In this letter, constructions of sequences with perfect odd autocorrelation and sequence sets with zero odd correlation zone (ZOCZ) over the 8-QAM+ constellation are presented. Based on odd perfect ternary sequences, odd perfect sequences and ZOCZ sequence sets over the 8-QAM+ constellation are constructed by using shift vectors and mappings. These odd perfect sequences and ZOCZ sequence sets over 8-QAM+ constellation can be used in communication systems to achieve high transmission data rate (TDR) and low interference.

We consider the problem of two-dimensional (2-D) angles of arrival estimation using a newly proposed structure of nonuniform linear array, referred to as nested coprime array with compressed inter-element spacing (CACIS). By constructing a cross-correlation matrix of the received signals, the nested CACIS exhibits a larger number of degrees of freedom. A two-step weighted l1-norm penalty strategy is proposed to fully utilize these degrees of freedom, where the weight matrices are constructed by MUSIC spectrum function and the threshold function, respectively. The proposed method has several salient advantages over the compared method, including increased resolution and accuracy, estimating many more number of sources and suppressing spurious peaks efficiently. Simulation results validate the superiority of the proposed method.

Dedicated Short Range Communication (DSRC) employs one control channel for safety-oriented applications and six service channels for non-safety commercial applications. However, most existing multi-channel schemes require all neighboring vehicles periodically (e.g. every 100 milliseconds) tune to the control channel for a full update of safety-oriented data before they can switch to the service channels for non-safety services. The safety exchange interval increases with the increase of traffic density. Consequently, under high traffic densities, the service channels are often completely idle while the control channel is congested. We propose a RSU Assisted Multi-channel Coordination MAC (RAMC) protocol that fully utilizes all channels to provide simultaneous safety and non-safety communications. Within the radio range of a roadside unit (RSU), vehicles are free to tune to any service channel. The RSU monitors all the safety messages being transmitted in both the control and service channels. Periodically, the RSU broadcasts a consolidated traffic view report to all neighboring vehicles in all channels. Therefore, a vehicle can operate in a service channel as long as it needs to achieve high throughput for non-safety applications, while maintaining adequate and timely safety awareness. Our simulation results show that the proposed RAMC protocol consistently achieves very high percentage of non-safety usage, while maintaining high safety message delivery ratios in various traffic density conditions.

Generalized approximate message passing (GAMP) is introduced into distributed compressed sensing (DCS) to reconstruct jointly sparse signals under the mixed support-set model. A GAMP algorithm with known support-set is presented and the matching pursuit generalized approximate message passing (MPGAMP) algorithm is modified. Then, a new joint recovery algorithm, referred to as the joint MPGAMP algorithm, is proposed. It sets up the jointly shared support-set of the signal ensemble with the support exploration ability of matching pursuit and recovers the signals' amplitudes on the support-set with the good reconstruction performance of GAMP. Numerical investigation shows that the joint MPGAMP algorithm provides performance improvements in DCS reconstruction compared to joint orthogonal matching pursuit, joint look ahead orthogonal matching pursuit and regular MPGAMP.

Unsupervised Feature selection is an important dimensionality reduction technique to cope with high-dimensional data. It does not require prior label information, and has recently attracted much attention. However, it cannot fully utilize the discriminative information of samples, which may affect the feature selection performance. To tackle this problem, in this letter, we propose a novel discriminative virtual label regression method (DVLR) for unsupervised feature selection. In DVLR, we develop a virtual label regression function to guide the subspace learning based feature selection, which can select more discriminative features. Moreover, a linear discriminant analysis (LDA) term is used to make the model be more discriminative. To further make the model be more robust and select more representative features, we impose the ℓ2,1-norm on the regression and feature selection terms. Finally, extensive experiments are carried out on several public datasets, and the results demonstrate that our proposed DVLR achieves better performance than several state-of-the-art unsupervised feature selection methods.

Mutipath matching pursuit (MMP) is a new reconstruction algorithm based on compressed sensing (CS). In this letter, we applied the MMP algorithm to channel estimation in orthogonal frequency division multiplexing (OFDM) communication systems, and then proposed an improved MMP algorithm. The improved method adjusted the number of children generated by candidates. It can greatly reduce the complexity. The simulation results demonstrate that the improved method can reduce the running time under the premise of guaranteeing the performance of channel estimation.

Variable-rate linear network codes are investigated in this paper, which are referred to as linear network codes that can support a demanded range of transmission rates on a common netowrk. A new kind of linear network code, called as strict linear broadcast, is defined. Compared with general linear broadcast, it imposes more rigid constraints on the global encoding kernels, but does not require larger finite field size for construction. Then, an efficient scheme is proposed to construct variable-rate linear broadcasts based on the strict linear broadcast. Instead of construcing a fix-rate linear broadcast for each demanded transmission rate, this scheme implements variable-rate linear broadcasts with a single-rate strict linear broadcast. Every node in the network, including the source node, needs to store only one local encoding kernel. When transmission rate varies, the coding operations performed on every network node remain unchanged. Thus, small storage space and no kernel-swithching operations are required on any network code. Furthermore, by combining the strict linear broadcast with a special source-data packetization strategy, a hierarchical broadcast scheme is proposed. With this scheme, multi-rate service can be provided by a single-rate strict linear broadcast to heterogeneous receivers, even at variable transmission rate. Thus, the variable-rate linear broadcasts constructed in this paper are also applicable to the network with heterogeneous receivers.

In this correspondence, a generic method of constructing optimal p2-ary low correlation zone sequence sets is proposed. Firstly p2-ary column sequence sets are constructed, then p2-ary LCZ sequence sets with parameters (pn-1, pm-1, (pn-1)/(pm-1),1) are constructed by using column sequences and interleaving technique. The resultant p2-ary LCZ sequence sets are optimal with respect to the Tang-Fan-Matsufuji bound.

Binary sequence pairs as a class of mismatched filtering of binary sequences can be applied in radar, sonar, and spread spectrum communication system. Binary sequence pairs with two-level periodic autocorrelation function (BSPT) are considered as the extension of usual binary sequences with two-level periodic autocorrelation function. Each of BSPT consists of two binary sequences of which all out-phase periodic crosscorrelation functions, also called periodic autocorrelation functions of sequence pairs, are the same constant. BSPT have an equivalent relationship with difference set pairs (DSP), a new concept of combinatorial mathematics, which means that difference set pairs can be used to research BSPT as a kind of important tool. Based on the equivalent relationship between BSPT and DSP, several families of BSPT including perfect binary sequence pairs are constructed by recursively constructing DSP on the integer ring. The discrete Fourier transform spectrum property of BSPT reveals a necessary condition of BSPT. By interleaving perfect binary sequence pairs and Hadamard matrix, a new family of binary sequence pairs with zero correlation zone used in quasi-synchronous code multiple division address is constructed, which is close to the upper theoretical bound with sequence length increasing.

This letter presents new methods for transforming perfect ternary sequences into perfect 8-QAM+ sequences. Firstly, based on perfect ternary sequences with even period, two mappings which can map two ternary variables to an 8-QAM+ symbol are employed for constructing new perfect 8-QAM+ sequences. In this case, the proposed construction is a generalization of the existing one. Then based on perfect ternary sequence with odd period, perfect 8-QAM sequences are generated. Compared with perfect 8-QAM+ sequences, the resultant sequences have no energy loss.

Ring-based topology is popular for optical network-on-chip. However, the network congestion is serious for ring topology, especially when optical circuit-switching is employed. In this paper, we proposed an algorithm to build a low congestion multi-ring architecture for optical network-on-chip without additional wavelength or scheduling overhead. A network congestion model is established with new network congestion factor defined. An algorithm is developed to optimize the low congestion multi-ring topology. Finally, a case study is shown and the simulation results by OPNET verify the superiority over the traditional ONoC architecture.

Generalized approximate message passing (GAMP) can be applied to compressive phase retrieval (CPR) with excellent phase-transition behavior. In this paper, we introduced the cartoon-texture model into the denoising-based phase retrieval GAMP(D-prGAMP), and proposed a cartoon-texture model based D-prGAMP (C-T D-prGAMP) algorithm. Then, based on experiments and analyses on the variations of the performance of D-PrGAMP algorithms with iterations, we proposed a 2-stage D-prGAMP algorithm, which makes tradeoffs between the C-T D-prGAMP algorithm and general D-prGAMP algorithms. Finally, facing the non-convergence issues of D-prGAMP, we incorporated adaptive damping to 2-stage D-prGAMP, and proposed the adaptively damped 2-stage D-prGAMP (2-stage ADD-prGAMP) algorithm. Simulation results show that, runtime of 2-stage D-prGAMP is relatively equivalent to that of BM3D-prGAMP, but 2-stage D-prGAMP can achieve higher image reconstruction quality than BM3D-prGAMP. 2-stage ADD-prGAMP spends more reconstruction time than 2-stage D-prGAMP and BM3D-prGAMP. But, 2-stage ADD-prGAMP can achieve PSNRs 0.2∼3dB higher than those of 2-stage D-prGAMP and 0.3∼3.1dB higher than those of BM3D-prGAMP.

In this letter, based on cyclic difference sets with parameters $(N,rac{N-1}{2},rac{N-3}{4})$ and complex transformations, a method for constructing degree-4 perfect Gaussian integer sequences (PGISs) with good balance property of length $N'equiv2( ext{mod}4)$ are presented. Furthermore, the elements distribution of the proposed Gaussian integer sequences (GISs) is derived.

With the decrease in transistor feature size, power consumption, especially leakage power, has become a most important design concern. Because of their superior electrical properties and design flexibility, fin-type field-effect transistors (FinFETs) seem to be the most promising option in low-power applications. In order to support the VLSI digital system design flow based on logic synthesis, this paper proposes a design method for low-power high-performance standard cells based on IG-mode FinFETs. Such a method is derived on the basis of appropriately and artfully designing and optimizing the stacked structures in each standard cell, and applying the mixed forward and reverse back-gate bias technique in a well-chosen manner. The proposed method is also applicable when the supply voltage reduces to 0.5V to further reduce the leakage power consumption. By applying this design method, optimized IG-mode FinFET standard cells are generated, and they form a low-power high-performance standard cell library. Simulation results of the library cells indicate that the performance of the standard cells designed with the proposed method can be maintained while reducing leakage consumption by a factor of 58.9 at most. The 16-bit ripple carry adder implemented with this library can acquire up to 17.5% leakage power reduction.

Based on a perfect Gaussian integer sequence, shift and combination operations are performed to construct Gaussian integer sequences with zero correlation zone (ZCZ). The resultant sequence sets are optimal or almost optimal with respect to the Tang-Fan-Matsufuji bound. Furthermore, the ZCZ Gaussian integer sequence sets can be provided for quasi-synchronous code-division multiple-access systems to increase transmission data rate and reduce interference.

Quadriphase sequences with good correlation properties are required in higher order digital modulation schemes, e.g., for timing measurements, channel estimation or synchronization. In this letter, based on interleaving technique and pairs of mismatched binary sequences with perfect cross-correlation function (PCCF), two new methods for constructing quadriphase sequences with mismatched filtering which exist for even length N ≡ 2(mod4) are presented. The resultant perfect mismatched quadriphase sequences have high energy efficiencies. Compared with the existing methods, the new methods have flexible parameters and can give cyclically distinct perfect mismatched quadriphase sequences.

In this letter, several new families of binary sequence pairs with period N=np, where p is a prime and gcd(n,p)=1, and optimal correlation values 1 and -3 are constructed. These classes of binary sequence pairs are based on Chinese remainder theorem. The constructed sequence pairs have optimum balance among 0's and 1's.

Pose estimation is a research hot spot in computer vision tasks and the key to computer perception of human activities. The core concept of human pose estimation involves describing the motion of the human body through major joint points. Large receptive fields and rich spatial information facilitate the keypoint localization task, and how to capture features on a larger scale and reintegrate them into the feature space is a challenge for pose estimation. To address this problem, we propose a multi-scale convergence network (MSCNet) with a large receptive field and rich spatial information. The structure of the MSCNet is based on an hourglass network that captures information at different scales to present a consistent understanding of the whole body. The multi-scale receptive field (MSRF) units provide a large receptive field to obtain rich contextual information, which is then selectively enhanced or suppressed by the Squeeze-Excitation (SE) attention mechanism to flexibly perform the pose estimation task. Experimental results show that MSCNet scores 73.1% AP on the COCO dataset, an 8.8% improvement compared to the mainstream CMUPose method. Compared to the advanced CPN, the MSCNet has 68.2% of the computational complexity and only 55.4% of the number of parameters.

The goal of Acoustic Scene Classification (ASC) is to simulate human analysis of the surrounding environment and make accurate decisions promptly. Extracting useful information from audio signals in real-world scenarios is challenging and can lead to suboptimal performance in acoustic scene classification, especially in environments with relatively homogeneous backgrounds. To address this problem, we model the sobering-up process of “drunkards” in real-life and the guiding behavior of normal people, and construct a high-precision lightweight model implementation methodology called the “drunkard methodology”. The core idea includes three parts: (1) designing a special feature transformation module based on the different mechanisms of information perception between drunkards and ordinary people, to simulate the process of gradually sobering up and the changes in feature perception ability; (2) studying a lightweight “drunken” model that matches the normal model's perception processing process. The model uses a multi-scale class residual block structure and can obtain finer feature representations by fusing information extracted at different scales; (3) introducing a guiding and fusion module of the conventional model to the “drunken” model to speed up the sobering-up process and achieve iterative optimization and accuracy improvement. Evaluation results on the official dataset of DCASE2022 Task1 demonstrate that our baseline system achieves 40.4% accuracy and 2.284 loss under the condition of 442.67K parameters and 19.40M MAC (multiply-accumulate operations). After adopting the “drunkard” mechanism, the accuracy is improved to 45.2%, and the loss is reduced by 0.634 under the condition of 551.89K parameters and 23.6M MAC.

A new class of almost quadriphase sequences with four zero elements of period 4N, where N ≡ 1(mod 4) being a prime, is constructed. The maximum nontrivial autocorrelations of the constructed almost quadriphase sequences are shown to be 4.