In this paper, we propose a hierarchical Stackelberg game based resource allocation algorithm (HGRAA) to jointly allocate the wireless and computational resources of a mobile edge computing (MEC) system. The proposed HGRAA is composed of two levels: the lower-level evolutionary game (LEG) minimizes the cost of mobile terminals (MTs), and the upper-level exact potential game (UEPG) maximizes the utility of MEC servers. At the lower-level, the MTs are divided into delay-sensitive MTs (DSMTs) and non-delay-sensitive MTs (NDSMTs) according to their different quality of service (QoS) requirements. The competition among DSMTs and NDSMTs in different service areas to share the limited available wireless and computational resources is formulated as a dynamic evolutionary game. The dynamic replicator is applied to obtain the evolutionary equilibrium so as to minimize the costs imposed on MTs. At the upper level, the exact potential game is formulated to solve the resource sharing problem among MEC servers and the resource sharing problem is transferred to nonlinear complementarity. The existence of Nash equilibrium (NE) is proved and is obtained through the Karush-Kuhn-Tucker (KKT) condition. Simulations illustrate that substantial performance improvements such as average utility and the resource utilization of MEC servers can be achieved by applying the proposed HGRAA. Moreover, the cost of MTs is significantly lower than other existing algorithms with the increasing size of input data, and the QoS requirements of different kinds of MTs are well guaranteed in terms of average delay and transmission data rate.

This letter presents an analytical study of the reverse link Erlang capacity of 3G/Ad Hoc Integrated networks. In the considered integrated network, 3G networks and Ad Hoc networks operate over the same frequency band and hence cause interference to each other. The reverse link Erlang capacity is analyzed and discussed in two cases: Ad Hoc networks use and do not use power control.

In the localization systems based on time difference of arrival (TDOA), multipath fading and the interference source will deteriorate the localization performance. In response to this situation, TDOA estimation based on blind beamforming is proposed in the frequency domain. An additional constraint condition is designed for blind beamforming based on maximum power collecting (MPC). The relationship between the weight coefficients of the beamformer and TDOA is revealed. According to this relationship, TDOA is estimated by discrete Fourier transform (DFT). The efficiency of the proposed estimator is demonstrated by simulation results.

This letter presents an analytical study of outage probability of a 3G/Ad Hoc cooperative network. The considered cooperative network can improve the signal quality so as to decrease the outage probability. Meanwhile, it imposes additional interference on other ongoing users. But on the whole, our analytical study and simulation results show that the cooperative network can still effectively overcome outage event and decrease the average outage probability.

We propose a call admission control scheme in cellular and wireless local area networks (WLANs) integration: integrated service-based admission control with load-balancing capability (ISACL). The novel aspects of the ISACL scheme include that load transfer in the cellular/WLAN overlapping areas is allowed for the admission of originating data calls from the area with cellular access only and vertical handoff requests to the cellular network. Packet-level quality of service (QoS) constraints in the WLANs and other-cell interference in the code division multiple access (CDMA) cellular network are taken into account to derive the WLANs and cellular capacity. We model the integrated networks using a multi-dimensional Markov chain and the important performance measures are derived for effective optimization of the admission parameters. The analytical model is validated by a computer simulation. The variation of admission parameters with traffic load and the dependence of resource utilization on admission parameters are investigated. It is shown that optimal balancing of the traffic load between the cellular network and WLANs results in the maximum resource utilization. Numerical results demonstrate that substantial performance improvements can be achieved by applying the proposed ISACL scheme.

We propose two vertical handoff schemes for cellular network and wireless local area network (WLAN) integration: integrated service-based handoff (ISH) and integrated service-based handoff with queue capabilities (ISHQ). Compared with existing handoff schemes in integrated cellular/WLAN networks, the proposed schemes consider a more comprehensive set of system characteristics such as different features of voice and data services, dynamic information about the admitted calls, user mobility and vertical handoffs in two directions. The code division multiple access (CDMA) cellular network and IEEE 802.11e WLAN are taken into account in the proposed schemes. We model the integrated networks by using multi-dimensional Markov chains and the major performance measures are derived for voice and data services. The important system parameters such as thresholds to prioritize handoff voice calls and queue sizes are optimized. Numerical results demonstrate that the proposed ISHQ scheme can maximize the utilization of overall bandwidth resources with the best quality of service (QoS) provisioning for voice and data services.

Much attention has recently been paid to sparsity-aware space-time adaptive processing (STAP) algorithms. The idea of sparsity-aware technology is commonly based on the convex l1-norm penalty. However, some works investigate the lq (0 < q < 1) penalty which induces more sparsity owing to its lack of convexity. We herein consider the design of an lq penalized STAP processor with a generalized sidelobe canceler (GSC) architecture. The lq cyclic descent (CD) algorithm is utilized with the least squares (LS) design criterion. It is validated through simulations that the lq penalized STAP processor outperforms the existing l1-based counterparts in both convergence speed and steady-state performance.

In the traditional time delay estimation methods, it is usually implicitly assumed that the observed signals are either only direct path propagate or coherently received. In practice, the multipath propagation and incoherent reception always exist simultaneously. In response to this situation, the joint maximum likelihood (ML) estimation of multipath delays and system error is proposed, and the estimation of the number of multipath is considered as well for the specific incoherent signal model. Furthermore, an algorithm based Gibbs sampling is developed to solve the multi-dimensional nonlinear ML estimation. The efficiency of the proposed estimator is demonstrated by simulation results.

It is well known that both shape and motion can be factorized directly from the measurement matrix constructed from feature points trajectories under orthographic camera model. In practical applications, the measurement matrix might be contaminated by noises and contains outliers. A direct SVD (Singular Value Decomposition) to the measurement matrix with outliers would yield erroneous result. This paper presents a novel algorithm for computing SVD with outliers. We decompose the SVD computation as a set of alternate linear regression subproblems. The linear regression subproblems are solved robustly by applying the RANSAC strategy. The proposed robust factorization method with outliers can improve the reconstruction result remarkably. Quantitative and qualitative experiments illustrate the good performance of the proposed method.

The problem of multi-body motion segmentation is important in many computer vision applications. In this paper, we propose a novel algorithm called fuzzy k-subspace clustering for robust segmentation. The proposed method exploits the property that under orthographic camera model the tracked feature points of moving objects reside in multiple subspaces. We compute a partition of feature points into corresponding subspace clusters. First, we find a "soft partition" of feature points based on fuzzy k-subspace algorithm. The proposed fuzzy k-subspace algorithm iteratively minimizes the objective function using Weighted Singular Value Decomposition. Then the points with high partition confidence are gathered to form the subspace bases and the remaining points are classified using their distance to the bases. The proposed method can handle the case of missing data naturally, meaning that the feature points do not have to be visible throughout the sequence. The method is robust to noise and insensitive to initialization. Extensive experiments on synthetic and real data show the effectiveness of the proposed fuzzy k-subspace clustering algorithm.

The recently proposed distributed adaptive direct position determination (D-ADPD) algorithm provides an efficient way to locating a radio emitter using a sensor network. However, this algorithm may be suboptimal in the situation of colored emitted signals. We propose an enhanced distributed adaptive direct position determination (EDA-DPD) algorithm. Simulations validate that the proposed EDA-DPD outperforms the D-ADPD in colored emitted signals scenarios and has the similar performance with the D-ADPD in white emitted signal scenarios.

Infrared and visible image fusion can combine the thermal radiation information and the textures to provide a high-quality fused image. In this letter, we propose a hybrid variational fusion model to achieve this end. Specifically, an ℓ0 term is adopted to preserve the highlighted targets with salient gradient variation in the infrared image, an ℓ1 term is used to suppress the noise in the fused image and an ℓ2 term is employed to keep the textures of the visible image. Experimental results demonstrate the superiority of the proposed variational model and our results have more sharpen textures with less noise.

We present a review of several types of microwave antennas made of metamaterials, including the resonant electrically small antennas, metamaterial-substrate patch antennas, metamaterial flat-lens antennas, and Luneburg lens antennas. In particular, we propose a new type of conformal antennas using anisotropic zero-index metamaterials, which have high gains and low sidelobes. Numerical simulations and experimental results show that metamaterials have unique properties to design new antennas with high performance.