A Proportional Fairness Algorithm with QoS Provision in Downlink OFDMA Systems

In this letter, we formulate a downlink packet scheduling problem for proportional fairness in orthogonal frequency division multiple access with frequency division multiple access (OFDMA) systems to derive necessary conditions for optimality, which results in efficient subcarrier and power allocation algorithms. Simulation results reveal that our proposed algorithm achieves the tradeoff between system throughput and fairness     

Efficient Packet Scheduling Using Channel Adaptive Fair Queueing in Distributed Mobile Computing Systems

In a distributed mobile computing system, an efficient packet scheduling policy is a crucial component to achieve a high utilization of the precious bandwidth resources while satisfying users' QoS (quality of service) demands. An important class of scheduling techniques, namely, the wireless fair queueing algorithms, have been extensively studied recently. However, a major drawback in existing approaches is that the channel model is overly simplified – a two-state channel (good or bad) is assumed. While it is relatively easy to analyze the system using such a simple model, the algorithms so designed are of a limited applicability in a practical environment, in which the level of burst errors is time-varying and can be exploited by using channel adaptive coding and modulation techniques. In this paper, we first argue that the existing algorithms cannot cater for a more realistic channel model and the traditional notion of fairness is not suitable. We then propose a new notion of fairness, which bounds the actual throughput normalized by channel capacity of any two data connections. Using the new fairness definition, we propose a new fair queueing algorithm called CAFQ (Channel Adaptive Fair Queueing), which, as indicated in our numerical studies, outperforms other algorithms in terms of overall system throughput and fairness among error prone connections.     

Performance Analysis of Multiuser Selection Diversity

In this paper, the performance of scheduling algorithms exploiting the multiuser selection diversity is studied. The authors consider schedulers with affordable-rate transmission and adaptive transmission based on the absolute signal-to-noise ratio (SNR) and the normalized SNR. In contrast to previous studies on multiuser diversity systems, channel dynamics is taken into consideration in this paper by a novel formulation based on the level-crossing analysis of stochastic processes. Then, a connection is made between the Doppler frequency shift, which indicates the channel temporal correlation, and the average (channel) access time, the average waiting time between accesses, and the average access rate of active users. These properties are important for the scheduler design, especially for applications where delay is a concern. In addition, analytical expressions for the system throughput and the degree of fairness when users have nonidentical average channel conditions are presented. These expressions quantify the effect of disparateness in users' average channel conditions on the system performance.      

面向电网业务质量保障的5G高可靠低时延通信资源调度方法

该文研究面向电网业务质量保障的5G 高可靠低时延通信(URLLC)的资源调度机制,以高效利用低频段蜂窝通信系统内有限的频谱和功率资源来兼顾电力终端传输速率和调度时延、调度公平性,保障不同电力业务的通信质量（QoS）。首先,基于URLLC的高可靠低时延传输特性,建立电力终端多小区下行传输模型。然后,提出面向系统下行吞吐量最大化的资源分配问题模型并对其进行分步求解,分别提出基于定价机制与非合作博弈的功率分配算法和基于调度时延要求的改进比例公平算法（DPF）动态调度信道资源。仿真结果表明,提出的资源调度方法能在保证一定传输可靠性和公平性的条件下降低电力终端调度时延,满足不同业务等级的QoS需求,与已知算法对比有一定的优越性。     

Spatial Transmission Mode Switching in Multiuser MIMO-OFDM Systems With User Fairness

Multiantenna radio systems allow accessing the channel in diversity or spatial multiplexing (SMUX) mode. Adequate switching between these modes according to current channel conditions was shown to yield significant performance improvements while requiring little feedback from the receiving side. We present a transmission concept for the downlink of a multiuser multiple-input–multiple-output orthogonal frequency-division-multiplexing (MU-MIMO-OFDM) system aiming at high user rates with limited feedback demands. An extended score-based scheduling (SB) approach ensures fair-resource allocation to the users, whereas transmission mode switching is used to guarantee high user rates. The degree of fairness of the scheduler can be adapted by adequately configuring a weighting function for the scores. Comparison with single-mode schemes reveals substantial throughput gains of the adaptive switching concept. Furthermore, targeting maximum throughput, we show that a considerable proportion of the capacity of the MIMO broadcast channel (BC) can be achieved with a comparatively low amount of required feedback.      

Achieving Long-Term Fairness and Optimum Multiuser Diversity Gain in Time-Varying Broadcast Channels

In this paper, a downlink system in which a single-antenna base station communicates with k single antenna users over a time-correlated fading channel is considered. It is assumed that each receiver knows its own channel state, while the rate of the channel variation for all users and the corresponding initial fading gains are known to the base station. The average (per channel use) throughput of the system is studied by applying various adaptive signaling schemes. Assuming a large number of users in the system, it is shown that using a scheduling scheme in which the base station transmits to the user with the maximum initial fading gain, while using a fixed codeword length for all users, achieves the order of the maximum throughput. Moreover, an alternative scheduling scheme is proposed (by accounting for users' delays) and shown to achieve the optimum long-term fairness, while preserving the order of the maximum throughput.     

Opportunistic packet scheduling algorithm for non-real-time service with a soft QoS requirement in a mobile broadband wireless access system

In this paper, we present a packet scheduling algorithm for a non-real-time service, with soft QoS requirements, which allows for degrading the QoS level, e.g., typically the packet delay, whenever necessary, in mobile broadband wireless Internet access systems. This algorithm is designed to properly trade off system throughput and delay performance, which can improve the system capacity by relaxing the delay constraint with respect to the underlying soft QoS requirement. This is as opposed to most of the existing packet scheduling algorithms for non-real-time service which are simply designed to maximize the system throughput without a delay constraint. The proposed adaptive exponential scheduling algorithm intentionally introduces additional delay to some users, especially under bad channel conditions, opportunistically allowing for serving users only under good channel conditions, as long as the resulting QoS degradation is acceptable for non-real-time service users. The results from a system-level simulation demonstrate that the system capacity can be significantly increased over existing algorithms, by as much as 65%, using the adaptive exponential scheduling algorithm while satisfying the given QoS-level requirements.     

Dynamic channel-sensitive scheduling algorithms for wireless data throughput optimization

The relative delay tolerance of data applications, together with bursty traffic characteristics, opens up the possibility for scheduling transmissions so as to optimize throughput. A particularly attractive approach in fading environments is to exploit the variations in the channel conditions and transmit to the user with the current "best" channel. We show that the "best" user may be identified as the maximum-rate user when feasible rates are weighted with some appropriately determined coefficients. Interpreting the coefficients as shadow prices, or reward values, the optimal strategy may thus be viewed as a revenue-based policy, which always assigns the transmission slot to the user yielding the maximum revenue. Calculating the optimal-revenue vector directly is a formidable task, requiring detailed information on the channel statistics. Instead, we present adaptive algorithms for determining the optimal-revenue vector online in an iterative fashion, without the need for explicit knowledge of the channel behavior. Starting from an arbitrary initial vector, the algorithms iteratively adjust the reward values to compensate for observed deviations from the target throughput rates. The algorithms are validated through extensive numerical experiments. Besides verifying long-run convergence, we also examine the transient performance, in particular the rate of convergence to the optimal-revenue vector. The results show that the target throughput ratios are tightly maintained and that the algorithms are well able to track sudden changes in channel conditions or throughput targets.     

Multicast Link Adaptation in Reliable Transmission Over Geostationary Satellite Networks

The exploitation of fluctuating channel conditions in link adaption techniques for unicast transmission has been shown to provide large system capacity gains. However, the problem of choosing transmission rates for multicast transmission has not been thoroughly investigated. In this paper, we investigate multicast adaptive techniques for reliable data delivery in GEO satellite networks. An optimal multicast link adaptation is proposed with the aim to maximise terminal throughput whilst increasing resource utilization and fairness in the face of diverse channel conditions. Via simulation results and theoretical analysis, the proposed algorithm has shown to outperform other alternative multicast link adaptation techniques especially when the terminals are in vigorous channel conditions.     

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.     

WCFQ: an opportunistic wireless scheduler with statistical fairness bounds

We present wireless credit-based fair queuing (WCFQ), a new scheduler for wireless packet networks with provable statistical short- and long-term fairness guarantees. WCFQ exploits the fact that users contending for the wireless medium will have different "costs" of transmission depending on their current channel condition. For example, in systems with variable coding, a user with a high-quality channel can exploit its low-cost channel and transmit at a higher data rate. Similarly, a user in a code-division multiple access system with a high-quality channel can use a lower transmission power. Thus, WCFQ provides a mechanism to exploit inherent variations in channel conditions and select low-cost users in order to increase the system's overall performance (e.g., total throughput). However, opportunistic selection of the best user must be balanced with fairness considerations. In WCFQ, we use a credit abstraction and a general "cost function" to address these conflicting objectives. This provides system operators with the flexibility to achieve a range of performance behaviors between perfect fairness of temporal access independent of channel conditions and purely opportunistic scheduling of the best user without consideration of fairness. To quantify the system's fairness characteristics within this range, we develop an analytical model that provides a statistical fairness bound in terms of the cost function and the statistical properties of the channel. An extensive set of simulations indicate that the scheme is able to achieve significant throughput gains while balancing temporal fairness constraints.     

Scheduling and Resource Allocation Strategy for OFDMA Systems Over Time-Varying Channels

A cross-layer scheduling and resource allocation (SRA) strategy for an adaptive modulation and coding (AMC) based orthogonal frequency multiple access (OFDMA) system is proposed. The objective of this paper is to maximize the system throughput as a function of the bit error rate (BER) and the spectral efficiency based on the selected modulation and coding schemes (MCSs). The proposed strategy contains two main algorithms. Firstly, the scheduling algorithm that aims to maximize the average system throughput by arranging the users in distinct queues according to their priorities and selecting the best user of each queue individually in order to guarantee a fair user service amongst different priority levels. Secondly, the resource allocation algorithm that allocates the user, bit and power based on the channel conditions of the scheduling users and the transmission power constraints. The transmitter of the investigated AMC-OFDMA system at the assigned base station (BS) divides the transmitted OFDMA frame into sub-channels and assigns each sub-channel to a scheduled user. In this paper, we compare the performance of the proposed SRA with the conventional first in first out (FIFO) queuing based scheduling and resource allocation strategies used for an AMC-OFDMA system. The simulation results show that the investigated AMC-OFDMA system based on the proposed SRA strategy outperforms the conventional approaches.     

Predictive channel scheduling algorithm between macro base station and micro base station group

A novel predictive channel scheduling algorithm was proposed for non-real-time traffic transmission between macro-base stations and micro-base stations in 5G ultra-cellular networks.First,based on the stochastic stationary process characteristics of wireless channels between stationary communication agents,a discrete channel state probability space was established for the scheduling process from the perspective of classical probability theory,and the event domain was segmented.Then,the efficient scheduling of multi-user,multi-non-real-time services was realized by probability numerical calculation of each event domain.The theoretical analysis and simulation results show that the algorithm has low computational complexity.Compared with other classical scheduling algorithms,the new algorithm can optimize traffic transmission in a longer time dimension,approximate the maximum signal-to-noise ratio algorithm in throughput performance,and increase system throughput by about 14% under heavy load.At the same time,the new algorithm is accurate.Quantitative computation achieves a self-adaption match between the expected traffic rate and the actual scheduling rate.     

Throughput and Channel Access Statistics of Generalized Selection Multiuser Scheduling

To provide a near-optimal low-complexity solution to parallel multiuser scheduling in code-division multiple-access (CDMA), we propose generalized selection multiuser diversity (GSMuD) schemes with multi-code channel assignment and analyze their performance. The proposed GSMuD (Lc, L) schemes rank a total of L users awaiting transmissions by their signal-tonoise ratios (SNRs) and select the Lc (1 ? Lc ? L) users with the largest absolute (or normalized) SNRs for parallel channel access, which achieve near-optimal sum rate with a low scheduling complexity. The sum and individual channel throughput rates, second order statistics, fairness, and channel access statistics of the proposed GSMuD schemes are derived, taking into account different types of generalized fading channels. Compared to the round robin (RR) scheduling without SNR ranking, the GSMuD with normalized SNR ranking achieves a substantially higher sum rate while maintaining fairness. GSMuD also significantly improves the channel access performance and the degree of fairness than selective multiuser diversity (SMuD), which selects one best user only at each time slot.     

基于HSDPA的信道相关分组调度算法研究

针对HSDPA(高速下行分组接入)系统中几种支持非实时业务的经典分组调度算法Max C/I(最大载干比)和PF(正比公平)算法缺乏系统公平性的问题,提出一种基于HSDPA的快速公平分组调度算法。此算法在保证信道瞬时条件和系统吞吐量的前提下,旨在为那些平均吞吐量低于某一阈值的用户提供优先被服务的机会。仿真结果表明,此算法较之Max C/I和PF算法能够保证用户间的长期公平性。     

自适应OFDMA系统无线资源分配和分组数据调度算法的研究

在对无线资源分配和下行链路分组数据调度算法研究的基础上，提出了一种适应于自适应OFDMA系统的联合算法，即K＆H／MPF算法。理论分析和仿真结果表明：该算法在满足不同用户QoS要求的前提下，不但能够提供比多载波正比公平调度器更高的容量增益，而且以极大的灵活性实现了用户数据的公平发送。     

Scheduling schemes for multimedia service in wireless OFDM systems

Scheduling schemes play a key role in the system performance of broadband wireless systems such as WLANs/WMANs. Maximal SNR and round robin are two conventional scheduling strategies that emphasize efficiency and fairness, respectively. The proportional fair scheme provides a trade-off between efficiency and fairness, and has been well studied in TDMA and CDMA systems. In this article we extended the PF scheduling scheme to OFDM-based BWSs (OPF). In addition, we propose three variations: adaptive OPF (AOPF), multimedia AOPF (MAOPF), and normalized MAOPF (NMAOPF) in order to meet the QoS requirements for multirate services in multimedia systems. The adaptive modulation and coding schemes in time varying and frequency selective fading are considered. The system performances of the algorithms are compared in terms of efficiency (throughput and mean packet delay) and fairness (user satisfaction rate and average user rate). Joint physical and media access control layer simulation results show that AOPF and MAOPF can improve throughput at the cost of fairness, and NMAOPF can provide the highest throughput without losing fairness.     

虚拟两天线蜂窝网络中考虑中继公平性的协作博弈调度方法(英文)

In thsssse cellular network, Relay Stations (RSs) help to improve the system performance; however, little work has been done considering the fairness of RSs. In this paper, we study the cooperative game approaches for scheduling in the wireless relay networks with two-virtual-antenna array mode. After defining the metric of relay channel capacity, we form a cooperative game for scheduling and present the interpretation of three different utilization objectives physically and mathematically. Then, a Nash Bargaining Solution (NBS) is utilized for resource allocation considering the traffic load fairness for relays. After proving the existence and uniqueness of NBS in Cooperative Game (CG-NBS), we are able to resolve the resource allocation problem in the cellular relay network by the relay selection and subcarrier assignment policy and the power allocation algorithm for both RSs and UEs. Simulation results reveal that the proposed CG-NBS scheme achieves better tradeoff between relay fairness and system throughput than the conventional Maximal Rate Optimization and Maximal Minimal Fairness methods.     

Adaptive transmission with finite code rates

This work examines a transmission system which adapts a finite set of code rates and a continuously varying transmit power. We propose a technique for finding the average reliable throughput (ART)-maximizing policy satisfying an average power constraint for a slow fading additive white Gaussian noise (AWGN) channel. ART is a measure motivated by the information outage and can, for example, be argued to characterize the long-term average throughput of a data packet transmission system with a transmit queue and a feedback protocol which requests retransmission of erroneously received packets. Given the size of the code rate set L, the ART-maximizing policy has the following properties. 1. For a given set of code rates, the optimum allocation policy suggests quantizing the fading state space into a set of L+1 corresponding intervals. For each quantization interval the optimal policy specifies a minimum transmitted power assignment which guarantees zero information outage. The optimum average power assignments across quantization intervals have a waterfilling relationship with respect to the interval channel quality measure. 2. The joint optimization of quantization intervals and the corresponding rate assignments are shown to have multiple local maxima. Nevertheless, this optimization problem can be reduced to a simple one-dimensional search over a parameter which determines the outage interval. Numerical results show that, in a Rayleigh-fading channel, there is only a 1-dB gap between the ergodic capacity and the throughput of a two-rate adaptive transmission system when the throughput is less than 6 bits/s/Hz. A special case of our optimal policy assignment is the optimal power and rate policy for an adaptive M-QAM system.     

The Effect of On-Off Scheduling to the Required Transmit Power in Systems with Fast Power Control

Physical layer channel-aware scheduling may significantly improve coverage and throughput of IP based services in wireless cellular networks, and the feasibility of such schedulers is actively studied within 3G and 4G systems. A channel-aware scheduler requires access to instantaneous channel state information in order to direct transmission to users with favorable channel conditions. In frequency division duplex (FDD) systems, this requires a fast feedback channel between mobile and base stations, and the overhead of the feedback control channel should be kept as low as possible.In this paper, we study the effect of control channel overhead to on-off scheduling (OOS) when fast transmit power control is applied in data and control channels. On-off scheduling is a simple channel-aware scheduling algorithm, where transmission to a user is suspended if the transmit power exceeds a given threshold. On-off scheduling is applied on the data channel while control channel is always on so that the scheduler is able to obtain channel state information from active users. The gain of OOS strongly depends on the power ratio between control and data channels, and increased interference due to control signaling and decreased interference due to channel-aware scheduling should be jointly considered in system design. Gains in the required transmit power are translated into gains in coverage and capacity assuming WCDMA parameters, and the results can be applied, e.g., when designing scheduling algorithms and corresponding signaling formats for WCDMA uplink.