Po-Ning Chen

Distributed fault-tolerant classification in wireless sensor networks

Fault-tolerance and data fusion have been considered as two fundamental functions in wireless sensor networks. In this paper, we propose a novel approach for distributed multiclass classification using a fault-tolerant fusion rule for wireless sensor networks. Binary decisions from local sensors, possibly in the presence of faults, are forwarded to the fusion center that determines the final classification result. Classification fusion in our approach is implemented via error correcting codes to incorporate fault-tolerance capability. This new approach not only provides an improved fault-tolerance capability but also reduces computation time and memory requirements at the fusion center. Code matrix design is essential for the design of such systems. Two efficient code matrix design algorithms are proposed in this paper. The relative merits of both algorithms are also studied. We also develop sufficient conditions for asymptotic detection of the correct hypothesis by the proposed approach. Performance evaluation of the proposed approach in the presence of faults is provided. These results show significant improvement in fault-tolerance capability as compared with conventional parallel fusion networks.

Optimal Transmission Range for Wireless Ad Hoc Networks Based on Energy Efficiency

The transmission range that achieves the most economical use of energy in wireless ad hoc networks is studied for uniformly distributed network nodes. By assuming the existence of forwarding neighbors and the knowledge of their locations, the average per-hop packet progress for a transmission range that is universal for all nodes is derived. This progress is then used to identify the optimal per-hop transmission range that gives the maximal energy efficiency. Equipped with this analytical result, the relation between the most energy-economical transmission range and the node density, as well as the path-loss exponent, is numerically investigated. It is observed that when the path-loss exponent is high (such as four), the optimal transmission ranges are almost identical over the range of node densities that we studied. However, when the path-loss exponent is only two, the optimal transmission range decreases noticeably as the node density increases. Simulation results also confirm the optimality of the per-hop transmission range that we found analytically.

Optimum transmission range for wireless ad hoc networks

The transmission range that achieves the most economical use of energy in wireless ad hoc networks is studied under homogeneous node distribution. By assuming the knowledge of node location, we first proposed a transmission strategy to ensure the progress of data packets toward their final destinations. Then the average packet progress for a transmission range universal for all nodes is derived, which is accordingly used to determine the optimal transmission range that gives the maximum efficiency of energy consumption. Different from some previous work, our analysis does not make the assumption of large nodal density in the wireless ad hoc networks studied. Numerical and simulation results are presented to examine our analysis for wireless ad hoc networks.

A maximum-likelihood soft-decision sequential decoding algorithm for binary convolutional codes

We present a trellis-based maximum-likelihood soft-decision sequential decoding algorithm (MLSDA) for binary convolutional codes. Simulation results show that, for (2, 1, 6) and (2, 1, 16) codes antipodally transmitted over the AWGN channel, the average computational effort required by the algorithm is several orders of magnitude less than that of the Viterbi algorithm. Also shown via simulations upon the same system models is that, under moderate SNR, the algorithm is about four times faster than the conventional sequential decoding algorithm (i.e., stack algorithm with Fano metric) having comparable bit-error probability.

New asymptotic results in parallel distributed detection

The performance of a parallel distributed detection system is investigated as the number of sensors tends to infinity. It is assumed that the i.i.d. sensor data are quantized locally into m-ary messages and transmitted to the fusion center for binary hypothesis testing. The boundedness of the second moment of the postquantization log-likelihood ratio is examined in relation to the asymptotic error exponent. It is found that, when that second moment is unbounded, the Neyman-Pearson error exponent can become a function of the test level, whereas the Bayes error exponent remains, as previously conjectured by J.N. Tsitsiklis, (1986), unaffected. Large deviations techniques are also used to show that in Bayes testing the equivalence of absolutely optimal and best identical-quantizer systems is not limited to error exponents, but extends to the actual Bayes error probabilities up to a multiplicative constant. >

Optimistic Shannon coding theorems for arbitrary single-user systems

The conventional definitions of the source coding rate and of channel capacity require the existence of reliable codes for all sufficiently large block lengths. Alternatively, if it is required that good codes exist for infinitely many block lengths, then optimistic definitions of source coding rate and channel capacity are obtained. In this work, formulas for the optimistic minimum achievable fixed-length source coding rate and the minimum /spl epsi/-achievable source coding rate for arbitrary finite-alphabet sources are established. The expressions for the optimistic capacity and the optimistic /spl epsi/-capacity of arbitrary single-user channels are also provided. The expressions of the optimistic source coding rate and capacity are examined for the class of information stable sources and channels, respectively. Finally, examples for the computation of optimistic capacity are presented.

Performance Analysis and Code Design for Minimum Hamming Distance Fusion in Wireless Sensor Networks

Distributed classification fusion using error-correcting codes (DCFECC) has recently been proposed for wireless sensor networks operating in a harsh environment. It has been shown to have a considerably better capability against unexpected sensor faults than the optimal likelihood fusion. In this paper, we analyze the performance of a DCFECC code with minimum Hamming distance fusion. No assumption on identical distribution for local observations, as well as common marginal distribution for the additive noises of the wireless links, is made. In addition, sensors are allowed to employ their own local classification rules. Upper bounds on the probability of error that are valid for any finite number of sensors are derived based on large deviations technique. A necessary and sufficient condition under which the minimum Hamming distance fusion error vanishes as the number of sensors tends to infinity is also established. With the necessary and sufficient condition and the upper error bounds, the relation between the fault-tolerance capability of a DCFECC code and its pair-wise Hamming distances is characterized, and can be used together with any code search criterion in finding the code with the desired fault-tolerance capability. Based on the above results, we further propose a code search criterion of much less complexity than the minimum Hamming distance fusion error criterion adopted earlier by the authors. This makes the code construction with acceptable fault-tolerance capability for a network with over a hundred of sensors practical. Simulation results show that the code determined based on the new criterion of much less complexity performs almost identically to the best code that minimizes the minimum Hamming distance fusion error. Also simulated and discussed are the performance trends of the codes searched based on the new simpler criterion with respect to the network size and the number of hypotheses

Low-complexity ML decoding for convolutional tail-biting codes

Recently, a maximum-likelihood (ML) decoding algorithm with two phases has been proposed for convolutional tailbiting codes. The first phase applies the Viterbi algorithm to obtain the trellis information, and then the second phase employs the algorithm A* to find the ML solution. In this work, we improve the complexity of the algorithm A* by using a new evaluation function. Simulations showed that the improved A* algorithm has over 5 times less average decoding complexity in the second phase when Eb/N0ges 4 dB.

STROKE RELATION CODING—A NEW APPROACH TO THE RECOGNITION OF MULTI-FONT PRINTED CHINESE CHARACTERS

This paper describes a new approach to the recognition of multi-font printed Chinese characters. The basic idea is to encode a character in terms of two pre-defined stroke relations, namely, relative position relation and relative direction relation. The code-mapping method chosen in our system possesses two main advantages: the first is that the tree-like data base can be easily extended, and the second is that the processing time is independent of the amount of data base. Since the stability of the extracted strokes greatly affects the coding results, a new stroke merging method, which has been experimentally proven to extract strokes more steadily, is also proposed.

Broadband service creation and operations

Three challenges for deploying broadband services are the time-consuming process of service creation, the interoperability over heterogeneous platforms, and the gap between the needs of service management and the functionalities of network management. We describe a methodology to attack the first two challenges, namely, to simplify the process of service creation and provide a platform-independent framework for service operations. A set of broadband service-independent building blocks (SIBs) are designed and used to create and customize SIB graphs for broadband services. During service running time, the service agent interprets a SIB graph and executes SIB procedures which are all downloaded from the service provider. Web, Java, and CORBA are the technological elements of this methodology. Two examples, video conferencing and video on demand, are given to demonstrate the feasibility of this approach.