This paper presents the design and analysis of dual-band monolithic microwave integrated circuit (MMIC) switches, including a single pole double throw (SPDT) and a single pole four throw (SP4T). With a novel on-chip coupled-line (OCL) topology, the input signal can be switched into low- or high-band paths to create dual-band characteristics. By carefully selecting the electrical lengths of OCLs and device size for corresponding shunt-FETs, the operating frequencies for low- and high-bands can be determined. This brings about improved insertion loss (IL) and isolation (ISO) in a compact structure. With the proposed techniques, two switch prototypes have been designed and fabricated in a 0.25-$\mu $m GaN-on-SiC process for high-power capability. The SPDT consists of a low-band path and a high-band path. It achieves an average IL/ISO of 1.0/32 dB with the best input 1-dB compression points (IP1dB) of 37.2 dBm at a low-band of DC-15 GHz; and an average IL/ISO of 2.0/28.5 dB with the best IP1dB of 32.8 dBm at a high-band of 20-40 GHz, respectively. The return loss is better than 11 dB for each port. The SP4T achieves a fully integrated dual-band transmit/receive (T/R) switch with doubled low-/high-band paths. It shows an average IL/ISO of 2.26/27.5 dB with the best IP1dB of 31.2 dBm at a low-band of 5-15 GHz; and an average IL/ISO of 2.7/26.5 dB with the best IP1dB of 30 dBm at a high-band of 20-30 GHz have been achieved, respectively. Better than 11.3 dB return loss is obtained for each port. The chip sizes are$1.8\times 0.9$mm2 for the SPDT and$2.2\times 1.7$mm2 for the SP4T.

This article presents the design theory and implementation of a fully integrated coupled-line-based load-modulated balanced amplifier (CLLMBA) monolithic microwave integrated circuit (MMIC). To facilitate the design, a novel design method is proposed for the CLLMBA to precisely control the load modulation and output power back-off (OBO) level by arranging the current ratio among the control amplifier (CA) and balanced amplifiers (BAs). Moreover, to further expand the working bandwidth, the coupled-line couplers are adopted in the CLLMBA. Subsequently, the physical dimensions and operating conditions of the three sub-amplifiers are selected accurately based on load modulation analysis at the fundamental frequency. It leads to properly modulated impedances and cancels the output matching networks for sub-amplifiers. Besides, meandering lange couplers are adopted by double metal layers and air-bridges for a compact layout. To validate the proposed techniques, a CLLMBA prototype is implemented and fabricated in a commercial 0.25-$\mu $m GaN HEMT process with the die size of$3.1\times 2.3$mm2. The measurement result exhibits a 38.1-39.3 dBm saturated output power with a 45.8%-57.6% saturated drain efficiency (DE), and a 31.7%-42.3% DE at 10-dB OBO from 4 to 6 GHz. Furthermore, under a 100 MHz orthogonal frequency division multiplexing (OFDM) signal with 8.5 dB peak-to-average power ratio (PAPR), the average DE is 32.8%-40.6% and the adjacent channel leakage ratio (ACLR) after digital predistortion is better than −47.5 dBc.

The research on community question answering (CQA) has been paid increasing attention in recent years. In CQA, to reduce the number of unanswered questions and the time for askers to wait, it is very necessary to identify relevant experts or best answers for these questions. Generally, the experts' answers are more likely to be the best answers. Existing studies considered that user expertise is reflected by the voting scores of both answers and questions. However, voting scores of questions are not really related to user expertise. In this paper, we proposed a new probabilistic model to depict users' expertise based on answers and their descriptive ability based on questions. To exploit social information in CQA, the link analysis is also considered. Extensive experiments on the large Stack Overflow dataset demonstrate that our methods can achieve comparable or even better performance than the state-of-the-art models.

Social networking services are attracting increasing interest in the domain of community discovery. In social networks, the interactions among users are very frequent by sending emails, posting tweets, and sharing comments online, etc. Such networks usually include rich sentiment information, which can provide us with useful resources for identifying communities with different sentiment-topic distributions. Most conventional community discovery methods only consider the social links among users, which ignore the valuable content information. Recent studies have focused on community detection by integrating both links and content. However, most of these methods are not available for identifying sentiment-topic based communities. In this paper, we propose two novel community discovery models by combining social links, author based topics and sentiment information to identify communities with different sentiment-topic distributions. We evaluate our models on two real-world datasets, and the experimental results demonstrate the effectiveness of our proposed models.

Community question answering (CQA) sites provide us online platforms to post questions or answers. Generally, there are a great number of questions waiting to be answered by expert users. However, most of answerers are ordinary with just basic background knowledge in certain areas. To help askers to get their preferable answers, a set of possible expert users should be recommended. There have been some studies on the expert recommendation in CQA, the latest work models the user expertise under topics, where each topic is learnt based on the content and tags of questions and answers. Practically, such topics are too general, whereas question tags can be more informative and valuable than the topic of each question. In this paper, we study the user expertise under tags. Experimental analysis on a large data set from Stack Overflow demonstrates that our method performs better than the up-to-date method.

The paper presents a low complexity channel estimator based on windowed discrete Fourier transform (DFT) and scalar Wiener filter for orthogonal frequency division multiplexing (OFDM) mobile communications systems. In the method, a generalized Hanning window is applied to the channel frequency response observation vector in the frequency domain to reduce the spectral leakage, and a scalar Wiener filter is applied to the effective channel impulse response in the time domain to suppress the channel noise. Analysis results show that the proposed method's performance is close to the optimal minimum mean square error (MMSE) estimator and is much better than the direct DFT based estimator. Compared with the optimal MMSE estimator, however, the computation load of the proposed method can be significantly reduced because the IDFT/DFT transforms can be implemented with the fast algorithms IFFT/FFT.

Low-complexity windowed discrete Fourier transform (DFT)-based minimum mean square error (MMSE) channel estimators are proposed and analyzed for both the interpolation and noninterpolation cases for orthogonal frequency-division multiplexing (OFDM) mobile communications systems. In the proposed method, the frequency domain data windowing is used to reduce the aliasing errors for the interpolation case and get better noise filtering performance for the noninterpolation case. The time domain MMSE weighting is also used to suppress the channel noise for both cases. Moreover, the optimal generalized Hanning window shape is searched to minimize the channel estimation mean square error (MSE). Analysis and simulation results show that the proposed method performance is close to the optimal MMSE estimator and is much better than the direct DFT-based estimator for both cases. Compared with the optimal MMSE estimator, however, the computation load of the proposed method can be significantly reduced because the IDFT/DFT transforms can be implemented with the fast algorithms IFFT/FFT.

We present an improved channel estimation algorithm for orthogonal frequency-division multiplexing mobile communication systems using pilot subcarriers. This algorithm is based on a parametric channel model where the channel frequency response is estimated using an L-path channel model. In the algorithm, we employ the ESPRIT (estimation of signal parameters by rotational invariance techniques) method to do the initial multipath time delays acquisition and propose an interpath interference cancellation delay locked loop to track the channel multipath time delays. With the multipath time delays information, a minimum mean square error estimator is derived to estimate the channel frequency response. It is demonstrated that the use of the parametric channel model can effectively reduce the signal subspace dimension of the channel correlation matrix for the sparse multipath fading channels and, consequently, improve the channel estimation performance.

Orthogonal frequency division multiplexing (OFDM) is an effective modulation technique for high-rate and high-speed transmission over frequency selective fading channels. However, OFDM systems can be extremely sensitive and vulnerable to synchronization errors. In this paper, we present a scheme for performing timing recovery that includes symbol synchronization and sampling clock synchronization in OFDM systems. The scheme is based on pilot subcarriers. In the scheme, we use a path time delay estimation method to improve the accuracy of the correlation-based symbol synchronization methods, and use a delay-locked loop (DLL) to do the sampling clock synchronization. It is shown that by using this scheme, the mean square values of the symbol timing estimation error can be decreased by several orders of magnitude compared to the common correlation methods in both the AWGN and multipath fading channels. In addition, the scheme can track the symbol timing drift caused by the sampling clock frequency offsets.

In this paper, we present a delay-locked loop (DLL) technique for performing a combined symbol and sampling clock synchronization in orthogonal frequency division multiplexing (OFDM) systems. In addition, we propose a symbol timing acquisition algorithm for the DLL. It is shown that by using this combined scheme, we can achieve symbol timing recovery and sampling clock adjustment simultaneously. In particular, the symbol timing estimation error variance can be decreased by several orders of magnitude compared with the common correlation methods in both the AWGN and multipath fading channels.