An extension of the traditional color-based visual tracker, i.e., the continuously adaptive mean shift tracker, is given for improving the convenience and generality of the color-based tracker. This is achieved by introducing a probability density function for pixels based on the hue histogram of object. As its merits, the direction and size of the tracked object are easily derived by the principle component analysis (PCA), and its extension to three-dimensional case becomes straightforward.

In a multi-user orthogonal frequency division multiplexing (OFDM) system, efficient resource allocation is required to provide service to more users. In this letter, we propose an improved subcarrier allocation algorithm that can increase the spectral efficiency and the number of total transmission bits even if the number of users is too large. The proposed algorithm is divided into two stages. In the first stage, a group of users who are eligible for services is determined by using the bit error rate (BER), the users' minimum data rate requirement, and channel information. In the second stage, subcarriers are first allocated to the users on the basis of channel state, and then the reallocation is performed so that resource waste is minimized. We show that the proposed algorithm outperforms the conventional one on the basis of outage probability, spectral efficiency, and the number of total transmission bits through a computer simulation.

This paper studies a dual-hop amplify-and-forward (AF) relaying systems over shadowed Nakagami-m fading channels and derives an approximate analytical expression for the outage probability. The numerical results show that the derived analytical expression can provide very well approximations to the simulation results.

In this letter, we analyze the pairwise error probability (PEP) behaviour of distributed space-time code (DSTC) with amplify-and-forward relaying over Nakagami-m multipath channels. An upper bound of PEP for DSTC is derived. From our analysis, it is seen that of the paths from the source to relays and from relays to the destination, those with smaller diversity order result in an overall system performance bottleneck. Numerical examples are provided to corroborate our theoretical analysis.

In this letter, a theoretical analysis of bit error probability for 4-state convolutional code with Max-Log-maximum a posteriori probability (MAP) decoding is presented. This technique employs an iterative calculation of probability density function of the state metric per one transition, and gives the exact bit error probability for all signal-to-noise power ratio.

To satisfy both the bandwidth efficiency of low-speed mobile hosts (MHs) and seamless handoff of high-speed MHs in cellular networks, this paper proposes a reservation scheme which exploits a dynamic two-tier cell structure and the handoff probability. The dynamic two-tier cell structure determines the reservation and non-reservation zones according to the speed of MHs. The handoff probability is calculated using the moving speed and the direction of MHs.

In this letter, we investigate the outage performance for decode-and-forward relaying under Rayleigh fading in the presence of multiple unequal-powered Rayleigh co-channel interferers. A close-form expression for the outage probability is derived and simulation results verify the theoretical solution.

One of the major challenges facing the design of a routing protocol for Wireless Sensor Networks (WSNs) is to find the most reliable path between the source and sink node. Furthermore, a routing protocol for WSN should be well aware of sensor limitations. In this paper, we present an energy efficient, scalable, and distributed node disjoint multipath routing algorithm. The proposed algorithm, the Energy-aware Multipath Routing Algorithm (EMRA), adjusts traffic flows via a novel load balancing scheme. EMRA has a higher average node energy efficiency, lower control overhead, and a shorter average delay than those of well-known previous works. Moreover, since EMRA takes into consideration network reliability, it is useful for delivering data in unreliable environments.

In this paper, we investigate the performance of maximum ratio combining (MRC) in the presence of multiple cochannel interferences over a flat Rayleigh fading channel. Closed-form expressions of signal-to-interference-plus-noise ratio (SINR), outage probability, and average symbol error rate (SER) of quadrature amplitude modulation (QAM) with M-ary signaling are obtained for unequal-power interference-to-noise ratio (INR). We also provide an upper-bound for the average SER using moment generating function (MGF) of the SINR. Moreover, we quantify the array gain loss between pure MRC (MRC system in the absence of CCI) and MRC system in the presence of CCI. Finally, we verify our analytical results by numerical simulations.

Vertically stacked optical banyan (VSOB) is an attractive architecture for constructing banyan-based optical switches. Blocking behaviors analysis is an effective approach to studying network performance and finding a graceful compromise among hardware costs, blocking probability and crosstalk tolerance; however, little has been done on analyzing the blocking behavior of VSOB networks under crosstalk constraint which adds a new dimension to the switching performance. In this paper, we study the overall blocking behavior of a VSOB network under various degree of crosstalk, where an upper bound on the blocking probability of the network is developed. The upper bound depicts accurately the overall blocking behavior of a VSOB network as verified by extensive simulation results and it agrees with the strictly nonblocking condition of the network. The derived upper bound is significant because it reveals the inherent relationship between blocking probability and network hardware cost, by which a desirable tradeoff can be made between them under various degree of crosstalk constraint. Also, the upper bound shows how crosstalk adds a new dimension to the theory of switching systems.

Due to the dynamics of topology and resources, Call Admission Control (CAC) plays a significant role for increasing resource utilization ratio and guaranteeing users' QoS requirements in wireless/mobile networks. In this paper, a dynamic multi-threshold CAC scheme is proposed to serve multi-class service in a wireless/mobile network. The thresholds are renewed at the beginning of each time interval to react to the changing mobility rate and network load. To find suitable thresholds, a reward-penalty model is designed, which provides different priorities between different service classes and call types through different reward/penalty policies according to network load and average call arrival rate. To speed up the running time of CAC, an Optimized Genetic Algorithm (OGA) is presented, whose components such as encoding, population initialization, fitness function and mutation etc., are all optimized in terms of the traits of the CAC problem. The simulation demonstrates that the proposed CAC scheme outperforms the similar schemes, which means the optimization is realized. Finally, the simulation shows the efficiency of OGA.

In this paper, a channel allocation scheme is studied for overlay wireless networks to optimize connection-level QoS. The contributions of our work are threefold. First, a channel allocation strategy using both horizontal channel borrowing and vertical traffic overflowing (HCB-VTO) is presented and analyzed. When all the channels in a given macro-cell are used, high-mobility real-time handoff requests can borrow channels from adjacent homogeneous cells. In case that the borrowing requests fail, handoff requests may also be overflowed to heterogeneous cells, if possible. Second, high-mobility real-time service is prioritized by allowing it to pre-empt channels currently used by other services. And third, to meet the high QoS requirements of some services and increase the utilization of radio resources, certain services can be transformed between real-time services and non-real-time services as necessary. Simulation results demonstrate that the proposed schemes can improve system performance.

To estimate the impact of electromagnetic disturbances on multi-carrier wireless systems, a method for converting an amplitude probability distribution (APD) of disturbance measured at a frequency to be valid for another frequency is presented. The conversion uses two parameters, the receiver noise power of the APD measuring equipment and a scale factor that can be estimated from a measured disturbance spectrum. The method is based on the assumption that the difference in measurement frequency affects only the relative scale of the probability distribution of band-limited disturbance amplitude, and is applicable to disturbances of practically importance such as 1) continuous or pulse-modulated wideband Gaussian noise, 2) disturbance with a much narrower bandwidth than receiver bandwidth B, and 3) repetitive short pulses with similar waveforms with an interval much longer than 1/B. The validity of the proposed method is examined by measurements of actual disturbances.

Prior studies have shown that the performance of amplify-and-forward (AF) relay systems can be considerably improved by using multiple antennas and low complexity linear processing at the relay nodes. However, there is still a lack of performance analysis for the cases where the processing is based on limited feedback (LFB). Motivated by this, we derive the closed-form expression of the outage probability of AF relay systems with LFB beamforming in this letter. Simulation results are also provided to confirm the analytical studies.

This paper will propose a wolf attack probability (WAP) as a new measure for evaluating security of biometric authentication systems. The wolf attack is an attempt to impersonate a victim by feeding "wolves" into the system to be attacked. The "wolf" means an input value which can be falsely accepted as a match with multiple templates. WAP is defined as a maximum success probability of the wolf attack with one wolf sample. In this paper, we give a rigorous definition of the new security measure which gives strength estimation of an individual biometric authentication system against impersonation attacks. We show that if one reestimates using our WAP measure, a typical fingerprint algorithm turns out to be much weaker than theoretically estimated by Ratha et al. Moreover, we apply the wolf attack to a finger-vein-pattern based algorithm. Surprisingly, we show that there exists an extremely strong wolf which falsely matches all templates for any threshold value.

This paper presents a coexistence model of IEEE 802.15.4 with IEEE 802.11b interference in fading channels and proposes two adaptive channel allocation schemes. The first avoids the IEEE 802.15.4 interference only and the second avoids both of the IEEE 802.15.4 and IEEE 802.11b interferences. Numerical results show that the proposed algorithms are effective for avoiding interferences and for maximizing network capacity since they select a channel which gives the maximum signal to noise ratio to the system.

In order for the interconnect effects due to process-induced variations to be applied to the designs in 0.13 µm and below, it is necessary to determine and characterize the realistic interconnect worstcase models with high accuracy and speed. This paper proposes new statistically-based approaches to the characterization of realistic interconnect worstcase models which take into account process-induced variations. The Effective Common Geometry (ECG) and Accumulated Maximum Probability (AMP) algorithms have been developed and implemented into the new statistical interconnect worstcase design environment. To verify this statistical interconnect worstcase design environment, the 31-stage ring oscillators are fabricated and measured with UMC 0.13 µm Logic process. The 15-stage ring oscillators are fabricated and measured with 0.18 µm standard CMOS process for investigating its flexibility in other technologies. The results show that the relative errors of the new method are less than 1.00%, which is two times more accurate than the conventional worstcase method. Furthermore, the new interconnect worstcase design environment improves optimization speed by 29.61-32.01% compared to that of the conventional worstcase optimization. The new statistical interconnect worstcase design environment accurately predicts the worstcase and bestcase corners of non-normal distribution where conventional methods cannot do well.

We analyze the energy consumption of the sensor-medium access control (S-MAC) protocol, where contending nodes exist. Because all nodes running the S-MAC within a virtual cluster always behave with a fixed frame length, the behavior should be analyzed based on its frame. Hence, reflecting the frame architecture, we first present an analytic model for the S-MAC behavior with a discrete-time Markov chain, and then we analyze energy consumption under unsaturated conditions.

In optical burst switching (OBS) networks, burst with different numbers of hops experience unfairness in terms of the burst loss probability. In this paper, we propose a preemptive scheme based on the number of transit hops in OBS networks. In our proposed scheme, preemption is performed with two thresholds; one is for the total number of hops of a burst and the other is for the number of transit hops the burst has passed through. We evaluate the performance of the scheme by simulation, and numerical examples show that the proposed scheme improves the fairness among the bursts with different numbers of hops, keeping the overall burst loss probability the same as that for the conventional OBS transmission without preemption.

Robust automatic language identification (LID) is the task of identifying the language from a short utterance spoken by an unknown speaker. The mainstream approaches include parallel phone recognition language modeling (PPRLM), support vector machine (SVM) and the general Gaussian mixture models (GMMs). These systems map the cepstral features of spoken utterances into high level scores by classifiers. In this paper, in order to increase the dimension of the score vector and alleviate the inter-speaker variability within the same language, multiple data groups based on supervised speaker clustering are employed to generate the discriminative language characterization score vectors (DLCSV). The back-end SVM classifiers are used to model the probability distribution of each target language in the DLCSV space. Finally, the output scores of back-end classifiers are calibrated by a pair-wise posterior probability estimation (PPPE) algorithm. The proposed language identification frameworks are evaluated on 2003 NIST Language Recognition Evaluation (LRE) databases and the experiments show that the system described in this paper produces comparable results to the existing systems. Especially, the SVM framework achieves an equal error rate (EER) of 4.0% in the 30-second task and outperforms the state-of-art systems by more than 30% relative error reduction. Besides, the performances of proposed PPRLM and GMMs algorithms achieve an EER of 5.1% and 5.0% respectively.