In this letter, we propose a packet loss probability (PLP) assessment method that uses active measurements. Considering the statistical nature of measurement data in a network, we adopt the confidence interval to assess whether the performance of a network complies with a target PLP or not. Using both analysis and simulations, we show that the proposed method can guarantee that the probabilities of erroneous assessments are not more than a given significance level. In addition, we provide a systematic method to determine the number of probing packets needed for statistical assurance by presenting a clear relation between the assessment accuracy and the measurement overhead.

Cooperative relay selection, in which one of multiple relays is selected to retransmit the source signal to the destination, has received considerable attention in recent years, because it is a simple way to obtain cooperative diversity in wireless networks. The exact expression of outage probability for a decode-and-forward cooperative relay selection with multiple source and destination antennas over Rayleigh fading channels was recently derived in [9]. In this letter, we derive the exact expressions of outage probability and diversity-multiplexing tradeoff over independent and non-identically distributed Nakagami-m fading channels as an extension of [9]. We then analyze the effects of various parameters such as fading conditions, number of relays, and number of source and destination antennas on the outage probability.

In this letter, we address the performance analysis of underlay selective decode-and-forward (DF) relay networks in Rayleigh fading channels with non-necessarily identical fading parameters. In particular, a novel result on the outage probability of the considered system is presented. Monte Carlo simulations are performed to verify the correctness of our exact closed-form expression. Our proposed analysis can be adopted for various underlay spectrum sharing applications of cognitive DF relay networks.

This study shows a fast simulation method of turbo codes over slow Rayleigh fading channels. The reduction of the simulation time is achieved by applying importance sampling (IS). The conventional IS method of turbo codes over Rayleigh fading channels focuses only on modification of additive white Gaussian noise (AWGN) sequences. The proposed IS method biases not only AWGNs but also channel gains of the Rayleigh fading channels. The computer runtime of the proposed method is about 1/5 of that of the conventional IS method on the evaluation of a frame error rate of 10-6. When we compare with the Monte Carlo simulation method, the proposed method needs only 1/100 simulation runtime under the condition of the same accuracy of the estimator.

Cognitive radios are intelligent communications, and are expected to more efficiently utilize the radio channel. Modulation identification is one of the key issues in the cognitive radios. Many works were devoted to the classification of symbol-by-symbol modulations, however, few papers on block modulations have been published. In this paper, an identification error analysis is presented for block orthogonal modulations using General Orthogonal Modulation~(GOM). A symbol error probability is derived for the identified block orthogonal modulation. Numerical results of 4-dimensional block orthogonal modulation are presented with simulation results.

In an orthogonal frequency division multiplexing (OFDM) system, carrier frequency offset (CFO) causes intercarrier interference (ICI) which significantly degrades the system error performance. In this paper we provide a closed-form expression to evaluate the exact error probabilities of arbitrary 2-D modulation OFDM systems with CFO, and analyze the effect of CFO on error performance.

In this letter, we propose and analyze a cooperative transmission scheme (CTS) that uses transmission timing control for LTE enterprise femtocells. In our scheme, the user equipment (UE) can receive the desired signal from an adjacent fBS as well as its serving femtocell BS (fBS). Thus, UE achieves an improved signal to interference ratio (SIR) due to the synchronization of the two signals. Analysis and simulation results show that the proposed scheme can reduce the outage probability for enterprise femtocells compared to the conventional system. In particular, a significant performance improvement can be achieved for UEs located at cell edges.

The general method for estimating phrase translation probabilities consists of sequential processes: word alignment, phrase pair extraction, and phrase translation probability calculation. However, during this sequential process, errors may propagate from the word alignment step through the translation probability calculation step. In this paper, we propose a new method for estimating phrase translation probabilities that reduce the effects of error propagation. By considering the semantic recoverability of phrase retranslation, our method identifies incorrect phrase pairs that have propagated from alignment errors. Furthermore, we define retranslation similarity which represents the semantic recoverability of phrase retranslation, and use this when computing translation probabilities. Experimental results show that the proposed phrase translation estimation method effectively prevents a PBSMT system from selecting incorrect phrase pairs, and consistently improves the translation quality in various language pairs.

This letter presents an analytical study of outage probability of a 3G/Ad Hoc cooperative network. The considered cooperative network can improve the signal quality so as to decrease the outage probability. Meanwhile, it imposes additional interference on other ongoing users. But on the whole, our analytical study and simulation results show that the cooperative network can still effectively overcome outage event and decrease the average outage probability.

The energy consumption of the information and communication technology (ICT) industry, which has become a serious problem, is mostly due to the network infrastructure rather than the mobile terminals. In this paper, we focus on reducing the energy consumption of base stations (BSs) by adjusting their working modes (active or sleep). Specifically, the objective is to minimize the energy consumption while satisfying quality of service (QoS, e.g., blocking probability) requirement and, at the same time, avoiding frequent mode switching to reduce signaling and delay overhead. The problem is modeled as a dynamic programming (DP) problem, which is NP-hard in general. Based on cooperation among neighboring BSs, a low-complexity algorithm is proposed to reduce the size of state space as well as that of action space. Simulations demonstrate that, with the proposed algorithm, the active BS pattern well meets the time variation and the non-uniform spatial distribution of system traffic. Moreover, the tradeoff between the energy saving from BS sleeping and the cost of switching is well balanced by the proposed scheme.

In this paper, we present a maximum a posteriori probability (MAP) approach to the problem of blind estimation of single-input, multiple-output (SIMO), finite impulse response (FIR) channels. A number of methods have been developed to date for this blind estimation problem. Some of those utilize prior knowledge on input signal statistics. However, there are very few that utilize channel statistics too. In this paper, the unknown channel to be estimated is assumed as the frequency-selective Rayleigh fading channel, and we incorporate the channel prior distributions (and hyperprior distributions) into our model in two different ways. Then for each case an iterative MAP estimator is derived approximately. Performance comparisons over existing methods are conducted via numerical simulation on randomly generated channel coefficients according to the Rayleigh fading channel model. It is shown that improved estimation performance can be achieved through the MAP approaches, especially for such channel realizations that have resulted in large estimation error with existing methods.

PMOS stress (ON) probability has a strong impact on circuit timing degradation due to NBTI effect. This paper evaluates how the granularity of stress probability calculation affects NBTI prediction using a state-of-the-art long term prediction model. Experimental evaluations show that the stress probability should be estimated at transistor level to accurately predict the increase in delay, especially when the circuit operation and/or inputs are highly biased. We then devise and evaluate two annotation methods of stress probability to gate-level timing analysis; one guarantees the pessimism desirable for timing analysis and the other aims to obtain the result close to transistor-level timing analysis. Experimental results show that gate-level timing analysis with transistor-level stress probability calculation estimates the increase in delay with 12.6% error.

In the underlay decode-and-forward (DaF) cooperative cognitive radio (CR) network, an optimal relay can be selected by the conventional max-min selection on the condition of not violating the interference temperature (IT) constraint. However, the max-min selection may cause some extra amount of interference to the primary system (PS) such that the so-called transfer ratio (TR) may be lower. Note that TR is newly defined as the ratio of the secondary system's (SS's) capacity gain to the PS's capacity loss due to the activities of SS. In order to improve the TR value, we are motivated by the pricing function in game theory to propose a novel low-interference relay selection by taking the impacts of the interference from SS to PS into consideration. Using the low-interference selection, however, it will not always allow the optimal relay to be picked. To clarify this phenomenon, the still optimal probability is defined as the probability of selecting the optimal relay by the proposed scheme. In addition, the impacts of the low-interference selection on the SS's capacity and outage probability are also analyzed. The simulation results prove that compared with the max-min selection, the proposed scheme can achieve higher TR values as well as the total capacity which also indicates that a higher spectrum efficiency can be achieved. It is believed that the results of this paper can provide an alternative viewpoint of evaluating the spectrum efficiency and inspire more interesting and important research topics in the future.

The overflow probability is one of criteria that evaluate the performance of fixed-to-variable length (FV) codes. In the single source coding problem, there were many researches on the overflow probability. Recently, the source coding problem for correlated sources, such as Slepian-Wolf coding problem or source coding problem with side information, is one of main topics in information theory. In this paper, we consider the source coding problem with side information. In particular, we consider the FV code in the case that the encoder and the decoder can see side information. In this case, several codes were proposed and their mean code lengths were analyzed. However, there was no research about the overflow probability. We shall show two lemmas about the overflow probability. Then we obtain the condition that there exists a FV code under the condition that the overflow probability is smaller than or equal to some constant.

We propose a high-speed and low-complexity architecture for the very large-scale integration (VLSI) implementation of the maximum a posteriori probability (MAP) algorithm suited to the double binary turbo decoder. For this purpose, equation manipulations on the conventional Linear-Log-MAP algorithm and architectural optimization are proposed. It is shown by synthesized simulations that the proposed architecture improves speed, area and power compared with the state-of-the-art Linear-Log-MAP architecture. It is also observed that the proposed architecture shows good overall performance in terms of error correction capability as well as decoder hardware's speed, complexity and throughput.

In this paper, we consider multiple source and destination antennas based on relay selection scheme to improve the end-to-end outage performance for decode-and-forward cooperative networks. We derive an exact closed-form expression of the outage probability for the proposed system over a Rayleigh fading channel and describe the diversity-multiplexing tradeoff of the system. We then analyze the effects of the number of source and destination antennas on the outage probabilities and diversity-multiplexing tradeoffs.

In this letter, we propose a power allocation scheme to optimize the ergodic secrecy rate of multiple-input single-output (MISO) fading wiretap channels with a probabilistic constraint, using the statistical channel state information (CSI) of the eavesdropper (CSI-E). The analytical expressions of the false secrecy probability are derived and used as constraints in the rate maximization problem. Moreover, we obtain a suboptimal solution by formulating the power allocation problem as a Rayleigh quotient problem.

This paper proposes likelihood smoothing techniques to improve decision tree-based acoustic models, where decision trees are used as replacements for Gaussian mixture models to compute the observation likelihoods for a given HMM state in a speech recognition system. Decision trees have a number of advantageous properties, such as not imposing restrictions on the number or types of features, and automatically performing feature selection. This paper describes basic configurations of decision tree-based acoustic models and proposes two methods to improve the robustness of the basic model: DT mixture models and soft decisions for continuous features. Experimental results for the Aurora 2 speech database show that a system using decision trees offers state-of-the-art performance, even without taking advantage of its full potential and soft decisions improve the performance of DT-based acoustic models with 16.8% relative error rate reduction over hard decisions.

The probability of making mistakes on the decoded signals at the relay has been used for the maximum-likelihood (ML) decision at the receiver in the decode-and-forward (DF) relay network. It is well known that deriving the probability is relatively easy for the uncoded single-antenna transmission with M-pulse amplitude modulation (PAM). However, in the multiplexing multiple-input multiple-output (MIMO) transmission, the multi-dimensional decision region is getting too complicated to derive the probability. In this paper, a high-performance near-ML decoder is devised by applying a well-known pairwise error probability (PEP) of two paired-signals at the relay in the MIMO DF relay network. It also proves that the near-ML decoder can achieve the maximum diversity of MSMD+MR min (MS,MD), where MS, MR, and MD are the number of antennas at the source, relay, and destination, respectively. The simulation results show that 1) the near-ML decoder achieves the diversity we derived and 2) the bit error probability of the near-ML decoder is almost the same as that of the ML decoder.

This paper proposes an adaptive sequential cooperative energy detection scheme for primary user detection in cognitive radio to minimize the detection time while guaranteeing the desired detection accuracy. Simulation results are provided to show the effectiveness of the proposed scheme.