车联网中基于NOMA-MEC的卸载策略研究

随着车联网(IoV)的迅猛发展,请求进行任务卸载的汽车终端用户也逐渐增长,而基于移动边缘计算(MEC)的通信网络能够有效地解决任务卸载在上行传输时延较高的挑战,但是该网络模型同时也面临着信道资源不足的问题。该文引入的非正交多址(NOMA)技术相较于正交多址(OMA)能够在相同的信道资源条件下为更多的用户提供任务卸载,同时考虑到任务卸载过程中多方面的影响因子,提出了混合NOMA-MEC卸载策略。该文设计了一种基于深度学习网络(DQN)的博弈算法,帮助车辆用户进行信道选择,并通过神经网络多次迭代学习,为用户提供最优的功率分配策略。仿真结果表明,该文所提出的混合NOMA-MEC卸载策略能够有效地优化多用户卸载的时延以及能耗,最大限度保证用户效益。     

Optimal resource allocation in multiservice CDMA networks

This paper addresses the problem of dynamic resource allocation in a multiservice direct-sequence code-division multiple-access (DS-CDMA) wireless network supporting real-time (RT) and nonreal-time (NRT) communication services. For RT users, a simple transmission power allocation strategy is assumed that maximizes the amount of capacity available to NRT users without violating quality of service requirements of RT users. For NRT users, a joint transmission power and spreading gain (transmission rate) allocation strategy, obtained via the solution of a constrained optimization problem, is provided. The solution maximizes the aggregate NRT throughput, subject to peak transmission power constraints and the capacity constraint imposed by RT users. The optimization problem is solved in a closed form, and the resulting resource allocation strategy is simple to implement as a hybrid CDMA/time-division multiple-access strategy. Numerical results are presented showing that the optimal resource allocation strategy can offer substantial performance gains over other conventional resource allocation strategies for DS-CDMA networks.     

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。     

Resource Allocation in OFDMA Wireless Communications Systems Supporting Multimedia Services

We design a resource allocation algorithm for downlink of orthogonal frequency division multiple access (OFDMA) systems supporting real-time (RT) and best-effort (BE) services simultaneously over a time-varying wireless channel. The proposed algorithm aims at maximizing system throughput while satisfying quality of service (QoS) requirements of the RT and BE services. We take two kinds of QoS requirements into account. One is the required average transmission rate for both RT and BE services. The other is the tolerable average absolute deviation of transmission rate (AADTR) just for the RT services, which is used to control the fluctuation in transmission rates and to limit the RT packet delay to a moderate level. We formulate the optimization problem representing the resource allocation under consideration and solve it by using the dual optimization technique and the projection stochastic subgradient method. Simulation results show that the proposed algorithm well meets the QoS requirements with the high throughput and outperforms the modified largest weighted delay first (M-LWDF) algorithm that supports similar QoS requirements.     

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.     

博弈论框架下认知小蜂窝网络的动态资源分配算法

为提高认知小蜂窝网络(CSCN)的系统容量,本文基于博弈论框架分析了上行链路中频谱、小蜂窝基站和功率的动态分配行为.传统的频谱分配方案只考虑了异质网路中相互独立频带间的最优分配,而没有考虑可重叠频段间的分配模式和上行链路资源的联合优化.基于此,本文提出了一种具有频带可交叉特性的联合分配模型.通过引入干扰温度限制、全新的干扰算子和记忆因子构造了一种新型的上行注水功率算法.仿真结果表明,基于博弈理论的动态选择特性和干扰温度的干扰避免准则,本算法可以有效提高CSCN的吞吐量和鲁棒性.     

QoS-guaranteed multi-relay selection and power allocation optimization in cooperative systems

This paper investigates the relay selection and power allocation problem in multi-user based cooperative networks, where intermediate relay nodes help source forward information to destination using decode-and-forward (DF) relaying protocol. Specifically, we propose a novel multi-relay nodes selection strategy taking both instantaneous channel state information (I-CSI) and residual energy into consideration, by which 'emergence' diversity gain can be achieved and the imbalance of resource utilization can be overcome. Besides, using Largangian dual-primal decomposition and subgradient projection approach, an optimal power allocation algorithm at source and cooperative relay nodes is presented with the constraints of each user's individual quality of service (QoS) requirements and system total transmit power. Theoretical analysis and simulation results demonstrate that the proposed scheme can significantly improve energy efficiency, while guaranteeing a good balance between achievable data rate and average network lifetime with relatively low implementation complexity.     

具有时延QoS保证的OFDM中继系统子载波配对与功率分配算法

 本文研究具有直接通信链路的OFDM解码转发(Decode-and-Forward,DF)中继系统的子载波配对与功率分配算法,目标是在满足业务时延QoS要求的前提下最大化系统容量.利用有效容量模型,首先把OFDM DF中继系统的子载波配对与功率分配问题形成为混合整数规划问题,然后把其转化为连续松弛凸规划问题,利用凸优化方法得到原问题的最优解,从而提出了一种联合最优的子载波配对与功率分配迭代算法.理论推导结果和仿真结果表明,最优子载波配对与功率分配不仅取决于子载波的信道增益,还取决于业务的时延QoS要求.与已有算法相比,本文算法获得的有效容量最大.     

DF协作中继网络基于买者/卖者博弈的中继选择和功率分配策略

该文针对采用解码-转发(DF)协议的协作中继网络,提出了一种基于买者-卖者博弈的中继选择和功率分配策略,通过将用户建模为买者,可以以最大效用为标准选择最优中继和确定最佳的购买功率;将中继建模为卖者,可通过先市场后利润的功率价格调整策略获得最大的利润。分析了两者博弈达到平衡的条件并进行了仿真,结果验证了纳什均衡点的存在并表明,该策略计算量少,收敛速度快,实用性强,在兼顾用户和中继节点的利益的同时可以有效提高用户的传输速率,扩大基站的覆盖范围,提高功率利用效率。     

Resource allocation based on cross-layer QoS-guaranteed scheduling for multi-service multi-user MIMO–OFDMA systems

Cross-layer strategies for resource allocation in wireless networks are essential to guaranty an efficient utilization of the scarce resource. In this paper, we present an efficient radio resource allocation scheme based on PHY/MAC cross layer design and QoS-guaranteed scheduling for multi-user (MU), multi-service (MS), multi-input multi-output (MIMO) concept, orthogonal frequency division multiple access (OFDMA) systems. It is about a downlink multimedia transmission chain in which the available resources as power and bandwidth, are dynamically allocated according to the system parameters. Among these parameters, we can mention the physical link elements such as channel state information, spectral efficiency and error code corrector rate, and MAC link variables, which correspond to the users QoS requirements and the queue status. Primarily, we use a jointly method which parametrizes these system parameters, according to the total power, and the bit error rate constraints. Secondly, we propose a QoS-guaranteed scheduling that shares the sub-carriers to the users. These users request several type of traffic under throughput threshold constraints. The main objective in this work is to adjust the average throughput per service of each user, according to their needs and likewise to satisfy a great number of connexions. Subsequently, we consider a model of moderated compartmentalization between various classes of services by partitioning the total bandwidth into several parts. Each class of service will occupy a part of the bandwidth and will be transmitted over a maximum number of sub-carriers. The simulation results show that the proposed strategy provides a more interesting performance improvement (in terms of average data rate and user satisfaction) than other existing resource allocation schemes, such as nonadaptive resource allocation strategy. The performances are also analyzed and compared for the two multi-service multi-user MIMO–OFDMA systems; with sub-carriers partitioning and without sub-carriers partitioning.     

Power control and channel allocation for real‐time applications in cellular networks

The next‐generation packet‐based wireless cellular network will provide real‐time services for delay‐sensitive applications. To make the next‐generation cellular network successful, it is critical that the network utilizes the resource efficiently while satisfying quality of service (QoS) requirements of real‐time users. In this paper, we consider the problem of power control and dynamic channel allocation for the downlink of a multi‐channel, multi‐user wireless cellular network. We assume that the transmitter (the base‐station) has the perfect knowledge of the channel gain. At each transmission slot, a scheduler allots the transmission power and channel access for all the users based on the instantaneous channel gains and QoS requirements of users. We propose three schemes for power control and dynamic channel allocation, which utilize multi‐user diversity and frequency diversity. Our results show that compared to the benchmark scheme, which does not utilize multi‐user diversity and power control, our proposed schemes substantially reduce the resource usage while explicitly guaranteeing the users' QoS requirements. Copyright © 2007 John Wiley & Sons, Ltd.     

车联网中基于NOMA-MEC的卸载策略研究

随着车联网(IoV)的迅猛发展,请求进行任务卸载的汽车终端用户也逐渐增长,而基于移动边缘计算(MEC)的通信网络能够有效地解决任务卸载在上行传输时延较高的挑战,但是该网络模型同时也面临着信道资源不足的问题。该文引入的非正交多址(NOMA)技术相较于正交多址(OMA)能够在相同的信道资源条件下为更多的用户提供任务卸载,同时考虑到任务卸载过程中多方面的影响因子,提出了混合NOMA-MEC卸载策略。该文设计了一种基于深度学习网络(DQN)的博弈算法,帮助车辆用户进行信道选择,并通过神经网络多次迭代学习,为用户提供最优的功率分配策略。仿真结果表明,该文所提出的混合NOMA-MEC卸载策略能够有效地优化多用户卸载的时延以及能耗,最大限度保证用户效益。     

基于QoS保证的多用户OFDM系统跨层资源分配

针对正交频分复用(OFDM)系统资源分配和调度问题,提出一种基于第三代移动通信长期演进(LTE)系统的分块跨层资源分配算法。此算法考虑物理层的信道状态信息、媒体接入层(MAC)的有限用户缓存队列长度、用户的丢失率和时延等QoS要求,以提高系统频谱效率为总体目标。通过从实时视频业务和混合业务两种业务类型下进行大量对比分析,得出提出的算法能有效提高系统的频谱效率和降低系统时延。     

A Cross-Layer Packet Scheduling Scheme for Multimedia Broadcasting via Satellite Digital Multimedia Broadcasting System [Advances in Mobile Multimedia]

In recent years, multimedia content broadcasting via satellite has attracted increased attention. The satellite digital multimedia broadcasting (S-DMB) system has emerged as one of the most promising alternatives for the efficient delivery of multimedia broadcast multicast service (MBMS). The design of an efficient radio resource management (RRM) strategy, especially the packet scheduling scheme, becomes a key technique for provisioning multimedia services at required quality of service (QoS) in S-DMB. In this article, we propose a novel cross-layer packet scheduling scheme that consists of a combined delay and rate differentiation (CDRD) service prioritization algorithm and a dynamic rate matching (DRM)-based resource allocation algorithm. The proposed scheme considers multiple key factors that span from the application layer to the physical layer, aiming at simultaneously guaranteeing diverse QoS while utilizing radio resources efficiently under the system power and resource constraints. Simulation results demonstrate that the proposed cross-layer scheme achieves significantly better performance than existing schemes in queuing delay, jitter, and channel utilization.     

认知无线电网络中最优分组长度设计

为满足不同种类多媒体应用的服务质量需求,研究了一个多等级多信道认知无线电网络中的资源分配问题。根据时延和吞吐量为该网络模型定义一个效用函数并最大化这个效用函数的期望值。首先用不考虑传输功率分配的"浪费功率的方式"设计分组长度。然后在选择分组长度时考虑传输功率分配提出一种基于贪婪算法的改进方式,得到了最优分组长度和相应的传输功率。MATLAB的仿真结果表明,在传输功率受限下,当达到相同效用值时,改进方式和"浪费功率的方式"相比能减小传输功率,并取得更加合理的分组长度,而且能更好地满足带宽需求,这是由于改进方式不仅考虑了各个信道上数据包的到达时间间隔,还考虑了信道增益。     

Distributed congestion control strategy using network utility maximization theory in VANET

Cooperative vehicle safety system (CVSS) rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization (NUM) theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control (UBRCC) algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.     

基于对偶分解的OFDMA系统资源分配算法

该文针对多业务OFDMA系统资源分配问题,建立了考虑业务服务质量、数据到达、系统约束的最优化问题。分析了不同业务的速率约束、延时约束和队列长度之间的关系,并利用对偶分解方法将原问题分解为若干独立子问题,分别得到了最优资源块与最优功率分配规则,进而提出了基于对偶分解的最优资源分配算法。仿真结果表明,该算法在业务违反概率较低、公平性较好、算法复杂度略有上升的情况下,可以实现非实时业务吞吐量最大化。     

Spectrum resource allocation method of maximizing transmission rate in cognitive heterogeneous wireless networks

Aiming at the problem that it is difficult to allocate spectrum resources to secondary users efficiently in cognitive heterogeneous wireless networks with heterogeneous spectrum attributes,dynamic channel conditions and diverse service requirements,a spectrum resource allocation strategy with maximum transmission rate was proposed.Firstly,the strategy aimed at maximizing the total transmission rate,and constrained the limited spectrum resources and user service requirements to construct a non-linear multi-constrained spectrum resource allocation 0-1 planning model.Then a polynomial time complexity simplification method was designed.According to idle spectrum information,channel conditions,business requirements and allocation decision history information,and the benefit matrix was constructed and modified to achieve constraint simplification,and the execution efficiency was improved by improving the coefficient matrix transformation strategy of the traditional Hungarian algorithm.Finally,the performance of the method was compared and analyzed by experiments.Experimental results show that the proposed method has higher transmission rate and execution efficiency.     

Low complexity resource allocation and scheduling algorithms for downlink SDMA systems

The downlink zero-forcing beamforming strategy in the case of random packet arrivals is investigated. Under this setting, the relevant fairness criterion is the stabilization of all buffer queues which guarantees a bounded average delay for all users. It has been shown that allocating resources to maximize a queue-length-weighted sum of the rates is a stabilizing policy. However, the high complexity of user selection and the feasible rates determination for optimal scheme may prevent the real-time scheduling operation. Two low complexity algorithms are provided taking the channel state, queue state and orthogonality into account. In particular, the authors pick the first user with the largest product between channel gain and queuing length, and select the remaining users to construct candidate user set based on the greedy user selection method or channel orthogonal user selection method. Then, the power and rate allocation for the selected users are implemented based on the modified water-filling method. The complexity of the proposed algorithms is analyzed. The average delay and average throughput are studied in homogeneous scenarios and heterogeneous scenarios, respectively. Simulation results show that the proposed algorithms can take full advantage of the multi-user diversity gain and provide average delay (or throughput) and fairness improvement compared with channel-aware-only schemes.     

基于速率约束的OFDM中继链路能效最优资源分配策略

该文研究解码转发(DF)模式的OFDM中继链路的能效最大化资源分配问题。与现有典型的固定速率最小化发射功率或无约束最大化能效算法不同,该文考虑电路功率消耗的前提下,将问题建模为以最大化系统能效为目标,同时考虑用户最小速率需求、源节点S和中继节点R各自总发射功率约束下的联合子载波配对和最优功率分配问题。证明了速率和功率联合约束条件下中继链路全局能效最优解的唯一性,在此基础上提出一种低复杂度联合最优资源分配策略。仿真结果表明,该文所提方案能够在最小速率和S/R节点最大发射功率约束下自适应分配功率资源,实现系统能效最优,并能够降低链路的中断概率。