Short Packet Transmission Research Articles

Power Allocation of Superimposed Pilots for URLLC With Short-Packet Transmission in IIoT

Intelligent manufacturing in future factories requires ultra-reliable and low-latency communications (URLLC) between central controllers and actuators (e.g., robots). This letter studies a superimposed pilot (SP)-aided uplink transmission system in industrial scenarios, where each actuator sends short-packet messages containing a superimposition of pilot and data signals to the central controller. A practical setting is considered where the blocklength is finite and imperfect pilot removal (IPPR) is available. Then, a closed-form lower bound of the achievable rate with a maximum ratio combining receiver is derived, which can be easily extended to the special cases of perfect pilot removal (PPR) and regular pilot (RP). Based on the derived lower bound, the pilot and data power allocation is optimized by exploiting successive convex approximation method to transform the weighted sum rate maximization problem into a series of geometric programs. Simulation results reveal that the SP-aided transmission outperforms the RP-aided transmission in both the PPR and IPPR cases.

A Novel Expectation-Maximization-Based Blind Receiver for Low-Complexity Uplink STLC-NOMA Systems.

In this paper, we revisit a two-user space-time line coded uplink non-orthogonal multiple access (STLC-NOMA) system for Internet-of-things (IoT) networks and propose a novel low-complexity STLC-NOMA system. The basic idea is that both IoT devices (stations: STAs) employ amplitude-shift keying (ASK) modulators and align their modulated symbols to in-phase and quadrature axes, respectively, before the STLC encoding. The phase distortion caused by wireless channels becomes compensated at the receiver side with the STLC, and thus each STA’s signals are still aligned on their axes at the access point (AP) in the proposed uplink STLC-NOMA system. Then, the AP can decode the signals transmitted from STAs via a single-user maximum-likelihood (ML) detector with low-complexity, while the conventional uplink STLC-NOMA system exploits a multi-user joint ML detector with relatively high-complexity. We mathematically analyze the exact BER performance of the proposed uplink STLC-NOMA system. Furthermore, we propose a novel expectation-maximization (EM)-based blind energy estimation (BEE) algorithm to jointly estimate both transmit power and effective channel gain of each STA without the help of pilot signals at the AP. Somewhat interestingly, the proposed BEE algorithm works well even in short-packet transmission scenarios. It is worth noting that the proposed uplink STLC-NOMA architecture outperforms the conventional STLC-NOMA technique in terms of bit-error-rate (BER), especially with high-order modulation schemes, even though it requires lower computation complexity than the conventional technique at the receiver.

Mobile jammer enabled secure UAV communication with short packet transmission

This paper studies a mobile jammer enabled secure unmanned aerial vehicle (UAV) communication network in the finite packet length scenario, where the external friendly jammer UAV will transmit jamming signal to deteriorate the quality of eavesdropping channel, and help to improve the secure communication performance of the source UAV. Specifically, an average effective secrecy rate (AESR) maximization problem is formulated by jointly designing the trajectories and transmit power of the source/jammer UAV subject to the UAVs’ mobility constraints and power constraints. It is also verified that there exists a unique optimal packet error rate to maximize the AESR. The formulated problem is mathematically intractable, as it is nonconvex and involves coupled optimization variables. Therefore, we first decompose the trajectories and power optimization problem into four non-convex subproblems, and then transform them into standard convex problems by applying first-order Taylor expansion. Then, an efficient alternating optimization algorithm for AESR problem based on Bisection method and successive convex approximation (SCA) technology is presented by addressing the five subproblems iteratively. Simulation results are provided to verify that our proposed scheme can obtain considerable better AESR gain compared to other four benchmark schemes.

Joint power and blocklength optimization for RIS‐aided multiple‐access downlink ultra‐reliable low‐latency communication

Ultra-reliable low-latency communication (URLLC) has gained significant interest since it deals with short packet transmission adopted to reduce latency; however, this implies that the conventional Shannon capacity formula is not applicable, and the achievable data rate becomes a complex function of the decoding error probability and blocklength. This paper studies URLLC transmission using a time-division multiple access scheme with an arbitrary number of actuators utilising a reconfigurable intelligent surface. The authors optimisze the weighted sum rate of this system subject to reliability, total energy, and latency constraints. For the blocklength allocation in a scenario where each actuator is allocated equal power, a closed-form analytical solution is provided. Also, for the case of joint optimization of the blocklength and power of each actuator, an analytical solution is provided for the case of two actuators, while an iterative sequential quadratic programing method is adopted for the case of an arbitrary number of actuators. The proposed methodology provides a low-complexity, fast solution, which is more efficient than using exhaustive search techniques. The results show that in some cases, optimization of the blocklength provides a near-optimal solution at low complexity, while jointly optimising the blocklength and the power per actuator has an improved performance at the cost of additional complexity.

Active device detection and performance analysis of massive non-orthogonal transmissions in cellular Internet of Things

This paper investigates multiple access schemes for uplink and downlink transmissions in cellular networks with massive Internet of Things (IoT) devices. Recall that single-carrier frequency division multiple access and orthogonal frequency division multiple access, which are orthogonal multiple access (OMA) schemes, have been conventionally adopted for uplink and downlink transmissions in narrow-band IoT, respectively. Unlike these OMA schemes, we propose two non-orthogonal multiple access (NOMA) schemes for cellular IoT with short-packet transmissions. Especially, a generalized expectation consistent signal recovery-based algorithm is proposed to estimate active devices, channel state information and data in uplink transmission, where all of the active devices are allowed to transmit their pilots and data through the same resource block without authorization. On the other hand, the active devices estimated during uplink transmission are grouped for downlink transmission with a trade-off between performance and detection complexity. Additionally, the data error rates are analysed for both uplink and downlink transmissions with low-resolution analog-to-digital converters (ADCs), where the effects of critical parameters such as the estimation error, ADC bits, packet length, and message bits are revealed. Both simulation and analytical results are provided to demonstrate the excellent performance of the proposed NOMA schemes and algorithms, especially for active device, channel, and data estimations. More importantly, the obtained results show that the data error rate performance of downlink NOMA is superior to that of OMA when the message bits of devices in one group are selected following the proposed strategy.

Decentralized Power Control for an ALOHA-Type Random Multiple Access System with Short Packet Transmission

Machine to machine communication is an important scenario in a 6G communication network. Random multiple access has recently been revisited and considered a key technology for machine to machine communication scenarios due to many advantages such as without coordination setup time. It is a regret that packet collision probability will be extremely higher for random multiple access when massive devices randomly accessing base station. Decentralized power control is an efficient scheme in random multiple access systems which can support intraslot successive interference cancellation to recover multiple collided packets at receivers. However, existing studies of decentralized power control for random multiple access are with the assumption that blocklength of transmitted packets is infinite, which neglects that machine to machine communication is characterized by finite blocklength transmission (i.e., short packet) in 6G. This paper focuses decentralized power control with short packet transmission in random multiple access systems. First, the closed-form expression of signal to interference plus noise ratio (SINR) threshold for short packets is derived. Then, decentralized transmission power profile is defined based on derived SINR threshold of short packets, which can support intraslot successive interference cancellation deciding at receivers for an ALOHA-type random multiple access system. Further, we propose derivation method to maximize system throughput, which can reduce optimization cost. Theoretical findings in this paper can provide valuable benchmark for short packet transmission with decentralized power control in random multiple access systems.

Research on Efficient Channel Decoding Algorithm for Memory Channel and Short Packet Transmission in Smart Grid

Many smart factories use the smart grid for power system automation, and its wireless control technology requires low-time-delay and high-reliability communication. Guessing random additive noise decoding algorithm has outstanding short packet error correction performance. In the decoding process, the order of noise parameter combination affects the decoding delay. Aiming at the communication problem of the smart grid in the process of factory power supply and distribution, this study analyzes the characteristics of the original noise parameter ranking algorithm. When the steady-state flip probability is large, more search times are required to obtain the correct combination of noise parameters, which means that greater delay is required for decoding in the time-varying channel. To solve the aforementioned problems, this study optimizes the noise parameter ranking before the noise error mode arrangement and proposes a noise parameter ranking algorithm for predicting the symbol string. First, the channel perception is completed by edge computing. Then, the algorithm uses the obtained soft information to rank the channel noise parameters. Simulation results show that the proposed algorithm has better search performance than the original sorting algorithm, especially when the channel parameter b is greater than 0.5. Finally, by comparing the BM Decoding Algorithm of BCH with different noise parameter ranking algorithms of decoding, the results show that the noise parameter ranking algorithm proposed in this study has better decoding performance in the environmental channel of the smart factory, so as to improve the reliability of the smart grid in the process of factory power supply and distribution.

Compressed Random Access for Noncoherent Massive Machine-Type Communications With Energy Modulation

Massive machine-type communications (mMTC) for the Internet of Things (IoT) are expected to support a large number of devices/users for short packet transmissions with low complexity and low energy consumption. By utilizing the simple while efficient noncoherent energy-based transmission scheme, this work aims to jointly detect the user activity and the desired data for mMTC. First, by exploiting the sparse characteristics of the user activity, approximation message passing (AMP) algorithm is proposed to eliminate the multi-user interference, and a denoiser is designed to minimize the mean-squared error (MSE) of the transmitted signals. Then, maximum <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${a}$ </tex-math></inline-formula> <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">posteriori</i> (MAP) criterion is adopted to approximately detect the user activity and the desired data. By minimizing the symbol error probability of the above two-step algorithm, the power constellation for each user is designed, and it is shown to be asymptotically optimal as the number of the receiver antennas goes to infinity. Finally, simulation results reveal that the proposed noncoherent scheme outperforms the coherent one in the low SNR regime and for short packet transmissions.

Short-Packet Transmission in Irregular Repetition Slotted ALOHA System Over the Rayleigh Fading Channel

Random access systems are potential for Internet of Things in the future wireless communication network for its operational simplicity. Irregular repetition slotted ALOHA (IRSA) system is one of the high-efficiency random access systems. In this paper, performance analysis of the irregular repetition slotted ALOHA systems with short-packet, i.e. finite-blocklength, transmission for the quasi-static Rayleigh fading channel is given. A cumulative distribution function of signal-to-interference power ratio (SIR) is derived and thus a closed-form expression of an average packet error probability (PEP) at the SIR with short packets for the Rayleigh fading channel is given. The closed-form expression makes it possible to optimize the degree distributions at a specific blocklength in the sense that the systems give the maximum system load.

Energy efficient short‐packet‐communication in UAV‐assisted cognitive network

AbstractThis paper studies unmanned aerial vehicle (UAV)‐assisted cognitive network, where the UAV can improve the communication quality of edge users. Short packet communication (SPC) is widely used due to its low delay transmission characteristic. Unlike long packet communication in conventional wireless networks, SPC has a non‐negligible packet error rate and its data transmission rate is less than Shannon capacity. Considering the fact that the UAV is usually powered by battery, the energy efficiency (EE) maximisation problem is investigated based on short packet transmission in the UAV‐assisted cognitive network. Firstly, the closed‐form expression of EE is analysed, and then the optimisation problem is formulated by jointly optimising the spectrum sensing time, packet error rate, the flight speed, and the coverage range of UAV. Secondly, the optimisation problem is solved by dividing it into four subproblems. Then, an efficient iterative algorithm is proposed to tackle this problem. Simulation results show that the proposed optimisation scheme can evidently improve the EE performance compared with other benchmark schemes. In addition, the proposed joint optimisation algorithm not only has better convergence than exhaustive method, but also has higher stability than PSO algorithm.

Mission Effective Capacity—A Novel Dependability Metric: A Study Case of Multiconnectivity-Enabled URLLC for IIoT

Various industrial Internet of Things applications demand execution periods throughout which no communication failure is tolerated. However, the classical understanding of reliability in the context of ultra-reliable low-latency communication (URLLC) does not reflect on the time-varying characteristics of the wireless channel. In this article, we introduce a novel mission reliability and mission effective capacity metric that takes these phenomena medium into account, while specifically studying multiconnectivity (MC)-enabled industrial radio systems. We assume uplink short packet transmission with no channel state information at URLLC user (the transmitter) and sporadic traffic arrival. Moreover, we leverage the existing framework of dependability theory and provide closed-form expressions (CFEs) for the mission reliability of the MC system using the maximal-ratio combining scheme. We do so by utilizing the mean time to first failure, which is the expected time of failure occurring for the first time. Moreover, we also derive exact CFEs for second-order statistics, such as level crossing rate and average fade duration, showing how fades are distributed in fading channels with respect to time. Furthermore, the design throughput maximization problem under the mission reliability constraint is solved numerically through the cross-entropy method.

Throughput optimization of interference limited cognitive radio-based Internet of Things (CR-IoT) network

The Internet of Things (IoT) technology allows massive devices to connect to the internet for data exchange. It is anticipated that in near future, trillions of IoT devices will be connected to the internet. To deploy these devices, the requirement of the spectrum is increasing day by day. Most of these devices transmit data over unlicensed frequency bands that cause severe interference to each other while exchanging the data as these bands are becoming overcrowded. Therefore, to overcome spectrum scarcity and interference problems among these devices, a novel communication paradigm called cognitive radio-based internet of things (CR-IoT) is evolving at a very fast pace that integrates cognitive radio technology into the IoT devices. The technology has the potential to overcome the spectrum scarcity and interference problem by allowing dynamic spectrum access to conventional IoT networks. Such devices continuously monitor spectrum availability to transmit the data by incorporating an intelligent sensing mechanism into the devices. However, the performance of the sensing unit in terms of the probability of detection and the probability of false alarm, significantly deteriorates due to the noise uncertainties, especially in low signal-to-noise ratio environments. For the efficient utilization of the spectrum, the probability of detection and the probability of false alarm of the spectrum sensor should be high and low, respectively. Both sensing parameters are greatly influenced by the selection of the sensing threshold. Moreover, these IoT devices deal with short packet transmissions, the optimum sensing time is another crucial parameter that governs the performance of these devices.While addressing these two important issues, the convex optimization problem is formed over sensing time and sensing threshold, and the concavity on sensing threshold is proved. Further, an iterative algorithm is proposed for the CR-IoT system that intelligently adapts the sensing threshold to meet desired sensing performance in terms of Pd and Pf especially, in low SNR regions, and also optimize the sensing time to overcome the sensing throughput tradeoff. The simulation results are presented to validate the effectiveness of the proposed algorithm. It is demonstrated that the proposed algorithm increases the CR-IoT system throughput by 95% as compared to the conventional scheme at the received signal to noise ratio equals −20 dB while satisfying the requirement of Pd and Pf as per IEEE 802.22 standard.

Massive Uncoordinated Multiple Access for Beyond 5G

Existing wireless communication systems have been mainly designed to provide substantial gain in terms of data rates. However, 5G and Beyond will depart from this scheme, with the objective not only to provide services with higher data rates. One of the main goals is to support massive machine-type communications (mMTC) in the Internet-of-Things (IoT) applications. Supporting massive uplink communications for devices with sporadic traffic pattern and short-packet size, as it is in many mMTC use cases, is a challenging task, particularly when the control signaling is not negligible in size compared to the payload. In addition, channel estimation becomes challenging for sporadic and short-packet transmission due to the limited number of employed pilots. In this paper, a new uplink multiple access (MA) scheme is proposed for mMTC, which can support a large number of uncoordinated IoT devices with short-packet and sporadic traffic. The proposed uplink MA scheme removes the overheads associated with the device identifier as well as pilots and preambles related to channel estimation. An alternative mechanism for device identification (DI) is employed, where a unique spreading code is dedicated to each IoT device as identifier. This unique code is simultaneously used for the spreading purpose and DI. Two IoT DI algorithms which employ sparse signal reconstruction methods are proposed to determine the active IoT devices prior to data detection. Specifically, the Bayesian information criterion model order selection method is employed to develop an IoT DI algorithm for unknown and time-varying activity rate. Our proposed MA scheme benefits from a new non-coherent nonlinear multiuser detection algorithm designed on the basis of unsupervised machine learning techniques to enable data detection without <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> knowledge on channel state information. For performance improvement, an extension to multiple receive antennas through hard decision combining is proposed. The effectiveness of the proposed MA scheme for known and unknown activity rate and high overloading factor is supported by simulation results.

Joint Semi-Blind Self-Interference Cancellation and Equalisation Processes in 5G QC-LDPC-Encoded Short-Packet Full-Duplex Transmissions.

The paper proposes a joint semi-blind algorithm for simultaneously cancelling the self-interference component and estimating the propagation channel in 5G Quasi-Cyclic Low-Density Parity-Check (QC-LDPC)-encoded short-packet Full-Duplex (FD) transmissions. To avoid the effect of channel estimation processes when using short-packet transmissions, this semi-blind algorithm was developed by taking into account only a small number (four at least) pilot symbols, which was integrated with the intended information sequence and used for the feedback loop of the estimation of the channels. The results showed that this semi-blind algorithm not only achieved nearly optimal performance, but also significantly reduced the processing time and computational complexity. This semi-blind algorithm can also improve the performances of the Mean-Squared Error (MSE) and Bit Error Rate (BER). The results of this study highlight the potential efficiency of this joint semi-blind iterative algorithm for 5G and Beyond and/or practical IoT transmission scenarios.

Reliable and Secure Short-Packet Communications

Exploiting short packets for communications is one of the key technologies for realizing emerging application scenarios such as massive machine type communications (mMTC) and ultra-reliable low-latency communications (uRLLC). In this paper, we investigate short-packet communications to provide both reliability and security guarantees simultaneously with an eavesdropper. In particular, an outage probability considering both reliability and secrecy is defined according to the characteristics of short-packet transmission, while the effective throughput in the sense of outage is established as the performance metric. Specifically, a general analytical framework is proposed to approximate the outage probability and effective throughput. Furthermore, closed-form expressions for these quantities are derived for the high signal-to-noise ratio (SNR) regime. Both effective throughput obtained via a general analytical framework and a high-SNR approximation are maximized under an outage-probability constraint by searching for the optimal blocklength. Numerical results verify the feasibility and accuracy of the proposed analytical framework, and illustrate the influence of the main system parameters on the blocklength and system performance under the outage-probability constraint.

Effective capacity maximization of two-way full-duplex and half-duplex relays with finite block length packets transmission

In order to satisfy the delay requirements of telecommunication systems, in this paper, we present a cooperative network with the short packet transmission in the Rayleigh fading channel. The desired relay can be implemented as a two-way half-duplex (HD) or a two-way full-duplex (FD). Also, for more accurate satisfaction and reduction of communication delays, sending and receiving with short packets is considered. Effective capacity appropriately measures the transmission rate under the delay constraint. Therefore, it is considered as a performance evaluation criterion here. With a two-way relay, two nodes exchange data with each other using a relay simultaneously. The priorities and requirements of the two nodes are not necessarily the same. Therefore, to increase performance, the system is modeled and solved as a multi-objective problem. In this way, the available power in the network is divided between the relay and two nodes, and the effective capacity of the two nodes is maximized. Depending on the different conditions, the optimal amount of allocated power to relay and nodes is calculated. However, due to the complexity and time consuming calculations, an approximate method which speeds up the calculation is presented. The approximated solution has a very close performance to the optimal allocated power. Finally, various comparisons have been made in different conditions between the performance of two-way HD and two-way FD relays. The improvement of multi-objective power allocation has been shown, especially when the relay is not located in the middle of two nodes.

Energy-Efficient Secure Short-Packet Transmission in NOMA-Assisted mMTC Networks With Relaying

Massive Machine-Type Communication (mMTC) is proposed by ITU to provide a large scale of connectivity services for billions of machine-type communications devices (MTCDs) via cellular networks. However, MTCDs are generally energy-constrained, security capability limited and short-packet transmission dominated. It has great challenges for massive MTCDs to perform short-packet transmission simultaneously while guaranteeing the confidentiality and energy efficiency of the information transmission. In this paper, we investigate the energy-efficient secure short-packet transmission of Non-Orthogonal Multiple Access (NOMA) assisted mMTC networks, in which MTCDs aim to transmit secrecy messages to the destination base station via trusted relays with a passive eavesdropper present. To realize secure, reliable and energy-efficient transmission, we maximize the secrecy energy efficiency (SEE) by implementing joint relay and power level selection. Furthermore, we formulate a decentralized stateless Q-learning-based multi-agent reinforcement learning (MARL) algorithm for the dynamic and complex mMTC systems. The simulation results show that adopting the proposed decentralized MARL algorithm and relaying with NOMA can improve the performance of SEE while reducing information exchange overhead.

Deployment of Polar Codes for Mission-Critical Machine-Type Communication Over Wireless Networks

Mission critical Machine-type Communication, also referred to as Ultra-reliable Low Latency Communication is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected devices. While the reduction in PHY layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability, the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper layers. The mcMTC has a significant technical impact on the design of all layers of the communication protocol stack. In this paper, an innovative bottom-up approach has been proposed for mcMTC applications through PHY layer targeted at improving the transmission reliability by implementing ultra-reliable channel coding scheme in the PHY layer of IEEE 802.11a bearing in mind short packet transmission system. To achieve this aim, we analyzed and compared the channel coding performance of convolutional codes, LDPC codes, and polar codes in wireless network on the condition of short data packet transmission. The Viterbi decoding algorithm, logarithmic belief propagation algorithm, and cyclic redundancy check - successive cancellation list decoding algorithm were adopted to CC, LDPC codes, and polar codes, respectively. Consequently, a new PHY layer for mcMTC has been proposed. The reliability of the proposed approach has been validated by simulation in terms of Bit error rate vs. SNR. The simulation results demonstrate that the reliability of IEEE 802.11a standard has been significantly improved to be at PER less 10e-5 with the implementation of polar codes. The results also show that the general-purpose wireless networks are prominent in providing short packet mcMTC with the modification needed.

A Survey on FEC Techniques for Industrial Wireless Communications

Industry 4.0 aims to digitize industrial processes entirely, and wireless technologies represent one of the enablers for scalable and flexible communications. However, the current standards and proprietary solutions do not meet the industry's tight requirements in fundamental use cases such as Factory Automation (FA). One of the key research challenges towards replacing wired fieldbuses with wireless links is the design of techniques that enable real-time and deterministic behavior when transmitting short packets. Forward Error Correction (FEC) techniques are critical to this objective, and coding/decoding algorithms must comply with reliability and low latency specifications. This paper surveys existing FEC techniques for short packet transmissions. Compared to other survey papers in the field, we propose several FEC candidate techniques specifically suitable for FA wireless systems. We explore four of these techniques, also examining hardware architecture proposals. The paper proposes a methodology to evaluate their latency and reliability performance. We finally discuss the lessons learned and challenges for future research.

Beamforming Design for Multiuser uRLLC With Finite Blocklength Transmission

Driven by the explosive growth of Internet of Things (IoT) devices with stringent requirements on latency and reliability, ultra-reliability and low latency communication (uRLLC) has become one of the three key communication scenarios for the 5th generation (5G) and 6G communication systems. In this paper, we focus on the beamforming design problem for the downlink multiuser uRLLC system. Since the strict demand on the reliability and latency, in general, short packet transmission is a favorable way for uRLLC systems, which indicates the classical Shannon&#x2019;s capacity formula is no longer applicable. With the finite blocklength transmission, the achievable rate is greatly influenced by the reliability and finite blocklength. Using the developed achievable rate formula for finite blocklength transmission, we respectively formulate the problems of interest as the weighted sum rate maximization, energy efficiency maximization, and user fairness optimization by considering the maximum allowable transmission power and minimum rate requirement. These problems considered are non-convex and are hard to obtain the global optimal solution, even for the local optimal solution. To overcome these difficulties, some important insights have been discovered by analyzing the function of achievable rate. For example, an analytical solution of the minimum rate requirement is provided with respective to the signal-to-interference-plus-noise ratio. Based on the discovered results, we provide algorithms to optimize the beamforming vectors and power allocation, which are guaranteed to converge to a local optimum solution to the formulated problems with low computational complexity. Our simulation results reveal that our proposed beamforming algorithms outperform the zero-forcing beamforming algorithm with equal power or water filling allocation widely used in the existing literatures.