[show abstract][hide abstract] ABSTRACT: Currently, single sample biometrics recognition (SSBR) has emerged as one of the major research contents. It may lead to bad
recognition result. To solve this problem, we present a novel approach by fusing two kinds of hand-based biometrics, i.e.,
palmprint and middle finger. We obtain their discriminant features by combining statistical information and structural information
of each modal which are extracted using locality preserving projection (LPP) based on wavelet transform (WT). In order to
reduce the influence of affine transform, we utilize mean filtering to enhance the robustness of structural information to
improve the discriminant ability of palmprint high-frequency sub-bands. The two types of features are then fused at score
level for the final hand-based SSBR. The experiments on the hand image database that contains 1,000 samples from 100 individuals
show that the proposed feature extraction and fusion methods lead to promising performance.
KeywordsSingle sample biometrics recognition–Palmprint and middle finger biometrics–Wavelet transform–Structural feature enhancement–Feature fusion
Neural Computing and Applications 04/2012; · 1.17 Impact Factor
[show abstract][hide abstract] ABSTRACT: Multicell coordinated beamforming (MCBF), where multiple base stations (BSs) collaborate with each other in the beamforming design for mitigating the intercell interference (ICI), has been a subject drawing great attention recently. Most MCBF designs assume perfect channel state information (CSI) of mobile stations (MSs); however CSI errors are inevitable at the BSs in practice. Assuming elliptically bounded CSI errors, this paper studies the robust MCBF design problem that minimizes the weighted sum power of BSs subject to worst-case signal-to-interference-plus-noise ratio (SINR) constraints on the MSs. Our goal is to devise a distributed optimization method to obtain the worst-case robust beamforming solutions in a decentralized fashion with only local CSI used at each BS and limited backhaul information exchange between BSs. However, the considered problem is difficult to handle even in the centralized form. We first propose an efficient approximation method for solving the nonconvex centralized problem, using semidefinite relaxation (SDR), an approximation technique based on convex optimization. Then a distributed robust MCBF algorithm is further proposed, using a distributed convex optimization technique known as alternating direction method of multipliers (ADMM). We analytically show the convergence of the proposed distributed robust MCBF algorithm to the optimal centralized solution. We also extend the worst-case robust beamforming design as well as its decentralized implementation method to a fully coordinated scenario. Simulation results are presented to examine the effectiveness of the proposed SDR method and the distributed robust MCBF algorithm.
IEEE Transactions on Signal Processing - TSP. 01/2012; 60(6):2988-3003.
[show abstract][hide abstract] ABSTRACT: Signal-Time Coding (STC), a novel transmission mechanism, was proposed recently. It combines the traditional encoding/modulation mode in the signal domain with the signal pulse phase modulation in the time domain and can achieve higher information flow rate in some cases for relay networks. However, there are still many fundamental problems to be investigated. This paper considers the implementing issue of STC in AWGN relay networks. Firstly, an energy detection based STC (ED-STC) scheme is proposed and the error probabilities of ED-STC in both the signal domain and the time domain are given. Secondly, a performance evaluation criterion, the reliable information per symbol (RIPS), is proposed to characterize the performance of STC in noisy wireless networks. Moreover, the performance bounds of the RIPS of ED-STC are derived. Numerical analysis show that ED-STC outperforms traditional transmission method in terms of effective information rate within some practical conditions.
Communications (ICC), 2011 IEEE International Conference on; 07/2011
[show abstract][hide abstract] ABSTRACT: Multi-cell coordinated beamforming (MCBF), where multiple base stations (BSs)
collaborate with each other in the beamforming design for mitigating the
inter-cell interference, has been a subject drawing great attention recently.
Most MCBF designs assume perfect channel state information (CSI) of mobile
stations (MSs); however CSI errors are inevitable at the BSs in practice.
Assuming elliptically bounded CSI errors, this paper studies the robust MCBF
design problem that minimizes the weighted sum power of BSs subject to
worst-case signal-to-interference-plus-noise ratio (SINR) constraints on the
MSs. Our goal is to devise a distributed optimization method that can obtain
the worst-case robust beamforming solutions in a decentralized fashion, with
only local CSI used at each BS and little backhaul signaling for message
exchange between BSs. However, the considered problem is difficult to handle
even in the centralized form. We first propose an efficient approximation
method in the centralized form, based on the semidefinite relaxation (SDR)
technique. To obtain the robust beamforming solution in a decentralized
fashion, we further propose a distributed robust MCBF algorithm, using a
distributed convex optimization technique known as alternating direction method
of multipliers (ADMM). We analytically show the convergence of the proposed
distributed robust MCBF algorithm to the optimal centralized solution and its
better bandwidth efficiency in backhaul signaling over the existing dual
decomposition based algorithms. Simulation results are presented to examine the
effectiveness of the proposed SDR method and the distributed robust MCBF
[show abstract][hide abstract] ABSTRACT: Multicell coordinated beamforming (MCBF) has been recognized as a promising
approach to enhancing the system throughput and spectrum efficiency of wireless
cellular systems. In contrast to the conventional single-cell beamforming (SBF)
design, MCBF jointly optimizes the beamforming vectors of cooperative base
stations (BSs) (via a central processing unit(CPU)) in order to mitigate the
intercell interference. While most of the existing designs assume that the CPU
has the perfect knowledge of the channel state information (CSI) of mobile
stations (MSs), this paper takes into account the inevitable CSI errors at the
CPU, and study the robust MCBF design problem. Specifically, we consider the
worst-case robust design formulation that minimizes the weighted sum
transmission power of BSs subject to worst-case
signal-to-interference-plus-noise ratio (SINR) constraints on MSs. The
associated optimization problem is challenging because it involves infinitely
many nonconvex SINR constraints. In this paper, we show that the worst-case
SINR constraints can be reformulated as linear matrix inequalities, and the
approximation method known as semidefinite relation can be used to efficiently
handle the worst-case robust MCBF problem. Simulation results show that the
proposed robustMCBF design can provide guaranteed SINR performance for the MSs
and outperforms the robust SBF design.
[show abstract][hide abstract] ABSTRACT: Biometric cryptosystem has emerged as a promising solution in information security. Fuzzy vault is a widely accepted scheme binding biometric data and cryptography effectively. Polynomial projection is often used in the implementation of fuzzy vault. However, the drawback of polynomial projection is that the increase of key length would lead to a higher degree of polynomial, reconstruction of which would cause poor convergence in practice. To resolve the problem, we propose a new fuzzy vault method based on cubic spline interpolation. The piecewise low-degree polynomial of spline interpolation could overcome poor convergence problem and much longer key could be generated. Because the security of the fuzzy vault arises from the number of chaff points in the vault, the same security level could be guaranteed compared to polynomial reconstruction based fuzzy vault. Experimental results based on HA-BJTU palm print database show the feasibility of the proposed method and performances are satisfied.
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on; 11/2010
[show abstract][hide abstract] ABSTRACT: Single sample biometrics recognition may lead to bad recognition result in real-world applications. To solve this problem, we present a novel feature level biometrics fusion approach by combining two kinds of biometrics: palmprint and middle finger image, both of which can be acquired from one hand image. We first utilize a manifold learning method to find the local embedding subspaces of palmprint and middle finger images, and then use principal component analysis (PCA) to extract the concatenated feature. To do so, a well performance could be obtained for the reason that the local structures of single model biometrics are preserved, while the redundancies between them are reduced. Comparing with single modal biometrics and score level fusion, the experimental results illustrated the average recognition rate of the proposed approach was significantly promoted to 98.71%. The performance comparisons in terms of cumulative match characteristic (CMC) curves for different recognition approaches were also presented to demonstrate the strength of the proposed fusion scheme.
Emerging Techniques and Challenges for Hand-Based Biometrics (ETCHB), 2010 International Workshop on; 09/2010
[show abstract][hide abstract] ABSTRACT: Biometrics is emerging as the most foolproof method of automated personal identification. And fusing the scores of several biométrie systems is a very promising approach to improve the overall system's accuracy. Fusion operators, which contain sum rule, product rule, max rule and min rule, are considered to be one of the most useful schemes at score-level fusion, while the optimal fusion operator is chosen experimentally in real-world classification tasks. In this paper, a novel method is presented for optimal fusion operator selection. We estimate the PDF (probability density function) of each representation. Assuming that the representations used are conditionally statistically independent, then the PDFs of the fusion operators can be calculated. As a result, the distance between the class of genuine and impostor based on PDF can be used to evaluate the capabilities of fusion operators. It provides a theoretical support to evaluate the performances of fusion operators, and enables adaptive selection without experimentation. Its effectiveness when applied to bimodal biométrie authentication is confirmed by the results of 21 experiments.
[show abstract][hide abstract] ABSTRACT: Noncoherent receivers are attractive for ultra wideband (UWB) impulse radio systems due to the implementation simplicity. Recently, a block differential transmission scheme was proposed to improve the maximum achievable data rate of noncoherent UWB systems. In this paper, based on the generalized likelihood ratio test (GLRT) optimization criterion, we derive a novel multiple symbol differential detection (MSDD) receiver under block differential transmission framework. Compared with the conventional symbol-by-symbol differential detection (DD) receiver, the proposed MSDD receiver has better performance at the cost of increased computational complexity. We thus propose a reduced-complexity implementation of the MSDD by using a two-step search strategy.
Networks Security, Wireless Communications and Trusted Computing, International Conference on. 01/2010; 1:11-14.
[show abstract][hide abstract] ABSTRACT: Recently, an energy efficient noncoherent receiver scheme, called codeword matching and signal aggregation (CMSA), has been proposed for ultra-wideband (UWB) communications. However, its optimality and analytical error performance have not been studied. This letter shows the CMSA receiver is the optimal receiver in the sense of generalized likelihood ratio test (GLRT) and presents closed-form upper bound expression for bit error probability (BEP).
[show abstract][hide abstract] ABSTRACT: The paper considers MIMO relay networks where a source node transmits the signals to a destination node through multiple relay nodes, each of which is equipped with multiple antennas. As shown by previous studies, using multiple relay nodes to forward the signals can improve the performance. The distributed array gain can be achieved at the destination node while maintaining the maximum spatial multiplexing gain when the zero-forcing (ZF) weighting matrices are applied at the relay nodes. However, this relaying scheme cannot obtain the receive array gain simultaneously. To overcome the disadvantage, we propose a novel multiple relay nodes selection scheme based on the criterion of maximizing the minimum received SNR among all antennas at the destination node to enhance the diversity gain and the array gain. Simulation results confirm the superiority of our proposed selection scheme over the conventional ZF MIMO relaying scheme.
Proceedings of the 72nd IEEE Vehicular Technology Conference, VTC Fall 2010, 6-9 September 2010, Ottawa, Canada; 01/2010
[show abstract][hide abstract] ABSTRACT: Biometric cryptosystem has emerged as a promising solution in information security. Fuzzy vault is a widely accepted scheme that binding biometric data and cryptography effectively. In vault encoding, random chaff points which are not on the polynomial are added to protect genuine points. In vault decoding, query biometric data is generated to retrieve the genuine points by measuring the distance between the registered data and query data. However, because of the within-class differences and randomness of chaff points, it is difficult to distinguish the genuine data from chaff data. This paper proposes a novel 3D fuzzy vault scheme that selects unused data from template feature vector and inserts it into the genuine points. In our scheme, every point in the vault has three dimensions, two of which could be used for distance measurement. The precision of the data matching is improved by the new inserted data and genuine points could be recognized more accurately. Experimental results based on HA-BJTU database show the better performances compared to traditional fuzzy vault.
Cyber-Enabled Distributed Computing and Knowledge Discovery, International Conference on. 01/2010;
[show abstract][hide abstract] ABSTRACT: In this paper, a modified sequential probability ratio test (SPRT) scheme, namely sequential energy detection (SED), is proposed for cooperative spectrum sensing to reduce the average number of required samples. In the scheme, the data samples are first grouped into data blocks and the sequential probability ratio test (SPRT) use the energies of the data blocks as the statistics variables. The resulting detection rule exhibits simplicity in implementation and in analysis and avoid the deterministic knowledge of primary signals. The detection performance in terms of average sample number (ASN) is evaluated theoretically. Numerical results are provided to verify the theoretical analysis.
[show abstract][hide abstract] ABSTRACT: For transmit beamforming in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, channel state information (CSI) need to be available to the transmitter. Clustering is an effective approach to reduce the data rate of CSI feedback. In this paper, different clustering schemes are investigated, and a new clustering method based on mean channel response is proposed. Further, we present an effective feedback reduction method, where the residual frequency correlation of adjacent clusters is exploited to reduce the feedback overhead. The simulation results show that the proposed clustering method has the similar BER performance with low computation complexity relative to the SNR-maximizing clustering, and the feedback reduction approach can reduce remarkably the feedback rate with some performance loss.
Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5th International Conference on; 10/2009
[show abstract][hide abstract] ABSTRACT: In cognitive radio networks, multiple cognitive radio nodes perform spectrum sensing cooperatively in order to detect the primary user more accurately. Previous works on cooperative spectrum sensing have shown that the detection performance can be improved through increasing either the observation interval or the number of the sensing nodes. However, increasing the observation interval will result in the reduction of transmit efficiency and the agility of cognitive users, and at the same time increasing the number of sensing nodes may lead to the overhead increase of control channel and computational complexity. In this paper, we formulate the tradeoff relation between the observation interval and the number of the sensing nodes under the constraint of required detection performance. The numerical results show the proposed relation.
Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5th International Conference on; 10/2009
[show abstract][hide abstract] ABSTRACT: The peak signal-to-noise ratio (PSNR) is a simple and widely used fidelity measure in the image watermarking. The position of watermarking plays an important role when the tradeoff between robustness and invisibility is considered. In the paper we analyze the mathematical relationship between the embeddable position and the PSNR in the DCT (discrete cosine transform) domain. We consider DC (direct current) coefficient to tradeoff robustness and invisibility. And a blind watermarking scheme is implemented through quantization index modulation (QIM) technology. Experimental results show watermarking is robust to common signal processing operation such as additional noise, filtering, resizing and JPEG compressing, and invisibility is satisfaction.
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on; 01/2009