Hierarchical mobility prediction in the future heterogeneous networks for the tradeoff between accuracy and complexity

Mobility prediction is one of the promising technologies for improving quality of service(QoS) and network resource utilization. In future heterogeneous networks(HetNets), the network topology will become extremely complicated due to the widespread deployment of different types of small-cell base stations(SBSs). For this complex network topology, traditional mobility prediction methods may cost unacceptable overhead to maintain high prediction accuracy. This problem is studied in this paper, and the hierarchical mobility prediction scheme(HMPS) is proposed for the future HetNets. By dividing the entire process into two prediction stages with different granularity, the tradeoff between prediction accuracy and computational complexity is investigated. Before performing prediction of user mobility, some frequently visited locations are identified from the user’s trajectory, and each location represents an important geographic area(IGA). In the coarse-grained prediction phase, the next most possible location to be visited is predicted at the level of the possible geographic areas by using a second-order Markov chain with fallback. Then, the fine-grained prediction of user position is performed based on hidden Markov model(HMM) from temporal and spacial dimensions. Simulation results demonstrate that, compared with the existing prediction methods, the proposed HMPS can achieve a good compromise between prediction accuracy and complexity.

Guide for Authors

It mainly publishes academic papers, research reports, surveys, research briefings, and degree theses in the field of communications & information systems, signal & information processing, computer software and computer theory, computer application technology, electromagnetism & microwave technology, microelectronics & solid electronics, control theory and control engineering, management science & engineering, and other related basic theories and technologies. The readerships are universities faculties and students, scientists in research institutions, and engineers and managers in enterprises, etc.

Improved distinguisher for Achterbahn-128 stream cipher

Achterbahn-128 is a stream cipher proposed by Gammel et al. and submitted to the eSTREAM project. Though many attacks have been published, no recovery attack better than Naya-Plasencia＇ s results with 256 bit keystream limitation. Similar approach is shown and found a specific parity check and decimation. Then an improved distinguisher is constructed for Achterbahn-128 to recover the key with only O （255） keystream bit and O （2102） time complexity. Furthermore, this result is much more effective than the former.

One-bit compressed sensing recovery algorithm robust to perturbation

One-bit compressed sensing （CS） technology reconstructs the sparse signal when the available measurements are reduced to only their sign-bit. It is well known that CS reconstruction should know the measurement matrix exactly to obtain a correct result. However, the measurement matrix is probably perturbed in many practical scenarios. An iterative algorithm called perturbed binary iterative hard thresholding （PBIHT） is proposed to reconstruct the sparse signal from the binary measurements （sign measurements） where the measurement matrix experiences a general perturbation. The proposed algorithm can reconstruct the original data without any prior knowledge about the perturbation. Specifically, using the ideas of the gradient descent, PBIHT iteratively estimates signal and perturbation until the estimation converges. Simulation results demonstrate that, under certain conditions, PBIHT improves the performance of signal reconstruction in the perturbation scenario.

Reduced-complexity MPA decoder based on multi-level dynamic input thresholds

As a key technology of the fifth generation （5G） wireless communications, sparse code multiple access （SCMA） system has quite high frequency utilization, but its message passing algorithm （MPA） decoder still has high time complexity. By the aid of the proposed multi-level dynamic threshold, the complexity of the MPA decoding can be greatly reduced with little error performance loss. In order to reduce a great deal of insignificant computational amounts of message update, we compare the multi-level symbols probability products with optimized multi-level thresholds step by step before they are used for message update calculation. The dynamic threshold configuration refers to the three factors： the level of input symbol probabilities, signal noise ratio （SNP.） and the number of iterations. Especially, in the joint iterative MPA-Turbo decoding procedure, since most encoded bits have good convergence, the inp^t thresholds can avoid more unnecessary computational overhead of message update and reduce the decoding time more significantly. The simulation results show that the proposed multi-level dynamic thresholds considerably reduce the decoding delay in both additive white Gaussian noise （AWGN） channel and frequency selective fading channel.

Measuring web page complexity by analyzing TCP flows and HTTP headers

To understand website complexity deeply, a web page complexity measurement system is developed. The system measures the complexity of a web page at two levels： transport-level and content-level, using a packet trace-based approach rather than server or client logs. Packet traces surpass others in the amount of information contained. Quantitative analyses show that different categories of web pages have different complexity characteristics. Experimental results show that a news web page usually loads much more elements at more accessing levels from much more web servers within diverse administrative domains over much more concurrent transmission control protocol （TCP） flows. About more than half of education pages each only involve a few logical servers, where most of elements of a web page are fetched only from one or two logical servers. The number of content types for web game traffic after login is usually least. The system can help web page designers to design more efficient web pages, and help researchers or Internet users to know communication details.

Design of a wideband common-mode filter using approximate closed-loop pattern of compact C-shaped defected ground structure

A compact common-mode filter is proposed to suppress common-mode noise for application of high-speed differential signal traces. The filter adopts one big C-shaped defected ground structure （DGS） cell in the left of ground plane and two small C-shaped DGS cells with opposite direction in the right of ground plane. Because these DGS cells have different dimensions, the filter has three adjacent equivalent resonant points, which can suppress wideband common-mode noise effectively. The left C-shaped DGS and its adjacent C-shaped DGS cell form an approximate closed structure, which can efficiently reduce the influence of the mutual capacitance. The filter provides a common-mode suppression from 3.6 GHz to 14.4 GHz over 15 dB while it has a small size of 10 minx 10 mm. The fractional bandwidth of the filter is 120%, and the differential signals still keep good signal integrity. The experimental results are in good agreement with the simulated results.

User abnormal behavior analysis based on neural network clustering

It is the premise of accessing and controlling cloud environment to establish the mutual trust relationship between users and clouds. How to identify the credible degree of the user identity and behavior becomes the core problem？ This paper proposes a user abnormal behavior analysis method based on neural network clustering to resolve the problems of over-fitting and flooding the feature information, which exists in the process of traditional clustering analysis and calculating similarity. Firstly, singular value decomposition （SVD） is applied to reduce dimension and de-noise for massive data, where map-reduce parallel processing is used to accelerate the computation speed, and neural network model is used for softening points. Secondly, information entropy is added to hidden layer of neural network model to calculate the weight of each attribute. Finally, weight factor is used to calculate the similarity to make the cluster more accuracy. For the problem of analyzing the mobile cloud user behaviors, the experimental results show that the scheme has higher detection speed （DS） and clustering accuracy than traditional schemes. The proposed method is more suitable for the mobile cloud environment.

High-throughput low-delay MAC protocol for Tera Hertz ultra-high data-rate wireless networks

To address the problems of the present Tera Hertz medium access control（MAC） protocols such as not updating the time slot requests numbers in time, unreasonable superframe structures and not merging time slot requests from the same pair of nodes, high throughput low delay medium access control（HLMAC）, a novel MAC protocol for Tera Hertz ultra-high data-rate wireless networks is proposed. It reduces the data access delay largely with a new superframe structure, from which nodes can get time slot allocation information immediately. The network throughput is also improved with the help of updating time slot requests number and merging time slot requests from the same pair of nodes. The theoretical analysis verifies the effectiveness of HLMAC, and the simulation results show that HLMAC improves the network throughput by 65.7% and decreases the access delay by 30%, as compared to energy and spectrum-aware medium access control（ES-MAC）.

Heterogeneous wireless network selection algorithm based on group decision

In the environment of heterogeneous wireless networks, it is vital to select a currently optimal network for applications and subscribers. The use of multiple attribute decision making （MADM） for heterogeneous network selection can provide subscribers with satisfactory service quality. Converting heterogeneous network selection into a MADM problem, the authors present an improved algorithm for MADM based on group decision theory. The algorithm combines weight vectors of multiple attribute decision making to obtain a combinational weight vector. Then the results＇ compatibility will be assessed. If they do not meet the requirements of compatibility, the judgment matrix will be modified until a comprehensive vector that satisfies compatibility requirements is produced. The vector is combined with simple weighting method （SAW） for network selection. Simulation shows that the algorithm can provide users with satisfactory quality of service （QoS）.

Guide for Authors

General It mainly publishes academic papers, research reports, surveys, research briefings, and degree theses in the field of communications ＆ information systems, signal ＆ information processing, computer software and computer theory, computer application technology, electromagnetism ＆ microwave technology, microelectronics ＆ solid electronics, control theory and control engineering, management science ＆ engineering, and other related basic theories and technologies. The readerships are universities faculties and students, scientists in research institutions, and engineers and managers in enterprises, etc.

Study on coexistence between DCS1800 and TDD-LTE systems in multi-mode terminals

It＇s well known that the mobile stations will comprise a wide range of radio access technologies（RAT）, providing user with flexible and efficient access to multi-media service and high data rate communications. Although much work has been done for coexistence analysis between different systems base stations（BS）, most of them have not addressed the interference within multi-mode terminal. Hence, for filling the gap, The authors in the article present coexistence studyies of digital cellular system at 1 800 MHz（DCS1800） and time division duplex long term evolution（TDD-LTE） network in multi-mode terminal with multi-service provisioning. A new system model for coexistence was introduced and how deterministic analysis can be done within the terminal was explained. The interference evaluation model was given based on relations between reference sensitivity and signal-to-noise ratio（SNR）, which is also deduced. The system simulation methodology was provided and assumption used in simulation was given. Simulation results were shown with different system parameters. Numeric results indicate that multi-mode terminal is mainly affected by local interference. The minimum antenna isolation required for a health system operation was provided.

Priority-based IEEE 802.15.4 CSMA/CA mechanism for WSNs

The IEEE 802.15.4 standard is widely used in wireless sensor networks （WSNs）. In this paper, we propose a priority-based IEEE 802.15.4 carrier sense multiple access with collision avoidance （CSMA/CA） mechanism for WSNs. Considering traffic load and traffic type of sensor nodes, we classify sensor nodes into three types. In our mechanism, different contention parameters are set for nodes with different priority levels, in order that nodes with high priority achieve high probability to access the channel. By modeling the proposed mechanism using a Markov chain, we analyze and compute the successful transmission probability, throughput and energy consumption for nodes with different priority levels. Finally, our numerical results demonstrate that our mechanism performs well for WSNs.

Trust routing algorithm based on multiple decision factor theory in OSPF protocol

This paper presents a novel trust model based on multiple decision factor theory （MDFT） and a trust routing algorithm based on MDFT to exactly evaluate routing node trust and establish a trustworthy routing path. MDFT integrates four dimensional trust decision factors including behavior, state, recommend and node liveness to realize an exactly finer-grained trust evaluation. On the basis of MDFT, a trust routing algorithm is presented and validated in open shortest path first （OSPF） protocol. Simulation resuRs show that the algorithm can reflect the routing node trust accurately and has better dynamic response ability. Under the circumstance of existing deceptive nodes, the algorithm has better anti-deception performance and higher attack node detection rate than conventional algorithm.

Guide for Authors

It mainly publishes academic papers, research reports, surveys, research briefings, and degree theses in the field of communications ＆ information systems, signal ＆ information processing, computer software and computer theory, computer application technology, electromagnetism ＆ microwave technology, microelectronics ＆ solid electronics, control theory and control engineering, management science ＆ engineering, and other related basic theories and technologies. The readerships are universities faculties and students, scientists in research institutions, and engineers and managers in enterprises, etc.

AMC-based resource allocation in adaptive frequency reused OFDMA-relay networks

In orthogonal frequency division multiple access（OFDMA） relay system,for supporting relay transmission,the base station（BS）-the relay station（RS） link must consume an extra part of resource,which may result in serious resource shortage.In order to improve resource utilization,this paper proposes a dynamic resource allocation scheme in adaptive frequency reused OFDMA-relay system based on adaptive modulation and coding（AMC） technology.In this scheme,relay nodes have two independent antennas and operate in decode-and-forward（DF） and full-duplex mode.Then the BS and RSs share the same subcarriers by spatial multiplexing by two independent antennas.The resource allocation problem is formulated for system downlink throughput maximization.Since the optimal solution couldn＇t be obtained easily,a sub-optimal algorithm is proposed.The adaptive frequency reused algorithm with two independent antennas RS improves the system throughput about 24.3 % compared with the orthogonal frequency allocation with single-antenna model,and increases the system throughput 10.4 % compared with adaptive frequency reused algorithms with single-antenna RS.It is proved that both of the RS with two-antenna model and adaptive frequency reused scheme can improve the system throughput significantly.

Bit error probability of distributed Turbo coded relay systems over quasi-static Rayleigh fading channels

As is known, distributed Turbo coding （DTC） performs close to the theoretic outage probability bound of a relay channel when correct decoding is assumed at the relay. However, decoding error is inevitable in practical fading channels due to the error-prone feature of radio channels, and the decoding error propagation in DTC scheme will severely degrade the error performance of the relay system. As a result, it is necessary to evaluate the error performance of the DTC scheme in multi-hop relaying wireless systems in practical fading channels. Moreover, the theoretical method of analysis provides an effective tool for obtaining the error performance besides lengthy simulations. In this article, the concept of equivalent signal-to-noise ratio （SNR） of the two-hop relay channel and the method of computing equivalent SNR are developed, and then the upper bound on the bit error probability （BEP） of DTC relay systems is analyzed by use of Turbo code＇s distance spectrum, the concept of uniform interleaver, the limit-before-averaging technique, and the union bound method. Both theoretical analysis and numerical simulation are implemented for relay systems with DTC scheme over quasi-static Rayleigh fading channels. The results show that the upper bound approaches the simulation results in the medium to high SNR region.

Iterative estimation of doubly selective channels with ICI suppression for OFDM using KL-BEM

Channel estimation for orthogonal frequency division multiplexing （OFDM） systems operating over doubly selective channels is complicated by the existence of intercarrier interference （ICI）.This paper extends the idea of estimating time-variant channel impulse response （CIR） via time-averaged CIR proposed by Hijazi,and proposes a low-complexity channel estimation scheme with ICI suppression based on Karhunen-Loeve basis expansion model （KL-BEM）,which is in a more general form.In the proposed scheme,the KL-BEM coefficients are obtained through their numerical relationship with the time-averaged CIR.The estimation performance is improved by adopting an expectation-maximization （EM）-based iterative structure combined with a low-complexity ICI equalizer and canceller.Theoretical analysis and simulation results show that the proposed scheme achieves superior performance over the original one with lower computational complexity.

Blind image deconvolution for single motion-blurred image

Motion blur due to camera shake during exposure is one of the most common reasons of image degradation, which usually reduces the quality of photographs seriously. Based on the statistical properties of the natural image＇s gradient and the blur kernel, a blind deconvolution algorithm is proposed to restore the motion-blurred image caused by camera shake, adopting the variational Bayesian estimation theory. In addition, the ring effect is one problem that is not avoided in the process of image deconvolution, and usually makes the visual effect of the restored image badly. So a dering method is put forward based on the sub-region detection and fuzzy filter. Tested on the real blurred photographs, the experimental results show that the proposed algorithm of blind image deconvolution can remove the camera-shake motion blur from the degraded image effectively, and can eliminate the ring effect better, while preserve the edges and details of the image well.

Simplified transmitter design for MIMO systems with channel uncertainty

This article investigates transmitter design in Rayleigh fading multiple input multiple output （MIMO） channels with spatial correlation when there are channel uncertainties caused by a combined effect of channel estimation error and limited feedback. To overcome the high computational complexity of the optimal transmit power allocation, a simple and suboptimal allocation is proposed by exploiting the transmission constraint and differentiating a bound based on Jensen inequality on the channel capacity. The simulation results show that the mutual information corresponding to the proposed power allocation closely approaches the channel capacity corresponding to the optimal one and meanwhile the computational complexity is greatly reduced.