- EI核心期刊
For the requirements of future green communication, the impacts of location and amounts for distributed antenna on the system energy efficiency are studied in wireless communication systems. Based on the analysis of energy consumption and capacity, the closed-form expression of energy efficiency is obtained, and energy-efficient networking schemes are proposed under the constraints of mobile station quality of service and total energy consumption. Simulation indicates that the distributed antenna systems with energy-efficient networking scheme can significantly reduce the total energy consumption and enhance the energy efficiency.
Aiming at that the multidimensional orthogonal envelope signal performance under quantum reception is still unclear with the existence of background noise, the multidimensional space recursive law is used to receive multidimensional orthogonal envelope signal. Simultaneously, the angle between received photon signal state and measuring state is reduced by a pivoting way to achieve the optimal detection design of quantum receiver. Also, the expression of maximum correct detection probability under multidimensional orthogonal envelope signal is unified. Numerical analysis indicates that, compared with the direct direction way, the space pivoting way to receive multidimensional orthogonal envelope signal can improve the receiver direction performance when influenced by background noise because it reduces the bit error rate and the symbol error rate.
Application graph cuts algorithm to optimization solution the equivalent energy function of Markov random field model for image fusion problem could not only obtain global optimal solution, but also can get significant calculation efficiency when compare with the simulated annealing algorithm for solving the same energy function of image fusion problem, simulation results show that the algorithm is feasible and efficient.
In order to exploit the sparsity inherent in underwater acoustic channel, and improve the channel estimation accuracy as well as the bit error rate of a cyclic prefixed single carrier block transmission system, a new sparse channel estimation scheme based on compressed sensing is proposed. The new method uses a pilot sequence with unit energy to construct frequency domain measurement matrix that satisfies restricted isometry property, and recovers sparse channel impulse response of the underwater acoustic channel from limited number of observation measurements by using Dantzig selector. Computer simulations based on real lake channel profile shows that the new method can significantly improve the channel estimation accuracy, the proposed compressed sensing based channel estimation method can outperform the traditional frequency domain least square method by about 5 dB when using frequency domain minimum mean square error detection method at the same training sequence length.
An uplink transmission non-codebook based precoding method is proposed which can be used in local area network or wide area network wireless communication systems. The new method is based on the geometric mean decomposition (GMD) decomposition precoding and the mixed parallel interference cancellation/serial interference cancellation (PIC/SIC) detection based on orthogonal-triangular (QR) decomposition algorithms. Two main disadvantages of complex algorithm of uplink transmission with codebook based precoding and the wide bandwidth occupying of the codebook numbers for feedback are overcomed. Simulation shows that the performance of the mixed PIC/SIC based on QR decomposition detection algorithm applied in our transmission method can be improved, and the complexity of mixed PIC/SIC algorithm is lower than that of codebook based precoding methods. The proposed transmission method is appropriate for detecting received signals in wireless local area network uplink devices.
Aiming at solving automated negotiation problem, an active learning based method was proposed to learn opponents negotiation preference. The process of negotiation was viewed as a proposals sequence which can be mapped into bidding trajectory feature space to form sample set. Due to fierce competition, the cost of labeling samples is high. Therefore, active learning algorithm was applied to improve the prediction accuracy of opponents negotiation preference within budget. The experimental results show that the proposed method has better prediction ability, which can reduce the number of negotiation steps and increase the overall utility of negotiation.
In order to solve the uneven energy consumption caused by typical clustering routing using multi-hop transmission in wireless sensor networks(WSN), a ring-based clustering routing protocol for WSN using particle swarm optimization is proposed. The entire region is divided into a number of concentric circles with different intervals. Each ring contains many sectors regarded as the basic unit for cluster head selection. And each node runs for cluster head according to the distance to the center of sector and its residual energy. Meanwhile, the energy level mechanism is introduced to overcome the weaknesses that the network overhead is too large when the cluster head rotation speed is too fast and a single node dies prematurely when the cluster head rotation speed is too slow. Simulation shows that this protocol can effectively balance the energy consumption among the rings, and extend the network lifetime.
In order to improve the performance of energy detection on broadband signals without priori information of interference system, a broadband spectrum model based on sampling is set up, and the closed-form of the decision threshold based on the minimum-error-rate criteria is derived. Simulation shows that the minimum error rate detection outperforms traditional narrowband signal detection in broadband scenario in absence of priori information.
By using the method of matrix analysis, the orbit of the resilient 2-rotation symmetric Boolean functions with 2p variables is investigated, where p≥3and p is prime. Some properties about characteristic matrix of them are given. A necessary and sufficient condition for 2-rotation symmetric Boolean functions(RSBFs) with 4 or 2p variables being resilient is derived. Construction and counting of this class functions are equivalent to solving three equation systems. Construction and counting of all the resilient 2-RSBFs with 2p variables are determined by this way.
The population diversity of conventional genetic algorithm can be easily destroyed, which further leads to premature convergence. To solve this problem, based on adaptive genetic algorithm (AGA) proposed by Srinivas, a modified adaptive genetic algorithm (MAGA) is presented by introducing a parameter measuring the population diversity. In this way, the probabilities of crossover and mutation are adjusted automatically according to both population diversity and the trends of fitness values. Since MAGA and back-propagation (BP) algorithm are good at searching global and local optimum respectively, an optimized BP neural network based on MAGA (MAGA+BP) is then presented for traffic classification. The Internet traffic dataset provided by university of Cambridge is introduced for experimental validation. Results show that: MAGA shows better performance on maintaining population diversity, overcomes the premature convergence of AGA and improves the fitness value of resulting optimum by 10.17%; MAGA+BP shows a better performance on Internet traffic classification.
A multivariate quadratic signature scheme with double checks is presented. In the method, a homomorphic Hash function was used to medium field extension cryptosystem, and the private secrets were hidden in the central functions of the scheme. As signature verification is to verify public key polynomial vector in general and its interior structure, this method improves the ability to resist Grbner-basis attack to some extent. Analysis shows that the scheme with the double checks can prevent forging signature effectively and have a higher security.
Multi-objective particle swarm optimization based on a K-means guide selection strategy (KMOPSO) is proposed. A K-means algorithm based guide selection strategy is used to select K evenly located non-dominated particles from the archive in order to ensure the particles in the population move to the entire Pareto front and improve the diversity of solutions. A pruning method based on the nearest neighbour is adopted to control the size of the archive, while preserving the diversity of the archive. A mutation operator is presented to improve the exploration ability for preventing from premature. Simulation on five classical test functions indicates the feasibility of the proposed algorithm. KMOPSO can generate non-dominated solutions close to the true Pareto front and outperform non-dominated sorting genetic algorithm II and multi-objective particle swarm optimization with crowding distance in terms of the diversity of non-dominated solutions.
In order to realize energy-efficient transmission in cognitive radio networks, a method of the joint optimization scheme of spectrum sensing and transmission power allocation under hybrid spectrum sharing is investigated. Firstly, the energy-efficient transmission under hybrid spectrum sharing is formulated as an optimization problem with multiple constraints. The optimal spectrum sensing and power allocation schemes are analyzed. And a low-complexity joint optimization iterative algorithm is proposed to approximate the optimal solution as well. Simulation indicates that the performance of the proposed algorithm is very closed to the optimal algorithm, but with the greatly decreased complexity.
A new weighted proportional fairness adaptive particle swarm optimization cross-layer resource allocation algorithm (WAPCRA) is proposed for multi-user orthogonal frequency division multiplexing (OFDM) system. The algorithm executes weighted proportional fairness scheduling in the media access control layer, leads adaptive particle swarm optimization algorithm into its resource allocation and derives a new power allocation pattern in the physical layer. Simulation demonstrates that WAPCRA algorithm can increase effectively the total system rates on the basis of low complexity, guaranteeing users 'fairness and meeting the delay of users’ traffic.
In order to solve problems of the low traverse efficiency and the high cost of optimal beam sequence searching of multiple-beam antenna with large number of typical test beams combination, a fast search algorithm based on the beam pruning optimization sequence is proposed based on the exploration of the relation between beam and feed source array of the incentive coefficient matrix system. By employing the least squares evaluation method and the beam forming principle of the composite beams, the proposed method establishes a criteria in which, the independence and the coverage and the feed contribution rate of typical tested beam combination is guaranteed respectively, and the average estimation error of the feed source is minimized. Simulations show that the algorithm complexity is reduced, the search results are accurate and the efficiency is obviously improved, and the optimal test beams sequence is searched in actual conditions as well. The proposed method can provide an excellent reference value to find the optimal test beams sequence efficiency and accurately for a practical system.
To overcome intrinsic shortcomings of back propagation(BP)neural network, including slow convergence rate and easy trapping in local minimum, an empirical mode decomposition (EMD)genetic neural networks method is proposed. Firstly, EMD is used to decompose the signals with noise to obtain each intrinsic mode function, each intrinsic mode function corresponding to a frequency band with different energy or a fault feature, and feature vector of each frequency band is used as input sample to optimize neural network. Secondly, the genetic algorithm is used to optimize the weights and thresholds of BP neural network. This method is applied in a simulating experiment for the rolling bearings multiple fault signal analysis, and the ability of fault identification is therefore improved by this method.
A new certificate-based signature scheme is proposed. Assuming the intractability of discrete logarithm problem, the scheme proves to be secure in the strongest security model of certificate-based signature schemes. It requires general cryptographic Hash functions; with no need of any heavily cost bilinear pairing operations in its signing and verifying algorithms. So, it is of advantage of high computation efficiency, and can be used in some power-constrained devices, such as wireless sensor networks.
A design method for asymmetric two-cavity hairpin filter is proposed. Firstly, by using transmission matrices, the relation between the types of serial coupled microstrip transmission line and transmission zeros of transfer response is analyzed. and then, the transmission response formula of the parallel-coupled transmission line filter is derived through even and odd-mode excitations. The serial and parallel microstrip line structures are applied to the design of a two-pole microstrip hairpin filter with asymmetric feed. A N-order cross coupling network with source-load coupling can realize a maximum number of transmission zeros that can equal to N. Compared with source-load coupling, the new two-pole hairpin filter which can obtain three transmission zeros has improved selectivities. A good agreement between measured and simulated data has been reached.
In view of the domain environment in E-documents management, an interoperable cross-domain distribution protocol for E-document is proposed. Based on proxy re-encryption, the scheme uses a semi-trusted entity called proxy server to re-encrypt the document ciphertext without decrypting the ciphertext, such that only users can decrypt the data with his private key. Compared with the existing system, the scheme relieves the server from intense encryption/decryption processing, and achieves reliable decentralized encryption/decryption with good scalability and efficiency.
A cooperative compressed spectrum sensing with low cost is proposed. Each cognitive user derives the measurements as the sign information of the compressed samples by using 1-bit quantization. After receiving the sign information from different cognitive users, the fusion center will utilize two joint sensing algorithms to determine the occupancy of the spectrum. Simulations show that the proposed scheme has a preferable performance, which is not only better than that of independent sensing, but also better than the sensing scheme based on multi-bit quantization at low signal-to-noise ratio.
The forgoing experiments have shown that the method of opinion words identification with non-propagation is extremely limited on social medium information. A method of opinion words expansion identification based on dependency parsing is presented. Through new words and phrases discovery, pruning and merger on dependency tree, the opinion words are expanded. A key advantage of the proposed method is that it can expand words in direct dependency and indirect dependency. Experiments verify the feasibility of this method.
Smart community construction in the smart power consumption link of the smart grid can bring real time interaction between the grid and end-users, improve demand response performance, enhance user energy efficiency management, and realize the load peak shaving. A new approach was proposed to recognize the resident user type in the smart community based on the support vector machine (SVM) classification model, some interesting features were discussed, which included the power consumption rate in the peak load period, load rate, user cooperation degree and so on. Experiment data were collected from the users of the smart community. Experimental results show that SVM is effective for the power resident user type.
In order to improve the comprehensive performance of the decoding algorithm for the error correcting code, a new genetic probability decoding (GPD) algorithm based on genetic algorithm is proposed. This GPD algorithm can further offset the quantification error of the hard decision by applying the additional information in the received sequence with non-quantification, and then restore the maximal likelihood transmission code word. Analysis of the GPD algorithm shows it wont be affected by the number of code symbols, the decoding complexity is relatively lower and the optimization fast decoding can be achieved. Simulation shows that the proposed GPD algorithm has a better decoding correction-error performance.
In Ad hoc networks, a wireless link may be unidirectional because of the difference of transmission range and transmission capability of each node, etc. The features of unidirectional links were studied in Ad hoc networks. A unidirectional link-state advertisement mechanism based on power adjustment (ULAPA) is designed. ULAPA can improve the network connectivity. According to ULAPA, a unidirectional link-state advertisement mechanism based on accurate power adjustment (ULAAPA) is proposed. ULAAPA can decrease energy consumption of nodes through accurate power adjustment. A routing method using unidirectional links is described for Ad hoc network. Results of simulation show some performances are better than those of traditional routing mechanisms.
A generalized probabilistic data association algorithm fusing measurements of multi-sensor to estimate the position of target is proposed. Firstly, the algorithm implements pre-correlation statistical test on all possible multi-tuple of measurement, and estimates the targets position that the valid multi-tuple of measurement which has passed through the pre-correlation statistical test corresponds to. Then the association probability between the valid measurement and target track is calculated according to generalized probabilistic data association algorithm, and is further used to calculate the update state of target. In comparison with sequential processing of multi-sensor generalized probabilistic data association algorithm and joint probabilistic data association algorithm fusing measurements of multi-sensor to estimate the position of target, the new algorithm has the advantages of both the optimal estimate and effective reuse of information. Both theory analyses and simulation results have verified the effectiveness of the proposed algorithm.
Traditional access control restrains unauthorized access only by logical method, which is vulnerable to suffer from address spoofing because of ignoring physical location. It can provide better security through introducing spatial information into access control. Security properties of objects are closely related to time in mandatory access control model. Therefore, the change of objects security property over time should be reflected in access control model. Based on classic Bell-Lapadula model (BLP), a mandatory access control model with temporal and spatial constraints is proposed, in which both time constraints and space constraints are considered. Compared to BLP model, the new model can provide better flexibility and security.
A chaotic ultra-wideband (UWB) frequency adaptive detect and avoid (DAA) design method based on chaotic spread spectrum-carrier modulation is proposed for narrow band interference suppression. Furthermore, Gaussian 7-th derivative pulse is considered as UWB original pulse and Tent chaotic sequence is acted as spread spectrum sequence. Simulation shows that the proposed DAA method can provide stable UWB normal transmit power, and have high transmission efficiency and make uninterrupted communications. Moreover, the adaptive notch pulse can produce arbitrary spectral notches and have flexible anti-interference ability, the Tent chaotic sequence is proved to have stronger byte error rate performance than that of the traditional pseudo noise sequence in the direct sequence spread spectrum system.
Joint optimization assisted by the channel and power allocation of multi-terminal cooperative communication is a new paradigm for cooperative wireless network, and parallel data transmission between the source and destination node is implemented based on various transmission modes (e.g., direct, dual-hop and relay transmission). By modeling nodes of network as energy sellers, a new joint optimization scheme based on energy pricing is proposed for channel allocation and power control. Simulation shows that system energy-consumption cost and network lifetime of the parallel transmission using our proposed scheme significantly outperforms the single transmission. Moreover, by introducing energy price incentive mechanism, the superiority of the optimal rate allocation over average rate allocation in terms of system performance is verified.
With code division multiple access 2000 1X evolution data optimized standard for wireless transmission, the session setup delay in internet protocol multimedia subsystem is analyzed by using mathematical analysis quantitatively. The produced transmission delay in date link layer is discussed used with radio link protocol, as well as the transmission delay produced by the retransmission scheme of upper layers. Analysis shows, the session setup delay becomes shorter when radio link protocol is used in date link layer, the datagram protocol is used in transport layer, and the session initiation protocol is used in application layer.