In order to extract the micro-Doppler of multi-scatters when the echo is subject to strong noise and translation modification, a method based on the instantaneous Doppler of the strongest scatter is proposed. The instantaneous Doppler of the strongest scatter is obtained by the Viterbi algorithm. The translation Doppler is extracted according to the relation between Doppler rate and micro-Doppler. Translation parameters, on the basis of which the translation signal is reconstructed, are estimated by polynomial regression. Then translation modification is compensated and Micro-Doppler parameters of every scatter are extracted by Hough transform. Simulation results indicate that the method is valid and accurate.
Device-to-Device (D2D) communication underlaying LTE-A cellular networks is effective to improving spectral efficiency and offload traffic of the base station by reusing cellular resources. However, the mutual interference between D2D and cellular communications can degrade the performance of both D2D and cellular users. In this paper, a resource reusing selection scheme based on minimizing power increase is proposed, which enables selective compensation for signal to interference plus noise ratio (SINR) diminution caused by interference. Simulation results demonstrate that the proposed scheme notably improves the access grant probability of D2D users and increases the link spectral efficiency of D2D and cellular networks, without sacrificing the quality of cellular and D2D communication.
The conventional linear interpolation method will introduce the estimation error when the gapped data of ISAR is large. A high resolution imaging method based on compressed sensing for gapped data of ISAR is proposed in this paper. We first construct a sparse basis dictionary and linear measurement matrix. Then the convex optimization means as the base pursuit can be used to extract the scatter property and Doppler frequency information. By all the steps above, the image of ISAR is formed in the plane of range and Doppler. No interpolation is needed for the sparse aperture, and no sidelobes exit in the ISAR images. Simulation results and real sparse ISAR data validate the feasibility and superiority of the approach.
This paper presents a scheme for Quantum Local Area Networks (QLAN) based on entanglement swapping and classical switching, in which the Carrier Sense Multiple Access with Collision Detection (CSMA/CD) protocol is applied to implement multiple users communication, the message on building and releasing channel, etc. is transferred by the classical switch, and the entanglement of photons between sender and receiver is built by entanglement swapping and quantum information is transferred by the principle of quantum teleportation. Performance analysis results show that the throughput of QLAN increases greatly with higher probabilities with which entanglement is built between sender’s photons and receiver’s photons, the sender finishes the joint Bell state measurement successfully and the receiver detects the sender’s qubit information, respectively.
This paper analyzes the structure and characteristics of several types of quasi-orthogonal space-time block codes (QSTBC). It proposes two new methods for QSTBC for four antennas which enrich the family of QSTBC. Experimental results indicate that the two new QSTBC have good performance as in TBH and Jafarkhani cases, while the decoding complexity is the same as that of other QSTBC. This paper has compared the Maximum Likelihood (ML) decoding algorithm and QR decomposition decoding algorithm for the new QSTBC. Simulation results indicate that the QR decoding algorithm has good performance and can reduce the computation complexity.
The paper employs the thoughts of distance vector hop and average hop distance of the DV-hop location algorithm,based on principles of geometry,and a position estimation deviation is introduced to conduct the weighted centroid algorithm, leading to a novel range-free three-dimensional (3D) localization scheme. Both the principles and implementation steps of the algorithm are given. Simulation results indicate that almost all nodes could be located and that the location accuracy will be within 0.4 in the set of three-dimensional space with 40 randomly scattered anchor nodes, while the communication cost remains reasonable compared with the 2D algorithm.
In order to improve the solving performance of particle swarm optimization(PSO), first the basic principle of PSO is analyzed and mapping rules for two types of chaos map are given. Next, PSO based on the Logistic map (LGM-PSO) and Lozi's map (LZM-PSO) are constructed, and the methods for treating two types of constraints are given. To compare the performances of LGM-PSO, LZM-PSO and the standard particle swarm optimization, the three methods are used to solve the benchmark constrained optimal problem. Their performances are compared in terms of optimal solution, success ratio, average valid evaluation number, iterative occupancy hours and so on. Comparison results indicate that the LZM-PSO has many advantages, such as higher solution accuracy and higher computational efficiency.
An improved passive TDOA location method is proposed. The novel method uses the elevation angle of the target as a new measurement to form a redundant location system consisting of three subsystems. Each subsystem can obtain a set of location results with ambiguity. A better performance can be achieved after eliminating the ambiguity by the nearest matching and processing the location results by SWLS fusion. Simulation results show that the proposed method has almost the same precision as the usual method for the high-altitude targets; however, it has a much higher precision for the low-altitude targets.
The inlet is a strong scattering source in the aircraft head important attitude angle. One way to reduce RCS (Radar Cross Section) is to make the inlet S-shaped to increase the electromagnetic wave reflection time to reduce backward wave energy. A series of S-shaped inlets bended vertically and horizontally are tested in the microwave anechoic chamber to study relative curvature's influence. Experimental result shows that when the incident is vertically polarized, the head direction RCS average's variation along the relative curvature is of “W” shape and has 2 minimum values; when horizontally polarized, the head direction RCS average's variation is different in two bend fashions. The variation is of “W” shape when vertically bended and monotonously descends when horizontally bended. Generally speaking, a proper relative curvature can reduce the backward's RCS of the inlet.
An algorithm against eavesdropping adversaries is presented. By means of this algorithm an eavesdropper is unable to get any meaningful information about the source, which we call practical security. We show that if we give up a small amount of overall capacity, then a random code achieves the practically secure condition at a much higher probability. When there is a low rate secret channel between the source and destination, the shared secret algorithm not only achieves the max-flow but also the practically secure condition at a probability of one. Furthermore, implementing the algorithm involves only a slight modification of the source and destination with the operations at the intermediate nodes remaining unchanged.
Considering the motion error of the enemy SAR, this paper proposes a novel realtime approach of deception-jamming. Via quick algorithm, this method pretreats the deception picture first, and then does the convolution operation with the received signal and transmits the signal. In this way, the distance between SAR platform and jamming equipment can be simulated effectively, and the echos contain the motion information. After motion compensation and SAR imaging operation, a more lifelike image can be obtained. This method proposes a quick algorithm of deceptive scene signal generation based on two-step processing, which ensures realtime generation of the signal. Simulation and experimental data have proved the validity of the approach.
To improve the efficiency of the Bonsai trees signature which was proposed in Eurocrypt'10, utilizing the Bonsai trees algorithm, a new lattice-based signature scheme is proposed. Based on the hardness of the short integer solution problem (SIS), the proposed scheme is provably existentially unforgeable under a static chosen-massage attack in the standard model. Moreover, the public-key length of our proposed signature is (k+1)mn log q bit while the bonsai trees signature's is (2k+1)mn log q bit; the signature length of message is (1+k/2)m log q bit while the Bonsai trees signature scheme's is (k+1)m log q bit. So the proposed signature scheme is more efficient than the Bonsai trees signature.
Object tracking is an important task in computer vision applications. One of the crucial challenges is the real-time speed requirement. In this paper we implement an object tracking system in reconfigurable hardware using an efficient parallel architecture. In our implementation, we adopt a background subtraction based algorithm. The designed object tracker exploits hardware parallelism to achieve a high system speed. We also propose a dual object region search technique for further boosting the performance of our system under complex tracking conditions. For our hardware implementation we use the Altera Stratix III EP3SL340H1152C2 FPGA device. We compare the proposed FPGA-based implementation with the software implementation running on a 2.2GHz processor. It has been observed that the speed can be increased by more than 100 times for complex video inputs.
An improved super-exponential iteration decision feedback blind equalization algorithm with the second order digital phase-locked loop (NMSEI-DFE-2DPLL) is proposed in order to overcome the problem of the ill convergence performance of the super-exponential iteration decision feedback algorithm in the underwater acoustic communication system. Based on the analysis of the modified super-exponential iteration error function, a new fast convergence error function is presented which increases carrier recovery ability; a second order digital phase-locked loop is introduced in decision feedback equalization to track and compensate phase rotation, carrying out the transmitted sequence recovery. Computer simulations of the new algorithm about convergence and carrier recovery ability are carried out respectively under two underwater acoustic channels, using two modulation signals. Simulation results demonstrate that the mean square error and convergence rate of the proposed algorithm have been improved to a large extent compared with the SEI-DFE algorithm in mixed phase channel environment, and the phase rotation has been compensated and carrier recovery ability has been improved greatly in channel environment with phase rotation.
After analyzing the influences of quality on inverse halftoning, the research on how to classify the halftone has gone into our view. Using the Self-correlation Function of one-dimension, the Grey Level Co-ocurrence Matrices(GLCM) and the Grey Run-length Matrices(GLRM) the periodic and texture features of the halftoning image are discovered. Based on these properties a new classification algorithm for usual halftones is proposed. Experimental results indicate that the average rate of correct recognition has reached 99%. The new algorithm not only solves the application problem for Estimated-Inverse-Halftoning, but also makes a basic of design and optimization for inverse halftoning.
In order to solve the problem of the blind recognition of Turbo codes,some methods for blind recognition of the Turbo coding parameter with trellis termination are proposed for the first time. Based on the analysis of the sub-encoder structure of Turbo codes,some analytical models of convolutional codes at a rate of 1/2 are proposed, and by recoverying the interleaver sequence of Turbo codes,interleaver mapping is decided by exhaust comparison, and blind recognition of Turbo codes with trellis termination is realized.Simulation results illustrate that given the unknown Turbo encoded data sequence, the recognized coding parameters are correct by comparing prior conditions which validates the accuracy of the proposed methods.
Most existing differential evolution algorithms for the Constrained Optimization Problem(COP) use the penalty function method to handle constrains, which depends strongly on the penalty parameter. So, this paper transforms the COP into two-objective multi-objective optimization by taking constraints as an objective function. Based on the concept of Pareto, the grades of individuals in population are prescribed so as to determine their selection probability in the process of “survival of the fittest”. In addition, when the algorithm gets into a local optimum, an infeasible solution replacing mechanism is also given to improve the search capability. The results of the 13 Standard tests show that compared to the Evolutionary Algorithm based on Homomorphous Maps (EAHM), Constraint Handling Differential Evolution (CHDE), Evolutionary Strategies based on Stochastic Ranking (ESSR) and Artificial Immune Response Constrained Evolutionary Strategy (AIRCES), the proposed algorithm has certain advantages in convergence speed and solution accuracy.
In multi-objective decision, the problem of computing the weights of the indexes is usually considered In view of the shortcomings in the existing techniques, this paper proposes an improved weights determination method by the efficient combination of the entropy weight method (EWM) and the analytic hierarchy process (AHP). In the presented method, the amalgamation is firstly carried out between the objective weights of underlying indexes by EWM and the subjective weights of indexes on the sub-criterion level by AHP. The obtained weights of indexes are synthesized subsequently with the weights of upper indexes. After normalization, the final weights of indexes are obtained. The results show that the final weights by this presented method have higher reliability.
Crucial issues in a particle filter(PF) are to remove the degeneracy phenomenon and alleviate the sample impoverishment problem. In this paper, by using techniques from a genetic algorithm we propose some modifications to solve these problems simultaneously. A genetic algorithm with arithmetic crossover, fast Metropolis-Hastings mutation and the roulette wheel selection improves resampling procedures for the standard particle filter. The new particle filter is developed for IR dim target tracking and detection. By using multi-frame target amplitude and motion features some values of the filter's output are used to approximately construct the likelihood ratio for hypothesis test in the detection stage. Simulation results show that genetic resampling based on fast Metropolis-Hastings can produce various particles and remove the degeneracy phenomenon. For some actual image sequences with an SNR of 2.0, successful detection probability reaches 98.5％ with 10-3 false alarm probability. Experimental results show that the performance of the proposed algorithm is better than that of traditional resampling particle filter algorithms.
The accuracy rate of the face recognition by tensor PCA is higher than that by PCA. And wavelet has two abilities to capture localized time-frequency information and to reduce the dimension of images. According to the two advantages of the above algorithms, a new face recognition algorithm based on wavelet transform and tensor PCA is proposed. Wavelet transform is firstly used and then tensor PCA is used to extract the feature of subband images, and the efficient recognition of face images can be realized. The recognition rate of the proposed alogorithm is 6％ higher than that of the tensror PCA algorithm, and the recognition time of the proposed algorithm is 35.74％ that of the tensor PCA algorithm, which is illustraed in experimental results.
It is a troublesome matter for a Zigbee designer that using the general wireless channel model to estimate transmission distance results in lager errors. By the 802.15.4a channel model, the analytical methods of 2.4GHz Zigbee RF module radiation transmission loss is discussed; the factors that affect the transmission distance are analyzed, and the estimation formula for the maximum transmission distance is derived. For the Zigbee RF module specific circuit designed, the transmission loss and the largest transmission distance are calculated and through the experimental test, the estimated error is less than 10％, which is in line with the requirements of engineering applications, and it can be used as the theoretical basis for 2.4GHz Zigbee RF module design and engineering applications to estimate the transmission distance.
Based on the quadtree structure of the HEVC coding unit, a fast intra coding algorithm that skips splitting subblock is proposed according to the result of the smooth region detection to reduce the intra coding complexity. First, the relationship between the image smoothness and coding unit's size has been analyzed by counting statistically the distribution of corresponding final coding units' sizes selected under different quantization parameters for different video contents. Second, whether the current coding unit belongs to the smooth region is detected according to the coding information on the current coding unit, which can help determine how to adaptively skip the coding process of the coding unit sizes not suitable for the texture features. Experimental results on the latest HM4.0 show that, on average, compared with the default fast approach set in the HEVC reference software, the proposed algorithm reduces the computational complexity by 24.8％ and 18.6％ for Low Complexity (Loco) and High Efficiency (HE) test sets, respectively, while incurring only 0.44％ and 0.12％ increment on the total bit rate, at the same peak signal to noise ratio (PSNR), which is of great practical value.
According to the heavy computation of two-dimensional DOA estimation with 2D-MUSIC, this paper proposes an RD-MUSIC(Reduced-Dimension MUSIC) DOA estimation method without conjunction search or angle pairing. This algorithm decomposes two dimensional DOA estimation into two stage one dimensional DOA estimation. Firstly, we use the rooting method to estimate the angle between signal direction and x axis. Secondly, least square method is used to estimate the angle between signal direction and y axis. Finally, the 2D angle can be obtained with the angle formula. Simulation results show that the angle accuracy of RD-MUSIC is higher than that of 2D-MUSIC in the low SNR condition, and that they are equal in the high SNR condition, but RD-MUSIC has a higher operation speed.
This paper presents an improved particle swarm optimization based fast K-means algorithm which effectively overcomes the shortcomings of the K-means algorithm such as sensitive to initial cluster centroid and easiness to fall into local optimum so as to affect the clustering results. Compared with the existing particle clustering algorithm, is algorithm first normalizes the attributes of all the samples, and then computes the dissimilarity matrix. We propose simplified particle encoding rules and use PSO-based K-means clustering based on the dissimilarity matrix to ensure the basis for the clustering effect and reduce computational complexity. Experimental results on several UCI data sets validate the advantages of the proposed algorithm.
A conventional microstrip low-pass filter has a large area and a narrow stop-band. To solve this problem, a new microstrip low-pass filter is presented in this paper, which is composed of semicircle defected ground structures and semicircle stepped-impedance shunt stubs. The effect of parameter variation of S-DGS and S-SISS on band-stop characteristic is studied. An equivalent circuit model of the proposed LPF is also described. The proposed filter is compact and the 3dB cutoff frequency is 2.7GHz. The stop-band is 4~16GHz, which is wider by 20％ than that of the conventional DGS filter. Simulation results are in good agreement with the measured results, which verifies the reliability of the designed filter.
This paper addresses a new method for parameter estimation of hybrid DS/FH_BPSK signals based on a time-frequency(TF) technique known as the S transform(ST). Good performance is achieved by three stages. Firstly, a nonlinear process is used to produce the reference signal(RFS) which has the same hop parameter as the original signal and its frequencies could be estimated by the cyclic spectrum as the modification information. Then the S transform is improved by adding a Gaussian window width parameter to realize the adaptation of its time-frequency resolution and the ridge curve of ST is extracted as the instantaneous frequency of RFS. Finally, the modification information is used to reduce the estimation error in the high frequency region caused by noise. Simulation results show that the proposed method can operate effectively for hop parameter estimation. Since no prior knowledge of signals is needed, the proposed method is easily implemented in a reconnaissance receiver.
The digital receiver should possess the ability to process a large number of data in real-time for the wideband signal. A new kind of efficient digital channelized receiver is proposed in this paper which is based on polyphase filters and short-time FFT technology(polyphase fast Fourier transform). It can detect objects and measure parameters for the wideband signal in real-time. A digital receiver system with a 640MHz instantaneous bandwidth is built based on the structure proposed using FPGA and DSP devices. It has high accuracy of time-frequency parameter measurement and low data output ratio, which shows the structure is feasible.
To improve the efficiency of web services selection, a computational model for computing the QoS attributes of composite services is first presented, which utilizes a binary tree to express the dependency relationship of tasks in composite services, and aggregates the QoS attributes of different nodes in a bottom-up fashion. As a result, the QoS computing time is reduced by avoiding unnecessary repetitive computation. Then a web services selection approach based on the QGA (Quantum Genetic Algorithm) is proposed. Two dimensional multi-qubits (quantum bits) are employed to code chromosomes with attached identifier marking multi-paths. The quantum rotation gate is introduced to accelerate individual evolution. Experimental results show that, compared with the TGA(Traditional Genetic Algorithm), the QGA can give a better solution in a shorter time.
A new knapsack-type public key cryptosystem is proposed, which is based on an easy knapsack problem. The cryptosystem is secure against Shamir's key-recovery attack in that it prevents the use of the super-increasing knapsack sequence in the construction of the cryptosystem. The cryptosystem is also invulnerable to the low-density subset-sum attack in that it obtains a relatively high density. It is shown that the cryptosystem withstands some brute-force attacks and the simultaneous Diophantine approximation attack. It only performs n addition operations for the cryptosystem to encrypt a plaintext, and the decryption algorithm only carries out n modular 2 divisions. Therefore, the cryptosystem is efficient with respect to the encryption and the decryption. Furthermore, the cryptosystem is suited for software and hardware implementations.
A new method for generating the structural code from the standard program flowcharts is presented. By analyzing the flowchart, linearizing the cycle structure and delimiting the branch structure, the structual C code agreeing with the semanteme of the flowchart is generated. At the same time, the unstructural flowchart is recognized.
In order to implement the multi-parameter estimation for the bistatic radar without any synchronization,a multi-targets signal model of the MIMO bistatic radar is set up and a joint angles-Doppler frequencies estimation algorithm for multi-targets is proposed. In the algorithm, the virtual array data of multitarget echoes in MIMO receivers is first uncorrelated, then a special matrix based on the propagation operator constructed, and finally the joint estimation of the DODs, DOAs and Doppler frequencies can be obtained by the corresponding relationships between the eigenvalue or eigenvector and the estimated parameters. The proposed algorithm does not need the multi-dimensional nonlinear peak search, and only needs an eigenvalue decomposition, and the estimated parameters of the targets can be paired automatically. The correctness and effectiveness of the proposed method are verified with computer simulation.
This paper describes the method for designing a high-resolution frequency meter based on the DDS (Direct Digital Synthesizer) using a simple circuit. In this method, DDS is used to track the value of the measured frequency and synthesizes automatically appropriate frequency standard signals. This method is applicable to measuring signals within a wide range of frequency. Prototype measured data show that the high-resolution frequency meter can reach the magnitude of 10-12/s.
This paper investigates the application of the high impedance surface (HIS) to reduce the radar cross section (RCS) of the antenna. The HIS elements are fabricated on the same surface together with the antenna. Around the operational frequency of the HIS elements, the reflection of the HIS and PEC have the opposite phases, so for any normal incident plane wave the reflections cancel out, thereby reducing the RCS. Thus the HIS can be used to reduce the RCS of the antenna which has a PEC surface radiator. To assess the validity of the proposed method, the HIS is employed to reduce the RCS of two microstrip patch antennas. Simulated and measured results show that the RCS in-band of the two microstrip patch antennas with HIS is reduced by at least 5.3dB compared with the common antennas, with the impedance bandwidth (S11<-10dB) not changed.
Based on the centralized control plane in SDN, an online traffic anomaly detection method (OpenTAD) is proposed. Firstly the flow table statistic is collected from the controller online, and the traffic matrix and sample entropy matrix are constructed and assembled. Then the PCA method is used to detect the abnormal traffic. The result of experiments show that, compared with the traditional PCA method which disposes the traffic matrix or the entropy matrix respectively offline, the OpenTAD is simple and effective, and traffic anomaly could be isolated rapidly. This method is a lightweight online traffic anomaly detection method for SDN.
The modular Bayesian network is proposed, which is utilized to assess the situation in the battlefield. According to the event and target action, the modular Bayesian network is dynamically constructed. In the process of inference for the Bayesian model, the inference result of combined Bayesian networks is considered as the soft evidence of the corresponding node in the present networks. Finally, a simple application of the method is described. The results show that the method is available and computationally efficient.
In the field of high resolution range profile (HRRP) based radar automatic target recognition (ATR), it is an effective approach to tackle the target-aspect sensitivity by segmenting continuous radar data into several sectors in equal angular intervals. This equal angular-sector segmentation algorithm is based on the condition for good quality of ISAR images, but it is not a satisfactory choice with the application of ATR for its inclination to cause model mismatch, performance limitation, and time-consumption. This paper proposes a recursive algorithm for adaptively angular sector segmenting based on Adaptive Gaussian Classifier (AGC) and Gaussian Processes classifier (GPC).Since the HRRP data are continuous along the azimuth,we first exploit the nonlinear structure characteristic embedded in HRRP data through AGC or GPC, then present a criterion for determining the angular-sector boundary, and finally recursively segment the data. Promising experimental results are presented for measured radar data.
Individual communication signals identification is an important issue in the field of communication reconnaissance in recent years. The recurrence plot method is proposed to detect the start-up point of the transient signals, which is based on the nonlinear characteristics of the transient signal. Wavelet transform is used to extract features from the transmitters. The most discriminatory features are selected from a large number of wavelet transform features by genetic algorithms, and Support Vector Machines (SVM) are used to realize the individual identification. Experimental results show that the introduced method achieves good accuracy recognition rate in terms of a little features as reference, with the accuracy recognition being more than 90％.
A novel camera calibration method based on the circular pattern and ellipse fitting is proposed, which combines the advantages of camera calibration based on the planar pattern and one dimensional object. The proposed method designs a new circular pattern, which needs three images of the pattern to calibrate the camera. Ellipse fitting is introduced to locate the feature points in the circular pattern precisely and nonlinear optimization is utilized, and thus the calibration precision has been improved significantly. Experimental results for synthetic data show that the proposed strategy is both accurate and robust. Experimental results for real images prove the performance of the proposed algorithm.
A new approach to ground moving target detection based on two-look processing is proposed for the single channel SAR system. In the proposed approach, according to the shifts of the Doppler spectra of moving targets relative to that of a stationary scene, the Doppler spectra of echoes are separated into two parts and focused separately to obtain two sub-images; the ground clutter can be suppressed by incoherent subtracting of t1he two sub-images; so the signal-to-clutter-plus-noise ratio(SCNR) can be improved. The procedures for ground moving targets location are as follows: the detected moving target complex signatures are first extracted by a window in the SAR image after clutter suppression, then the ground moving targets can be precisely located through estimating the Doppler spectra shift quantities between the ground moving targets and clutter through which the constant false alarm rate (CFAR) can be decreased simultaneously. The validity of this method is verified by the simulation data and the measured data.
According to the effect of limited radio range of sensor nodes upon routing in wireless sensor networks(WSN), an improved multi-hop clustering algorithm based on the minimal structure tree(MST) is proposed to ameliorate the problems of energy consumption because of routing. This algorithm optimizes cluster heads according to the characteristic in the poisson process of the voronoi diagram, and establishes the MST as sensor nodes' dynamic routing for optimizing energy consumption in WSN. This algorithm establishes the MST as sensor nodes' routing and then optimizes the distributed density of cluster heads according to the characteristic in the poisson process of the voronoi diagram. Simulation results indicate that the novel algorithm is able to make energy load balanced at the premise of the cost tolerance, prolong the life-span of the networks effectively and reduce the time complexity compared with multi-hop hierarchy algorithms based on low-energy adaptive cluster hierarchy (LEACH) under the same simulation conditions.
The sample degeneracy is the critical problem existing in the particle filter. In order to solve this problem, a new combined particle filter algorithm, based on the genetic simulated annealing algorithm and unscented Kalman filter algorithm, is presented in this paper. In the proposed algorithm, unscented Kalman filter algorithm is used to generate the importance proposal distribution which can match the true posterior distribution more closely, and the genetic simulated annealing algorithm based upon the survival-of-the-fitness principle is applied to enhance the diversity of samples. Simulation results indicate the effectiveness and feasibility of the proposed algorithm.
A low complexity partial transmit sequence (PTS) scheme is proposed to improve the performance of the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. By analyzing the characteristic of candidate signals, the number of phase factor vectors is reduced from 64 to 16 without the loss of PAPR performance and the search time of the phase factor is reduced. The hardware cost of the IFFT unit can be reduced by adopting the group concept, rescheduling the time of the multiplication with twiddle factors, and using path-based constant multipliers instead of complex multipliers. In the IFFT unit, the hardware costs of complex multipliers, complex adders, and registers are respectively reduced by 58.8％, 28.6％, and 75.6％ compared with four independent IFFT processors with radix 23 and single-path delay feedback. In addition, there is no need for ROM to store the twiddle factor. Moreover, because of the characteristic of the needed phase factor vectors, the hardware overhead of the optimization unit can be lessened.
Confined to the measuring and transmitting conditions in the field, the mud signal model is usually set which contains all kinds of noises. In order to manipulate the signals, an optimal wavelet is designed according to the characteristics of the signals based on the minimum entropy. By using the wavelet, the modular maximum of signals, noises and the baseline are calculated for different scales. The advanced processing algorithms for the modular maximum are conducive to noise-reduction, baseline correction, and singularity detection. The algorithms have been applied with satisfactory results in the Measure While Drilling system in some oil field.
