Si-based photonic materials and devices, including SiGe/Si quantum structures, SOI and InGaAs bonded on Si, PL of Si nanocrystals, SOI photonic crystal filter, Si based RCE (Resonant Cavity Enhanced) photodiodes, SOI TO (thermai-optical) switch matrix were investigated in Institute of Semiconductors, Chinese Academy of Sciences. The main results in recent years are presented in the paper. The mechanism of PL from Si NCs embedded in SiO2 matrix was studied, a greater contribution of the interface state recombination (PL peak in 850~900 nm) is associated with larger Si NCs and higher interface state density. Ge dots with density of order of 1011 cm-2 were obtained by UHV/CVD growth and 193 nm excimer laser annealing. SOI photonic crystal filter with resonant wavelength of 1598 nm and Q factor of 1140 was designed and made. Si based hybrid InGaAs RCE PD with η of 34.4% and FWHM of 27 nm were achieved by MOCVD growth and bonding technology between InGaAs epitaxial and Si wafers. A 1616 SOI optical switch matrix were designed and made. A new current driving circuit was used to improve the response speed of a 44 SOI rearrangeable nonblocking TO switch matrix, rising and falling time is 970 and 750 ns, respectively.

A thin high-doping layer was inserted in the uniform doped collector to extend the operational current before current gain and cut-off frequency roll-off. Two times higher collector current before onset of Kirk effect was obtained and the resulted John figure of merit was improved from 846 to 1008 V-GHz.

For AES 128 security level there are several natural choices for pairing-friendly elliptic curves. In particular, as we will explain, one might choose curves with k=9 or curves with k=12. The case k=9 has not been studied in the literature, and so it is not clear how efficiently pairings can be computed in that case. In this paper, we present efficient methods for the k=9 case, including generation of elliptic curves with the shorter Miller loop, the denominator elimination and speed up of the final exponentiation. Then we compare the performance of these choices. From the analysis, we conclude that for pairing-based cryptography at the AES 128 security level, the Barreto-Naehrig curves are the most efficient choice, and the performance of the case k=9 is comparable to the Barreto-Naehrig curves.

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.

To evaluate the radial eigenmode field distributions and the resonance wavelengths of axially symmetric pillbox resonator, a numerical method is described which is based on the FE-BPM expression in cylindrical coordinates. Under the weakly guiding approximation, we solve Fresnel equation and can get a fairly accurate result. By using effective index method, 3-D pillbox guiding structure is reduced to 2-D one which is then used for the analysis. One advantage of this method is that it is applicable for the axially symmetric optical waveguides with arbitrary index distribution. The validity of this method is checked by comparing the results of this method with those of the analytical ones. This method is applied for the evaluation of the coupling properties of a coupled structure consisting of a pillbox resonator and a curved waveguide placed outside the pillbox. This coupled structure has a good prospect to be used as optical wavelength filter. By varying the separation distance between the pillbox and the outer curved waveguide, the power transfer due to coupling is determined near the resonance wavelength 0.9 µm.

The Localization of distributed sources has attracted significant interest recently. There mainly are two types of localization methods which are able to estimate distributed source positions: two-step methods and direct localization methods. Unfortunately, both fail to exploit the location information and so suffer a loss in localization accuracy. By utilizing the information not used in the above, a direct localization method of multiple distributed sources is proposed in this paper that offers improved location accuracy. We construct a direct localization model of multiple distributed sources and develop a direct localization estimator with the theory of multiple signal classification. The distributed source positions are estimated via a three-dimensional grid search. We also provide Cramer-Rao Bound, computational complexity analysis and Monte Carlo simulations. The simulations demonstrate that the proposed method outperforms the localization methods above in terms of accuracy and resolution.

We present a novel scheme for digital steganography of point-sampled geometry in the spatial domain. Our algorithm is inspired by the concepts proposed by Cayre and Macq for 3D polygonal models. It employs a principal component analysis (PCA), resulting in a blind approach. We validate our scheme with various model complexities in terms of capacity, complexity, visibility, and security. This scheme is robust against translation, rotation, and scaling operations. It is fast and can achieve high data capacity with insignificant visual distortion in the stego models.

We present a novel, simple, efficient algorithm to generate random samples uniformly on the directional space of a cone. This algorithm has three advantages over the conventional non-uniform approach. First, to the best of our knowledge, this algorithm is original for uniformly sampling smaller areas of cones. Second, it is faster. Third, it always generates valid samples, which is not possible for the conventional approach.

We propose a novel approach based on wavelet decomposition for progressive full spectral rendering. In the fourth progressive stage, our method renders an image that is 95% similar to the final non-progressive approach but requires less than 70% of the execution time. The quality of the rendered image is visually plausible that is indistinguishable from that of the non-progressive method. Our approach is graceful, efficient, progressive, and flexible for full spectral rendering.

The flexibility of wireless communication makes it more and more widely used in industrial scenarios. To satisfy the strict real-time requirements of industry, various wireless methods especially based on the time division multiple access protocol have been introduced. In this work, we first conduct a mathematical analysis of the network model and the problem of minimum packet loss. Then, an optimal Real-time Scheduling algorithm based on Backtracking method (RSBT) for industrial wireless sensor networks is proposed; this yields a scheduling scheme that can achieve the lowest network packet loss rate. We also propose a suboptimal Real-time Scheduling algorithm based on Urgency and Concurrency (RSUC). Simulation results show that the proposed algorithms effectively reduce the rate of the network packet loss and the average response time of data flows. The real-time performance of the RSUC algorithm is close to optimal, which confirms the computation efficiency of the algorithm.

Modulated signal detection has been rapidly advancing in various wireless communication systems as it's a core technology of spectrum sensing. To address the non-Gaussian statistical of noise in radio channels, especially its pulse characteristics in the time/frequency domain, this paper proposes a method based on Information Geometric Difference Mapping (IGDM) to solve the signal detection problem under Alpha-stable distribution (α-stable) noise and improve performance under low Generalized Signal-to-Noise Ratio (GSNR). Scale Mixtures of Gaussians is used to approximate the probability density function (PDF) of signals and model the statistical moments of observed data. Drawing on the principles of information geometry, we map the PDF of different types of data into manifold space. Through the application of statistical moment models, the signal is projected as coordinate points within the manifold structure. We then design a dual-threshold mechanism based on the geometric mean and use Kullback-Leibler divergence (KLD) to measure the information distance between coordinates. Numerical simulations and experiments were conducted to prove the superiority of IGDM for detecting multiple modulated signals in non-Gaussian noise, the results show that IGDM has adaptability and effectiveness under extremely low GSNR.

The application of millimeter wave (mmWave) directional transmission technology in high-speed railway (HSR) scenarios helps to achieve the goal of multiple gigabit data rates with low latency. However, due to the high mobility of trains, the traditional initial access (IA) scheme with high time consumption is difficult to guarantee the effectiveness of the beam alignment. In addition, the high path loss at the coverage edge of the millimeter wave remote radio unit (mmW-RRU) will also bring great challenges to the stability of IA performance. Fortunately, the train trajectory in HSR scenarios is periodic and regular. Moreover, the cell-free network helps to improve the system coverage performance. Based on these observations, this paper proposes an efficient IA scheme based on location and history information in cell-free networks, where the train can flexibly select a set of mmW-RRUs according to the received signal quality. We specifically analyze the collaborative IA process based on the exhaustive search and based on location and history information, derive expressions for IA success probability and delay, and perform the numerical analysis. The results show that the proposed scheme can significantly reduce the IA delay and effectively improve the stability of IA success probability.

This paper puts forward the concept of cellular network location with less information which can overcome the weaknesses of the cellular location technology in practical applications. After a systematic introduction of less-information location model, this paper presents a location algorithm based on AGA (Adaptive Genetic Algorithm) and an optimized RBF (Radical Basis Function) neural network. The virtues of this algorithm are that it has high location accuracy, reduces the location measurement parameters and effectively enhances the robustness. The simulation results show that under the condition of less information, the optimized location algorithm can effectively solve the fuzzy points in the location model and satisfy the FCC's (Federal Communications Commission) requirements on location accuracy.

Since HEVC intra rate control has no prior information to rely on for coding, it is a difficult work to obtain the optimal λ for every coding tree unit (CTU). In this paper, a convolutional neural network (CNN) based intra rate control is proposed. Firstly, a CNN with two last output channels is used to predict the key parameters of the CTU R-λ curve. For well training the CNN, a combining loss function is built and the balance factor γ is explored to achieve the minimum loss result. Secondly, the initial CTU λ can be calculated by the predicted results of the CNN and the allocated bit per pixel (bpp). According to the rate distortion optimization (RDO) of a frame, a spatial equation is derived between the CTU λ and the frame λ. Lastly, The CTU clipping function is used to obtain the optimal CTU λ for the intra rate control. The experimental results show that the proposed algorithm improves the intra rate control performance significantly with a good rate control accuracy.

In this letter, we first present a new construction method for uncorrelated binary periodic Complementary sequence sets (CSS). Next, the uncorrelated periodic CSSs are used as pilot sequences for multiple-input multiple-output (MIMO) channel estimation. Later on, we propose a low-complexity periodic correlator. Finally, simulation results verify the optimality of pilot sequences for MIMO channel estimation.

Spectrum sharing effectively improves the spectrum usage by allowing secondary users (SUs) to dynamically and opportunistically share the licensed bands with primary users (PUs). The concept of cooperative spectrum sharing allows SUs to use portions of the PUs' radio resource for their own data transmission, under the condition that SUs help the PUs' transmission. The key issue with designing such a scheme is how to deal with the resource splitting of the network. In this paper we propose a relay-based cooperative spectrum sharing scheme in which the network consists of one PU and multiple SUs. The PU asks the SUs to relay its data in order to improve its energy efficiency, in return it rewards the SUs with a portion of its authorized spectrum. However each SU is only allowed to transmit its data via the rewarded channel at a power level proportional to the contribution it makes to the PU. Since energy cost is considered, the SUs must carefully determine their power level. This scheme forms a non-cooperative Stackelberg resource allocation game where the strategy of PU is the bandwidth it rewards and the strategy of each SU is power level of relay transmission. We first investigate the second stage of the sub-game which is addressed as power allocation game. We prove there exists an equilibrium in the power allocation game and provide a sufficient condition for the uniqueness of the equilibrium. We further prove a unique Stackelberg equilibrium exists in the resource allocation game. Distributed algorithms are proposed to help the users with incomplete information achieve the equilibrium point. Simulation results validate our analysis and show that our proposed scheme introduces significant utility improvement for both PU and SUs.

In CDMA system, the RAKE receiver is commonly used to attain diversity gain by taking advantage of the good correlation properties of the spreading codes. However, at low spreading gains the good correlation properties of the spreading codes are lost and the RAKE receiver performance is severely degraded by intersymbol interference (ISI) due to the interpath interference (IPI). In case of multi-code CDMA system, there are exist multi-code interference (MCI). In order to suppress ISI and MCI, a novel receiver based on soft-output viterbi algorithm (SOVA) equalization is proposed in this paper. The SOVA equalization is applied to symbol sequences after RAKE combining and MCI cancellation to effectively eliminate the ISI during transmission of high rate data in wideband DS-CDMA systems. Simulation results show that the proposed RAKE-SOVA receiver significantly outperform the traditional RAKE and RAKE-VA receivers.

In this letter, we propose a simple distributed space-frequency code with both timing errors and multiple carrier frequency offsets (CFO) in asynchronous cooperative communications. By employing both the Alamouti coding approach and the transmit repetition diversity technique, full diversity gain can be achieved by the fast symbol-wise maximum likelihood (ML) decoding at the destination node. Analysis and simulations demonstrate the effectiveness of the proposed method.

Routing is still a challenging issue for wireless sensor networks (WSNs), in particular for WSNs with a non-uniform deployment of nodes. This paper introduces a Node Aggregation Degree-aware Random Routing (NADRR) algorithm for non-uniform WSNs with the help of two new concepts, namely the Local Vertical Aggregation Degree (LVAD) and Local Horizontal Aggregation Degree (LHAD). Our basic idea is to first apply the LVAD and LHAD to determine one size-proper forwarding region (rather than a fixed-size one as in uniform node deployment case) for each node participating in routing, then select the next hop node from the size-proper forwarding region in a probabilistic way, considering both the residual energy and distribution of nodes. In this way, a good adaptability to the non-uniform deployment of nodes can be guaranteed by the new routing algorithm. Extensive simulation results show that in comparison with other classical geographic position based routing algorithms, such as GPSR, TPGF and CR, the proposed NADRR algorithm can result in lower node energy consumption, better balance of node energy consumption, higher routing success rate and longer network lifetime.

In [1], an algorithm based on phase variations of received pilot symbols was proposed to estimate one of the most important channel parameters, maximum Doppler shift, fd. However, AWGN (Additive white gauss noise) will cause large estimation error in some cases. In order to analyze the influence of noise, we extended the phase probability density function (pdf) in [1] to the scenario with both fading and AWGN, then the estimation error is characterized in closed-form expression. By this error expression, we found that power control will affect the estimator of [1] and we proposed a modification method based on SNR estimation to obtain accurate Doppler shift estimation in moderate low SNRs (signal-to-noise ratio). Simulation results show high accuracy in wide range of velocities and SNRs.