We provide an overview of techniques for the photonic generation of arbitrary RF waveforms, particularly those suitable for impulse radio or multi-band ultrawideband (UWB)-over-fiber transmission, and chirped microwave waveforms, with an emphasis on microwave photonic filtering and optical spectral shaping followed by wavelength-to-time mapping. We discuss possibilities for integrating the various device and component technologies with silicon photonics.

This paper presents the design of an ad hoc two-way two-hop relay network using physical-layer network coding (PNC) in which multiple antennas are used at all nodes. In the considered network, the Alamouti's space-time block code (STBC) is used for transmission while linear detection is used for signal recovery. In order to facilitate linear estimation, we develop an equivalent multiuser STBC model for the proposed network and design the sum-and-difference matrix which allows convenient combination of the transmitted symbols from the end nodes. In addition, a simple relay selection method based on minimum mean square error (MSE) is proposed for performance improvement. Simulation results show that the proposed network achieves diversity order 2 while requiring only polynomial complexity. Moreover, it is possible to achieve significant bit error rate (BER) performance improvement when the proposed relay selection algorithm is used.

In this paper, a specified hardware architecture of the Fast Mode Decision (FMD) algorithms presented by our previous work is proposed. This architecture is designed as an embedded mode dispatch module. On the basis of this module, some unnecessary modes can be skipped or the mode decision process can be terminated in advanced. In order to maintain a higher compatibility, the FMD algorithms are unitedly designed as an unique module that can be easily embedded into a common video codec for H.265/HEVC. The input and output interfaces between the proposed module and other parts of the codec are designed based on simple but effective protocol. Hardware synthesis results on FPGA demonstrate that the proposed architecture achieves a maximum frequency of about 193 MHz with less than 1% of the total resources consumed. Moreover, the proposed module can improve the overall throughput.

To achieve more accurate measurements of the mobile station (MS) location, it is possible to integrate many kinds of measurements. In this paper we proposed several hybrid methods that utilized time of arrival (TOA) at seven base stations (BSs) and the angle of arrival (AOA) information at the serving BS to give location estimation of the MS in non-line-of-sight (NLOS) environments. Rather than applying the nonlinear circular lines of position (LOP), the proposed methods are easier by using linear LOP to determine the MS. In addition, the proposed methods can mitigate the NLOS effect, simply by applying the weighted sum of the intersections between different linear LOP and the AOA line, without requiring priori knowledge of NLOS error statistics. Simulation results show that the proposed methods can always yield superior performance in comparison with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) and the previous proposed methods employing circular LOP.

Recent studies on switching fabrics mainly focus on the switching schedule algorithms, which aim at improving the throughput (a key performance metric). However, the delay (another key performance metric) of switching fabrics cannot be well guaranteed. A good switching fabric should be endowed with the properties of high throughput, delay guarantee, low component complexity and high-speed multicast, which are difficult for conventional switching fabrics to achieve. This has fueled great interest in designing a new switching fabric that can support large-scale extension and high-speed multicast. Motivated by this, we reuse the self-routing Boolean concentrator network and embed a model of multicast packet copy separation in front to construct a load-balanced multicast switching fabric (LB-MSF) with delay guarantee. The first phase of LB-MSF is responsible for balancing the incoming traffic into uniform cells while the second phase is in charge of self-routing the cells to their final destinations. In order to improve the throughput, LB-MSF is combined with the merits of erasure codes against packet loss. Experiments and analyses verify that the proposed fabric is able to achieve high-speed multicast switching and suitable for building super large-scale switching fabric in Next Generation Network(NGN) with all the advantages mentioned above. Furthermore, a prototype of the proposed switch is developed on FPGA, and presents excellent performance.

The fifth generation (5G) mobile communication technologies are attracting a lot of attention in terms of accommodating the huge traffic expected in the future. Millimeter wave communications, which utilize wide frequency bands, are attracting attention for the realization of the high capacity required in the 5G era. In millimeter wave communications, beamforming with massive antennas is expected to play a very important role in compensating the large propagation loss of millimeter waves. Because massive beamforming yields narrow beams, the search for the optimal beam could have considerable impact on the system. In this paper, we propose a new beam search method that can reduce the load of beam search significantly while keeping beamforming gain almost the same as that of the conventional method. The proposed method consists of three stages with the creation of a set of candidate beams in the first stage, selection of an initial beam in the second stage, and refinement of the selected beam in the third stage. In the first stage, the created set of candidate beams contains beams of various widths instead of beams of a uniform width to reduce the number of candidate beams in the set. Here, we leverage the property of millimeter waves according to which the fluctuation of millimeter wave propagation loss is spatially and temporally small because of the fewer multipaths, and therefore, the propagation loss has strong correlation with the user location. By using the decreased set of candidate beams, the beam search time can be reduced in the second stage. Then the beam refinement can increase the beamforming gain to increase user throughput in the third stage. To confirm the effects of the proposed beam search method, we conduct system level simulations by using a propagation model for millimeter wave communications proposed by MiWEBA, which is an international project between Europe and Japan. The results show that the proposed beam search method can reduce the number of candidate beams, and can therefore shorten the beam search time by about 39% without any degradation in outage probability compared with a conventional method.

Object extraction and tracking in a video image is basic technology for many applications, such as video surveillance and robot vision. Many moving object extraction and tracking methods have been proposed. However, they fail when the scenes include illumination change or light reflection. For tracking the moving object robustly, we should consider not only the RGB values of input images but also the shape information of the objects. If the objects' shapes do not change suddenly, matching positions on the cost matrix of exclusive block matching are located nearly on a line. We propose a method for obtaining the correspondence of feature points by imposing a matching position constraint induced by the shape constancy. We demonstrate experimentally that the proposed method achieves robust tracking in various environments.

Blur is one of the most common distortion type and greatly impacts image quality. Most existing no-reference (NR) image blur metrics produce scores without a fixed range, so it is hard to judge the extent of blur directly. This letter presents a NR perceptual blur metric using Saliency Guided Gradient Similarity (SGGS), which produces blur scores with a fixed range of (0,1). A blurred image is first reblurred using a Gaussian low-pass filter, producing a heavily blurred image. With this reblurred image as reference, a local blur map is generated by computing the gradient similarity. Finally, visual saliency is employed in the pooling to adapt to the characteristics of the human visual system (HVS). The proposed metric features fixed range, fast computation and better consistency with the HVS. Experiments demonstrate its advantages.

The paper addresses a scheme of lightly supervised training of an acoustic model, which exploits a large amount of data with closed caption texts but not faithful transcripts. In the proposed scheme, a sequence of the closed caption text and that of the ASR hypothesis by the baseline system are aligned. Then, a set of dedicated classifiers is designed and trained to select the correct one among them or reject both. It is demonstrated that the classifiers can effectively filter the usable data for acoustic model training. The scheme realizes automatic training of the acoustic model with an increased amount of data. A significant improvement in the ASR accuracy is achieved from the baseline system and also in comparison with the conventional method of lightly supervised training based on simple matching.

This paper investigates the detection performance of an improved energy detector for a secondary user with spatially correlated multiple antennas. In an improved energy detector, an arbitrary positive power operation p replaces the squaring operation in a conventional energy detector, and the optimum value of p that gives the best detection performance may be different from 2. Firstly, for a given value of p, we derive closed-form expressions for the probability of detection and the probability of false alarm when antennas at the secondary user are exponentially correlated. We then find the optimum value of p for two different detection criteria-maximizing the probability of detection for a target probability of false alarm, and minimizing the probability of false alarm for a target probability of detection. We show that the optimum p is strongly dependent on system parameters like number of antennas, antenna correlation coefficient among multiple antennas, and average received signal-to-noise ratio (SNR). From results, we infer that, in low SNR regime, the effect of antenna correlation is less pronounced on the optimum p. Finally, we find the optimum values of p and threshold jointly that minimize the total error rate.

High dynamic range (HDR) images that include large differences in brightness levels are studied to address the lack of knowledge on the quality estimation method for real HDR images. For this, we earlier proposed a new metric, the independent signal-to-noise ratio (ISNR), using the independent pixel value as the signal instead of the peak value (PSNR). Next, we proposed the local peak signal-to-noise ratio (LPSNR), using the maximum value of neighboring pixels, as an improved version. However, these methods did not sufficiently consider human perception. To address this issue, here we proposed an objective estimation method that considers spatial frequency characteristics based on the actual brightness. In this method, the approximated function for human characteristics is calculated and used as a 2D filter on an FFT for spatial frequency weighting. In order to confirm the usefulness of this objective estimation method, we compared the results of the objective estimation with a subjective assessment. We used the organic EL display which has a perfect contrast ratio for the subjective assessment. The results of experiments showed that perceptual weighting improves the correlation between the SNR and MOS of the subjective assessment. It is recognized that the weighted LPSNR gives the best correlation.

A prompt rescue is a serious operation when a catastrophic disaster occurs. In an uncommunicable area where the existing communication systems are damaged, it is, however, difficult to collect SOS messages of victims. So far, we have proposed a smartphone application named SOSCast to collect SOS messages via device-to-device transmission in such an area. However, with the limitation of coverage area and battery consumption, it decreases the possibility of finding the victim due to the risk of losing the SOS messages. In this paper, thus, we propose an information-sharing cluster to virtually extend the communication coverage area and to secure the SOS messages by reducing the battery consumption. In the performance evaluation, compared with the original SOSCast, we showed that the proposed method can reduce battery consumption to secure the message through a prototype system and simulation experiments.

Aperture synthesis technology represents an effective approach to millimeter-wave radiometers for high-resolution observations. However, the application of synthetic aperture imaging radiometer (SAIR) is limited by its large number of antennas, receivers and correlators, which may increase noise and cause the image distortion. To solve those problems, this letter proposes a compressive regularization imaging algorithm, called CRIA, to reconstruct images accurately via combining the sparsity and the energy functional of target space. With randomly selected visibility samples, CRIA employs l1 norm to reconstruct the target brightness temperature and l2 norm to estimate the energy functional of it simultaneously. Comparisons with other algorithms show that CRIA provides higher quality target brightness temperature images at a lower data level.

The complexity of the graph isomorphism problem for trapezoid graphs has been open over a decade. This paper shows that the problem is GI-complete. More precisely, we show that the graph isomorphism problem is GI-complete for comparability graphs of partially ordered sets with interval dimension 2 and height 3. In contrast, the problem is known to be solvable in polynomial time for comparability graphs of partially ordered sets with interval dimension at most 2 and height at most 2.

A re-configurable wavelength de-multiplexer for wave-length-division-multiplexed (WDM) radio-over-fiber (RoF) systems, which is specially designed for delivering frequency-modulated continuous-wave (FM-CW) signals, is newly developed. The principle and characteristics of the developed de-multiplexer are described in detail. Then the de-multiplexing performances of 4-channel WDM 32-GHz-band, 8-channel WDM 48-GHz-band, and 5-channel WDM 96-GHz-band FM-CW RoF signals are evaluated with the de-multiplexer.

We propose a joint channel, power and rate allocation scheme to minimize the weighted group outage probability of the secondary users (SUs) in a downlink cognitive radio (CR) multicast network coexisting with a primary network, subject to the service outage constraint as well as the interference power constraint and the transmit power constraint. It is validated by simulation results that, compared to the existing schemes, the proposed scheme achieves lower group outage probability.

In this study, we propose a two-step approach to evaluate electromagnetic interference (EMI) with a wearable vital signal sensor. The two-step approach combines a quasi-static electromagnetic (EM) field analysis and an electric circuit analysis, and is applied to the EMI evaluation at frequencies below 1 MHz for our developed wearable electrocardiogram (ECG) to demonstrate its usefulness. The quasi-static EM field analysis gives the common mode voltage coupled from the incident EM field at the ECG sensing electrodes, and the electric circuit analysis quantifies a differential mode voltage at the differential amplifier output of the ECG detection circuit. The differential mode voltage has been shown to come from a conversion from the common mode voltage due to an imbalance between the contact impedances of the two sensing electrodes. When the contact impedance is resistive, the induced differential mode voltage increases with frequency up to 100kHz, and keeps constant after 100kHz, i.e., exhibits a high pass filter characteristic. While when the contact impedance is capacitive, the differential mode voltage exhibits a band pass filter characteristic with the maximum at frequency of around 150kHz. The differential voltage may achieve nearly 1V at the differential amplifier output for an imbalance of 30% under 10V/m plane-wave incident electric field, and completely mask the ECG signal. It is essential to reduce the imbalance as much as possible so as to prevent a significant interference voltage in the amplified ECG signal.

This paper investigates an interference mitigation technique for dynamic time division duplex (TDD) based frequency-separated small cell networks in future long term evolution advanced (LTE-A) based wireless access systems. In dynamic TDD, cross-link interference, i.e. evolved node B (eNB)-eNB interference and user equipment (UE)-UE interference, also occur, and eNB-eNB interference in particular significantly degrades the uplink (UL) transmission performance. In order to alleviate the impacts of eNB-eNB interference and to obtain high traffic adaptation gain, we investigate a transmit power control (TPC) based interference mitigation (IM) scheme. In TPC-IM, time-domain subframes are divided into two subframe sets according to whether the cross-link interference can occur or not, and different TPC parameters are applied depending on the type of subframe. To improve of UL signal to interference plus noise power ratio (SINR) in the subframe set with the potential to occur eNB-eNB interference, there are two approaches of UL power boosting and downlink (DL) power reduction. We investigate the adequate combination of these two approaches to avoid an impact of DL performance degradation and increase of UE power consumption. Moreover, we further investigate a combined scheme of the TPC-IM and a cell clustering interference mitigation (CCIM) to avoid the significantly strong cross-link interference from the neighbouring cells. Computer simulation confirms that the proposed TPC-IM scheme can achieve 4.4% and 26.2% gain in the average DL and UL throughputs, respectively, compared to the case without any IM schemes on dynamic TDD. Moreover, when the CCIM is applied to the TPC-IM scheme, 11.6% and 40.3% gain can be achieved in the average DL and UL throughputs, respectively.

Due to the fact that natural images are approximately sparse in Discrete Cosine Transform (DCT) or wavelet basis, the Compressive Sensing (CS) can be employed to decode both the host image and watermark with zero error, despite not knowing the host image. In this paper, Limited-Random Sequence (LRS) matrix is utilized to implement the blind CS detection, which benefits from zero error and lower complexity. The performance in Bit Error Rate (BER) and error-free detection probability confirms the validity and efficiency of the proposed scheme.