Journal of China Universities of Posts and Telecommunications最新文献

An ant colony optimization (ACO) based load balancing routing and wavelength assignment (RWA) algorithm (ALRWA) was put forward for the sake of achieving a fairy load balancing over the entire optical satellite networks. A multi-objective optimization model is established considering the characteristic of global traffic distribution. This not only employs the traffic intensity to modify the light path cost, but also monitors the wavelength utilization of optical inter-satellite links (ISLs). Then an ACO algorithm is utilized to solve this model, leading to finding an optimal light path for every connection request. The optimal light path has the minimum light path cost under satisfying the constraints of wavelength utilization, transmission delay and wavelength-continuity. Simulation results show that ALRWA performs well in blocking probability and realizes efficient load balancing. Meanwhile, the average transmission delay can meet the basic requirement of real-time business transmission.

Due to the difficulty of deploying Internet protocol (IP) multicast on the Internet on a large scale, overlay multicast has been considered as a promising alternative to develop the multicast communication in recent years. However, the existing overlay multicast solutions suffer from high costs to maintain the state information of nodes in the multicast forwarding tree. A stateless overlay multicast scheme is proposed, in which the multicast routing information is encoded by a bloom filter (BF) and encapsulated into the packet header without any need for maintaining the multicast forwarding tree. Our scheme leverages the node heterogeneity and proximity information in the physical topology and hierarchically constructs the transit-stub overlay topology by assigning geometric coordinates to all overlay nodes. More importantly, the scheme uses BF technology to identify the nodes and links of the multicast forwarding tree, which improves the forwarding efficiency and decreases the false-positive forwarding loop. The analytical and simulation results show that the proposal can achieve high forwarding efficiency and good scalability.

Voice conversion (VC) based on Gaussian mixture model (GMM) is the most classic and common method which converts the source spectrum to target spectrum. However this method is prone to over-fitting because of its frame-by-frame conversion. The VC with non-negative matrix factorization (NMF) is presented in this paper, which can keep spectrum from over-fitting by adjusting the size of basis vector (dictionary). In order to realize the non-linear mapping better, kernel NMF (KNMF) is adopted to achieve spectrum mapping. In addition, to increase the accuracy of conversion, KNMF combined with GMM (GKNMF) is also introduced into VC. In the end, KNMF, GKNMF, GMM, principal component regression (PCR), PCR combined with GMM (GPCR), partial least square regression (PLSR), NMF correlation-based frequency warping (NMF-CFW) and deep neural network (DNN) methods are compared with each other. The proposed GKNMF gets better performance in both objective evaluation and subjective evaluation.

A feature fusion approach is presented to extract the region of interest (ROI) from the stereoscopic video. [0]Based on human vision system (HVS), the depth feature, the color feature and the motion feature are chosen as vision features. [0]The algorithm is shown as follows. Firstly, color saliency is calculated on superpixel scale. Color space distribution of the superpixel and the color difference between the superpixel and background pixel are used to describe color saliency and color salient region is detected. Then, the classic visual background extractor (Vibe) algorithm is improved from the update interval and update region of background model. The update interval is adjusted according to the image content. The update region is determined through non-obvious movement region and background point detection. So the motion region of stereoscopic video is extracted using improved Vibe algorithm. The depth salient region is detected by selecting the region with the highest gray value. Finally, three regions are fused into final ROI. Experiment results show that the proposed method can extract ROI from stereoscopic video effectively. In order to further verify the proposed method, stereoscopic video coding application is also carried out on the joint model (JM) encoder with different bit allocation in ROI and the background region.

Owing to the unreliability of wireless link and the resource constraints of embedded devices in terms of energy, processing power, and memory size in low power and lossy networks (LLNs), network congestion may occur in an emergency and lead to significant packet loss and end-to-end delay. To mitigate the effect of network congestion, this paper proposes a centralized congestion control routing protocol based on multi-metrics (CCRPM). It combines the residual energy of a node, buffer occupancy rate, wireless link quality, and the current number of sub-nodes for the candidate parent to reduce the probability of network congestion in the process of network construction. In addition, it adopts a centralized way to determine whether the sub-nodes of the congested node need to be switched based on the traffic analysis when network congestion occurs. Theoretical analysis and extensive simulation results show that compared with the existing routing protocol, the performance of CCRPM is improved significantly in reducing the probability of network congestion, prolonging average network lifetime, increasing network throughput, and decreasing end-to-end delay.

Aiming at making full use of analog to digital converter (ADC) digitalizing bit without oversaturation while keeping peak to average ratio (PAR) stable, this paper puts forward a new segmented full-digital (SFD)-automatic gain control (AGC) algorithm for a new long term evolution (LTE) communication system. Segmented digital gain control strategy is adopted to adjust the gain by only one step based on detected power status. Whether the gain needs to be adjusted is determined by current signal state derived from the change ranges of adjacent root mean square (RMS) of input signal, but not the difference between the power level of current signal and target signal. Software simulation and hardware implementing had been conducted with LTE frequency division dual (FDD) uplink signal and the results indicated that the proposed AGC algorithm can judge power status accurately and hence adjust the gain precisely in one step with a short delay, further, it can make full use of ADC digitalizing bit without oversaturation as well as keeping stable PAR. In addition, the mean error vector magnitude (EVM) was confined less than 1.6% to meet the 3rd generation partnership project (3GPP) standard well.

To achieve secure communication in wireless sensor networks (WSNs), where sensor nodes with limited computation capability are randomly scattered over a hostile territory, various key pre-distribution schemes (KPSs) have been proposed. In this paper, a new KPS is proposed based on symplectic geometry over finite fields. A fixed dimensional subspace in a symplectic space represents a node, all 1-dimensional subspaces represent keys and every pair of nodes has shared keys. But this naive mapping does not guarantee a good network resiliency. Therefore, it is proposed an enhanced KPS where two nodes have to compute a pairwise key, only if they share at least q common keys. This approach enhances the resilience against nodes capture attacks. Compared with the existence of solution, the results show that new approach enhances the network scalability considerably, and achieves good connectivity and good overall performance.

Cloud download service, as a new application which downloads the requested content offline and reserves it in cloud storage until users retrieve it, has recently become a trend attracting millions of users in China. In the face of the dilemma between the growth of download requests and the limitation of storage resource, the cloud servers have to design an efficient resource allocation scheme to enhance the utilization of storage as well as to satisfy users' needs like a short download time. When a user's churn behavior is considered as a Markov chain process, it is found that a proper allocation of download speed can optimize the storage resource utilization. Accordingly, two dynamic resource allocation schemes including a speed switching (SS) scheme and a speed increasing (SI) scheme are proposed. Both theoretical analysis and simulation results prove that our schemes can effectively reduce the consumption of storage resource and keep the download time short enough for a good user experience.

Abstract

An efficient solution for locating a target was proposed, which by using time difference of arrival (TDOA) measurements in the presence of random sensor position errors to increase the accuracy of estimation. The cause of position estimation errors in two-stage weighted least squares (TSWLS) method is analyzed to develop a simple and effective method for improving the localization performance. Specifically, the reference sensor is selected again and the coordinate system is rotated according to preliminary estimated target position by using TSWLS method, and the final position estimation of the target is obtained by using weighted least squares (WLS). The proposed approach exhibits a closed-form and is as efficient as TSWLS method. Simulation results show that the proposed approach yields low estimation bias and improved robustness with increasing sensor position errors and thus can easily achieve the Cramer-Rao lower bound (CRLB) easily and effectively improve the localization accuracy.

Abstract

An isotropic electromagnetic (EM) lens based on Huygens' metasurface is proposed for 28.0 GHz lens antenna design. The lens consists of a series of non-resonant and subwavelength metallic patterns etched on both sides of an ultrathin dielectric substrate. Both electric and magnetic responses are introduced to realize desired abrupt phase change and high-efficiency transmission for the secondary wavelets in the incident wavefront. Then, a substrate-integrated waveguide (SIW) fed patch antenna is combined with the lens as the primary feed to form a low-profile lens antenna system. The simulated and measured results coincide with each other, and demonstrate that the prototype realizes 8.8 dB∼12.6 dB gain increment and low side-lobe levels over the bandwidth of 26.7 GHz∼30.0 GHz. The novel design leads to a low-profile, light weight, and low-cost antenna solution in a wireless communication system.