This letter deals with blind multiuser detection based on the multi-channel linearly constrained constant modulus algorithm (MLCCMA) for asynchronous code division multiple access (CDMA) systems over frequency-selective Rayleigh fading channels. In conjunction with the decision-feedback generalized sidelobe canceller (DFGSC), we present an efficient approach to combat multiple access interference and intersymbol interference. Computer simulations confirm that the proposed MLCCMA-based DFGSC can significantly speed up convergence and improve the output performance.

Eavesdropping on backward channels in RFID environments may cause severe privacy problems because it means the exposure of personal information related to tags that each person has. However, most existing RFID tag security schemes are focused on the forward channel protections. In this paper, we propose a simple but effective method to solve the backward channel eavesdropping problem based on Randomized-tree walking algorithm for securing tag ID information and privacy in RFID-based applications. In order to show the efficiency of the proposed scheme, we derive two performance models for the cases when CRC is used and not used. It is shown that the proposed method can lower the probability of eavesdropping on backward channels near to '0.'

We present a computationally efficient Fano detection algorithm with an iterative structure for V-BLAST systems. As our previous work, we introduced a Fano-based sequential detection scheme with three interrelated steps whose computational loads are excessive. To deal with the computational inefficiency, the proposed algorithm is redesigned by the addition of two steps: preparation and iterative tree searching. In particular, it employs an early stop technique to avoid the unnecessary iteration or to stop the needless searching process of the algorithm. Computer simulation shows that the proposed scheme yields significant saving in complexity with very small performance degradation, compared with sphere detection (SD).

Because of its simplicity and intuitive approach, point-based rendering has been a very popular research area. Recent approaches have focused on hardware-accelerated techniques. By applying a deferred shading scheme, both high-quality images and high-performance rendering have been achieved. However, previous methods showed problems related to depth-based visibility computation. We propose an extended point-based rendering method using a visibility map. In our method we employ a distance-based visibility technique (replacing depth-based visibility), an averaged position map and an adaptive fragment processing scheme, resulting in more accurate and improved image quality, as well as improved rendering performance.

Let G =(V, E) be an undirected simple graph with u ∈ V. If there exist any two vertices in G whose distance becomes longer when a vertex u is removed, then u is defined as a hinge vertex. Finding the set of hinge vertices in a graph is useful for identifying critical nodes in an actual network. A number of studies concerning hinge vertices have been made in recent years. In a number of graph problems, it is known that more efficient sequential or parallel algorithms can be developed by restricting classes of graphs. In this paper, we shall propose a parallel algorithm which runs in O(log n) time with O(n/log n) processors on EREW PRAM for finding all hinge vertices of a circular-arc graph.

In a key scheduling algorithm (KSA) of stream ciphers, a secret key is expanded into a large initial state. An internal state reconstruction method is known as a general attack against stream ciphers; it recovers the initial state from a given pair of plaintext and ciphertext more efficiently than exhaustive key search. If the method succeeds, then it is desirable that the inverse of KSA is infeasible in order to avoid the leakage of the secret key information. This paper shows that it is easy to compute a secret key from an initial state of RC4. We propose a method to recover an -bit secret key from only the first bits of the initial state of RC4 using linear equations with the time complexity less than that of one execution of KSA. It can recover the secret keys of which number is 2103.6 when the size of the secret key is 128 bits. That is, the 128-bit secret key can be recovered with a high probability when the first 128 bits of the initial state are determined using the internal state reconstruction method.

This letter presents a new vertical Bell Labs layered space-time (V-BLAST) transmission scheme for developing low-complexity tree searching in the QRD-M algorithm. In the new V-BLAST system, we assign modulation scheme in ascending order from top to bottom tree branches. The modulation set to be assigned is decided by two criteria: minimum performance loss and maximum complexity reduction. We also propose an open-loop power allocation algorithm to surmount the performance loss. Numerical results show that the proposed V-BLAST transmission approach can significantly reduce the computational loads of the QRD-M algorithm with a slight performance degradation.

We propose an accurate, distributed localization method that uses the connectivity measure to localize nodes in a wireless sensor network. The proposed method is based on a self-organizing isometric embedding algorithm that adaptively emphasizes the most accurate range of measurements and naturally accounts for communication constraints within the sensor network. Each node adaptively chooses a neighborhood of sensors and updates its estimate of position by minimizing a local cost function and then passes this update to the neighboring sensors. Simulations demonstrate that the proposed method is more robust to measurement error than previous methods and it can achieve comparable results using much fewer anchor nodes than previous methods.

The clonal selection algorithm (CS), inspired by the basic features of adaptive immune response to antigenic stimulus, can exploit and explore the solution space parallelly and effectively. However, antibody initialization and premature convergence are two problems of CS. To overcome these two problems, we propose a chaotic distance-based clonal selection algorithm (CDCS). In this novel algorithm, we introduce a chaotic initialization mechanism and a distance-based somatic hypermutation to improve the performance of CS. The proposed algorithm is also verified for numerous benchmark traveling salesman problems. Experimental results show that the improved algorithm proposed in this paper provides better performance when compared to other metaheuristics.

In this paper we propose a discrete program-size dependent software reliability growth model flexibly describing the software failure-occurrence phenomenon based on a discrete Weibull distribution. We also conduct model comparisons of our discrete SRGM with existing discrete SRGMs by using actual data sets. The program size is one of the important metrics of software complexity. It is known that flexible discrete software reliability growth modeling is difficult due to the mathematical manipulation under a conventional modeling-framework in which the time-dependent behavior of the cumulative number of detected faults is formulated by a difference equation. Our discrete SRGM is developed under an existing unified modeling-framework based on the concept of general order-statistics, and can incorporate the effect of the program size into software reliability assessment. Further, we discuss the method of parameter estimation, and derive software reliability assessment measures of our discrete SRGM. Finally, we show numerical examples of discrete software reliability analysis based on our discrete SRGM by using actual data.

This paper proposes an algorithm for calculating routes that considers the include route constraint while minimizing cost. A route with include route constraint has to traverse a group of assigned nodes. The trouble when calculating a route that satisfies an include route constraint is that routes set in different sections may traverse the same link. In order to prevent this violation (overlap), we introduce an alternate route selection policy. Numerical results show that the probability of finding appropriate routes (no overlap) is more than 95% with the proposed algorithm while only 35% with the conventional algorithm.

FeedForward (FF-) Blind Source Separation (BSS) systems have some degree of freedom in the solution space. Therefore, signal distortion is likely to occur. First, a criterion for the signal distortion is discussed. Properties of conventional methods proposed to suppress the signal distortion are analyzed. Next, a general condition for complete separation and distortion-free is derived for multi-channel FF-BSS systems. This condition is incorporated in learning algorithms as a distortion-free constraint. Computer simulations using speech signals and stationary colored signals are performed for the conventional methods and for the new learning algorithms employing the proposed distortion-free constraint. The proposed method can well suppress signal distortion, while maintaining a high source separation performance.

A training-based vector channel estimation method has been proposed for single-user code-division multiple access (CDMA) systems in fast-varying correlated multipath fading channels. In this paper, we extend it in an iterative way to multiuser multiple-input multiple-output (MIMO) CDMA systems where both the transmitter and receiver have multiple antennas. In the training period, we propose to add the minimum mean square error (MMSE) front end before channel estimation to suppress multiuser interference (MUI) from substreams with difference spreading codes, so then we can get good initial vector channel estimation for each user. In the data transmission period, we proposed to add MMSE/parallel interference cancellation (PIC) front end to suppress MUI, interference suppression, and vector channel estimation in an iterative way. The perfect channel estimation is assumed in Liu et al., and the inter-play between channel estimation and multiuser detection is not discussed either. On the contrary, the novelty of the proposed method is that we add MMSE/PIC front end (in addition to matched filter) before channel estimation and we repeatedly switch between MMSE/PIC front end and channel estimation.

The fixed charge transportation problem (FCTP) is a classic challenge for combinatorial optimization; it is based on the well-known transportation problem (TP), and is one of the prime examples of an NP-complete variant of the TP, of general importance in a wide range of transportation network design problems. Many techniques have been applied to this problem, and the most effective so far (in terms of near-optimal results in reasonable time on large instances) are evolutionary algorithm based approaches. In particular, an EA proposed by Eckert and Gottlieb has produced the best performance so far on a set of specific benchmark instances. We introduce a new scheme, which has more general applicability, but which we test here on the FCTP. The proposed scheme applies an adaptive mutation process immediately following the evaluation of a phenotype. It thereby adapts automatically to learned information encoded in the chromosome. The underlying encoding approach is to encode an ordering of elements for interpretation by a constructive algorithm (such as with the Link and Node Biased encoding for spanning trees, and the Random Keys encoding which has been applied to both scheduling and graph problems), however the main adaptive process rewards links in such a way that genes effectively encode a measure of the number of times their associated link has appeared in selected solutions. Tests are done which compare our approach with Eckert and Gottlieb's results on benchmark FCTP instances, and other approaches.

This paper addresses a new surface reconstruction scheme for approximating the isosurface from a set of tomographic cross sectional images. Differently from the novel Marching Cubes (MC) algorithm, our method does not extract the iso-density surface (isosurface) directly from the voxel data but calculates the iso-density point (isopoint) first. After building a coarse initial mesh approximating the ideal isosurface by the cell-boundary representation, it metamorphoses the mesh into the final isosurface by a relaxation scheme, called shrink-wrapping process. Compared with the MC algorithm, our method is robust and does not make any cracks on surface. Furthermore, since it is possible to utilize lots of additional isopoints during the surface reconstruction process by extending the adjacency definition, theoretically the resulting surface can be better in quality than the MC algorithm. According to experiments, it is proved to be very robust and efficient for isosurface reconstruction from cross sectional images.

In 1995, Vanstone and Zuccherato proposed a novel method of generating RSA moduli having a predetermined set of bits which are the ASCII representation of user's identification information (i.e., name, email address, etc.). This could lead to a savings in bandwidth for data transmission and storage. In this paper, we apply this idea of Vanstone and Zuccherato for reducing the storage requirement of RSA public moduli to integer factoring based public-key schemes with their moduli of the form prq. More precisely, we explicitly propose two efficient methods for specifying high-order bits of prime factors of their public-keys. We also consider the security of the proposed methods.

It is well known that Pisarenko's frequency estimate for a single real tone can be computed easily using the sample covariance with lags 1 and 2. In this Letter, we propose to use alternative covariance expressions, which are inspired from the modified covariance (MC) frequency estimator, in Pisarenko's algorithm. Computer simulations are included to corroborate the theoretical development of the variant and to demonstrate its superiority over the MC and Pisarenko's methods.

We have been developing a secure and reliable distributed storage system, which uses a secret sharing scheme. In order to efficiently store data in the system, this paper introduces an optimal share transfer problem, and proves it to be, generally, NP-hard. It is also shown that the problem can be resolved into a Steiner tree problem. Finally, through computational experiments we perform the comparison of heuristic algorithms for the Steiner tree problem.

Ziv-Lempel incremental parsing [1] is a fundamental algorithm for lossless data compression. There is a simple enumerative implementation [7] which preserves a duality between the encoder and the decoder. However, due to its compactness, the implementation when combined with a complete integer code, allows only an input sequence with a length consistent with the parsing boundaries. In this letter, we propose a simple additional mechanism for post-processing a binary file of arbitrary length, provided the file punctuation is externally managed.

In order to find paths guaranteed by Quality of Service (QoS), the link state database (LSDB), containing QoS constraint information, and residing in routers, needs to be well managed. However, there is a trade-off between the exact reflection of the current link status and the update cost to calculate and maintain this data. In order to perfectly reflect the current link state, each router immediately notifies its neighbors whenever link state information changes. However, this may degrade the performance of the router. On the other hand, if current link state information is not updated routinely, route setup requests may be rejected because of the discrepancy between the current link state information and the previously updated link state information in the LSDB. Therefore, we need link state update (LSU) algorithms making it possible to appropriately update the LSDB. In addition, to facilitate implementation, they also should have low-complexity and must be adaptive under the variation of network conditions. In this paper, we propose an enhanced simple-adaptive (ESA) LSU algorithm, to reduce the generation of LSU messages while maintaining simplicity and adaptivity. The performance of this algorithm is compared with five existing algorithms by rigorous simulations. The comparision shows that the ESU algorithm can adapt to changes in network conditions and its performance is superior to existing LSU algorithms.