A Survey of Scheduling in 5G URLLC and Outlook for Emerging 6G Systems

Future wireless communication is expected to be a paradigm shift from three basic service requirements of 5th Generation (5G) including enhanced Mobile Broadband (eMBB), Ultra Reliable and Low Latency communication (URLLC) and the massive Machine Type Communication (mMTC). Integration of the three heterogeneous services into a single system is a challenging task. The integration includes several design issues including scheduling network resources with various services. Specially, scheduling the URLLC packets with eMBB and mMTC packets need more attention as it is a promising service of 5G and beyond systems. It needs to meet stringent Quality of Service (QoS) requirements and is used in time-critical applications. Thus through understanding of packet scheduling issues in existing system and potential future challenges is necessary. This paper surveys the potential works that addresses the packet scheduling algorithms for 5G and beyond systems in recent years. It provides state of the art review covering three main perspectives such as decentralised, centralised and joint scheduling techniques. The conventional decentralised algorithms are discussed first followed by the centralised algorithms with specific focus on single and multi-connected network perspective. Joint scheduling algorithms are also discussed in details. In order to provide an in-depth understanding of the key scheduling approaches, the performances of some prominent scheduling algorithms are evaluated and analysed. This paper also provides an insight into the potential challenges and future research directions from the scheduling perspective

Deep Reinforcement Learning for Practical Phase Shift Optimization in RIS-aided MISO URLLC Systems

Reconfigurable intelligent surfaces (RISs) can assist the wireless systems in providing reliable and low-latency links to realize the requirements in Industry 4.0. In this paper, the practical phase shift optimization in a RIS-aided ultra-reliable and low-latency communication (URLLC) system at a factory setting is performed by applying a novel deep reinforcement learning (DRL) algorithm named as twin-delayed deep deterministic policy gradient (TD3). First, the system achievable rate in finite blocklength (FBL) regime is identified for each actuator then, the problem is formulated where the objective is to maximize the total achievable FBL rate, subject to non-linear amplitude response and the phase shift values constraint. Since the amplitude response equality constraint is highly non-convex and non-linear, we employ the TD3 to tackle the problem. The considered method relies on interacting RIS with industrial scenario by taking actions which are the phase shifts at the RIS elements, to maximize the total FBL rate. We assess the performance loss of the system when the RIS is non-ideal, i.e., non-linear amplitude response with/without phase quantization and compare it with ideal RIS. The numerical results show that optimizing phase shifts in non-ideal RIS via the considered TD3 method is highly beneficial to improve the performance.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Guaranteed Dynamic Scheduling of Ultra-Reliable Low-Latency Traffic via Conformal Prediction

The dynamic scheduling of ultra-reliable and low-latency traffic (URLLC) in the uplink can significantly enhance the efficiency of coexisting services, such as enhanced mobile broadband (eMBB) devices, by only allocating resources when necessary. The main challenge is posed by the uncertainty in the process of URLLC packet generation, which mandates the use of predictors for URLLC traffic in the coming frames. In practice, such prediction may overestimate or underestimate the amount of URLLC data to be generated, yielding either an excessive or an insufficient amount of resources to be pre-emptively allocated for URLLC packets. In this paper, we introduce a novel scheduler for URLLC packets that provides formal guarantees on reliability and latency irrespective of the quality of the URLLC traffic predictor. The proposed method leverages recent advances in online conformal prediction (CP), and follows the principle of dynamically adjusting the amount of allocated resources so as to meet reliability and latency requirements set by the designer

Five Facets of 6G: Research Challenges and Opportunities

Whilst the fifth-generation (5G) systems are being rolled out across the globe, researchers have turned their attention to the exploration of radical next-generation solutions. At this early evolutionary stage we survey five main research facets of this field, namely {\em Facet~1: next-generation architectures, spectrum and services, Facet~2: next-generation networking, Facet~3: Internet of Things (IoT), Facet~4: wireless positioning and sensing, as well as Facet~5: applications of deep learning in 6G networks.} In this paper, we have provided a critical appraisal of the literature of promising techniques ranging from the associated architectures, networking, applications as well as designs. We have portrayed a plethora of heterogeneous architectures relying on cooperative hybrid networks supported by diverse access and transmission mechanisms. The vulnerabilities of these techniques are also addressed and carefully considered for highlighting the most of promising future research directions. Additionally, we have listed a rich suite of learning-driven optimization techniques. We conclude by observing the evolutionary paradigm-shift that has taken place from pure single-component bandwidth-efficiency, power-efficiency or delay-optimization towards multi-component designs, as exemplified by the twin-component ultra-reliable low-latency mode of the 5G system. We advocate a further evolutionary step towards multi-component Pareto optimization, which requires the exploration of the entire Pareto front of all optiomal solutions, where none of the components of the objective function may be improved without degrading at least one of the other components

A Comprehensive Overview on 5G-and-Beyond Networks with UAVs: From Communications to Sensing and Intelligence

Due to the advancements in cellular technologies and the dense deployment of cellular infrastructure, integrating unmanned aerial vehicles (UAVs) into the fifth-generation (5G) and beyond cellular networks is a promising solution to achieve safe UAV operation as well as enabling diversified applications with mission-specific payload data delivery. In particular, 5G networks need to support three typical usage scenarios, namely, enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). On the one hand, UAVs can be leveraged as cost-effective aerial platforms to provide ground users with enhanced communication services by exploiting their high cruising altitude and controllable maneuverability in three-dimensional (3D) space. On the other hand, providing such communication services simultaneously for both UAV and ground users poses new challenges due to the need for ubiquitous 3D signal coverage as well as the strong air-ground network interference. Besides the requirement of high-performance wireless communications, the ability to support effective and efficient sensing as well as network intelligence is also essential for 5G-and-beyond 3D heterogeneous wireless networks with coexisting aerial and ground users. In this paper, we provide a comprehensive overview of the latest research efforts on integrating UAVs into cellular networks, with an emphasis on how to exploit advanced techniques (e.g., intelligent reflecting surface, short packet transmission, energy harvesting, joint communication and radar sensing, and edge intelligence) to meet the diversified service requirements of next-generation wireless systems. Moreover, we highlight important directions for further investigation in future work.Comment: Accepted by IEEE JSA

Heterogeneous Traffic Multiplexing in Next Generation Cellular Networks

The vision shaping the upcoming sixth-generation (6G) wireless cellular networks has recently gained considerable attention from researchers in academia and industry. 6G networks are expected to fulfill the limitations of the fifth-generation (5G) networks and support a wide range of new applications and services beyond those supported by 5G, namely, enhanced mobile broadband (eMBB), ultra-reliable and low latency communications (URLLC) and massive machine-type communications (mMTC). Further, these emerging networks are thus mandated to support new emerging applications that concurrently demand multiple quality of service (QoS) requirements of data rate, reliability, latency, and connectivity. Due to the fundamental trade-off of such extremely diverse QoS requirements, the coexistence of these emerging applications has been identified as a major challenge in 6G networks and their predecessors. This dissertation aims at addressing the coexistence problem, specifically URLLC and eMBB traffic, by developing spectrally efficient multiplexing and scheduling solutions. By considering different key enabling technologies, this dissertation provides unique research contributions to the coexistence problem that led to effective designs. In particular, coupling URLLC and eMBB through the Third Generation Partnership Project (3GPP) superposition/puncturing scheme naturally arises as a promising option due to the latter's tolerance in terms of latency and reliability. Moreover, reconfigurable intelligent surface (RIS) has been proposed as a potential low-cost and energy-efficient technology that can control the wireless propagation environment providing endless benefits in supporting coexisting 6G services. Regarding the superposition scheme, this thesis investigates the joint scheduling of eMBB and URLLC traffic while minimizing the eMBB rate loss, considering URLLC reliability and the eMBB QoS. In the context of puncturing, this thesis studied the interplay between the RIS configuration, URLLC reliability and eMBB rate by proposing proactive RIS configurations to guarantee the URLLC latency requirements. Although simulation results demonstrate that adopting the proposed scheme can further boost eMBB and URLLC traffic performance, the computational complexity of optimizing the RIS phase shifts is challenging. To this end, this thesis proposes two low-complexity methods for optimizing the RIS phase shift matrix. The first solution proposes reducing the number of optimization variables configuring the RIS to the number of users. The second algorithm is based on a closed-form expression for the RIS phase shift matrix. Finally, a new puncturing strategy is proposed to mitigate the impact on the eMBB transmission. The key idea of the proposed scheme is to puncture the eMBB data that has maximum symbol similarities with the URLLC leading to reducing the contaminated eMBB symbols. We study the performance of the proposed schemes in terms of the eMBB spectral efficiency, URLLC reliability and low complexity. We show analytically and through simulations the efficacy of the proposed schemes over their existing counterparts

Multidimensional Index Modulation for 5G and Beyond Wireless Networks

This study examines the flexible utilization of existing IM techniques in a comprehensive manner to satisfy the challenging and diverse requirements of 5G and beyond services. After spatial modulation (SM), which transmits information bits through antenna indices, application of IM to orthogonal frequency division multiplexing (OFDM) subcarriers has opened the door for the extension of IM into different dimensions, such as radio frequency (RF) mirrors, time slots, codes, and dispersion matrices. Recent studies have introduced the concept of multidimensional IM by various combinations of one-dimensional IM techniques to provide higher spectral efficiency (SE) and better bit error rate (BER) performance at the expense of higher transmitter (Tx) and receiver (Rx) complexity. Despite the ongoing research on the design of new IM techniques and their implementation challenges, proper use of the available IM techniques to address different requirements of 5G and beyond networks is an open research area in the literature. For this reason, we first provide the dimensional-based categorization of available IM domains and review the existing IM types regarding this categorization. Then, we develop a framework that investigates the efficient utilization of these techniques and establishes a link between the IM schemes and 5G services, namely enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communication (URLLC). Additionally, this work defines key performance indicators (KPIs) to quantify the advantages and disadvantages of IM techniques in time, frequency, space, and code dimensions. Finally, future recommendations are given regarding the design of flexible IM-based communication systems for 5G and beyond wireless networks.Comment: This work has been submitted to Proceedings of the IEEE for possible publicatio