JournalTOCs

IEEE Transactions on Broadcasting
Journal Prestige (SJR): 0.941

Citation Impact (citeScore): 5
Number of Followers: 11

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-9316
Published by IEEE

[228 journals]

IEEE Transactions on Broadcasting
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  Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
IEEE Transactions on Broadcasting information for authors
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  Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
An Improved SIC-Based Detection Scheme for Non-Uniform Constellations in
ATSC 3.0 MIMO
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  Authors: Hyeongseok Kim;Jeongchang Kim;Sung-Ik Park;Namho Hur;
  Pages: 286 - 294
  Abstract: This paper presents an alternative approach to real-valued signal representation and proposes an improved successive interference cancellation (SIC)-based detection scheme using the alternative signal representation for non-uniform constellations (NUCs) in Advanced Television Systems Committee (ATSC) 3.0. Since I/Q polarization interleaving in ATSC 3.0 multiple-input multiple-output (MIMO) precoding performs a non-linear operation, it makes it difficult to use conventional suboptimal detection schemes based on interference cancellation. Therefore, the alternative signal representation is designed to easily apply various suboptimal detection schemes. Further, to obtain more robustness and lower complexity, a suboptimal detection scheme based on the alternative signal representation and interference cancellation with QR decomposition is proposed. The proposed detection scheme exploits the structural properties of NUCs and jointly detects the real and imaginary parts as a block. In addition, by considering one or more candidate symbols in the interference cancellation for the proposed detection scheme, the performance and the complexity are trade-offs according to the number of the considering candidate symbols. Simulation results show that the proposed detection scheme with a slight increase of the complexity significantly outperforms a linear detection under fixed and mobile channels.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
Machine Learning-Based 5G RAN Slicing for Broadcasting Services
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  Authors: Junsheng Mu;Xiaojun Jing;Yangying Zhang;Yi Gong;Ronghui Zhang;Fangpei Zhang;
  Pages: 295 - 304
  Abstract: Along with the commercialization of evolved multimedia broadcast multicast services (eMBMS), the number of mobile broadcasting users is growing notably. Previous works reveal that the accuracy of mobile channel estimation will significantly impact the quality of broadcasting services. Motivated by this fact, we apply machine learning (ML) to the fifth-generation Radio Access Network (5G RAN) slicing in this paper for the estimation and the prediction of the channel status in mobile scenarios. More specifically, a cascaded convolutional neural network (CNN)-long short term memory network (LSTM) architecture is developed to achieve channel estimation for mobile broadcasting users. The energy efficiency of the base station (BS) is modeled mathematically, and the sub-optimal solution is achieved by deep Q-Network (DQN) based on the available channel status. Finally, we present the simulation results to justify the performance of our proposed schemes.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
Sliding Window Decoding for QC-SC-LDPC Codes Under the Constraint of
Implementation Complexity
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  Authors: Zhitong He;Kewu Peng;Jian Song;Yushu Zhang;
  Pages: 305 - 316
  Abstract: Sliding window decoding has been employed as the decoding scheme of quasi-cyclic spatially-coupled low-density parity-check (QC-SC-LDPC) codes, with the decoding latency and complexity independent of the coupling length but proportional to the window size. The window size was empirically chosen at least three times the constraint length in previous works, which results in the preference of QC-SC-LDPC codes with small constraint length, to reduce the decoding latency and complexity in practical systems. However, the code design freedom and the decoder throughput are limited for these QC-SC-LDPC codes. In this paper, the optimal window size under the constraint of practical decoding complexity is analyzed employing multi-edge-type density evolution (MET-DE). It can be verified from the MET-DE analytical result that the optimal window size could achieve less than twice the constraint length for several edge spreading patterns, which largely loose this restriction in practical code design. Furthermore, it could be observed that besides the constraint length, the specific structure of the edge spreading pattern could affect the optimal window size as well, and thus the MET-DE analytical method for the optimal window size could effectively guide the design of QC-SC-LDPC codes in practical systems. Then an improved sliding window decoding scheme is proposed, including the optimal choice of window size and a parity-check based early termination scheme. Finally, the performance and robustness of the proposed sliding window decoding scheme for QC-SC-LDPC codes are demonstrated via simulation, with the decoding complexity at most twice as that of the conventional LDPC coded schemes.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
Direct-Link Interference Cancellation Design for Backscatter
Communications Over Ambient DVB Signals
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  Authors: Wenbo Guo;Hongzhi Zhao;Changqing Song;Shihai Shao;Youxi Tang;
  Pages: 317 - 330
  Abstract: Ambient backscatter (AB) communication enables the backscatter devices to modulate and transmit data by reflecting surrounding digital video broadcasting (DVB) signals, and has emerged as a promising solution to connect low-power and small-sized devices in Internet of Things (IoT). Unfortunately, the AB receiver may suffer from the strong direct-link interference (DLI) transmitted from the ambient DVB station, making it difficult to decode the backscattered signal (BS) directly. In this paper, to tackle this issue, we propose a DLI cancellation method for AB communications over ambient DVB signals. First, a general signal processing operation for DLI cancellation at the AB receiver is designed, where neither special design on waveform nor cooperation between the ambient DVB station and the backscatter transceiver is required. Then, by minimizing the residual reception power after DLI cancellation, a three-layer parameter searching algorithm is proposed to separate the BS from the ambient DVB signal, which is of low implementation complexity. Simulation results show that when the DLI-to-BS ratio (ISR) is greater than 30 dB, the proposed DLI cancellation method can effectively suppress the DLI at the AB receiver, and the demodulation and capacity performance of the ambient DVB transmission and the backscatter transmission are barely deteriorated, as compared with the scenarios of original DVB transmission without BS and pure backscatter transmission without DLI. In addition, there is a trade-off between the convergence time and the interference cancellation ratio (ICR) performance of the proposed DLI cancellation scheme.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
mmWave Indoor Channel Measurement Campaign for 5G New Radio Indoor
Broadcasting
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  Authors: Hequn Zhang;Yue Zhang;John Cosmas;Nawar Jawad;Wei Li;Robert Muller;Tao Jiang;
  Pages: 331 - 344
  Abstract: Due to the great demand of throughput and reliability for multimedia applications in Fifth Generation (5G) networks, many broadcasting systems adopt the Millimeter Wave (mmWave) technology to address the lack of the spectrum resources. As one of 5G-PPP projects, Internet of Radio Light (IoRL) project adopts 40GHz mmWave band to support a high-speed and stable Ultra-High-Definition (UHD) television broadcasting service in the indoor environment. Because of the high frequency property, mmWave bands usually suffers from the high path loss and the penetration loss. Thus, in order to overcome these issues, directional antennas are employed to provide additional power gain while increasing transmission distance. However, the mmWave with directional antennas brings additional problems, such as limited transmission angle and more multipath effects. Therefore, in this paper, for better understanding of impact factors on the signal quality and transmission coverage of the directional 40GHz mmWave band in the indoor environment, a measurement campaign is introduced in detail and the channel characteristics are measured and analysed in varying cases. The mainly concerned characteristics are path loss, shadow fading, average Power Delay Profile (PDP), Root-Mean-Square (RMS) delay spread, arrival rate and coherence bandwidth. All Measured characteristic values are summarised in three tables at the end of this paper. Besides of these, as a reference of channel analysis and a metric of signal quality and effective coverage, Error Vector Magnitude (EVM) of received signal in each case is measured and discussed. Moreover, a simulation is performed based on a statistical channel model to validate the measured results.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
Learning for Unconstrained Space-Time Video Super-Resolution
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  Authors: Zhihao Shi;Xiaohong Liu;Chengqi Li;Linhui Dai;Jun Chen;Timothy N. Davidson;Jiying Zhao;
  Pages: 345 - 358
  Abstract: Recent years have seen considerable research activities devoted to video enhancement that simultaneously increases temporal frame rate and spatial resolution. However, the existing methods either fail to explore the intrinsic relationship between temporal and spatial information or lack flexibility in the choice of final temporal/spatial resolution. In this work, we propose an unconstrained space-time video super-resolution network, which can effectively exploit space-time correlation to boost performance. Moreover, it has complete freedom in adjusting the temporal frame rate and spatial resolution through the use of the optical flow technique and a generalized pixelshuffle operation. Our extensive experiments demonstrate that the proposed method not only outperforms the state-of-the-art, but also requires far fewer parameters and less running time.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
Cross-Frame Transformer-Based Spatio-Temporal Video Super-Resolution
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  Authors: Wenhui Zhang;Mingliang Zhou;Cheng Ji;Xiubao Sui;Junqi Bai;
  Pages: 359 - 369
  Abstract: In this paper, we explore the spatio-temporal video super-resolution task, which aims to generate a high-resolution and high-frame-rate video from an existing video with low resolution and frame rate. First, we propose an end-to-end spatio-temporal video super-resolution network chiefly composed of cross-frame transformers instead of traditional convolutions. Especially, the cross-frame transformer module divides the input feature sequence into query, key, value matrixes, and then obtains the maximum similarity and similarity coefficient matrixes between neighboring and current feature maps through self-attention processing operations. Next, we propose a multi-level residual reconstruction module, which could make full use of the maximum similarity and similarity coefficient matrixes obtained by the cross-frame transformer, to reconstruct the high resolution and frame rate results from coarse to fine. Qualitative and quantitative evaluation results show that our method offers better performance and requires fewer training parameters compared with the existing two-stage network.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
A Global Appearance and Local Coding Distortion Based Fusion Framework for
CNN Based Filtering in Video Coding
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  Authors: Jian Yue;Yanbo Gao;Shuai Li;Hui Yuan;Frédéric Dufaux;
  Pages: 370 - 382
  Abstract: In-loop filtering is used in video coding to process the reconstructed frame in order to remove blocking artifacts. With the development of convolutional neural networks (CNNs), CNNs have been explored for in-loop filtering considering it can be treated as an image de-noising task. However, in addition to being a distorted image, the reconstructed frame is also obtained by a fixed line of block based encoding operations in video coding. It carries coding-unit based coding distortion of some similar characteristics. Therefore, in this paper, we address the filtering problem from two aspects, (i) global appearance restoration for disrupted texture and (ii) local coding distortion restoration caused by fixed pipeline of coding. Accordingly, a three-stream global appearance and local coding distortion based fusion network is developed with a high-level global feature stream, a high-level local feature stream and a low-level local feature stream. Ablation study is conducted to validate the necessity of different features, demonstrating that the global features and local features can complement each other in filtering and achieve better performance when combined. To the best of our knowledge, we are the first one that clearly characterizes the video filtering process from the above global appearance and local coding distortion restoration aspects with experimental verification, providing a clear pathway to developing filter techniques. Experimental results demonstrate that the proposed method significantly outperforms the existing single-frame based methods and achieves 13.5%, 11.3%, 11.7% BD-Rate saving on average for AI, LDP and RA configurations, respectively, compared with the HEVC reference software.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
High Efficiency Intra Video Coding Based on Data-Driven Transform
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  Authors: Na Li;Yun Zhang;C.-C. Jay Kuo;
  Pages: 383 - 396
  Abstract: In this work, we propose a high efficiency intra video coding based on data-driven transform, which is able to learn the source distributions of intra prediction residuals and improve the subsequent transform coding efficiency. Firstly, we model learning based transform design as an optimization problem of maximizing energy compaction or decorrelation. A data-driven Subspace Approximation with Adjusted Bias (Saab) transform is analyzed and compared with the mainstream Discrete Cosine Transform (DCT) on their energy compaction and decorrelation capabilities. Secondly, we propose a Saab transform based intra video coding framework with offline Saab transform learning. Meanwhile, intra mode dependent Saab transform is developed. Then, Rate-Distortion (RD) gain of Saab transform based intra video coding is theoretically and experimentally analyzed in detail. Finally, three strategies that apply the Saab transform to intra video coding are developed to improve the coding efficiency. Experimental results demonstrate that the proposed $8times 8$ Saab transform based intra coding can achieve Bjønteggard Delta Bit Rate (BDBR) from −1.19% to −10.00% and −3.07% on average as compared with the mainstream $8times 8$ DCT based intra coding. In case of variable size transform unit setting, the proposed algorithm achieves BDBR from −0.17% to −6.09% and −1.80% on average, which outperform the DCT based and the neural network based schemes.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
Monocular Accommodation in the Light Field Imaging
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  Authors: Beom-Ryeol Lee;Hyoung Lee;Wookho Son;Sumio Yano;Jung-Young Son;Gwanghee Heo;Tetiana Venkel;
  Pages: 397 - 406
  Abstract: The presence of monocular depth sense is identified with a light field imaging system which can project up to 8 different view images simultaneously to a viewer’s each eye. The depth of field of subjects’ eyes increases further as the number of simultaneously projected images to subjects’ each eye increases more, though the increasing rate is somewhat different for different subjects. The diopter values exceed more than those of real object as the number exceeds more than six for the binocular viewing while it is eight for monocular viewing. The increasing rate of the diopter values for the binocular viewing is more than that for monocular viewing. These results assure that a natural viewing condition can be incorporated in light field imaging systems. These results are derived from 7 subjects under age 35, having eye sight greater than 1.0.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)
An Enhanced Pedestrian Dead Reckoning Aided With DTMB Signals
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  Authors: Xiaoyan Liu;Zhenhang Jiao;Liang Chen;Yinghua Pan;Xiangchen Lu;Yanlin Ruan;
  Pages: 407 - 413
  Abstract: Pedestrian Dead Reckoning (PDR) is a good alternative positioning method in Global Navigation Satellite Systems (GNSS)-challenged environments. It has the advantage in terms of infrastructure-independent, while the disadvantage is that, the estimated errors grow rapidly with time. The Digital Terrestrial Multimedia Broadcasting (DTMB) signals have strong transmission power, which contributes to better urban propagation and building penetration than GNSS signals. So, in this paper, an enhanced PDR algorithm aided with DTMB signals is proposed. In the study, a complete software-defined radio receiver is developed to estimate the Doppler speed and range information from DTMB signals. To reduce the accumulated errors of the PDR, the Extended Kalman Filter (EKF) algorithm is carried out to fuse the information of Doppler speed and ranging from the DTMB signals, as well as the information of walking speed and heading from the PDR. The results of the field tests showed that the 95% positioning error of the proposed algorithm is less than 3.94 m, while the PDR only is less than 9.19 m, which suggests the effectiveness of the proposed method to provide continuous positioning by fusing DTMB signals with PDR.
  PubDate: June 2022
  Issue No: Vol. 68, No. 2 (2022)