Joint Source-channel Research Articles

On Simultaneously Generating Multiple Keys in a Joint Source-Channel Model

In this paper, the problem of simultaneously generating multiple keys over a cascade of a noiseless channel and a wiretap channel is considered. The problem consists of three legitimate parties (i.e., Alice, Bob, and Carol) and an eavesdropper (Eve), where Alice and Bob wish to agree with Carol on independent secret keys, both of which should be kept secret from Eve. Alice and Bob are connected via a noiseless channel, and Bob is connected with Carol via a wiretap channel, while there is no direct connection between Alice and Carol. To Alice and Carol, Bob acts as a relay. Under this model, a full characterization of the secret-key capacity region is provided for the case in which Eve has no side information. This result shows that there exists a tradeoff between the individual secret-key rates. Then, this result is generalized to the case in which Eve has side information, and the corresponding secret-key capacity region is fully characterized.

Robust distributed video coding for wireless multimedia sensor networks

Coding complexity and error-resilience are the two key factors for video streaming in Wireless Multimedia Sensor Networks (WMSNs). Towards this objective, this paper proposes a Robust Distributed Video Coding (RDVC) framework to optimize the quality of video transmission for WMSNs. A new error-resilient Key frame coding scheme is proposed based on the protection of Wyner-Ziv Coding (WZC), in which additional Wyner-Ziv bits play a significant role for better error resilience and better Rate/Distortion (RD) performance. In addition, following the theoretical background of Distributed Joint Source Channel Coding (DJSCC), a novel distributed source channel codec based on Group Puncture Rate Adaptive IRA code (GPRA-IRA) is proposed, upon which the error-resilient Wyner-Ziv codec is designed. These experimental results show that the proposed RDVC scheme outperforms the relevant coding in terms of RD performance, notably by up to 1-3 dB, while achieving a lower encoding complexity.

Systematic Polar Codes for Joint Source-Channel Coding in Wireless Sensor Networks and the Internet of Things

The Internet of Things (IoT) is becoming an increasingly growing topic of interest in the research community. Its requirements meet those of the next generation 5G mobile communication system which is expected to be an enabling technology for IoT, where networks of large numbers of sensors require massive connectivity demands. As polar codes have strongly entered into action within the standardization of 5G, this paper proposes and investigates the use of systematic polar codes for joint-source channel coding of correlated sources thus allowing, on one hand, the compression of the volume of data to be transmitted over the network, and on the other hand, the protection of this data from channel impairments. Results show that systematic polar codes can achieve a distributed compression with rates close to the theoretical bound, with better error rates obtained for larger blocks. However, stronger compression and shorter block lengths allow for a better robustness against transmission errors.

Finite-Length Linear Schemes for Joint Source-Channel Coding over Gaussian Broadcast Channels with Feedback

In this paper, we study linear encoding for a pair of correlated Gaussian sources transmitted over a two-user Gaussian broadcast channel in the presence of unit-delay noiseless feedback, abbreviated as the GBCF. Each pair of source samples is transmitted using a linear transmission scheme in a finite number of channel uses. We investigate three linear transmission schemes: A scheme based on the Ozarow–Leung (OL) code, a scheme based on the linear quadratic Gaussian (LQG) code of Ardestanizadeh et al., and a novel scheme derived in this paper using a dynamic programming (DP) approach. For the OL and LQG schemes we present lower and upper bounds on the minimal number of channel uses needed to achieve a target mean-square error (MSE) pair. For the LQG scheme in the symmetric setting, we identify the optimal scaling of the sources, which results in a significant improvement of its finite horizon performance, and, in addition, characterize the (exact) minimal number of channel uses required to achieve a target MSE. Finally, for the symmetric setting, we show that for any fixed and finite number of channel uses, the DP scheme achieves an MSE lower than the MSE achieved by either the LQG or the OL schemes.

Joint Source-Channel Coding of JPEG 2000 Image Transmission Over Two-Way Multi-Relay Networks.

In this paper, we develop a two-way multi-relay scheme for JPEG 2000 image transmission. We adopt a modified time-division broadcast cooperative protocol, and derive its power allocation and relay selection under a fairness constraint. The symbol error probability of the optimal system configuration is then derived. After that, a joint source-channel coding (JSCC) problem is formulated to find the optimal number of JPEG 2000 quality layers for the image and the number of channel coding packets for each JPEG 2000 codeblock that can minimize the reconstructed image distortion for the two users, subject to a rate constraint. Two fast algorithms based on dynamic programming and branch and bound are then developed. Simulation demonstrates that the proposed JSCC scheme achieves better performance and lower complexity than other similar transmission systems.

Knowledge-Enhanced Mobile Video Broadcasting Framework With Cloud Support

The convergence of mobile communications and cloud computing facilitates the cross-layer network design and content-assisted communication. Mobile video broadcasting can benefit from this trend by utilizing joint source-channel coding and strong information correlation in clouds. In this paper, a knowledge-enhanced mobile video broadcasting (KMV-Cast) is proposed. The KMV-Cast is built on a linear video transmission instead of a traditional digital video system, and exploits the hierarchical Bayesian model to integrate the correlated information into the video reconstruction at the receiver. The correlated information is distilled to obtain its intrinsic features, and the Bayesian estimation algorithm is used to maximize the video quality. The KMV-Cast system consists of both likelihood broadcasting and prior knowledge broadcasting. The simulation results show that the proposed KMV-Cast scheme outperforms the typical linear video transmission scheme called Softcast, and achieves 8 dB more of the peak signal-to-noise ratio (PSNR) gain at low-SNR channels (i.e., −10 dB), and 5 dB more of PSNR gain at high-SNR channels (i.e., 25 dB). Compared with the traditional digital video system, the proposed scheme has 7 dB more of PSNR gain than the JPEG2000 + 802.11a scheme at a 10-dB channel SNR.

Soft decoding algorithms for optimized JPEG 2000 wireless transmission over realistic MIMO-OFDM systems

In this paper, we investigate a new cross layer PHYsical/APPlication (PHY-APP) communication strategy for scalable JPEG 2000 wireless image transmission over a realistic Multiple-Input Multiple-Output (MIMO) system. To exploit the channel diversity, we use a closed-loop MIMO-OFDM scheme. In the proposed scheme, the MIMO channel is decomposed into several hierarchical Single-Input Single-Output (SISO) subchannels by using a precoding approach. The scalable bitstream is divided into hierarchical quality layers which are passing through these SISO subchannels. In this paper, we propose a Joint Source-Channel (JSC) decoding approach based on soft-inputs decoding techniques to decrease the error rates at the reception without introducing extra redundancy. This scheme involves the serial concatenation of a soft-input soft-output Reed-Solomon (RS) decoder and a soft-input arithmetic decoder that were integrated into the JPEG 2000 wireless decoder. The objective of our approach is to guarantee the Quality of Service (QoS) required by the user for varying channel states. To this end, a link adaption strategy adjusting all the systems parameters of each SISO sub-channel (number of used subchannels, modulation order, Forward Error Correction (FEC) code capability, source coding rate) is also adopted in order to maximize the image visual quality at the reception. Thus, Unequal Error Protection (UEP), Unequal Power Allocation (UPA), adaptive modulation and source coding rate are provided for each quality layer. Simulation results of the optimized adaptive strategy illustrate good image quality improvements at the receiver side compared to a non adaptive strategy, with significant Peak Signal to Noise Ratio (PSNR) gains, especially for a realistic noisy channel provided by a 3D ray-tracing software.

Partially Block Markov Superposition Transmission of a Gaussian Source With Nested Lattice Codes

This paper studies the transmission of Gaussian sources through additive white Gaussian noise channels in bandwidth expansion regime, i.e., the channel bandwidth is greater than the source bandwidth. To mitigate the error propagation phenomenon of conventional digital transmission schemes, we propose in this paper a new capacity-approaching joint source channel coding (JSCC) scheme based on partially block Markov superposition transmission (BMST) of nested lattice codes. In the proposed scheme, first, the Gaussian source sequence is discretized by a lattice-based quantizer, resulting in a sequence of lattice points. Second, these lattice points are encoded by a short systematic group code. Third, the coded sequence is partitioned into blocks of equal length and then transmitted in the BMST manner. The main characteristics of the proposed JSCC scheme include: 1) entropy coding is not used explicitly and 2) only parity-check sequence is superimposed, hence, termed partially BMST. This is different from the original BMST. To show the superior performance of the proposed scheme, we present extensive simulation results which show that the proposed scheme performs within 1 dB of the Shannon limits. Hence, the proposed scheme provides an attractive candidate for transmission of Gaussian sources.

On Reconstructing Linear Combinations of Correlated Gaussian Sources Over a MAC

In this letter, we study the joint source-channel coding problem of communicating the linear functions of correlated Gaussian sources over a Gaussian multiple access channel. In this setup, each transmitter observes one of two correlated sources. The receiver aims to reconstruct a linear combination of both correlated Gaussian sources within an average distortion level. For this setup, we first obtain a new lower bound on the achievable distortion and then, we propose a novel lattice-based hybrid transmission scheme and its achievable distortion is derived. We show that our proposed scheme can achieve the optimal distortion under some conditions.

Joint Source-Channel Coding and Digital Modulation Technique with Index Assignment Optimization

Channel optimized Index Assignment (IA) of source codeword is an approach to improve the transmission error resilience without the addition of extra bits and coding/decoding complexity. In this paper, we study the IA scheme with consideration to the given modulation technique. This study also presents an IA scheme for joint source channel coding and modulation technique for the general case when the codeword is not required to correspond to a modulation symbol and to occupy consecutive bits of the transmitted bitstream as some prior works. Besides the improvement in channel error robustness for the traditional IA approach, the proposed scheme can be combined with other techniques of mitigating or controlling the channel error when needed (in systems with high reliability or transmission of important codeword) such as Cyclic Redundancy Check (CRC), Forward Error Correction (FEC) coding and interleaving. We also consider the combination of the IA approach and FEC coding and the effectiveness of the proposed scheme is confirmed by experiments.

Distributed Source–Channel Coding Using Reduced-Complexity Syndrome-Based TTCM

In the context of distributed joint source–channel coding, we conceive reduced-complexity turbo trellis coded modulation (TTCM)-aided syndrome-based block decoding for estimating the cross-over probability $p_{e}$ of the binary symmetric channel, which models the correlation between a pair of sources. Our joint decoder achieves an accurate correlation estimation for varying correlation coefficients at 3 dB lower SNR, than conventional TTCM decoder, despite its considerable complexity reduction.

Comments on “Approximate Characterizations for the Gaussian Source Broadcast Distortion Region”

Recently, Tian et al. [1] considered joint source-channel coding of transmitting a Gaussian source over $K$-user Gaussian broadcast channel, and derived an outer bound on the admissible distortion region. In [1], they stated "due to its nonlinear form, it appears difficult to determine whether it is always looser than the trivial outer bound in all distortion regimes with bandwidth compression". However, in this correspondence we solve this problem and prove that for the bandwidth expansion case ($K\geq2$), this outer bound is strictly tighter than the trivial outer bound with each user being optimal in the point-to-point setting; while for the bandwidth compression or bandwidth match case, this outer bound actually degenerates to the trivial outer bound. Therefore, our results imply that on one hand, the outer bound given in [1] is nontrivial only for Gaussian broadcast communication ($K\geq2$) with bandwidth expansion; on the other hand, unfortunately, no nontrivial outer bound exists so far for Gaussian broadcast communication ($K\geq2$) with bandwidth compression.

A Simplified Joint Source and Channel Coding System for Data Transmission over Fading Channel

The major challenge with multimedia communication lies in the demand for higher data rates with better quality of service and lower latency over the wireless channel. Multimedia content is usually source encoded with variable length codes (VLCs) for optimizing bandwidth utilization. VLCs, even though uniquely decodable, suffer from the problem of error propagation. A single bit error can cause an entire block of data to be decoded wrongly, because the ending of a codeword and the beginning of the next can no longer be determined correctly. Several joint source-channel coding (JSCC) techniques are studied in literature to have efficient source coding with resilience to channel errors, but such methods pose a prohibitively high computational complexity. A variant of JSCC for efficient transmission of information is presented in this paper. The information text is encoded by reversible VLC (RVLC) and corresponding to it, a header sequence is generated. Since the headers are critical in decoding a block, they are channel coded with convolution code to protect from errors. Orthogonal frequency division multiplexing is used to provide high data rate communication and robustness to multipath fading. The performance of the system is analysed over Rayleigh fading channel in terms letter error rate (LER) and computational complexity. The proposed method is seen to provide a good LER performance at moderate to high signal to noise ratio, along with minimal computational complexity, when compared with the contemporary JSCC based schemes. Theoretical performance bounds for the error rate of the proposed system are also derived.

Joint source–channel coding for band‐limited backhauls in coordinated multi‐point systems

Coordinated multi-point (CoMP) transmission has been considered in the 3GPP long-term evolution advanced standard and beyond networks to improve the system throughput and coverage, particularly for cell-edge users. However, in practice the global channel state information (CSI) required by the coordinated points is usually transmitted by the band-limited backhauls, which degrades the performance of CoMP due to the erroneous backhaul transmission via the insufficient bandwidth. To address this problem, the authors propose a joint source–channel coding scheme for the backhaul transmission. They choose wavelet transform to compress the source CSI, and furthermore use irregular low-density parity-check codes to realise unequal error protection. They theoretically analyse how the joint coding affects the performance of CoMP. A trade-off between the compression ratio and channel coding gain is given. The numerical results verify that the proposed scheme can improve the performance of CoMP with band-limited backhauls.

Multi-Class Source-Channel Coding

This paper studies an almost-lossless source-channel coding scheme in which source messages are assigned to different classes and encoded with a channel code that depends on the class index. The code performance is analyzed by means of random-coding error exponents and validated by simulation of a low-complexity implementation using existing source and channel codes. While each class code can be seen as a concatenation of a source code and a channel code, the overall performance improves on that of separate source-channel coding and approaches that of joint source-channel coding when the number of classes increases.

Compensating Spectral Efficiency Loss of Wireless RF Energy Transfer With Analog Joint Source Channel Coding Compression

We investigate the use of discrete-time analog joint source channel coding (JSCC) in a wireless sensor network where the source of information is wirelessly powered by the destination. Wireless energy transfer and information transmission are multiplexed via a time-switching protocol. As a fraction of the time slot is spent for energy transfer, the source samples are saved and compressed using either parametric or non-parametric $N$ : $K$ dimension compression analog JSCC to transmit the information in the remaining fraction of the time slot. We analyze both matched and unmatched source and channel bandwidths. Moreover, we investigate the time-sharing parameter that optimizes the analog system performance and show that the proposed analog scheme can outperform a fully digital system.

Speeding Up Future Video Distribution via Channel-Aware Caching-Aided Coded Multicast

Future Internet usage will be dominated by the consumption of a rich variety of online multimedia services accessed from an exponentially growing number of multimedia capable mobile devices. As such, future Internet designs will be challenged to provide solutions that can deliver bandwidth-intensive, delay-sensitive, on-demand video-based services over increasingly crowded, bandwidth-limited wireless access networks. One of the main reasons for the bandwidth stress facing wireless network operators is the difficulty to exploit the multicast nature of the wireless medium when wireless users or access points rarely experience the same channel conditions or access the same content at the same time. In this paper, we present and analyze a novel wireless video delivery paradigm based on the combined use of channel-aware caching and coded multicasting that allows simultaneously serving multiple cache-enabled receivers that may be requesting different content and experiencing different channel conditions. To this end, we reformulate the caching-aided coded multicast problem as a joint source-channel coding problem and design an achievable scheme that preserves the cache-enabled multiplicative throughput gains of the error-free scenario,by guaranteeing per-receiver rates unaffected by the presence of receivers with worse channel conditions.

Zero-Delay Joint Source-Channel Coding in the Presence of Interference Known at the Encoder

Zero-delay transmission of a Gaussian source over an additive white Gaussian noise (AWGN) channel is considered in the presence of an independent additive Gaussian interference signal. The mean squared error (MSE) distortion is minimized under an average power constraint assuming that the interference signal is known at the transmitter. Optimality of simple linear transmission does not hold in this setting due to the presence of the known interference signal. While the optimal encoder-decoder pair remains an open problem, various non-linear transmission schemes are proposed in this paper. In particular, interference concentration (ICO) and one-dimensional lattice (1DL) strategies, using both uniform and non-uniform quantization of the interference signal, are studied. It is shown that, in contrast to typical scalar quantization of Gaussian sources, a non-uniform quantizer, whose quantization intervals become smaller as we go further from zero, improves the performance. Given that the optimal decoder is the minimum MSE (MMSE) estimator, a necessary condition for the optimality of the encoder is derived, and the numerically optimized encoder (NOE) satisfying this condition is obtained. Based on the numerical results, it is shown that 1DL with non-uniform quantization performs closer (compared with the other schemes) to the NOE while requiring significantly lower complexity.

Performance Enhancement of Cooperative Cognitive Relay Network using Multi Antennas Multi Hopping Techniques

In this paper, two systems will be introduced to improve the performance of Cooperative Cognitive Relay Network (CCRN). The first is Compress-and-Forward (CF) relay scheme based on joint source-channel coding for threeterminal classical relay network. Simulation results show that CF relay scheme gives remarkable performance gains over other cooperation strategies such as decode-and-forward and amplify-and-forward in this scenario where both source-relay and relay destination links have low signal-to-noise ratios. The second system is multi-hopping cooperative relaying with multi-antennas using decode and forward scheme. Using multi-hopping with multi-antennas techniques in CCRN gives a remarkable enhancement in the performance than using only one hop with single antenna system.

Enhancing the Protection of Digital Images against Tampering Using Joint Source Channel Coding

Enhancing the Protection of Digital Images against Tampering Using Joint Source Channel Coding