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This paper, aiming at the problem of the traditional RD rate control model and inaccurate bit allocation of multi-view high-efficiency video coding (MV-HEVC), proposes a rate control algorithm for MV-HEVC based on the similarity analysis of the views and timedomain complexity of the frame activity. First, the algorithm core uses the similarity analysis of the views to reasonably perform bit allocation among the views. Then, the frame layer and basic unit layer bit allocation and rate control are performed based on the frame rate, target buffer capacity, actual buffer size, and active time domain complexity of the frame. The experimental results show that compared with the fixed bit allocation algorithm applied to views, the proposed method not only effectively controls the bit rate of multiview video coding with a rate control accuracy of over 99% but also improves the PSNR by 0.38dB. [ABSTRACT FROM AUTHOR]

Millimeter-wave (mmWave) communication and network densification hold great promise for achieving high-rate communication in next-generation wireless networks. Cloud radio access network (CRAN), in which low-complexity remote radio heads (RRHs) coordinated by a central unit (CU) are deployed to serve users in a distributed manner, is a cost-effective solution to achieve network densification. However, when operating over a large bandwidth in the mmWave frequencies, the digital fronthaul links in a CRAN would be easily saturated by the large amount of sampled and quantized signals to be transferred between the RRHs and the CU. To tackle this challenge, we propose in this paper a new architecture for the mmWave-based CRAN with advanced lens antenna arrays at the RRHs. Due to the energy focusing property, the lens antenna arrays are effective in exploiting the angular sparsity of mmWave channels, and thus help in substantially reducing the fronthaul rate and simplifying the signal processing at the multi-antenna RRHs and the CU, even when the channels are frequency-selective. We consider the uplink transmission in a mmWave CRAN with lens antenna arrays and propose a low-complexity quantization bit allocation scheme for multiple antennas at each RRH to meet the given fronthaul rate constraint. Furthermore, we propose a channel estimation technique that exploits the energy focusing property of the lens array and can be implemented at the CU with low complexity. Finally, we compare the proposed mmWave CRAN using lens antenna arrays with a conventional CRAN using uniform planar arrays at the RRHs, and show that the proposed design achieves significant throughput gains, yet with much lower complexity. [ABSTRACT FROM AUTHOR]

This paper describes a 4K/60p high efficiency video coding (HEVC, the latest coding standard) real-time encoding system with high quality high dynamic range (HDR) color representations. The HDR technology provides attractive video contents with a wider dynamic range of luminance, which can make shadows and brighter details appear clearly without any blown out highlights or blocked up shadows. We propose a new rate control method for HDR video coding. The method consists of two algorithms for improving perceptual quality by reducing degradation of HDR-specific color artifacts. The first one, adaptive block size and prediction mode decision, is conducted to suppress perceptual degradation due to prediction error in high chroma areas. The second, local quantization parameter control, is carried out to improve the visual quality with appropriate bit allocation in low chroma areas. The method was implemented in an HEVC real-time encoding system and its performance was assessed by measuring the color difference metrics by 3.86% at the most degraded frame, while peak signal-to-noise ratio remained almost the same. The subjective quality of the decoded HDR images was improved by reducing color artifacts. [ABSTRACT FROM AUTHOR]

We study a two-user multiple-input single-output Gaussian interference channel with limited rate feedback and transmitter cooperation. Each receiver quantizes the channel state information of the direct and cross channels, and sends the codebook indices back to the transmitters through two sum-rate-limited feedback channels. The quantization errors reduce the beamforming gain from the direct transmitter, and cause interference leakage from the cross transmitter. Under an assumption of high signal-to-noise ratio, we first approximate the average transmission rate of each link, and use the sum rate to find the optimal transmit power and corresponding feedback bit allocation. We show that the maximum sum throughput is achieved using full transmit power, and the achievable sum rate under limited feedback is bounded above by a constant. We then extend the results to the case where secrecy is desired. In contrast to the first problem, increasing the transmit power beyond a certain point decreases the secrecy performance. Additionally, we analyze the asymptotic behavior of the solutions when the total feedback bandwidth and the number of transmit antennas grow large. We derive all results in closed form. Simulations validate the theoretical analysis and demonstrate the significant performance gains that result from the use of optimal transmit power control and intelligent feedback bit allocation. [ABSTRACT FROM AUTHOR]

In this paper, we propose and experimentally demonstrate a switching multiple input and multiple output (MIMO) system combining with adaptive orthogonal frequency division multiplexing (OFDM) modulation for high-speed indoor visible light communications. The adaptive OFDM modulation, which is realized by power and bit allocation on OFDM subchannels, is utilized to achieve the maximum channel capacity under a given target bit error rate (BER). Meanwhile, the MIMO mode switches between spatial multiplexing and transmit diversity adapting to the channel correlation, where the modulation order solved by adaptive OFDM modulation is chosen as the switching criterion. Experimental results validate data rates improvement over the pure spatial multiplexing and the pure transmit diversity system, where BERs are all below the 7% preforward error correction (pre-FEC) threshold of 3.8 × 10−3 in experiments. [ABSTRACT FROM AUTHOR]

Rate control in scalable video coding (SVC) is a very challenging problem because of the inter-layer prediction structure, which makes developing an efficient rate-control algorithm complex and difficult. Little prior work is available for joint temporal-quality (T-Q) scalability considering the rate-distortion (R-D) dependence among the temporal and quality layers. However, most of the rate-control algorithms in SVC suffer from high computational complexity, growing significantly with the number of layers. In this paper, a single-pass joint temporal-quality rate-control algorithm is presented for H.264/SVC. In this algorithm, by analyzing the R-D dependence of joint T-Q scalability, Cauchy distribution-based rate-quantization, and distortion-quantization models, a set of empirical values are first derived to estimate the initial values of the R-D model parameters for the joint temporal and quality layers. Then, a novel prediction mechanism to update these model parameters is proposed to allocate the bit budgets efficiently among the temporal and quality layers, and hence to improve the performance of the proposed algorithm. Experimental results show that the proposed algorithm achieves better coding efficiency with low computational complexity compared with two other benchmark rate-control algorithms. [ABSTRACT FROM AUTHOR]

The quality of a 3D video display depends on virtual view synthesis process which is affected by the bit allocation criterion. The performance of a bit allocation algorithm is dependent on various encoding parameters like quantization parameter, motion vector, mode selection, and so on. Rate-distortion optimization (RDO) is used to efficiently allocate bits with minimum distortion. In 3D video, rate-distortion (RD) property of synthesized view is used to assign bits between texture video and depth map. Existing literature on bit allocation methods use mean square error (MSE) as distortion metric which is not suitable for measuring perceptual quality. In this paper, we propose structural similarity (SSIM)-based joint bit allocation scheme to enhance visual quality of 3D video. Perceptual quality of a synthesized view depends on texture and depth map quality. Thus, SSIM-based RDO is performed on both texture and depth map where SSIM is used as distortion metric in mode decision and motion estimation. SSIM-based distortion model for synthesized view is determined experimentally. As SSIM cannot be related to quantization step, SSIM-MSE relation is used to convert distortion model in terms of MSE. The Lagrange multiplier method is used to solve the bit allocation problem. The proposed algorithm is implemented using 3DV-ATM as well as HEVC. RD curves show reduction in bitrate with an improvement in SSIM of synthesized view. [ABSTRACT FROM AUTHOR]

Visual saliency is used to guide the coding tree unit (CTU)-level bit allocation process in high-efficiency video coding (HEVC) to improve the visual quality. At first, a saliency detection algorithm is proposed. With the detected saliency map, the distortion of each CTU is weighted by the corresponding saliency, so that the distortion of the salient areas (SAs) is more critical. Then, the optimal bit allocation problem constrained by the picture-level target bits and minimum weighted distortion is built. Numerical method is used to solve the bit allocation problem. Finally, bits reallocation and the rate distortion optimization parameters clipping methods are presented to tackle the bits error accumulation problem. Experiment results show that quality gaining in SAs is up to 0.8658 dB and the gaining of saliency weighted peak signal-to-noise ratio is up to 1.0318 dB. ©2018 SPIE and IS&T [DOI: 10.1117/1 .JEI.27.4.043009] [ABSTRACT FROM AUTHOR]

Bit starvation resulted from inefficient rate control of 3D video coding deteriorates visual quality of synthesized views. Most region based rate control schemes allocate higher bitrate to regions of interest (ROIs), but bits may be still consumed by early coded units. This paper avoids reducing coding bits in high-cost regions of 3D-HEVC. Instead of ROIs that are determined by humans, high-cost regions sensitive to bit starvation are detected. Region-level bit allocation is achieved by curve fitting of coding statistics, and recursive Taylor expansion (RTE) based bit allocation is adopted to optimally estimates the target bitrate and the QP related λ of LCUs in each region. Based on retained earnings in economics, bits are reserved for LCUs that are sensitive to distortions. Experimental results show that the proposed scheme outperforms both the R-λ model and RTE model in bitrate accuracy with similar R-D performance. [ABSTRACT FROM AUTHOR]

Capturing a scene using multiple cameras from different angles is expected to provide the necessary interactivity in the 3-D space to satisfy end-users’ demands for observing objects and actions from different angles and depths. Existing multiview video coding (MVC) technologies face tradeoff among rate-distortion performance, random access frame delay, i.e., interactivity, and computational time. To address above mentioned tradeoffs, a novel cuboid MVC strategy is proposed with 3-D frame referencing structure to improve interactivity and computational time, an additional reference frame to improve rate-distortion performance for occluded areas, and visual attention-based bit allocation to provide better perceptual video quality. The experimental results reveal that the proposed scheme provides better interactivity, reduced computational time, and better perceptual quality compared to the 3D-HEVC implementation, HTM 15.0. [ABSTRACT FROM AUTHOR]

Image compression leads to minimize the storage-requirement of an image by reducing the size of the image. This paper presents a bit allocation strategy based on psychovisual threshold in image compression considering a similar idea of audio coding. In the audio coding, a dynamic bit allocation to each signal is related to the concept of variable block coding and bit allocation is performed on either a short block or long block of sample signals. Similarity, in our technique, more bits are assigned to a local block with visually-significant low frequency order, and fewer, with visually-insignificant high frequency order. This paper presents a bit allocation strategy based on psychovisual threshold in image compression. A psychovisual threshold is developed by minimizing the visual impact on the image quality degradation in image frequency coding. This paper investigates the error generated by the discrete cosine transform and sets the maximum acceptable error as a psychovisual threshold. The average reconstruction error per pixel on frequency order is utilized to prescribe a set of bit allocations which provide a significant improvement on the quality of image reconstruction at relatively low bit rates. The experimental results show that our dynamic bit-allocation technique in image compression manages to overcome artifact images in the image output. The proposed bit allocation strategy improves the quality of image reconstruction by about 20% compared to JPEG compression. This bit allocation strategy is designed to replace the traditional role of the quantization process in image compression. [ABSTRACT FROM AUTHOR]

In recent days, the allocation of resources in a wireless communication system is one of the demanding and crucial task. Multi input multi output (MIMO)-Orthogonal frequency division multiplexing is the widely used communication system, in which scheduling the resource to the appropriate user equipment (UE) is quite a challenging process. To overcome this a different scheduling mechanisms are proposed in the traditional works for efficient resource allocation. But, it lacks with some limitations such as, increased error rate, inefficient allocation, increased load at tower, and increased interference. Thus, this paper objects to introduce a new optimization based scheduling mechanism, namely, Joint local shortest scheduling (JLSS) for a successful MIMO communication. Initially, the Rayleigh channel initialization and estimation processes are performed after creating the Cellular radio network with different number of users. Then, the features of the channel are extracted by implementing a beamforming feature extraction technique. Here, a Multi-channel bacterial foraging optimization algorithm (MC-BFOA) is implemented for selecting the most suitable channel for communication, due to its increased efficiency. Finally, the JLSS is employed to scheduling the resource to the user equipment (UE), in which three different mechanisms such as Primary channel bit allocation, Secondary channel bit allocation, and Extra channel bit allocation are used. Based on the priority level, the resource is allocated with the use of these mechanisms. During experimentation, the scheduling results of existing and proposed techniques are evaluated by employing different parameters. [ABSTRACT FROM AUTHOR]

Rate control typically involves two steps: bit allocation and bitrate control. The bit allocation step can be implemented in various fashions depending on how many levels of allocation are desired and whether or not an optimal rate–distortion (R-D) performance is pursued. The bitrate control step has a simple aim in achieving the target bitrate as precisely as possible. In our recent research, we have developed a \lambda -domain rate control algorithm that is capable of controlling the bitrate precisely for High Efficiency Video Coding (HEVC). The initial research showed that the bitrate control in the \lambda -domain can be more precise than the conventional schemes. However, the simple bit allocation scheme adopted in this initial research is unable to achieve an optimal R-D performance reflecting the inherent R-D characteristics governed by the video content. In order to achieve an optimal R-D performance, the bit allocation algorithms need to be developed taking into account the video content of a given sequence. The key issue in deriving the video-content-guided optimal bit allocation algorithm is to build a suitable R-D model to characterize the R-D behavior of the video content. In this paper, to complement the R- \lambda model developed in our initial work, a D- \lambda model is properly constructed to complete a comprehensive framework of \lambda -domain R-D analysis. Based on this comprehensive \lambda -domain R-D analysis framework, a suite of optimal bit allocation algorithms are developed. In particular, we design both picture-level and basic-unit-level bit allocation algorithms based on the fundamental R-D optimization theory to take full advantage of the content-guided principles. The proposed algorithms are implemented in HEVC reference software, and the experimental results demonstrate that they can achieve an obvious R-D performance improvement with a smaller bitrate control error. The proposed bit allocation algorithms have already been adopted by the Joint Collaborative Team on Video Coding and integrated into the HEVC reference software. [ABSTRACT FROM PUBLISHER]

For High Efficiency Video Coding (HEVC), the R– $\lambda $ scheme is the latest rate control (RC) scheme, which investigates the relationships among allocated bits, the slope of rate-distortion (R-D) curve $\lambda $ , and quantization parameter. However, we argue that bit allocation in the existing R– $\lambda $ scheme is not optimal. In this paper, we therefore propose an optimal bit allocation (OBA) scheme for coding tree unit level RC in HEVC. Specifically, to achieve the OBA, we first develop an optimization formulation with a novel R-D estimation, instead of the existing R– $\lambda $ estimation. Unfortunately, it is intractable to obtain a closed-form solution to the optimization formulation. We thus propose a recursive Taylor expansion (RTE) method to iteratively solve the formulation. As a result, an approximate closed-form solution can be obtained, thus achieving OBA and bit reallocation. Both theoretical and numerical analyses show the fast convergence speed and little computational time of the proposed RTE method. Therefore, our OBA scheme can be achieved at little encoding complexity cost. Finally, the experimental results validate the effectiveness of our scheme in three aspects: R-D performance, RC accuracy, and robustness over dynamic scene changes. [ABSTRACT FROM AUTHOR]

Scalable video coding (SVC) is a coding paradigm that allows once-encoded video content to be used in diverse scenarios. SVC-coded videos can be transmitted and rendered at specified bitrates according to network bandwidth and end device requirements. In this paper, an adaptive bit allocation algorithm is proposed for the emerging scalable High Efficiency Video Coding (SHVC) standard. The bit budget at the group-of-pictures level is allocated according to buffer occupancy. Picture complexity, measured using the predicted mean absolute difference (MAD), buffer occupancy, and hierarchical level, is proposed for regulating the bitrate at the picture level. The MAD of the current picture is predicted using a novel mean prediction error (MPE) model, which is obtained from the advanced motion vector prediction, and the test zone search specified in SHVC and the associated reference software of SHVC. Moreover, MPE is used to determine the number of assigned bits at the coding-tree-unit level. The bit budget of each level is incorporated with the $R-\lambda $ model for computing the required quantization parameter. Experimental results reveal that the proposed method achieves accurate bitrates with enhanced and consistent visual quality and more satisfactorily controls buffer occupancy compared with the state-of-the-art approaches reported in the literature. [ABSTRACT FROM PUBLISHER]

In the multi-view video plus depth 3D video coding, texture image and depth map are coded jointly. The texture image is utilized for displaying and synthesizing the virtual view as reference image. The depth map provides the scene geometry information and is utilized to synthesize the virtual view at the terminal through Depth-Image Based Rendering technique. The distortion of the compressed texture image and depth map will be propagated to the synthesized virtual view. Besides the coding efficiency of texture image and depth map, bit allocation between texture image and depth map also has a great effect on the synthesized virtual view quality. Several methods are proposed for bit allocation between texture image and depth map, but most of them attempt to allocate a fixed target bitrate based on virtual view distortion model to achieve optimal synthesized virtual view quality, and the modeling process brings extra complexity. In practical application, the video sequence has different contents and fixed bit ratio cannot achieve optimal performance. In this paper, we propose an adaptive bit allocation algorithm for 3D video coding. First, we present a model to estimate the synthesized virtual view distortion, and then adjust the bit ratio between adjacent views and between texture image and depth map at Group of Picture level based on the virtual view quality fluctuation. We adjust the bit ratio to achieve the optimal virtual view quality for different video contents. Experimental results demonstrate that the proposed algorithm can optimally allocate bits to achieve optimal virtual view quality under different target bitrates and for different video contents, and the computational complexity of the proposed algorithm is extremely low. [ABSTRACT FROM AUTHOR]

It is necessary to improve the energy efficiency of batteries in wireless sensor networks (WSNs). The multiple-input multiple-output (MIMO) technique has become an important means to ameliorate WSNs, and interference management is the core of improving energy efficiency. A promising approach is interference alignment (IA), which effectively reduces the interference and improves the throughput of a system in the MIMO interference channels. However, the IA scheme requires perfect channel state information (CSI) at all transceivers in practice, which results in considerable feedback overhead. Thus, limited IA feedback has attracted much attention. In this paper, we analyze the throughput loss of the K-user MIMO interference channels when each transmitter delivers multiple streams in one slot, and derives the upper-bound of the system interference leakage and throughput loss. Then, to reduce the interference leakage and throughput loss for the MIMO interference alignment with limited feedback, a joint power and feedback bit allocation optimization scheme is proposed. The simulation results show that, compared with the conventional schemes, the presented optimal scheme achieves less residual interference and better performance in the system throughput. [ABSTRACT FROM AUTHOR]

Multi-view video plus depth (MVD) format 3D video consists of color texture image and gray depth map, the depth map provides the scene geometry information and is utilized to synthesize the virtual views through Depth Image Based Rendering (DIBR) technique. The quality of the synthesized virtual views is related to the qualities of both texture image and depth map, thus bit allocation between texture image and depth map is very important in 3D video coding. In this paper, we propose to optimally allocate bits between texture image and depth map by adjusting the Lagrangian Multiplier (LM) in depth map coding, we adjust the LM based on the difference between texture image coding Quantization Parameter (QP) and depth map QP. Experimental results show that the proposed method can achieve optimal 3D video coding performance for different sequences under different bitrates, and the complexity of our method is extremely low. [ABSTRACT FROM AUTHOR]

We propose an inter-view dependency-based rate control (RC) algorithm for 3D extension of high efficiency video coding (HEVC). First, considering the rate-distortion (R-D) dependency between the synthesized views and the input views (including texture videos and depth maps), a synthesized view distortion model is derived. Second, a novel distortion model for dependent views is proposed by investigating the inter-view dependency between the base and dependent views. Based on these two distortion models, a joint optimal bit allocation strategy (including texture/depth level, view level, and frame level) is developed to allocate target bits for both texture videos and depth maps of different views. Furthermore, an effective initial quantization parameter decision scheme considering the characteristics of the input video content is presented. Extensive experimental results exhibit that the proposed scheme achieves a higher rate control accuracy and provides a better R-D performance than the state-of-the-art RC algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel rate control method with optimized region-based bit allocation for depth video coding. First, a synthetic view distortion oriented segmentation method is proposed to divide depth video into different regions, including texture areas and smooth areas. Then, the expanded exponential distortion-rate (D-R) models and power quantization parameter-rate (QP-R) models are investigated to simulate rate-distortion (R-D) characteristics of different regions. Finally, an optimal bit allocation scheme is developed to adaptively allocate target bit with the division. Experimental results on various video sequences demonstrate that the proposed algorithm achieves excellent R-D efficiency and bit rate accuracy compared with benchmark algorithms. [ABSTRACT FROM AUTHOR]

There are various techniques for speech watermarking based on modifying the linear prediction coefficients (LPCs); however, the estimated and modified LPCs vary from each other even without attacks. Because line spectral frequency (LSF) has less sensitivity to watermarking than LPC, watermark bits are embedded into the maximum number of LSFs by applying the least significant bit replacement (LSBR) method. To reduce the differences between estimated and modified LPCs, a checking loop is added to minimize the watermark extraction error. Experimental results show that the proposed semifragile speech watermarking method can provide high imperceptibility and that any manipulation of the watermark signal destroys the watermark bits since manipulation changes it to a random stream of bits. [ABSTRACT FROM AUTHOR]

Pseudorandom number generators (PRNGs) generate random bit streams based on deterministic algorithms. Any bit stream generated with a PRNG will repeat itself at a certain point, and the bit streams will become correlated. As a result, all bit streams generated in this manner are statistically weak. Such weakness leads to a strong connection between PRNGs and chaos, which is characterized by ergodicity, confusion, complexity, sensitivity to initial conditions, and dependence on control parameters. In this study, we introduce a PRNG that generates bit sequences by sampling two Arnold cat map outputs. The statistical randomness of bit streams obtained using this PRNG was verified by statistical analyses such as the NIST test suite, the scale index method, statistical complexity measures, and autocorrelation. The generated bit streams successfully passed all the analytical tests and can be safely used for the many applications of randomness. [ABSTRACT FROM AUTHOR]

We investigate coordinated regularized zero-forcing (RZF) precoding for limited feedback multicell multiuser (MU) multiple-input–single-output (MISO) systems. We begin by deriving an approximation to the expected signal-to-interference-plus-noise (SINR) ratio for the proposed scheme with perfect channel direction information (CDI) at the base station (BS). We also derive an expected SINR approximation for limited feedback systems with random vector quantization (RVQ)-based codebook CDI at the BS. Using the expected interference result for the RVQ-based limited feedback CDI, we propose an adaptive feedback bit allocation strategy to minimize the expected interference by partitioning the total number of bits between the serving and out-of-cell interfering channels. Numerical results show that the proposed adaptive feedback bit allocation method offers a spectral efficiency gain over the existing coordinated zero-forcing (ZF) scheme. [ABSTRACT FROM PUBLISHER]

Ultra high definition (UHD) is the latest trend in broadcasting area, which enables new services with $3840\times 2160$ resolution and comes with enhanced color-gamut, frame-rate, dynamic range, and better audio system compared to the currently deployed HD services. The UHD format for broadcasting is already under standardization in the digital video broadcasting consortium which plans to introduce UHD services in three phases. The increase in data brought by these services requires more efficient compression and transmission systems. The recent scalable video coding standard scalable High Efficiency Video Coding (SHVC) is a promising candidate to handle these three phases while ensuring backward compatibility. Moreover, delivering such contents over networks needs an accurate control of the output bitrate from encoder engines to match rigid constraints on bandwidth and QoS. Several contributions have already been proposed to jointly encode scalable stream, but without considering the impact of bitrate ratio between layers on the compression performance. In this paper, the impact of the bitrate ratio between layers on the coding performance is first investigated for several UHD scalable schemes including spatial, color-gamut, and SDR-to-HDR scalability in SHVC. Based on this investigation, an adaptive rate control algorithm which dynamically allocates the bitrate between two layers is proposed to optimize the performance under quality and bitrate constraints. The algorithm has been implemented in the SHVC reference software (SHM9.0) and tested over 15 video sequences under two industrial use-cases. The performance shows an average BD-BR improvement of 7.51% and 3.35% for these two use-cases. [ABSTRACT FROM PUBLISHER]

Automatic modulation classification (AMC) techniques enable the estimation of the bit allocation table in adaptive orthogonal frequency division multiplexing (OFDM) systems. In this study, the authors investigate the classification performance of a low-complexity maximum-a-posteriori (MAP) algorithm for AMC. Also, they derive an approximation of the probability of classification error in a subcarrier for this classifier. Furthermore, based on these theoretical derivations, a novel modified rate adaptive (RA) bit loading algorithm with additional classification error constraint is proposed. Numerical results show that the authors' proposed method outperforms the RA algorithm significantly in terms of classification performance, while providing reasonable data throughput specifically at higher signal-to-noise ratios. [ABSTRACT FROM AUTHOR]

This paper investigates the schemes of asymptotically optimal quantization and bit allocation for distributed estimation in wireless sensor networks in which a total bit rate constraint is imposed. Because there is no communication among all sensors, quantizers for observations need to be designed separately. The Lloyd-Max quantizer is shown to be asymptotically optimal for each sensor. Moreover, it is shown that the level number of asymptotically optimal quantization for sensors is proportional to the signal-to-noise ratio, which is determined by the variances of observation and noise. Because the original quantized minimum mean-square error estimator often corresponds to a high computational cost when a large number of sensors are active, in our work, an asymptotically equivalent algorithm of iterative quantized estimator (IQE), which enjoys a low computational cost, is proposed. In addition, an IQE algorithm can be applied to wireless sensor networks with delay or packet loss. Simulation results of this work indicate that the effectiveness of our IQE algorithm is obvious; that is, a significant improvement of estimation performance is achieved by using the optimal bit allocation when comparing with the uniform bit allocation. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We study strategies for enhanced secrecy using cooperative jamming in secure communication systems with limited rate feedback. A Gaussian multiple-input multiple-output (MIMO) wiretap channel with a jamming helper is considered. The transmitter and helper both require channel state information (CSI), which is quantized at the receiver and fed back through two sum-rate-limited feedback channels. The quantization errors result in reduced beamforming gain from the transmitter, as well as interference leakage from the helper. First, under the assumption that the eavesdropper's CSI is completely unknown, we derive a lower bound on the average main channel rate and find the feedback bit allocation that maximizes the jamming power under a constraint on the bound. For the case where statistical CSI for the eavesdropper's channel is available, we derive a lower bound on the average secrecy rate, and we optimize the bound to find a suitable bit allocation and the transmit powers allocated to the transmitter and helper. For the case where the transmitter and helper have the same number of antennas, we obtain a closed-form solution for the optimal bit allocation. Simulations verify the theoretical analysis and demonstrate the significant performance gain that results with intelligent feedback bit allocation and power control. [ABSTRACT FROM PUBLISHER]

The newest video coding standard-- high efficiency video coding (HEVC) optimizes its coding efficiency in terms of sum of square error (SSE), which does not fully consider the perceptual characteristic of the input video. Thus, the HEVC is not effective in the sense of perceptual video coding. To address this problem, an efficient perceptual sensitivity-based rate control (PSRC) method for HEVC is proposed based on the human visual system (HVS) observation that the region with less perceptual sensitivity can tolerate more distortion. In the first stage, the proposed method develops a perceptual sensitivity measurement to evaluate the perceptual sensitivity of each coding tree unit (CTU) and each frame, which is then used to guide the bit allocation so that more bits will be allocated to those regions with higher perceptual sensitivity. To meet the target bits, an improved R- λ model is utilized to determine the quantization parameter (QP). Experimental results have shown that the proposed method is able to improve the perceptual coding performance, compared with the original rate control in HEVC. [ABSTRACT FROM AUTHOR]

Most existing intraframe rate control algorithms for the high efficiency video coding (HEVC) standard do not consider the extremely low end-to-end delay required by various applications. An intraframe extremely low-delay rate control scheme for HEVC is presented. First, compared with existing intraframe complexity estimation methods in HEVC, the proposed scheme provides a more accurate complexity estimation method by considering spatial-temporal complexity correlations. Second, based on the proposed complexity estimation method, a linear relationship is modeled between the encoding bit rate and the complexity estimated at the largest coding units (LCU) level. Finally, in order to meet the extremely low-delay constraint, an adaptive bit allocation scheme is proposed, in which the rate control starts as soon as the first LCU row of each frame becomes available. Compared with existing intraframe rate control schemes in HEVC, in which the buffer size is far greater than the number of bits needed for encoding one frame, the proposed rate control scheme has a buffer size that is approximately one-third the average number of bits for encoding one frame in order to achieve extremely low delay. Experimental results show that the proposed scheme can keep the buffer in an extreme low status along with reliable coding performance. © 2016 SPIE and IS&T [DOI: 10.1117/1.JEI.25.4.043008] [ABSTRACT FROM AUTHOR]

Recently, there are more and more image encryption algorithms being proposed based on chaotic systems. The classical architecture employs permutation plus diffusion. However, the traditional permutation operation can only shuffle the positions of the image pixels, but not change the pixels values and not implement the bit shifting in different bit planes. We can also see that most of them are key-dependent structures. So, they cannot resist efficiently the known-plaintext or chosen-plaintext attacks. To overcome these existing low-security problems, we suggest a new feedback image encryption scheme, in which a mathematical model is established for updating the initial conditions of the chaotic system in the permutation stage. Then, the secure SHA-3 algorithm is employed further to generate the keystream combined with new initial keys of the chaotic system in a diffusion stage. Both keystreams generated in the permutation and diffusion processes are dependent on the plain-image. Theoretical analysis and numerical simulations demonstrate the high security of the proposed encryption scheme, especially the ability to resist the known-plaintext and chosen-plaintext attacks. [ABSTRACT FROM AUTHOR]

This study aimed to investigate efficient bit-allocation and rate-control methods for H.264 scalable video encoders. We first presented a new bit-allocation algorithm at the frame level for H.264 temporal scalability. Additional to the target bit-rate and buffer occupancy, the temporal hierarchical level and visual complexity were considered for determining the bit budget of a frame. This bit-allocation scheme was followed by a quantization parameter (QP) estimation procedure to achieve the desired bit-rate. We improved the conventional QP assignment by identifying and correcting inappropriate QP values due to incorrect visual complexity prediction. Furthermore, the proposed bit-allocation and rate-control algorithm for temporal scalability was seamlessly integrated with spatial/quality scalabilities to offer flexible bit-rate/quality combinations. Rate-control performance of an investigated method was extensively evaluated in the accuracy of produced bit rates, rate-distortion behavior, and stability of the decoder's buffer occupancy. Experimental results showed that the proposed algorithm achieved accurate bit-rates, prevented buffer overflow and underflow, and simultaneously produced more favorable and stable visual quality as compared to the state-of-the-art approaches in the literature. [ABSTRACT FROM AUTHOR]

Massive multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) is a promising technology for next-generation wireless communications. However, when channel state information (CSI) at the transmitter is obtained using channel feedback, the benefits of this system are severely limited by the tradeoff between downlink capacity and feedback overhead. To solve this problem, we propose a time-domain differential feedback scheme for massive multiple-input single-output (MISO) OFDM systems. The proposed scheme exploits channel correlations in time, frequency, and space domains simultaneously by considering differential channel impulse response (CIR). To simplify the codebook design, and to reduce codeword-search complexity, we partition and then quantize the differential CIR using a number of subcodebooks. Because the total feedback bits are shared by the subcodebooks, we further optimize the bit allocation for them to minimize the total quantization error. For this, we analyze the quantization error of the proposed scheme and then use the analysis results for the bit-allocation optimization. In simulations, the proposed scheme efficiently exploits all correlations and achieves significant spectral-efficiency gain compared to conventional feedback schemes. [ABSTRACT FROM PUBLISHER]

A frame-level bit allocation optimization method is proposed to improve the rate–distortion performance for High Efficiency Video Coding. First, to avoid the demerits of the mixture Laplacian distribution model on complexity, a new synthesized Laplacian distribution (SynLD) model is proposed to describe the discrete cosine transform transformed coefficients based on Kullback–Leibler-divergence analysis. Second, quality dependencies among frames are investigated, and a linear relationship between quality dependency factor (QDF) and skip-mode percentage is proposed for QDF prediction. Based on the proposed SynLD model and QDF prediction method, a $\rho $ -domain-based frame-level bit allocation method is proposed. Experimental results show that when compared with the state-of-the-art pixel-based unified rate–quantization (URQ) model and $R$ – $\lambda $ -model-based algorithms, 1.75- and 0.16-dB BD-peak signal-to-noise ratio (PSNR) gains can be achieved by the proposed bit allocation method, respectively. For quality consistency, the average PSNR standard deviation shows 0.16 and 0.02 dB lower than URQ and $R$ – $\lambda $ -model-based algorithms, respectively. The proposed method also has a much more stable buffer control status and works well for scene change cases. [ABSTRACT FROM PUBLISHER]

Product quantization (PQ) is a popular vector quantization method for approximate nearest neighbor search. The key idea of PQ is to decompose the original data space into the Cartesian product of some low-dimensional subspaces and then every subspace is quantized separately with the same number of codewords. However, the performance of PQ depends largely on the distribution of the original data. If the energies of subspaces are extremely unbalanced, PQ will achieve bad results. In this paper, we propose an adaptive bit allocation product quantization (BAPQ) method to deal with the problem of unbalanced energies of subspaces in PQ. In BAPQ, we adaptively allocate different numbers of codewords (or bits) to subspaces to quantize data for minimizing the total quantization distortion. The essence of our method is to find the optimal bit allocation scheme. To this end, we formulate an objective function about minimizing quantization distortion with respect to bit allocation scheme and adopt a greedy algorithm to find the near-optimal solution. BAPQ can achieve lower quantization distortion than PQ and optimized product quantization (OPQ). Besides, both bias and variance of difference between the true distance and the BAPQ׳s estimated distance are reduced from those of PQ and OPQ. Extensive experiments have verified the superiority of BAPQ over state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

In general, to achieve high compression efficiency, a 2D image or a 2D block is used as the compression unit. However, 2D compression requires a large memory size and long latency when input data are received in a raster scan order that is common in existing TV systems. To address this problem, a 1D compression algorithm that uses a 1D block as the compression unit is proposed. 1D set partitioning in hierarchical trees (SPIHT) is an effective compression algorithm that fits the encoded bit length to the target bit length precisely. However, the 1D SPIHT can have low compression efficiency because 1D discrete wavelet transform (DWT) cannot make use of the redundancy in the vertical direction. This paper proposes two schemes for improving compression efficiency in the 1D SPIHT. First, a hybrid coding scheme that uses different coding algorithms for the low and high frequency bands is proposed. For the low-pass band, a differential pulse code modulation–variable length coding (DPCM–VLC) is adopted, whereas a 1D SPIHT is used for the high-pass band. Second, a scheme that determines the target bit length of each block by using spatial correlation with a minimal increase in complexity is proposed. Experimental results show that the proposed algorithm improves the average peak signal to noise ratio (PSNR) by 2.97 dB compared with the conventional 1D SPIHT algorithm. With the hardware implementation, the throughputs of both encoder and decoder designs are 6.15 Gbps, and gate counts of encoder and decoder designs are 42.8 K and 57.7 K, respectively. [ABSTRACT FROM AUTHOR]

The study presented in this paper shows that the coding gain between different allocation modalities between turbo encoder and quadrature amplitude modulator with 16 signal points is over 0.6dB in fading environment. The study presents comparatively the performances obtained with the single binary and double binary turbo codes of memory 4 (with 16 states) used in the LTE and DVB standards. It took into consideration the channel with flat fading, non-selective in frequency, of Ricean type for various degrees of strength. Because of the preferential protection offered by the quadrature amplitude modulation, the various modes of binary allocation between turbo encoding and the quadrature amplitude modulation provide very different bit error rates performances. The hierarchies in performance are strongly influenced by the signal per noise ratio at which work is done. The presented results are a guide for choosing the most adequate binary allocation modality between coding and modulation for specific applications. [ABSTRACT FROM AUTHOR]

This paper considers limited feedback for a two-cell interfering multiple-input–multiple-output multiple-access channel (MIMO-MAC). We propose a QR decomposition-based interference alignment (QRD-IA) scheme for efficient limited feedback and investigate the conditions for the antenna configuration. We characterize the interference leakage caused by quantization error as a function of the number of feedback bits. To minimize the interference leakage, we further propose a quantized-precoder-based IA (QP-IA) scheme by modifying the proposed QRD-IA scheme. By characterizing the interference leakage of the QP-IA scheme, we investigate the number of feedback bits to maintain the degrees of freedom (DOFs) in the two-cell interfering MIMO-MAC and a feedback bit allocation algorithm to improve the sum rate. From simulation results, we demonstrate that our proposed schemes can provide better sum-rate performance than the existing scheme using the same number of feedback bits, and our feedback bit allocation algorithm provides a higher sum rate compared with equal feedback bit allocation. [ABSTRACT FROM PUBLISHER]

Rate control (RC) is crucial in controlling compression bitrates and encoding qualities for networked video applications. In this paper, we propose a direct non-buffer real-time rate control algorithm for video encoding, which has two unique features. First, unlike traditional algorithms which adopt buffers in rate control, the proposed algorithm does not use a buffer in rate regulation which can reduce the delay and improve real-time response. Second, we propose a new Proportional-Integral-Derivative (PID) bit controller to directly control encoding bitrates. In addition, we also develop a simple but effective method for real-time target bit allocation. To the best of our knowledge, this is the first work that conducts video rate control without using a buffer. Our extensive experimental results have demonstrated that the proposed algorithm outperforms the MPEG-4 rate control algorithm by achieving more accurate rate regulation and improving overall coding quality. [ABSTRACT FROM AUTHOR]

We consider an orthogonal frequency division multiple access (OFDMA)-based multicast system where multiple base stations transmit a multicast session to a multicast group. The goal is to maximize the multicast rate (i.e. the minimum achievable user rate) subject to a total power constraint. We assume the use of an erasure code (e.g., a Reed{Solomon code) or rateless code (e.g., Luby transform code). This facilitates each user to accumulate rates from their best subchannels, so that the achievable multicast rate is not limited to the worst user. The resource allocation problem involves determining the transmitting base station at each OFDMA subchannel, the number of bits to be transmitted at each subchannel, and the set of nodes to decode the bits at each subchannel. We formulate the problem as a mixed binary integer linear programming and find the optimal solution as a benchmark. We also propose a greedy subchannel and bit allocation algorithm that is close to optimal. [ABSTRACT FROM AUTHOR]

Using hashing algorithms to learn binary codes representation of data for fast approximate nearest neighbor (ANN) search has attracted more and more attention. Most existing hashing methods employ various hash functions to encode data. The resulting binary codes can be obtained by concatenating bits produced by those hash functions. These methods usually have two main steps: projection and thresholding. One problem with these methods is that every dimension of the projected data is regarded as of same importance and encoded by one bit, which may result in ineffective codes. In this paper, we introduce an adaptive bit allocation hashing (ABAH) method to encode data for ANN search. The basic idea is, according to the dispersions of all the dimensions after projection we use different numbers of bits to encode them. In our method, more bits will be adaptively allocated to encode dimensions with larger dispersion while fewer bits for dimensions with smaller dispersion. This novel bit allocation scheme makes our hashing method effectively preserve the neighborhood structure in the original data space. Extensive experiments show that the proposed ABAH significantly outperforms other state-of-the-art methods for ANN search task. [ABSTRACT FROM AUTHOR]

In the multiview video plus depth (MVD) coding format, both texture and depth views are jointly compressed to represent the 3-D video content. The MVD format enables synthesis of virtual views through depth-image-based rendering; hence, distortion in the texture and depth views affects the quality of the synthesized virtual views. Bit allocation between texture and depth views has been studied with some promising results. However, to the best of our knowledge, most of the existing bit-allocation methods attempt to allocate a fixed amount of total bit rate between texture and depth views; that is, to select appropriate pair of quantization parameters for texture and depth views to maximize the synthesized view quality subject to a fixed total bit rate. In this paper we propose a scalable bit-allocation scheme, where a single ordering of texture and depth packets is derived and used to obtain optimal bit allocation between texture and depth views for any total target rates. In the proposed scheme, both texture and depth views are encoded using the quality scalable coding method; that is, medium grain scalable (MGS) coding of the Scalable Video Coding (SVC) extension of the Advanced Video Coding (H.264/AVC) standard. For varying target total bit rates, optimal bit truncation points for both texture and depth views can be obtained using the proposed scheme. Moreover, we propose to order the enhancement layer packets of the H.264/SVC MGS encoded depth view according to their contribution to the reduction of the synthesized view distortion. On one hand, this improves the depth view packet ordering when considered the rate-distortion performance of synthesized views, which is demonstrated by the experimental results. On the other hand, the information obtained in this step is used to facilitate optimal bit allocation between texture and depth views. Experimental results demonstrate the effectiveness of the proposed scalable bit-allocation scheme for texture and depth views. [ABSTRACT FROM AUTHOR]

An energy efficient adder design based on a hybrid carry computation is proposed. Addition takes place by considering the carry as propagating forwards from the LSB and backwards from the MSB. The incidence at a midpoint significantly accelerates the addition. This acceleration together with combining low-cost ripple-carry and carry-chain circuits, yields energy efficiency compared to other adder architectures. The optimal midpoint is analytically formulated and its closed-form expression is derived. To avoid the quadratic RC delay growth in a long carry chain, it is optimally repeated. The adder is enhanced in a tree-like structure for further acceleration. 32, 64 and 128-bit adders targeting 500 MHz and 1 GHz clock frequencies were designed in 65 nm technology. They consumed 11–18% less energy compared to adders generated by state-of-the-art EDA synthesis tool. [ABSTRACT FROM AUTHOR]

Applying multi-bit flip-flops (MBFFs) for clock power reduction in modern nanometer ICs has been becoming a promising lower-power design technique. Many previous works tried to utilize as more MBFFs with larger number of bits as possible to gain more clock power saving. However, an MBFF with larger number of bits may lead to serious crosstalk due to the close interconnecting wires belonging to different signal nets which are connected to the same MBFF. This paper analyzes, evaluates, and compares the relationship between power consumption and crosstalk when applying MBFFs with different numbers of bits. To solve the addressed problem, a novel crosstalk-aware power optimization approach is further proposed to optimize power consumption while satisfying the crosstalk constraint. Experimental results show that the proposed approach is very effective in crosstalk avoidance when applying MBFFs for power optimization. [ABSTRACT FROM AUTHOR]

The axis compensation is a procedure in which the sender and the receiver compensate the axes of their transmitter and detector so that the bit sequence can be transmitted more reliably. We show the optimal axis compensations maximizing the key generation rate for unital channels. We consider the case in which only Bob is allowed to compensate his axis, and the case in which both Alice and Bob are allowed to compensate their axes. In the former case, we show that we should utilize the mismatched measurement outcomes in the channel estimation phase. In the latter case, we show that we do not have to utilize the mismatched measurement outcomes in the channel estimation phase. [ABSTRACT FROM AUTHOR]

Specific to the security issues of medical information falsifying and stealing, this paper proposed a zero-bit water mark algorithm based on chaos. It used the Arnold algorithm to scramble the original carrier image for k times. Then it extracted the least significant bit of each pixel of the scrambled image for the XOR operation with binary watermark to construct the zero-bit watermark. The actual embedded watermark image adopted chaos mapping encryption to hide the watermark information. After it extracted the watermark, took the absolute difference between the original watermark image and the extracted one, if it had suffered from falsifying, the falsifying position and shape could be located. The experimental results show that the large key space of chaotic system and sensitivity to the initial value can increase the robustness of the algorithm, and the algorithm can still accurately locate the distorted site and shape under conventional attacks. [ABSTRACT FROM AUTHOR]

In three dimensional video coding (3-DVC), it is reasonable to allocate bits for texture videos and depth maps differently as the characteristic of texture videos is different with that of depth maps. In order to improve the accuracy of bit allocation performance for 3-DVC, a more accurate distortion model for virtual view and rate models for texture videos and depth maps are proposed based on interview rate distortion analysis. Based on the proposed models, the bit allocation optimization problem is resolved by a coarse to fine strategy. The proposed bit allocation algorithm is implemented in the High Efficiency Video Coding-based 3-DVC platform version 6.0 (3-D-HTM 6.0). Experimental results demonstrate that the proposed distortion and rate models are accurate; meanwhile, the absolute difference (denoted as “rate inaccuracy”) between the actual coding bit rate ( R \textbf {ABR} ) and the target coding bit rate ( R \textbf {TBR} ) of the proposed method is only 2.67% on average; while the rate inaccuracy of the existing planar model-based method is 17.71%. Besides, there is an average 29.68% complexity increment when comparing with the planar model-based method. [ABSTRACT FROM AUTHOR]

The switching current density in a bit of spin transfer torque magnetic random access memory (STT-MRAM) has to be <1 MA/cm ^2 for realistic application. The STT-MRAM using CoFeB magnetic tunnel junctions (MTJs) with perpendicular anisotropy are possible to match this target. In this paper, the switching properties in this system are investigated by a micromagnetic model. To simulate the perpendicular and in-plane hysteresis loops correctly, inhomogeneity of the perpendicular interfacial anisotropy constant $K$ is introduced to the free layer of the MTJ. The calculated resistance versus applied current density curves of the bits are highly asymmetric, which agrees with experiment. The critical switching currents have dispersion due to the inhomogeneity of $K$ . In addition, the simulation confirms the nucleation-type reversal process, and the reversal time decreases with increasing applied current. [ABSTRACT FROM AUTHOR]