Channel Aware Sparse Transmission for Ultra Low-Latency Communications in TDD Systems

Future mobile communication systems need to support wide variety of new services and applications. In order to support these, ITU-R introduced new types of use cases. One such use case, called ultra reliable and low latency communication (URLLC), concerns the reduction of latency down to a millisecond level while ensuring the reliability of the transmission. In case of uplink transmission, supporting the stringent latency requirement of URLLC is quite challenging due to a time-consuming and complicated handshaking process. In the time division duplexing (TDD) systems, satisfying the latency requirement is far more difficult since the mobile device cannot transmit the data when the subframe is directed to the downlink. In this paper, we propose a new grant signaling scheme, referred to as channel-aware sparse signaling (CASS), to achieve a low latency access in the TDD-based URLLC systems. Key idea of CASS is to map the grant information into a small number of subcarriers and then decode it using a small number of early received samples. From the numerical evaluations, we demonstrate that the proposed CASS scheme achieves significant reduction in access latency over the conventional LTE-TDD systems.

The ultra-reliable and low-latency communication (URLLC) is the key driver of the current 5G new radio standardization. URLLC encompasses sporadic and small-payload transmissions that should be delivered within extremely tight radio latency and reliability bounds, i.e., a radio latency of 1 ms with 99.999% success probability. However, such URLLC targets are further challenging in the 5G dynamic time division duplexing (TDD) systems, due to the switching between the uplink and downlink transmission opportunities and the additional inter-cell cross-link interference (CLI). This paper presents a system level analysis of the URLLC outage performance within the 5G new radio flexible TDD systems. Specifically, we study the feasibility of the URLLC outage targets compared to the case with the 5G frequency division duplexing (FDD), and with numerous 5G design variants. The presented results therefore offer valuable observations on the URLLC outage performance in such deployments, and hence, introducing the state-of-the-art flexible-FDD technology.

The fifth generation (5G) radio access technology is designed to support highly delay-sensitive applications, i.e., ultra-reliable and low-latency communications (URLLC). For dynamic time division duplex (TDD) systems, the real-time optimization of the radio pattern selection becomes of a vital significance in achieving decent URLLC outage latency. In this study, a dual reinforcement machine learning (RML) approach is developed for online pattern optimization in 5G new radio TDD deployments. The proposed solution seeks to minimizing the maximum URLLC tail latency, i.e., min-max problem, by introducing nested RML instances. The directional and real-time traffic statistics are monitored and given to the primary RML layer to estimate the sufficient number of downlink (DL) and uplink (UL) symbols across the upcoming radio pattern. The secondary RML sub-networks determine the DL and UL symbol structure which best minimizes the URLLC outage latency. The proposed solution is evaluated by extensive and highly-detailed system level simulations, where our results demonstrate a considerable URLLC outage latency improvement with the proposed scheme, compared to the state-of-the-art dynamic-TDD proposals.

Recently, wireless multimedia services have been growing because of the spread of various wireless applications. Hence, time division duplex (TDD) systems and their crossed-slot interference problems in a cellular environment have been attracting growing interests. Considering large signaling overhead between cells, decentralized time slot allocation (TSA) strategy is suitable for practical implementation. Thus, Fixed-TSA strategy which fixes the same ratio of uplink and downlink time slots in all cells is adopted in commercial WiBro systems (IEEE802.16e Mobile WiMax) to mitigate the crossed-slot interference. However, the Fixed-TSA strategy reduces the flexibility in time slot allocation due to a strong constraint set by a predefined boundary. Moreover, the mathematical derivation of the optimal value for the predefined boundary has not been presented yet. In this paper, we propose two decentralized TSA strategies. The first one is Enhanced Fixed-TSA strategy, which dynamically adapts the predefined boundary of the conventional Fixed-TSA strategy according to traffic conditions. The second one is region-based Decentralized Time Slot Allocation (RED-TSA) strategy, which utilizes partial location information of MSs to reduce crossedslot interference. We fully analyze the proposed TSA strategies in terms of new call blocking probability, average bit error probability, and the overall system throughput. Numerical results show that the proposed RED-TSA strategy provides the highest system throughput by compromising both new call blocking performance and average bit error performance, whereas it requires additional location information and complicated computation. On the contrary, the proposed Enhanced Fixed-TSA strategy requires reasonable computational complexity while it provides almost the same system throughput with that of the proposed RED-TSA strategy. In a nutshell, the proposed Enhanced Fixed- TSA strategy is more appropriate for the practical systems. Moreover, it can be directly applied to the current commercial WiMax/WiBro systems with minimum changes.

Dynamic time division duplexing (TDD) is envisioned as a vital transmission technology of the 5G new radio, due to its reciprocal propagation characteristics. However, the potential cross-link interference (CLI) imposes a fundamental limitation against the feasibility of the ultra-reliable and low latency communications (URLLC) in dynamic-TDD systems. In this work, we propose a near-optimal and complexity-efficient CLI suppression scheme using orthogonal spatial projection, while the signaling overhead is limited to B-bit, over the back-haul links. Compared to the state-of-the-art dynamic-TDD studies, proposed solution offers a significant improvement of the URLLC outage latency, e.g., $\sim -199$% reduction, while boosting the achievable capacity per the URLLC packet by $\sim +156$%.

5G is envisaged to support diverse use cases and applications. Enhanced Mobile Broadband (eMBB) and Ultra-Reliable and Low Latency Communications (URLLC) have been identified as two main communication scenarios in 5G. Unlike eMBB service which demands high data rate, URLLC has stringent latency and reliability requirement. Due to the sporadic and stochastic characteristics of URLLC traffic, an URLLC transmission may suddenly occurs during the transmission of eMBB data. It is sometimes necessary to transmit URLLC data on the resources occupied by eMBB. Thus in this paper, we investigate the dynamic downlink multiplexing for eMBB and URLLC data on the same time/frequency resource. Specifically, we present a dynamical puncturing scheme, which allows URLLC data occupy part of the radio resource that has been scheduled to ongoing eMBB transmission. The puncturing will degrade the performance of the eMBB traffic, therefore we introduce the signal space diversity (SSD) scheme into the proposed dynamic puncturing scheme. The decoding performance of eMBB data over the fading channel is thus improved through the component interleaving and rotation modulation. Furthermore, we derive the optimal rotation angel that can achieve the optimal puncturing performance by maximizing the average mutual information (AMI). The link-level simulation results show that the proposed scheme outperforms existing strategy, and the performance gain is around 1dB when the code rate is set as $2/3$. This observation also validates the theoretical analysis based on the AMI.

Ultra-reliable and low-latency communication (URLLC) is expected to lead AR/VR, factory automation, transport industry, and power distribution as an important requirement in 5G wireless networks. This class of services could be considered as the most challenging and intriguing part because achieving low latency and ultra-high reliability at the same time is hard. In the 3rd Generation Partnership Project(3GPP) standard, a general URLLC requirement is 99.999% target reliability with 1 ms (two-way) user-plane latency. The reliability here is defined as the percentage of packets that are correctly received within the delay budget. In this paper, a relay selection algorithm based on the Finite Blocklength (FBL) regime is proposed to satisfy high reliability and low latency required in URLLC of 5G systems, using the genetic algorithm (GA). The simulation results showed better performance of the proposed algorithm than of the fixed relay selection.

In this paper, we investigate the secrecy performance of short-packet transmissions in ultra-reliable and low-latency communications (URLLC). We consider the scenario where a multi-antenna source communicates with a single-antenna legitimate receiver requiring ultra-high reliability and low latency, in the presence of a single-antenna eavesdropper. In order to safeguard URLLC, the source transmits the artificial noise (AN) signal together with the confidential signal to confuse the eavesdropper. We adopt a lower bound on the maximal secrecy rate as the secrecy performance metric for short-packet transmissions in URLLC, which takes the target decoding error probabilities at the legitimate receiver and the eavesdropper into account. Using this metric, we first derive a compact expression of the generalized secrecy outage probability (SOP). Then, we formally prove that the generalized SOP is a convex function with respect to the power allocation factor between the confidential signal and the AN signal. We further determine the optimal power allocation factor that minimizes the generalized SOP. The results presented in this work can be useful for designing new secure transmission schemes for URLLC.

An ultra-reliable and low latency communications assisted modulation based non-orthogonal multiple access scheme

Carrier frequency offset (CFO) and channel equalization are two critical problems for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) wireless communication systems in ultra-reliable and low latency communication (URLLC). In this paper, we propose a semi-blind precoding aided structure that includes two CFO estimation approaches and an independent component analysis (ICA) based equalization scheme for MIMO OFDM systems in URLLC, requiring no pilots. We design a non-redundant balanced precoding strategy, killing two birds with one stone, where reference signals are superimposed into source signals to simultaneously allow CFO estimation and ambiguity elimination in the ICA-equalized signals. The proposed precoding-aided CFO estimation approach performs by maximizing a cost function formulated via the cross-correlations between the reference signal and the received signal. We further propose a low-complexity closed-form CFO estimation approach, by transforming the formulated cost function into a new expression. To maximize bit error rate (BER) performance, particle swarm optimization (PSO) is employed to perform the joint optimization of precoding constant and the number of OFDM blocks for CFO estimation, while avoiding exhaustive search. The proposed semi-blind precoding-aided structure provides a trade-off between performance, complexity and spectral efficiency for MIMO OFDM systems in URLLC.

This paper studies the coexistence of enhanced mobile broadband (eMBB) and ultra-reliable and low-latency communication (URLLC) services in a cellular network that is assisted by a reconfigurable intelligent surface (RIS). The system model consists of one base station (BS) and one RIS that is deployed to enhance the performance of both eMBB and URLLC in terms of the achievable data rate and reliability, respectively. We formulate two optimization problems, a time slot basis eMBB allocation problem and a mini-time slot basis URLLC allocation problem. The eMBB allocation problem aims at maximizing the eMBB sum rate by jointly optimizing the power allocation at the BS and the RIS phase-shift matrix while satisfying the eMBB rate constraint. On the other hand, the URLLC allocation problem is formulated as a multi-objective problem with the goal of maximizing the URLLC admitted packets and minimizing the eMBB rate loss. This is achieved by jointly optimizing the power and frequency allocations along with the RIS phase-shift matrix. In order to avoid the violation in the URLLC latency requirements, we propose a novel framework in which the RIS phase-shift matrix that enhances the URLLC reliability is proactively designed at the beginning of the time slot. For the sake of solving the URLLC allocation problem, two algorithms are proposed, namely, an optimization-based URLLC allocation algorithm and a heuristic algorithm. The simulation results show that the heuristic algorithm has a low time complexity, which makes it practical for real-time and efficient multiplexing between eMBB and URLLC traffic. In addition, using only 60 RIS elements, we observe that the proposed scheme achieves around 99.99% URLLC packets admission rate compared to 95.6% when there is no RIS, while also achieving up to 70% enhancement on the eMBB sum rate.

Inspired by the new and dominating traffic services - ultra-reliable and low latency communications (URLLC), finite blocklength coding (FBC) has been developed to support delay and error-rate bounded quality-of-services (QoS) provisioning for time-sensitive wireless applications by using short-packet data communications. On the other hand, the age of information (AoI) has recently emerged as a new dimension of QoS performance metric in terms of the freshness of updated information. Since the status updates normally consist only of a small number of information bits but warrant ultra-low latency, exploring AoI in the finite blocklength regime creates another promising solution for supporting URLLC services. However, how to efficiently integrate and implement the above new techniques for statistical delay and error-rate bounded QoS provisioning in the finite blocklength regime has neither been well understood nor thoroughly studied. To overcome these challenges, we propose the AoI-driven statistical delay and error-rate bounded QoS provisioning schemes which leverage the AoI technique as a key QoS performance metric to efficiently support URLLC in the finite blocklength regime. First, we build up the AoI-metric based modeling frameworks in the finite blocklength regime. Second, we apply the stochastic network calculus (SNC) to characterize the upper-bounded peak AoI violation probability. Third, we jointly optimize the peak AoI violation probability and ∊-effective capacity and characterize their tradeoff in supporting statistical delay and error-rate bounded QoS provisioning for URLLC. Finally, we conduct the extensive simulations to validate and evaluate our developed schemes in the finite blocklength regime.

In 6G networks, integrated sensing and communication (ISAC) is envisioned as a key technology that enables wireless systems to perform joint sensing and communication using shared hardware, antenna(s) and spectrum. ISAC designs facilitate emerging applications such as digital twins, smart cities and autonomous driving. Such applications also demand ultra-reliable and low-latency communication (URLLC), a feature that was first introduced in 5G and is expected to be further enhanced in 6G. Thus, an ISAC-enabled URLLC system can prioritize critical and time-sensitive targets and ensure information delivery under strict latency and reliability constraints. We propose a bi-static multiple-input multiple-output (MIMO) ISAC system to detect the arrival of URLLC messages and prioritize their delivery. In this system, a dual-function base station (BS) communicates with a user equipment (UE) and a sensing receiver (SR) is deployed to collect echo signals reflected from a target of interest. The BS regularly transmits messages of enhanced mobile broadband (eMBB) services to the UE. During each eMBB transmission, if the SR senses the presence of a target of interest, it immediately triggers the transmission of an additional URLLC message. To reinforce URLLC transmissions, we propose a dirty-paper coding (DPC)-based technique that mitigates the interference of both eMBB and sensing signals. To decode the eMBB message, we consider two approaches for handling the URLLC interference: treating interference as noise (TIN) and successive interference cancellation (SIC). For this system, we formulate the rate-reliability-detection trade-off in the finite blocklength (FBL) regime by evaluating the communication rate of the eMBB transmissions, the reliability of the URLLC transmissions and the probability of the target detection. Our numerical analysis show that our proposed DPC-based ISAC scheme significantly outperforms power-sharing based ISAC and traditional time-sharing schemes. In particular, it achieves higher eMBB transmission rate while satisfying both URLLC and sensing constraints.

In this paper, we present an analytical approach to design the inner region size for the fractional frequency reused (FFR) time division duplex (TDD) orthogonal frequency division multiple access (OFDMA) systems when supporting asymmetrical traffic services. In TDD system, supporting asymmetrical traffic can be achieved by adjusting the ratio of downlink and uplink transmission period. Nevertheless, the intercell interference may be deteriorated by the cross-slot interference resulting from the different downlink and uplink ratios among neighboring cells. Although the FFR technique can overcome the inter-cell interference, the impact of the cross-slot interference of TDD systems due to various downlink to uplink traffic ratios in different cells on the inner region size of a FFR-based OFDMA system is an open issue to our best knowledge. Intuitively, the larger the inner region of a FFR system, the higher the system capacity. Thus, this paper can provide a systematic method to determine the size of the inner region of FFR-based OFDMA system for different ratios of the downlink to uplink traffic among two neighbor cells.

5G and beyond networks are being designed to support the future digital society, where numerous sensors, machinery, vehicles and humans will be connected in the so-called Internet of Things (IoT). The support of time-critical verticals such as Industry 4.0 will be especially challenging, due to the demanding communication requirements of manufacturing applications such as motion control, control-to-control applications and factory automation, which will require the exchange of critical sensing and control information among the factory nodes. To this aim, important changes have been introduced in 5G for Ultra-Reliable and Low-Latency Communications (URLLC). One of these changes is the introduction of grant-free scheduling for uplink transmissions. The objective is to reduce latency by eliminating the need for User Equipments (UEs—sensors, devices or machinery) to request resources and wait until the network grants them. Grant-free scheduling can reserve radio resources for dedicated UEs or for groups of UEs. The latter option is particularly relevant to support applications with aperiodic or sporadic traffic and deterministic low latency requirements. In this case, when a UE has information to transmit, it must contend for the usage of radio resources. This can lead to potential packet collisions between UEs. 5G introduces the possibility of transmitting K replicas of the same packet to combat such collisions. Previous studies have shown that grant-free scheduling with K replicas and shared resources increases the packet delivery. However, relying upon the transmission of K replicas to achieve a target reliability level can result in additional delays, and it is yet unknown whether grant-free scheduling with K replicas and shared resources can guarantee very high reliability levels with very low latency. This is the objective of this study, that identifies the reliability and latency levels that can be achieved by 5G grant-free scheduling with K replicas and shared resources in the presence of aperiodic traffic, and as a function of the number of UEs, reserved radio resources and replicas K. The study demonstrates that current Fifth Generation New Radio (5G NR) grant-free scheduling has limitations to sustain stringent reliability and latency levels for aperiodic traffic.