Most applications can adapt their coding techniques and sending rates according to the network congestion and the resource needed can be provided at the beginning of the transmission. So traditional Differentiated Services (DiffServ) model is too rigid to them. In this paper, we are seeking a balance between the relative DiffServ and the absolute DiffServ and propose a new Diffserv model, a relative Differentiated Service model with admission control, which suits the adaptive application. By providing the proportional differentiated services in core routers and loss-rate based CAC control in edge routers, we can make both the network and the users adaptive: the network is adaptive to the traffic load and the users is adaptive to the network congestion. This model is promising to the elastic but unpredictable traffic, such as IP telephony or other multimedia applications.

This paper proposes a parallel coupled microstrip bandpass filter (BPF) with ring Electromagnetic Bandgap (EBG) cells on the middle layer for spurious suppression. The ring EBG cells of the middle layer add a good stopband-rejection mode to the second harmonics of the parallel coupled microstrip BPF with suppression of over -50 dB, without affecting the center frequency and insertion loss of the original designed BPF. The design of ring EBG cells is presented and verified by the experimented results.

In this paper, an inverse S-shaped slotted ground structure (S-SGS) is proposed and analyzed. The S-SGS generates dual attenuation poles that can be easily controlled by its structure parameters. The equivalent circuit of the S-SGS consists of lumped elements that can be extracted from the measured S parameters. Moreover, several S-SGS cells are applied to form a miniaturized lowpass filter (LPF), which has a smaller area and a wider stopband in comparison to previous works.

The similarity of words extracted from the rich text relation network is the main way to calculate the semantic similarity. Complex relational information and text content in Wikipedia website, Community Question Answering and social network, provide abundant corpus for semantic similarity calculation. However, most typical research only focused on single relationship. In this paper, we propose a semantic similarity calculation model which integrates multiple relational information, and map multiple relationship to the same semantic space through learning representing matrix and semantic matrix to improve the accuracy of semantic similarity calculation. In experiments, we confirm that the semantic calculation method which integrates many kinds of relationships can improve the accuracy of semantic calculation, compared with other semantic calculation methods.

This investigation proposes a novel dual-mode patch bandpass filter (BPF) that uses defect ground structure (DGS) to suppress spurious response. The proposed dual-mode patch BPF has exhibits a wide stopband characteristic owing to that uses the bandgap resonant characteristic of DGS in the harmonic frequency of the dual-mode patch BPF. The novel proposed filter demonstrates the frequency characteristics with center frequency f0 = 2.2 GHz, 3-dB bandwidth (FBW) of 8% and wider stopband from 2.6 to 6 GHz at the level of -35 dB. The experimental and simulated results agree.

In this paper, a compact ultra-wideband bandpass filter (UWB-BPF) using pseudo-interdigital stepped-impedance resonators (PIDT-SIRs) is designed and implemented on a commercial printed circuit board (PCB) of RT/Duroid 5880 substrate. The first two resonant modes of the SIR are coupled together and they are applied to create a wide passband. The proposed filter at center frequency f0 of 7.1 GHz has very good measured characteristics including the bandwidth of 3.68-10.46 GHz (3-dB fractional bandwidth of 95%), low insertion loss of -0.50.4 dB, sharp rejection due to two transmission zeros in the passband edge created by the inter-stage coupling. Experimental results of the fabricated filter show a good agreement with the predicted results.

This paper proposes a novel dual-mode ring bandpass filter (BPF) using defect ground structure (DGS). The proposed filter provides wide stopband characteristic resulted from the bandgap characteristic of DGS for suppressing spurious response of the dual-mode ring BPF. The H shaped DGS cell is modeled as a parallel LC resonator and the equivalent circuit parameters are extracted. The relationship between bandgap characteristic and design parameters of DGS dimension is discussed and the bandgap characteristic of DGS on the filter performance is also investigated. The novel proposed filter has the frequency characteristics with a central frequency f0 = 7.7 GHz, a 3-dB bandwidth of 4.5% and wider stopband from 9 to 15.5 GHz at the level of -35 GHz. Measured results of experimental filter has good agreement with the theoretical simulation results.

This investigation proposes a modified equivalent circuit of single complementary split-ring resonator (CSRR) in planar transmission media and a dual-mode ring bandpass filter (BPF) that uses periodic CSRRs to suppress the spurious response. The proposed modified equivalent circuit consists of lumped elements that can be easily extracted from the measured S parameters. The proposed dual-mode ring BPF has exhibits a wide stopband characteristic owing to the bandgap resonant characteristic of CSRRs in the harmonic frequency of the dual-mode ring BPF. Good agreement with EM simulation and measurement is demonstrated.

In this letter, we propose a semantic guided infrared and visible image fusion method, which can train a network to fuse different semantic objects with different fusion weights according to their own characteristics. First, we design the appropriate fusion weights for each semantic object instead of the whole image. Second, we employ the semantic segmentation technology to obtain the semantic region of each object, and generate special weight maps for the infrared and visible image via pre-designed fusion weights. Third, we feed the weight maps into the loss function to guide the image fusion process. The trained fusion network can generate fused images with better visual effect and more comprehensive scene representation. Moreover, we can enhance the modal features of various semantic objects, benefiting subsequent tasks and applications. Experiment results demonstrate that our method outperforms the state-of-the-art in terms of both visual effect and quantitative metrics.

In this paper, we propose a novel censor-based cooperative spectrum sensing strategy, called adaptive energy-efficient sensing (AES), in which both sequential sensing and censoring report mechanism are employed, aiming to reduce the sensing energy consumption of secondary user relays (SRs). In AES, an anchor secondary user (SU) requires cooperative sensing only when it does not detect the presence of PU by itself, and the cooperative SR adopts decision censoring report only if the sensing result differs from its previous one. We derive the generalized-form expressions false alarm and detection probabilities over Rayleigh fading channels for AES. The sensing energy consumption is also analyzed. Then, we study sensing energy overhead minimization problem and show that the sensing time allocation can be optimized to minimize the miss detection probability and sensing energy overhead. Finally, numerical results show that the proposed strategy can remarkably reduce the sensing energy consumption while only slightly degrading the detection performance compared with traditional scheme.

This letter investigates transmit optimization in multi-user multi-input multi-output (MIMO) wiretap channels. In particular, we address the transmit covariance optimization for an artificial-noise (AN)-aided secrecy rate maximization (SRM) when subject to individual harvested energy and average transmit power. Owing to the inefficiency of the conventional interior-point solvers in handling our formulated SRM problem, a custom-designed algorithm based on penalty function (PF) and projected gradient (PG) is proposed, which results in semi-closed form solutions. The proposed algorithm achieves about two orders of magnitude reduction of running time with nearly the same performance comparing to the existing interior-point solvers. In addition, the proposed algorithm can be extended to other power-limited transmit design problems. Simulation results demonstrate the excellent performance and high efficiency of the algorithm.

The paper reports a compact and high performance dual-band bandpass filter (BPF) using two types of dual-mode resonators. The dual mode cross shaped resonator and the three dual mode ring resonators in the designed dual-band BPF are excited to control the first and second passband, respectively. It is shown that the designed and fabricated dual-band BPF has narrow bandwidths and very sharp attenuation rate due to the existence of the transmission zeros. The frequency response of the designed dual-band BPF shows good agreement between the simulations and experiments.

The potential for using millimeter-wave (mmWave) frequencies in future 5G wireless cellular communication systems has motivated the study of large-scale antenna arrays to achieve highly directional beamforming. However, the conventional fully digital beamforming (DBF) methods which require one radio frequency (RF) chain per antenna element are not viable for large-scale antenna arrays due to the high cost and large power consumption of high frequency RF chain components. Hybrid precoding can significantly reduce the number of required RF chains and relieve the huge power consumption in mmWave massive multiple-input multiple-output (MIMO) systems, thus attracting much interests from academic and industry. In this paper, we consider the downlink communication of a massive multiuser MIMO (MU-MIMO) system in the mmWave channel, and propose a low complexity hybrid block diagonal geometric mean decomposition (BD-GMD) scheme. More specially, a joint transmit-receive (Tx-Rx) analog beamforming with large-scale arrays is proposed to improve channel gain, and then a low-dimensional BD-GMD approach is implemented at the equivalent baseband channel to mitigate the inter-user interference and equalize different data streams of each user. With the help of successive interference cancellation (SIC) at the receiver, we can decompose each user's MIMO channel into parallel sub-channels with identical higher SNRs/SINRs, thus equal-rate coding can be applied across the sub-channels of each user. Finally, simulation results verify that the proposed hybrid BD-GMD precoding scheme outperforms existing conventional fully digital and hybrid precoding schemes and is able to achieve much better BER performance.

The investigation presents a low cost and low insertion loss X-band dual mode bandpass filter (BPF) based on inexpensive commercial FR4 substrate. The proposed filter at a central frequency f0 of 11.3 GHz has high filter performance filter with a fractional bandwidth of 14%, the insertion loss of -2.7 dB, and two transmission zeros. The designed procedures are presented in this letter and the fabricated filter verifies the proposed designed concept.

Non-Terrestrial-Network (NTN) can provide seamless and ubiquitous connectivity of massive devices. Thus, the feeder links between satellites and gateways need to provide essentially high data transmission rates. In this paper, we focus on a typical high-capacity scenario, i.e., LEO-IoT, to find an optimal satellite selection schema to maximize the capacity of feeder links. The proposed schema is able to obtain the optimal mapping among all the satellites and gateways. By comparing with maximum service time algorithm, the proposed schema can construct a more balanced and reasonable connection pattern to improve the efficiency of the gateways. Such an advantage will become more significant as the number of satellites increases.

Visual quality evaluation is crucially important for various video and image processing systems. Traditionally, subjective image quality assessment (IQA) given by the judgments of people can be perfectly consistent with human visual system (HVS). However, subjective IQA metrics are cumbersome and easily affected by experimental environment. These problems further limits its applications of evaluating massive pictures. Therefore, objective IQA metrics are desired which can be incorporated into machines and automatically evaluate image quality. Effective objective IQA methods should predict accurate quality in accord with the subjective evaluation. Motivated by observations that HVS is highly adapted to extract irregularity information of textures in a scene, we introduce multifractal formalism into an image quality assessment scheme in this paper. Based on multifractal analysis, statistical complexity features of nature images are extracted robustly. Then a novel framework for image quality assessment is further proposed by quantifying the discrepancies between multifractal spectrums of images. A total of 982 images are used to validate the proposed algorithm, including five type of distortions: JPEG2000 compression, JPEG compression, white noise, Gaussian blur, and Fast Fading. Experimental results demonstrate that the proposed metric is highly effective for evaluating perceived image quality and it outperforms many state-of-the-art methods.

Similar to algebraic decoding schemes, the (23, 12, 7) Golay code can be decoded by applying the step-by-step decoding algorithm. In this work, a modified step-by-step algorithm for decoding the Golay code is presented. Logical analysis yielded a simple rule for directly determining whether a bit in the received word is correct. The computational complexity can be reduced significantly using this scheme.

The continuous advances in sensing and positioning technologies have resulted in a dramatic increase in popularity of Location-Based Services (LBS). Nevertheless, the LBS can lead to user privacy breach due to sharing location information with potentially malicious services. A high degree of location privacy preservation for LBS is extremely required. In this paper, a clustering K-anonymity scheme for location privacy preservation (namely CK) is proposed. The CK scheme does not rely on a trusted third party to anonymize the location information of users. In CK scheme, the whole area that all the users reside is divided into clusters recursively in order to get cloaked area. The exact location information of the user is replaced by the cloaked spatial temporal boundary (STB) including K users. The user can adjust the resolution of location information with spatial or temporal constraints to meet his personalized privacy requirement. The experimental results show that CK can provide stringent privacy guarantees, strong robustness and high QoS (Quality of Service).

This paper proposes a sampling strategy for bandlimited graph signals over perturbed graph, in which we assume the edge between any pair of the nodes may be deleted randomly. Considering the mismatch between the true graph and the presumed graph, we derive the mean square error (MSE) of the reconstructed bandlimited graph signals. To minimize the MSE, we propose a greedy-based algorithm to obtain the optimal sampling set. Furthermore, we use Neumann series to avoid the pseudo-inverse computing. An efficient algorithm with low-complexity is thus proposed. Finally, numerical results show the superiority of our proposed algorithms over the other existing algorithms.

A low-complexity step-by-step decoding algorithm for t-error-correcting binary Bose-Chaudhuri-Hocquenghem (BCH) codes is proposed. Using logical analysis, we obtained a simple rule which can directly determine whether a bit in the received word is correct. The computational complexity of this decoder is less than the conventional step-by-step decoding algorithm, since it reduces at least half of the matrix computations and the most complex element in the conventional step-by-step decoder is the "matrix-computing" element.