Qilian Liang

Tianjin Normal University, T’ien-ching-shih, Tianjin Shi, China

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Publications (182)97.69 Total impact

  • Ishrat Maherin · Qilian Liang
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    ABSTRACT: In this paper, we propose a multistep information fusion scheme for target detection through foliage and wall, using ultrawideband (UWB) radar sensor networks. We apply an information theory to detect target with poor signal quality in dynamic forest-environment. This method is motivated by the fact that echoes from the stationary target that is obscured by foliage has strong random characteristics. This is resolved by three steps of information fusion. For the first step of information fusion, we use Kullback–Leibler divergence-based weighting and generated a modified histogram. In the second step, we use entropy- and mutual information-based information fusion. Finally, we use three different fusion methods: 1) Dempster and Shafer theory of evidence; 2) proportional conflict redistribution rule 5; and 3) Bayesian network for decision fusion. Results show that when echoes are in poor quality, accurate detection can be achieved by applying our method. To demonstrate that our algorithm could be applied to other scenarios, we apply it to sense-through-wall human detection using different UWB radars, and simulation results show that our approach works well.
    IEEE Sensors Journal 10/2015; 15(10):5927-5937. DOI:10.1109/JSEN.2015.2451160 · 1.85 Impact Factor
  • Qilian Liang · Jian Ren · Jing Liang · Baoju Zhang · Yiming Pi · Chenglin Zhao
    Security and Communication Networks 09/2015; 8(14). DOI:10.1002/sec.1332 · 0.72 Impact Factor
  • Xin Wang · Qilian Liang
    IEEE Systems Journal 01/2015; DOI:10.1109/JSYST.2015.2391284 · 1.75 Impact Factor
  • Ishrat Maherin · Qilian Liang
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    ABSTRACT: In this paper, we propose to apply information theory to Ultra wide band (UWB) radar sensor network (RSN) to detect target in foliage environment. Information theoretic algorithms such as Maximum entropy method (MEM) and mutual information are proven methods, that can be applied to data collected by various sensors. However, the complexity of the environment posses uncertainty in fusion center. Chernoff information provides the best error exponent of detection in Bayesian environment. In this paper, we consider the target detection as binary hypothesis testing and use Chernoff information as sensor selection criterion, which significantly reduce the processing load. Another strong information theoretic algorithm, method of types, is applicable to our MEM based target detection algorithm as entropy is dependent on the empirical distribution only. Method of types analyze the probability of a sequence based on empirical distribution. Based on this, we can find the bound on probability of detection. We also propose to use Relative entropy based processing in the fusion center based on method of types and Chernoff Stein Lemma. We study the required quantization level and number of nodes in gaining the best error exponent. The performance of the algorithms were evaluated, based on real world data.
    Physical Communication 12/2014; 13. DOI:10.1016/j.phycom.2014.01.003
  • Junjie Chen · Qilian Liang
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    ABSTRACT: In this paper, rate distortion performance of nested sampling and coprime sampling is studied. It is shown that with the increasing of distortion, the data rate decreases. With these two sparse sampling algorithms, the data rate is proved to be much less than that without sparse sampling. With the increasing of sampling spacings, the data rate decreases at certain distortion, which is because with more sparse sampling, less number of bits is required to represent the information. We also prove that with the same sampling pairs, the rate of nested sampling is less than that of coprime sampling at the same distortion. The reason is that nested sampling collects a little less number of samples than coprime sampling with the same length of data, which is a little sparser than coprime sampling.
    Journal on Advances in Signal Processing 11/2014; 2014(1). DOI:10.1186/1687-6180-2014-18 · 0.81 Impact Factor
  • Zhuo Li · Qilian Liang · Xiuzhen Cheng
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    ABSTRACT: Considering the power saving potential of the emerging WiFi Direct technique, we evaluate the performance of WiFi Direct technique in Home Area Networks (HANs) for Smart Grid Communication from two aspects: power consumption and downlink outage performance. By modeling the traffic intensity and the number of working devices in a dynamic HAN as a Markov chain, the power consumption of the dynamic HAN with Power Saving Mechanism (PSM) and the conventional static HAN with Continuous Active Mode (CAM) are evaluated and compared. On the other hand, the probability density function (PDF) of the signal to interference and noise ratio (SINR) for the active user connected in the HAN is derived from the amplitude distribution property of the classical indoor Saleh-Valenzuela (S-V) channel. The numerical results show that WiFi Direct technique not only improves the power saving in the HAN for Smart Grid, but also enhances the reliability of HAN communications for Smart Grid.
    Ad Hoc Networks 11/2014; 22. DOI:10.1016/j.adhoc.2014.05.004 · 1.94 Impact Factor
  • Source
    Wireless Communications and Mobile Computing 09/2014; 14(13). DOI:10.1002/wcm.2513 · 1.29 Impact Factor
  • Ji Wu · Wei Wang · Qilian Liang · Xiaorong Wu · Baoju Zhang
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    ABSTRACT: In this paper, we propose a new compressive sensing-based compression and recovery ultra-wideband (UWB) communication system. Compared with the conventional UWB system, we can jointly estimate the channel and compress the data, which can also simplify the design of hardware. No information about the transmitted signal is required in advance as long as the channel follows autoregressive process. As an application example, real-world UWB signal is collected and processed to evaluate the performance of our proposed system. The compression procedure is so simple that we just multiply random Gaussian or Bernoulli matrix with the original data to capture all the information we want. Simulation results show that the data could be perfectly recovered if the compression ratio does not exceed 2.5:1 when Bernoulli matrix is chosen as the sensing matrix. Copyright © 2012 John Wiley & Sons, Ltd.
    Wireless Communications and Mobile Computing 09/2014; 14(13). DOI:10.1002/wcm.2228 · 1.29 Impact Factor
  • Qiong Wu · Qilian Liang
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    ABSTRACT: This paper studies higher-order statistics of non-Gaussian signal using temporal co-prime sampling. We extend co-prime sampling to pairwise co-prime sequences (PCS) to derive higher-order statistics (HOS), and analyze the computational complexity of PCS-based HOS algorithm for both parametric and nonparametric methods. Compared to the existing HOS algorithms, the proposed algorithm vastly reduces the computation complexity by several orders in terms of the length of segmentation window. We also apply PCS-based HOS algorithm to estimate the coefficients of simplified LTE spacial channel model only based on its outputs. Our simulations show that 3rd-order PCS-based HOS achieves 80% performance gain compared to the existing HOS with the same computational complexity, or it has 12% performance loss with 15% complexity compared to the counterpart processing the same length of signal.
    ICC 2014 - 2014 IEEE International Conference on Communications; 06/2014
  • Qiong Wu · Qilian Liang
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    ABSTRACT: This paper proposes an algorithm deriving higher-order statistics (HOS) from co-prime sampled sequences and implements it in the order determination of the parametric approach for modeling ultra-wide bandwidth indoor channel. We extend the co-prime sampling to pairwise co-prime sequences, and apply singular value decomposition in the matrix formed by third-order cumulants for the order determination of autoregressive model. We also analyze the variance of third-order cumulants and use their basic characteristic to determine the order of moving average model. In simulations, the proposed algorithm reduces the computational complexity to 17% of the existing HOS algorithms with negligible performance loss in high noise-to-signal ratio (SNR) environment. In low SNR scenario, the proposed algorithm is more sensitive to order mismatch in terms of the variances of expectations, which makes it a more reliable indicator to confirm the correct order.
    ICC 2014 - 2014 IEEE International Conference on Communications; 06/2014
  • Xiaoyang Li · Qilian Liang · Francis CM Lau
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    ABSTRACT: A maximum likelihood routing algorithm for smart grid wireless networks is proposed in this paper. It is designed to select the meters as relays in smart grid wireless networks and to calculate the probability of being selected based on the battery levels and the transmission distances. After describing the applied environment, the routing principle and the system model are explained in details. Finally, the proposed algorithm is compared with other two simple methods: a random method and a maximum method. The comparison results show that the maximum likelihood method can extend the lifetime of smart grid wireless network.
    EURASIP Journal on Wireless Communications and Networking 05/2014; 2014(1):75. DOI:10.1186/1687-1499-2014-75 · 0.81 Impact Factor
  • Na Wu · Qilian Liang
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    ABSTRACT: This paper firstly introduces nested sampling and co-prime sampling, which were proposed recently, but have never been applied to real world target detection. We apply nested sampling and co-prime sampling to target detection in UWB radar sensor networks (RSN), based on a differential approach. The non-stationary UWB signal needs to be decomposed into several approximate wide sense stationary (WSS) signals so that nested sampling could be used in this situation. We also compare the performance of nested sampling and co-prime sampling against uniform under-sampling. The results show that in terms of good quality data and poor quality data, both nested sampling and co-prime sampling work better.
    Physical Communication 02/2014; 13. DOI:10.1016/j.phycom.2014.02.001
  • Ashith Kumar · Zhuo Li · Qilian Liang · Baoju Zhang · Xiaorong Wu
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    ABSTRACT: Measurement of weak signals is very challenging since the signals may be buried by noise. In this paper, we study measurement of sense-through-wall signals using UWB radar sensors, and measurements show that the collected signals due to respiratory movement of human target are very weak. Based on the measurements, we perform through-wall human detection. The detection of human targets hidden by walls, or trapped in buildings is of interest for rescue, surveillance and security operations. In this paper, experiments on through-wall human detection using the ultra wideband (UWB) radar PulsOn 220 in monostatic mode are carried out in two scenarios: through gypsum wall, and through wooden door. And three analytic methods are employed for the detection: normalized difference square matrix method, reference moving average method with Discrete Fourier Transform (DFT), and Empirical Mode Decomposition (EMD) from Hilbert Huang Transform, of which the breathing information of the human target is contained in the third intrinsic mode function (IMF3). The experimental results for the human target detection behind the wall are demonstrated and thus compared using these three methods. It shows that the distance of the human target to the UWB radar could be approximately estimated by the normalized difference square matrix method and the reference moving average method. As to Hilbert Huang Transform, even though the existence of the through-wall human target can be clearly detected, the range information is ambiguous.
    Measurement 01/2014; 47(1):869-879. DOI:10.1016/j.measurement.2013.10.016 · 1.53 Impact Factor
  • Xiaoyang Li · Qilian Liang · Francis C.M. Lau
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    ABSTRACT: In this paper, a method for through-wall human detection based on the singular values decomposition of the measurement matrices is presented. After demonstrating the sparsity of the matrices using CLEAN algorithm, an SVD algorithm based on Lanczos process is applied to compute their singular values. We also analyze the singular values of matrices constructed by difference square techniques for different types of walls and compare our algorithm with a 2-D imaging approach proposed by researchers in Time Domain Company. Detection results show that our method performs well in gypsum wall, brick wall, and wooden door.
    Physical Communication 12/2013; 13. DOI:10.1016/j.phycom.2013.12.002
  • Junjie Chen · Qilian Liang
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    ABSTRACT: In this paper, we analyzed the performance of noisy compressive sensing theoretically, and derived both the lower bound and upper bound of the probability of error for compressive sensing, with the assumption that both the original information and the noise follow Gaussian distribution. Both the lower bound and upper bound of the probability of error for the general case without special requirement of the measurement matrix Φ are provided. It has been shown that under some condition, perfect reconstruction of the information vector is impossible, as there will always be certain error. Specially, when the Bernoulli matrix is chosen as the measurement matrix, the corresponding lower bound and upper bound of the probability of error are given with a much neat and clear expression. The corresponding Cramer-Rao lower bound is also provided. These results provide some theoretical reference of the probability of error of compressive sensing.
    GLOBECOM 2013 - 2013 IEEE Global Communications Conference; 12/2013
  • Xin Wang · Qilian Liang
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    ABSTRACT: Cooperative diversity techniques have emerged as promising solutions to combat the deleterious effects caused by multipath fading. The main advantage of this technique is that the diversity gain can be achieved without installing multiple antennas at the transmitter or the receiver. In this paper, we study the ergodic capacity performance of cooperative communication systems with decode-and-forward (DF) relaying protocol over Nakagami-m fading channels. Specifically, the ergodic capacity over both independent identically distributed (i.i.d.) fading channels and independent non-identically distributed (i.n.d.) fading channels are investigated. We first explore the ergodic capacity over i.i.d. fading channels, and then derive the tight bounds for the ergodic capacity at the regime of low signal-to-noise (SNR) and high SNR, respectively. Further, we obtain an exact closed-form analytical expression of the ergodic capacity over i.n.d. fading channels. Finally, the Monte-Carlo simulations are provided to verify the tightness of the proposed bounds. The theoretical results obtained are instrumental to the future cooperative-diversity network modeling and design.
    GLOBECOM 2013 - 2013 IEEE Global Communications Conference; 12/2013
  • Qilian Liang · Baoju Zhang · Chenglin Zhao · Yiming Pi
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    ABSTRACT: The measurement of an emitter's position using electronic support passive sensors is termed passive localization and plays an important part both in electronic support and electronic attack. The emitting target could be in terrestrial or underwater environment. In this paper, we propose a time difference of arrival (TDoA) algorithm for passive localization in underwater and terrestrial environment. In terrestrial environment, it is assumed that a Rician flat fading model should be used because there exists line of sight. In underwater environment, we apply a modified UWB Saleh-Valenzuela (S-V) model to characterize the underwater acoustic fading channel. We propose the TDoA finding algorithm via estimating the delay of two correlated channels, and compare it with the existing approach. Simulations were conducted for terrestrial and underwater environment, and simulation results show that our TDoA algorithm performs much better than the cross-correlation-based TDoA algorithm with a lower level of magnitude in terms of average TDoA error and root-mean-square error (RMSE). Compared to the TDoA performance in terrestrial environment, the TDoA performance in underwater environment is much worse. This is because the underwater channel has clusters and rays, which introduces memory and uncertainties. For the two scenarios in underwater environment, the performance in rich scattering underwater environment is worse than that in less scattering underwater environment, because the latter has less clusters and rays, which would cause less uncertainties in TDoA.
    IEEE Transactions on Parallel and Distributed Systems 10/2013; 24(10):2100-2108. DOI:10.1109/TPDS.2012.310 · 2.17 Impact Factor
  • Ishrat Maherin · Qilian Liang
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    ABSTRACT: One of the biggest challenges in cognitive radio CR network is to maximise the throughput of the secondary user while keeping the interference to the primary under the interference threshold. Efficient spectrum sensing along with transmit power control can achieve this conflicting goal. In this paper, we propose a sensor network aided cognitive radio system which will reduce the missed detection and reduce the interference. We investigate the performance of various sensing and power allocation schemes for an OFDM-based cognitive radio system. We formulate an optimisation problem to design the optimal sensing time and transmit power. Mathematical analysis shows that interference between primary and secondary in OFDM-based system depends on spectral distance. Results show that distance dependent modified water filling DDMWF scheme can achieve the highest data rate for the cognitive radio based secondary user and then the optimal sensing time can be designed to maximise the throughput.
    International Journal of Sensor Networks 07/2013; 13(4):234-240. DOI:10.1504/IJSNET.2013.055586 · 1.39 Impact Factor
  • Qiong Wu · Qilian Liang
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    ABSTRACT: Estimating the spectrogram of non-stationary signal relates to many important applications in radar signal processing. In recent years, coprime sampling and array attract attention for their potential of sparse sensing with derivative to estimate autocorrelation coefficients with all lags, which could in turn calculate the power spectrum density. But this theoretical merit is based on the premise that the input signals are wide-sense stationary. In this paper, we take the first step to design coprime sampling algorithm using with non-stationary signal and discuss how to attain the benefits of coprime sampling meanwhile limiting the disadvantages due to lack of observations for estimations.
    2013 ICC - 2013 IEEE International Conference on Communication Workshop (ICC); 06/2013
  • Xin Wang · Qilian Liang
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    ABSTRACT: In this paper, we investigate the theoretical per-node transmission limit of hybrid wireless networks over fading channels. We formulate a hybrid wireless network model, in which a wired network of base stations is deployed to support long-range communications between wireless nodes. Two types of transmission mode, the so called intra-cell transmission mode and the infrastructure transmission mode are considered. Aiming to effectively overcome the fading impairments, we introduce an optimal multiple access technique allowing opportunistic sources to transmit concurrently with the scheduled source. A successive interference cancelation (SIC) strategy is then applied at the receiver to limit the intra-cell interference and achieve the maximum throughput. In addition, the frequency reuse scheme is employed to minimize the inter-cell interference. We first study the scaling laws for outage throughput capacity in the slow fading scenario and provide the closed-form analytical expressions for the outage throughput capacity at the regime of high signal-to-interference-plus-noise ratio (SINR). The ergodic throughput capacity, which serves as the performance criterion for fast fading situation, is then explored. We derive the tight bounds for ergodic throughput capacity at low SINR and high SINR scenarios, respectively. Finally, we provide the detailed quality of service (QoS) performance analysis in terms of the per-node average error probability (AEP). The theoretical bounds obtained are instrumental to the future energy-limited network modeling and design.
    IEEE Transactions on Wireless Communications 06/2013; 12(6):2930-2940. DOI:10.1109/TWC.2013.041913.121236 · 2.76 Impact Factor

Publication Stats

1k Citations
97.69 Total Impact Points

Institutions

  • 2011–2014
    • Tianjin Normal University
      T’ien-ching-shih, Tianjin Shi, China
    • George Washington University
      • Department of Computer Science
      Washington, D. C., DC, United States
  • 2002–2014
    • University of Texas at Arlington
      • Department of Electrical Engineering
      Arlington, Texas, United States
  • 2012
    • Signal Processing Inc.
      Роквилл, Maryland, United States