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In this work, two electronic nose (E-nose) prototypes for lung cancer detection via breath analysis are built. The instrumental variation between them is a critical problem, as it impacts on the generalization performance of classification model. The conventional domain adaption (DA) methods are based on the assumption that the data quality of both devices is high enough. However, it is not true in our case because the concentrations of volatile organic compounds (VOCs) biomarkers in breath are very low and the acquisition process of breath samples is prone to many confounding factors. As a countermeasure, a novel and effective two-step sparse unidirectional domain adaptation (SUDA) algorithm is proposed. In the first step, the data quality of each domain is improved, at the meantime, the distribution discrepancy between source and target domain is reduced by finding the common discriminative features via the sparse group lasso algorithm. In the second step, the distribution gap is further narrowed down by adopting the strategies of distribution alignment, local geometric characteristics preserving and label dependence constraint. Experimental results show that the proposed method is not only significantly effective for correcting instrumental variation in the two homemade lung-cancer-detection E-noses, but also demonstrates superior performance on a public E-nose instrumental variation dataset.

In an 8B/10B mode giga-bit-per-second serial data transactions, the de-serialized data is sent to a comma detection and word alignment (CDWA) module to identify the word boundaries, which is a prerequisite in the high-speed transceivers such as PCIe, USB and JESD204B/C. In order to ensure that the comma code (/K/-code) can be correctly detected. Ten 10-bit comma detector cells are adopted in a typical CDWA module, which require a complex circuitry and an enormous power consumption. To overcome these limitations, a low-area and low-power CDWA circuit for JESD204B/C transceiver chip in 8B/10B mode has been proposed in this paper. The bit width of the detector cells can be truncated from 10 to 6 under the condition, that CDWA module can detect a complete comma code correctly. On one hand, the proposed CDWA module is verified with a FPGA development platform with the reduction of the hardware resources and power consumption to 31.72% and 20.11% respectively as compared to the typical structure available. On the other hand, a 10-Gbps transceiver chip with the proposed CDWA module is fabricated with a 55-nm CMOS process and the word alignment function of the proposed module is proved by the measurement results. The area of this transceiver chip including $2\times $ transmitting links and $2\times $ receiving links is 2.89 mm2, and the power consumption is 467.8 mW, under a maximum data transmission rate of 10 Gbps.

In this letter, a low-complexity selected mapping (SLM) algorithm without phase sequence index information, e.g., side information (SI), is proposed. Different from the SLM algorithm without SI using maximum likelihood (ML), the proposed algorithm uses cyclic redundancy check (CRC) to terminate the decoding calculation in advance. Meanwhile, a small amount of known information is adopeted to assist CRC and a simpler phase sequence set is applied to the SLM. The calculation complexity and bit error rate (BER) of typical algorithms are compared with different phase sequence groups under several different channel conditions. As a result, lower computation complexity is obtained with the same peak to average power ratio (PAPR) suppression effect and no BER increase.

This brief presents a dual-band tunable concurrent passive phase shifter monolithic microwave integrated circuit utilizing a two-stage dual-branch phase tuning network topology. The designed phase shifter with two independent phase tuning bands operates at 5.9 GHz and 16 GHz. The dual-band phase shifter is fabricated in a $0.25~\mu \text{m}$ GaAs process and occupies a small chip area of 0.98 mm2 (including pads). Measurement results show that transmission phases in the two frequency bands can be tuned concurrently. Phase tuning range is greater than 105° in either band. Insertion losses of less than 2.8 dB and 3.5 dB are exhibited in 5.8~6 GHz and 15.8~16.2 GHz, respectively. And amplitude imbalances within the whole phase tuning range in 5.8~6 GHz and 15.8~16.2 GHz are less than 1.1 dB and 1.3 dB, respectively. The return losses are greater than 10 dB in both frequency bands. The phase shifter is employed in a four-element dual-band phased array network. The phased array is able to independently tilt its main beam toward −20° ~ +20° in either band.

Due to uneven space–time distribution of vehicles, Internet of Vehicles (IoV) has problems with load imbalance and low resource utilization of Base Stations (BSs) in the Coordinated Multi-Point (CoMP) communication scenario. This paper proposes a dynamic load balancing algorithm based on vehicle prediction. It is assumed that the number of vehicles arriving at the BSs obeys the segmented Poisson distribution to determine the current and predicted load statuses of BSs. First, analyze the load status of each BS and the location of users (vehicles). Then, screen out BSs whose load below the full load threshold as a switchable low-load cooperative cluster, which can convert interference signals into useful signals and reduce the interference between adjacent BSs. Finally, complete load balancing by redistributing the communication service of edge users through sharing channel information and user date among coordinated BSs. Because IoV is a dynamic network, the proposed algorithm runs dynamically in cycles. Simulation results show that the algorithm can perform balance the load of BSs well, the overload rates of BSs during the traffic off-peak period and peak period are reduced significantly, and the average information rate of users is greatly improved.

This brief presents an analog mm-wave active phase shifter utilizing a frequency-reconfigurable vector-summing topology. A frequency-tunable I/Q signal generator followed by frequency-tunable single-to differential convertors and variable gain amplifiers is employed to build the phase shifter. The designed phase shifter can be switched to operate over 24–30 GHz band or 35–41 GHz band. The phase shifter, fabricated in 90 nm CMOS technology, provides 360° of phase shifting range in both frequency bands while consuming only 17.6 mW of power and 0.34 mm2 of chip area (excluding pads). Measurement results show that the phase shifter’s RMS phase errors for 32 phase states are less than 4° and 5.1° over 24–30 GHz band and 35–41 GHz band, respectively. RMS amplitude errors of the phase shifter for 32 measured phase states are less than 0.6 dB and 0.35 dB over the lower and higher operation bands, respectively. The measured input 1 dB compression points are larger than −2.8 dBm and −3.7 dBm over the lower and higher operation bands, respectively. The proposed phase shifter, which is able to cover the released frequency bands of n257, n258 and n260, is a good candidate for 5G mm-wave applications.

In the diagnosis of lung cancer, electronic nose (E-nose) has attracted much attention by detecting the volatile organic compounds (VOCs) in exhaled breath. In this research, an E-nose platform with a novel thermal desorption preconcentration subsystem is designed to verify whether analyzing VOCs can reliably differentiate lung cancer patients from healthy individuals and patients with benign pulmonary diseases. To this end, total 87 subjects (46 patients with lung cancer, 36 healthy volunteers and 5 patients with benign pulmonary diseases) are enrolled for the sensor array data collection. 13 composite features are extracted from each sensor, and some classical classifiers are established to demonstrate the feasibility of identifying lung cancer patients through VOCs. To improve the performance, considering the inherent characteristics of E-nose data, a sparse group feature selection (FS) method is applied to the raw sensor array data. It is observed that the FS method can reduce data dimensionality and improve the classification performance significantly. Statistical analysis for the effect of age and smoking habit on classification results shows that no significant influences are found.

This paper proposed an effective interference alignment algorithm based on channel state feedback concentration (FCIA) for device-to-device (D2D) communications. The algorithm iteratively calculates the precoding matrix by using the global channel state information. Furthermore, as D2D discovery is the premise of the D2D communications, an effective interference alignment algorithm based on D2D discovery is also proposed. Simulation results show that, the proposed FCIA algorithm reduces the feedback overhead for transmission coordination compared with the existing full feedback based algorithm. The proposed interference alignment scheme based on D2D discovery feedback is compared with the existing D2D discovery scheme: it is found that although the discovery time slots has increased by about 6.2%, the sum rate achieved by interference alignment is improved by almost 50%.

The spectrum allocation for cognitive radio networks (CRNs) has received considerable studies under the assumption that the bandwidth of spectrum holes is static. However, in practice, the bandwidth of spectrum holes is time-varied due to primary user/ secondary user (PU/SU) activity and mobility, which result in non-determinacy. This paper studies the spectrum allocation for CRNs with non-deterministic bandwidth of spectrum holes. We present a novel probability density function (PDF) through order statistics as well as its simplified form to describe the statistical properties of spectrum holes, with which a statistical spectrum allocation model based on stochastic multiple knapsack problem (MKP) is formulated for spectrum allocation with non-deterministic bandwidth of spectrum holes. To reduce the computational complexity, we transform this stochastic programming problem into a constant MKP through exploiting the properties of cumulative distribution function (CDF), which can be solved via MTHG algorithm by using auxiliary variables. Simulation results illustrate that the proposed statistical spectrum allocation algorithm can achieve better performance compared with the existing algorithms when the bandwidth of spectrum holes is time-varied.

Through decreasing inter-cell interferences, CoMP (Coordinated Multi-Point) can enhance system capacity and spectral efficiency of cell-edge users significantly. BSs (Base stations) are the front-end accesses of CoMP and their planning influences the overall performance of the system directly. Different from the traditional cellular network, the coverage of BSs in CoMP always overlaps with each other to some degree. In order to investigate the BSs planning for CoMP, this paper builds two optimization models to obtain the location and the number of the BSs. A joint optimization algorithm is proposed to solve models, in which the methodologies of mesh adaptive direct search and successive elimination have been used. Numerical results show that the proposed models can effectively reduce the total transmission power and the number of BSs without losing the quality of service for users, which verifies the effectiveness of the proposed algorithms and the inherent advantage of CoMP.

In C-V2X (cellular vehicle-to-everything) communication networks, dense spatial reuse of the available radio spectrum is required to achieve efficient spectral usage. Spectrum reuse causes severe network interference where signals from many undesired transmitters are aggregated at a receiver. This paper investigates the 3D spatial characteristics of C-V2X communication interference in the angular domain. A 3D GIDM (Gaussian interference distribution model) is proposed, and the corresponding interference APD (angular power density) is given. Then, the closed-form expressions of some key spatial statistics of interference are derived based on the interference APD. Finally, the closed-form expressions of the probability density function and spatial correlation function of SIR (signal&ndash, to&ndash, interference ratio) are derived based on the 3D multipath APD model and spatial statistics of the Rice channel. Simulation analysis shows that 3D spatial angular directions have significant effect on these spatial statistics of interference and the spatial correlation function of SIR. The results provide useful insight on the analysis and design of the interference-limited networks.

With the deployment of small cells and device to device communications in future heterogeneous networks, in many situations we would encounter mobile radio channels with partly blocked line of sight component, which are well modeled by the Rician shadowed (RS) fading channel. In this paper, by the usage of Kummer transformation, a simplified representation of the RS fading channel with integral fading parameter is given. It is a finite series representation involving only exponential function and low order polynomials. This allows engineers not only the closed-form expressions for exact performance analysis over RS fading channel, but also the insights on the system design tactics.

The spectrum allocation for cognitive radio sensor networks (CRSNs) has received considerable research attention under the assumption that the spectrum environment is static. However, in practice, the spectrum environment varies over time due to primary user/secondary user (PU/SU) activity and mobility, resulting in time-varied spectrum resources. This paper studies resource allocation for chunk-based multi-carrier CRSNs with time-varied spectrum resources. We present a novel opportunistic capacity model through a continuous time semi-Markov chain (CTSMC) to describe the time-varied spectrum resources of chunks and, based on this, a joint power and chunk allocation model by considering the opportunistically available capacity of chunks is proposed. To reduce the computational complexity, we split this model into two sub-problems and solve them via the Lagrangian dual method. Simulation results illustrate that the proposed opportunistic capacity-based resource allocation algorithm can achieve better performance compared with traditional algorithms when the spectrum environment is time-varied.

In an orthogonal frequency division multiplexing (OFDM) communication system, the reduction of peak-to-mean envelope power ratio (PMEPR) is one of crucial issues. It is all known that in an OFDM system, Golay complementary sequence (CS) pairs result in lowest upper bound 2 of PMEPR. Hence, this letter focuses on constructions of 16-QAM Golay CS sets. The proposed two constructions can produce the required sequences with arbitrary lengths, including lots of unknown ones in the existing references, if there exist the quaternary Golay CS sets of such lengths, and the PMEPRs of the Golay CS pairs from both are at most 2. As a consequence, the resultant sequences by this letter can be used as the inputs of using non-radix-2 inverse fast Fourier transform (IFFT) in the time domain OFDM signals.

The special geometric layout of actual engineering project requires the tag to be placed in a special metal cavity, which severely blocks the propagation of the electromagnetic (EM) field from the reader to tag. To guarantee the effective communication between the reader and tag, an innovative semicircular spiral antenna that works on 13.56 MHz with an effective working distance up to 100 mm has been developed to realize noncontact synchronous transmission of power and data from the reader to tag. By using the finite element method, the key features of this innovative semicircular spiral antenna, and its design and optimization processes have been presented in detail.

In context of Machine Type Communication (MTC) applications, network has to face increased load as well as possible surges of MTC traffic due to massive concurrent data and signaling transmission, in which case the interarrival time distribution of MTC devices may follow Beta distribution. In this paper, we model the network with MTC applications as a Beta/M/1 queue model. By deducing the moment generation function's analytical expression of Beta distributions with integral shape parameters, the full performance analysis of Beta/M/1 model is presented. The conclusions drawn from numerical analysis can be used as a preliminary guide to appropriately choose the model for different MTC application scenarios and promptly judge the effectiveness of the chosen model.

In this letter, we present a family of 16-QAM periodic complementary sequences (PCSs), including three constructions. Our basic idea is to transform the known quaternary PCSs/GCSs (Golay complementary sequences) into the required ones. In order to guarantee that such transformation of every construction is successful, the own sufficient conditions of three constructions are derived, respectively. Our methods can provide quite rich 16-QAM periodic PCSs, whose main parameters up to period 50 and number 12 of sub-sequences are given in Table 1, from a large number of available quaternary PCSs/GCSs, which can potentially satisfy the requirements of communication systems making use of 16-QAM constellation.

This letter investigates the construction methods of perfect 8-QAM+ sequences, which relate to one of three open problems proposed by Boztas and Parampalli in 2010, and two constructions that transform the known perfect ternary sequences (PTSs) into the required sequences are presented. The resultant sequences and the employed sequences have the same period, or the former's length is twice as long as the latter's, depending on the differently proposed methods. In addition, the simulation results by a computer show that energy efficiency of the proposed sequences in Construction 2 is higher than that of the employed PTSs. Incidentally, one of our constructions can also produce a family of almost perfect 8-QAM+ sequences with only two nonzero nontrivial autocorrelation values.

Blind source separation (BSS) based on time-frequency distributions (TFDs) exploits the underlying diagonal or off-diagonal structure of TFD matrices to separate the source signals. In this paper, we propose a new signal-independent kernel which is defined in both the time-lag and the Doppler-lag domain and satisfies most of the desirable properties of a TFD. The main objective of this research is to achieve the high resolution and the maximum cross-term reduction with the preferable diagonal or off-diagonal structure of TFD matrices in BSS applications. Moreover, a BSS approach is developed which includes first whitening mixed signals, then constructing a set of TFD matrices using the proposed TFD and the Hough transform, finally a joint diagonalization of a combined set of TFD matrices to estimate the mixing matrix and the source signals. By use of the techniques proposed in this paper, the improved performance of BSS of nonstationary signals has been achieved.

SUMMARY Based on quadriphase perfect sequences and their cyclical shift versions, three families of almost perfect 16-QAM sequences are presented. When one of two time shifts chosen equals half a period of quadriphase sequence employed and another is zero, two of the proposed three sequence families possess the property that their out-of-phase autocorrelation function values vanish except one. At the same time, to the other time shifts, the nontrivial autocorrelation function values in three families are zero except two or four. In addition, two classes of periodic complementary sequence (PCS) pairs over the 16-QAM constellation, whose autocorrelation is similar to the one of conventional PCS pairs, are constructed as

The main limitation to the accuracy of the detection of a bridge deflection using laser-based optical solutions is atmospheric turbulence because of the laser beam propagation in ground proximity. The multi-beam method is presented to increase the stability of bridge deflection measurement. It is based on the use of a four-beam optical system and a subpixel resolution algorithm for the measurement of the deflection of a laser beam that propagates through the system. To obtain accurate results, different algorithms for measuring the position of the deflected beam in different optical systems are tested and compared. Based on this comparison, the four-beam method based on the macropixels iteration centroid and four-beam optical system is selected, and an accuracy of 0.16 pixels is obtained by the determination of the beam position in our setup. The proposed method is adopted to detect the bridge deflection and an accuracy of 0.01 mm is gained when the scintillation index Cn2 is 3×10−4 m−2/3.

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user's QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user's tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.

This paper systematically proposed a multi-population agent co-genetic algorithm with double chain-like agent structure (MPATCGA) to solve the problem of the low optimization precision and long optimization time of simple genetic algorithm in terms of two coding strategy. This algorithm adopted multi-population parallel searching mode, close chain-like agent structure, cycle chain-like agent structure, dynamic neighborhood competition, and improved crossover strategy to realize parallel optimization, and has the characteristics of high optimization precision and short optimization time. Besides, the size of each sub-population is adaptive. The characteristic is very competitive when dealing with imbalanced workload. In order to verify the optimization precision of this algorithm with binary coding, some popular benchmark test functions were used for comparing this algorithm and a popular agent genetic algorithm (MAGA). The experimental results show that MPATCGA has higher optimization precision and shorter optimization time than MAGA. Besides, in order to show the optimization performance of MPATCGA with real coding, the authors used it for feature selection problems as optimization algorithm and compared it with some other well-known GAs. The experimental results show that MPATCGA has higher optimization precision (feature selection precision). In order to show the performance of the adaptability of size of sub-populations, MPATCGA with sub-populations with same size and MPATCGA with sub-populations with different size are compared. The experimental results show that when the workload on different sub-populations becomes not same, the adaptability will adaptively change the size of different sub-population to obtain precision as high as possible.

Directional wavelet can effectively capture the directional dependence in images. However, the computational complexity is high. Based on the image statistics estimated by the structure tensor, a novel directional lifting image coder locally adapting the filtering directions to image content is presented. Before performing wavelet transform (WT), the proposed algorithm detects all the image blocks in a given image to decide whether the block is homogenous or not. For homogeneous block, the conventional 2-D discrete WT is used. This will considerably reduce the computational complexity and the number of bits needed to code the directional information. On the other hand, heterogeneous block is decomposed using directional lifting wavelet transform, which can effectively capture the directional dependence in the selected image and improve the coding gain of the image coder. Experimental results have shown that, compared to some existing methods, the proposed scheme has a better performance in terms of peak signal to noise ratio (PSNR) and subjective quality.

The high demand for multimedia applications in environmental monitoring, invasion detection, and disaster aid has led to the rise of wireless sensor network (WSN). With the increase of reliability and diversity of information streams, the higher requirements on throughput and quality of service (QoS) have been put forward in data transmission between two sensor nodes. However, lower spectral efficiency becomes a bottleneck in non-line-of-sight (NLOS) transmission of WSN. This paper proposes a novel nondata-aided error vector magnitude based adaptive modulation (NDA-EVM-AM) to solve the problem. NDA-EVM is considered as a new metric to evaluate the quality of NLOS link for adaptive modulation in WSN. By modeling the NLOS scenario as the η − μ fading channel, a closed-form expression for the NDA-EVM of multilevel quadrature amplitude modulation (MQAM) signals over the η − μ fading channel is derived, and the relationship between SER and NDA-EVM is also formulated. Based on these results, NDA-EVM state machine is designed for adaptation strategy. The algorithmic complexity of NDA-EVM-AM is analyzed and the outage capacity of NDA-EVM-AM in an NLOS scenario is also given. The performances of NDA-EVM-AM are compared by simulation, and the results show that NDA-EVM-AM is an effective technique to be used in the NLOS scenarios of WSN. This technique can accurately reflect the channel variations and efficiently adjust modulation order to better match the channel conditions, hence, obtaining better performance in average spectral efficiency.

To smooth out speckle noise and preserve edge information in noisy images, a novel algorithm called speckle reduction by adaptive window anisotropic diffusion is proposed. Based on the image's structure, the proposed method can adaptively modulate its window size and orientation. This adaptive window method can calculate the instantaneous coefficient of variation for the edge area with more accuracy than a fixed window method. Furthermore, a novel method for finding the diffusion coefficient is presented. The experimental results show that compared with existing methods, the performance of the proposed method is satisfactory in terms of both speckle suppression and preservation of image details.

To fit the limited volume and power consumption of the passive radio frequency transmission system of the electronic time fuze, an improved coded mark inversion (CMI) is proposed in this letter. From the performance analysis, the energy transmission efficiency of this encoding method is at least 50% higher than that of CMI and NRZ. Finally, the experiment results show that by adopting this improved CMI, the change of DC voltage through magnetic coupling is lower than 0.2 V when the accuracy of data transmission is above 99.5%.

Distortion-product otoacoustic emissions (DPOAEs) are sound energy generated by healthy inner ears when stimulated by two tones. Since DPOAEs are physiologically related with the functional status of the inner ear, they have been widely used as a clinical tool in hearing screening and diagnoses. Currently, almost all DPOAEs recording systems use pure tones as the stimuli and can test only one frequency at a time, resulting in low efficiency and insufficient resolution. In this study, conventional pure tones were replaced by swept tones with time-varying frequencies to overcome the limitation of current DPOAEs measurements. A tracking filter with dynamic center frequencies was proposed to extract the swept-tone DPOAEs from recorded signals with stimulus artifacts and background noises. The results of this study showed that the dynamic tracking filter had great performance in effectively extracting the swept-tone DPOAEs under different noise conditions for both the simulation and experimental data. The spectrogram of the extracted swept-tone DPOAEs could provide useful information to examine the functional status of the inner ear and to identify the detailed frequency regions of the hearing loss. These preliminary findings suggested that the swept-tone DPOAEs might be useful for developing a more efficient and accurate tool for hearing loss screening in the clinic.

To address the drawbacks of continuous partial differential equations, a diffusion method based on spectral graph theory and random walk with restart kernel is proposed, which uses non-subsampled contourlet transform to capture the geometric feature of image. Specifically, a new graph weighting function is constructed based on the geometric feature. Moreover, a second-order random walk with restart kernel was generated. The derivation shows that the proposed method is equivalent to the denoising methods based on partial differential equations. The simulation results demonstrate that the proposed method can effectively reduce Gaussian noise and preserve image edge with superior performance compared with other graph-based partial differential equation methods.