Payload Symbol-Based Nonlinear RF Fingerprint for Wireless QPSK-OFDM Devices

Radio Frequency(RF) fingerprinting is one physical-layer authentication method for wireless communication, which uses the unique hardware characteristic of the transmitter to identify its true identity.To improve the performance of RF Fingerprint(RFF)based on preamble with fixed duration, a nonlinear RF fingerprinting method based on payload symbols is proposed for the wireless OFDM communication with the bit mapping scheme of QPSK. The wireless communication system is modeled as a Hammerstein system containing the nonlinear transmitter and multipath fading channel. A parameter separation technique based on orthogonal polynomial is presented for the estimation of the parameters of the Hammerstein system. The Hammerstein system parameter separation technique is firstly used to estimate the linear parameter with the training signal, which is used to compensate the adverse effect of the linear channel for the demodulation of the successive payload symbols. The demodulated payload symbols are further used to estimate the nonlinear coefficients of the transmitter with the Hammerstein system parameter separation technique again, which is used as the novel RFF for the authentication of the QPSK-OFDM device. Numerical simulations have verified the proposed method, which can also be extended to the OFDM signals with other bit mapping schemes.

A Deep Learning Driven Feature Based Steganalysis Approach

The goal of steganalysis is to detect whether the cover carries the secret information which is embedded by steganographic algorithms.The traditional ste-ganalysis detector is trained on the stego images created by a certain type of ste-ganographic algorithm,whose detection performance drops rapidly when it is applied to detect another type of steganographic algorithm.This phenomenon is called as steganographic algorithm mismatch in steganalysis.To resolve this pro-blem,we propose a deep learning driven feature-based approach.An advanced steganalysis neural network is used to extract steganographic features,different pairs of training images embedded with steganographic algorithms can obtain diverse features of each algorithm.Then a multi-classifier implemented as lightgbm is used to predict the matching algorithm.Experimental results on four types of JPEG steganographic algorithms prove that the proposed method can improve the detection accuracy in the scenario of steganographic algorithm mismatch.

A Near Optimal Power Allocation Scheme for Cooperative Relay Networking with NOMA

In this paper, we propose cooperative relay networks with non-orthogonal multiple access in order to design a near-optimal power allocation strategy. Like other next generation wireless technologies, spatially multiplexed transmissions are achieved by relay nodes which enables decode-and-forward relaying of a new superposition code after reception from the source. It is worth noting that, since it is hard to exactly prove the proposed PA scheme, due the fact that it is one kind of the approximate conjectures. Therefore, mathematical and numerical methods have been used to clarify the feasibility of the proposal. Numerical results indicate that it is able to asymptotically achieve the optimal sum rate at the higher signal-to-noise ratio region with the proposed strategy applied instead of negligible performance loss.

Quantitative Survivability Analysis Using Probability Model Checking: A Study of Cluster-Based Vehicle Networks with Dual Cluster Heads

As an important part of future 5G wireless networks,a vehicular network demands safety,reliability and connectivity.In this context,networking survivability is usually considered an important metric to evaluate network performance.In this paper,we propose a survivability model for vehicle communication networking based on dual cluster heads,wherein a backup cluster head(CH)will be activated if the primary CH fails,thereby effectively enhancing the network lifetime.Additionally,we introduce a software rejuvenation strategy for the prime CH to further improve the survivability of the entire network.Using the Probabilistic Symbolic Model Checker(PRISM),we verify and discuss the proposed survivability model via numerical simulations.The results show that network survivability can be effectively improved by introducing an additional CH and further enhanced by adopting the software rejuvenation technique.

Use of NOMA for Maritime Communication Networks with P-DF Relaying Channel

In this paper,a partial decode-and-forward(P-DF)cooperative relaying network(CRN)with non-orthogonal multiple access(P-DF-CRN-NOMA)for maritime space communications is proposed.Without loss of generality,three kinds of relay forwarding protocols are studied to characterize the superiority of the proposed P-DF-CRN-NOMA scheme,where,after receptions from the coastal base station(BS),the island relay forwards the successful decoded symbols to the ship user to avoid the performance loss provided by the high decoding requirement in decode-and-forward(DF).To further improve the system performance,as well as for a fairness comparison,the maximum ratio combining(MRC)is utilized at the ship user.Specifically,to present the impact of the channel qualities,the scenarios of the weak and strong links that from the source to destination(S-D)are both considered.The closed-form expressions for the outage probability of the P-DF-CRN-NOMA are derived considering the three proposed forwarding cases.Qualitative numerical results corroborating our theoretical analysis,especially for the high signalto-noise ratio(SNR),show that the proposed P-DF-CRN-NOMA scheme significantly improves the outage probability performance in comparison to the conventional CRN-NOMA schemes.Furthermore,for an increased S-D link,the corresponding outage probability performance will be also better for all the cases.

Probabilistic Model Checking-Based Survivability Analysis in Vehicle-to-Vehicle Networks

Probabilistic model checking has been widely applied to quantitative analysis of stochastic systems, e.g., analyzing the performance, reliability and survivability of computer and communication systems. In this paper, we extend the application of probabilistic model checking to the vehicle to vehicle(V2V) networks. We first develop a continuous-time Markov chain(CTMC) model for the considered V2V network, after that, the PRISM language is adopted to describe the CTMC model, and continuous-time stochastic logic is used to describe the objective survivability properties. In the analysis, two typical failures are considered, namely the node failure and the link failure, respectively induced by external malicious attacks on a target V2V node, and interrupt in a communication link. Considering these failures, their impacts on the network survivability are demonstrated. It is shown that with increasing failure strength, the network survivability is reduced. On the other hand, the network survivability can be improved with increasing repair rate. The proposed probabilistic model checking-based approach can be effectively used in survivability analysis for the V2V networks, moreover, it is anticipated that the approach can be conveniently extended to other networks.

Gga3 gene-deleted C57BL/6J mice have elevated fasting blood glucose levels

Diabetes mellitus(DM)is one of the most common diseases in the elderly,and among DM patients,more than 90%have type 2 DM(T2DM).The etiology of T2DM is complex and associated with risk factors such as age,genetic disposition,and diet.The genetic factors underlying T2DM are currently the focus of intense research,and it has been established that the susceptibility genes associated with T2DM vary among different populations.A recent longitudinal exome-wide association study in the Japanese population has identified GGA3 as a susceptible locus for T2DM.1 GGA3 is one of the Golgi-localized-ear-containing ARF binding proteins(GGAs)that function widely in the transport of Golgi-derived vesicles and in endocytic trafficking pathways.However,although it is widely acknowledged that the control of glucose homeostasis via endocytosis and glucose metabolism plays a vital role in T2DM,the associations between intracellular trafficking and diabetes pathogenesis have not been sufficiently established.In this study,we used a Gga3 gene knockout mouse strain to investigate the potential involvement of GGA3 in controlling blood glucose.The study was approved by the ethics committee of Jining Medical University(No.2019-JS-005).Our results indicate that the GGA3 gene might play a protective role against diabetes.

Guidelines for burn rehabilitation in China

Quality of life and functional recovery after burn injury is the final goal of burn care,especially as most of burn patients survive the injury due to advanced medical science.However,dysfunction,disfigurement,contractures,psychological problems and other discomforts due to burns and the consequent scars are common,and physical therapy and occupational therapy provide alternative treatments for these problems of burn patients.This guideline,organized by the Chinese Burn Association and Chinese Association of Burn Surgeons aims to emphasize the importance of team work in burn care and provide a brief introduction of the outlines of physical and occupational therapies during burn treatment,which is suitable for the current medical circumstances of China.It can be used as the start of the tools for burn rehabilitation.

Guideline for diagnosis, prophylaxis and treatment of invasive fungal infection post burn injury in China 2013

Invasive fungal infection is one of the major complication of severe burns which can induce local or systemic inflammatory response and cause serious substantial damage to the patient. The incidence of fungal infection for burn victims is increasing dramatically during recent years. This guideline, organized by Chinese Society of Burn Surgeons, aims to standardize the diagnosis, prevention and treatment of burn invasive fungal infection. It can be used as one of the tools for treatment of major burn patients.