Hybrid Digital-analog Systems Research Articles

Distortion Estimation-Based Adaptive Power Allocation for Hybrid Digital–Analog Video Transmission

Hybrid digital–analog (HDA) video transmission schemes have shown advantages in avoiding the cliff effect . However, most current HDA schemes assume perfect transmission of the digital signal, which is hardly the case in practice. In this paper, we propose an adaptive recursive distortion estimate for the HDA system (ARDE-HDA), which recursively estimates the decoder-side distortion from the encoder and adaptively allocates the transmission power between the digital and analog signals in HDA. First, we derive the closed-form expression of a recursive distortion estimation (RDE) method, which does not require the digital part of the HDA output to be decoded perfectly, and both transmission error and superposition process of digital and analog parts are taken into consideration. Then, based on the deduced RDE model, an adaptive power allocation is proposed for the digital and analog parts to minimize the decoder-side distortion. Finally, simulation results are presented, which show the accuracy of the proposed RDE model and the ARDE-HDA method. Our method can achieve an average of 4.10 dB gain over existing HDA methods and 15.14-dB gain over the Softcast method in terms of the peak signal-to-noise ratio.

Joint Rate and Resource Allocation in Hybrid Digital–Analog Transmission Over Fading Channels

In hybrid digital-analog (HDA) systems, resource allocation has been utilized to achieve desired distortion performance. However, existing studies on this issue assume error-free digital transmission, which is not valid for fading channels. With time-varying channel fading, the exact channel state information is not available at the transmitter. Thus, random outage and resulting digital distortion cannot be ignored. Moreover, rate allocation should be considered in resource allocation, since it not only determines the amount of information for digital transmission and that for analog transmission, but also affects the outage probability. Based on above observations, in this paper, we attempt to perform joint rate and resource allocation strategies to optimize system distortion in HDA systems over fading channels. Consider a bandwidth expansion scenario where a memoryless Gaussian source is transmitted in an HDA system with the entropy-constrained scalar quantizer (ECSQ). Firstly, we formulate the joint allocation problem as an expected system distortion minimization problem where both analog and digital distortion are considered. Then, in the limit of low outage probability, we decompose the problem into two coupled sub-problems based on the block coordinate descent method, and propose an iterative gradient algorithm to approach the optimal solution. Furthermore, we extend our work to the multivariate Gaussian source scenario where a two-stage fast algorithm integrating rounding and greedy strategies is proposed to optimize the joint rate and resource allocation problem. Finally, simulation results demonstrate that the proposed algorithms can achieve up to 2.3dB gains in terms of signal-to-distortion ratio over existing schemes under the single Gaussian source scenario, and up to 3.5dB gains under the multivariate Gaussian source scenario.

Hybrid Digital–Analog Video Delivery With Shannon–Kotel’nikov Mapping

Hybrid digital–analog (HDA) transmission is beco-ming an attractive solution for mobile video delivery because it not only has graceful degradation with channel variations but also yields high power efficiency. However, the heavy bandwidth demand of analog transmission is still an unsolved problem, limiting the received video quality when the bandwidth is not sufficient. To address this problem, we propose adopting Shannon–Kotel’nikov (SK) mapping for HDA video transmission and design an HDA scheme called SK-Cast. SK-Cast consists of a digital and an analog branch. In the digital branch, SK-Cast compresses the video sequence using an high efficiency video coding digital encoder to produce a base layer. The base layer is transmitted through digital methods with strong protection. The residual signals are then decorrelated using three-dimensional discrete cosine transform transform. The SK mapping is exploited to transmit these coefficients, as they can achieve efficient bandwidth compression. We address the resource allocation problems in SK-Cast, including the allocation between digital and analog branches and the allocation among analog symbols. The simulation results show that the SK-Cast outperforms the state-of-the-art HDA systems, including WSVC and SharpCast, and a digital scalable video coding system.

An Optimal Resource Allocation for Superposition Coding-Based Hybrid Digital–Analog System

Hybrid digital–analog (HDA) video transmission is a new cross-layer design, which can be widely used in Internet of Things. The key problem of HDA video transmission is to find the optimal resource allocation between the digital and analog part. This paper presents a new general resource allocation algorithm for superposition coding-based HDA system. On one hand, in order to achieve successful decoding in digital part, the bitrate is controlled by the quantization parameter (QP), and the channel coding rate and modulation order are determined by the signal to interference noise power ratio, in which analog part is considered as the interference. On the other hand, the overall video quality is directly determined by the mean square error of analog part, which depends jointly on the data variance of the analog part, the power allocated to the analog part and the channel noise power. We propose a prediction model to describe how the data variance of the analog part changes with the QP in the digital part. Based on the proposed model, the power allocation of two parts can be quantitatively connected to form an optimization problem. We prove the convexity of the resource allocation problem and the gradient descent method is utilized in system implementation. With extensive simulations, the proposed algorithm is validated, achieving 1.4–5.3 dB gain over the conventional digital system, and 6.2–7.4 dB gain over pseudo-analog system in peak signal-to-noise ratio.

Design and Evaluation of Hybrid Digital-Analog Transmission Outperforming Purely Digital Concepts

Efficient digital transmission of analog speech, audio or video requires source coding which introduces unavoidable quantization errors. The bit stream produced by the source encoder needs to be protected against transmission errors by channel coding. The split of a given gross bit rate between source and channel coding is a compromise taking into account the design target of the worst case channel. Thus, even in clear channel conditions the quality of the decoded source signal is limited because of the quantization errors. Hybrid digital-analog (HDA) codes address this limitation by additionally transmitting the quantization error with quasi-analog methods (discrete-time, quasi-continuous-amplitude) with neither increasing the transmit power, nor the occupied frequency bandwidth on the radio channel. However, the decoding complexity of existing HDA codes is infeasible for the required block lengths. In this paper, the decoding complexity problem is solved by a new design approach. These HDA codes benefit from well-known digital codes. Furthermore, theoretical bounds are derived and explicit guidelines for the design of superior HDA systems are given. By experimental verification it is shown that the HDA concept may outperform conventional purely digital transmission systems at all channel qualities while additionally eliminating the quality saturation effect.

Hybrid Digital–Analog transmission for wireless acoustic sensor networks

A crucial task of a Wireless Acoustic Sensor Network (WASN) is the transmission of the acoustic signal to a central fusion node. Due to different microphone locations, the microphones may experience different or even varying radio channel qualities. Usually, the design of the digital transmission scheme is governed by the worst-case radio channel. For given radio resources, the end-to-end audio quality is specified by the compromise between the fidelity of the audio encoder and the required error protection capabilities of the channel encoder. The quantization noise of the audio encoder limits the end-to-end SNR even for increasing radio channel qualities. In the fusion node, the decoded signals are combined (fusion algorithm) and the overall output audio quality is limited due to the quantization noise even for error free transmission. In this paper it is shown that this unfavorable behavior can be avoided by using a Hybrid Digital-Analog (HDA) transmission concept. The key feature of HDA is that the audio output quality improves with increasing channel qualities. For typical fusion algorithms the HDA system supersedes purely digital transmission for all radio channel qualities.

Hybrid digital-analog coding with bandwidth compression for gaussian source-channel pairs

Three hybrid digital-analog (HDA) systems, denoted by HDA-I, HDA* and HDA-II, for the coding of a memoryless discrete-time Gaussian source over a discrete-time additive memoryless Gaussian channel under bandwidth compression are studied. The systems employ simple linear coding in their analog component and superimpose their analog and digital signals before channel transmission. Information-theoretic upper bounds on the asymptotically optimal mean squared error distortion of the systems are obtained under both matched and mismatched channel conditions. Allocation schemes for distributing the channel input power between the analog and the digital signals are also examined. It is shown that systems HDA* and HDA-II can asymptotically achieve the optimal Shannon-limit performance under matched channel conditions. Low-complexity and low-delay versions of systems HDA-I and HDA-II are next designed and implemented without the use of error correcting codes. The parameters of these HDA systems, which employ vector quantization in conjunction with binary phase-shift keying modulation in their digital part, are optimized via an iterative algorithm similar to the design algorithm for channel-optimized vector quantizers. Both systems have low complexity and low delay, and guarantee graceful performance improvements for high CSNRs. For memoryless Gaussian sources the designed HDA-II system is shown to be superior to the HDA-I designed system. When applied to a Gauss-Markov source under Karhunen-Loeve processing, the HDA-I system is shown to provide considerably better performance.

Hybrid Digital–Analog Source–Channel Coding for Bandwidth Compression/Expansion

An approach to hybrid digital-analog (HDA) source-channel coding for the communication of analog sources over memoryless Gaussian channels is introduced. The HDA system, which exploits the advantages of both digital and analog systems, generalizes a scheme previously presented by the authors, and can operate for any bandwidth ratio (bandwidth compression and expansion). It is based on vector quantization and features turbo coding in its digital component and linear/nonlinear processing in its analog part. Simulations illustrate that, under both bandwidth compression and expansion modes of operation, the HDA system provides a robust and graceful performance with good reproduction fidelity for a wide range of channel conditions

Design and performance of VQ-based hybrid digital-analog joint source-channel codes

A joint source-channel hybrid digital-analog (HDA) vector quantization (VQ) system is presented. The main advantage of the new VQ-based HDA system is that it achieves excellent rate-distortion-capacity performance at the design signal-to-noise ratio (SNR) while maintaining a graceful improvement characteristic at higher SNRs. It is demonstrated that, within the HDA framework, the parameters of the system can be optimized using an iterative procedure similar to that of channel-optimized vector quantizer design. Comparisons are made with three purely digital systems and one purely analog system. It is found that, at high SNRs, the VQ-based HDA system is superior to the other investigated systems. At low SNRs, the performance of the new scheme can be improved using the optimization procedure and using soft decoding in the digital part of the system. These results demonstrate that the introduced scheme provides an attractive method for terrestrial broadcasting applications.

Beam Manipulation Equipment at the Zero Gradient Synchrotron

The evolution of working accelerators invariably requires increasingly flexible beam manipulation to fulfill the demands of high energy physics experiments. The following reports on a hybrid digital-analog system that provides intricate beam manipulation programs for use with the Argonne Zero Gradient Synchrotron (ZGS). It describes the system requirements, the design philosophy, the equipment developed to fulfill these requirements, and finally, the present performance of this equipment. Figure 4 shows one view of the completed system.