Ultra-reliable Low-latency Communication Systems Research Articles

Nested Hash Access With Post Quantum Encryption for Mission-Critical IoT Communications

Secure ultra-reliable low-latency communication (URLLC) has become a crucial requirement of mission-critical Internet of Things (IoT) applications and use cases including automotive driving, remote surgery, and many others. However, it is still challenging to protect initial access of massive IoT devices over wireless channels, especially when malicious quantum adversaries paralyse the initial access by overhearing and tampering critical wireless messages, i.e., preambles. We propose a nested hash access system with post-quantum encryption to solve this issue. The system performs random repetition coding and nested hash coding on multi-domain physical-layer resources to encode and decode preambles precisely and resiliently. Particularly, a subtle compression and encryption mechanism based on quasi-cyclic (QC)-moderate-density parity-check (MDPC) code is proposed between repetition and hashing operations to avoid passive eavesdropping during preamble encoding process. We show that the code information can be maintained at 128-bit or higher privacy level, depending on the length of repetition code. Besides, the preamble decoding process can be proved secure agaisnt active attacks with a tolerable loss of decoding errors. Then we formulate two non-convex integer programming problems, each problem corresponding to the minimization of upper bound of preamble decoding error in an example application scenario. Finally, we can derive the expressions of system failure probability to evaluate the reliability of URLLC system under mission-critical IoT scenarios. Simulation results show the effectiveness of our proposed scheme despite attack.

Data-Driven Spectrum Partition for Multiplexing URLLC and eMBB

Multiplexing ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB) are critical in the next generation mobile network. URLLC requires ultra-high reliability and extremely low latency, whereas eMBB demands high data rates. Thus, the coexistence system of URLLC and eMBB faces the challenge of sharing the spectrum efficiently and effectively. In this study, we comprehensively investigate the state of the art spectrum partition methods in combined URLLC and eMBB services. We formulate a joint optimization problem for maximizing the eMBB throughput and guaranteeing the URLLC performance. For the eMBB and URLLC multiplexing system, a full separative spectrum partition scheme based on data-driven genetic algorithm-based spectrum partition (DDGSP) is proposed. Our simulation results demonstrate that the proposed DDGSP can make the URLLC and eMBB coexistence system outperform the state-of-the-art methods in terms of the error rate and computational efficiency.

Secrecy Outage Analysis of Pilot-Assisted URLLC Systems With Randomly Distributed Eavesdroppers

In this letter, we focus on the secrecy outage analysis of ultra-reliable low-latency communication (URLLC) systems in the presence of randomly located eavesdroppers and imperfect channel state information (CSI). To be specific, the secrecy outage probability (SOP) of pilot-assisted URLLC system is investigated, which is defined as the probability that either the reliability const-raint or the secrecy constraint cannot be satisfied when the packet is delivered with a target data rate and blocklength. In fact, the definition of SOP in URLLC scenarios with short-packet feature is evidently different from that in the infinite blocklength regime. Inspired by this, we first propose a novel analytical framework to approximate the SOP in a tractable manner. Then, the asymptotic behaviours of SOP in the high-SNR and large-antenna cases are also analyzed to gain a comprehensive insight. Numerical results illustrate how the SOP of our pilot-assisted URLLC system varies with specific transmission parameters.

Joint Optimization of URLLC Parameters and Beamforming Design for Multi-RIS-Aided MU-MISO URLLC System

This letter focuses on a novel resource allocation design for a multi-reconfigurable intelligent surface (RIS)-aided multi-input and single-output (MISO) ultra-reliable low-latency communication (URLLC) system. In particular, we formulate the sum-rate maximization problem for joint optimization of block-length and packet-error probability for each user, precoder design at the base-station (BS) and passive beamforming at the RIS. To solve it, we provide an alternating optimization framework which involves the decoupling of original problem into the sub-problems of beamforming design and block-length optimization, and later solving them using general convex approximations. Numerical results validate the fast convergence of the proposed solution. Moreover, the proposed solution achieves upto 40% better performance when compared to random resource allocation and each RIS deployment boost the rate performance by 3–5%.

Adaptive AF/DF Two-Way Relaying in FD Multiuser URLLC System With User Mobility

We consider a full-duplex (FD)-enabled multi-user two-way communication system with adaptive amplify-and-forward (AF)/decode-and-forward (DF) relaying protocol. All the users are assumed to be mobile and to have FD abilities. The effect of mobility, which results in time-selective fading, is modeled using a first-order autoregressive (AR1) process. The fading channel-based approach characterizes the residual self-interference (RSI) at the FD relay, user nodes and is modeled as a Rician distributed random variable. This paper constitutes the most critical use case of 5G, i.e., ultra-reliable low latency communication (URLLC), which adopts short-packets finite blocklength (FB) codes to spin out into the mission-critical applications where strict latency and reliability requirements are highly desirable. The outage performance of the system is studied over independent and non-identically distributed complex Gaussian (Rayleigh envelope) channels with imperfect channel state information (CSI) for with and without URLLC use cases. The closed-form expressions for the outage probability and block error rate (BLER) are derived for the absolute channel power-based scheduling scheme considering the different Doppler power spectra models and the effect of co-channel interference (CCI). The expressions for the asymptotic outage probability are also derived. The presented analysis is compared with baseline schemes, e.g., the results derived with adaptive AF/DF relaying are also compared with both AF and DF relaying, and the performance of the FD transmissions is compared to that of half-duplex (HD) transmissions. The impact of node mobility, RSI, FBL, number of user pairs, and imperfect CSI on the system performance is investigated. Moreover, essential insights are obtained related to the performance gain and region of the superiority of the adaptive AF/DF relaying scheme. The derived analytic results are validated through Monte Carlo simulations. Furthermore, at high transmit power, the outage performance for the adaptive AF/DF protocol approaches the derived asymptotic floor.

Frequency divided group beamforming with sparse space‐frequency code for above 6 GHz URLLC systems

In this study, we propose a limited feedback-based frequency divided group beamforming with sparse space-frequency transmit diversity coded orthogonal frequency division multiplexing (OFDM) system for ultrareliable low latency communication (URLLC) scenario. The proposed scheme has several advantages over the traditional hybrid beamforming approach, including not requiring downlink channel state information for baseband precoding, supporting distributed multipoint transmission structures for diversity, and reducing beam sweeping latency with little uplink overhead. These are all positive aspects of physical layer characteristics intended for URLLC. It is suggested in the system to manage the multipoint transmission structure realized by distributed panels using a power allocation method based on cooperative game theory. Link-level simulations demonstrate that the proposed scheme offers reliability by achieving both higher diversity order and array gain in a non-line-of-sight channel of selectivity and limited spatial scattering.

An Unsupervised Deep Unrolling Framework for Constrained Optimization Problems in Wireless Networks

In wireless networks, the optimization problems generally have complex constraints and are usually solved via utilizing the traditional optimization methods that have high computational complexity and need to be executed repeatedly with the change of network environments. In this paper, to overcome these shortcomings, an unsupervised deep unrolling framework based on projection gradient descent (PGD), i.e., unrolled PGD network (UPGDNet), is designed to solve a family of constrained optimization problems. The set of constraints is divided into two categories according to the coupling relations among optimization variables and the convexity of constraints. One category of constraints includes convex constraints with decoupling among optimization variables, and the other category of constraints includes non-convex or convex constraints with coupling among optimization variables. Then, the first category of constraints is directly projected onto the feasible region, while the second category of constraints is projected onto the feasible region using a neural network. Finally, an unrolled sum rate maximization network (USRMNet) is designed based on UPGDNet to solve the weighted SR maximization problem for the multiuser ultra-reliable low latency communication system. Numerical results show that USRMNet has a comparable performance with low computational complexity and an acceptable generalization ability in terms of the user distribution.

Downlink URLLC System Over Spatially Correlated RIS Channels and Electromagnetic Interference

This letter explores a reconfigurable intelligent surfaces (RISs) assisted multi-user ultra-reliable low-latency communication (URLLC) system in presence of electromagnetic interference (EMI). The spatial correlation among the channels corresponding to the RIS meta-atoms is considered. For downlink communication, source selects a user out of arbitrary <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> users through random or absolute channel power based (CPB) scheduling schemes. We derive the closed form expressions for outage probability, block error rate (BLER), capacity and system goodput for both the scheduling schemes under the assumption of imperfect channel state information (CSI). Moreover, asymptotic expression for outage probability is also derived. The correctness of the derived expressions is verified through Monte-Carlo simulations.

Transceiver Design and Power Control for Full-Duplex Ultra-Reliable Low-Latency Communication Systems

Ultra-reliable low-latency communication (URLLC) is one of the most important components in the fifth generation (5G) cellular networks for realizing mission-critical applications. In this paper, we jointly optimize the transceiver design and decoding error probability (DEP) of a full-duplex (FD) URLLC system, where the base station (BS) operates in FD mode, while the uplink (UL) and downlink (DL) users work in half-duplex (HD) mode. Accordingly, an optimization problem is formulated to maximize the achievable total (UL plus DL) rate for an FD URLLC system under finite blocklength, subject to the end-to-end (E2E) reliability constraint from the UL user to each DL user and the total transmission power constraint at the UL user and at the BS. We analyze the problem structure and convexify the problem by approximating the channel dispersion in scenarios of high and mid-to-high signal-to-interference plus noise ratio (SINR) regimes, respectively. Next, efficient iterative algorithms are proposed to find the near-optimal power allocation for the UL user and transceiver weights for the BS. Furthermore, closed-form expressions of the transceiver weights are derived, and the convergence of the proposed algorithms is proved. Simulation examples demonstrate the impact of the code blocklength, number of DL users, transmitter/receiver distortion and DEP threshold on the system performance.

Latency and Reliability Trade-Off With Computational Complexity Constraints: OS Decoders and Generalizations

In this article, we study the problem of latency and reliability trade-off in ultra-reliable low-latency communication (URLLC) in the presence of decoding complexity constraints. We consider linear block encoded codewords transmitted over a binary-input AWGN channel and decoded with order-statistic (OS) decoder. We first investigate the performance of OS decoders as a function of decoding complexity and propose an empirical model that accurately quantifies the corresponding trade-off. Next, a consistent way to compute the aggregate latency for complexity constrained receivers is presented, where the latency due to decoding is also included. It is shown that, with strict latency requirements, decoding latency cannot be neglected in complexity constrained receivers. Next, based on the proposed model, several optimization problems, relevant to the design of URLLC systems, are introduced and solved. It is shown that the decoding time has a drastic effect on the design of URLLC systems when constraints on decoding complexity are considered. Finally, it is also illustrated that the proposed model can closely describe the performance versus complexity trade-off for other candidate coding solutions for URLLC such as tail-biting convolutional codes, polar codes, and low-density parity-check codes.

Quantum Learning Based Nonrandom Superimposed Coding for Secure Wireless Access in 5G URLLC

Secure wireless access in ultra-reliable low-latency communications (URLLC), which is a critical aspect of 5G security, has become increasingly important due to its potential support of grant-free configuration. In grant-free URLLC, precise allocation of different pilot resources to different users that share the same time-frequency resource is essential for the next generation NodeB (gNB) to exactly identify those users under access collision and to maintain precise channel estimation required for reliable data transmission. However, this process easily suffers from attacks on pilots. We in this article propose a quantum learning based nonrandom superimposed coding method to encode and decode pilots on multidimensional resources, such that the uncertainty of attacks can be learned quickly and eliminated precisely. Particularly, multiuser pilots for uplink access are encoded as distinguishable subcarrier activation patterns (SAPs) and gNB decodes pilots of interest from observed SAPs, a superposition of SAPs from access users, by joint design of attack mode detection and user activity detection though a quantum learning network (QLN). We found that the uncertainty lies in the identification process of codeword digits from the attacker, which can be always modelled as a black-box model, resolved by a quantum learning algorithm and quantum circuit. Novel analytical closed-form expressions of failure probability are derived to characterize the reliability of this URLLC system with short packet transmission. Simulations how that our method can bring ultra-high reliability and low latency despite attacks on pilots.

Resource Allocation for Multi-User Downlink MISO OFDMA-URLLC Systems

This article considers the resource allocation algorithm design for downlink multiple-input single-output (MISO) orthogonal frequency division multiple access (OFDMA) ultra-reliable low latency communication (URLLC) systems. To meet the stringent delay requirements of URLLC, short packet transmission is adopted and taken into account for resource allocation algorithm design. The resource allocation is optimized for maximization of the weighted system sum throughput subject to quality-of-service (QoS) constraints regarding the URLLC users’ number of transmitted bits, packet error probability, and delay. Despite the non-convexity of the resulting optimization problem, the optimal solution is found via monotonic optimization. The corresponding optimal resource allocation policy can serve as a performance upper bound for sub-optimal low-complexity solutions. We develop such a low-complexity sub-optimal resource allocation algorithm based on successive convex approximation and difference of convex programming. Our simulation results reveal the importance of using multiple antennas for reducing the latency and improving the reliability of URLLC systems. Moreover, the proposed sub-optimal algorithm is shown to closely approach the performance of the proposed optimal algorithm and outperforms two baseline schemes by a considerable margin, especially when the users have heterogeneous delay requirements. Finally, conventional resource allocation designs based on Shannon’s capacity formula are shown to be not applicable in MISO OFDMA-URLLC systems as they are not able to guarantee the users’ delay constraints.

Fast and accurate analytical tools to estimate network capacity for URLLC in 5G systems

Ultra-Reliable Low-Latency Communication (URLLC) systems are one of the most challenging parts of the 5G systems due to very tight constraints on reliability and latency. Because of the strict requirements, the network capacity of URLLC depends on various system parameters such as channel bandwidth, distribution of users in the cell, traffic load, etc. A fast and accurate estimation of the network capacity under given conditions is crucial for the efficient deployment of new URLLC services and dynamic reconfiguration of the radio access network. This paper presents two analytical tools that estimate the capacity of URLLC systems. The first tool is an analytical model that accurately obtains the network capacity. The second one is an approximation method that significantly reduces the computational time at the cost of acceptable estimation errors.

Concatenated Graph Coding on Bandwidth Part for Secure Pilot Authentication in Grant-Free URLLC

Grant-free multiple access is a critical mechanism introduced in 5G new radio (NR) to support ultra-reliable low-latency communication (URLLC) services. Pilot authentication (PA) is a key security mechanism to guarantee reliable performance of grant-free URLLC. However, PA can be easily paralyzed by pilot-aware attack since pilot signals are usually publicly known, and unprotected. To solve this, we develop the concatenated graph coding (CGC) theory by which time-frequency resources on bandwidth part (BWP) can be encoded flexibly to protect PA securely. Particularly, we use bipartite graph, and multigraph theory to model PA on BWP as transmission, and retrieval of pilot (TRP). Each transmitter in the uplink needs transmit a unique random pilot sequence as subcarrier activation pattern (SAP) on BWP. After observing SAPs from multiple transmitters, the receiver decodes a pilot sequence of interest, and tests its authenticity. The retrievability of authentic pilots is defined, and formulated analytically. We also derive the analytical closed-form expression of system failure probability, and accessibility in the regime of large-scale antenna arrays, and short data packets. Interestingly, we find that four trade-offs exist: retrievability-latency, retrievability-accessibility, reliability-latency, and reliability-accessibility. Simulation results show the security advantage of our proposed theory in grant-free URLLC system.

Wireless Channel Dynamics and Robustness for Ultra-Reliable Low-Latency Communications

Interactive, immersive, and other timing-critical applications demand ultra-reliable low-latency communication (URLLC). To build wireless communication systems that can support these applications, understanding the relevant characteristics of the wireless medium is paramount. Although wireless channel characteristics and dynamics have been extensively studied, it is important to revisit these concepts in the context of the strict demands of low-latency and ultra-high reliability. In this paper, we bring a modeling approach from robust control to wireless communication—the wireless channel characteristics are given a nominal model around which we allow for some quantified uncertainty. We propose certain key URLLC-relevant parameters along which the model uncertainty is to be bounded. To validate the nominal model of the spatially independent quasi-static Rayleigh fading, we take an in-depth look at the spatial and temporal correlations based on Jakes’ model. We find that although the Rayleigh fading process is band-limited, the quasi-static assumption is not safe for relay selection even well within a single coherence time. We also find that under reasonable conditions, the spatial correlation of channels provide a fading distribution that is not too far off from an independent spatial fading model. In addition, we look at the impact of these channel models on cooperative communication-based systems. We find that while spatial-diversity-based techniques are necessary to combat the adverse effects of fading, time-diversity-based techniques are necessary to be robust against unmodeled errors. Robust URLLC systems need to operate with both an adequate SNR margin and a time margin through repetitions.

Uplink Transmissions in URLLC Systems With Shared Diversity Resources

5G features flagship use cases with ultra reliable low latency communication (URLLC), supported through high diversity. When multiple URLLC connections are only intermittently active, dedicating many diversity resources to a single connection leads to inefficient operation. We address this problem through shared diversity resources and compare it to per-link dedicated diversity. Two receiver types are considered, minimum mean squared error (MMSE) and MMSE successive interference cancelation. Outage probability is evaluated by assuming channel estimation errors. The results show that it is possible to remain close to the reliability of reference system with a relatively low amount of pre-allocated resources.