Coding Transmission Research Articles

Generative Joint Source-Channel Coding for Semantic Image Transmission

Recent works have shown that joint source-channel coding (JSCC) schemes using deep neural networks (DNNs), called DeepJSCC, provide promising results in wireless image transmission. However, these methods mostly focus on the distortion of the reconstructed signals with respect to the input image, rather than their perception by humans. However, focusing on traditional distortion metrics alone does not necessarily result in high perceptual quality, especially in extreme physical conditions, such as very low bandwidth compression ratio (BCR) and low signal-to-noise ratio (SNR) regimes. In this work, we propose two novel JSCC schemes that leverage the perceptual quality of deep generative models (DGMs) for wireless image transmission, namely InverseJSCC and GenerativeJSCC. While the former is an inverse problem approach to DeepJSCC, the latter is an end-to-end optimized JSCC scheme. In both, we optimize a weighted sum of mean squared error (MSE) and learned perceptual image patch similarity (LPIPS) losses, which capture more semantic similarities than other distortion metrics. InverseJSCC performs denoising on the distorted reconstructions of a DeepJSCC model by solving an inverse optimization problem using the pre-trained style-based generative adversarial network (StyleGAN). Our simulation results show that InverseJSCC significantly improves the state-of-the-art DeepJSCC in terms of perceptual quality in edge cases. In GenerativeJSCC, we carry out end-to-end training of an encoder and a StyleGAN-based decoder, and show that GenerativeJSCC significantly outperforms DeepJSCC both in terms of distortion and perceptual quality.

CRC-Aided Sparse Regression Codes for Unsourced Random Access

This letter considers a coding scheme for unsourced random access (URA) based on sparse regression codes (SPARCs). In particular, an efficient concatenated coding scheme is proposed, which concatenates SPARCs and cyclic redundancy check-based block Markov superposition transmission (CRC-BMST) codes. A hybrid decoder consisting of a successive cancellation algorithm and a simplified approximated message passing (AMP) algorithm is presented for inner SPARCs, and an improved tree decoder is proposed for outer CRC-BMST codes by introducing a pruning technique. Simulation results show the proposed coding scheme outperforms the coded compressed sensing (CCS) scheme with lower computational complexity.

BER performance of an FSOC system over atmospheric turbulence channels based on computational temporal ghost imaging.

In a free space optical communication (FSOC) system, atmospheric turbulence will increase the bit error ratio (BER) and impair FSOC link reliability. Since computational temporal ghost imaging (CTGI) has anti-interference, we present an FSOC system over atmospheric turbulence based on CTGI. The simulation results show that the BER performance of CTGI is better than on-off keying under different atmospheric turbulence regimes. To improve the performance of the CTGI scheme, the influence of the number of transmission samples and code length is analyzed. It is shown that BER performance improves with the increment of the number of samples, while code length has no impact. This scheme provides an idea for reliable communication over atmospheric turbulence and an important reference for improving wireless optical communication in an extreme environment.

Station Grouping Mechanism using Machine Learning Approach for IEEE 802.11ah

IEEE 802.11ah, also known as Wi-Fi HaLow, improves the scalability of the Internet of Things (IoT) by connecting a large number of low-power devices. IEEE 802.11ah has developed a novel feature called Restricted Access Window (RAW) that aims to address one of the main problems of the IoT: excessive channel contention in large sensor networks. All stations can access the channel from the same group when using RAW, which allows the Access Point (AP) to split stations into different groups. Existing station grouping schemes support only the homogeneous traffic scenarios, having the same data transmission interval, packet size, and Modulation and Coding Scheme (MCS). In this paper, we highlight two contributions to solving this problem. The first is a Machine Learning (ML) based model that predicts RAW configuration parameters and performance under specific network conditions. It predicts accurately and is very quick to train. Second, a technique for a channel access mechanism that uses an ML model to determine the optimal RAW station grouping configuration for dynamic traffic conditions and heterogeneous stations. We compare our ML-based model with the existing state-of-the-art solutions. We calculated the performance of our proposed model and compared it to traditional 802.11ah and the Traffic Adaptive RAW Optimization Algorithm (TAROA). The results show that our proposed model outperforms a significant improvement in terms of throughput, packet received ratio, delay, and execution time.

Deception attack detection based on bandwidth allocation for switched systems with quantization

This article discusses a more practical deception attack on the continuous-time switched systems, i.e. a malicious attacker tampers with the binary 01 code transmitted through the network. Assume that the switching is slow enough and the attacker’s energy is limited, we propose a coding transmission strategy based on bandwidth allocation, which selects a part of the network bandwidth for reverse data transmission. Under such strategy, partial detection of attacks and synchronous update of quantization rules are realized. Combined the increasing/decreasing rate of Lyapunov function with the success rate of attack detection, the sufficient conditions ensuring the mean square exponential stability of the system are given. Taking the maximum convergence rate as a performance indicator, the optimal bandwidth allocation scheme is provided for the specific values, which realizes a trade-off between attack detection rate and quantization error. Two-tank system is adopted to illustrate the effectiveness of the theoretical analysis.

Karakter Eğitiminin Sosyolojik Temelleri

Character and values education has gained importance in many societies since the first moments of the emergence of the phenomenon of education, and moreover, it has formed the basis and ultimate goal of educational processes. While values education focuses more on the adoption of the current values in society, character education focuses on universal virtues such as wisdom, justice, love, courage, honesty, etc. Character education is a sociological process by nature. Character development in students is under the influence of family, school and social environment as well as individual characteristics. Character education is based on the socialization of the individual. In this respect, a good individual is a sufficiently socialized individual. School and family constitute the basis for the formation and transmission of moral codes in the individual. In this respect, while some educational sociologists consider this socialization process as an automatic process outside the individual’s preferences, some contemporary sociologists have put forward the concept of individual character with a less deterministic perspective. Keyword: Character, character education, sociological foundations of character

Rapid adaptation of primate LGN neurons to drifting grating stimulation.

The visual system needs to dynamically adapt to changing environments. Much is known about the adaptive effects of constant stimulation over prolonged periods. However, there are open questions regarding adaptation to stimuli that are changing over time, interrupted, or repeated. Feature-specific adaptation to repeating stimuli has been shown to occur as early as primary visual cortex (V1), but there is also evidence for more generalized, fatigue-like adaptation that might occur at an earlier stage of processing. Here, we show adaptation in the lateral geniculate nucleus (LGN) of awake, fixating monkeys following brief (1 s) exposure to repeated cycles of a 4-Hz drifting grating. We examined the relative change of each neuron's response across successive (repeated) grating cycles. We found that neurons from all cell classes (parvocellular, magnocellular, and koniocellular) showed significant adaptation. However, only magnocellular neurons showed adaptation when responses were averaged to a population response. In contrast to firing rates, response variability was largely unaffected. Finally, adaptation was comparable between monocular and binocular stimulation, suggesting that rapid LGN adaptation is monocular in nature.NEW & NOTEWORTHY Neural adaptation can be defined as reduction of spiking responses following repeated or prolonged stimulation. Adaptation helps adjust neural responsiveness to avoid saturation and has been suggested to improve perceptual selectivity, information transmission, and predictive coding. Here, we report rapid adaptation to repeated cycles of gratings drifting over the receptive field of neurons at the earliest site of postretinal processing, the lateral geniculate nucleus of the thalamus.

Enhancing underwater VLC with spatial division transmission and pairwise coding.

In this paper, we propose and evaluate two spatial division transmission (SDT) schemes, including spatial division diversity (SDD) and spatial division multiplexing (SDM), for underwater visible light communication (UVLC) systems. Moreover, three pairwise coding (PWC) schemes, including two one-dimensional PWC (1D-PWC) schemes, i.e., subcarrier PWC (SC-PWC) and spatial channel PWC (SCH-PWC), and one two-dimensional PWC (2D-PWC) scheme are further applied for signal-to-noise ratio (SNR) imbalance mitigation in the UVLC systems using SDD and SDM with orthogonal frequency division multiplexing (OFDM) modulation. The feasibility and superiority of applying SDD and SDM with various PWC schemes in a practical bandlimited two-channel OFDM-based UVLC system have been verified through both numerical simulations and hardware experiments. The obtained results show that the performance of SDD and SDM schemes are largely determined by both the overall SNR imbalance and the system spectral efficiency. Moreover, the experimental results demonstrate the robustness of SDM with 2D-PWC against bubble turbulence. Specifically, SDM with 2D-PWC can obtain bit error rates (BERs) under the 7% forward error correction (FEC) coding limit of 3.8 × 10-3 with a probability higher than 96% for a signal bandwidth of 70 MHz and a spectral efficiency of 8 bits/s/Hz, achieving an overall data rate of 560 Mbits/s.

Fountain Codes for Reliable and Deterministic Packet Transmission in Industrial Cloud Control Systems

With the thriving of digitalization in industry and the rapid development of cloud computing and Internet of Things (IoT), it has become a growing trend to integrate industrial control with the cloud platform to form industrial cloud control systems (ICCSs). However, ICCSs bring great challenges to legacy communication networks, especially, wireless networks, on reliability and determinacy. This article utilizes fountain code as application-layer coding to provide high-reliability low-latency deterministic communication for ICCSs. According to the simulation results, fountain code scheme, especially, RaptorQ code significantly improves communication reliability. The performance difference of fountain codes between time-critical use cases and nontime-critical use cases provides another perspective to analyze and evaluate fountain codes. Then, we propose a self-adaptive coding parameter selection method based on different industrial use cases, to better meet the communication requirements and reduce the coding cost.

Performance on Cognitive Broadcasting Networks Employing Fountain Codes and Maximal Ratio Transmission

Performance on Cognitive Broadcasting Networks Employing Fountain Codes and Maximal Ratio Transmission

Delayed Bit-Interleaved Coded Transmission for Spatial Modulation

It has been shown that delayed bit-interleaved coded modulation (BICM) performs better than the original BICM in some scenarios. This paper is intended to enhance the performance of low-density parity-check (LDPC) coded spatial modulation. To this end, we present the delayed bit-interleaved coded spatial modulation (DBICSM) when LDPC codes are employed. The resulting transmission scheme is termed LDPC-DBICSM. Firstly, we present the encoding structure of the LDPC-DBICSM. Secondly, we present a non-iterative decoder that works only on two blocks of received sequences for the LDPC-BICSM. Thirdly, we present an estimated lower bound on the performance of the LDPC-DBICSM. Finally, we present extensive simulation results to show the performance advantages of the LDPC-DBICSM when compared to the LDPC-BICSM. Particularly, a performance gain of about 1.25 dB is obtained at a bit error rate (BER) of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-8</sup> .

Achievable rate optimization for space–time block code-aided cooperative NOMA with energy harvesting

Cooperative non-orthogonal multiple access (C-NOMA) is one of the promising techniques that support the massive connectivity of users and improve the fair allocation of network resources. However, the performance of C-NOMA networks is restricted due to the complexity introduced by multiple user-assisted relays coupled with their energy consumption bottleneck. In this paper, we develop a low-complexity network framework with the main goal of achieving a fair and optimal achievable rate. For the network model, we adopt a Space–time block code transmission scheme to increase the spatial diversity of the network with a minimum number of relays. Further to this, we consider a radio frequency-based energy harvesting technique known as simultaneous wireless information and power transfer in order to compensate for energy expended by the relays over the cooperating transmission links. Based on the proposed network model, we solve the achievable rate maximization problem from the perspective of joint optimal power allocation factor and power splitting ratio. Due to the non-convex nature of the problem and to also ensure fair resource allocation, we propose a low-complexity solution based on the concept of Nash bargaining solution. Further to this, we evaluate the achievable rate and energy efficiency of the system. Simulation results show that our proposed solution outperforms the baseline approaches.

Polar Coded Cooperative Differential Spatial Modulation Based on Plotkin Construction and Quasi-Uniform Puncturing

Coded-cooperation combines virtual MIMO transmission and channel coding to achieve forward error correction while achieving diversity gain. It is a promising technology in 5G communications. The polar code is the only channel coding technology that can theoretically achieve Shannon limit transmission, which make it the preferred coding technology in cooperative communication. In this paper, we proposed a new wireless communication scheme, which is a polar coded cooperative spatial modulation schemes based on Plotkin construction and Quasi-uniform puncturing (QUP). First, we adopt Plotkin construction based on the inverted codeword of the polar code to get a cooperation method, which offer a significant improvement in performance on the polar code cooperation under fading channels. We analyze the decoding characteristics of the inverted codewords and then introduces the QUP method to improve the cooperation benefits. At the same time, we extend the cooperation scheme with differential spatial modulation for the proposed coded cooperative schemes. The new coded-cooperation scheme outperforms its coded non-cooperative counterpart schemes under identical conditions, as expected. Monte Carlo simulated results show that the proposed cooperative schemes outperform their corresponding non-cooperative counterpart schemes, by the gain of 2.5 dB with 1024 code length and 0.25 code rate under identical conditions.

A Corpus-based Analysis of The Time Machine: From the Perspective of Literary Stylistics

From a corpus stylistic perspective, this paper analyses H.G. Wells’ book The Time Machine at the level of punctuation and vocabulary, etc. By utilizing the Sketch Engine and AntConc software, this paper finds that the author excels at using a large number of content words to present information and makes extensive use of transitive conjunctions in the course of the narration in order to present information that is difficult for the readers to anticipate. Based on the above methods, the author creates a contextual atmosphere suitable for the construction of the scientific discourse, eventually achieving an efficient degree of language code transmission with readers.

Low-density parity-check codes: Highway to channel capacity

Low-density parity-check (LDPC) codes are not only capacity-approaching, but also greatly suitable for high-throughput implementation. Thus, they are the most popular codes for high-speed data transmission in the past two decades. Thanks to the low-density property of their parity-check matrices, the optimal maximum a posteriori probability decoding of LDPC codes can be approximated by message-passing decoding with linear complexity and highly parallel nature. Then, it reveals that the approximation has to carry on Tanner graphs without short cycles and small trapping sets. Last, it demonstrates that well-designed LDPC codes with the aid of computer simulation and asymptotic analysis tools are able to approach the channel capacity. Moreover, quasi-cyclic (QC) structure is introduced to significantly facilitate their high-throughput implementation. In fact, compared to the other capacity-approaching codes, QC-LDPC codes can provide better area-efficiency and energy-efficiency. As a result, they are widely applied in numerous communication systems, e.g., Landsat satellites, Chang'e Chinese Lunar mission, 5G mobile communications and so on. What's more, its extension to non-binary Galois fields has been adopted as the channel coding scheme for BeiDou navigation satellite system.

Development of Code‐Editable Multicolor Chemiluminescent Hydrogels and Their Application in the Detection of Sarcosine Using Portable Devices

AbstractConventional luminol chemiluminescence (CL) is widely used in imaging and analytical assays. As far as we can search, there are no studies on the use of CL for information encryption and protection. Here, a novel CL hydrogel is developed. A rapid color visualization of sarcosine in urine using a mobile phone camera is achieved based on CL energy resonance transfer. Four different colors of CL hydrogels are prepared by adding different ratios of rhodamine B or fluorescein. In the multicolor CL hydrogels, activated CL can generate conventional multicolor code shift and original white light. The luminescence duration and the cause of the white light are analyzed using CL spectroscopy. Sarcosine oxidase is replaced with sarcosine in the multicolor CL hydrogels to obtain the translation of editable code, which facilitates the secondary information encryption and code transmissions. The effective luminescence time of these hydrogels are short (13–50 min), and code can be deleted naturally.

A generalization of properly colored paths and cycles in edge-colored graphs

A properly colored walk, is a walk where every two consecutive edges have different colors, including the first and last edges in the case when the walk is closed. Properly colored walks have shown to be an effective way to model certain real applications. In view of this, it is natural to ask about the existence of properly colored walks with restrictions on the transitions of colors allowed in the edges of a graph. Let H be a graph, possibly with loops, and G a graph. We will say that G is H-colored iff there exists a function c:E(G)⟶V(H). A path (v0,v1,⋯,vk) in G is an H-path whenever (c(v0v1),⋯,c(vk−1vk)) is a walk in H; in particular, a cycle (v0,v1,⋯,vk,v0) is an H-cycle iff (c(v0v1),c(v1v2),⋯,c(vk−1vk),c(vkv0),c(v0v1)) is a walk in H. Hence, the graph H determines what color transitions are allowed in a walk. An interesting application of H-walks states as follows: suppose that it is required to send a message through a hostile environment (network), in which the edges are colored with its transmission code; in order to make more difficult the decoding task, it is necessary to avoid not only monochromatic transitions, but some specific color transitions that make easier that task. Some authors have studied the existence of H-cycles in an H-colored graph, saying nothing about its length. In this paper, we give conditions that imply the existence of H-paths and H-cycles of certain length, in an H-colored graph with a given structure. As a consequence of the main results, we obtain known theorems in the theory of properly colored walks.

Minimum-Rate Spectrum-Blind Sampling Based on Sparse-Graph Codes

We study the problem of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">spectrum-blind</i> sampling, that is, sampling signals with sparse spectra whose frequency support is unknown. The minimum sampling rate for this class of signals has been established as twice the measure of its frequency support; however, constructive sampling schemes that achieve this minimum rate are not known to exist, to the best of our knowledge. We propose a novel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">constructive</i> sampling framework by leveraging a mix of tools from <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">modern coding theory</i> , which has been largely untapped in the field of sampling. We make interesting connections between the fundamental problem of spectrum-blind sampling, and that of designing erasure-correcting codes based on sparse graphs, which have both theoretically and practically revolutionized the design of modern communication systems. Our key idea is to cleverly exploit, rather than avoid, the resulting aliasing artifacts induced by subsampling, which introduce linear mixing of spectral components in the form of parity constraints for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sparse-graph codes</i> . We achieve this by subsampling the input signal after filtering it using a carefully designed ‘sparse-graph coded filter-bank’ structure, where the pass-band on/off patterns of the filters are designed to match the parity-check constraints of a sparse-graph code. We show that the signal reconstruction under this sampling scheme is equivalent to the fast message-passing based “peeling” decoding of sparse-graph codes for reliable transmission over erasure channels. Most importantly, we further show that the achievable sampling rate is determined by the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rate</i> of the sparse-graph codes used in the filter bank. As a result, based on insights derived from the design of capacity-achieving sparse-graph codes (such as Low Density Parity Check codes), we can <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">simultaneously</i> approach the minimum sampling rate for spectrum-blind sampling and low computational complexity based on fast peeling-based decoding with operations per unit of time scaling <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">linearly</i> with the sampling rate.

Sparse Vector Coding for Short-Packet Transmission on Industrial Communications: Reference Architecture and Design Challenges

Reliable, fast, and deterministic communications are fundamental for future industrial wireless systems. This goal requires multiple cooperating technologies that pertain to different areas of the communication arena. The weight of the waveform and coding technique choices are critical to match industrial use cases' reliability and latency requirements. Specifically, this article contributes to the field of channel coding in wireless fieldbus links. Classical block coding schemes were designed to maximize information bit rates without stringent latency requirements. Their performance in applications that use short messages degrades significantly. Recently, sparse vector coding (SVC) has been proposed as a coding approach suitable for short-packet communications with moderate complexity and low processing latency. This article presents a comprehensive analysis of SVC and a reference communication framework for its implementation on a wireless system. A set of simulations is also designed to establish the cross correlation between the different parameters involved in the code design. As a result, the coding matrix has been identified as a critical parameter that can improve coding performance. In addition, this article includes two new procedures for determining the matrix that could lead to a gain of up to 2 dB with respect to the current state of the art.

Adaptive Rate Polar Code for DCT-Based Digital Image Transmission

Adaptive Rate Polar Code for DCT-Based Digital Image Transmission