Bi Guangguo

An improved channel estimation algorithm for OFDM UWB

Channel estimation is very important for OFDM based UWB system because of its coherent demodulation. In this paper, a new improved channel estimation method is proposed based on the characteristics of the UWB channels. Compare with the estimator using discrete Fourier-transform, the proposed algorithm can properly choose suitable length of time-domain filter by distinguishing different channel conditions. It is shown by simulation that better performance can be achieved especially for IEEE cm1 and cm2 channels.

Multiple Cumulants Based Spectrum Sensing Methods for Cognitive Radios

In cognitive radios, energy detector is considered for spectrum sensing in the literature. However, its performance deteriorates rapidly if the noise power is not known exactly. Moreover, due to the presence of a colored channel interferer or some other reasons, the conventional white Gaussian noise may become colored. In order to solve these problems, this paper proposes several multicumulant based spectrum sensing methods: generalized likelihood ratio test (GLRT) based multicumulant (GLRTMC) based detection method and multiantenna-assisted multicumulant (MAMC) based detection method. GLRTMC detection method is derived from generalized likelihood ratio test and assumed to be near optimum in theory. MAMC detection method, on the other hand, by using multiple antennas, is a complexity-reduced detector and allows us to make a compromise between performance and complexity. It is well known that cumulants higher than second order are zero for Gaussian distributions. Thus, GLRTMC detection method and MAMC detection method can extract a non-Gaussian signal from Gaussian noise even when the noise is colored. In addition, the proposed methods are nonparametric in the sense that they do not require any exact prior knowledge about the signal or the noise, such as noise power or cyclic frequencies. Hence they are immune from noise uncertainty. Simulation experiments are provided to show the validity and the superiority over single-cumulant based detector of the proposed multicumulant based detectors.In cognitive radios, energy detector is considered for spectrum sensing in the literature. However, its performance deteriorates rapidly if the noise power is not known exactly. Moreover, due to the presence of a colored channel interferer or some other reasons, the conventional white Gaussian noise may become colored. In order to solve these problems, this paper proposes several multicumulant based spectrum sensing methods: generalized likelihood ratio test (GLRT) based multicumulant (GLRTMC) based detection method and multiantenna-assisted multicumulant (MAMC) based detection method. GLRTMC detection method is derived from generalized likelihood ratio test and assumed to be near optimum in theory. MAMC detection method, on the other hand, by using multiple antennas, is a complexity-reduced detector and allows us to make a compromise between performance and complexity. It is well known that cumulants higher than second order are zero for Gaussian distributions. Thus, GLRTMC detection method and MAMC detection method can extract a non-Gaussian signal from Gaussian noise even when the noise is colored. In addition, the proposed methods are nonparametric in the sense that they do not require any exact prior knowledge about the signal or the noise, such as noise power or cyclic frequencies. Hence they are immune from noise uncertainty. Simulation experiments are provided to show the validity and the superiority over single-cumulant based detector of the proposed multicumulant based detectors.

An overview on Underwater Acoustic Sensor Networks

Underwater Acoustic Sensor Networks (UW-ASNs) is of growing research interest. This paper gives description on underwater channel model. It overviews transmission schemes in data link layer and network layer, and simulates different transmission schemes. Finally, it offers comparison and guides for future development.

Generalized soft decision metric generation for MPSK/MQAM without noise variance knowledge

In this paper, a new simplified soft decision metric, without noise variance knowledge, is derived. By recognizing that it is simply a distance metric in Euclidian space, we further generalize it to p-norm. Performance comparisons are presented for LDPC coded 8PSK/16QAM with different parameters. Simulation results show that, when compared with the simplified soft decision metric reported in [F. Tosato et al. 2002], there is no performance loss with our proposed generalized soft decision metric. Moreover, it is unnecessary to estimate noise variance at the channel output, which greatly facilitates practical implementation. Further simulation indicates that, at high signal to noise ratio, a small performance gain can be obtained with p a bit less than 2.

Suppression of FM interference in QAM systems using adaptive decision-feedback filters

In this paper, the performance of QAM (quadrature amplitude modulation) systems using adaptive transversal filters with additional decision-feedback (DF) taps, in the presence of Gaussian noise and one FDM-FM interfering signals, is analysed. On the basis of an approximate statistical model of an FDM-FM signal, the analytic expressions and curves of symbol error probability of QAM systems with and without adaptive filters, are obtained. The performance improvement achieved by adopting adaptive filters is clearly evident. Simulation results also display the effectiveness of adaptive DF filters for suppressing FM interference in QAM systems.<<ETX>>

Novel autocorrelation based spectrum sensing methods for cognitive radios

In cognitive radios, energy detector is often considered for spectrum sensing in the literature. However, its performance deteriorates rapidly when noise power is fluctuating. In order to solve this problem, several autocorrelation based detection methods such as statistical covariances based (CAV) detection method and eigenvalue based (MME) detection method have been proposed. However, CAV detector is derived based on the assumption the noise is real and MME detector on the other hand is a little conservative. In this paper, two novel autocorrelation based spectrum sensing methods, which are correlation coefficients (CCE) based detection method and nonparametric autocorrelation (NAC) based detection method, have been proposed. CCE detector is suitable for complex Gaussian noise and NAC detector can distinguish correlated signals from arbitrary independent noise without knowing the noise type. Both CCE detector and NAC detector are also nonparametric. Simulation experiments are provided to show the validity of the proposed CCE detector and NAC detector.

An improvement for ad hoc on-demand routing protocol

The two well-known on-demand protocols for ad hoc networks - DSR and AODV show degraded performance with traffic load increase. In this paper, we propose a traffic-balanced scheme, called TB scheme, to solve this problem. The TB scheme adopts MAC layer information for routing decisions. It avoids involving heavy loaded nodes in a new route and thus balances network traffic. Simulation results show that the new scheme significantly improves DSR and AODVs performance under heavy load conditions.The two well-known on-demand protocols for ad hoc networks - DSR and AODV show degraded performance with traffic load increase. In this paper, we propose a traffic-balanced scheme, called TB scheme, to solve this problem. The TB scheme adopts MAC layer information for routing decisions. It avoids involving heavy loaded nodes in a new route and thus balances network traffic. Simulation results show that the new scheme significantly improves DSR and AODVs performance under heavy load conditions.

Woven convolutional codes and a new iterative decoding algorithm

Based on the soft-input soft-output (SISO) algorithm that is used to iteratively decode serially concatenated codes, we present a new modular iterative decoding algorithm for woven convolutional codes. The proposed algorithm takes the log-likelihood ratio of a priori probability as inputs and produces log-likelihood ratio of post a priori probability as outputs. The justification and the performance are demonstrated by numerical simulation.Based on the soft-input soft-output (SISO) algorithm that is used to iteratively decode serially concatenated codes, we present a new modular iterative decoding algorithm for woven convolutional codes. The proposed algorithm takes the log-likelihood ratio of a priori probability as inputs and produces log-likelihood ratio of post a priori probability as outputs. The justification and the performance are demonstrated by numerical simulation.

Ultra Wideband OFDM Channel Estimation Algorithm Based on Instantaneous Power Filtering

The Ultra Wide-Band (UWB) is one of the important development trends of the new-generation wireless communication technology. The channel estimation technology,is the key part of the Orthogonal Frequency-Division Multiplexing (OFDM). After the strengths and weaknesses of the Least Mean Square (LMS) algorithm in the system implementation were compared, a UWB OFDM channel estimation algorithm based on instantaneous power filtering and applicable to system implementation was put forward.The Ultra Wide-Band (UWB) is one of the important development trends of the new-generation wireless communication technology. The channel estimation technology,is the key part of the Orthogonal Frequency-Division Multiplexing (OFDM). After the strengths and weaknesses of the Least Mean Square (LMS) algorithm in the system implementation were compared, a UWB OFDM channel estimation algorithm based on instantaneous power filtering and applicable to system implementation was put forward.

System and chip design for high-speed impulse radio UWB

Impulse radio (IR) ultra-wideband (UWB) wireless communication system has the advantages of low power consumption and low complexity. However, its transmission rate is usually limited. This paper proposes a high-speed IR-UWB system scheme. By using high sampling rate, low resolution quantization, and digital processing, the proposed scheme achieves more than 100 Mbps wireless transmission rate with reasonable power consumption and complexity. The system scheme, core algorithms, key implementations in the chip design, and simulation results are given in the paper. As a core algorithm, a joint synchronization and channel estimation (JSCE) algorithm is proposed. The JSCE algorithm conducts synchronization and channel estimation at the same time. It has the advantage of low complexity and is feasible to real-time implementation. The implementation issues in the chip design, including the digital baseband chip structure, the state transform of the receiver, and the implementation of the JSCE algorithm are introduced. Based on the proposed system scheme, a digital baseband chip is designed and fabricated. The core power consumption of the chip is less than 100 mW. An experimental system is also implemented which uses the baseband chip as a core processor. The system is capable of real-time high de nition video transmission. Experimental results on the experimental system validate the proposed system scheme.