This paper presents two approaches for reducing the peak power in precoded multi-input multi-output (MIMO) systems with space division multiplexing (SDM). First, we present a peak power aware linear precoding scheme for MIMO-SDM single carrier systems, where the precoder is designed to restrict per-antenna transmit power below a permissible level while mitigating the performance degradation caused by per-antenna power restriction. Second, we present an analytical method to represent bit error rate (BER) performance of maximum ratio combining (MRC) precoded massive MIMO OFDM systems with adaptive peak cancellation, where peak amplitude is canceled below a given threshold to reduce peak-to-average power ratio (PAPR). With this method, we clarify the impact of adaptive peak cancellation on approximated BER of MRC-precoded massive MIMO OFDM with an arbitrary number of the transmit antennas and users. Numerical results prove that our proposed approaches are effective in restricting the peak power at each antenna while mitigating performance degradation in BER performance of the precoded MIMO-SDM systems.
We consider applying Lloyd-Max quantization to a distributed collaborative interference canceller (DCIC) with digital higher-frequency radio (HR) forwarding in order to effectively use the HR-band resources. A destination terminal (DT) achieves higher throughput and earns higher diversity order by gathering the other received signals forwarded from surrounding relay stations (RSs) with HR band even if it mounts fewer receive antennas than the transmit antennas at the base station (BS). However enormous HR-band resources are required to forward the received signals which are digitally encoded at the surrounding RSs with sufficiently low latency. We need to develop techniques to effectively use the HR-band resources. The simulation results show that Lloyd-Max quantization achieves higher data reliability as compared to the uniform quantization for MIMO-OFDM signal with high peak-to-average power ratio (PAPR). Also increasing transmit antennas with the same spatial diversity order is less sensitive to the required number of quantization bits.
In this paper, the transmission scheme that combines LDM(Layered Division Multiplexing) with BST-OFDM (Band Segmented Transmission - Orthogonal Frequency Division Multiplexing) is proposed for the Japanese next-generation DTTB (Digital Terrestrial Television Broadcasting). The proposed LDM-BST-OFDM scheme provides a more effective frequency utilization and improvement of the performance in the stream for fixed reception. In addition, power boost of partial reception band for LDM-BST-OFDM is also studied in this paper. The performance of the proposed scheme is evaluated by computer simulations where the effectiveness of proposed scheme for fixed reception is shown.
Although LDM-BST-OFDM scheme improves the performance, dedicated receivers that can demodulate LDM multiplexed symbols are required. Therefore, LDM-BST-OFDM scheme which can decode the stream for fixed reception even if LDM multiplexed symbols are not demodulated by using conventional fixed receivers is proposed. In this paper, ”LDM-BST-OFDM using frequency diversity scheme” and ”LDM-BST-OFDM using extended parity in lower layer of LDM” is proposed. The reception characteristics of the proposed scheme is evaluated by computer simulations.
Studies on live program production systems using Internet Protocol (IP) communications technology at broadcast stations are progressing. Remote production is attracting attention as a new style of live program production using IP. In remote production, broadcast stations and venues are connected by IP network, and programs are remotely produced from the broadcast station side. To enable remote production, it is necessary for both the venue and the broadcast station to share, in real-time, high-quality video taken at the venue. It is also required to bidirectionally communicate signals other than video/audio that are necessary for program production, such as control and communication line signals. To realize 8K remote production, we have developed a lightweight compressed 8K over IP transmission device. In this work, we describe its functions and report experimental results on multi-channel audio remote production with 8K video and real-time 8K camera control on a 1000-km IP network.
We propose a disparity compensation framework for efficient light-field coding. We have proposed a novel lightfield coding scheme of approximating a light field with the sum of weighted binary patterns. This coding scheme achieves comparable performance to the modern video coding standards H.265/HEVC and enables a dramatically simple decoding process, but its computational complexity for encoding is quite high. We have also proposed a progressive coding scheme that progressively encodes the target light field with a small number of weighted binary patterns in a step-by-step manner. The progressive scheme remarkably mitigates the computational complexity, but its rate-distortion performance is degraded. To address the above problems, we design a disparity compensation framework, which can be applied to the existing progressive coding, to improve the rate-distortion performance while keeping feasible computational complexity. Experimental results demonstrate that the proposed method improves the rate-distortion performance of the progressive coding without a computational complexity explosion.
The market size of online video advertising is expanding rapidly along with the spread of smartphones and social media. In this study, we estimate advertising effectiveness in the natural environment using online data collection and the remote measurement of webcam facial expressions and physiological responses. We collected 4, 108 videos of the faces of 411 Japanese people who were watching the video advertisement in their natural environment via the Internet. Facial expression and physiological responses such as heart rate and gaze were remotely measured by analyzing facial videos. We found that the accuracies of ad liking and purchase intent prediction are better when various acquired features are combined and machine learning is used than when only single-mode features are used. In addition, we aim to improve prediction accuracy by clustering the personality of the subjects and designing an estimation model for each personality.
We present a system for reenacting a person's face driven by speech. Given a video sequence with the corresponding audio track of a person giving a speech and another audio track containing different speech from the same person, we reconstruct a 3D mesh of the face in each frame of the video sequence to match the speech in the second audio track. Audio features are extracted from such two audio tracks. Assuming that the appearance of the mouth is highly correlated to these speech features, we extract the mouth region of the face's 3D mesh from the video sequence when speech features from the second audio track are close to those of the video's audio track. While retaining temporal consistency, these extracted mouth regions then replace the original mouth regions in the video sequence, synthesizing a reenactment video where the person seemingly gives the speech from the second audio track. Our system, coined S2TH (speech to talking head), does not require any special hardware to capture the 3D geometry of faces but uses the state-of-the-art method for facial geometry regression. We visually and subjectively demonstrate reenactment quality.