Shih Yu Chang

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.

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.

Efficient Non-Pilot-Aided Channel Length Estimation for Digital Broadcasting Receivers

Channel estimation and equalization techniques are crucial for the ubiquitous broadcasting systems. Conventional receivers for most broadcasting or wireless standards preset the channel length to the maximal expected duration of the channel impulse response for the adopted channel estimation and equalization algorithms. The excessive channel length often significantly increases the implementational complexity of the wireless receivers and leads to the redundant information which would induce the additional estimation errors. Moreover, such a scheme does not allow the dynamic memory allocation for variable channel lengths. This could further increase the power consumption and reduce the battery life of a mobile device. The knowledge of the actual channel length would, in principle, help the system designers decrease the complexity of the channel estimators using maximum likelihood (ML) and minimum-mean-square-error (MMSE) algorithms. In this paper, we address this important channel length estimation problem and propose a novel autocorrelation-based algorithm to estimate the channel length without the need of pilots or training sequence. The associated threshold for the channel length estimation depends on the sample size, the signal-to-noise ratio and the leading/last channel coefficients. In addition, we provide the mean-square analysis on the effectiveness of the proposed non-pilot-aided channel length estimator through Monte Carlo simulations.

Novel sequence design for low-PMEPR and high-code-rate OFDM systems

In this paper, we propose a new family of 64-QAM based sequences for achieving the lowest PMEPR and the highest code rate compared to all other 64-QAM based schemes, which can be applied for OFDM systems. The construction of the proposed sequences is simple and the theoretical analysis is presented.

Determination of Wireless Networks Parameters through Parallel Hierarchical Support Vector Machines

We consider the problems of 1) estimating the physical locations of nodes in an indoor wireless network, and 2) estimating the channel noise in a MIMO wireless network, since knowing these parameters are important to many tasks of a wireless network such as network management, event detection, location-based service, and routing. A hierarchical support vector machines (H-SVM) scheme is proposed with the following advantages. First, H-SVM offers an efficient evaluation procedure in a distributed manner due to hierarchical structure. Second, H-SVM could determine these parameters based only on simpler network information, e.g., the hop counts, without requiring particular ranging hardware. Third, the exact mean and the variance of the estimation error introduced by H-SVM are derived which are seldom addressed in previous works. Furthermore, we present a parallel learning algorithm to reduce the computation time required for the proposed H-SVM. Thanks for the quicker matrix diagonization technique, our algorithm can reduce the traditional SVM learning complexity from O(n3) to O(n2) where n is the training sample size. Finally, the simulation results verify the validity and effectiveness for the proposed H-SVM with parallel learning algorithm.

Analysis and Design of a Novel Randomized Broadcast Algorithm for Scalable Wireless Networks in the Interference Channels

In this paper, we study the minimum-latency broadcast scheduling problem in the probabilistic model. We establish an explicit relationship between the tolerated transmission-failure probability and the latency of the corresponding broadcast schedule. Such a tolerated transmission-failure probability is calculated in the strict sense that the failure to receive the message at any single node will lead to the entire broadcast failure and only if all nodes have successfully received the message do we consider it a success. We design a novel broadcast scheduling algorithm such that the broadcast latency is evaluated under such a strict definition of failure. The latency bound we derive is a strong result in the sense that our algorithm achieves a low broadcast latency under this rather strict broadcast-failure definition. Simulation results are also provided to justify our derived theoretical latency bound.

Performance analysis for relay networks with hierarchical support vector machines

SUMMARY In this paper, we consider a cooperative relay scheme for a mobile network with MIMO technology. The channel capacity for two well-known relaying schemes are investigated: analogue relaying (amplify and forward) and digital relaying (decode and forward) from a mobile device to the base station through a relay node. In order to further increase the channel capacity, we propose an efficient hierarchical procedure based on support vector machine, namely hierarchical support vector machines (HSVM), to estimate the wireless networks condition approximately and design two ways (matched filter and minimum mean square error filter) of increasing the channel capacity according to the estimated wireless network condition. The proposed HSVM can estimate the wireless networks condition in much shorter time compared with the traditional minimum mean square error scheme without incurring much estimation error, which is spatial, useful for delay sensitive communication. For digital relaying, the effect of imperfect channel decode is also addressed. Our numerical results demonstrate the reduction of estimation complexity by adopting HSVM and the significant improvement of network capacity by applying the matched filter weight at relay nodes according to the network estimation. Copyright

Constellation Subset Selection: Theories and Algorithms

Constellation subset selection is a new topic emerging in the adaptive modulation communications. How to choose the subset of the original constellation phasers appears to be challenging and interesting to the researchers. There hardly exists any literature which studies the feasibility and the solution of constellation subset selection in details. Here we dedicate to this problem in both theoretical exploration and algorithm design. In this paper, we introduce the detailed theoretical analysis regarding the mathematical properties of the commonly-used constellations and then facilitate the constellation subset selection problem. Based on our problem formulation, we design two algorithms to solve this problem thereby. Our complexity analysis evinces the effectiveness of the proposed algorithms.

A novel adaptive prefix interval scheme for MIMO OFDM systems

This paper introduces a novel adaptive guard-interval scheme for multiple-input multiple-output (MIMO) orthogonal-frequency-division-multiplexing (OFDM) systems. Conventional OFDM systems set the guard-intervals large enough to combat the inter-symbol interference (ISI). However, such long guard-intervals would often lead to the severe throughput reduction. We design a non-pilot-aided channel-length estimation scheme, which does not require the additional pilot overhead, and propose a new MIMO-OFDM system built on such an adaptive prefix mechanism triggered by the feedback channel length information. Our simulations show that the proposed scheme greatly outperforms the conventional MIMO-OFDM systems.

Novel adaptive DCF protocol using the computationally-efficient optimization with the feedback network information for wireless local-area networks

In this paper, we design a novel computationally-efficient linear programming (LP) algorithm to maximize the throughput with respect to the minimum contention window size for the IEEE 802.11 Distributed Coordination Function (DCF) protocol. Based on our LP scheme, a new DCF protocol which can select the best access mode and the optimal size of the minimum contention window is proposed by considering the channel condition and the number of competing stations jointly. The numerical results demonstrate that our proposed DCF protocol significantly outperforms the conventional method.