To solve the problems of the poor reduction performance of Filter Bank MultiCarrier (FBMC) signals' Peak-to-Average Power Ratio (PAPR) and the high Side Information Error Rate (SIER) of the existing Selected Mapping (SLM) method to reduce PAPR signals, an SLM method with embedded Side Information (SI) was presented to reduce PAPR. At the transmitter, a group of phase rotation vectors with embedded SI were designed, and the candidate data blocks were generated by multiplying the phase rotation vectors with the transmitting data blocks. By using the outputs of Inverse Discrete Fourier Transform (IDFT) of the real and imaginary components of the candidate data blocks, the candidate FBMC signals based on cyclic time shift were designed and the candidate signal with the lowest PAPR was selected and transmitted. At the receiver, by using the difference between the phase rotations of the SI subcarrier data, a low-complexity SI detector unrelated to modulation order of transmitted symbols was proposed. Simulation results show that the proposed method can effectively reduce the PAPR of FBMC signals at the transmitter and obtain good SI detection and Bit Error Rate (BER) performances at the receiver.

The advancement of network technologies such as bluetooth and WiFi has promoted the development of the Internet of Things(IoT). IoT facilitates people's lives, but there are also serious security issues in it. Without secure access control, illegal access of IoT may bring losses to users in many aspects. Traditional access control methods usually rely on a trusted central node, which is not suitable for an IoT environment with nodes distributed. The blockchain technology and smart contracts provide a more effective solution for access control in IoT applications. However, it is difficult to ensure the correctness of smart contracts used for access control in IoT applications by using general test methods. To solve this problem, a method was proposed to formally verify the correctness of smart contracts for access control by using model checking tool Verds. In the method, the state transition system was used to define the semantics of the Solidity smart contract, the Computation Tree Logic(CTL) formula was used to describe the properties to be verified, and the smart contract interaction and user behavior were modelled to form the input model of Verds and the properties to be verified. And then Verds was used to verify whether the properties to be verified are correct. The core of this method is the translation from a subset of Solidity to the input model of Verds. Experimental results on two smart contracts for access control of IoT source show that the proposed method can be used to verify some typical scenarios and expected properties of access control contracts, thereby improving the reliability of smart contracts.

To satisfy the requirement of real-time and rapid processing of Scale-Invariant Feature Transform(SIFT) algorithm for remote sensing images of large-scale Unmanned Aerial Vehicle (UAV) network on the scene, an implementation scheme of the algorithm by using the hardware multiplier of Digital Signal Processor(DSP)kernel was proposed to process the multiplication of single-precision floating-point pixel data. Firstly,according to the characteristics of data input and output of the hardware multiplier with DSP kernel,the image data structure and the image function of SIFT algorithm were reconstructed in order to make the hardware multiplier perform the multiplication calculation of single-precision floating-point pixel data of SIFT algorithm. Secondly,the software pipelining technology was adopted to rearrange the iterative computation,so as to enhance the parallel computing ability of the algorithm. Finally,the dynamic data produced in the algorithm calculation process were transferred to the Double Data Rate 3 synchronous dynamic random access memory(DDR3)to enlarge the storage space of the algorithm data. Experimental results show that the SIFT algorithm on DSP platform is able to achieve high-precision and fast processing for 1 000×750 remote sensing images of UAV,and the scheme satisfies the requirement of real-time and rapid processing of SIFT algorithm for remote sensing images of UAV network on the scene.

Aiming at the lack of security assessment in cloud environment, a cloud-based security modeling method was proposed, and a Security-Performance (S-P) association model in cloud environment was established. Firstly, a model was constructed for virtual machines, the most important component of the cloud system, to evaluate its security. The model fully reflected the impact of security mechanisms and malicious attacks on virtual machines. Secondly, based on the relationship between virtual machine and cloud system, an indicator was proposed for assessing the security of the cloud system. Thirdly, a hierarchical modeling method was proposed to establish an S-P association model. Queuing theory was used to model the performance of cloud computing systems, and the relationship between security and performance was established based on Bayesian theory and association analysis, and a new index for evaluating the association of complex S-P was proposed. Experimental results verify the correctness of the theoretical model and reveal the dynamic change rule of performance caused by safety factors.

Concerning the problems of heavy network traffic, which is caused by the excessive load of master node, bad expansibility and poor ability to handle node failure in existing monitoring system, a novel Cloud Monitoring System based on Bionic autonomic nervous system (B-CMS) was proposed. Firstly, B-CMS imported hierarchical storage and batch-wise report mechanism to upload the monitoring information, which can decrease the network traffic at any moment to ensure monitor system's stability. In addition, the use of similar Dynamic Host Configuration Protocol (DHCP) and polling-driven heartbeat checking mechanism enabled the monitor system to get the self-organizing and self-repairing ability which is similar to Bionic Autonomic Nervous System (BANS) when adding new node and handling node failure in autonomic way. The experimental results show that B-CMS achieves self-organizing and self-repairing, and effectively decreases network traffic. In some special moment, the network traffic is only one-third of the original system.

A satellite antenna characterized by wide-beam, wide-bandwidth and microwave right-hand-circular polarization was designed. First, the Dynamic Dominant Evolution Algorithm (DDEA) was used to search globally on a parallel computing platform. Then orthogonal design and HFSS software based on finite element method were used to search within local scope evenly and elaborately, so that the antenna gain was further improved. The improved antenna meets the requirements on beam and saves the feeding power of satellite.