面向5G URLLC业务的时延分析与无线超低时延技术研究

5G面向三大场景业务,其中URLLC业务的低时延高可靠特性为无线网络带来了新的挑战.无线空口侧时延主要受传输间隔、资源调度、混合重传、终端和基站处理时延等因素影响.为解决时延问题,3GPP R15标准中已从减少传输时间间隔和优化资源调度两个方向提出了低时延技术,满足5G网络部署初期的低时延业务需求.     

5G URLLC技术应用

低时延高可靠通信(URLLC)技术的标准化工作已基本完成,而实现从标准到落地应用对产业界提出了更高的要求。基于URLLC场景需求,总结了3GPP组织标准化的低时延类技术和高可靠类技术;研究了在5G网络实际部署中,URLLC技术与网络切片、与传统e MBB业务协同实现机制;面向对低时延高可靠指标需求迫切的工业场景,研究了基于5G与TSN融合架构的部署方案,最后探讨了URLLC技术协同保障工业确定性业务的端到端实现方案。     

面向5G URLLC业务的无线超低时延技术方案探讨

文章基于5G网络中URLLC业务所具备的低时延高可靠特性以及所带来的新的挑战,对空口时延的概念以及URLLC标准进展展开分析,并从减少传输时延间隔、优化资源调度方案等方面对5G无线超低时延技术方案和技术部署展开分析探讨,结果表明,为有效解决时延问题,3GPPR15标准中已经从优化资源调度和缩短传输时间间隔等方面提出可行思路,可为5G网络部署初期低时延业务提供技术支持。     

3GPP LTE系统中无线视频传输调度算法研究

摘要：针对3GPP LTE系统,本文提出了适用于下行链路视频业务的一种新的分组调度算法,即时延优先比例公平调度（Delay First-Proportional Fair Scheduling,DF-PFS）。当需要做出调度决策时,该算法利用每个用户的数据包时延信息和瞬时下行信道条件,在满足用户QoS前提下最大限度地提高系统吞吐量。同时,当用户选择资源块（RB）进行传输后,即从用户集合中将该用户删除,避免接近eNodeB的用户一直占用无线资源,确保了资源分配的公平性。实验仿真结果表明,该算法在丢包率和PSNR性能上优于最大权重时延优先（M-LWDF）算法,在保证用户间公平性前提下,满足了视频业务的QoS要求。     

面向电力业务质量保障的NR-U与Wi-Fi频谱共享

为了缓解5G授权频谱资源短缺的问题，使用非授权频谱成为重要的解决方案。随着电力终端的大规模接入，面向电力业务保障的NR-U(NR in unlicensed spectrum）与Wi-Fi频谱共享成为重要的研究热点。首先，提出了一种NR-U上行传输机制，在保障Wi-Fi用户平均速率的同时实现了电力业务终端的数据上行传输。此外，还提出了联合传输时间和子载波分配（joint transmission time and subcarrier allocation,TTSA）的资源优化算法，以保障各类型电网业务的服务质量（quality of service,QoS），并最大化终端的总速率。将该优化问题解耦，使用近端策略优化（proximal policy optimization,PPO）为终端分配子载波。仿真结果表明，与已有算法相比，提出的TTSA资源优化算法在保障电力业务QoS和最大化终端总速率方面性能优越。     

H2H与M2M共存场景下的上行资源分配算法

未来网络中将有大量的机器与机器（machine-to-machine,M2M）通信终端,比人与人（human to human,H2H）通信终端至少要多出2个数量级,网络中传统的资源分配算法无法满足新业务的通信需求.基于H2H与M2M共存场景,本文通过分析M2M终端特性,提出了一种基于背包模型的分级传输的资源分配算法,此分配算法优先保障H2H与时延敏感的M2M通信业务的服务质量（Quality of Service,QoS）,同时充分考虑时延非敏感的M2M的业务特性,节省能量消耗.仿真结果表明该算法能够提高资源利用率,同时满足H2H与M2M业务的QoS.     

一种适用于B3G移动通信系统下行共享信道的调度算法

本文针对后三代(B3G)移动通信系统中的宽带无线信道特性和流媒体业务特征,分析了可用于高速下行共享信道的各种传统分组调度算法,提出面向流媒体业务能够提高系统吞吐量的基于优先级公平调度(Priority-Based Fairness Scheduling,PBFS)算法.该算法根据各移动用户收发信道质量和业务传输的QoS要求动态调整各用户的业务传输优先级,确定下行共享信道的调度方案.并给出该算法的简化形式S-PBFS.仿真结果表明,与传统调度算法相比,S-PBFS算法在数据包传输时延受限的条件下具有无线信道利用率高、实现复杂度低等特点.     

基于时延和速率效用函数的LTE无线资源调度算法研究

为了提高LTE实时业务调度的公平性,在M-LWDF资源调度算法的优先级判断机制中引入了平均传输速率和保证比特速率,将经济学中的效用思想和效用函数引入M-LWDF调度算法,提出了一种基于时延效用函数和速率效用函数的M-LWDF改进算法,更好地体现了调度算法的时延特性和速率特性。仿真结果表明基于时延和速率效用函数的M-LWDF调度算法具有更高的公平性,能够更好地满足对实时业务的调度要求。     

基于QoS付费业务的LTE下行跨层分组调度算法

准4G网络（LTE）即将商用会给人们带来更多的方便,以至于大量用户在日常生活中使用更多的QoS业务,这样系统会出现了拥塞和调度不够合理的情况,影响了高优先级业务的丢包率、时延和公平性。通过对LTE下行跨层分组调度各种算法的研究分析,从时延、丢包率、吞吐量和公平性等因素入手,在原有的比例公平性调度算法（PF）上进行改进,加入了补偿因子和付费权重值,使得改进型跨层调度算法,在吞吐量有一定提高的情况下,有效地降低了高优先级业务的丢包率和时延,并确保了高优先级业务的公平性。     

IEEE802.15.4标准的自适应GTS调度机制

介绍了IEEE 802.15.4协议的GTS调度机制。基于现有的IEEE802.15.4MAC协议,提出了一种针对传输时延和公平性问题的自适应GTS调度(Adaptive GTS Allocation,AGA)算法。建立相应的自适应GTS仿真模型,对GTS算法的性能进行评估,并用网络演算理论对GTS进行理论分析。结果表明,提出的GTS调度机制在传输时延和公平性上明显优于现有的GTS调度方案。     

Joint user pairing and power allocation in multi-slicing NOMA system

Joint user pairing and power allocation approach is investigated to meet the rate requirement of enhanced mobile broadband (eMBB) slicing and delay constraint of ultra-reliable low-latency communication (URLLC) slicing simultaneously in downlink non-orthogonal multiple access ( NOMA) system. For maximizing the proportional fairness among mobile terminals, a two-step algorithm is proposed. For a given user sets, the optimal user pairing sets and the factor of the power allocation in a group were obtained to ensure the quality of service (QoS) and the isolation between different types of slicings. Simulation results show that the proposed joint algorithm can provide better throughput than orthogonal multiple access (OMA).     

Utility-based adaptive radio resource allocation in OFDM wireless networks with traffic prioritization

In this letter, a joint transmit scheduling and dynamic sub-carrier and power allocation method is proposed to exploit multi-user diversity in downlink packet transmission in an OFDM wireless network with mixed real-time and non-real-time traffic patterns. To balance efficiency and fairness and to satisfy the QoS requirements of real-time users, we utilize a utility-based framework and propose a polynomial-time heuristic algorithm to solve the formulated optimization problem. The distinguishing feature of the proposed method is that it gives in one shot, the transmission scheduling, the sub-carriers assigned to each user, and the power allocated to each sub-carrier, based on a fair and efficient framework while satisfying the delay requirements of real-time users.     

正交频分多址系统中一种面向多业务应用的自适应资源分配算法

针对正交频分多址(OFDMA)系统下行链路多业务自适应调度的问题,该文首先以最大化系统吞吐量为优化目标、每种业务的服务质量(QoS)保证为约束条件,建立了一种通用的多业务自适应资源分配模型。为解决此优化问题,提出了一种具体的自适应资源调度算法。该算法对实时业务按照用户选择最好的信道的原则分配尽可能少的资源以保证其QoS,对非实时业务把尽可能多的剩余资源按照信道选择最好的用户的原则进行分配,充分利用信道资源,提升系统容量。仿真结果表明,该算法保证了下行OFDMA系统吞吐量的同时,在实时业务的延时和丢包率等方面有一定的优越性。     

Resource allocation algorithm for LTE networks using fuzzy based adaptive priority and effective bandwidth estimation

In this paper, we propose a scheme to allocate resource blocks for the Long Term Evolution (LTE) downlink based on the estimation of the effective bandwidths of traffic flows, where users’ priorities are adaptively computed using fuzzy logic. The effective bandwidth of each user traffic flow that is estimated through the parameters of the adaptive β-Multifractal Wavelet Mode modeling, is used to attain their quality of service (QoS) parameters. The proposed allocation scheme aims to guarantee the QoS parameters of users respecting the constraints of modulation and code schemes (modulation and coding scheme) of the LTE downlink transmission. The proposed algorithm considers the average channel quality and the adaptive estimation of effective bandwidth to decide about the scheduling of available radio resources. The efficiency of the proposed scheme is verified through simulations and compared to other algorithms in the literature in terms of parameters such as: system throughput, required data rate not provided, fairness index, data loss rate and network delay.     

一种用于MIMO-OFDMA系统的调度和资源分配算法

该文提出了一种用于MIMO-OFDMA 系统下行链路的调度和资源分配算法,该方法能够优化利用空时频三维资源,为不同类业务提供QoS保证。该算法不仅结合了先进的物理层技术,同时从媒体接入控制(MAC)层考虑了业务特性、QoS 需求以及用户公平性等因素对资源进行分配。仿真结果表明,该算法在保证多业务传输质量的同时提高系统吞吐量。     

Downlink scheduling of multiuser MIMO systems with transmit beamforming

This article deals with downlink scheduling for multiuser multiple-input multiple-output （MIMO） systems, where the base station communicates with multiple users simultaneously through transmit beamforming. Most of the existing transmission schemes for multiuser MIMO systems focus on optimizing sum rate performance of the system. The individual quality of service （QoS） requirements （such as packet delay and minimum transmission rate for the data traffic） are rarely considered. In this article, a novel scheduling strategy is proposed, where we try to optimize the global system performance under individual QoS constraints. By performing scheduling into two steps, namely successive user selection and power allocation, the scheduler can achieve efficient resource utilization while maintaining the QoS requirements of all users. Extensive simulations and analysis are given to show the effectiveness of the proposed scheduler.     

Max-utility subcarrier allocation for heterogeneous services in wireless OFDM system

In future wireless network, one user will require multiple homogeneous or heterogeneous services simultaneously. Then, the scheduling algorithm is not only responsible for assigning a resource block to different users but also sharing the assigned resource block among multiple services for one user. Most of the traditional scheduling algorithms are designed to serve one service per user, and cannot be applied directly to this scenario because of the fairness criterion. This article focuses on adaptive resource allocation for multiple services per user at the downlink of orthogonal frequency division multiplexing (OFDM) based system. This article addresses this integrative resource scheduling problem based on utility function. First, the optimal algorithm for dynamic subcarrier allocation and share is deduced for homogeneous best-effort service system. Then the algorithm is extended to heterogeneous services system by classifying the delay sensitive service according to the head-of-line packet delay. The design goal is to maximize aggregate utility function to exploit multiuser diversity gain to the greatest extent even as guaranteeing quality of service (QoS) for delay sensitive service.     

Joint packet scheduling and resource allocation with quality fairness for wireless VoD system

This paper investigates the problem of multiuser packet scheduling and resource allocation for video transmission over downlink OFDMA networks. A cross-layer approach is proposed to maximize the received video quality under the video quality fairness constraint. Unlike the previous methods in which the objective index is estimated the video quality in the unit of bit, the proposed algorithm develops the objective index in unit of packet, which is more fit for video transmission. In order to solve the optimization problem, a suboptimal algorithm of joint packet scheduling and resource allocation is proposed. The algorithm is compatible with the emerging wireless standards, such as IEEE 802.16. The simulation results show that the proposed method outperforms the conventional resource allocation schemes in terms of received video qualities and quality fairness.     

Fairness based resource allocation for multiuser MISO-OFDMA systems with beamforming

Resource allocation problem in multiuser multiple input single output-orthogonal frequency division multiple access (MISO-OFDMA) systems with downlink beamforming for frequency selective fading channels is studied. The article aims at maximizing system throughput with the constraints of total power and bit error rate (BER) while supporting fairness among users. The downlink proportional fairness (PF) scheduling problem is reformulated as a maximization of the sum of logarithmic user data rate. From necessary conditions on optimality obtained analytically by Karush-Kuhn-Tucker (KKT) condition, an efficient user selection and resource allocation algorithm is proposed. The computer simulations reveal that the proposed algorithm achieves tradeoff between system throughput and fairness among users.