On the background of low-altitude radar seeker detecting the sea surface targets, this paper analyzes the effect of the multipath scattering and sea clutter on the detection performance of radar seeker. On the basis of modeling the target echo, specular reflection, diffuse reflection and the sea clutter, it gives the specular reflection signal, diffuse reflection signal and sea clutter radar seeker received under concrete circumstances by simulation. Then it analyzes the effect of the multipath scattering and sea clutter on the detection performance of radar seeker when detecting different size targets. Simulation results shows that sea clutter is the key factor affecting the detection performance of radar seeker when radar seeker detects the small target whose RCS is lower than 1 m². While multipath effect is the key factor affecting the detection performance of radar seeker when radar seeker detects the target whose RCS is bigger than 10 m². The detection performance of radar seeker is not affected when the radar seeker detects the target whose RCS is bigger than 10⁴  m².

Compared with the single mode radar, because the transmitter and the receiver are separate, the first- order sea clutter of HF over the horizon hybrid mode radar based on sky wave transmitting and surface wave receiving presents different characteristic. This paper introduces simply elementary composing and operating principle of this hybrid mode radar system, considering the particular geometrical configuration of this system, derives its localization principle, combining electromagnetic wave propagating path and bistatic working mode of this hybrid mode radar, derives the theoretical calculation formula of the Doppler frequency of the first-order sea clutter, analyzes the phenomenon that the first-order sea clutter changes with different orientation, as well as verifies the theoretically analyzed result with practical metrical data.

High-precision height acquisition needs to correct the interferometric parameters errors by interferometric calibration for Interferometric SAR (InSAR) system. The traditional interferometric calibration method needs more Ground Control Points (GCPs) to reduce the influence of systematic random errors to the calibration precision, but it is very difficult to dispose GCPs in the field with complicated terrains, some areas probably only have little GCPs or even no GCPs and the traditional interferometric calibration method is inapplicable to this situation. A new calibration method is proposed for airborne InSAR based on block adjustment, which introduces the block adjustment theory in Photogrammetry to the processing of InSAR system calibration, through the joint multi-strip processing the method can be used to calibrate the interferometric parameters for airborne InSAR applied to large areas with sparse GCPs. Moreover, the problem of inconsistent height in the overlapping areas caused by the traditional calibration method is also solved. Finally, a joint calibration is adapted to the simulative data of three strips from the highland and the results confirm the validity and rationality of the proposed method.

In order to solve the land-mine classification problem on a Forward-Looking Ground Penetrating Virtual Aperture Radar (FLGPVAR), a new classification algorithm composed of weak classification iteration and adaptive feature selection is proposed. It is based on traditional AdaBoost algorithm, the feature selection is part of weak classification iterations, and the false alarm is treated as the cost function under constant detection rate. It is proved by real data that the method is applicable to the classification of land-mine and clutter on forward-looking ground penetrating virtual aperture Radar and the performance is better than traditional AdaBoost algorithm.

The moving speed can cause the target image to disperse in the vehicle-mounted forward-looking virtual aperture radar using stepped frequency and it could heavily infect image feature extraction of target. In this paper, the influence on imaging introduced by vehicle moving is analyzed basing on an ideal point model, and then the equivalent principle of speed compensating is brought forward. Basing on the analyses discussed upon, a new method of speed compensation, which will make the compactness of the Range Of Interest (ROI) image optimal, is introduced. This method can not only enhance the speed compensation efficiency, but also improve the stability of the feature extraction. Both the simulation data and the practical data prove the effectiveness of the method mentioned above.

A novel method of Weighted Minimum Entropy Autofocus (WMEA) algorithm for ISAR imaging is proposed where the objective function of weighed entropy is constructed and then solved with iterative technique to seek for phase errors. Based on Weighted Least-Squares (WLS) principle, the algorithm proposed is very robust by exploting the difference of phase error variations in range cells. Contrary to traditional Minimum Entropy Autofocus (MEA) algorithm, the convergence rate could be greatly promoted by weighted minimum entropy autofocus algorithm. Besides, with this method clutter and noise could be suppressed efficiently to achieve better performance. The experimental results using both simulated data and measured data confirm the validation of the proposed algorithm.

This paper presents a new method to jointly estimate the Direction Of Arrival-Direction Of Departure (DOA-DOD) and Doppler frequency of bistatic MIMO radar. Utilizing the characteristics of the signal received, the Doppler frequency vector, DOA vector and DOD vector are obtained by using least square algorithm. Because these three vectors are interdependent, the iterative algorithm is then proposed to update them and to get finally the DOA-DOD and Doppler frequency estimations. The estimated parameters are automatically paired without the additional pairing method. The algorithm has low complexity and fast operation speed. Simulation results demonstrate that compared with the PARAFAC based method, this new method can get precise DOA-DOD and Doppler frequency estimations with higher probability.

In this paper, Inverse Synthesis Aperture Radar (ISAR) turntable imaging of near field rotating target with large angle is implemented using UWB (Ultra Wide Band) system. With large and discrete rotation angle, and noise pollution considered, the robust Windowing Filtered Spherical Back Projection (WFSBP) algorithm is presented. The compensation of filtering for error resulted from discrete rotation angle is explained geometrically. The Point Spread Function (PSF) is analyzed, which also proves high resolution image can be obtained even transmitting monochromatic signal. Simulation and experiment are conducted, showing the better performance of WFSBP than traditional algorithm. High quality and high resolution image is obtained for the large rotation angle target.

By using multiple-receive apertures in azimuth, Synthetic Aperture Radar (SAR) systems are enabled with high-resolution and wide-swath imaging ability. In this paper, influence of channel imbalances on SAR systems with multiple-receive apertures in azimuth is derived theoretically. Azimuth multi-channel sequence is related with the single-channel sequence by use of zero padding. The result of the compression on mismatched multi-channel sequence shows that several ghosting peaks are presented around the main peak. Analytical formulas to calculate the Peek-to-Ghost-Ratio (PGR) and ghost locations are given, which show that the PGR is determined by the magnitude of channel mismatch, the number of the channels, the Doppler bandwidth and the azimuth oversampling ratio. The correctness of these formulas is validated further by simulation experiments.

To overcome the multipath effect, a fast algorithm for low elevation estimation for MIMO radar via matrix pencil is proposed. The signals both in transmit multipath and receive multipath are considered. Firstly, a forward-backward matrix pencil is formed based on the single-sampled vector. Secondly, the reduced-dimensional processing is applied to the matrix pencil via two unitary matrices. Finally, the generalized eigen-decomposition is employed to estimate the low elevation in multipath environments directly. Without the covariance matrix estimation, the proposed method can overcome multipath effect effectively in case of low SNR and estimate multi-target simultaneously. Compared with Maximum Likelihood (ML) method, it avoids spectrum peak searching and reduces the computational burden. Numerical results verify the effectiveness of this method.

As the HF (High-Frequency) ground wave radar requires high duty-cycle, echo-eclipse becomes a serious problem for short-range target. Complementary signals with double-pulse has zeros sidelobes, but in the case of echo-eclipse, which has very high sidelobes for the reason of complementary feature is destructed. To solve this problem, this paper proposes a ‘sub-complementary’ signal, and by using modified Golay algorithm a novel complementary signal is got whose incomplete codes also has perfect pulse-compressed characteristic. Computer simulation and test show that this coding method has very low sidelobes in case of echo-eclipse, whose signal resolution is much higher than other codes.

Target radiometric error deteriorates SAR image quality. A method is proposed in this paper to analyze theoretically target radiometric error resulting from SAR Block Adaptive Quantization (BAQ). Meanwhile, thermal noise is taken into consideration. During the analysis, first, the process of BAQ is described by sign function. Second, the output signal from BAQ is expanded into harmonics by Bessel function of first kind. Third, the harmonics are processed by matched filter in frequency domain, and finally the analytical expression of target radiometric error is obtained as expected. Numerical experiments of single point target and multi-point targets with thermal noise are implemented to verify this method, and BAQ compression ratios in the experiments are 8:1, 8:2, 8:3 and 8:4. Analytical results derived in this paper could be quite useful for the decision of BAQ compression ratio and the process of target radiometric correction.

A new range-Doppler imaging algorithm is presented for processing bistatic Synthetic Aperture Radar (SAR) data acquired in the hybrid spaceborne/airborne sliding spotlight SAR configuration. This paper firstly presents the 2-D point target spectrum by using the series reversion, and then analyses the spectrum with the space-variant in range. Based on the previous discussions, the algorithm overcomes the spectrum folding of the azimuth raw signal with a SPECtral ANalysis (SPECAN) process, and focuses the full image in the Doppler domain. Without sub-aperture and interpolation, this algorithm is great in computational efficiency. Simulation results confirm the validity of the imaging algorithm.

A novel method is developed to calibrate the non-ideal transfer function and I/Q imbalances in quadrature modulate/demodulate systems which occur frequently in wideband radar systems, without changing the hardware of the radar calibration system. Based on analyzing channel errors in radar systems and taking account of time-frequency relationship of chirp signal, split-pulse method called is adopted to separate image frequency component due to I/Q channel error. Then, the complete description of channel error is got and the calibration function is constructed which is used to correct the raw radar echo in frequency domain. The effectiveness of this method is verified by the experiment of channel error correction in wideband radar system with 500 MHz effective band width. Results show that the method proposed is characterized by high feasibility and performance.

The Symmetrical Triangular Linear Frequency Modulated Continuous Wave (STLFMCW) signal is a sort of typical Low Probability of Intercept (LPI) radar signal. The spectrum distribution characteristics of the STLFMCW signal is analyzed in the FRactional Fourier Transform (FRFT) domain. It is discovered that the each segment of Linear Frequency Modulated (LFM) signal contained by the STLFMCW signal has an energy peak in its “optimal” fractional Fourier transform, and the spectrum of all the LFM signal segments contained by the STLFMCW signal folds together completely in the Fourier domain, so the amplitude of the spectrum is very high. It badly influences the detection and parameter estimation of the STLFMCW signal on the low SNR condition. Therefore, this problem must be solved when FRFT is used to detect the STLFMCW signal. A novel method is presented to detect STLFMCW signal and estimate its parameters based on the FRFT and clustering analysis. The method solves the problem brought by the spectrum folding of the STLFMCW signal, and this method overcomes the limit that the peaks of the STLFMCW signal must be higher than the amplitude of the noise. On the low SNR condition, this method still has better effect to detect STLFMCW signal. Finally, simulations verify the effectiveness of the method.

In the progress of 3-Dimensional (3D) reconstruction from 2-Dimensional (2D) rock slice images, it is difficult to determine the auto-correlation function of the 3D microstructure. The reconstruction method based on the fast Fourier transforms uses empirical formula to predict the auto-correlation function of the 3D microstructure, but the reconstruction result has relative large error. Another reconstruction method based on Particle Swarm Optimization (PSO) to optimize the reconstruction progress is proposed in this paper. This method sets autocorrelation function of 3D microstructure as the position of particles, calculates fitness value as the error between 3D microstructure and 2D image. Compared with FFT reconstruction method, the similarity between reconstruction results and 2D image is greatly improved. Compared with simulated annealing method, the proposed method reaches similar reconstruction result. The reconstruction method based on PSO is more efficient and can be well applied to the image reconstruction.

In order to recognize one’s identity accurately, a dorsal hand vein recognition algorithm based on establishing and fusing multi Hidden Markov Models (HMMs) is proposed in the paper, where multi-scale subband energies are used as the features of HMMs after the vein images are processed by Contourlet transform. In the proposed algorithm near infrared light source array whose light intensity can be adjustable is applied, and the dorsal hand vein image sequence is acquired through increasing the light intensity gradually. Then every vein image is processed by Contourlet transform, subband energies under three scales are computed and used as the features of three HMMs. Finally, the probabilities of three HMMs generating observable symbol sequences are calculated and fused, and the result of fusion is compared to threshold, then the vein recognition process is completed. Experiments show that the proposed algorithm can make the discrimination between true and false matching maximum, and comparing with the recognition algorithms based on feature points or vein information fusion, the correct recognition rate is improved.

Graph based transductive classifiers are dependent on graph structure. Because of redundant and noisy features in high dimensional data, a graph, constructed from these data, can not reflect their distribution information faithfully. Consequently, the performance of a transductive classifier is downgraded. To address this problem, a multiple graphs construction scheme is introduced and applied into transductive classification. The scheme generates firstly several random subspaces and applies semi-supervised discriminative analysis in each subspace. Next, it trains a transductive classifier in each discriminative subspace. And finally, by voting rule, it fuses these classifiers as an ensemble classifier. Empirical results show that, in comparison with other transductive classifiers, the proposed ensemble classifier is more precise and robust to parameters selection.

A novel blind joint 2D-angle and frequency estimation method is presented. At first the double parallel linear array is given. The output signal of the array antennas is analyzed and it has quadrilinear model characteristics. The frequency and 2D-angle can be estimated from the matrices via low-rank decomposition which utilizing the uniqueness of parallel factor decomposition. The method does not require searching spectral peak or pairing parameters. In comparison with the conventional methods, the algorithm has high precision estimation of parameters and works well under small sizes. The simulation results verify its effectiveness.

Considering the strict preprocessing requirement of modulation recognition algorithm in fading channels, an algorithm of modulation classification based on cyclostationary test is proposed to promote the classification performance under blind reception conditions. Combing cyclostationary test, the signal cyclic frequency features of cyclic cumulants are used to discriminate common digital modulation signals, such as OFDM, PSK, FSK, etc.. The method obviates the need for preprocessing tasks, such as estimation of parameters and synchronization. The theoretical derivations and simulations simultaneously confirm the effectiveness of discriminating signals in the fading channel with low SNR. Furthermore, this method can be used to promote the signal blind classification performance in fading channels under the non-cooperative reception conditions.

A new impulsive hybrid observer is firstly designed for nonlinear impulsive hybrid systems based on a Finite State Machine (FSM). Then, a class of impulsive output feedback controller based on the hybrid observer is designed for above systems by applying FSM theory and backstepping method, and a multi-Lyapunov function is constructed. The sufficient condition for asymptotic stability of the whole closed-loop systems is given by applying asymptotic stability theory of hybrid system and multi-Lyapunov function method. Finally, a simulation example is given to illustrate the effectiveness of the controller proposed in the paper.

In this paper, five constructions of binary sequences with almost optimal autocorrelation magnitude are proposed. The first construction is to use an arbitrary ideal 2-level autocorrelation sequence. The other four constructions are based on some sequences and their modified versions. 2N×2 interleaved sequences are used to get the sequences whose values of the autocorrelations are optimal except one points. And the distributions of the periodic autocorrelation functions of the resultant sequences are given. The results provide more choices for CDMA system and other applications.

Most traditional probabilistic key management schemes of wireless sensor networks have disadvantages of low connectivity, poor resiliency against node capture, and high energy-consumption. A key sharing model is proposed based on (q,l )-threshold secret sharing. In this model, a key is divided into shadows to be shared by “virtual cluster heads” and re-constructed by the “physical cluster head”. For tiny cluster member nodes, this model is optimized in improving their resilience against node capture attacks and saving the energy consumption. At the same time, the cluster head nodes’ properties of security, tolerance and efficiency can be adjusted by controlling the parameters of q and l . Both theoretic analysis and the experimental results prove that, this model improves effectively the resilience against nodes capture attack and the network connectivity, and decreases the nodes’ overheads.

Source detection of Wireless Sensor Network (WSN) would encounter problems of lacks of processing power and energy. To overcome these problems, an adaptive compressive sensing algorithm based on energy balance is proposed. Unlike the traditional adaptive compressive sensing algorithms, the proposed algorithm not only takes into account the reconstruction performance, but also considers the energy balance of the nodes when chooses the measurement vector. It prevents some nodes from the excessive consumption of energy and leading to the destruction of the whole network structure. At the same time in order to meet the needs of different application scenarios, the adaptive compressive sensing algorithm is combined with the energy balance based compressive sensing algorithm, and flexible configuration purpose is achieved by choosing the threshold. The simulations show that the proposed algorithm can extend the survival time of the network and consider both the energy consumption and convergence.

Most present lossy link identification algorithms do not achieve both high stability and low computation complexity. A novel Reference Path based lossy link Identification algorithm (RPI) is proposed to address this problem. RPI first selects reference paths from the paths passing through a link according to the measured performance differences, and then employs a heuristic method to infer the state of the link based on the correlation of its reference paths. Compared with other algorithms, RPI has high stability because of using the information of measurement data sufficiently. It also achieves low computation complexity due to the heuristic link state inference method. Simulation results show that RPI can identify lossy links more accurately than other algorithms.

In current evidential trust models, there exist some deficiencies such as local trust degree is sensitive to the threshold and the exact meaning of recommendation trust degree for trust target provided by recommender are obscure to the trust source, so an evidential trust model is proposed with fuzzy adjustment method to solve these problems. On the one hand, the trust ratings are adjusted through applying fuzzy sets, which makes local trust degree changes with the change parameter gradual and can avoid the occurrence of the mutation effectively. On the other hand, the exact meaning of recommendation trust degree can be comprehended through constructing a adjust method for the recommendation trust degree, which improve the accuracy of the trust metric calculated from the recommendation trust values. The simulation results show that compared with existing evidential trust models, the trust model in this paper has a strong ability in anti-disturbance and anti-attack, which is applied to a variety of dynamic environments, and has more remarkable enhancements in the accuracy of trust measurement.

There are some instinctive characteristics in unstructured P2P network, such as frequent reappearance of keywords and uneven resource sharing. To enhance performance of resource searching, a Response Tracing based Resource Searching Mechanism (RTRSM) is proposed, which traces the content and the latest source of responses to construct an informed search. RTRSM adaptively forwards the query to the suitable neighbor, according to the related degree of the storing information and the query itself. By constructing an informed search, RTRSM hopes to maintain high success rate, decrease searching cost and promote searching efficiency. Simulation results show that RTRSM is scalable. It can be extended to large scale unstructured P2P network with a low cost. Simulation results also show that RTRSM achieves good searching efficiency. RTRSM decreases 54.2% of average message counts and 56.4% of average hops by contrast to flooding, and decreases 28.9% of average message counts and 6.4% of average hops by contrast to SQR (Scalable Query Routing), while the success rate keeps up to 90%.

Packet-level multi-path transfers can cause packets reordering at the destination, this profoundly affects TCP performance. Addressing with this problem, reordering performance under multi-path transfers with Round-Robin packet assignment is analyzed in the view of queuing theory. The influence of path difference and path numbers on reordering performance under multi-path transfers is discussed with respect to three criterions: disorder rate, resequencing time and end-to-end total time. Results demonstrate that it is preferable to make paths with closer transmission rate for two paths transfers, and the paths number dose not exceed four to significantly improve the reorder performance if the paths have the same transmission rate.

Today, Internet is facing two challenges simultaneously: the need of a higher switching speed and provision of a QoS guarantee. The first requires that the buffers in switch must work at a line rate and the second requires that switch should mimic output queued switch. In this paper, a new buffered crossbar architecture with duplicated ports is presented. Theoretical analyzing demonstrate that the new fabric can not only mimic output queued switch without speedup, but also provide the low bound of crosspoint buffer. This shows that the proposed fabric is more appropriate for high performance switches.

This paper proposes a fast algorithm particularly for the most computational complexity part in a Multiview Video Coding (MVC) systemuni-directional and bi-directional predictions. Based on the stereo-motion consistency constraint, an iterative search strategy with adaptive refinement search range adjustment technique is proposed for uni-directional prediction, in which motion and disparity vectors can be achieved jointly. Furthermore, an efficient early termination is proposed for bi-directional prediction on the basis of the analysis of multiview video sequences. Experimental results demonstrate the effectiveness of the proposed fast algorithm.

Soft Output Viterbi Algorithm (SOVA) is more practical than MAP in the algorithms for decoding Turbo codes, because of its shorter decoding delay. In order to decrease further the decoding delay and increase the decoding speed, based on the simple analysis of the radix-4Max-Log-MAP algorithm, a novel radix-4SOVA algorithm is proposed and a comprehensive mathematical explanation is given. The key of the algorithm is to propose a novel reliability update method which achieves the reliability update after combining two-step state transitions in trellis diagram. Simulation results show that the BER performance of the novel algorithm is very close to that of radix-4Max-Log-MAP, and approaches radix-4MAP when the extrinsic information coefficient is adaptively added. Moreover, it reduces greatly the decoding delay and memory unit and achieves a good trade-off with the computational complexity.

The start-up conditions for differential oscillator with an even number of stages are analyzed in this paper. Compared with those that have an odd number of stages, such oscillators may have two stable equilibrium states besides an astable equilibrium state in which the circuits can start to oscillate. To avoid the risk of possible latching up into the stable states, an additional start-up circuit technique is proposed. The proposed circuit should also reduce the start-up time. The theory is further confirmed with the design and fabrication of three kinds of differential ring Voltage-Controlled Oscillator (VCO), a 3-stage one, 4-stage ones with and without the start-up circuit based on a 0.13 μm standard CMOS process. The measurement results show that the 3-stage one and the 4-stage one with the start-up circuit have the correct output oscillation signals, but the 4-stage without the start-up circuit has nothing to output.

The Adaptive Integral Method (AIM) in conjunction with the Asymptotic Waveform Evaluation (AWE) technique is presented for fast Radar Cross Section (RCS) calculation of arbitrarily shaped perfect electric conductor targets over a broad frequency band. The application of AWE enables fast frequency sweep analysis. The AIM is employed to reduce the matrix storage and to accelerate the matrix-vector multiplications in the solutions of the Taylor coefficients, the computational rate is improved and the memory requirement is reduced. Combining with Automatic Differentiation (AD) technique, the high order frequency derivatives of Green’s function required in the hybrid method are calculated. The numerical results presented in this paper are compared with the results obtained by the conventional AIM point-by-point calculations. The proposed hybrid technique can greatly reduce the computation time without loss of accuracy.

Three problems of the coaxial output cavity operating at TM₃₁₀ mode for Multiple-Beam Klystron (MBK) are concerned: the field distribution symmetry, the external Q-factor of operating mode, and the frequency interval between operating mode and neighboring modes. In order to improve the performance of coaxial output cavity, a cavity with reentrant ring and short circuit pole is proposed. Setting the short circuit pole suitably can not only decrease external Q-factor, but also make field distribution uniform. Furthermore, inserting the reentrant ring can enlarge frequency interval between operating mode and neighboring modes to suppress the parasitic modes. The coaxial output cavity in X-band is modeled and simulated by CST-MWS. And then the actual output cavity is manufactured and tested. The tested frequency intervals between TM₃₁₀ mode and neighboring modes are both enlarged to more than 1.2 GHz. The external Q-factor is diminished from 507.4 to 193.5. And the symmetry of the field distribution of TM₃₁₀ mode is improved.

MIMO (Multiple-Input Multiple-Output) radar has evident advantages in target detection, parameter estimation, and so on. The Cramer-Rao Bound (CRB) for parameter estimation is proved to be a useful tool for characterizing system design and STAP performance. Therefore, based on MIMO radar with collocated antennas utilizing orthogonal frequency division signal, the space time frequency signal model of target and clutter is given to be used in MIMO radar first. On the basis of the model, the CRB of the ML estimator of ground moving target angle and Doppler for MIMO radar are deduced based on STFAP. Finally, through simulation of CRB performance, it is demonstrated that MIMO radar is effective in eliminating velocity blind zones and improving target parameter estimation accuracy.

The issue of Co-Channel Interference (CCI) in the Orthogonal Frequency Division Multiplexing (OFDM) systems is studied in this paper. A time-domain estimation and elimination scheme of sinusoidal-modeled CCI is proposed based on the Minimum Mean Square Error (MMSE) criterion. It is proved by simulation that the proposed algorithm can suppress the CCI effectively. Compared with the existing scheme, the proposed time-domain method can avoid the interference leakage because of the time-to-frequency transformation, the dependence on channel estimation and the loss of useful data caused by directly erasing.

In the high-dimensional space, the classification hyperplane tends to pass through the origin and bias (b) is not need. To study whether ν-SVM for classification needs (b), dual optimization formulation of ν-SVM without (b) is proposed and the corresponding method of solving the optimization formulation is presented. The dual optimization formulation is transformed into equality constraint sub-optimization formulation by the active set strategy in this method, then the sub-optimization formulation is transformed into the linear equation by lagrange multiplier method. The experimental results show that the existence of (b) would reduce the generalization ability of ν-SVM and ν-SVM can only obtain the sub-optimal solution of ν-SVM without b.

The date rate to bandwidth ratio is one of the most important parameter of a communication system in band limited channels. For improving the date rate to bandwidth ratio of the nonsinusoidal orthogonal modulation system in time domain, a new efficient nonsinusoidal modulation method is proposed based on the ternary coding. By converting the serial binary data stream into parallel ternary ones and mapping with three phases of corresponding orthogonal pulses, each symbol can carry more information, so the date rate to bandwidth ratio can be increased. The modulation and demodulation models are proposed and the performance of data-rate-to bandwidth ratio and the bit error rate are derived theoretically. The comparing and simulation result shows that the proposed method can increase the date rate to bandwidth ratio with the cost of the signal to noise ratio not more than 0.3 dB. The proposed method can be used in the condition with high transmission rate in band limited channels and helpful for reducing the complexity of realization.

Base Station Cooperation (BSC) is considered as a promising way for Co-Channel Interference (CCI) mitigation and system capacity improvement in multicell OFDMA systems. How to allocate radio resource optimally to guarantee the quality of services is a key problem in OFDMA systems with BSC. Previous research mostly focuses on the case of homogenous service. This paper studies subcarrier and power allocation problem in such a system where users with Best Effort (BE) service and those with Rate-Constrained (RC) service coexist. A two-stage heuristic algorithm is proposed. In the first stage, the algorithm allocates resource to only RC users, trying to minimize the number of subcarriers needed to satisfy their rate requirements with the help of value matrix of subcarriers. In the second stage, the remaining subcarriers are assigned optimally to BE users to maximize their sum rate. Simulation results show that the proposed algorithm outperforms the counterparts in both system outage probability and BE users' sum rate.

Exploring a new routing control protocol is a hot spot in WSN research. A cluster-based Self-Adaptive Hybrid Routing Control (SAHRC) protocol for WSN in special application is proposed based on traditional LEACH protocol. It takes account of large-scale event-driven network application scenarios, uses self-configuring and trigger mechanism to solve the shortages of LEACH in large-scale networks, such as the lack of self-adaptability, leaving consideration of the node’s residual energy, and the difficulty in improving communication efficiency. The simulation experiments show that, compared with existing LEACH algorithm, the algorithm SAHRC provides higher performance in stability and energy-saving.

Considering the routing optimization issue in nested NEtwork MObility (NEMO), an adaptive routing optimization scheme based on cost function is proposed. In the scheme, depending on the communication and mobility pattern, the communication of nested NEMO is divided into three communication models, including binding update model, data routing model and balanced communication model; Different routing optimization strategy is chosen to balance the binding update signaling and the data tunneling cost to minimize the total cost in the models. The simulation results show that the scheme can shorten tunnel length and transmission delay, achieve the minimum cost of the communication in nested NEMO and have good adaptability for network topology dynamic changes.

Based on memory polynomial model, this paper proposes a new RF power amplifier predistortion linearization method using single feedback, which only needs the in-phase or quadrature component of the quadrature demodulated IQ signal, and it also can acquire the model parameters of predistorter. This method can eliminate the gain and phase imbalance problems caused by quadrature demodulator, and one feedback sampling circuit is saved, which can reduce the costs, simplify the system design, as well as improve the predistortion linearization performance. Simulation and experiment results show the correctness of the proposed method, which can achieve satisfied linearization performance.

The development of a 16-channel electrophysiological signal detecting system based on the microelectrode array is described. The detecting system consists of hardware and software components, and the hardware can be divided into the following three modules: Microelectrode array interface module, which is used for connection of the micro-electrode array and the detecting system; Multi-channel signal amplification module, which is used for signal amplification; Data acquisition module, which is used for high speed data acquisition. The software design uses multi-threaded and multi-caching technology to ensure the data’s real-time observation and analysis. The main parameters of the detecting system are tested, and the laboratory-made microelectrode array is used for the detection of acute hippocampus slices. The system,s input noise Vrms is less than 2 μV, total gain of the amplifier is 1000, frequency band is 10-3000 Hz. The neural electrophysiological signals of brain slice are successfully detected. With the proper design of hardware and software system, the voltage revolution of system can attain 0.6 μV which can meet the demand of neural electrophysiological signal detection.