. In each level the power compensation amount varies with fading gradient and the compensation scheme varies as well. The digital results show that adoption of the fuzzy-GPC power regulation scheme has acquired a reasonable performance improvement when compared with fixed-step and fuzzy schemes. According to theoretic analysis and simulation results, we can conclude that under a variational transmission environment, a flexible power regulation scheme such as fuzzy-GPC is easy to adapt to the environment and thus overcomes the near-far effect and multi-access interference effectively.
文摘New industrial applications call for new methods and new ideas in signal analysis. Wavelet packets are new tools in industrial applications and they have just recently appeared in projects and patents. In training neural networks, for the sake of dimensionality and of ratio of time, compact information is needed. This paper deals with simultaneous noise suppression and signal compression of quasi-harmonic signals. A quasi-harmonic signal is a signal with one dominant harmonic and some more sub harmonics in superposition. Such signals often occur in rail vehicle systems, in which noisy signals are present. Typically, they are signals which come from rail overhead power lines and are generated by intermodulation phenomena and radio interferences. An important task is to monitor and recognize them. This paper proposes an algorithm to differentiate discrete signals from their noisy observations using a library of nonorthonormal bases. The algorithm combines the shrinkage technique and techniques in regression analysis using Shannon Entropy function and Cross Entropy function to select the best discernable bases. Cosine and sine wavelet bases in wavelet packets are used. The algorithm is totally general and can be used in many industrial applications. The effectiveness of the proposed method consists of using as few as possible samples of the measured signal and in the meantime highlighting the difference between the noise and the desired signal. The problem is a difficult one, but well posed. In fact, compression reduces the level of the measured noise and undesired signals but introduces the well known compression noise. The goal is to extract a coherent signal from the measured signal which will be ＂well represented＂ by suitable waveforms and a noisy signal or incoherent signal which cannot be ＂compressed well＂ by the waveforms. Recursive residual iterations with cosine and sine bases allow the extraction of elements of the required signal and the noise. The algorithm that has been developed is utilized as a filter to extract features for training neural networks. It is currently integrated in the inferential modelling platform of the unit for Advanced Control and Simulation Solutions within ABB＇s industry division. An application using real measured data from an electrical railway line is presented to illustrate and analyze the effectiveness of the proposed method. Another industrial application in fault detection, in which coherent and incoherent signals are univocally visible, is also shown.
