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A new detection algorithm for direct sequence spread spectrum (DSSS) signals using peak-to-average power ratio (PAPR) is proposed. The received signals are divided into several blocks. Then we calculate peak-to-average power ratio of each block and we use the average of peak-to-average power ratios as test statistics. The advantage of the proposed algorithm is no need to estimate noise variance. Additionally,...
This paper presents an analyzing on the prediction of a primary signal in cognitive radio networks using a hybrid algorithm based on two parts, know as: an alpha-beta filter and a neyman-pearson (NP) detector. Today, it is important to predict a primary signal in a cluttered environment and especially when the secondary user (SU) is moving. However, the challenges of this contribution are based on...
This paper addresses the robust beamforming design for a downlink cloud radio access network (cloud RAN) subject to per-base-station (BS) power constraint and individual signal-to-interference-plus-noise ratio (SINR) requirements. Our objective is to minimize the overall network power and backhaul cost while guaranteeing the users' SINR constraints for every channel realization by designing the joint...
Spectrum sensing is a method which is used to find out whether the channel is idle or not in Cognitive Radio Network (CRN). Traditional methods are not much reliable due to the uncertain noise during the detection. In this paper, a weighted cooperative spectrum sensing strategy with jointing energy and spectrum-width detection under noise uncertainty is proposed to improve the detection performance...
In this paper a new direct nonparametric estimation of the period and the shape of a periodic component in short duration signals is proposed and evaluated. Classical Fourier Transform (FT) methods lack precision and resolution when the duration of the signal is very short and the signal is noisy. The proposed method is based on the direct description of the problem as a linear inverse problem and...
In view of dynamic multi-criteria decision-making problems, in which the criteria value of alternatives are three-parameters interval numbers and criteria exists different natural states, a dynamic grey stochastic multi-criteria decision-making method is proposed. According to the stationary distribution thought of Markov chain, the final state of natural possibility is obtained. The time information...
Estimating the direction of arrival (DOA) in sensor arrays is a crucial task in array signal processing systems. This task becomes more difficult when the sensors have gain/phase uncertainty. We have addressed this issue by modeling the problem as a combination of two sparse components, the DOA vector and the gain/phase uncertainty vector. Therefore, a sparse decomposition technique is suggested to...
It is known that the features of the radio station vary with the signal to noise ratio (SNR) in a certain range which leads to the uncertainty of the radio station identification system. In this paper, we study the interval evidence recognizer by extending the individual features of the obtained radio from single value to interval and constructing the radio station feature database. Firstly, the range...
The existing joint design methods of transmit waveform and receive filter for cognitive radar(CR) radar are all based on the precise previous information about the target and interference, also the efficiency of transmitter has not been taken into account in practical applications. For these problems, a low peak-to-average power ratio (PAR) robust waveform and receive filter design algorithm is proposed...
In this paper the Cramer-Rao bound (CRB) for the estimation of nearfield source location under unknown gain/phase responses is analyzed. We first derive the CRB under the special case of single source and then extend to more general case of multiple sources. For single-source scenario we show that the CRB can be segmented into two parts, which separately corresponds to gain responses and phase responses...
Wireless network localization (WNL) is a paradigm proposed recently for providing reliable location services. The localization performance is highly dependent on the placement of nodes in the network. In this paper, we study the node placement problem for localization networks. We first propose a mathematical formulation of the node placement problem. Such a formulation takes into account the uncertainty...
Nowadays, face recognition systems are going to widespread in many fields of application, from automatic user login for financial activities and access to restricted areas, to surveillance for improving security in airports and railway stations, to cite a few. In such scenarios, several architectures based on both 2D image analysis and 3D reconstruction are investigated and proposed in literature...
The spectrum sensing is a vital stage in cognitive radio networks. The performance of energy-based spectrum sensing scheme degrades under noise uncertainty, which can be improved by covariance-based sensing methods. In this paper, a double threshold-based spectrum sensing scheme using sample covariance matrix of received signal is presented, that improves the performance of conventional covariance-based...
Cognitive radio (CR) is a form of wireless communication in which a transceiver can wisely detect communication channels that are in use and those which are not, and immediately move into vacant channels while avoiding occupied ones. In such systems, spectrum sensing (SS) is a crucial operation. It consists to detect the available frequency bands. Many spectrum sensing techniques are presented in...
We propose a TDOA-based algorithm for source localization on rigid surfaces. This allows the conversion of readily available large surfaces into touch interfaces using surface-mounted vibration sensors. To achieve this, we characterize the arrival of each sensor-received signal by the arrival times of its frequency components. To estimate the arrival time of each frequency component, we first model...
In this work, we consider the robust beamforming design for secondary downlink multicasting channels, where primary users are present with norm-bounded channel errors. In particular, the max-min-fair formulation is considered and the resulting design problem is a quadratically constrained quadratic program (QCQP) with a set of semi-infinite constraints, which is NP-hard in general. As a remedy, we...
In cognitive radio, the secondary user (SU) can only utilize the spectrum hole with assurance of sufficient protection to the licenced primary user (PU). In this paper, a reliable spectrum sensing scheme based on eigenvalue of sample covariance matrix of received signal is proposed. The conventional energy-based detection method is highly vulnerable under noise uncertainty and eigenvalue-based method...
This paper studies a robust beamforming optimization problem of minimizing total transmit power in a distributed manner in the presence of imperfect channel state information (CSI) in multicell interference networks. Due to the fact that worst- case is a rare occurrence in practical network, this problem is constrained to satisfying a set of signal-to-interference-plus-noise-ratio (SINR) requirements...
In this paper, we study resource allocation for secondary users (SUs) in underlay full-duplex cognitive networks, where the channel state information of the links between SUs and primary users (PUs) is uncertain. To protect the transmission of the PUs from interference generated by the SUs, we utilize robust optimization theory to characterize the channel uncertainty and formulate a resource allocation...
In cognitive radio spectrum sensing is a fundamental problem. Under the case of uncorrelated noise different methods are used for spectrum sensing. In this paper we compare the performance of MP and eigenvalue based methods. In eigenvalue based method we find the threshold using random matrix theory (RMT). Marchenko-Pastur (MP) method use standard condition number (SCN) to find the threshold. Here...
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