The Cuckoo Search (CS) is apt to be trapped in local optimum relating to complex target functions. This drawback has been recognized as the bottleneck of its widespread use. This paper, with the purpose of improving CS, puts forward a Cuckoo Search algorithm featuring Multi-Learning Strategies (LSCS). In LSCS, the Converted Learning Module, which features the Comprehensive Learning Strategy and Optimal Learning Strategy, tries to make a coordinated cooperation between exploration and exploitation, and the switching in this part is decided by the transition probability Pc. When the nest fails to be renewed after m iterations, the Elite Learning Perturbation Module provides extra diversity for the current nest, and it can avoid stagnation. The Boundary Handling Approach adjusted by Gauss map is utilized to reset the location of nest beyond the boundary. The proposed algorithm is evaluated by two different tests: Test Group A(ten simple unimodal and multimodal functions) and Test Group B(the CEC2013 test suite). Experiments results show that LSCS demonstrates significant advantages in terms of convergence speed and optimization capability in solving complex problems.

Constrained by quality-of-service (QoS), a robust transceiver design is proposed for multiple-input multiple-output (MIMO) interference channels with imperfect channel state information (CSI) under bounded error model. The QoS measurement is represented as the signal-to-interference-plus-noise ratio (SINR) for each user with single data stream. The problem is formulated as sum power minimization to reduce the total power consumption for energy efficiency. In a centralized manner, alternating optimization is performed at each node. For fixed transmitters, closed-form expression for the receive beamforming vectors is deduced. And for fixed receivers, the sum-power minimization problem is recast as a semi-definite program form with linear matrix inequalities constraints. Simulation results demonstrate the convergence and robustness of the proposed algorithm, which is important for practical applications in future wireless networks.

In this paper, we study the approximate point set matching (APSM) problem with minimum RMSD score under translation, rotation, and one-to-one correspondence in d-dimension. Since most of the previous works about APSM problems use similality scores that do not especially care about one-to-one correspondence between points, such as Hausdorff distance, we cannot easily apply previously proposed methods to our APSM problem. So, we focus on speed-up of exhaustive search algorithms that can find all approximate matches. First, we present an efficient branch-and-bound algorithm using a novel lower bound function of the minimum RMSD score for the enumeration version of APSM problem. Then, we modify this algorithm for the optimization version. Next, we present another algorithm that runs fast with high probability when a set of parameters are fixed. Experimental results on both synthetic datasets and real 3-D molecular datasets showed that our branch-and-bound algorithm achieved significant speed-up over the naive algorithm still keeping the advantage of generating all answers.

With the existing of coverage holes, the Quality of Service (such as event response, package delay, and the life time et al.) of a Wireless Sensor Network (WSN) may become weaker. In order to recover the holes, one can locate them by identifying the boundary nodes on their edges. Little effort has been made to distinguish the boundary nodes in a model where wireless sensors are randomly deployed on a three-dimensional surface. In this paper, we propose a distributed method which contains three steps in succession. It first projects the 1-hop neighborhood of a sensor to the plane. Then, it sorts the projected nodes according to their angles and finds out if there exists any ring formed by them. At last, the algorithm validates a circle to confirm that it is a ring surrounding the node. Our solution simulates the behavior of rotating a semicircle plate around a sensor under the guidance of its neighbors. Different from the existing results, our method transforms a three-dimensional problem into a two-dimensional one and maintaining its original topology, and it does not rely on any complex Hamiltonian Cycle finding to test the existence of a circle in the neighborhood of a sensor. Simulation results show our method outperforms others at the correctness and effectiveness in identifying the nodes on the edges of a three-dimensional WSN.

In this letter, as a generalization of Luo et al.'s constructions, a construction of codebook, which meets the Welch bound asymptotically, is proposed. The parameters of codebook presented in this paper are new in some cases.

In this paper, we consider a group testing (GT) problem. We derive a lower bound on the probability of error for successful decoding of defected binary signals. To this end, we exploit Fano's inequality theorem in the information theory. We show that the probability of error is bounded as an entropy function, a density of a pooling matrix and a sparsity of a binary signal. We evaluate that for decoding of highly sparse signals, the pooling matrix is required to be dense. Conversely, if dense signals are needed to decode, the sparse pooling matrix should be designed to achieve the small probability of error.

Price-based power control problem is investigated in the spectrum sharing cognitive radio networks (CRNs) by Stackelberg game. Using backward induction, the revenue function of the primary user (PU) is expressed as a non-convex function of the transmit power of the secondary users (SUs). To solve the non-convex problem of the PU, a branch and bound based price-based power control algorithm is proposed. The proposed algorithm can be used to provide performance benchmarks for any other low complexity sub-optimal price-based power control algorithms based on Stackelberg game in CRNs.

Instance features based deep learning methods prompt the performances of high speed object tracking systems by directly comparing target with its template during training and tracking. However, from the perspective of human vision system, prior knowledge of target also plays key role during the process of tracking. To integrate both semantic knowledge and instance features, we propose a convolutional network based object tracking framework to simultaneously output bounding boxes based on different prior knowledge as well as confidences of corresponding Assumptions. Experimental results show that our proposed approach retains both higher accuracy and efficiency than other leading methods on tracking tasks covering most daily objects.

In this letter, as a generalization of Heng's constructions in the paper [9], a construction of codebooks, which meets the Welch bound asymptotically, is proposed. The parameters of codebooks presented in this paper are new in some cases.

Workflow nets (WF-nets for short) are a subclass of Petri nets and are used for modeling and analysis of workflows. Soundness is a criterion of logical correctness defined for WF-nets. A WF-net is said to be sound if it satisfies three conditions: (i) option to complete, (ii) proper completion, and (iii) no dead tasks. In this paper, focusing our analysis on acyclic free choice WF-nets, we revealed that (1) Conditions (i) and (ii) of soundness are respectively equivalent to the liveness and the boundedness of its short-circuited net; (2) The decision problem for each condition of soundness is co-NP-complete; and (3) If the short-circuited net has no disjoint paths from a transition to a place (or no disjoint paths from a place to a transition), each condition can be checked in polynomial time.

This paper gives an overview on the design process of modulated metasurface (MTS) antennas and focus on their performance in terms of efficiency and bandwidth. The basic concept behind MTS antennas is that the MTS imposes the impedance boundary conditions (IBCs) seen by a surface wave (SW) propagating on it. The MTS having a spatially modulated equivalent impedance transforms the SW into a leaky wave with controlled amplitude, phase and polarization. MTS antennas are hence highly customizable in terms of performances by simply changing the IBCs imposed by the MTS, without affecting the overall structure. The MTS can be configured for high gain (high aperture efficiency) with moderate bandwidth, for wide bandwidth with moderate aperture efficiency, or for a trade-off performance for bandwidth and aperture efficiency. The design process herein described relies on a generalized form of the Floquet wave theorem adiabatically applied to curvilinear locally periodic IBCs. Several technological solutions can be adopted to implement the IBCs defined by the synthesis process, from sub-wavelength patches printed on a grounded slab at microwave frequencies, to a bed of nails structure for millimeter waves: in any case, the resulting device has light weight and a low profile.

In the successive refinement problem, a fixed-length sequence emitted from an information source is encoded into two codewords by two encoders in order to give two reconstructions of the sequence. One of two reconstructions is obtained by one of two codewords, and the other reconstruction is obtained by all two codewords. For this coding problem, we give non-asymptotic inner and outer bounds on pairs of numbers of codewords of two encoders such that each probability that a distortion exceeds a given distortion level is less than a given probability level. We also give a general formula for the rate-distortion region for general sources, where the rate-distortion region is the set of rate pairs of two encoders such that each maximum value of possible distortions is less than a given distortion level.

The construction of frequency hopping sequences with good Hamming correlation is the foundation of research in frequency hopping communication. In this letter, classes of optimal low hit zone frequency hopping sequence set are constructed based on the interleaving technology. The results of the study show that the sequence set with large family size is optimal for the Peng-Fan-Lee bound. And all the sequences in the set are inequivalent.

An optimal arrangement problem involves finding a component arrangement to maximize system reliability, namely, the optimal arrangement. It is useful to obtain the optimal arrangement when we design a practical system. An existing study developed an algorithm for finding the optimal arrangement of a connected-(r, s)-out-of-(m, n): F lattice system with r=m-1 and n<2s. However, the algorithm is time-consuming to find the optimal arrangement of a system having many components. In this study, we develop an algorithm for efficiently finding the optimal arrangement of the system with r=m-1 and s=n-1 based on the depth-first branch-and-bound method. In the algorithm, before enumerating arrangements, we assign some components without computing the system reliability. As a result, we can find the optimal arrangement effectively because the number of components which must be assigned decreases. Furthermore, we develop an efficient method for computing the system reliability. The numerical experiment demonstrates the effectiveness of our proposed algorithm.

A b-symbol read channel is a channel model in which b consecutive symbols are read at once. As special cases, it includes a symbol-pair read channel (b=2) and an ordinary channel (b=1). The sphere packing bound, the Gilbert-Varshamov (G-V) bound, and the asymptotic G-V bound for symbol-pair read channels are known for b=1 and 2. In this paper, we derive these three bounds for b-symbol read channels with b≥1. From analysis of the proposed G-V bound, it is confirmed that the achievable rate is higher for b-symbol read channels compared with those for ordinary channels based on the Hamming metric. Furthermore, it is shown that the optimal value of b that maximizes the asymptotic G-V bound is finitely determined depending on the fractional minimum distance.

A novel secure spatial modulation (SM) scheme based on dynamic multi-parameter weighted-type fractional Fourier transform (WFRFT), abbreviated as SMW, is proposed. Each legitimate transmitter runs WFRFT on the spatially modulated super symbols before transmit antennas, the parameters of which are dynamically updated using the transmitting bits. Each legitimate receiver runs inverse WFRFT to demodulate the received signals, the parameters of which are also dynamically generated using the recovered bits with the same updating strategies as the transmitter. The dynamic update strategies of WFRFT parameters are designed. As a passive eavesdropper is ignorant of the initial WFRFT parameters and the dynamic update strategies, which are indicated by the transmitted bits, it cannot recover the original information, thereby guaranteeing the communication security between legitimate transmitter and receiver. Besides, we formulate the maximum likelihood (ML) detector and analyze the secrecy capacity and the upper bound of BER. Simulations demonstrate that the proposed SMW scheme can achieve a high level of secrecy capacity and maintain legitimate receiver's low BER performance while deteriorating the eavesdropper's BER.

This paper presents an efficient acceleration algorithm for Lloyd-type k-means clustering, which is suitable to a large-scale and high-dimensional data set with potentially numerous classes. The algorithm employs a novel projection-based filter (PRJ) to avoid unnecessary distance calculations, resulting in high-speed performance keeping the same results as a standard Lloyd's algorithm. The PRJ exploits a summable lower bound on a squared distance defined in a lower-dimensional space to which data points are projected. The summable lower bound can make the bound tighter dynamically by incremental addition of components in the lower-dimensional space within each iteration although the existing lower bounds used in other acceleration algorithms work only once as a fixed filter. Experimental results on large-scale and high-dimensional real image data sets demonstrate that the proposed algorithm works at high speed and with low memory consumption when large k values are given, compared with the state-of-the-art algorithms.

In this paper, we consider coded multi-input multi-output (MIMO) systems with low-density parity-check (LDPC) codes and space-time block code (STBC) in MIMO channels. The LDPC code takes the role of a channel code while the STBC provides spatial-temporal diversity. The performance of such coded MIMO system has been shown to be excellent in the past. In this paper, we present a performance analysis for an upper bound on probability of error for coded MIMO schemes. Compared to previous works, the proposed approach for the upper bound can avoid any explicit weight enumeration of codewords and provide a significant step for the upper bound by using a multinomial theorem. In addition, we propose a log domain convolution that enables us to handle huge numbers, e.g., 10500. Comparison of system simulations and numerical evaluations shows that the proposed upper bound is applicable for various coded MIMO systems.

In an approximately synchronized (AS) code-division multiple-access (CDMA) communication system, zero correlation zone (ZCZ) sequences can be used as its spreading sequences so that the system suppresses multiple access interference (MAI) and multi-path interference (MPI) fully and synchronously. In this letter, the mutually orthogonal (MO) ZCZ polyphase sequence sets proposed by one of the authors are improved, and the resultant ZCZ sequences in each set arrive at the theoretical bound regarding ZCZ sequences under some conditions. Therefore, the improved MO ZCZ sequence sets are optimal.

IEEE 802.11ah is a specification being developed for sub-1GHz license-exempt operation and is intended to provide Low Power Wide Area (LPWA) communication services and support Internet of Things (IoT) features such as large-scale networks and extended transmission range. However, these features also make the 802.11ah networks highly susceptible to channel contention and hidden node problem (HNP). To address the problems, the 11ah Task Group proposed a Restricted Access Window (RAW) mechanism. It shows outstanding performance in alleviating channel contention, but its effect on solving HNP is unsatisfactory. In this paper, we propose a simple and effective hidden node grouping algorithm (HNGA) based on IEEE 802.11ah RAW. The algorithm collects hidden node information by taking advantage of the 802.11 association process and then performs two-stage uniform grouping to prevent hidden node collisions (HNCs). Performance of the proposed algorithm is evaluated in comparison with other existing schemes in a hidden node situation. The results show that our proposed algorithm eliminates most of hidden node pairs inside a RAW group with low overhead penalty, thereby improving the performance of the network. Moreover, the algorithm is immune to HNCs caused by cross slot boundary transmissions.