Short Packet Transmission Research Articles

Freshness-in-air: An AoI-inspired UAV-assisted wireless sensor networks

The Age-of-Information (AoI) metric has emerged as a performance measurement metric for evaluating time-sensitive wireless communications systems. Maintaining the freshness and reliability of data is critical in time-critical wireless networks, where outdated information can have significant consequences. Moreover, short packet transmissions are used in wireless sensor networks (WSNs) to maintain energy efficiency and low latency. This paper proposes a theoretical model that utilizes the AoI metric and finite block length information theory to estimate information freshness in an unmanned aerial vehicle (UAV)-assisted WSN. This network includes multiple sensing nodes and relies on short-packet communication for transmission. In this paper, closed-form expressions for average AoI (AAoI) and the block error rate are derived. Furthermore, the optimal altitude and block length that ensures the freshness of received information at the destination is determined. The results of the analysis provide valuable insights into the performance characteristics of UAV-assisted WSNs and have important implications for the design and optimization of such systems.

Risk-Aware and Energy-Efficient AoI Optimization for Multiconnectivity WNCS With Short-Packet Transmissions

Risk-Aware and Energy-Efficient AoI Optimization for Multiconnectivity WNCS With Short-Packet Transmissions

Cell-Free mMIMO Systems in Short Packet Transmission Regime: Pilot and Power Allocation

Cell-Free mMIMO Systems in Short Packet Transmission Regime: Pilot and Power Allocation

Resource allocation and passive beamforming for IRS‐assisted short packet systems

AbstractThis paper investigates an intelligent reflecting surface (IRS) assisted downlink short packet transmission system, where an access point sends short packets to multiple devices with the help of an IRS. Specifically, a performance comparison between the frequency division multiple access and time division multiple access is conducted for the considered system, from the perspective of average age of information (AoI). To minimize the maximum average AoI among all devices, the resource allocation and passive beamforming are jointly optimized. However, the formulated problem is difficult to solve due to the non‐convex objective function and coupled variables. Thus, an alternating optimization based algorithm is proposed by exploiting the semidefinite relaxation and bisection search techniques. Simulation results show that time division multiple access can achieve lower AoI by exploiting the time‐selective passive beamforming of IRS for maximizing the signal to noise ratio of each device consecutively. Moreover, it also shows that as the length of information bits becomes sufficiently large as compared to the available bandwidth, the proposed frequency division multiple access transmission scheme becomes more favourable due to more flexible power allocation.

Optimized IEEE 802.11ax for smart warehouses

Industry 4.0 aspires to digitize factories processes wholly. Wireless technologies represent one of the elements of this goal. However, the current standards and proprietary solutions need to meet the industry’s tight requirements for various use cases, such as smart warehouses, where robots manage and control entire tasks. One of the key research challenges toward replacing wired fieldbuses with wireless links is the design of wireless systems that address short packet transmissions and multi-user environments. Nevertheless, this challenge is partially obstructed by the limits of the current proposals and the industrial channel models. The authors detect as a potential solution the optimization of IEEE 802.11ax that, due to the use of OFDMA, could offer a high-performant system for smart warehouses. This article proposes an ad-hoc wireless system based on IEEE 802.11ax for smart warehouses that comprises optimization for MAC and PHY layers. Furthermore, two retransmission schemes based on frequency domain are described. This article proposes a methodology to evaluate the latency and reliability performance. Compared to previous proposals, the system shows improved performance.

Mobile Edge Computing aided Integrated Sensing and Communication with Short-Packet Transmissions

Mobile Edge Computing aided Integrated Sensing and Communication with Short-Packet Transmissions

Energy Efficient Defense Against Cooperative Hostile Detection and Eavesdropping Attacks for UAV-Aided Short-Packet Transmissions

Energy Efficient Defense Against Cooperative Hostile Detection and Eavesdropping Attacks for UAV-Aided Short-Packet Transmissions

Movable Antenna Enhanced NOMA Short-Packet Transmission

Movable Antenna Enhanced NOMA Short-Packet Transmission

Reliable Transmission of Short Packets in Cognitive Radio Inspired NOMA Network

Reliable Transmission of Short Packets in Cognitive Radio Inspired NOMA Network

Reliability-Oriented Resource Allocation for Wireless Powered Short Packet Communications With Multiple WPT Sources

We study a multi-source wireless power transfer (WPT) enabled network supporting multi-sensor transmissions. Activated by the energy harvesting from multiple WPT sources, the sensors transmit short packets to a destination with finite blocklength (FBL) codes. This work <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">for the first time</i> characterizes the FBL reliability for such multi-source WPT enabled network and accordingly provides reliability-oriented resource allocation designs, while a practical nonlinear EH model (including the effects of mutual interference among multiple RF signals) is considered. For the scenario with a fixed frame structure, we aim to maximize the FBL reliability via optimally allocating the transmit power among the multiple WPT sources. In particular, we investigate the relationship between the overall error probability and the transmit power of multiple WPT sources, based on which a power allocation problem is formulated. To solve the formulated non-convex problem, we first introduce auxiliary variables to make the problem analytically tractable, based on which an iterative algorithm is proposed while applying successive convex approximation (SCA) technique to the non-convex components of the problem. Then, we extend our design into a dynamic frame structure scenario, i.e., the blocklength allocated for WPT phase and short-packet transmission phase are adjustable, which introduces more flexibility and new challenges. In particular, we provide a joint power and blocklength allocation design maximizing the overall reliability under total power and blocklength constraints. A problem with high-dimension variables is formulated, which suffers from the complex and non-convex relationship among system reliability, multiple source power and blocklength. To tackle the difficulties, auxiliary variables introduction, multiple variable substitutions along with SCA technique utilization are exploited to reformulate and efficiently solve the problem. Finally, through numerical results, we validate our analytical model and evaluate the system performance, where a set of guidelines for practical system design are concluded.

Secure short-packet transmission in uplink massive MU-MIMO assisted URLLC under imperfect CSI

Ultra-reliable and low-latency communication (URLLC) is still in the early stage of research due to its two strict and conflicting requirements, i.e., ultra-low latency and ultra-high reliability, and its impact on security performance is still unclear. Specifically, short-packet communication is expected to meet the delay requirement of URLLC, while the degradation of reliability caused by it makes traditional physical-layer security metrics not applicable. In this paper, we investigate the secure short-packet transmission in uplink massive multiuser multiple-input-multiple-output (MU-MIMO) system under imperfect channel state information (CSI). We propose an artificial noise scheme to improve the security performance of the system and use the system average secrecy throughput (AST) as the analysis metric. We derive the approximate closed-form expression of the system AST and further analyze the system asymptotic performance in two regimes. Furthermore, a one-dimensional search method is used to optimize the maximum system AST for a given pilot length. Numerical results verify the correctness of theoretical analysis, and show that there are some parameters that affect the tradeoff between security and latency. Moreover, appropriately increasing the number of antennas at the base station (BS) and transmission power at user devices (UDs) can increase the system AST to achieve the required threshold.

IRS-Based Energy Efficiency and Admission Control Maximization for IoT Users With Short Packet Lengths

In this paper, we study a multiuser multiple-input single-output (MISO) machine type communication (MTC)-enabled intelligent reflecting surface (IRS) system, where a multi-antenna access point (AP) transmits information symbols to a set of Internet of Things (IoT) users with short packet transmission. In particular, the total energy efficiency (EE) and the number of IoT users that could be served fairly are maximized by jointly optimizing active and passive beamformers. An efficient algorithm based on alternating optimization (AO) is proposed to solve the main optimization problem iteratively. To this end, we adopt the difference of convex functions (DC) and successive convex approximation (SCA) to make a concave-convex function. Then, we employ the fractional programming based on the quadratic form to obtain a sub-optimal solution for the active beamformers at the AP and the number of admitted users. In the passive beamforming case, a penalty-based approach is utilized together with the SCA technique to handle the unit-modulus constraints at the IRS. Simulation results unveil an interesting tradeoff between EE and user admissibility performance. Besides, the results show the effectiveness of the IRS deployment in improving EE and successfully admitted users.

Beamforming Design in Short-Packet Transmission for URLLC in Cell-Free Massive MIMO System

Low latency, high reliability, and high data rate are three performance indicators of Ultra-reliable and low latency communication (URLLC) systems, but they are not able to be met simultaneously. Based on the determined latency and reliability requirements, this paper investigates the problem of the weighted sum rate (WSR) in cell-free massive multi-input multi-output (MIMO) system with multiple access points (APs). User-centric access point selection is considered to further reduce the computational complexity for AP used with acceptable performance loss. The transmitting beamforming is designed to mitigate inter-user interference so as to maximize the WSR under the backhaul and transmitting power constraints. Since the proposed problem is non-convex, two algorithms are proposed to solve the problem under the general SINR regime and the high SINR regime, respectively. For the former, we first approximate the objective function with the difference of convex (DC) programming and reformulate the problem into a semi-definite relaxation (SDR) form. Afterward, auxiliary variables are introduced in accordance with the successive convex approximation (SCA) method to further transform the nonconvex problem into a convex one. In the end, the sub-optimal WSR is obtained by iteratively solving a final convex problem. For the latter, the well-known WMMSE method is applied to address the WSR problem. Numerical results demonstrate the efficiency of our proposed algorithm, e.g., the maximum performance gain of the proposed algorithm is about 25% compared to the classical MMSE method. And the user-centric approach achieves 8 times computational complexity reduction with 4% performance loss.

Analysis of the Efficiency of Various Receipting Multiple Access Methods with Acknowledgement in IoT Networks

An Internet of things (IoT) network is a distributed set of “smart” sensors, interconnected via a radio channel. The basic method of accessing the radio channels for these networks is Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA), in which access is carried out on the basis of contention, and confirmation of the correct reception of the packet is achieved using a receipt. If the sizes of information packets are small and comparable to the sizes of receipts, then the transmission of receipts requires a significant bandwidth of the channel, which reduces the efficiency of the network. This problem exists not only for IoT networks but also for monitoring systems, operational management of fast processes, telemetry, short messaging and many other applications. Therefore, an urgent task is to develop effective methods of multiple random access in the transmission of short information packets, the size of which is comparable to the size of receipts. To solve this problem, the authors proposed modifications of CSMA/CA random access in which, when packet collisions are detected, a diagnostic message (DM) is generated and transmitted in the broadcast mode. Based on simulation modeling, it is shown that in a wide range of network loads, the proposed random access options provide an increase in network capacity (the number of connected subscribers) of 1.5–2 times compared to the basic CSMA/CA access method when the size of the information packet is an order of magnitude larger than the size of receipts. The variant of access without acknowledgment is also considered, in which, as shown by the simulation results, at sufficiently large loads, the network can go into an unstable state.

Energy-Efficient Optimization in Distributed Massive MIMO Systems for Slicing eMBB and URLLC Services

The fifth generation (5G) communication system aims to support diverse services such as enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communication (URLLC). In order to enable the coexistence of eMBB and URLLC services on a common physical infrastructure, network slicing incorporated in the distributed massive multiple-input multiple-output (DM-MIMO) system is regarded as a promising solution. In this paper, a non-orthogonal slicing scheme is proposed to improve the spectral efficiency, and the short packet transmission is adopted for URLLC to meet the low latency requirement. Through a joint optimization of beamforming and remote radio unit (RRU) selection, we investigate the energy efficiency (EE) maximization problem for the downlink DM-MIMO system. The formulated problem is a mixed integer nonlinear program (MINLP) that we solve by applying some efficient approaches, such as the Dinkelbach method, the reweighted <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell _{1}$</tex-math></inline-formula> -norm and difference of convex (DC) programming. By combining these approaches in one iteration, a double-loop procedure based on semi-definite relaxation (SDR) and successive convex approximation (SCA) is employed to find the suboptimal solution of the problem. Simulation results show that the proposed scheme significantly improves the EE of the DM-MIMO system and efficiently manages resource allocation.

Reliability analysis for NOMA‐based UAV assisted short packet communication

AbstractThis paper introduces the short packet transmission in non‐orthogonal multiple access (NOMA)‐based unmanned aerial vehicle (UAV) assisted relay communication system. Short packet transmission has considerable potential to decrease the transmission latency of UAV communication, and NOMA can effectively enhance the spectrum efficiency and fairness. To improve the reliability of the system, an effective packet error rate (PER) minimization problem within short packet transmission is proposed by jointly optimizing the packet length, UAV placement, and power allocation under the reliability requirement and total power constraints. To address the intricate PER minimization problem, the optimization problem is firstly decomposed into three sub‐problems, and the corresponding monotonicity and convexity are analyzed, respectively. Then, an overall iterative optimization algorithm for PER minimization based on alternating direction method of multipliers algorithm and optimal solution algorithm is formulated by solving the three sub‐problems in an iterative manner. Simulation results validate the effectiveness and convergence of the proposed NOMA scheme and overall iterative optimization algorithm, respectively.

Outage Analysis of Sparse Vector Coding-Based Downlink Multicarrier NOMA for URLLC

Ultra-reliable and low latency communication (uRLLC) is a promising use case in the fifth generation and beyond systems for critical and delay-sensitive applications with aid of short packet transmission. Nevertheless, multi-carrier non-orthogonal multiple access (MCNOMA) is a promising technique to achieve spectral efficiency and massive connectivity, however, inter-carrier interference (ICI) stands out to be a major downside. Recently, sparse vector coding (SVC) is proposed to fulfill the trade-off between reliability and latency, thereby achieving the benchmarks of uRLLC. In this paper, SVC based downlink MCNOMA (SVC-MCNOMA) system is considered and first it is shown that SVC-MCNOMA is free from ICI due to the sparse nature of the information. Further, compressed sensing-based recovery at the receiver end helps in reducing the latency as well as enhances reliability. Moreover, to study the system performance, this paper derives the closed form outage expressions of the SVC-MCNOMA system over the Rician fading channel and through Monte-Carlo simulation, the analytical results are validated. The analyses demonstrate that SVC-MCNOMA outperforms conventional MCNOMA (C-MCNOMA), thereby achieving spectral efficacy, ultra-reliability with low latency and eradicates the effect of ICI.

Trade Reliability for Security: Leakage-Failure Probability Minimization for Machine-Type Communications in URLLC

How to provide information security while fulfilling ultra reliability and low-latency requirements is one of the major concerns for enabling the next generation of ultra-reliable and low-latency communications service (xURLLC), specially in machine-type communications. In this work, we investigate the reliability-security tradeoff by defining the leakage-failure probability, a metric that jointly characterizes both reliability and security performances for short-packet transmissions. We discover that the system performance can be enhanced, counter-intuitively, by allocating fewer resources for the transmission with finite blocklength (FBL) codes. In order to solve the corresponding optimization problem for the joint resource allocation, we propose an optimization framework, that leverages lower-bounded approximations for the decoding error probability in the FBL regime. We characterize the convexity of the reformulated problem and establish an efficient iterative searching method, the convergence of which is guaranteed. To show the extendability of the framework, we further discuss the blocklength allocation schemes with practical requirements of reliable-secure performance, as well as the transmissions with the statistical channel state information (CSI). Numerical results verify the accuracy of the proposed approach and demonstrate the reliability-security tradeoff under various setups.

Permutation-Based Short-Packet Transmissions Improve Secure URLLCs in the Internet of Things

As a promising candidate for ultra-reliable and low-latency communications, the recent permutation-based transmission concept substantially improves the resource utilisation efficiency in the Internet of Things (IoT). In this context, the age of information (AoI) experienced in permutation-based short-packet transmissions is characterised in a wiretap channel, where eavesdroppers are wiretapping the status updates delivered over the legitimate link. The AoI of the legitimate link and the secrecy margin of the wiretap channel are formulated in closed forms within the regime of finite-blocklength information theory to quantify the data freshness and security of status updates in the IoT. The optimal packet structure to be delivered over the network interface is found by solving the optimisation problems of minimising the legitimate link’s AoI and maximising the secrecy margin. Illustrative numerical results are provided for our permutation-based transmission to quantify its performance gains over the conventional encapsulation, specifically in short-packet communications.

Efficient Massive Machine Type Communication (mMTC) via AMP

We propose efficient and low-complexity multiuser detection (MUD) algorithms for Gaussian multiple access channel (G-MAC) for short-packet transmission in massive machine type communications. To do so, we first formulate the G-MAC MUD problem as a sparse signal recovery problem and obtain the exact and approximate joint prior distribution of the sparse vector to be recovered. Then, we employ the Bayesian approximate message passing (AMP) algorithms with the optimal separable and nonseparable minimum mean squared error (MMSE) denoisers for soft decoding of the sparse vector. The effectiveness of the proposed MUD algorithms for a large number of devices is supported by simulation results. For packets of 8 information bits, while the state-of-the-art AMP with soft-threshold denoising achieves 8/100 of the upper bound at Eb/N0 = 4 dB, the proposed algorithms reach 4/7 and 1/2 of the upper bound.