Coordinate interleaved orthogonal design (CIOD) using four transmit antennas provides full diversity, full rate (FDFR) properties with low decoding complexity. However, the constellation expansion due to the coordinate interleaving of the rotated constellation results in peak to average power ratio (PAPR) increase. In this paper, we propose two signal constellation design methods which have low PAPR. In the first method we propose a signal constellation by properly selecting the signal points among the expanded square QAM constellation points, based on the co-prime interleaving of the first coordinate signal. We design a regular interleaving pattern so that the coordinate distance product (CPD) after the interleaving becomes large to get the additional coding gain. In the other method we propose a novel constellation with low PAPR based on the clipping of the rotated square QAM constellation. Our proposed signal constellations show much lower PAPR than the ordinary rotated QAM constellations for CIOD.

The information maximization (Infomax) based on information entropy theory is a class of methods that can be used to blindly separate the sources. Torkkola applied the Infomax criterion to blindly separate the mixtures where the sources have been delayed with respect to each other. Compared to the frequency domain methods, this time domain method has simple adaptation rules and can be easily implemented. However, Torkkola's method works only in the real valued field. In this letter, the Infomax for blind separation of the delayed sources is extended to the complex case for processing of complex valued signals. Firstly, based on the gradient ascent the adaptation rules for the parameters of the unmixing network are derived and the steps of algorithm are given. Then, a measurement matrix is constructed to evaluate the separation performance. The results of computer experiment support the extended algorithm.

As the demand for high-throughput communications in wireless LANs (WLAN) increases, the need for expanding channel bandwidth also increases. However, the use of wider band channels results in a decrease in the number of available channels because the total available bandwidth for WLAN is limited. Therefore, if multiple access points (APs) are in proximity and the cells overlap, it is difficult for each AP to use an orthogonal channel and competition increases between APs using the same channel. Coordination of APs is one promising approach; however, it is impractical to control all APs in WLAN systems. To cope with this problem, we proposed to analyze throughput performances of a multibandwidth channel selection by the coordinating APs at Nash equilibria, which can be considered as operating points for independent channel selection by APs. To clarify the effect of coordinating APs, we assume a simple scenario where the cells of three or more APs overlap, and each AP can select multibandwidth channels to maximize their own throughput. Through game-theoretic analysis, we find that the coordinated APs are able to select channels more effectively than if each AP independently selects channels. Consequently, the total throughput of the coordinated APs at Nash equilibria is significantly improved.

This paper proposes a power saving control method for battery-powered portable wireless LAN (WLAN) access points (APs) in an overlapping basic service set (OBSS) environment. The IEEE802.11 standard does not support power saving control for APs. Some conventional power saving control methods for APs have been proposed that use the network allocation vector (NAV) to inhibit transmission at stations (STAs) while the AP is sleeping. However, since with these approaches the actual beacon interval in the OBSS environment may be extended due to the NAV as compared to the beacon interval which is set at the AP, the power consumption and delay may be increased as compared to a single BSS unaffected by interference from neighboring APs. To overcome this problem, this paper introduces a new action frame named power saving access point (PSAP) action frame which the AP uses to inform STAs within its BSS about the AP's sleep length. In addition, a function of the PSAP action frame is that STAs enter the sleep state after receiving the PSAP action frame. The proposed control method avoids the postponement of beacon transmission and reduces the power consumption in an OBSS environment, as compared to the conventional control method. Numerical analysis and computer simulation reveal that the newly proposed control method conserves power as compared to the conventional control method. The proposed control method achieves the minimum consumed power ratio at the AP, which is 44% as compared to the standard, when the beacon interval is 100 ms and the sleep length is 60 ms, even if the number of neighboring APs in an OBSS environment is increased.

Fetal electrocardiogram (FECG) extraction is of vital importance in biomedical signal processing. A promising approach is blind source extraction (BSE) emerging from the neural network fields, which is generally implemented in a semi-blind way. In this paper, we propose a robust extraction algorithm that can extract the clear FECG as the first extracted signal. The algorithm exploits the fact that the FECG signal's kurtosis value lies in a specific range, while the kurtosis values of other unwanted signals do not belong to this range. Moreover, the algorithm is very robust to outliers and its robustness is theoretically analyzed and is confirmed by simulation. In addition, the algorithm can work well in some adverse situations when the kurtosis values of some source signals are very close to each other. The above reasons mean that the algorithm is an appealing method which obtains an accurate and reliable FECG.

In this study, we propose a robust approach for blind source separation (BSS) by using radial basis function networks (RBFNs) and higher-order statistics (HOS). The RBFN is employed to estimate the inverse of a hypothetical complicated mixing procedure. It transforms the observed signals into high-dimensional space, in which one can simply separate the transformed signals by using a cost function. Recently, Tan et al. proposed a nonlinear BSS method, in which higher-order moments between source signals and observations are matched in the cost function. However, it has a strict restriction that it requires the higher-order statistics of sources to be known. We propose a cost function that consists of higher-order cumulants and the second-order moment of signals to remove the constraint. The proposed approach has the capacity of not only recovering the complicated mixed signals, but also reducing noise from observed signals. Simulation results demonstrate the validity of the proposed approach. Moreover, a result of application to X-ray image separation also shows its practical applicability.

This paper overviews a total solution for frequency-domain blind source separation (BSS) of convolutive mixtures of audio signals, especially speech. Frequency-domain BSS performs independent component analysis (ICA) in each frequency bin, and this is more efficient than time-domain BSS. We describe a sophisticated total solution for frequency-domain BSS, including permutation, scaling, circularity, and complex activation function solutions. Experimental results of 22, 33, 44, 68, and 22 (moving sources), (#sources#microphones) in a room are promising.

This study investigates the effect of the method of time division in frequency domain ICA on estimation accuracy of ICA. We show that source signals expressed in the frequency domain lose non-Gaussianity and independence because of the long and overlapping window function, respectively, in time division. Consequently, the estimation accuracy of ICA decreases.

In radio surveillance systems we consider the problem of identifying interferers or illegal radios in licensed communication channels. The systems considered are receivers using arrays of antennas for spatial processing. At the output of each antenna, we have a mixture of communication signals. The mixture will depend on the distance of the source radios and the propagation environment. These signals may or may not have the same modulation type. The main four tasks in the radio surveillance system are: Separation of the source signals contained in the data mixture at the array antenna, modulation recognition to identify the illegal radio, direction of arrival estimation to pinpoint the location of the illegal radios, and demodulation to intercept the information contained within the illegal transmission. In this paper we deal with the application of the Fast ICA algorithm to a uniform linear array. Our interest is to separate the independent source signals from the mixture of signals obtained at the sensors. Since the target system operates in the HF domain, where analog modulations dominate, the impinging signals are assumed analog modulated communication signals.