Wireless Personal Communications

In wireless sensor and actuator networks, WSAN, actuators often act as cluster headers. Since the transmission range of actuator is much larger than that of sensor, both of the coverage of actuator and the connectivity of sensor-actuator require to be considered in the clustered WSAN. However, the existing clustering algorithms in WSAN only addressed the coverage issue. None of them considered the coverage and the connectivity jointly. Thus we proposed a K-hop coverage and connectivity aware clustering (K-CCAC) in this paper. The different sensor deployment models may affect the coverage and the connectivity for clustering. Thus K-CCAC was evaluated in five sensor deployment models we proposed. Simulation results demonstrated that the coverage and the connectivity in K-CCAC could be up to 100 % with fewer actuators in each model. The hop count from leaf sensors to cluster headers could be limited to K. Moreover, the number of actuators could decrease when the ratio of the transmission radius of actuator to that of sensor or the number of sensors increased.

A beamspace-time (BT) RAKE receiver is proposed for multiple accessinterference (MAI) suppression and multipath diversity reception insectored wireless CDMA communications. The scheme involves three stages.First, a set of adaptive beamformers encompassing a prescribed angular sectoris constructed on an antenna array, each providing effective suppression ofout-of-sector MAI and reception of in-sector signal. Second, a set of adaptivecorrelators is attached to each beam to combat in-sector MAI. Finally, thebeamspace correlator output data are combined to capture the signal multipathscoherently.The above three-stage operation is performed in a blind mode inthat no training signal is needed. The only information required is the signature,timing and a rough estimate of the angle of arrival (AOA) of the desired signal.

In this paper, algorithms for navigating a mobile robot through wireless sensor networks are presented. The mobile robot can navigate without the need for a map, compass, or GPS module while interacting with neighboring sensor nodes. Two navigation algorithms are proposed in this paper: the first uses the distance between the mobile robot and each sensor node and the second uses the metric calculated from one-hop neighbors’ hop-counts. Periodically measuring the distance or metric, the mobile robot can move toward a point where these values become smaller and finally come to reach the destination. These algorithms do not attempt to localize the mobile robot for navigation, therefore our approach permits cost-effective robot navigation while overcoming the limitations of traditional navigation algorithms. Through a number of experiments and simulations, the performance of the two proposed algorithms is evaluated.

In this paper the performance of soft interference cancellation in synchronous multiuser channels is investigated. Two-stage detection with decorrelator in the first stage is considered. Soft first stage tentative decisions are formed by means of a multilevel quantizer or linear clipper. The asymptotic multiuser efficiency (AME) is used as a performance measured for optimization of the nonlinearity. It is shown, for the two-user case, that soft interference cancellation by means of an optimized linear clipper achieves the AME of the maximum likelihood detector if the crosscorrelation of the signature waveforms is less than $$1/\sqrt 2 $$ . For the K-user case, novel upper bounds on the AME for two-stage detectors with feedback interference cancellation, with both hard and soft tentative decisions, are obtained. The derived bounds are used to examine the performance of two-stage detectors in a cellular scenario.

Linear Least Squares (LLS) estimation is a low complexity but sub-optimum method for estimating the location of a mobile terminal (MT) from some measured distances. It requires selecting one of the known fixed terminals (FTs) as a reference FT for obtaining a linear set of expressions. In this paper, the choosing of the reference FT is investigated. By analyzing the objective function of LLS algorithm, a new method for selecting the reference FT is proposed, which selects the reference FT based on the minimum residual (denoted as MR-RS) rather than the smallest measured distance and improves the localization accuracy significantly in Line of sight (LOS) environment. In Non-line of sight (NLOS) environment, we combine MR-RS algorithm with two other existing algorithms (residual weighting algorithm and three-stage algorithm) to form new algorithms, which also improve the localization accuracy comparing with the two algorithms. Moreover, the time complexity of the proposed algorithms is analyzed. Simulation results show that the proposed methods are always better than the existing methods for arbitrary geometry position of the MT and the LOS/NLOS conditions.

The concept of anonymous channel ticket is one of the effective measures to protect user privacy and to reduce the overhead of re-authentication for wireless environments. Most recently, Hsieh et al. proposed an anonymous authentication protocol based on elliptic curve cryptography to enhance the efficiency and security strength. However, we identify that Hsieh et al.’s scheme has four weaknesses. (1) The scheme fails to provide identity anonymity. (2) The ticket authentication phase of the scheme suffers from desynchronization attack. (3) The scheme is vulnerable to the privileged insider attack. (4) Users cannot change passwords when required. We further propose an improved authentication scheme, which not only preserves the merits of the scheme of Hsieh et al., but also enjoys several other advantages. Our improved scheme is effective in protection from the weaknesses identified and achieves user anonymity and unlinkability. We compare the functionality and performance of our improved scheme with other related schemes, which indicates that our scheme is more secure and yet efficient for wireless access networks.

Chi square distribution is a continuous probability distribution primarily used in hypothesis testing, contingency analysis, and construction of confidence limits in inferential statistics but not necessarily in the modeling of real-life phenomena. The closed-form expression for the quantile function (QF) of Chi square is not available because the cumulative distribution function cannot be transformed to yield the QF and consequently places limitations on the use of the QF. Researchers have over the years proposed approximations that improve over time in terms of speed, computational efficiency, and precision, and so on. However, most of the available closed-form expressions (quantile approximation) fail at the extreme tails of the distribution. This paper used the Quantile mechanics approach to obtain second-order nonlinear ordinary differential equations whose solutions using the power series method yielded initial approximates in form of series for different values of the degrees of freedom. The initial approximate varies with the exact (R software) values which serve as the reference and the error between them was minimized by the natural cubic spline interpolation. The final approximates are correct up to an average of 8 decimal places, have small error, and is closer to the exact when compared with some other results from other researchers. The upper tail of the distribution was considered and excellent results were obtained which is a major improvement over the existing results in the literature. The approach used in this work is a hybrid of series expansions and numerical algorithms. Computer codes can be written for the application.