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This paper deals with carrier frequency offset (CFO) estimation for interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. Firstly, gravitational search algorithm (GSA) with center-symmetric trimmed correlation matrix and multiple signal classification criterion is presented for the purpose of efficient estimation. It has been shown that the estimate accuracy of the searching-based...
Power allocation in small cell networks has mostly been investigated using ideal communication links, where it is generally assumed that information can be relayed perfectly between base stations. In this paper, we propose a model with non-ideal links and a power adjustment algorithm for heterogeneous networks. Contrary to the power allocation approaches in the literature, channel state information...
This paper presents a target localization problem based on the time difference of arrival (TDOA) measurements by employing an improved genetic algorithm (GA) for estimation. The weighted least square (WLS) technique is applied as an efficient existing approach. The TDOA target localization problem is formulated as an optimization problem, with a highly nonlinear and multimodal objective function....
Anti-jamming interference alignment (IA) algorithm is an effective method to battle with adversarial jammers. Nevertheless, the abundant power from the jammers and interferences can be harvested by the legitimate users as a natural power supply. In this paper, we propose a novel anti-jamming IA scheme with wireless energy harvesting (EH). In the scheme, the power partition coefficient and transmit...
Automatic link establishment (ALE) is one of the important technologies in HF communication. One of the indicators to measure the performance of an ALE system is the linking time, which includes channel switching, spectrum sensing, and trying to call three periods. Asynchronous mode has been widely used for its simple operation. When establishing an link, the station sorts all the channels and selects...
The occurrence of noise in almost all types of signals is natural. Though the noise variants are many, the impulsive noise in signal highly affects its quality. In this piece of work, speech signal is considered for enhancement that is contaminated with impulsive noise. Generally, hiccups create such type of noise due to tiredness or myoclonic problem of human subjects. Removal of this type of impulsive...
In this paper, we comparative analysis the performance of DFT-based interpolation algorithm with different windows and Digital Lock-in amplifier(DLA) method. We recommend that DLA is a good choice for low signal to noise ratio (SNR). DFT-based interpolation can work with unknown frequency. In comparison with rectangle window, triangle window has better side-band affection with accuracy lose. Beside,...
For improving the range accuracy of LFMCW Radar with triangle wave modulation, frequency estimation performance of Jacobsen algorithm and Quinn algorithm are discussed. When the signal frequency is close to the midpoint of two neighboring discrete frequencies, Jacobsen algorithm has poor accuracy, while Quinn algorithm has good one. A novel combined algorithm named J-Quinn algorithm is proposed. Firstly,...
This work considers methods to detect unknown signals in cognitive radio networks. These methods can be applied when taking decision about presence of a signal in the frequency channel when monitoring radio spectrum. The problem of uncertainty can appear when monitoring spectrum. A way of overcoming a priori uncertainty that arises when monitoring the radio spectrum is proposed.
In real life situations, the statistical characteristics of signal and noise are generally unknown & hence a digital filter having ‘constant coefficients’ is hardly of any use. In such situations adaptive filter is desirable. Adaptive filters are capable of adapting their filter coefficients as per the abnormality in characteristics of input signal and noise to achieve a noise free signal. This...
For the Sinusoid Signals with additive Gauss white noise, a frequency estimation algorithm based on discrete Fourier transform (DFT) interpolation algorithm is proposed in this paper. Based on the classical interpolation algorithm, the algorithm of this paper takes full use of the Peak Spectral Frequency and its neighbor spectral lines to estimate the frequency of the signal. The analysis and simulation...
An endpoint detection in low signal-to-noise ratio (SNR) environment plays an important role in speech processing. In this paper, we propose an endpoint detection algorithm applying a novel feature parameter, called Spectrogram Boundary Factor (SBF), to improve the endpoint detection performance in noisy environments. In the first step, the time-frequency spectrogram is obtained from the noisy speech...
In order to obtain better performance at low SNR regimes and reduce computational complexity in wideband sensing, a novel cyclostationary spectrum sensing (CSS) algorithm exploiting partial QR decomposition is proposed in this paper. At the first step of the CSS algorithm, spectral correlation functions (SCFs) for sampled signals that exhibit cyclostationary are calculated by secondary user (SU) to...
The calibration of Phasor Measurement Units (PMUs) consists of comparing Coordinated Universal Time (UTC) timestamped phasors (synchrophasors) estimated by the PMU under test, against reference synchrophasors generated through a PMU calibrator. The IEEE Standard C37.118-2011 and its amendment (IEEE Std) describe compliance tests for static and dynamic conditions, and indicate the relative limits in...
Cognitive radio is a promising technology that aims to enhance the utilization of the radio spectrum. This is achieved by providing opportunistic access to the unlicensed users or the secondary users. In this paper, quality of service (QoS) in cognitive radio networks is investigated for a heterogeneous network model. A modified cognitive radio spectrum sharing algorithm based on the Hungarian algorithm...
This paper deals with the problem of audio source separation using multichannel observation. Utilizing the sparseness of sound signals in the time-frequency domain is a successful approach to source separation that enables us to perform separation based on spatial features obtained from a microphone array. On the other hand, nonnegative matrix factorization (NMF) is also a promising approach for audio...
The spectrum sensing function allows a cognitive radio to determine the absence/presence of primary users' (PUs) signals in a frequency band of interest. These signals might exhibit very low-power at cognitive (or secondary) users' receivers. Thus requiring detection algorithms that work well in the very low signal-to-noise ratio (SNR) region. It is known that secondary users (SUs) can improve its...
It is of great significance to acquire seismic signal accurately in seismic observation and research. A seismic data acquisition system based on high-precision data acquisition card NI USB-4432 and LabVIEW platform is designed and implemented. Firstly, the seismic signal is modulated by the front-end conditioning circuit composed of AD620 and MAX292, then, it is obtained and analyzed by data acquisition...
Bounded Component Analysis (BCA) is a recent approach which enables the separation of both dependent and independent signals from their mixtures. This article introduces a novel deterministic instantaneous BCA approach for the separation of sparse bounded sources. The separation problem is posed as a geometric maximization problem, where the objective is the volume ratio of two geometric objects related...
This paper addresses the speech enhancement problem with adaptive filtering algorithms. We propose a new dual forward blind source separation (FBSS) algorithm based on the use of the recursive least square algorithm to update the cross-filters of the forward structure. This algorithm inherits the good characteristics of the combination between the FBSS and the good properties of the RLS algorithm...
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