Error Probability Analysis for Ultra-Massive MIMO System and Near-Optimal Signal Detection

In this paper,average bit error probability(ABEP)bound of optimal maximum likelihood(ML)detector is first derived for ultra massive(UM)multiple-input-multiple-output(MIMO)system with generalized amplitude phase modulation(APM),which is confirmed by simulation results.Furthermore,a minimum residual criterion(MRC)based lowcomplexity near-optimal ML detector is proposed for UM-MIMO system.Specifically,we first obtain an initial estimated signal by a conventional detector,i.e.,matched filter(MF),or minimum mean square error(MMSE)and so on.Furthermore,MRC based error correction mechanism(ECM)is proposed to correct the erroneous symbol encountered in the initial result.Simulation results are shown that the performance of the proposed MRC-ECM based detector is capable of approaching theoretical ABEP of ML,despite only imposing a slightly higher complexity than that of the initial detector.

Bayesian estimator of human error probability based on human performance data

A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data and prior information about human performance together,a more accurate and specific HEP estimation can be achieved.For the time-unrelated task without rigorous time restriction,the HEP estimated by the common-used human reliability analysis（HRA） methods or expert judgments is collected as the source of prior information.And for the time-related task with rigorous time restriction,the human error is expressed as non-response making.Therefore,HEP is the time curve of non-response probability（NRP）.The prior information is collected from system safety and reliability specifications or by expert judgments.The（joint） posterior distribution of HEP or NRP-related parameter（s） is constructed after prior information has been collected.Based on the posterior distribution,the point or interval estimation of HEP/NRP is obtained.Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.

Bit error probability of distributed Turbo coded relay systems over quasi-static Rayleigh fading channels

As is known, distributed Turbo coding （DTC） performs close to the theoretic outage probability bound of a relay channel when correct decoding is assumed at the relay. However, decoding error is inevitable in practical fading channels due to the error-prone feature of radio channels, and the decoding error propagation in DTC scheme will severely degrade the error performance of the relay system. As a result, it is necessary to evaluate the error performance of the DTC scheme in multi-hop relaying wireless systems in practical fading channels. Moreover, the theoretical method of analysis provides an effective tool for obtaining the error performance besides lengthy simulations. In this article, the concept of equivalent signal-to-noise ratio （SNR） of the two-hop relay channel and the method of computing equivalent SNR are developed, and then the upper bound on the bit error probability （BEP） of DTC relay systems is analyzed by use of Turbo code＇s distance spectrum, the concept of uniform interleaver, the limit-before-averaging technique, and the union bound method. Both theoretical analysis and numerical simulation are implemented for relay systems with DTC scheme over quasi-static Rayleigh fading channels. The results show that the upper bound approaches the simulation results in the medium to high SNR region.

NEW APPROACH FOR RELIABILITY-BASED DESIGN OPTIMIZATION:MINIMUM ERROR POINT

Conventional reliability-based design optimization （RBDO） requires to use the most probable point （MPP） method for a probabilistic analysis of the reliability constraints. A new approach is presented, called as the minimum error point （MEP） method or the MEP based method, for reliability-based design optimization, whose idea is to minimize the error produced by approximating performance functions. The MEP based method uses the first order Taylor＇s expansion at MEP instead of MPP. Examples demonstrate that the MEP based design optimization can ensure product reliability at the required level, which is very imperative for many important engineering systems. The MEP based reliability design optimization method is feasible and is considered as an alternative for solving reliability design optimization problems. The MEP based method is more robust than the commonly used MPP based method for some irregular performance functions.

Dynamic portfolio choice with uncertain rare‑events risk in stock and cryptocurrency markets

In response to the unprecedented uncertain rare events of the last decade,we derive an optimal portfolio choice problem in a semi-closed form by integrating price diffusion ambiguity,volatility diffusion ambiguity,and jump ambiguity occurring in the traditional stock market and the cryptocurrency market into a single framework.We reach the following conclusions in both markets:first,price diffusion and jump ambiguity mainly determine detection-error probability;second,optimal choice is more significantly affected by price diffusion ambiguity than by jump ambiguity,and trivially affected by volatility diffusion ambiguity.In addition,investors tend to be more aggressive in a stable market than in a volatile one.Next,given a larger volatility jump size,investors tend to increase their portfolio during downward price jumps and decrease it during upward price jumps.Finally,the welfare loss caused by price diffusion ambiguity is more pronounced than that caused by jump ambiguity in an incomplete market.These findings enrich the extant literature on effects of ambiguity on the traditional stock market and the evolving cryptocurrency market.The results have implications for both investors and regulators.

A Unified Bit-to-Symbol Mapping for Generalized Constellation Modulation

Gray mapping is a well-known way to improve the performance of regular constellation modulation,but it is challenging to be applied directly for irregular alternative.To address this issue,in this paper,a unified bit-to-symbol mapping method is designed for generalized constellation modulation(i.e.,regular and irregular shaping).The objective of the proposed approach is to minimize the average bit error probability by reducing the hamming distance(HD)of symbols with larger values of pairwise error probability.Simulation results show that the conventional constellation modulation(i.e.,phase shift keying and quadrature amplitude modulation(QAM)with the proposed mapping rule yield the same performance as that of classical gray mapping.Moreover,the recently developed golden angle modulation(GAM)with the proposed mapping method is capable of providing around1 d B gain over the conventional mapping counterpart and offers comparable performance to QAM with Gray mapping.

Analysis for MIMO correlated frequency-selective channel in the presence of interference

The space time spreading, superimposed training sequences, and space-time coding are used to present a multiple input and multiple output （MIMO） systems model, and a closed-form of average error probability upper bound expression for MIMO correlated frequency-selective channel in the presence of interference （co-channel interference and jamming signals） is derived. Moreover, the correlation at both ends of the wireless link that can be incorporated equivalently into correlation at the transmit end is also derived, which is significant to analyze space-time link algorithm of MIMO systems.

Performance of Relay Networks in Fading Environments with Dominant Specular Components

Radio propagation in dense and super dense wireless networks as well as indoor-to-outdoor picocell networks can have multiple line-of-sight or multiple specular components. The performance of a dual-hop decode-and-forward relaying system over multiple specular components fading channels(MSCC)with multiple Rayleigh distributed co-channel interferers in an interference-limited environment is investigated. The MSCC fading model is designed to allow direct and meaningful comparisons to be made between line-of-sight channels and non-line-of-sight channels, with exact parameter correspondences. Comparisons of outage and bit error performance between Nakagami-m/Rayleigh and MSCC/Rayleigh fading environments show that the MSCC model is needed to describe line-of-sight channels that cannot be accurately modeled by the Nakagami-m, or other fading models.

Handling Uncertainty in Human Cognitive Reliability Method for Safety Assessment Based on DSET

Human Reliability Analysis(HRA)is an important part in safety assessment of a large complex system.Human Cognitive Reliability(HCR)model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time,which is widely used in HRA.In the application of this method,cognitive patterns of humans are required to be considered and classified,and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain.How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy and applicability of HCR.In this paper,a new model was proposed to deal with the uncertain information which exists in the processes of cognitive pattern classification in HCR.First,an evaluation panel was constructed based on expert opinions and processing including setting corresponding anchor points and qualitative indicators of different cognitive patterns,and mapping them to fuzzy numbers and unit intervals.Second,based on the evaluation panel,different analysts judge the cognitive pattern types of actual specific events and provide the level of confidence he or she has in the judgments.Finally,the evaluation opinions of multiple analysts were expressed and fused based on the Dempster-Shafer Evidence Theory(DSET),and the fused results were applied to the HCR model to obtain the Human Error Probability(HEP).A case study was used to demonstrate the procedure and effectiveness of the proposed method.

Asymptotic analysis of multi-branch two-way amplify-and-forward relaying in Nakagami-m fading with arbitrary fading parameter

Two-way relay networks have received lots of attention, thanks to its ability to overcome the loss in the spectral efficiency due to half-duplex transmission. Asymptotic performance analysis can provide valuable insights in- to practical system designs. However, this is a gap in two-way relay network. In this paper, the asymptotic performance is studied for multi-branch dual-hop two-way amplify-and-forward （AF） relaying networks in independently but not necessarily identically distributed （i.n.i.d.） Nakagami-m fading channels, with arbitrary m 〉 5. The approximate prob- ability density function （PDF） of the instantaneous dual-hop link power at high SNR region is derived. Then we present the asymptotic outage probability expression, and analyze the diversity order and coding gain. Simulations are per- formed to verify the tightness of the presented analysis at medium and high SNR regions.

Entanglement-enhanced classical communication through an amplitude-damping channel

We consider the problem of trying to send a single classical bit through an amplitude-damping channel when two transmissions through the channel are available as a resource. It is demonstrated that two entangled transmissions can enhance the receiver＇s capability of making a correct inference under certain conditions compared with two product-state transmissions.

Joint optimization algorithm of sensing thresholds and cooperative users in cooperative detection

Cooperative detection is an effective method to improve the spectrum sensing of Cognitive Radio (CR), and its detection performance can be improved through optimization. An optimization algorithm for cooperative detection based on "OR Rule" which can optimize the detection threshold of each user and the number of cooperative users simultaneously is proposed in this paper. The algorithm, which is based on minimizing the error detection probability, adopts partial fusion to improve the detection performance effectively. The simulation results show that the error detection probability of the proposed algorithm is lower than that of the cooperative detection algorithm with the settled threshold, and the better performance can be achieved through choosing fewer users.

Entanglement-enhanced classical communication through generalized amplitude damping channel

The problem of sending a single classical bit through a generalized amplitude damping channel is considered. When two transmissions through the channel arc available as a resource, we find that two entangled transmissions can enhance the capability of receiver＇s judging information correctly under certain conditions compared with two productstate transmissions. In addition, we find a special case in which the two entangled transmissions can always make a classical bit more effectively disable the noise influence.

M-ary information processing via an optimal nonlinear detector

This paper presents a novel approach of M-ary baseband pulse amplitude modulated signal processing via a parameter-optimized nonlinear dynamic system. This nonlinear system usually shows the phenomenon of stochastic resonance by adding noise. To thoroughly discuss the signal processing performance of the nonlinear system, we tune the system parameters to obtain a nonlinear detector with optimal performance. For characterizing the output of the nonlinear system, the derivation of the probability of detection error is given by the system response speed and the probability density function of the nonlinear system output. By varying the noise intensity with fixed system parameters, the phenomenon of stochastic resonance is shown and by tuning the system parameters with fixed noise, the probability of detection error is minimized and the nonlinear system is optimized. The detection performance of the two cases is compared with the theoretical probability of detection error, which is validated by numerical simulation.

Performance analysis of cooperative diversity for two-way multi-relay system with channel estimation error

In this work, we consider an amplify-and-forward two-way multi-relay system for wireless communication and mvesngate me effect of channel estimation error on the error rate performance. With the derivation of effective signal-to-noise ratio at the transceiver and its probability density function, we can get approximate expression for average bit error rate. Simulation results are performed to verify the analytical results.

Modelling the probability of erroneous negative lymph node staging in patients with colon cancer

Background:Patients in who with insufficient number of analysed lymph nodes(LNs)are more likely to receive an incorrect LN staging.The ability to calculate the overall probability of undiagnosed LN involvement errors in these patients could be very useful for approximating the real patient prognosis and for giving possible indications for adjuvant treatments.The objective of this work was to establish the predictive capacity and prognostic discriminative ability of the final error probability(FEP)among patients with colon cancer and with a potentially incorrectly-staged LN-negative disease.Methods:This was a retrospective multicentric population study carried out between January 2004 and December 2007.We used a mathematical model based on Bayes’theorem to calculate the probability of LN involvement given a FEP test result.Cumulative sum graphs were used to calculate risk groups and the survival rates were calculated,by month,using the Kaplan-Meier method.Results:A total of 548 patients were analysed and classified into three risk groups according to their FEP score:low-risk(FEP<2%),intermediate-risk(FEP 2%-15%),and high-risk(FEP>15%).Patients with LN involvement had the lowest overall survival rate when compared to the three risk groups.This difference was statistically significant for the low-and intermediate-risk groups(P=0.002 and P=0.004,respectively),but high-risk group presented similar survival curves to pN+group(P=0.505).In terms of disease-free survival,the high-risk group presented similar curves to the intermediate-risk group until approximately 60 months’follow-up(P=0.906).After 80 months’follow-up,the curve of high-risk group coincided with that of the pN+group(P=0.172).Finally,we summarized the FEP according to the number of analysed LNs and accompanied by a contour plot which represents its calculation graphically.Conclusions:The application of Bayes’theorem in the calculation of FEP is useful to delimit risk subgroups from among patients without LN involvement.

ERROR DETECTION CAPABILITY OF SHORTENED HAMMING CODES AND THEIR DUAL CODES

The undetected error probability and error detection capability of shortened Hamming codes and their dual codes are studied in this paper. We also obtain some interesting properties for the shortened Simplex codes.

The undetected error probabilities of combinatorial codes and their dual codes

IT is known that the average undetected error probability （UEP） of a binary [n, k] code Con a binary symmetric channel with crossover probability p is given byPe（p） = sum from i=1 Aipi（1-p）n-1, （1）where （A0, A1,…, An） is the weight distribution of C. If for all 0≤p≤0.5, Pe（p）≤Pe（0. 5） = 2k-n-2-n, then C is called good for error detection. Moreover, if Pe （p） ismonotonously increasing in the interval [0, 0.5], then C is called proper. Clearly, propercodes are good.

Minimax Optimal Rates of Convergence for Multicategory Classifications

In the problem of classification （or pattern recognition）, given a set of n samples, we attempt to construct a classifier gn with a small misclassification error. It is important to study the convergence rates of the misclassification error as n tends to infinity. It is known that such a rate can＇t exist for the set of all distributions. In this paper we obtain the optimal convergence rates for a class of distributions L^（λ,ω） in multicategory classification and nonstandard binary classification.

Optimal fusion rule for cooperative spectrum sensing in cognitive radio networks

In this paper, we analyze performance of cooperative spectrum sensing under counting rules when exponential model is utilized to characterize the burst nature of primary user （PU） link. Our objective is to minimize the average error probability （AEP） so that the link utilization in the considered link achieves its maximum. We derive a closed-form expression of AEP as well as the probability of interference （PoI） by classifying cognitive transmission into six events. Then, we consider the minimization of AEP over counting rules under the constraint of interference. As the solution, we develop an efficient algorithm to evaluate the optimal fusion rule. Finally, we verify our analysis in numerical results.