This PDF file contains the front matter associated with SPIE Proceedings Volume 9902 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

DP-QDQ is a partial-response shaping modulation based on 16QAM, which has been proposed in our previous research paper. In this paper, the power spectral density (PSD) of the DP-QDQ signal is analyzed and compared with DP-16QAM, DP-64QAM, and DP-256QAM signals, and the simulation setup is presented. The analysis results show the DP-QDQ signal has high spectral efficiency. In addition, the optical coherent DP-QDQ system is discussed in compared with DP-16QAM, DP-64QAM, and DP-256QAM systems in terms of the tolerance to optical signal to noise ratio (OSNR), transmission distance at 100G/s by simulations. It is revealed that DP-QDQ not only achieves high spectral efficiency, but also obtains a good compromise of the performances on spectral efficiency, OSNR tolerance and transmission distance.

The performance of long-haul high speed coherent optical fiber communication systems is significantly degraded by the laser phase noise and the equalization enhanced phase noise (EEPN). In this paper, the analysis of the one-tap normalized least-mean-square (LMS) carrier phase recovery (CPR) is carried out and the close-form expression is investigated for quadrature phase shift keying (QPSK) coherent optical fiber communication systems, in compensating both laser phase noise and equalization enhanced phase noise. Numerical simulations have also been implemented to verify the theoretical analysis. It is found that the one-tap normalized least-mean-square algorithm gives the same analytical expression for predicting CPR bit-error-rate (BER) floors as the traditional differential carrier phase recovery, when both the laser phase noise and the equalization enhanced phase noise are taken into account.

Advanced modulation technology is one of the key technologies of High-speed optical communication network for the development of long distance and large capacity. With the increase of velocity, nonlinear effect and polarization dispersion which can be ignored in low-speed systems, became the main reason for the restriction of system performance. Advanced optical modulation formats can improve the ability to resist dispersion and nonlinearity, improve the transmission performance and spectrum efficiency of high-speed optical communication systems. In this paper, we researched and compared the nonlinear performance and receptivity of 33%RZ-DQPSK, 50%RZ-DPSK and CSRZDQPSK signals.

Visible light channel modeling is one of the key technologies in visible light communication researches. But traditional Modified Monte Carlo Algorithm and Photon Tracing Algorithm still exist the problem of nesting too many times for visible light channel modeling, which leads to large computational complexity, so the system will take up too much computing resources. To solve this problem, we present the visible light channel modeling based on matrix reconstruction, which can simulate multiple diffuse reflection channel response in the case of low complexity. The simulation results show that the matrix reconstruction method can significantly reduce computational complexity comparing with the traditional modeling methods when the number of diffuse reflection increases. Meanwhile, the high modeling accuracy is guaranteed when the simulation time is shortened.

In this paper, the direct current (DC)-biased optical orthogonal frequency division multiplexing (DCO-OFDM) visible light communication (VLC) system using modified μ-law companding is modeled and investigated. The simulation results reveal that the high peak to average power ratio (PAPR) induced by multi-carrier modulation (MCM) and DC bias, can aggravate signal distortion that is caused by the nonlinear characteristic of light emitting diode (LED). Thus, a pre-distortion method based on modification of μ-law companding is proposed for DCO-OFDM VLC system to resolve this problem. With the proposed method, the system can achieve a good performance of PAPR reduction and bit error rate (BER), compared to the original DCO-OFDM VLC system. It is demonstrated that the modified μ-law companding is appropriate to alleviate LED nonlinearity without degradation of the signal quality in DCO-OFDM VLC system.

An optical transmitting antenna for visible light communication(VLC) is designed in this work, in which the antenna is positioned before the light-emitting diodes (LED) source to change the lighting distribution, in order to achieve uniform received power effect. The method to design antenna is introduced into physical optical lens principle. According to the energy conservation law and Snell law, the antenna is designed via establishing energy mapping between the luminous flux emitted by a LED source with Lambertian distribution and the target plane. The coordinates of the antenna model are obtained under matrix laboratory (MATLAB). The antenna model entity is generated through three dimensional (3D) composition software AutoCAD with the coordinates of antenna. Ray-tracing software Tracepro is used to trace the ray which through antenna, and validate the irradiance maps. The uniformity of illumination and received power of the designed VLC is improved from approximately 35% to over 83%.

An adaptive priori likelihood ratio (LLR) estimation method is proposed over non-Gaussian channel in the intensity modulation/direct detection (IM/DD) optical communication systems. Using the nonparametric histogram and the weighted least square linear fitting in the tail regions, the LLR is estimated and used for the soft decision decoding of the low-density parity-check (LDPC) codes. This method can adapt well to the three main kinds of intensity modulation/direct detection (IM/DD) optical channel, i.e., the chi-square channel, the Webb-Gaussian channel and the additive white Gaussian noise (AWGN) channel. The performance penalty of channel estimation is neglected.

The source localization base on wireless sensor network has attracted considerable attention in recent years. However, most of the previous works focus on the accurate measurement or single source localization. The multiple-source localization has extensive application prospect in many fields. The quantized measurement is a low-cost and low energy consumption solution for wireless sensor network. In this paper, we present a novel multiple-source consecutive localization algorithm using the quantized measurement. We first introduce the multiple acoustic sources model and quantized measurement method. Then the maximum likelihood method is used to establish the localization function and the particle swarm optimization is employed to estimate the initial position of the source. Finally the Kalman filter is used to mitigate the random processing noise. Simulation results show that the proposed method owns high localization accuracy.

In-network processing is an efficient way to reduce the transmission cost in wireless sensor networks (WSNs). The in-network processing of many domain-specific computation tasks in WSNs usually requires to losslessly distribute the computation of the tasks into the sensor nodes, which is however usually not easy. In this paper we are concerned with such kind of tasks whose computation can only be partitioned into recursive computation mode. To distribute the recursive computations into WSNs, it is required to design an appropriate single in-network processing path, along which the intermediate data is forwarded and updated in the WSNs. We address the recursive computation with constant size of computation result, e.g., distributed least square estimation (D-LSE). Finding the optimal in-network processing path to minimize the total transmission cost in WSNs, is a new problem and seldom studied before. To solve it, we propose a novel routing algorithm called as S-TSP, and compare it with some other greedy algorithms. Extensive simulations are conducted, and the results show the good performance of the proposed S-TSP algorithm.

Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocrine system of the human body. Sensor nodes in our network are secreting different hormones according to certain rules. The hormone level enables the nodes to regulate an efficient sleep and wake up cycle of nodes to reduce the energy consumption. It is evident from the simulation results that the proposed ESAM in autonomous sensor network exhibits a stable performance without the need of commands from a central controller. Moreover, the proposed ESAM generates more efficient and persistent results as compared to other algorithms for tracking an invading object.

In order to ensure the safe and stable operation of the prefabricated substations, temperature sensing subsystem, temperature remote monitoring and management subsystem, forecast subsystem are designed in the paper. Wireless temperature sensing subsystem which consists of temperature sensor and MCU sends the electrical equipment temperature to the remote monitoring center by wireless sensor network. Remote monitoring center can realize the remote monitoring and prediction by monitoring and management subsystem and forecast subsystem. Real-time monitoring of power equipment temperature, history inquiry database, user management, password settings, etc., were achieved by monitoring and management subsystem. In temperature forecast subsystem, firstly, the chaos of the temperature data was verified and phase space is reconstructed. Then Support Vector Machine - Particle Swarm Optimization (SVM-PSO) was used to predict the temperature of the power equipment in prefabricated substations. The simulation results found that compared with the traditional methods SVM-PSO has higher prediction accuracy.

Content centric networking (CCN) is a novel and increasingly popular paradigm for data dissemination. In contrast to host centric IP networking, CCN is more suitable to Internet of things (IoT) scenario. Smart building is one of the special scenarios of IoT and many CCN architectures have been proposed in literature to exploit CCN’s data dissemination capability. However, it is less studied to use CCN in supporting clients to control sensor devices and to continually send interest packets get sensors’ reading. This paper describes a general service centric smart building architecture using a Context Driven Content Centric Network (CD-CCN) scheme, which can handle the diversity of devices, services, applications and context. Especially, this paper focuses on building an overall smart building network topology, routing and naming structures, to fit CD-CCN into a building network. The simulation results show that CD-CCN outperforms the conventional TCP/IP structure in terms of round-trip delay, due to CCN’s storage and broadcast characteristic, especially in scenarios such as message delivering and content sharing

Wireless devices can be identified by the fingerprint extracted from the signal transmitted, which is useful in wireless communication security and other fields. This paper presents a method that extracts fingerprint based on phase noise of signal and multiple level wavelet decomposition. The phase of signal will be extracted first and then decomposed by multiple level wavelet decomposition. The statistic value of each wavelet coefficient vector is utilized for constructing fingerprint. Besides, the relationship between wavelet decomposition level and recognition accuracy is simulated. And advertised decomposition level is revealed as well. Compared with previous methods, our method is simpler and the accuracy of recognition remains high when Signal Noise Ratio (SNR) is low.

During the last several years, the amount of wireless network traffic data increased fast and relative technologies evolved rapidly. In order to improve the performance and Quality of Experience (QoE) of wireless network services, the analysis of field network data and existing delivery mechanisms comes to be a promising research topic. In order to achieve this goal, a smartphone based platform named Monitor and Diagnosis of Mobile Applications (MDMA) was developed to collect field data. Based on this tool, the web browsing service of High Speed Downlink Packet Access (HSDPA) network was tested. The top 200 popular websites in China were selected and loaded on smartphone for thousands times automatically. Communication packets between the smartphone and the cell station were captured for various scenarios (e.g. residential area, urban roads, bus station etc.) in the selected city. A cross-layer database was constructed to support the off-line analysis. Based on the results of client-side experiments and analysis, the usability of proposed portable tool was verified. The preliminary findings and results for existing web browsing service were also presented.

Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 ~ 11 dB advantage.

To enable simultaneous multicast downlink transmit and receive operations on the same frequency band, also known as full-duplex links between an access point and mobile users. The problem of minimizing the total power of multicast transmit beamforming is considered from the viewpoint of ensuring the suppression amount of near-field line-of-sight self-interference and guaranteeing prescribed minimum signal-to-interference-plus-noise-ratio (SINR) at each receiver of the multicast groups. Based on earlier results for multicast groups beamforming, the joint problem is easily shown to be NP-hard. A semidefinite relaxation (SDR) technique with linear program power adjust method is proposed to solve the NP-hard problem. Simulation shows that the proposed method is feasible even when the local receive antenna in nearfield and the mobile user in far-filed are in the same direction.

A transmission experiment has been performed over an optical path of 1.53 km at a rural test site in Meppen, Northwest Germany. Direct transmission measurements were made by a 7-wavelength transmissometer. Transmission was further estimated from the average voltage received by a BLS2000 scintillometer, and evaluated with Mie theory from in-situ aerosol measurements near the optical path. Furthermore, the transmission was modeled with MODTRAN, driven with local meteorology, visibility and the rural aerosol model. For a central wavelength of 0.88 μm, the transmissometer, the BLS200 and MODTRAN agree well. Remaining differences may be due to water transmission and continuum around 0.95 μm that is picked up by the transmissometer and not by the narrow-banded BLS2000 and MODTRAN calculations. When MODTRAN is run without an aerosol model, or when this model is driven by a “default” visibility, the overlap with the measurements is extremely poor.

To guarantee the quality of service of licensed users, the unlicensed users must vacate the occupied channel by spectrum handoff if licensed users appear in the licensed spectrum. However, spectrum sensing with false alarm and missed detection may lead to more inaccuracy problems when unlicensed users perform spectrum handoff. To improve the problems mentioned before, we utilize PRP M/G/1 queuing network model to propose a spectrum handoff algorithm with error data retransmission mechanism and analyze its performance by transmission delay and extended data delivery time. In addition, we discuss the relationship between false alarm probability, extended data delivery time and user traffic load and verify the effectiveness of the proposed algorithm.

At present, the research on computer-aided diagnosis includes the sample image segmentation, extracting visual features, generating the classification model by learning, and according to the model generated to classify and judge the inspected images. However, this method has a large scale of calculation and speed is slow. And because medical images are usually low contrast, when the traditional image segmentation method is applied to the medical image, there is a complete failure. As soon as possible to find the region of interest, improve detection speed, this topic attempts to introduce the current popular visual attention model into small lesions detection. However, Itti model is mainly for natural images. But the effect is not ideal when it is used to medical images which usually are gray images. Especially in the early stages of some cancers, the focus of a disease in the whole image is not the most significant region and sometimes is very difficult to be found. But these lesions are prominent in the local areas. This paper proposes a visual attention mechanism based on sliding window, and use sliding window to calculate the significance of a local area. Combined with the characteristics of the lesion, select the features of gray, entropy, corner and edge to generate a saliency map. Then the significant region is segmented and distinguished. This method reduces the difficulty of image segmentation, and improves the detection accuracy of small lesions, and it has great significance to early discovery, early diagnosis and treatment of cancers.

As for shortcomings of the comprehensive evaluation system on traditional TV programs such as single data source, ignorance of new media as well as the high time cost and difficulty of making surveys, a new evaluation of TV series is proposed in this paper, which has a perspective in cross-platform multidimensional evaluation after broadcasting. This scheme considers the data directly collected from cable television and the Internet as research objects. It’s based on TOPSIS principle, after preprocessing and calculation of the data, they become primary indicators that reflect different profiles of the viewing of TV series. Then after the process of reasonable empowerment and summation by the six methods(PCA, AHP, etc.), the primary indicators form the composite indices on different channels or websites. The scheme avoids the inefficiency and difficulty of survey and marking; At the same time, it not only reflects different dimensions of viewing, but also combines TV media and new media, completing the multidimensional comprehensive evaluation of TV series on cross-platform.

A very compact UWB antenna with four notched bands is proposed. The antenna consists of a rectangular radiating patch with a half circle at bottom, a tapered microstrip feed-line, and a semielliptical ground plane. With a pair of Lshaped slots, complementary co-directional SRR on the patch and a pair of L-shaped slots on the ground plane, four notched bands are created to prevent interference from WiMAX /WLAN/X-band. Experimental results show that the designed antenna, with compact size 20×30mm2, has an operating band(VSWR<2) from 2.7 to 20GHz,except four stop bands of 3.1~3.7GHz, 5.13~5.48GHz, 5.74~6.04GHz, 7.3~7.96GHz. And good radiation patterns within the operating band have been observed.

Fractional Fourier OFDM or simply chirped OFDM performs better in time-frequency selective channel than its convectional OFDM. Although chirped OFDM outperforms OFDM it still inherits Peak to Average Power Ratio (PAPR) drawback as a convectional OFDM. To eliminate PAPR drawback Constant Envelope OFDM was developed and for better performance in time frequency selective channel Constant Envelope Fractional Fourier OFDM (CE-COFDM) is used. Its BER performance is analyzed and compared to chirped OFDM and OFDM in AWGN and Rayleigh channel. The simulations show the BER performance of CE-COFDM is the same as chirped OFDM and OFDM. The power efficiency of CE-COFDM is also studied and different simulations performed shows CE-COFDM is more power efficient than chirped OFDM and convectional OFDM for class A and class B Linear Power Amplifier (LPA).

In this paper, we propose a low-complexity differential transmission scheme for a two-way relay network (TWRN) with two sources and one relay node, where each source is equipped with a single antenna, while the relay node is equipped with a large number of antennas. In the proposed scheme, no channel state information (CSI) is required at each source node for signal detection. It is shown that as the number of relay antennas becomes large, the received signal at each source node includes the desired signal only. Numerical results are presented to demonstrate the bit-to-error rate (BER) performance of the proposed scheme.

Correlation filter based trackers have proved to be very efficient and robust in object tracking with a notable performance competitive with state-of-art trackers. In this paper, we propose a novel object tracking method named Adaptive Kernelized Correlation Filter (AKCF) via incorporating Kernelized Correlation Filter (KCF) with Structured Output Support Vector Machines (SOSVM) learning method in a collaborative and adaptive way, which can effectively handle severe object appearance changes with low computational cost. AKCF works by dynamically adjusting the learning rate of KCF and reversely verifies the intermediate tracking result by adopting online SOSVM classifier. Meanwhile, we bring Color Names in this formulation to effectively boost the performance owing to its rich feature information encoded. Experimental results on several challenging benchmark datasets reveal that our approach outperforms numerous state-of-art trackers.

This paper investigates the spectral and energy efficiencies of a multi-pair two-way amplify-and-forward (AF) relay system over Ricean fading channels, where multiple user-pairs exchange information within pair through a relay with very large number of antennas, while each user equipped with a single antenna. Firstly, beamforming matrixe of zero-forcing reception/zero-forcing transmission (ZFR/ZFT) with imperfect channel state information (CSI) at the relay is given. Then, the unified asymptotic signal-to-interference-plus-noise ratio (SINR) expressions with imperfect CSI are obtained analytically. Finally, two power scaling schemes are proposed and the asymptotic spectral and energy efficiencies based on the proposed power scaling schemes are derived and verified by the Monte-Carlo simulations. Theoretical analyses and simulation results show that with imperfect CSI, if the number of relay antennas grows asymptotically large, we need cut down the transmit power of each user and relay to different proportion when the Ricean K-factor is non-zero and zero (Rayleigh fading) in order to maintain a desirable rate.

Sphere-decoding (SD) algorithm is one of important detection scheme for the data detection of multiple-input multiple-output (MIMO) communication systems based on layered space–time structure, but it has a higher complexity in its pre-processing than the Maximum likelihood (ML) algorithm. For good performance and low complexity, an improved sphere-decoding algorithm for MIMO system is proposed by choosing effective search radius. It can reduce the complexity while having grid points in the sphere. The simulation results show that the proposed data detection algorithm for MIMO system has a very close to the traditional Sphere-decoding algorithm in Bit Error Rate (BER) performance, but it has lower complexity than traditional Sphere-decoding algorithm.

With the explosive growth of harmful Internet information such as pornography, violence, and hate messages, network monitoring is essential. Traditional network monitors is based mainly on bypass monitoring. However, we can’t filter network traffic using bypass monitoring. Meanwhile, only few studies focus on the network monitoring for HTTPS protocol. That is because HTTPS data is in the encrypted traffic, which makes it difficult to monitor. This paper proposes a network monitor for HTTPS protocol based on proxy. We adopt OpenSSL to establish TLS secure tunes between clients and servers. Epoll is used to handle a large number of concurrent client connections. We also adopt Knuth- Morris-Pratt string searching algorithm (or KMP algorithm) to speed up the search process. Besides, we modify request packets to reduce the risk of errors and modify response packets to improve security. Experiments show that our proxy can monitor the content of all tested HTTPS websites efficiently with little loss of network performance.

Because of go-stop mode not applying to FMCW CSAR (frequency modulated continuous wave circular synthetic aperture radar), received signal include Doppler shifting result from the radar fly in one period, which have a bad effect on the quality of imaging in wide-field FMCW CSAR. However the compensation functions of liner SAR are not suitable for CSAR. To solve the problem, the paper rebuild a received mode and elicit the Doppler shifting. At the same time, based on the model, the paper analysis the layover phenomenon while obtaining two-dimensional (2D) representations of 3D large scenes due to the wide-field FMCW CSAR and simulate the phenomenon. By the simulation, the effect of the layover can be expressed clearly.

In this paper, we consider channel estimation for Massive MIMO systems operating in frequency division duplexing mode. By exploiting the sparsity of propagation paths in Massive MIMO channel, we develop a compressed sensing(CS) based channel estimator which can reduce the pilot overhead. As compared with the conventional least squares (LS) and linear minimum mean square error(LMMSE) estimation, the proposed algorithm is based on the quantized multipath matching pursuit （MMP）reduced the pilot overhead and performs better than other CS algorithms. The simulation results demonstrate the advantage of the proposed algorithm over various existing methods including the LS, LMMSE, CoSaMP and conventional MMP estimators.

Conditional pulse nulling (CPN) receiver is proposed by Dolinar to discriminate pulse position modulation (PPM) signals. The receiver, which uses a beam splitter and an on-off photon detector can outperform the standard quantum limit (SQL) for PPM signals. In this paper, this receiver is applied to multi-pulse PPM (MPPM) and binary quantum coding signals, and a dynamic programming algorithm is proposed to optimize the control strategy. The MPPM signals are used to improve the band-utilization efficiency, and the binary quantum coding enables the communication system to correct the error. Numerical simulation results show that the CPN receiver with optimized strategy outperform SQL for both MPPM and binary quantum coding signals.

Time-frequency distribution (TFD) is two-dimensional function that indicates the time-varying frequency content of one-dimensional signals. And The Wigner-Ville distribution (WVD) is an important and effective time-frequency analysis method. The WVD can efficiently show the characteristic of a mono-component signal. However, a major drawback is the extra cross-terms when multi-component signals are analyzed by WVD. In order to eliminating the cross-terms, we decompose signals into single frequency components – Intrinsic Mode Function (IMF) – by using the Empirical Mode decomposition (EMD) first, then use WVD to analyze each single IMF. In this paper, we define this new time-frequency distribution as EMD-WVD. And the experiment results show that the proposed time-frequency method can solve the cross-terms problem effectively and improve the accuracy of WVD time-frequency analysis.

In this paper, assuming each node has delayed channel state information at the transmitter (CSIT), we investigate the achievable degrees of freedom (DOF) of MIMO two-way relay interference channel in frequency division duplex (FDD) systems, where there are K user pairs (i.e., 2K users) and each user in a user pair exchanges messages with the other user in the same user pair simultaneously via an intermediate relay. We propose a two-stage transmission scheme and derive the closed-form expressions for its achievable DOF.

A novel method based on fuzzy reasoning for radar clutter suppression is presented. In the method, the features of the returns from the target and clutter are analyzed. Then the fuzzy rules are extracted in order to establish the rule base and model for fuzzy Reasoning. In fuzzy reasoning process, the weight of each input element is updated through adaptive correction mechanism. So as to the output of Fuzzy reasoning converge to the ideal value. Targets and clutter are separated by making good use of the output. And the method achieves the aim of clutter suppression. The experimental results illustrate that the presented method has an ideal effect of suppressing clutter.

Virtual router enables the coexistence of different networks on the same physical facility and has lately attracted a great deal of attention from researchers. As the number of IPv6 addresses is rapidly increasing in virtual routers, designing an efficient IPv6 routing lookup algorithm is of great importance. In this paper, we present an IPv6 lookup algorithm called weight-balanced tree (WBT). WBT merges Forwarding Information Bases (FIBs) of virtual routers into one spanning tree, and compresses the space cost. WBT’s average time complexity and the worst case time complexity of lookup and update process are both O(logN) and space complexity is O(cN) where N is the size of routing table and c is a constant. Experiments show that WBT helps reduce more than 80% Static Random Access Memory (SRAM) cost in comparison to those separation schemes. WBT also achieves the least average search depth comparing with other homogeneous algorithms.

Automatic monitoring system gains significant interest in poultry industry due to the need of consistent environment condition. Appropriate environment increase the feed conversion ratio as well as birds productivity. This will increase the competitiveness of the poultry industry. In this research, a temperature and humidity monitoring system is proposed to observer the temperature and relative humidity of a poultry house. The system is intended to be applied in the poultry industry with partnership schema. The proposed system is equipped with CCTV for visual monitoring. The measured temperature and humidity implement wireless sensor network technology. The experiment results reveals that proposed system have the potential to increase the effectiveness of monitoring of poultry house in poultry industry with partnership schema.

The main disadvantage of Orthogonal Frequency Division Multiplexing (OFDM) signal is the high peak-to-average power ratio (PAPR) which influences the system power efficiency and system performance in the presence of nonlinearities within the high power amplifier (HPA). The error vector magnitude (EVM) is one of the performance metrics by communications standards in OFDM system. In this paper, a novel PAPR reduction method from geometric angle analysis is proposed which keeps the EVM and bit-error-rate (BER) performance. In our method, a threshold vector circle is designed in frequency domain in order to adjust the amplitude and phase of the OFDM signal constellation points to near the ideal points. Simulation results show that PAPR of a QPSK modulated OFDM signal is reduced from 10.98dB to 7.502dB with an EVM reduction of 2.57%. This technique should vastly improve the performance of OFDM signal in communication system.

Frame synchronization play a very important role in coding of AIS. There are much arithmetic like maximum-likelihood, correlation and so on. But most of those cannot achieve good performance with large frequency offset. As satellite-based AIS system exist larger time delay and Doppler frequency offset, this paper propose arithmetic of frame synchronization. It is based on folding auto-correlation, where the top half and second half of training sequence have largest correlation after it is modulated by GMSK. Simulation experiments indicate that this arithmetic has good anti-frequency-offset performance.