For general multiple-input multiple-output (MIMO) interference networks, determining the feasibility conditions of interference alignment (IA) to achieve the maximum degree of freedom (DoF), is tantamount to accessing the maximum spatial resource of MIMO systems. In this paper, from the view of antenna configuration, we first explore the IA feasibility in the K-user MIMO interference channel (IC), G-cell MIMO interference broadcast channel (IBC) and interference multiple access channel (IMAC). We first give the concept of the equalized antenna, and all antenna configurations are divided into two categories, equalized antennas and non-equalized ones. The feasibility conditions of IA system with equalized antennas are derived, and the feasible and infeasible regions are provided. Furthermore, we study the correlations among IC, IBC and IMAC. Interestingly, the G-cell MIMO IBC and IMAC are two special ICs, and a systemic work on IA feasibility for these three interference channels is provided.

In this letter, we introduce a novel keys distribution optimization scheme for CP-ABE based access control. This scheme integrates roles, role hierarchies and objects grouping to accelerate keys distribution, meanwhile the CP-ABE encrypting overhead is reduced by adopting deterministic cryptographic function. Experiments show that our scheme obtains noticeable improvement over the original one, especially when the number of objects is much greater than that of users.

In this paper, a low-complexity precoding scheme for minimizing the bit error rate (BER) subject to fixed power constraint for distributed antenna systems with non-Kronecker correlation over spatially correlated Rayleigh fading channels is presented. Based on an approximated BER bound and a newly defined compressed signal-to-noise ratio (CSNR) criterion, closed-form expressions of power allocation and beamforming matrix are derived for the developed precoding scheme. This scheme not only has the calculation of the power allocation less than and also obtain the BER performance close to that of the existing optimal precoding scheme. Simulation results show that the proposed scheme can provide BER lower than the equal power allocation and single mode beamforming scheme, has almost the same performance as the existing optimal scheme.

With development of wireless communication technologies, users are no longer satisfied with only a single service provided per time. They are willing to enjoy multiple services simultaneously. Therefore scheduling multiple services per user becomes quite important usability issue in the area of resource management. In this paper, the multiple-service scheduling problem is firstly formulated as an integrated optimization problem based on a utility function in homogeneous service systems. Due to its NP-hard characteristic, a set of low-complexity sub-optimal algorithms is therefore proposed and used to schedule resources for multiple services per user at the downlink of Orthogonal Frequency Division Multiplexing (OFDM) systems. The proposed algorithms are capable to effectively and efficiently distribute assigned resources among multiple services for one user. Moreover the utility of our algorithms is further extended from homogeneous service systems to heterogeneous service systems. And full exploitation of multi-user diversity gain is achieved while guaranteeing quality of service (QoS). The simulation results show that the proposed algorithm outperforms traditional algorithm in terms of system best effort service throughput and fairness criterion.

Head action recognition, as a specific problem in action recognition, has been studied in this paper. Different from most existing researches, our head action recognition problem is specifically defined for the requirement of some practical applications. Based on our definition, we build a corresponding head action dataset which contains many challenging cases. For action recognition, we proposed a real-time head action recognition framework based on HOF and ELM. The framework consists of face detection based ROI determination, HOF feature extraction in ROI, and ELM based action prediction. Experiments show that our method achieves good accuracy and is efficient enough for practical applications.

This paper investigates interference coordination for 3-dimension (3D) antenna array systems in multicell multiple-input multiple-output (MIMO) and orthogonal frequency division multiple-access (OFDMA) wireless networks. Cell-center user and cell-edge user specific downtilts are accordingly partitioned through dynamic vertical beamforming in the 3D MIMO-OFDM communication systems. Taking these user specific downtilts into consideration, the objective of our proposed interference coordination scheme is to maximize both the cell-edge users' and cell-center users' throughput, subject to per base-station (BS) power, cell-center user and cell-edge user specific downtilt constraints. Here, two coordination techniques, consisting of the fractional frequency reuse (FFR) scheme and partial joint process (JP) coordinated multiple point (COMP) transmission mode, are introduced in this paper. To solve the interference coordination problem, two resource block (RB) partitioning schemes are proposed for the above-mentioned coordination techniques accordingly. Based on such RB partitioning, JP CoMP-based dual decomposition method (JC-DDM) and FFR-based dual decomposition method (FDDM) are proposed, where RB assignment, power allocation (RAPA) and downtilts adjustment are jointly optimized. To simplify the computation complexity, a suboptimal algorithm (SOA) is presented to decouple the optimization problem into three subproblems by using FFR scheme. Simulation results show that all of our proposed algorithms outperform the interference coordination scheme with fixed downtilts. JC-DDM and FDDM find the local optimal throughput with different transmission techniques, while SOA iteratively optimize the downtilts and RAPA which shows close-to-optimal performance with much lower computation complexity.

Based on imperfect channel state information (CSI), the energy efficiency (EE) of downlink distributed antenna systems (DASs) with multiple receive antennas is investigated assuming composite Rayleigh fading channels. A new EE is introduced which is defined as the ratio of the average transmission rate to the total consumed power. According to this definition, an optimal power allocation (PA) scheme is developed for maximizing EE in a DAS subject to the maximum transmit power constraint. It is shown that a PA solution for the constrained EE optimization does exist and is unique. A Newton method based practical iterative algorithm is presented to solve PA. To avoid the iterative calculation, a suboptimal PA scheme is derived by means of the Lambert function, which yields a closed-form PA. The developed schemes include the ones under perfect CSI as special cases, and only need the statistical CSI. Thus, they have low overhead and good robustness. Moreover, the theoretical EE under imperfect CSI is derived for performance evaluation, and the resulting closed-form EE expression is obtained. Simulation results indicate that the theoretical EE can match the corresponding simulated value well, and the developed suboptimal scheme has performance close to optimal one, but with lower complexity.

In recent years, the increasing complexity of deep network structures has hindered their application in small resource constrained hardware. Therefore, we urgently need to compress and accelerate deep network models. Channel pruning is an effective method to compress deep neural networks. However, most existing channel pruning methods are prone to falling into local optima. In this paper, we propose a channel pruning method via Improved Grey Wolf Optimizer Pruner which called IGWO-Pruner to prune redundant channels of convolutional neural networks. It identifies pruning ratio of each layer by using Improved Grey Wolf algorithm, and then fine-tuning the new pruned network model. In experimental section, we evaluate the proposed method in CIFAR datasets and ILSVRC-2012 with several classical networks, including VGGNet, GoogLeNet and ResNet-18/34/56/152, and experimental results demonstrate the proposed method is able to prune a large number of redundant channels and parameters with rare performance loss.

Orthogonal arrays and orthogonal partitions have great significance in communications and coding theory. In this letter, by using a generalized orthogonal partition, Latin squares and orthogonal Latin squares, we present an iterative construction method of orthogonal arrays of strength t and orthogonal partitions. As an application of the method, more orthogonal arrays of strength t and orthogonal partitions than the existing methods can be constructed.

In this paper, we investigate the antenna and node selection issues for amplify-and-forward (AF) and decode-and-forward (DF) multi-antenna relay networks in correlated channels. Based on the channel statistics, optimal selection criteria for antenna and relay node are derived jointly, aiming to maximize the ergodic capacity. Instantaneous channel knowledge-based selection schemes, motivated by traditional antenna selection algorithms, are investigated as well. It is shown that the proposed node selection schemes derived from antenna selection on relay nodes are feasible and effective in relay systems. Statistical selection shows considerable capacity gain compared to full complexity scheme and random selection strategy in AF mode, while instantaneous selection performs better in DF relaying. Furthermore, the proposed schemes are shown to be robust to channel estimation errors due to their correlation-oriented nature.

A semi-distributed resource allocation scheme based on multihop equilibrium is proposed for OFDM-relay networks. This method aims to reduce the amount of feedback information from the relay nodes (RNs). Moreover, it utilizes radio resource by striking an efficient balance between the capacities of the BS-RN link and RN-MS link. Simulation results show that the proposed semi-distributed scheme achieves good performances in terms of throughputs and fraction of satisfied users.

This paper addresses the sensing-throughput tradeoff problem by using cluster-based cooperative spectrum sensing (CSS) schemes in two-layer hierarchical cognitive radio networks (CRNs) with soft data fusion. The problem is formulated as a combinatorial optimization problem involving both discrete and continuous variables. To simplify the solution, a reasonable weight fusion rule (WFR) is first optimized. Thus, the problem devolves into a constrained discrete optimization problem. In order to efficiently and effectively resolve this problem, a lexicographical approach is presented that solving two optimal subproblems consecutively. Moreover, for the first optimal subproblem, a closed-form solution is deduced, and an optimal clustering scheme (CS) is also presented for the second optimal subproblem. Numerical results show that the proposed approach achieves a satisfying performance and low complexity.

Power consumption has become a critical factor for embedded systems, especially for battery powered ones. Caches in these systems consume a large portion of the whole chip power. Embedded systems usually adopt set-associative caches to get better performance. However, parallel accessed cache ways incur more energy dissipation. This paper proposed a region-based way-partitioning scheme to reduce cache way access, and without sacrificing performance, to reduce the cache power consumption. The stack accesses and non-stack accesses are isolated and redirected to different ways of the L1 data cache. Under way-partitioning, cache way accesses are reduced, as well as the memory reference interference. Experimental results show that the proposed approach could save around 27.5% of L1 data cache energy on average, without significant performance degradation.

This letter proposes an intra-cell partial spectrum reuse (PSR) scheme for cellular OFDM-relay networks. The proposed method aims to increase the system throughput, while the SINR of the cell edge users can be also promoted by utilizing the PSR scheme. The novel pre-allocation factor γ not only indicates the flexibility of PSR, but also decreases the complexity of the reuse mechanism. Through simulations, the proposed scheme is shown to offer superior performances in terms of system throughput and SINR of last 5% users.

To tackle the increasing testing power during built-in self-test (BIST) operations, this paper proposes a new test pattern generator (TPG). With the proposed reconfigurable LFSR, the reconfigurable Johnson counter, the decompressor and the XOR gate network, the introduced TPG can produce the single input change (SIC) sequences with few repeated vectors. The proposed SIC sequences minimize switching activities of the circuit under test (CUT). Simulation results on ISCAS benchmarks demonstrate that the proposed method can effectively save test power, and does not impose high impact on test length and hardware for the scan based design.

The next generation mobile communication system is required to support wideband wireless data links when terminals are moving at very high speed. In such case, accurate channel estimation is more crucial in this case. This paper presents a downlink channel estimation scheme for Multi-Input and Multi-Output (MIMO) MC-CDMA system by introducing uncorrelated and continuous pilot symbol sequence for every transmit antenna in code domain. Compared with conventional pilot aided estimation methods which insert pilots symbols in time domain, frequency domain or both of them, the proposed method can obtain more accurate channel impulse response matrix estimation in fast fading environments with much lower computation complexity and less resources exhausted. At last, we analyzed the BER performances of the scheme under a typical fast fading environment-VB and AWGN.

The automatic analysis of retinal fundus images is of great significance in large-scale ocular pathologies screening, of which optic disc (OD) location is a prerequisite step. In this paper, we propose a method based on saliency detection and attention convolutional neural network for OD detection. Firstly, the wavelet transform based saliency detection method is used to detect the OD candidate regions to the maximum extent such that the intensity, edge and texture features of the fundus images are all considered into the OD detection process. Then, the attention mechanism that can emphasize the representation of OD region is combined into the dense network. Finally, it is determined whether the detected candidate regions are OD region or non-OD region. The proposed method is implemented on DIARETDB0, DIARETDB1 and MESSIDOR datasets, the experimental results of which demonstrate its superiority and robustness.

This letter addresses linear processing issues for the downlink of closed-loop multi-user non-regenerative MIMO-relay systems with arbitrary number of antennas at each node. First three precoding design schemes at BS are presented. Then given the fixed BS linear processing matrix, we propose a joint iterative linear processing scheme for the relay station and mobile stations, aiming to minimize the total mean squared error (MSE). Finally Simulation results are provided to show the performance gain of joint linear processing at the multi-antenna nodes.