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How to obtain a high return and face the low-risk investment is a hot topic widely discussed among investors. However, the specific method of targeting the optimal portfolio requires sophisticated mathematical computations. By research, some scholars found that the theory of portfolio helps investors to get a higher return and reduce investment risk. Thus, the aim of this paper is to collect and optimize a selected portfolio—Apple, Google, Netflix, Tesla, and Walmart—by GARCH model and Sharpe ratio, based on the mean returns and correlation matrix, among which Google and Apple are strongly positively correlated to each other, while Walmart, Tesla, and Netflix are weakly positively correlated. The price return of GARCH volatility of each equity shows the stock returns will go down in the next 7 days. We compare the optimal portfolio with NASDAQ composite to find the superiority of our model.

In this paper, two novel spectrum resource allocation schemes, based on orthogonal frequency division multiplexing with index modulation (OFDM-IM) and dual-mode OFDM-IM, are proposed for a three-node cooperative non-orthogonal multiple access (C-NOMA) system. In the first scheme, we allocate IM bits to serve the cell-edge user, and save the transmit power to assist the delivery of constellation symbols. Alternatively, constrained by the spectral efficiency (SE), the rest information bits of the cell-edge user can be carried by the conventional signal constellation. In the second scheme, to further eliminate the interference between users and boost the SE, different modulation modes (Mode I and Mode II) are employed to distinguish the subcarriers of the cell-center and cell-edge users, and to encode the incoming bit stream from these users, respectively. Furthermore, we consider two different detectors for the cell-edge user, i.e., the optimal/suboptimal maximum-likelihood detectors. Asymptotically tight bounds on the bit error rate of the above-mentioned users are derived in closed-form. Finally, simulation results verify the theoretical analysis and show that the proposed schemes have the potential to outperform C-NOMA.

The media-based modulation (MBM) system, which varies its channel state by controlling the on/off status of the radio frequency (RF) mirrors, and embeds additional information bits into the mirror activation pattern, is capable of achieving significant throughput and desirable bit-error-rate (BER) performance. Hence, it has attracted increasing attention from researchers of wireless communication community. In this paper1, the information secrecy issue for MBM is investigated, and a secure single-input-multiple-output MBM (SIMO-MBM) system is proposed utilizing physical-layer security techniques. By considering the time-division duplexing (TDD) mode with channel reciprocity property, the legitimate channel state information (CSI) is applied to secure the data transmission of SIMO-MBM. More specifically, on one hand, adaptive phase rotation is imposed on the transmitted signals, where the rotation angle is determined by the phase of legitimate CSI; on the other hand, the mapping rule between the mirror activation pattern and binary bits is changed according to the amplitude of legitimate CSI. The BER performance of the eavesdropper is investigated via theoretical derivations, and the system secrecy mutual information is also derived, based on which the optimal design of the adaptive phase rotation strategy is provided. Theoretical and simulative results demonstrate that the proposed secure SIMO-MBM system is capable of enhancing the data confidentiality whilst keeping reliable data transmission.

Terahertz (THz) communication has emerged as a promising technology that efficiently alleviates the scarcity of the frequency resources, and is capable of providing Terabit-per-second (Tbps) data transmission. However, the hardware impairments, which are usually omitted in the low-rate systems, have a detrimental impact on the THz communication link. These hardware imperfections, including in-phase/quadrature (I/Q) imbalance, phase noise and nonlinearities of the power amplifier, can be approximately modelled as complex-Gaussian distortions at both the transmitter and the receiver. In this paper, the channel estimator and signal detector (CE/SD) design of the THz-band spatial modulation (THz-SM) system is investigated, where the counterparts for classical low-rate SM are no longer applicable. More specifically, a dual-stage maximum-likelihood (ML) channel estimator is proposed containing two phases of candidate acquirement and exhaustive search. Then a novel low-complexity mean-least-squares (MLS) channel estimator is developed by considering the hardware impairments in an averaging manner. Besides, the optimal detector for THz-SM is designed by taking hardware impairments into account. Simulation results validate that the proposed CE/SD design is capable of attaining reliable data transmission in THz-SM with hardware imperfections.

Angiotensin I-Converting Enzyme (ACE, CD143) Gene plays a crucial role in the pathology of carcinomas in many cancers including colorectal cancer (CRC). However, the methylation of ACE was rarely r...

In 5G wireless networks, the escalating teletraffic and energy consumption has necessitated the development of green communication techniques in order to further enhance both the system’s spectral efficiency and energy efficiency. In the past few years, the novel index modulation (IM) has emerged as a promising technology that is widely employed in wireless communications. In this paper, we present a survey on IM in order to provide the readers with a better understanding of its principles, advantages, and potential applications. We start with a comprehensive literature review, where the concept of IM is introduced, and various existing IM schemes are classified according to their signal domains, including the frequency domain, spatial domain, time domain and channel domain. Then the principles of different IM-aided systems are detailed, where the transceiver design is illustrated, followed by descriptions of typical systems and corresponding performance evaluation. A range of challenges and open issues on IM are discussed before we conclude this survey.

With the rapid expansion of road traffic and vehicle scale, citizens have to face the serious life safety risks caused by vehicle accidents while enjoying an increasingly convenient life. Fortunately, vehicular ad hoc networks have provided us with important information about vehicle big data, which makes us have new methods to analyze vehicle traffic accidents. In this paper, we tackle the problem of predicting the risk of vehicle accidents and propose the trichotomy Adaboost with SMOTE and One-Hot encoding (AdaBoost-SO) algorithm to attain a vehicle accident risk prediction model. In this paper, predicting accident risk is mainly based on the use of big data mining and analysis of real-life accidents data. First, the experimental dataset is reconstructed by a synthetic minority oversampling technique. We complement the missing data and encode each sample feature to one-hot code. Second, the trichotomy AdaBoost algorithm is, respectively, used to train a series of weak classifiers from the experimental dataset and then combine them into a strong classifier to get the prediction model. Finally, the extensive simulation results illustrate that using the prediction model by trichotomy AdaBoost-SO algorithm can take the area under the curve of 0.77 and real-time into account. Through risk prediction and early warning, it provides the intelligent transportation system and driving safety assistance with a theoretical foundation.

Traffic accidents have globally increased over the past decades, and the driving safety has become an important issue for human society. Despite great progress, the existing driving safety prediction algorithms hardly consider the sophisticated feature interactions between the driving information, traffic information, and driver information. Therefore, in order to solve this problem, a factorization machine combined neural network (FMCNN) is proposed in this paper to predict the driving safety in vehicular communication. In the proposed framework, the factorization machine and the deep neural network are used to learn the effects of low-order and high-order feature interactions from the driving information and the weather information in the pre-training phase, respectively. After the pre-training phase, the high-order feature interactions extracted by the last hidden layer of the deep neural network and the low-order feature interactions trained by the factorization machine are the input of a new deep neural network to predict the driving safety. Varying from the most machine learning algorithms, the proposed algorithm does not require manual extraction of features. It can automatically extract features from the driving information, traffic information, and driver information collected by the vehicle ad hoc network. The experiment results show that the prediction result of the proposed FMCNN is better than DNN and FM in AUC and Logloss.

The convergence of sensing and communication in the millimeter-wave (mmWave) and low terahertz (THz) bands has been envisioned as a promising technology, since it incorporates high-rate data transmission of hundreds of Gbps and mm-level radar sensing in a spectrum- and cost-efficient manner, by sharing both the frequency and hardware resources. However, the joint radar sensing and communication (JRC) system faces considerable challenges in the mmWave and low-THz scale, due to the peculiarities of the propagation channel and radio-frequency (RF) front ends. To this end, the waveform design for the JRC systems in mmWave and low-THz bands with ultra-broad bandwidth is investigated in this paper. Firstly, by considering the JRC design based on the co-existence concept, where both functions operate in a time-domain duplex (TDD) manner, a novel multi-subband quasi-perfect (MS-QP) sequence, composed of multiple perfect subsequences on different subbands, is proposed for target sensing, which achieves accurate target ranging and velocity estimation, whilst only requiring cost-efficient low-rate analog-to-digital converters (A/Ds) for sequence detection. Furthermore, the root index of each perfect subsequence is designed to eliminate the influence of strong Doppler shift on radar sensing. Finally, a data-embedded MS-QP (DE-MS-QP) waveform is constructed through time-domain extension of the MS-QP sequence, generating null frequency points on each subband for data transmission. Unlike the co-existence-based JRC system in TDD manner, the proposed DE-MS-QP waveform enables simultaneous interference-free sensing and communication, whilst inheriting all the merits from MS-QP sequences. Numerical results validate the superiority of the proposed waveforms regarding the communication and sensing performances, hardware cost as well as flexibility of the resource allocation between the dual functions.

Terahertz (THz) wireless communication is envisioned as a promising technology, which is capable of providing ultra-high-rate transmission up to Terabit per second. However, some hardware imperfections, which are generally neglected in the existing literature concerning lower data rates and traditional operating frequencies, cannot be overlooked in the THz systems. Hardware imperfections usually consist of phase noise, in-phase/quadrature imbalance, and nonlinearity of power amplifier. Due to the time-variant characteristic of phase noise, frequent pilot insertion is required, leading to decreased spectral efficiency. In this paper, to address this issue, a novel pilot design strategy is proposed based on index modulation (IM), where the positions of pilots are flexibly changed in the data frame, and additional information bits can be conveyed by indices of pilots. Furthermore, a turbo receiving algorithm is developed, which jointly performs the detection of pilot indices and channel estimation in an iterative manner. It is shown that the proposed turbo receiver works well even under the situation where the prior knowledge of channel state information is outdated. Analytical and simulation results validate that the proposed schemes achieve significant enhancement of bit-error rate performance and channel estimation accuracy, whilst attaining higher spectral efficiency in comparison with its classical counterpart.

Background: This study was conducted to detect the expression of Cdc42 interacting protein 4 (CIP4) in patients with colorectal cancer (CRC), and explore the role of CIP4 in prognosis of CRC patients.Methods: The expression of CIP4 mRNA was determined by quantitative real-time PCR (qRT-CPR) and compared by student’s t-test between groups. Relationships of clinical characteristics and CIP4 expression were analyzed by Chi-square test. Kaplan-Meier curves were used to estimate the overall survival of CRC patients. And Cox regression analysis was conducted to identify the prognostic biomarkers for CRC patients.Results: The qRT-PCR results showed that CRC tissues were detected with significantly high CIP4 mRNA expression compared with adjacent normal controls (PCIP4 in CRC tissues was influenced by distant metastasis (P=0.021), lymphatic invasion (P=0.012) and TNM stage (P=0.006). But, other clinical factors including age, gender, differentiation and tumor site were proved to have no obvious effects on CIP4 expression (all, P>0.05). The survival curves showed that patients with high CIP4 expression generally lived shorter than those with low CIP4 expression (PP=0.044, HR=1.631, 95%CI=1.013-2.626) and CIP4 expression (P=0.000, HR=5.283, 95%CI=3.138-8.893) were of great prognostic significance for CRC patients.Conclusion: Taken together, up-regulation of CIP4 in CRC tissues represented poor prognosis for patients.

Background: The study was performed to compare the diagnostic roles of computed tomography (CT) and carcinoembryonic antigen (CEA) in colorectal liver metastasis (CRLM).Methods: 255 patients with colorectal cancer (CRC) were enrolled. These patients were confirmed as CRLM by histopathological assay. CT scans of the liver were performed with a 64-slice CT system. Serum CEA levels were determined using a human circulating cancer biomarker magnetic bead panel. True positive (TP), false positive (FP), true negative (TN) and false negative (FN) were calculated for CT and CEA with histopathological assay as golden standard.Results: 142 CRLM patients and 113 non-CRLM patients were confirmed in the study. There were no obvious differences in age, sex and Dukes stage between CRLM and non-CRLM patients (P＞0.05). Diagnostic roles of CT and CEA on per-patient and per-lesion were analyzed. Detection sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of CT on per-patient basis were 74.7%, 56.4%, 52.1%, and 77.9%, respectively. Sensitivity, specificity, PPV and NPV of CEA were 64.4%, 51.4%, 49.3%, and 67.3%. In the analysis on per-lesion basis, detection sensitivity, specificity, PPV, and NPV of CT were increased to 87.8%, 88.8%, 91.5%, and 84.1%, respectively. Detection sensitivity, specificity, PPV and NPV of CEA on per-lesion basis were 82.6%, 64.4%, 63.4%, and 83.2%.Conclusion: CT exhibited better performances than CEA in diagnosis of CRLM on both of per-patient and per-lesion basis.

Background: Gastric cancer (GC) represents one of the most serious cancers worldwide with the increasing mortality. Metastasis associated lung adenocarcinoma transcript 1 (MALAT1), a kind of lncRNAs, has been reported to be involved in the progression of cancers. This study aimed to assess serum expression pattern of MALAT1 and its clinical significance in diagnosis of GC.Methods: Serum specimens were collected from 120 GC patients and 58 healthy individuals. The expression profile of MALAT1 was examined using quantitative real-time polymerase chain reaction (qRT-PCR), and its association with clinical parameters was estimated by chi-square test. The diagnostic value of MALAT1 in GC was evaluated by the receiver operating characteristic (ROC) analysis.Results: Upregulated expression of MALTA1 was found in GC patients compared with the healthy controls (PConclusion: The expression of MALAT1 was upregulated in GC serum samples, and its expression might serve as a potential diagnostic biomarker in patients with GC.

Background: Breast cancer is one of the most common cancers among females with high morbidity and mortality. MicroRNAs (miRNAs) have been reported to play important roles in the development of cancers. However, the prognostic value of microRNA-421 (miR-421) in breast cancer have not been extensively explored.Methods: Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect the relative expression of miR-421 in breast cancer tissue samples. Relationships between miR-421 expression and clinicopathological factors were analyzed by chi-square test. The effects of several variables on survival status were tested by Kaplan-Meier curve and Cox proportional hazards regression analyses.Results: MiR-421 expression was significantly decreased in breast cancer tissues, compared with adjacent noncancerous tissues (PmiR-421 expression was closely correlated with lymph node metastasis (PP=0.021), and differentiation (P=0.044) of breast cancer patients. Kaplan-Meier analysis revealed that patients with low miR-421 expression had a shorter overall survival time than those with high miR-421 expression (P=0.001). Furthermore, multivariate analysis demonstrated that miR-421 (P=0.014, HR=2.000, 95%CI: 1.149-3.480) was an independent prognostic indicator in breast cancer patients, as well as lymph node metastasis (P=0.016, HR=1.987, 95%CI: 1.137-3.474).Conclusion: The reduced expression of miR-421 may predict the poor prognosis of breast cancer and miR-421 may be involved in the progression of breast cancer.

Background The HOXA9 gene, belonging to homeobox (HOX) gene family, has been recently reported dys-expressed in several kinds of human cancers. This study aimed to investigate the expression of HOXA9 and its prognostic value in cervical cancer. Methods The HOXA9 mRNA expression was detected with a quantitative real-time polymerase chain reaction (qRT-PCR) assay, and the association of HOXA9 expression with clinical characteristic was analyzed via chi-square test. Kaplan-Meier and cox regression analyses were conducted to estimate the prognostic value of HOXA9 in cervical cancer. Results HOXA9 expression was significantly down-expressed in cervical cancer tissues compared with that in adjacent normal tissues (P HOXA9 was significantly associated with TNM stage, pathological grade, FIGO stage and differentiation (All P HOXA9 expression was shorter than those with high HOXA9 expression (log rank test, P = 0.000). Cox regression analysis revealed that HOXA9 had a high prognostic value in cervical cancer. Conclusion HOXA9 is down-regulated and involved in the development of cervical cancer. Moreover, it may be an useful independent prognostic bio-marker for patients with cervical cancer.

Background: Long non-coding RNA (lncRNA) plays an important role in carcinoma progression and prognosis. However, little is known about the pathological role of lncRNA Sox2ot in colorectal cancer (CRC) patients. This study sought to investigate the expression level of lncRNA Sox2ot in CRC, as well as explore its association with CRC progression and prognosis. Methods: LncRNA Sox2ot expression was measured in 117 paired CRC tissues and adjacent non-cancerous tissues using quantitative real-time polymerase chain reaction (qRT-PCR). Then, the relationship between lncRNA Sox2ot expression and clinicopathological characteristic of CRC patients was detected by Chi-square test. Lastly, relationship between the expression level of lncRNA Sox2ot and overall survival (OS) was analyzed using Kaplan–Meier analysis and univariate and multivariate analyses were evaluated by Cox regression models. Results: The expression level of lncRNA Sox2ot in CRC tissues were significantly higher than in the adjacent non-cancerous tissues (P

Backgrounds: Serum microRNAs (miRNAs) are a novel class of diagnostic biomarkers for human cancers. However, the clinical relevance of circulating microRNA-429 (miR-429) in cervical cancer patients remains unclear. The purpose of this study was to investigate serum miR-429 levels in cervical cancer patients, as well as its association with clinical characteristics and diagnostic value.Methods: Serum miR-429 expression was investigated in 113 cervical cancer patients and 107 healthy normal controls by quantitative real-time PCR (qRT-PCR). Chi-square test was applied to evaluate the correlation between miR-429 expression and clinicopathological parameters. Receiver operating characteristic (ROC) curves were constructed to assess the diagnostic significance of serum miR-429 in cervical cancer.Results: Serum miR-429 expression was significantly down-regulated in cervical cancer compared with healthy controls (P=0.000). In addition, serum miR-429 level was correlated with differentiation (P=0.031), FIGO stage (P=0.030), and lymph node metastasis (P=0.045). ROC curves demonstrated that serum miR-429 expression could distinguish cervical cancer patients from healthy controls with the sensitivity of 81.4% and the specificity of 69.2%. Additionally, the area under the curve (AUC) was 0.816 and the cut-off value was 0.825.Conclusion: MiR-429 is down-regulated in cervical cancer and associated with aggressive clinical characteristics. MiR-429 may be a potential diagnostic biomarker for cervical cancer.

In this paper, we propose an EADO-OFDM (Enhanced Asymmetrically Clipped DC Biased Optical Orthogonal Frequency Division Multiplexing) method for IM/DD (Intensity-Modulated DirectDetection) optical systems, in which the AV-DCO-OFDM (Absolute Valued DC Biased Optical OFDM) symbols on the even subcarriers and ACO-OFDM (Asymmetrically Clipped Optical OFDM) symbols on the odd subcarriers are combined for simultaneous transmission. Moreover, we discuss the PDF (Probability Density Function) and electrical SNR (Signal to Noise Ratio) of the symbols, which are utilized to estimate the BER (Bit Error Ratio) performance and overall performance of EADO-OFDM. The Monte Carlo simulation results have validated the theoretical analysis and have also confirmed the EADO-OFDM is attractive considering the following benefits. Firstly, EADO-OFDM is more energy effcient compared to the power-effcient DCO-OFDM (DC Biased Optical OFDM), since the required DC bias is smaller when appropriate constellation size combinations are chosen. In addition, EADO-OFDM performs better than the conventional ADO-OFDM (Asymmetrically Clipped DC Biased Optical OFDM), because the absolute value operation causes no clipping distortion.

Dual-mode index modulation aided orthogonal frequency division multiplexing (DM-OFDM) is recently proposed, where subcarriers are partitioned into OFDM subblocks, divided into two groups within each subblock, and modulated by two differentiable constellation alphabets. In DM-OFDM, additional bits can be transmitted through indices of subcarriers modulated by the same constellation alphabet. In this letter, generalized DM-OFDM (GDM-OFDM) is proposed, where the number of subcarriers modulated by the same constellation mode in each subblock is alterable. By applying such enhancement, the spectral efficiency can be improved at the cost of marginal performance loss. Moreover, since the BER performance of GDM-OFDM degrades at low signal-to-noise ratios (SNRs), an interleaving technique is employed to address this issue. At the receiver, a maximum-likelihood (ML) detector and a reduced-complexity log-likelihood ratio (LLR) detector are employed for demodulation. Simulation results demonstrate that the proposed GDMOFDM is capable of enhancing the spectral efficiency compared with DM-OFDM at the cost of negligible performance loss, and the interleaved GDM-OFDM (IGDM-OFDM) can harvest on performance gain over GDM-OFDM.

Orthogonal frequency-division multiplexing (OFDM) with index modulation has been emerged as a promising technique for next-generation networks, where the specific activation pattern of the OFDM subcarriers is capable of conveying additional information implicitly without additional energy consumption, hence improving the system energy efficiency. In this paper, zero-padded tri-mode OFDM with index modulation (ZTM-OFDM-IM) is proposed, which is capable of achieving high spectral and energy efficiency. In ZTM-OFDM-IM, subcarriers are partitioned into subblocks. In each OFDM subblock, only a fraction of subcarriers are modulated by two distinguishable constellation alphabets, while the others remain empty, which reduces the energy consumption. With such an arrangement, extra information bits can be carried by the subcarrier activation pattern. At the receiver, a maximum-likelihood (ML) detector as well as a reduced-complexity two-stage log-likelihood ratio (LLR) detector are developed for signal demodulation. Theoretical performance analysis based on Euclidean distance metric and pairwise error probability are conducted. Besides, in order to attain better BER performance, the design strategies for the two distinguishable constellation alphabets are investigated, which is followed by brief discussions on generalization methods for the proposed ZTM-OFDM-IM. It is demonstrated via Monte Carlo simulations that ZTM-OFDM-IM is capable of enhancing the BER performance compared with the conventional OFDM and other conventional index-modulated OFDM benchmarks, which provides high-rate data transmission with low energy consumption. Moreover, the LLR detection of ZTM-OFDM-IM only suffers from slight performance loss in comparison with the ML detection and achieves significant complexity reduction.

The protein factor Glomulin (Glmn) is a regulator of the SCF (Skp1-CUL1-F-box protein) E3 ubiquitin-protein ligase complex. Mutations of Glmn lead to glomuvenous malformations. Glmn has been reported to be associated with FK506-binding proteins (FKBP). Here we present in vitro binding analyses of the FKBP-Glmn interaction. Interestingly, the previously described interaction of Glmn and FKBP12 was found to be comparatively weak. Instead, the closely related FKBP12.6 and FKBP51 emerged as novel binding partners. We show different binding affinities of full length and truncated FKBP51 and FKBP52 mutants. Using FKBP51 as a model system, we show that two amino acids lining the FK506-binding site are essential for binding Glmn and that the FKBP51-Glmn interaction is blocked by FKBP ligands. This data suggest FKBP inhibition as a pharmacological approach to regulate Glmn and Glmn-controlled processes.

Ellipse-based DC-biased optical orthogonal frequency division multiplexing (E-DCO-OFDM) is proposed for visible light communications (VLC), which achieves a significant peak-to-average power ratio (PAPR) reduction, thus enhancing the overall performance when light-emitting diode (LED) nonlinearity is considered. In E-DCO-OFDM, the real-valued output of OFDM is modulated onto an ellipse, whereby only the imaginary part of the complex point on the ellipse is transmitted. Although the PAPR of E-DCO-OFDM decreases as the ratio of major radius to minor radius becomes larger, it may be more vulnerable to the effect of noise, leading to the performance loss. Therefore, the relationship between the system performance and the critical parameters in E-DCO-OFDM, such as the ratio between the major and minor radius of the ellipse, is investigated. Meanwhile, simulations demonstrate that E-DCO-OFDM adopting the optimal parameters achieves a considerable signal-to-noise ratio (SNR) gain over the conventional DCO-OFDM.

The co-chaperone FKBP5 is a stress-responsive protein-regulating stress reactivity, and its genetic variants are associated with T2D related traits and other stress-related disorders. Here we show that FKBP51 plays a role in energy and glucose homeostasis. Fkbp5 knockout (51KO) mice are protected from high-fat diet-induced weight gain, show improved glucose tolerance and increased insulin signaling in skeletal muscle. Chronic treatment with a novel FKBP51 antagonist, SAFit2, recapitulates the effects of FKBP51 deletion on both body weight regulation and glucose tolerance. Using shorter SAFit2 treatment, we show that glucose tolerance improvement precedes the reduction in body weight. Mechanistically, we identify a novel association between FKBP51 and AS160, a substrate of AKT2 that is involved in glucose uptake. FKBP51 antagonism increases the phosphorylation of AS160, increases glucose transporter 4 expression at the plasma membrane, and ultimately enhances glucose uptake in skeletal myotubes. We propose FKBP51 as a mediator between stress and T2D development, and potential target for therapeutic approaches., Stress is recognized as risk factor for the development of type 2 diabetes. Here Balsevich et al. show that the stress responsive co-chaperone FKBP5 regulates glucose metabolism in mice by modulating AS160 phosphorylation, glucose transporter expression and muscle glucose uptake.

Index modulation has become a promising technique in the context of orthogonal frequency division multiplexing (OFDM), whereby the specific activation of the frequency domain subcarriers is used for implicitly conveying extra information, hence improving the achievable throughput at a given bit error ratio (BER) performance. In this paper, a dual-mode OFDM technique (DM-OFDM) is proposed, which is combined with index modulation and enhances the attainable throughput of conventional index-modulation-based OFDM. Specifically, the subcarriers are divided into several subblocks, and in each subblock, all the subcarriers are partitioned into two groups, modulated by a pair of distinguishable modem-mode constellations, respectively. Hence the information bits are conveyed not only by the classic constellation symbols, but implicitly also by the specific activated subcarrier indices, representing the subcarriers’ constellation mode. At the receiver, a maximum likelihood (ML) detector and a reduced-complexity near optimal log-likelihood ratio (LLR) based detector are invoked for demodulation. The minimum distance between the different legitimate realizations of the OFDM subblocks is calculated for characterizing the performance of DM-OFDM. Then the associated theoretical analysis based on the pairwise error probability is carried out for estimating the BER of DM-OFDM. Furthermore, the simulation results confirm that at a given throughput DM-OFDM achieves a considerably better BER performance than other OFDM systems using index modulation, while imposing the same or lower computational complexity. The results also demonstrate that the performance of the proposed low-complexity detector is indistinguishable from that of the ML detector, provided that the system’s signal to noise ratio is sufficiently high.

The primary objective of this study is to compare pedestrian evacuation strategies in the large-scale public space (LPS) using microscopic model. Data were collected by video recording from Tian-yi square for 36 hours in city of Ningbo, China. A pedestrian evacuation simulation model was developed based on the social force model (SFM). The simulation model parameters, such as reaction time, elasticity coefficient, sliding coefficient, et al, were calibrated using the real data extracted from the video. Five evacuation strategies, strategy 1 (S1) to strategy 5 (S5) involving distance, density and capacity factors were simulated and compared by indicators of evacuation time and channel utilization rate, as well as the evacuation efficiency. The simulation model parameters calibration results showed that a) the pedestrians walking speed is 1.0 ~ 1.5m/s; b) the pedestrians walking diameter is 0.3 ~ 0.4m; c) the frequency of pedestrian arrival and departure followed multi-normal distribution. The simulation results showed that, (a) in terms of total evacuation time, the performance of S4 and S5 which considering the capacity and density factors were best in all evacuation scenarios, the performance of S3 which only considering the density factor was the worst, relatively, and S1 and S2 which considering the distance factor were in the middle. (b) the utilization rate of channels under S5 strategy was better than other strategies, which performs best in the balance of evacuation. S3 strategy was the worst, and S1, S2 and S4 were in the middle. (c) in terms of the evacuation efficiency, when the number of evacuees is within 2, 500 peds, the S1 and S2 strategy which considering the distance factor have best evacuation efficiency than other strategies. And when the number of evacuees is above 2, 500 peds, the S4 and S5 strategy which considering the capacity factor are better than others.

Phase modulation is used in DCO-OFDM for visible light communications, whereby around 10 dB PAPR reduction is achieved. Considering the nonlinearity of LED emitters, our proposed method achieves better BER performance than that of conventional DCO-OFDM.

Single-photon avalanche diode (SPAD) is a promising photosensor because of its high sensitivity to optical signals in weak illuminance environment. Recently, it has drawn much attention from researchers in visible light communications (VLC). However, existing literature only deals with the simplified channel model, which only considers the effects of Poisson noise introduced by SPAD, but neglects other noise sources. Specifically, when an analog SPAD detector is applied, there exists Gaussian thermal noise generated by the transimpedance amplifier (TIA) and the digital-to-analog converter (D/A). Therefore, in this paper, we propose an SPAD-based VLC system with pulse-amplitude-modulation (PAM) under Poisson-Gaussian mixed noise model, where Gaussian-distributed thermal noise at the receiver is also investigated. The closed-form conditional likelihood of received signals is derived using the Laplace transform and the saddle-point approximation method, and the corresponding quasi-maximum-likelihood (quasi-ML) detector is proposed. Furthermore, the Poisson-Gaussian-distributed signals are converted to Gaussian variables with the aid of the generalized Anscombe transform (GAT), leading to an equivalent additive white Gaussian noise (AWGN) channel, and a hard-decision-based detector is invoked. Simulation results demonstrate that, the proposed GAT-based detector can reduce the computational complexity with marginal performance loss compared with the proposed quasi-ML detector, and both detectors are capable of accurately demodulating the SPAD-based PAM signals.