New acquisition decision algorithm for multiple access interference suppression in DSSS system

For decreasing the multiple access interference of weaker signal acquisition in direct sequence spread spectrum（DSSS） systems,a new single decision algorithm is presented.The maximum value of correlation results is conventionally detected.However,there may be not only one strong peak among correlation results when the cross-correlation noise is strong enough to affect the correlation results.The proposed algorithm decreases the false alarm probability through the decision of the ratio of the maximum value and the second maximum value of the correlation results.Theoretical analysis and simulation results indicate that the proposed algorithm effectively suppresses the acquisition problem of multiple access interference in DSSS system.

New Acquisition Algorithm for Direct Sequence Spread Spectrum Signals

Aiming at improving acquisition performance for direct sequence spread spectrum （DSSS） signals, a new acquisition algorithm based on fast Fourier transform （FFT） is proposed. The code phases are parallel searched throughout the Doppler frequency domain. Since the influence of Doppler frequency errors on peak-to- average ratios of correlation power shows a pattern similar to the sinc function, it is our belief that by judging on peak-to-average ratios for different Doppler frequency errors false alarm probabilities should be lowered. Analyses have supported the underlying principle of this new algorithm. Simulation results have also indicated that the new algorithm can effectively improve the acquisition performance for DSSS signals.

Mitigation of primary user emulation attack using a new energy detection method in cognitive radio networks

A most promising solution to the expansion of spectrum efficiency is cognitive radio(CR)and this expansion is achieved by permitting the licensed frequency bands to be accessed by unlicensed secondary users(SUs)with a lack of interference with licensed primary users(PUs).This utilization of CR networks in the spectrum sensing causes vulnerable attacks like primary user emulation(PUE)attack and here PUs play the role of malicious user and do not permit other users to utilize PUs channel even in their unavailability.On the basis of the traditional single-threshold energy detection algorithm,a novel modified double-threshold energy detector is formulated in the CR network and the detection probability,miss detection probability,probability of false alarm,and their inter-relationship are analyzed.This paper develops a modified double threshold energy detection cooperative spectrum sensing technique to alleviate the PUE attack.Finally,performance-based evaluation is carried out between the proposed and the existing energy detection spectrum sensing method that had no consideration on PUE attack.The resultant of the simulation in MATLAB has revealed that the proposed model has significantly mitigated PUE attack by means of providing outstanding performance.

Optimization of Multiband Spectrum Sensing for Cognitive Radio Networks under Sensing Capability Constrains

This paper addresses the problem of joint optimization of subchannel selection and spectrum sensing time for multiband cognitive radio networks under the sensing capability constrains. In particular, we construct a multiband spectrum sensing framework, and derive the probabilities of detection and false alarm taking the different subchannel gain into account. Furthermore, we formulate the multi- band sensing as a two-parameter optimization prob- lem under the sensing capability constrains and guaranteeing the QoS of the secondary user. Moreover, we develop a semi-analytical optimization scheme to achieve the optimal solution.

Enhanced spectrum sensing using a combination of energy detector,matched filter and cyclic prefix

In this paper,we propose a sensing scheme based on energy detection,matched filter and cyclic prefix.Both Equal Gain Combining(EGC)and optimal combination of the aforementioned detectors are investigated in cooperative and non-cooperative spectrum sensing scenarios.In packet transmission systems such as OFDM(Orthogonal Frequency Division Multiple access)systems,the proposed scheme takes advantage of utilizing more samples than individual detectors,i.e.,cyclic prefix,training or pilot samples,and data payload samples.The proposed combine-sensing scheme offers higher detection probability and lower false alarm probability,as compared with the performance of individual detectors over the same frame duration.Simulation results are congruent with the theoretical curves and confirm the validity of our derivations.

DCT domain filtering method for multi-antenna code acquisition

For global navigation satellite system （GNSS） signals in Gaussian and Rayleigh fading channel, a novel signal detection algorithm is proposed. Under the low frequency uncertainty case, after performing discrete cosine transform （DCT） to the outputs of the partial matched filter （PMF） for every antenna, the high order com- ponents in the transforming domain will be filtered, then the equalgain （EG） combination for the inverse discrete cosine transform （IDCT） reconstructed signal would be done subsequently. Thus, due to the different frequency distribution characteristics between the noise and signals, after EG combination, the energy of signals has almost no loss and the noise energy is greatly reduced. The theoretical analysis and simulation results show that the detection algorithm can effectively improve the signal-to-noise ratio of the captured signal and increase the probability of detection under the same false alarm probability. In addition, it should be pointed out that this method can also be applied to Rayleigh fading channels with moving antenna.

Hypothesis testing analysis and unknown parameter estimation of GPS signal detection

Hypothesis testing analysis and unknown parameter estimation of both the intermediate frequency(IF) and baseband GPS signal detection are given by using the generalized likelihood ratio test(GLRT) approach,applying the model of GPS signal in white Gaussian noise,It is proved that the test statistic follows central or noncentral F distribution,It is also pointed out that the test statistic is nearly identical to central or noncentral chi-squared distribution because the processing samples are large enough to be considered as infinite in GPS acquisition problem.It is also proved that the probability of false alarm,the probability of detection and the threshold are affected largely when the hypothesis testing refers to the full pseudorandom noise(PRN) code phase and Doppler frequency search space cells instead of each individual cell.The performance of the test statistic is also given with combining the noncoherent integration.

Robust and Low-Complexity Synchronization for Energy Detection UWB Receiver

A simple method using aided sliding rectangular windows for synchronization in energy detector （ED） receiver is proposed for impulse-based ultra wideband radios （IR-UWB） under binary pulse position modulation （PPM）, therefore grants an attractive solution for gaining low complexity while the accompanying performance loss in terms of UWB signal reception is comparatively low. Also, a method is developed to sup- press noise through accumulation of integrated results before synchronization point is reached. This proposed method can effectively reduce the impact of one of the major performance-degrading factors in ED receivers, i. e., noise caused by heightened noise floor due to large bandwidth product. Our theoretic work on this im- proved synchronization performance and relevant simulations are conducted on IEEE 802.15.4a channel mod- els, and results show that the proposed design scheme can effectively decrease both the probability of false alarm and probability of missed detection.

Generalized Approach to Signal Processing in CollaborativeWireless Sensor Systems for Target Detection

Collaboration in wireless sensor systems must be fault-tolerant due to the harsh environmental conditions at which such systems can be deployed. This paper focuses on finding the signal processing algorithms for collaborative target detection based on the generalized approach to signal processing （GASP） in the presence of noise. The signal processing algorithms are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the wireless sensor systems. Two types of generalized signal processing algorithms, namely, value fusion and decision fusion constructed according to GASP in the presence of noise, are identified first. When comparing their performance and communication overhead, the decision fusion algorithm is found to become superior to the value fusion algorithm as the ratio of faulty sensors to fault free sensors increases. The use of GASP under designing the value and decision fusion algorithms in wireless sensor systems allows us to obtain the same performance, but at low values of signal energy, as well as under employment of the universally adopted signal processing algorithms widely used in practice.

CUSUM control charts based on likelihood ratio for preliminary analysis

To detect and estimate a shift in either the mean and the deviation or both for the preliminary analysis, the statistical process control (SPC) tool, the control chart based on the likelihood ratio test (LRT), is the most popular method. Sullivan and woodall pointed out the test statistic lrt(n1, n2) is approximately distributed as x2(2) as the sample size n,n1 and n2 are very large, and the value of n1 = 2,3,..., n - 2 and that of n2 = n - n1. So it is inevitable that n1 or n2 is not large. In this paper the limit distribution of lrt(n1, n2) for fixed n1 or n2 is figured out, and the exactly analytic formulae for evaluating the expectation and the variance of the limit distribution are also obtained. In addition, the properties of the standardized likelihood ratio statistic slr(n1, n) are discussed in this paper. Although slr(n1, n) contains the most important information, slr(i, n)(i≠n1) also contains lots of information. The cumulative sum (CUSUM) control chart can obtain more information in this condition. So we propose two CUSUM control charts based on the likelihood ratio statistics for the preliminary analysis on the individual observations. One focuses on detecting the shifts in location in the historical data and the other is more general in detecting a shift in either the location and the scale or both. Moreover, the simulated results show that the proposed two control charts are, respectively, superior to their competitors not only in the detection of the sustained shifts but also in the detection of some other out-of-control situations considered in this paper.