Multicarrier code division multiple access (MC-CDMA) combines the advantages of CDMA and orthogonal frequency division multiplexing techniques. For time-varying channels, it can be further improved by introducing an a...
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Multicarrier code division multiple access (MC-CDMA) combines the advantages of CDMA and orthogonal frequency division multiplexing techniques. For time-varying channels, it can be further improved by introducing an additional spreading in the time direction (extended MC-CDMA). Two low complexity iterative detection algorithms with soft feedback are described: the iterative soft block decision feedback equalizer and a recurrent neural network based detector. Performance results are given for a typical mobile radio channel and compared to the optimum maximum likelihood detector. Introducing pilot symbol assisted channel estimation, the optimum number of pilot symbols is determined and the bit error rate performance is compared to the case of ideal channel estimation.
In this work, we derive an analytical expression for the probability of false alarm for the generalized likelihood ratio test (GLRT) in the channel matrix-based sonar/radar framework when the waveform-independent colo...
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In this work, we derive an analytical expression for the probability of false alarm for the generalized likelihood ratio test (GLRT) in the channel matrix-based sonar/radar framework when the waveform-independent colored noise (WICN) covariance is assumed known. The derived expression is independent of the noise covariance and proves that the GLRT exhibits the constant probability of false alarm (CFAR) property. Monte Carlo simulations are performed to check the validity of the derived expression.
A performance evaluation study of two proposed distributed deadlock detection algorithms, the central controller and distributed deadlock detection algorithms, is described. The author examines and reports the magnitu...
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A performance evaluation study of two proposed distributed deadlock detection algorithms, the central controller and distributed deadlock detection algorithms, is described. The author examines and reports the magnitude by which these algorithms provide an increase in the throughput, and an increase in the number of blocked, restarted transactions. A performance evaluation model is presented for a distributed database environment. A list of performance parameters and evaluation criteria is included.< >
We discuss techniques for voice activity detection (VAD) for voice over Internet Protocol (VoIP). VAD aids in saving the bandwidth requirement of a voice session, thereby increasing the bandwidth efficiently. We compa...
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We discuss techniques for voice activity detection (VAD) for voice over Internet Protocol (VoIP). VAD aids in saving the bandwidth requirement of a voice session, thereby increasing the bandwidth efficiently. We compare the quality of speech, level of compression and computational complexity for three time-domain and three frequency-domain VAD algorithms. Implementation of time-domain algorithms is computationally simple. However, better speech quality is obtained with the frequency-domain algorithms. A comparison of the merits and demerits along with the subjective quality of speech after removal of silence periods is presented for all the algorithms. A quantitative measurement of speech quality for different algorithms is also presented.
In this paper, we focus on cyber attacks in the context of macroscopic transportation network models. For our studies, we consider a strip of freeway traffic network that is actuated on the upstream boundary by ramp-m...
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ISBN:
(数字)9781538682661
ISBN:
(纸本)9781538682678
In this paper, we focus on cyber attacks in the context of macroscopic transportation network models. For our studies, we consider a strip of freeway traffic network that is actuated on the upstream boundary by ramp-metering, which are controlled remotely from a centralized command center. In our framework, we first formulate analytical conditions for generating stealthy cyber-attacks using Aw-Rascle-Zhang (ARZ) macroscopic traffic model. Such conditions elucidate the capability of attackers and theoretical limitations of attack detection algorithms. Subsequently, we propose a design framework for cyber attack detection algorithms that considers several desirable detection characteristics such as stability, robustness and attack sensitivity. Finally, we illustrate the effectiveness of our framework via simulation studies.
In this article, design, performance and simulation of wavelet based OFDM V-BLAST MIMO system has been discussed. Wavelet based OFDM technique is based upon orthonormal wavelets bases generated from Haar quadrature mi...
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In this article, design, performance and simulation of wavelet based OFDM V-BLAST MIMO system has been discussed. Wavelet based OFDM technique is based upon orthonormal wavelets bases generated from Haar quadrature mirror filter (QMF) bank. The BER performance of this system has been observed with three different V-BLAST detection algorithms. The three V-BLAST detection algorithms implemented in this article are: zero forcing (ZF), minimum mean squared error (MMSE) and QR-decomposition based V-BLAST detection algorithms.
Recently, density evolution techniques have been used to predict the performance of iterative decoders utilizing the sum-product belief propagation algorithm. We extend this analysis to the min-sum algorithm for binar...
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Recently, density evolution techniques have been used to predict the performance of iterative decoders utilizing the sum-product belief propagation algorithm. We extend this analysis to the min-sum algorithm for binary codes. Using two representative applications, i.e., low-density parity-check (LDPC) codes and repeat accumulate (RA) codes, the sum-product and min-sum algorithms are compared. The results demonstrate a performance degradation of 0.27-1.03 dB for the min-sum algorithm, which confirms earlier simulation results. However, it is shown that a small modification to the min-sum algorithm results in an approximate sum-product algorithm, which performs at least as well as the original sum-product algorithm when finite message precision is considered.
Change point detection (CPD) has proved to be an effective tool for detecting drifts in data and its use over the years has become more pronounced due to the vast amount of data and IoT devices readily available. This...
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ISBN:
(数字)9798350353266
ISBN:
(纸本)9798350353273
Change point detection (CPD) has proved to be an effective tool for detecting drifts in data and its use over the years has become more pronounced due to the vast amount of data and IoT devices readily available. This study analyzes the effectiveness of Cumulative Sum (CUSUM) and Shewhart Control Charts for identifying the occurrence of abrupt pressure changes for pipe burst localization in Water Distribution Network (WDN). Change point detection algorithms could be useful for identifying the nodes that register the earliest and most drastic pressure changes with the aim of detecting pipe bursts in real-time. TSN et, a Python package, is employed in order to simulate pipe bursts in a WDN. The pressure readings are served to the pipe burst localization algorithm the moment they are available for real-time pie burst localization. The performance of the pipe burst localization algorithm is evaluated using a key metric such as localization accuracy under different settings to compare its performance when paired with either CUSUM or Shewhart. Results show that the pipe burst localization algorithm has an overall better performance when paired with CUSUM. Although, it does show great accuracy for both CPD algorithms when pressure readings are being continuously made available without a big gap between time steps. The proposed approach however still needs further experiments on different WDNs to assess the performance and accuracy of the algorithm on real-world WDN models.
This paper presented signal detection algorithms for IEEE 802.11a orthogonal frequency division multiplexing (OFDM) systems. Signal detection is to detect the arrival of the OFDM packets. Due to the burst transmission...
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ISBN:
(纸本)0780378296
This paper presented signal detection algorithms for IEEE 802.11a orthogonal frequency division multiplexing (OFDM) systems. Signal detection is to detect the arrival of the OFDM packets. Due to the burst transmission characteristics, a simple and robust signal detection algorithm is required for practical hardware implementation. In this paper, we designed and compared three signal detection algorithms, which were based on the short training sequence transmitted in front of each OFDM packet. Computer simulations were conducted to evaluate the performance of these three signal detection algorithms.
Online auction sites are a target for fraud. Researchers have developed fraud detection and prevention methods. However, there are difficulties when using either commercial or synthetic auction data to evaluate the ef...
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Online auction sites are a target for fraud. Researchers have developed fraud detection and prevention methods. However, there are difficulties when using either commercial or synthetic auction data to evaluate the effectiveness of these methods. When using commercial data, it is not possible to accurately identify cases of fraud. Using synthetic data, the conclusions drawn may not extend to the real world. The availability of realistic synthetic auction data, which models real auction data, will be invaluable for effective evaluation of fraud detection algorithms. We present an agent-based simulator that is capable of generating realistic English auction data. The agents and model are based on data collected from the Trade Me online auction site. We evaluate the generated data in two ways to show that it is similar to the Trade Me auction data we have collected. In addition, we demonstrate that the simulator can have additional agents added to simulate fraudulent behaviour, and be used to evaluate fraud detection algorithms: we implement three different fraud behaviours and three detection algorithms, and using the simulator, compare the ability of the detection algorithms to correctly identify fraudulent agents.
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