In this paper the quality of adaptive bit rate video streaming is investigated and two state-of-the-art models, i.e., the NTT audiovisual quality-estimation and ITU-T P.1203 models, are considered. This paper shows how these models can be applied to new conditions, e.g., 4K ultra high definition (4K-UHD) videos encoded using H.265, considering that they were originally designed and trained for HD videos encoded with H.264. Six subjective evaluations involving up to 192 participants and a large variety of test conditions, e.g., durations from 10sec to 3min, coding-quality variation, and stalling events, were conducted on both TV and mobile devices. Using the subjective data, this paper addresses how models and coefficients can be transferred to new conditions. A comparison between state-of-the-art models is conducted, showing the performance of transferred and retrained models. It is found that other video-quality estimation models, such as VMAF, can be used as input of the NTT and ITU-T P.1203 long-term pooling modules, allowing these other video-quality-estimation models to support the specificities of adaptive bit-rate-streaming scenarios. Finally, all retrained coefficients are detailed in this paper allowing future work to directly reuse the results of this study.

We propose a new context-adaptive arithmetic coding (CAAC) scheme for lossless bit rate reduction of parametric stereo (PS) in enhanced aacPlus. Based on the probability analysis of stereo parameters indexes in PS, we propose a stereo band-dependent CAAC scheme for PS. We also propose a new coding structure of the scheme which is simple but effective. The proposed scheme has normal and memory-reduced versions, which are superior to the original and conventional schemes and guarantees significant bit rate reduction of PS. The proposed scheme can be an alternative to the original PS coding scheme at low bit rate, where coding efficiency is very important.

Multiuser MIMO (MU-MIMO) improves the system channel capacity by generating a large virtual MIMO channel between a base station and multiple user terminals (UTs) with effective utilization of wireless resources. Block beamforming algorithms such as Block Diagonalization (BD) and Block Maximum Signal-to-Noise ratio (BMSN) have been proposed in order to realize MU-MIMO broadcast transmission. The BD algorithm cancels inter-user interference (IUI) by creating the weights so that the channel matrices for the other users are set to be zero matrices. The BMSN algorithm has a function of maintaining a high gain response for each desired user in addition to IUI cancellation. Therefore, the BMSN algorithm generally outperforms the BD algorithm. However, when the number of transmit antennas is equal to the total number of receive antennas, the transmission rate by both BD and BMSN algorithms is decreased. This is because the eigenvalues of channel matrices are too small to support data transmission. To resolve the issue, this paper focuses on an antenna selection (AS) method at the UTs. The AS method reduces the number of pattern nulls for the other users except an intended user in the BD and BMSN algorithms. It is verified via bit error rate (BER) evaluation that the AS method is effective in the BD and BMSN algorithms, especially, when the number of user antennas with a low bit rate (i.e., low signal-to-noise power ratio) is increased. Moreover, this paper evaluates the achievable bit rate and throughput including an actual channel state information feedback based on IEEE802.11ac standard. Although the number of equivalent receive antenna is reduced to only one by the AS method when the number of antennas at the UT is two, it is shown that the throughputs by BD and BMSN with the AS method (BD-AS and BMSN-AS) are higher than those by the conventional BD and BMSN algorithms.

A method for encoding detection and bit rate classification of AMR-coded speech is proposed. For each texture frame, 184 features consisting of the short-term and long-term temporal statistics of speech parameters are extracted, which can effectively measure the amount of distortion due to AMR. The deep neural network then classifies the bit rate of speech after analyzing the extracted features. It is confirmed that the proposed features provide better performance than the conventional spectral features designed for bit rate classification of coded audio.

In this paper, we propose a zero-forcing (ZF) Tomlinson-Harashima precoding (THP) with substream permutations based on the bit rate maximization for single-user MIMO (SU-MIMO) systems. We study the effect of substream permutations on the ZF-THP SU-MIMO systems, when the mean squared error (MSE) and the bit rate are adopted for the selection of the permutation matrix as criteria. Based on our analysis, we propose a method to increase the bit rate by substream permutations, and derive QR and Cholesky decomposition-based algorithms which realize the proposed method. Furthermore, to improve the error rate performance, we apply zero transmission to subchannels with low signal-to-noise ratios. Numerical examples are provided to demonstrate the effectiveness of the proposed THP MIMO system.

In this paper, we propose a switchable linear prediction (LP)/warped linear prediction (WLP) hybrid scheme for the transform coded excitation (TCX) coder, which is adopted as a core codec in AMR-WB+ and USAC. The proposed algorithm selects either an LP or WLP filter on a per-frame basis. To provide a smooth transitions between LP and WLP frames, a window switching scheme is developed using sine and rectangular windows. In addition, a Gaussian Mixture Model (GMM)-based classification module is used to determine the prediction mode. Through a subjective listening test it was confirmed that the proposed LP/WLP switching scheme offers improved sound quality.

We propose a new coding scheme for lossless bit rate reduction of the MPEG Surround module in unified speech and audio coding (USAC). The proposed scheme is based on context-adaptive arithmetic coding for efficient bit stream composition of spatial parameters. Experiments show that it achieves the significant lossless bit reduction of 9.93% to 12.14% for spatial parameters and 8.64% to 8.96% for the overall MPEG Surround bit streams compared to the original scheme. The proposed scheme, which is not currently included in USAC, can be used for the improved coding efficiency of MPEG Surround in USAC, where the saved bits can be utilized by the other modules in USAC.

We consider the problem of transmit power and bit rate allocation for OFDM based cognitive radio systems. An efficient allocation algorithm which mainly consists of two steps is proposed to maximize the sum rate of secondary users. In the first step of the algorithm, original nonlinear problem is converted to a convex problem which is solved by dual methods, and in the second step the final resource allocation results is obtained via iterative power rescale operation. Numerical results show the effectiveness of the proposed algorithm.

Delivering video streaming service over the Internet encounters some challenges. Two of them are heterogeneity of networks capacity and variability of video data rate. The capacity of network segments are constrained. Meanwhile, the rate of video data to be transmitted is highly variable in order to get near-constant images quality. Therefore, to send variable bit rate (VBR) video data over capacity-constrained network, its bit rate should be adjusted. In this paper a system to adjust the transmission bit rate of VBR MPEG video data called Transcoding-after-Smoothing (TaS), which is a combination of bit rate transcoding and bit rate smoothing algorithm, is proposed. The system smoothes out transmission rate of video data while at the same time also performs transcoding on some video frames when necessary in order to keep the transmission bit rate below a certain threshold value. Two kinds of TaS methods are proposed. One method does not have transcoding preference, while the other method uses frame type preference where an intra-coded frame is the last one that will be transcoded. These methods are implemented in our video server where a VBR video data is accessed by a client. Our experiment results show that the first TaS method yields significant reduction in the number of transcoded frames compared with the second TaS method and conventional frame-level transcoding. However, the second method performs better in minimizing the quality distortion.

This paper proposes two efficient rate control algorithms for Motion JPEG2000. Both methods provide accurate visual quality control under buffer constraints. Frames of the same scene usually have the similar rate-distortion (R-D) characters. The proposed methods predict the R-D models of uncoded frames forwardly or bilaterally according to those of coded frames. Experimental results demonstrate that the proposed algorithms offer visual quality improvements over similar competing methods and save a large amount of memory simultaneously.

This paper presents an adaptive control design for the ABR traffic congestion control in ATM networks. Firstly, we consider a control-based mathematical model to the ABR traffic congestion control problem. Then the feedback pole placement control design is applied to the ATM ABR traffic congestion control problem for the case of known delays. Finally, by using the online plant parameter estimation algorithm and modifying the controller parameters adaptively in real time, a method to treat the case of unknown time-varying delays is proposed. Several design modifications are introduced to solve practical control issues such as bounded command rate constraint, output buffer saturation and bounded values to the plant parameter estimation algorithm. Simulations are implemented to verify the proposed control design. It is shown that while considering these practical control issues, the control method satisfies the requirements of fairness to users, network efficiency, unknown time-varying delays, queue length control and good convergence performance at an acceptable computation effort.

We describe a transmission system having a data rate of 160 Gbit/s based on the RZ-DPSK modulation format. The 160 Gbit/s single-polarization signal is generated by optical time division multiplexing technology using the base rate of 40 Gbit/s. The setup is explained and results are given with a special focus on the stability issue of the transmission system. The pulse source, the optical gate for demultiplexing, the clock recovery and the balanced photo-detector are based on semiconductor components. We present long-term bit error measurements (10 hours) over two different long-haul fiber links. The first link comprises 3106 km standard single mode fiber and uses a PMD mitigation scheme. The other link consists of 4 dispersion managed 80 km fiber spans without the need for an additional PMD compensation. Using EDFA amplification solely and also no FEC, error-free operation was achieved over several hours, only limited by slow drift effects in the laboratory system.

In this paper, we propose a novel traffic engineering architecture for IP networks with MPLS backbones. In this architecture, two link-disjoint label switched paths, namely the primary and secondary paths, are established among every pair of IP routers located at the edges of an MPLS backbone network. As the main building block of this architecture, we propose that primary paths are given higher priority against the secondary paths in the MPLS data plane to cope with the so-called knock-on effect. Inspired by the ABR flow control mechanism in ATM networks, we propose to split traffic between a source-destination pair between the primary and secondary paths using explicit rate feedback from the network. Taking into consideration the performance deteriorating impact of packet reordering in packet-based load balancing schemes, we propose a traffic splitting mechanism that operates on a per-flow basis (i.e., flow-based multipath routing). We show via an extensive simulation study that using flow-based multipath traffic engineering with explicit rate feedback not only provides consistently better throughput than that of a single path but is also void of out-of-order packet delivery.

We propose a novel handover initiation algorithm based on available bit rate and timing constraint criterion for multimedia capable cellular systems. Computer simulations are performed to evaluate the handover rate and handover initiation delay. Numerical results show that handover must be initiated at different positions for different services to maintain the required quality of service requirements.

This paper proposes a stable rate allocation algorithm for ABR service in ATM networks. The main goals in designing this algorithm are to speed up the convergence according to the max-min fairness criterion and to maximize the network utilization while the switch queue length can be properly controlled. Importantly, the set goals should be achieved in a wide range of network conditions without the need for adjusting the algorithm parameters. The algorithm is targeted to work in various networking environments with additional criteria as extended from the work of E-FMMRA (Enhanced Fast Max-Min Rate Allocation) and ERICA+ (Explicit Rate Indication for Congestion Avoidance) . The additional design criteria include the ability to enhance a large number of ABR connections and staggered TCP connections as well as to perform an accurate traffic averaging. The algorithm is analytically proved to be convergent. Simulation results indicate that the proposed algorithm achieves the goals in all evaluated configurations. However, it has some limitations when working in the large-scale network due to its per-connection accounting. It is not recommended to implement the algorithm with a switch that has a small buffer size due to its relatively long averaging interval.

In this paper, we propose a simplified transform-based and variable-rate vocoder, which is evolved from the code-excited linear prediction (CELP) coding structure. With pre-emphasis and de-emphasis filters, the transformed-based CELP vocoder incorporates a long-term predictor, a discrete cosine transform (DCT), and pre-filters and postfilters for achieving perceptually weighted quantization. The proposed transform-based vocoder requires less computational complexity with slightly worse quality than the CELP coders. Furthermore, the proposed DCT-based coding structure easily figured with additional DCT coefficients could simultaneously offer low, middle, and high bit rates to adapt the variation of bandwidth for modern Internet or wireless communications.

In this paper, we propose a new consolidation algorithm called the Selective Backward Resource Management (BRM) cell Feedback (SBF) algorithm. It achieves a fast response and low consolidation noise by selectively forwarding BRM cell from the most congested branch to the source instead of waiting from all branches. Mathematical models are derived to quantitatively characterize the performance, i.e. the response time and ACR of the source, of SBF and previously proposed algorithms. The interoperation of consolidation algorithms in point-to-multipoint available bit rate (ABR) is investigated. We address response time, consolidation noise and the effect of asymmetrical round trip delay (RTD) from branch point to destinations aspects. All combinations of four different consolidation algorithms are interoperated in both local/metropolitan area network (LAN/MAN) and wide area network (WAN) configuration. By a simulation method, we found that the consolidation algorithm used at the uppermost stream branch point, especially in WAN configuration, plays an important role in determining the performance of the network. However, consolidation algorithm used at the lower stream branch point affects the network performance insignificantly. Hence, in order to achieve a good and effective performance of the consolidation algorithms interoperated network, a fast response with low consolidation noise algorithm should be used at the uppermost stream branch point and a simple and easy to implement algorithm should be used at the lower stream branch point.

Scalabilities of bit rate and coding format in coded multimedia contents have become very important for the efficient use of network bandwidth and storage capacity with the recent availability of a wide variety of bandwidth and storage media. However, the conventional approach uses decompression and recompression processes to realize the above scalabilities, which require very expensive computations. In addition, a very large cache space is required for storing the decoded audio-video data. This paper describes three fast scalability methods for MPEG audio and video data, MPEG audio/video bit rate conversion and MPEG format conversion, in order to address these problems. As for the first scalability, MPEG audio coding bit rate conversions, we describe subband domain conversion using bandwidth limitation, requantization and a requantization reflecting phychoacoustic model. Four types of MPEG video bit rate conversion are described that use bandwidth limitation, out-loop requantization, in-loop requantization, and hybrid requantization. As for the format conversion, the fast baseband domain format conversion is performed using coding information such as motion vectors and coding types extracted from input coded video. The experimental results of several comparisons with the above scalabilities and conventional transcoding methods are also shown.

Disk-zoning technique has been widely adopted to increase disks capacities. As a result of disparity of capacities of inner and outer zones, the data transfer rates of the outer zones of a zoned-disk are higher than the inner zones that post a great challenge for zoned-disk based multimedia playback. In this paper, we study the data placement problem of VBR (variable bit rate) videos on zoned-disks. Our objective is to minimize video server buffer size and simultaneously to maximize disk utilization subject to the zone constraints of disk. We introduce the CRT (constant read time) method that allocates each user a constant time period in every service round to retrieve a variable-sized disk block. The CRT method can be formulated as constrained combinatorial problems that its optimum solution can be obtained by employing dynamic programming. Two heuristics are also explored to reduce time and space complexities. According to experiment results, the heuristic algorithms obtain near optimum solutions with shorter computation time.

The available bit rate (ABR) is an ATM service category that provides an economical support of connections having vague requirements. An ABR session may specify its peak cell rate (PCR) and minimum cell rate (MCR), and available bandwidth is allocated to competing sessions based on the max-min policy. In this paper, we investigate the ABR traffic control from a different point of view: Based on the decentralized bandwidth allocation model studied in [9], we prove that the max-min rate vector is the equilibrium of a certain system of noncooperative optimizations. This interpretation suggests a new framework for ABR traffic control that allows the max-min optimality to be achieved and maintained by end-systems, and not by network switches. Moreover, in the discussion, we consider the constrained version of max-min fairness and develop an efficient algorithm with theoretical justification to determine the optimal rate vector.