1,591 research outputs found
SGD Frequency-Domain Space-Frequency Semiblind Multiuser Receiver with an Adaptive Optimal Mixing Parameter
A novel stochastic gradient descent frequency-domain (FD) space-frequency (SF) semiblind multiuser receiver with an adaptive optimal mixing parameter is proposed to improve performance of FD semiblind multiuser receivers with a fixed mixing parameters and reduces computational complexity of suboptimal FD semiblind multiuser receivers in SFBC downlink MIMO MC-CDMA systems where various numbers of users exist. The receiver exploits an adaptive mixing parameter to mix information ratio between the training-based mode and the blind-based mode. Analytical results prove that the optimal mixing parameter value relies on power and number of active loaded users existing in the system. Computer simulation results show that when the mixing parameter is adapted closely to the optimal mixing parameter value, the performance of the receiver outperforms existing FD SF adaptive step-size (AS) LMS semiblind based with a fixed mixing parameter and conventional FD SF AS-LMS training-based multiuser receivers in the MSE, SER and signal to interference plus noise ratio in both static and dynamic environments
Low Complexity Blind Equalization for OFDM Systems with General Constellations
This paper proposes a low-complexity algorithm for blind equalization of data
in OFDM-based wireless systems with general constellations. The proposed
algorithm is able to recover data even when the channel changes on a
symbol-by-symbol basis, making it suitable for fast fading channels. The
proposed algorithm does not require any statistical information of the channel
and thus does not suffer from latency normally associated with blind methods.
We also demonstrate how to reduce the complexity of the algorithm, which
becomes especially low at high SNR. Specifically, we show that in the high SNR
regime, the number of operations is of the order O(LN), where L is the cyclic
prefix length and N is the total number of subcarriers. Simulation results
confirm the favorable performance of our algorithm
Visualization on colour based flow vector of thermal image for movement detection during interactive session
Recently thermal imaging is exploited in applications such as motion and face detection. It has drawn attention many researchers to build such technology to improve lifestyle. This work proposed a technique to detect and identify a motion in sequence images for the application in security monitoring system or outdoor surveillance. Conventional system might cause false information with the present of shadow. Thus, methods employed in this work are Canny edge detector method, Lucas Kanade and Horn Shunck algorithms, to overcome the major problem when using thresholding method, which is only intensity or pixel magnitude is considered instead of relationships between the pixels. The results obtained could be observed in flow vector parameter and the segmentation colour based image for the time frame from 1 to 10 seconds. The visualization of both the parameters clarified the movement and changes of pixel intensity between two frames by the supportive colour segmentation, either in smooth or rough motion. Thus, this technique may contribute to others application such as biometrics, military system, and surveillance machine
Coded DS-CDMA Systems with Iterative Channel Estimation and no Pilot Symbols
In this paper, we describe direct-sequence code-division multiple-access
(DS-CDMA) systems with quadriphase-shift keying in which channel estimation,
coherent demodulation, and decoding are iteratively performed without the use
of any training or pilot symbols. An expectation-maximization
channel-estimation algorithm for the fading amplitude, phase, and the
interference power spectral density (PSD) due to the combined interference and
thermal noise is proposed for DS-CDMA systems with irregular repeat-accumulate
codes. After initial estimates of the fading amplitude, phase, and interference
PSD are obtained from the received symbols, subsequent values of these
parameters are iteratively updated by using the soft feedback from the channel
decoder. The updated estimates are combined with the received symbols and
iteratively passed to the decoder. The elimination of pilot symbols simplifies
the system design and allows either an enhanced information throughput, an
improved bit error rate, or greater spectral efficiency. The interference-PSD
estimation enables DS-CDMA systems to significantly suppress interference.Comment: To appear, IEEE Transactions on Wireless Communication
Preprint: Using RF-DNA Fingerprints To Classify OFDM Transmitters Under Rayleigh Fading Conditions
The Internet of Things (IoT) is a collection of Internet connected devices
capable of interacting with the physical world and computer systems. It is
estimated that the IoT will consist of approximately fifty billion devices by
the year 2020. In addition to the sheer numbers, the need for IoT security is
exacerbated by the fact that many of the edge devices employ weak to no
encryption of the communication link. It has been estimated that almost 70% of
IoT devices use no form of encryption. Previous research has suggested the use
of Specific Emitter Identification (SEI), a physical layer technique, as a
means of augmenting bit-level security mechanism such as encryption. The work
presented here integrates a Nelder-Mead based approach for estimating the
Rayleigh fading channel coefficients prior to the SEI approach known as RF-DNA
fingerprinting. The performance of this estimator is assessed for degrading
signal-to-noise ratio and compared with least square and minimum mean squared
error channel estimators. Additionally, this work presents classification
results using RF-DNA fingerprints that were extracted from received signals
that have undergone Rayleigh fading channel correction using Minimum Mean
Squared Error (MMSE) equalization. This work also performs radio discrimination
using RF-DNA fingerprints generated from the normalized magnitude-squared and
phase response of Gabor coefficients as well as two classifiers. Discrimination
of four 802.11a Wi-Fi radios achieves an average percent correct classification
of 90% or better for signal-to-noise ratios of 18 and 21 dB or greater using a
Rayleigh fading channel comprised of two and five paths, respectively.Comment: 13 pages, 14 total figures/images, Currently under review by the IEEE
Transactions on Information Forensics and Securit
Frequency Domain Independent Component Analysis Applied To Wireless Communications Over Frequency-selective Channels
In wireless communications, frequency-selective fading is a major source of impairment for wireless communications. In this research, a novel Frequency-Domain Independent Component Analysis (ICA-F) approach is proposed to blindly separate and deconvolve signals traveling through frequency-selective, slow fading channels. Compared with existing time-domain approaches, the ICA-F is computationally efficient and possesses fast convergence properties. Simulation results confirm the effectiveness of the proposed ICA-F. Orthogonal Frequency Division Multiplexing (OFDM) systems are widely used in wireless communications nowadays. However, OFDM systems are very sensitive to Carrier Frequency Offset (CFO). Thus, an accurate CFO compensation technique is required in order to achieve acceptable performance. In this dissertation, two novel blind approaches are proposed to estimate and compensate for CFO within the range of half subcarrier spacing: a Maximum Likelihood CFO Correction approach (ML-CFOC), and a high-performance, low-computation Blind CFO Estimator (BCFOE). The Bit Error Rate (BER) improvement of the ML-CFOC is achieved at the expense of a modest increase in the computational requirements without sacrificing the system bandwidth or increasing the hardware complexity. The BCFOE outperforms the existing blind CFO estimator [25, 128], referred to as the YG-CFO estimator, in terms of BER and Mean Square Error (MSE), without increasing the computational complexity, sacrificing the system bandwidth, or increasing the hardware complexity. While both proposed techniques outperform the YG-CFO estimator, the BCFOE is better than the ML-CFOC technique. Extensive simulation results illustrate the performance of the ML-CFOC and BCFOE approaches
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