Automatic Repeat Request Research Articles

Hybrid Duplex Medium Access Control Protocol for Tsunami Early Warning Systems in Underwater Networks

Tsunamis are devastating natural phenomena that cause extensive damage to both human life and infrastructure. To mitigate such impacts, tsunami early warning systems have been deployed globally. South Korea has also initiated a project to install a tsunami warning system to monitor its surrounding seas. To ensure reliable warning decisions, various types of data must be combined, but efficiently transmitting heterogeneous data poses a challenge due to the unique characteristics of underwater acoustic communication. Therefore, this paper proposes a Hybrid Duplex Medium Access Control (HDMAC) protocol designed for a tsunami warning system, with a specific focus on heterogeneous data transmission. HDMAC efficiently handles both seismic and environmental data by utilizing hybrid duplexing, which combines frequency duplex for seismic data with time duplex for environmental data. The protocol addresses the distinct transmission requirements for each data type by optimizing channel utilization through a group Automatic Repeat request (ARQ) scheme and packet size adjustment. Theoretical analysis predicts that HDMAC can achieve a channel utilization of up to 0.91 in smaller networks and 0.64 in larger networks. HDMAC is validated through simulations, and the simulation results closely match these predictions. The simulation results demonstrate the efficiency of HDMAC in supporting real-time submarine earthquake monitoring systems.

Reliability and Security Performances Analysis of Rate Splitting Based VLC System With HARQ

This work first attempts to investigate the reliability and physical layer security (PLS) performances of a rate splitting (RS) based visible light communication (VLC) system with one trusted user and one untrusted user. Specifically, the hybrid automatic repeat request (HARQ) protocol is adopted at the trusted user and the movement of users is assumed to be subject to the random way point (RWP) model with four decoding strategies considered at receiver side. The exact closed-form expressions of outage probability (OP) for both users are then obtained, and the analytical expressions of secrecy outage probability (SOP), reliable and secure transmission probability (RSP), and effective secrecy throughput (EST) of trusted user are also mathematically derived. Through simulations, it is found that to guarantee the reliability and PLS performances, the trusted user should first decode the untrusted user’s private stream and the untrusted user should first decode the trusted user’s private stream. Besides, the reliability and PLS performances of RS-VLC system could be enhanced with the appropriate increase in the maximum transmission round of HARQ with the best decoding strategy. Moreover, they could be further enhanced by the proper common stream power allocation coefficient. This work will benefit the research and development of indoor VLC system.

Hybrid Automatic Repeat Request for Downlink Rate-Splitting Multiple Access

Hybrid Automatic Repeat Request for Downlink Rate-Splitting Multiple Access

A Channel-Sensing-Based Multipath Multihop Cooperative Transmission Mechanism for UE Aggregation in Asymmetric IoE Scenarios

With the continuous progress and development of technology, the Internet of Everything (IoE) is gradually becoming a research hotspot. More companies and research institutes are focusing on the connectivity and transmission between multiple devices in asymmetric networks, such as V2X, Industrial Internet of Things (IIoT), environmental monitoring, disaster management, agriculture, and so on. The number of devices and business volume of these applications have rapidly increased in recent years, which will lead to a large load of terminals and affect the transmission efficiency of IoE data transmission. To deal with this issue, it has been proposed to perform data transmission via multipath cooperative transmission with multihop transmission. This approach aims to improve transmission latency, energy consumption, reliability, and throughput. This paper designs a channel-sensing-based cooperative transmission mechanism (CSCTM) with hybrid automatic repeat request (HARQ) for user equipment (UE) aggregation mechanism in future asymmetric IoE scenarios, which ensures that IoE devices data can be transmitted quickly and reliably, and supports real-time data processing and analysis. The main contents of this proposed method include strategies of cooperative transmission and redundancy version (RV) determination, a joint combination of decoding process at the receiving side, and a design of transmission priority through ascending offset sort (AOS) algorithm based on channel sensing. In addition, multihop technology is designed for the multipath cooperative transmission strategy, which enables cooperative nodes (CN) to help UE to transmit data. As a result, it can be obtained that CSCTM provides significant advancements in latency and energy consumption for the whole system. It demonstrates improvements in enhanced coverage, improved reliability, and minimized latency.

Robust AI Based Bio Inspired Protocol using GANs for Secure and Efficient Data Transmission in IoT to Minimize Data Loss

Objectives: To propose an AI-based protocol to enhance the reliability and security of IoT data transmission in a robust manner. Deep learning with bio-inspired methods is employed to address real-time challenges such as route optimization, data integrity, error recovery, and end-to-end delay in order to minimize data loss and maximize the transmission rate. Methods: Generative Adversarial Networks (GANs) are used to enhance the robustness of the protocol in combination with a bio-inspired Artificial Immune System (AIS) to detect IoT network anomalies and responds to malicious activities by using the adaptive learning capabilities of IS. Hybrid Automatic Repeat Request (HARQ), an error recovery method, is utilized to detect network errors in order to correct and retransmit data to the destination during error-prone network conditions. Queue learning action sets are used to discover the finest path for efficient data transmission. The OMNeT++ simulator is used to assess the performance of the proposed BIP-GANs protocol. The performance results are compared with the prevailing data transmission protocols, such as EAP-IFBA, DNN-CSO, and ALO-DHT. Findings: The suggested BIP-GANs data transmission protocol outperforms with promising results, with an energy consumption rate of 6%, 8 seconds data transmission speed, 6 second less delay rate, 98% robustness (security and confidentiality), 98.5% alive nodes, and 99% network life span, which is higher than the prevailing methods. Novelty: This research study provides a comprehensive solution to secure and efficient data transmission by integrating the AI-based bio-inspired BIP-GANs method to address the security and data transmission challenges of existing methods such as EAP-IFBA, DNN-CSO, and ALO-DHT in terms of energy consumption rate, transmission speed, delay rate, life span of the network, robustness, and number of alive nodes. Keywords: Artificial Intelligence, Generative Adversarial Networks, Error Recovery, Secured Data Transmission, Deep Learning, Bio­Inspired Algorithm

Simultaneous update of sensing and control data using free-ride codes in vehicular networks: An age and energy perspective

In real-time Internet of Things networks, age of information (AoI) and energy cost (EC) are generally deemed as two significant performance metrics to characterize the information freshness and energy efficiency. This paper aims at updating not just sensing data but sensing data and control data simultaneously in vehicular networks. By employing the promising free-ride coding mechanism, the randomly encoded control data is superposed on the low-density parity-check coded sensing data and then is sent to the receiver, consuming neither additional bandwidth nor transmission power. Considering the time and energy of both status update generation and transmission, the average AoI (AAoI) and average EC (AEC) expressions are derived for preemptive and blocking updating schemes with truncated automatic repeat request protocol. Numerical simulations present the AAoI of both sensing data and control data, as well as the AEC of the transmitter, which demonstrate that free-ride coding mechanism not only can improve the freshness of control data but impose an insignificant influence on the performance of sensing data. Moreover, comparison with the blocking scheme suggests that the preemptive one obtains the smaller AAoI but the larger AEC.

Performance implications of channel aware cooperative probing-GBN ARQ in the context of wireless body area networks

The advent of Wireless Body Area Networks (WBAN) in patient care has revolutionized the healthcare sector as patients can now be monitored continuously in real-time and as well remotely. Despite its significant advantages, WBAN encounters a notable challenge in the fading aspect, which undermines its effectiveness. Improving WBAN efficiency involves tackling signal fading, which is crucial. Cooperative communication offers a promising solution by introducing spatial diversity to counteract fading effects. We propose a scheme that uses cooperative communication and the Probing-Go Back N Automatic Repeat Request (P-GBN ARQ) technique to reduce the fading effect. The proposed method uses feedback to predict the channel's current state, and the probing interval is determined by the received signal's Average Fading Duration (AFD). The proposed scheme's performance is also assessed extensively through simulations employing various metrics. The results demonstrate a considerable improvement in throughput performance with the inclusion of knowledge about channel fading. The Bit Error Rate (BER) execution is compared with Selection Combiner (SC) and conventional Maximal Ratio Combining (MRC). At 10−3, the cooperative method achieves it at 13 dB SNR, whereas the direct approach reaches it at 24 dB SNR, requiring an additional 11 dB. The proposed approach minimizes BER, enhancing throughput and reliability in WBAN.

Resource-Efficient Multicast URLLC Service in 5G Systems.

Many emerging applications, such as factory automation, electric power distribution, and intelligent transportation systems, require multicast Ultra-Reliable Low-Latency Communications (mURLLC). Since 3GPP Release 17, 5G systems natively support multicast functionality, including multicast Hybrid Automatic Repeat Request and various feedback schemes. Although these features can be promising for mURLLC, the specifications and existing studies fall short in offering guidance on their efficient usage. This paper presents the first comprehensive system-level evaluation of mURLLC, leveraging insights from 3GPP specifications. It points out (i) how mURLLC differs from traditional multicast broadband wireless communications, and (ii) which approaches to provide mURLLC require changing the paradigm compared with the existing solutions. Finally, the paper provides recommendations on how to satisfy strict mURLLC requirements efficiently, i.e., with low channel resource consumption, which increases the capacity of 5G systems for mURLLC. Simulation results show that proper configuration of multicast mechanisms and the corresponding algorithms for mURLLC traffic can reduce resource consumption up to three times compared to the baseline solutions proposed for broadband multicast traffic, which significantly increases the system capacity.

Simulation and analysis of C-V2X data transmission in different traffic scenarios based on MAC layer scheduling algorithms

With the rapid development of communication technology, vehicles are becoming more and more intelligent, and Vehicle to Vehicle (V2V) communication has become an important cornerstone for the future intelligence of vehicles. Because of the high-reliability and low-latency characteristics of 5G networks, many applications can be realized by using Vehicle to Network (V2N) communications. Different applications have different requirements for Quality of Service (QoS), which should be met by the network, and the base station can use different scheduling methods to satisfy these different requirements. This paper focuses on the scheduler at the MAC layer in 5G base stations. The scheduler must handle both video signals and other communication signals transmitted by the vehicle, and must also consider Hybrid Automatic Repeat reQuest (HARQ) retransmissions. We performed a C-V2X signaling network transmission simulation by using OMNeT++. We considered urban and motorway, two public transportation scenarios. Different types of data are set to be transmitted in two scenarios. We used different scheduling schemes for data scheduling, then investigated the performance of these scheduling schemes for transmitting data. The methods and simulation experiments mentioned in this paper are important for practical generalization.

Energy Consumption Analysis for Continuous Phase Modulation in Smart-Grid Internet of Things of beyond 5G.

Wireless sensor network (WSN) underpinning the smart-grid Internet of Things (SG-IoT) has been a popular research topic in recent years due to its great potential for enabling a wide range of important applications. However, the energy consumption (EC) characteristic of sensor nodes is a key factor that affects the operational performance (e.g., lifetime of sensors) and the total cost of ownership of WSNs. In this paper, to find the modulation techniques suitable for WSNs, we investigate the EC characteristic of continuous phase modulation (CPM), which is an attractive modulation scheme candidate for WSNs because of its constant envelope property. We first develop an EC model for the sensor nodes of WSNs by considering the circuits and a typical communication protocol that relies on automatic repeat request (ARQ)-based retransmissions to ensure successful data delivery. Then, we use this model to analyze the EC characteristic of CPM under various configurations of modulation parameters. Furthermore, we compare the EC characteristic of CPM with that of other representative modulation schemes, such as offset quadrature phase-shift keying (OQPSK) and quadrature amplitude modulation (QAM), which are commonly used in communication protocols of WSNs. Our analysis and simulation results provide insights into the EC characteristics of multiple modulation schemes in the context of WSNs; thus, they are beneficial for designing energy-efficient SG-IoT in the beyond-5G (B5G) and the 6G era.

Post-Cancellation-Based LLR Refining for MIMO Multiple ARQ Systems

In multiple-input multiple-output (MIMO) multiple automatic repeat request (ARQ) systems, multiple streams with independent hybrid ARQ (HARQ) processes can be simultaneously sent. Thus, the interference from other streams can affect future retransmissions of a packet as well as the current transmission, and proper management of interference at the receiver is required. Therefore, in this paper, a post-cancellation-based log-likelihood ratio (LLR) refining scheme is proposed for MIMO multiple ARQ (MMARQ) systems. In the proposed scheme, after the end of the entire conventional reception procedure for packet decoding, LLR refining is performed for the non-terminated packets that will be sent during the next transmission time interval. For LLR refining, the packet cancellation is performed to cancel only the successfully decoded packets. Thus, the LLRs of the non-terminated packets are refined without any error propagation, including the inter-transmission error propagation. Consequently, the proposed scheme can compensate for the interference problem in MMARQ systems and improve system performance. In order to utilize the error detection results of decoded codewords, the proposed scheme should be performed after the end of the entire reception procedure for packet decoding. Therefore, as the post-processing scheme, the proposed scheme can be employed to any existing LLR-level combining-based MMARQ receiver without changing the original procedure. Simulation results verify that the proposed scheme can significantly improve the error performance and throughput of MMARQ systems, especially for hard-decision interference cancellation-based receivers and high-order modulation. In addition, compared with the conventional reception procedure, the proposed scheme requires a smaller computational complexity in most of the simulated SNR region. Therefore, the proposed LLR refining scheme can be considered as an effective and practical post-processing scheme for an MMARQ receiver.

Fragmentation of data packets in wireless sensor network with variable temperature and channel conditions

This study formalizes and solves the problem of minimizing the energy dissipated by a node in order to successfully transmit the initial data amount during one round of communication over a wireless channel affected by Rice fading under varying temperature conditions. In this work, the models for the temperature dependence of the parameters in an incoherent frequency shift key (FSK) demodulator are presented and investigated for the first time, taking into account both the frequency separation and the synchronization type of the clock generator. The studied orthogonality coefficients of FSK signals represent internal parameters in the proposed model of the incoherent Rice wireless channel. This model allows the analytical relationship between the bit error probability (BEP) and node heating temperature, signal fading depth in the channel (Rician K-factor), and signal-to-noise ratio (SNR) to be established.Since it is necessary to retransmit the entire data packet when an erroneous bit is detected in a communication system that uses an automatic repeat request, at high BEP values, it is recommended to fragment packets in order to improve the energy efficiency of the nodes. By using the developed models for calculating energy losses during the communication round, it was determined that optimal fragmentation options (OFO) for data packets can be identified within specific ranges of temperature and Rician K-factor, which includes the overhead costs for packeting and retransmission. As a result, OFO matrices of packets in the "temperature – K-factor" (t0–K) coordinate system were obtained for minimizing the energy loss of nodes at different SNR values. In our example of using TI CC2500 node transceivers for 90-day monitoring of corn vegetation, the t0K-Frag algorithm reduced node energy losses by a factor of K = 3.3 compared to the case of transmitting an unfragmented packet of initial length.

Short-packet communication for MIMO NOMA relay networks: BLER and AoI analysis

This work considers a multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) dual-hop relay system in which the size of signal packets is finite and the propagation environment follows the Nakagami-m distribution. Based on an approximation of the Gaussian Q-function, Riemann integral, and incomplete Gamma function, we derive the closed-form expressions of the block error rate (BLER), age of information (AoI), and latency of the proposed system in both exact and asymptotic cases. On the other hand, the automatic repeat request (ARQ) protocol and acknowledgment (ACK) are applied to confirm the accuracy of the receiving data packet process. Moreover, the maximal-ratio transmission (MRT), and maximal-ratio combining (MRC) are used to improve the BLER, AoI, and latency of the proposed system. The accuracy of mathematical analysis frameworks is confirmed by simulation results. The calculation results show that the considered system satisfies the requirement of ultra-reliable and low-latency communications (URLLC). The results also represent that the MIMO-NOMA system outperforms the MIMO-OMA system in terms of BLER performance. The results also provide insight into the optimizations of the power allocation coefficient and the number of transmission bits that minimize the BLER and AoI of the considered system.

A Hybrid Millimeter-Wave and Free-Space-Optics Communication Architecture with Adaptive Diversity Combining and HARQ Techniques

We propose and demonstrate a hybrid communication architecture that combines millimeter-wave (MMW) in the radio frequency (RF) domain and free-space-optics (FSO) technologies using adaptive combining and hybrid automatic repeat request (HARQ) techniques. At the receiving end, we employed joint signal processing with an adaptive diversity combining technique (ADCT) based on a maximum ratio combining (MRC) algorithm. We derived closed-form expressions for the outage probability and throughput of the hybrid RF and FSO (RF/FSO) system, considering various characteristics of atmospheric turbulence in the FSO link. Experimental testing with 10-Gbaud quadrature phase shift keying (QPSK) data was conducted under different simulated atmospheric turbulence intensities, FSO and MMW speed-ratios, and forward error correction (FEC) overheads. Additionally, we validated improvements in terms of bit error ratio (BER), outage probability, and throughput performance.

Adaptive Automatic Repeat Request (AdARQ) Protocol to Improve the Throughput Characteristic of the Time-Varying Wireless Channel

Adaptive Automatic Repeat Request (AdARQ) Protocol to Improve the Throughput Characteristic of the Time-Varying Wireless Channel

An Adaptive Hybrid Automatic Repeat Request (A-HARQ) Scheme Based on Reinforcement Learning

V2X communication is susceptible to attenuation and fading caused by external interference. This interference often leads to bit error and poor quality and stability of the wireless link, and it can easily disrupt packet transmission. In order to enhance communication reliability, the 3rd Generation Partnership Project (3GPP) introduced the Hybrid Automatic Repeat Request (HARQ) technology for both 4G and 5G systems. Nevertheless, it can be improved for poor communication conditions (e.g., heavy traffic flow, long-distance transmission), especially in advanced or cooperative driving scenarios. In this paper, we propose an Adaptive Hybrid Automatic Repeat Request (A-HARQ) scheme that can reduce the average block error rate, the average number of retransmissions, and the round-trip time (RTT). It adapts the Q-learning model to select the timing and frequency of retransmission to enhance the transmission reliability. We also design some transmission schemes—K-repetition, T-delay and [T, K]-overlap—which are used to shorten latency and avoid packet collision. Compared with the conventional 5G HARQ, our simulation results show that the proposed A-HARQ scheme decreases the system’s average BLER, the number of retransmissions, and the RTT to 5.55%, 1.55 ms, and 0.97 ms, respectively.

Saving Energy and Spectrum in Enabling URLLC Services: A Scalable RL Solution

Communication systems supporting cyber-physical production applications should satisfy stringent delay and reliability requirements. Diversity techniques and power control are the main approaches to reduce latency and enhance the reliability of wireless communications at the expense of redundant transmissions and excessive resource usage. Focusing on the application layer reliability key performance indicators (KPIs), we design a deep reinforcement learning orchestrator for power control and hybrid automatic repeat request retransmissions to optimize these KPIs. Furthermore, to address the scalability issue that emerges in the per-device orchestration problem, we develop a new branching soft actor-critic framework in which a separate branch represents the action space of each industrial device. Our orchestrator enables near real-time control and can be implemented in the edge cloud. We test our solution with a 3GPP-compliant and realistic simulator for factory automation scenarios. Compared to the state-of-the-art, our solution offers significant scalability gains in terms of computational time and memory requirements. Our extensive experiments show significant improvements in our target KPIs, over the state-of-the-art, especially for 5th percentile user availability. To achieve these targets, our framework requires substantially less total energy or spectrum, thanks to our scalable RL solution.

Highly-Efficient Low-Latency HARQ Built on NOMA for URLLC: Radio Resource Allocation and Transmission Rate Control Aspects

Hybrid automatic repeat request (HARQ) is an essential technology that efficiently reduces the transmission error rate. However, for ultra-reliable low latency communications (URLLC) in the 5th generation mobile communication systems and beyond, the increase in latency due to retransmission must be minimized in HARQ. In this paper, we propose a highly-efficient low-latency HARQ method built on non-orthogonal multiple access (NOMA) for URLLC while minimizing the performance loss for coexisting services (use cases) such as enhanced mobile broadband (eMBB). The proposed method can be seen as an extension of the conventional link-level non-orthogonal HARQ to the system-level protocol. This mitigates the problems of the conventional link-level non-orthogonal HARQ, which are decoding error under poor channel conditions and an increase in transmission delay due to restrictions in retransmission timing. In the proposed method, delay-sensitive URLLC packets are preferentially multiplexed with best-effort eMBB packets in the same channel using superposition coding to reduce the transmission latency of the URLLC packet while alleviating the throughput loss in eMBB. This is achieved using a weighted channel-aware resource allocator (scheduler). The inter-packet interference multiplexed in the same channel is removed using a successive interference canceller (SIC) at the receiver. Furthermore, the transmission rates for the initial transmission and retransmission are controlled in an appropriate manner for each service in order to deal with decoding errors caused by error in transmission rate control originating from a time varying channel. We show that the proposed method significantly improves the overall performance of a system that simultaneously provides eMBB and URLLC services.

Performance Analysis and Optimal Design of HARQ-IR-Aided Terahertz Communications

Terahertz (THz) communications are envisioned to be a promising technology for 6G thanks to its broad bandwidth. However, the large path loss, antenna misalignment, and atmospheric influence of THz communications severely deteriorate its reliability. To address this, hybrid automatic repeat request (HARQ) is recognized as an effective technique to ensure reliable THz communications. This paper delves into the performance analysis of HARQ with incremental redundancy (HARQ-IR)-aided THz communications in the presence/absence of blockage. More specifically, the analytical expression of the outage probability of HARQ-IR-aided THz communications is derived, with which the asymptotic outage analysis is enabled to gain meaningful insights, including diversity order, power allocation gain, modulation and coding gain, etc. Then the long term average throughput (LTAT) is expressed in terms of the outage probability based on renewal theory. Moreover, to combat the blockage effects, a multi-hop HARQ-IR-aided THz communication scheme is proposed and its performance is examined. To demonstrate the superiority of the proposed scheme, the other two HARQ-aided schemes, i.e., Type-I HARQ and HARQ with chase combining (HARQ-CC), are used for benchmarking in the simulations. In addition, a deep neural network (DNN) based outage evaluation framework with low computational complexity is devised to reap the benefits of using both asymptotic and simulation results in low and high outage regimes, respectively. This novel outage evaluation framework is finally employed for the optimal rate selection, which outperforms the asymptotic based optimization.

Raptor-like Coded Broadcasting for Efficient V2X Communications

Broadcasting is a critical feature in V2X communication, allowing for the simultaneous dissemination of safety-critical messages to all nearby vehicles. However, the requirement for low latency in information dissemination and the need for reliable and efficient data transmission pose significant challenges to broadcasting in V2X communication systems. In this paper, we present a novel raptor-like coded broadcasting (RLCB) scheme for low-latency V2X communications. Firstly, we introduce feedback into a concatenated fountain code, and adjust its precoding and coding structure to achieve effective data deliverance under a limited number of retransmissions for low-latency transmission. Then, based on the raptor-like encoding and decoding structure, we propose a mutual exclusion-based network encoding (MENC) algorithm to enable retransmission in broadcasting scenarios. We also conduct a complexity analysis on the encoding and decoding process of our proposed scheme. Numerical results demonstrate the superior performance of our proposed scheme in reducing the packet error rate (PER) and improving spectral efficiency compared to the R10 code and hybrid automatic repeat request (HARQ) scheme.