Hsiao-Chun Wu

Physical layer security in wireless networks: a tutorial

Wireless networking plays an extremely important role in civil and military applications. However, security of information transfer via wireless networks remains a challenging issue. It is critical to ensure that confidential data are accessible only to the intended users rather than intruders. Jamming and eavesdropping are two primary attacks at the physical layer of a wireless network. This article offers a tutorial on several prevalent methods to enhance security at the physical layer in wireless networks. We classify these methods based on their characteristic features into five categories, each of which is discussed in terms of two metrics. First, we compare their secret channel capacities, and then we show their computational complexities in exhaustive key search. Finally, we illustrate their security requirements via some examples with respect to these two metrics.

Novel Automatic Modulation Classification Using Cumulant Features for Communications via Multipath Channels

Nowadays, automatic modulation classification (AMC) plays an important role in both cooperative and non-cooperative communication applications. Very often, multipath fading channels result in the severe AMC performance degradation or induce large classification errors. The negative impacts of multipath fading channels on AMC have been discussed in the existing literature but no solution has ever been proposed so far to the best of our knowledge. In this paper, we propose a new robust AMC algorithm, which applies higher-order statistics (HOS) in a generic framework for blind channel estimation and pattern recognition. We also derive the Cramer-Rao lower bound for the fourth-order cumulant estimator when the AMC candidates are BPSK and QPSK over the additive white Gaussian noise channel, and it is a nearly minimum-variance estimator leading to robust AMC features in a wide variety of signal-to-noise ratios. The advantage of our new algorithm is that, by carefully designing the essential features needed for AMC, we do not really have to acquire the complete channel information and therefore it can be feasible without any a priori information in practice. The Monte Carlo simulation results show that our new AMC algorithm can achieve the much better classification accuracy than the existing AMC techniques.

Analysis and characterization of intercarrier and interblock interferences for wireless mobile OFDM systems

OFDM has been applied in a wide variety of wireless communications in recent years since it has the advantage over the conventional single-carrier modulation schemes when enduring the frequency-selective fading. However, intercarrier-interference (ICI) and interblock interference (IBI) due to the Doppler effect, carrier frequency drift of local oscillators and multipath fading limit the capability of OFDM systems. In this paper, a new generalized mathematical model for intercarrier and interblock interferences is derived for wireless mobile OFDM systems, in which Doppler frequency drift, local carrier frequency offset, multipath fading, and cyclic prefix coding are all present in reality. Such a new ICI/IBI model can be applied for OFDM performance evaluation in different environments. This new formulation of IBI and ICI provides a generalized framework which includes special ICI models appearing in the previous literature. Besides, the derived OFDM performance evaluation analysis in this paper can greatly benefit OFDM designers for wireless multimedia networks and digital video broadcasting technologies.

Robust and Efficient Intercarrier Interference Mitigation for OFDM Systems in Time-Varying Fading Channels

Due to its spectral efficiency and robustness over multipath channels, orthogonal frequency-division multiplexing (OFDM) has served as one of the major modulation schemes for high-speed communication systems. In the future, wireless OFDM systems are expected to operate at high carrier frequencies, high speed, and high throughput for mobile reception, where fast time-varying fading channels are encountered. Channel variation destroys the orthogonality among the subcarriers and leads to intercarrier interference (ICI). ICI poses a significant limitation on wireless OFDM systems. The aim of this paper is to find an efficient method of providing reliable communications using OFDM in fast time-varying fading channels. It is observed that ICI power arises from a few adjacent subcarriers. This observation motivates us to design low-complexity -tap ICI equalizers. To employ these equalizers, channel state information is also required. In this paper, we also design a pilot-aided minimum mean square error (MMSE) channel estimation scheme for a time-varying wide-sense stationary uncorrelated scatters channel model. The MMSE channel estimator utilizes the statistical channel properties to achieve computational efficiency. Simulation results show that our proposed low-complexity ICI suppression scheme, which incorporates the -tap equalizer with the MMSE channel estimator, can significantly improve the performance of OFDM systems in fast time-varying fading channels.

Biologically Inspired Cooperative Routing for Wireless Mobile Sensor Networks

Biological systems present remarkable adaptation, reliability, and robustness in various environments, even under hostility. Most of them are controlled by the individuals in a distributed and self-organized way. These biological mechanisms provide useful resources for designing the dynamical and adaptive routing schemes of wireless mobile sensor networks, in which the individual nodes should ideally operate without central control. This paper investigates crucial biologically inspired mechanisms and the associated techniques for resolving routing in wireless sensor networks, including Ant-based and genetic approaches. Furthermore, the principal contributions of this paper are as follows. We present a mathematical theory of the biological computations in the context of sensor networks; we further present a generalized routing framework in sensor networks by diffusing different modes of biological computations using Ant-based and genetic approaches; finally, an overview of several emerging research directions are addressed within the new biologically computational framework.

Joint phase/amplitude estimation and symbol detection for wireless ICI self-cancellation coded OFDM systems

OFDM has been applied in the current wireless local-area networks and digital video broadcasting systems since it has the advantage over the conventional single-carrier modulation schemes when the frequency-selective fadings are present. Nevertheless, intercarrier-interference (ICI) due to Doppler frequency drift, phase offset, local oscillator frequency drift, and multipath fading will be a severe problem in OFDM systems. Previous ICI self-cancellation coding schemes can greatly reduce the ICI, but they are very sensitive to the phase ambiguity, which is due to the composite effect of the phase offset, the multipath fading and the local frequency drift. In this paper, the phase ambiguity and amplitude ambiguity problems in ICI self-cancellation coded OFDM receivers will be formulated and discussed. Then, a novel receiver which combines the current ICI self-cancellation coding techniques with a new expectation-maximization-based joint phase/amplitude estimation and symbol detection scheme is proposed. The outstanding performance of this proposed scheme is shown and compared with other existing methods at different noise levels through OFDM simulations.

A new ICI matrices estimation scheme using Hadamard sequence for OFDM systems

The intercarrier interference (ICI) matrix for the orthogonal frequency division multiplexing (OFDM) systems usually has a fairly large dimension. The traditional least-square solution based on the pseudo-inverse operation, therefore, has its limitation. In addition, the provision of a sufficiently long training sequence to estimate the complete ICI matrix is not feasible, since it will result in severe throughput reduction. In this paper, we derive a lower bound for the mean-square estimation error among the least-square ICI matrix estimators using different training sequences and prove that the minimum mean-square error (MMSE) optimality is attained when the training sequences in different OFDM blocks are orthogonal to each other, regardless of the sequence length. We also prove that the asymptotical mean-square estimation error using the maximal-length shift-register sequences (m-sequences) as in the existing communication standards is 3 dB larger than that using the perfectly orthogonal sequences for ICI matrix estimation. Thus, we propose to employ the training sequences based on the Hadamard matrix to achieve a highly efficient and optimal ICI matrix estimator with minimum mean-square estimation error among all least-square ICI matrix estimators. Meanwhile, our new scheme involves only square computational complexity, while other existing least-square methods require the complexity proportional to the cube of the ICI matrix size. Analytical and experimental comparisons between our new scheme using Hadamard sequences and the existing method using m-sequences (pseudo-random sequences) show the significant advantages of our new ICI matrix estimator. The proposed method is most suitable for OFDM systems with large amount of subcarriers, using high order of subcarrier modulation, and designed for high-end of RF frequency band, where accurate ICI estimation is crucial.

On the design and performance analysis of multisymbol encapsulated OFDM systems

A new multicarrier system, termed multisymbol encapsulated orthogonal frequency division multiplexing (MSE-OFDM), is proposed, in which one cyclic prefix (CP) is used for multiple OFDM symbols. The original motivation for the MSE-OFDM proposal is to reduce the redundancy due to the CP in static-channel environments. The authors then found that an alternative implementation of the system can be used to improve the robustness to frequency offset and reduce the peak-to-average power ratio (PAPR). Equalization and demodulation algorithms for the MSE-OFDM system are proposed. A new preamble and the corresponding frequency-offset and channel estimation techniques are studied for the MSE-OFDM system. Using the proposed MSE-OFDM preamble, the joint maximum likelihood (ML) estimation of the frequency offset and the channel impulse response (CIR) is investigated in this paper. Possible ways to reduce the joint estimation complexity, including exploitation of the preamble structure, approximation of the joint ML estimator, and fast Fourier transform (FFT) pruning, are discussed. The performance of the proposed MSE-OFDM systems and channel estimators are analyzed and verified through numerical simulations. An analysis on the bandwidth efficiency, the performance with frequency offset, and the PAPR of the MSE-OFDM system are also presented

A Novel Robust Detection Algorithm for Spectrum Sensing

In this paper, the DTV (digital television) spectrum sensing problem is studied, which plays a key role in the cognitive radio. In contrast to the existing higher-order-statistics (HOS) approach, we propose a novel robust spectrum-sensing method, which is based on the JB (Jarqur-Bera) statistic. In our studies, the existing detector may often not be robust when the sample size is small. Our proposed JB detector is heuristically justified to be superior for the simulated microphone signals as well as the real DTV signals. Moreover, the computational complexity analysis for our proposed new JB detector and the HOS detector is also presented. Ultimately, the normality test and the spectral analysis are provided to justify the advantage of our proposed spectrum sensing method.

Novel semi-blind ICI equalization algorithm for wireless OFDM systems

Intercarrier interference is deemed as one of the crucial problems in the wireless orthogonal frequency division multiplexing (OFDM) systems. The conventional ICI mitigation schemes involve the frequency-domain channel estimation or the additional coding, both of which require the spectral overhead and hence lead to the significant throughput reduction. Besides, the OFDM receivers using the ICI estimation rely on a large-dimensional matrix inverter with high computational complexity especially for many subcarriers such as digital video broadcasting (DVB) systems and wireless metropolitan-area networks (WMAN). To the best of our knowledge, no semi-blind ICI equalization has been addressed in the existing literature. Thus, in this paper, we propose a novel semi-blind ICI equalization scheme using the joint multiple matrix diagonalization (JMMD) algorithm to greatly reduce the intercarrier interference in OFDM. However, the well-known phase and permutation indeterminacies emerge in all blind equalization schemes. Hence we also design a few OFDM pilot blocks and propose an iterative identification method to determine the corresponding phase and permutation variants in our semi-blind scheme. Our semi-blind ICI equalization algorithm integrating the JMMD with the additional pilot-based iterative identification is very promising for the future high-throughput OFDM systems. Through Monte Carlo simulations, the QPSK-OFDM system with our proposed semi-blind ICI equalizer can achieve significantly better performance with symbol error rate reduction in several orders-of-magnitude. For the 16QAM-OFDM system, our scheme can also improve the performance over the plain OFDM system to some extent.