面向船联网的NOMA系统用户公平性研究

非正交多址技术(Non-orthogonal Multiple Access, NOMA)有助于提升船联网的连接数量和频谱效率。通过研究公平性约束下船联网NOMA系统的能量效率优化问题,设计基于速率方差的用户公平性因子,并提出了一种公平性约束下NOMA系统的能量效率优化策略。首先,假设基站到各个簇的发射功率相同且簇内用户数固定,以最大化能量效率作为用户分簇的目标,利用遗传算法对用户分簇方案进行优化;其次,在满足最小公平因子的条件下对簇内用户间的功率分配进行优化。仿真结果表明该优化策略能提高能量效率且用户公平性得到了保证。     

一种新型的OFDMA比例公平资源分配算法

针对已有算法对系统容量和高公平性兼顾较差的情况,提出了一种满足公平性的系统容量最大化资源分配算法。在子载波分配中通过建立信道效率控制模型,给当前用户分配信道效率最高的子载波,将信道增益低于门限值的子载波重新分配,改进了最大化最小(max-min)用户速率模型。在功率分配中将系统模型转化成用注水线表示的数学模型,首先求解各用户的注水线,再求解各用户的功率分配,保证了用户间比例公平性。两种信噪比情形下的仿真和分析表明,整个方案计算复杂度稍低,系统容量获得较大提升,并且用户间的公平性始终为1。     

LTE—Advanced系统基于Relay的下行集中式资源分配算法研究

传统的蜂窝系统频谱资源缺乏,小区边缘的用户需求也得到满足,传输数据的速率较小,为了提高小区的边缘用户性能及扩大小区覆盖面积,LTE-Advanced系统采用了无线中继技术。结合传统单跳网络系统的资源分配算法和LTE-Advanced系统中的无线中继技术（Relay）,提出了一种保证用户公平性的下行集中式资源分配算法,该算法在解决小区覆盖及传输速率的同时又较好地保证了用户间的公平性：该算法不仅保证了用户间的公平性还使尽可能地使每个用户的速率最大化。通过仿真表明本文提出的资源分配算法在考虑了用户间的公平性同时又使得每个用户的数据速率最大化。     

脏纸编码的多用户MIMO-OFDM系统中基于纳什公平的资源分配算法

MIMO-OFDM技术是实现大容量无线数据传输的一项关键技术。多用户系统中,在最大化系统资源利用率的同时保证用户间资源分配的公平性是系统设计的一个重要问题。该文首先分析了MIMO系统中最大化吞吐量的一种实现方式脏纸编码(DPC),然后基于纳什公平性准则提出了一种用于DPC的多用户MIMO-OFDM系统中的自适应资源分配算法。仿真结果表明,该算法在损失较小系统吞吐量的前提下,很好地保证了用户间资源分配的公平性。     

无线供电混合多址接入网络的资源分配

无线供电技术是延长无线网络节点寿命的有效方案。该文研究一个由基站和多个分簇用户组成的无线供电混合多址接入系统。系统的传输分为两个阶段。在第1阶段,基站向用户广播能量;在第2阶段,用户向基站传输信息。用户簇和用户簇之间采用时分多址接入,分时传输;同一簇内多个用户采用非正交多址接入,同时传输。该文研究联合优化系统的各阶段的传输时间、基站的发射功率、用户的发射功率等资源,分别以优化网络频谱效率和用户簇之间的公平性为目的,提出最大化网络吞吐量和最大化用户簇的最小吞吐量的联合资源分配算法。研究结果表明所提的两种算法分别能有效提高系统的频谱效率和保证用户簇之间的公平性。     

异构Femtocell网络中基于用户公平性的干扰协调

为使含有家庭基站和宏基站的异构网络(HetNet)中各用户的服务质量需求都能满足并达到用户间的公平性,在功率限制条件下对宏用户中最小的用户数据速率最大化,将此最小用户速率提供给家庭基站用户,获得各家庭基站用户的目标信干噪比(SINR),再利用对分法调整家庭基站的发射功率.仿真结果表明,该方法能够保证最小的宏用户数据速率且提高异构网络用户间的公平性.     

基于合作博弈的CPS通信资源分配算法

为了提高信息物理融合系统的通信速率,同时保证各用户的QoS需求,提出了一种基于合作博弈的CPS通信资源分配算法。将CPS中OFDMA网络下行链路的资源分配过程建模为多用户间的合作博弈,通过求解纳什议价解,实现用户间的Pareto最优性。仿真结果表明,该算法在系统速率最大化和用户公平性上获得了很好的折中,与最大化系统速率算法相比更具有公平性,与最大化最小公平性算法相比速率提高了34%,在一定程度上提高了CPS通信网络的性能。     

基于公平效用函数的多波束卫星通信下行链路波束成形算法

为了更好地平衡多波束卫星通信系统的频谱效率和能量效率,以及保证多用户服务场景下的用户服务公平性,该文提出一种基于公平效用函数的波束成形(BF)方案。具体而言,首先在同时考虑卫星发射功率最小化准则以及系统和速率最大化准则的前提下,建立一个多目标优化问题,并在最大化系统频谱效率的同时利用α公平效用函数提升用户间的服务公平性。然后利用加权和方法对复杂的多目标问题进行转换处理,并提出一种联合使用循环坐标上升(CCA)方法以及回溯直线搜索(BLS)方法的波束成形方案,从而求得最优的波束成形权矢量以及最优的帕累托解集。最后计算机仿真结果验证了所提方案的用户服务公平性,以及分析一些典型参数对公平性能的影响。并通过与其他传统方案相比,验证所提方案能够获得更高的系统频谱效率。     

双参数跨层自适应资源分配算法研究

针对多用户OFDM系统,该文提出了一种适合于混合业务的双参数跨层自适应资源分配方案,它只需调整时延补偿因子和吞吐量补偿因子两个参数,就可将现有的调度算法灵活高效地应用于系统中.仿真结果表明,该方案可以灵活地在系统功率效率和用户服务质量满意度之间取得折衷,并保证不同类型业务用户间的公平性.     

基于连续凸逼近的协作式非正交多址接入联合无线携能通信的能效优化方案

在传统的非正交多址(NOMA)系统中,通常将更多的功率分配给边缘用户以此来保证其通信质量,系统公平性以牺牲系统容量为代价。基于协作通信的NOMA系统虽可解决上述问题,但在协作阶段中心用户需承担中继的作用,这种方式必将给中心用户带来一定的负担。为了兼顾系统容量和公平性,该文提出一种基于协作通信和无线携能通信(SWIPT)的新型资源分配方案,该方案在满足边缘用户通信质量情况下,使用能量收集设备完成能量收集,通过连续凸逼近(SCA)求解目标问题最大化系统能效。仿真结果表明,与传统NOMA和协作式非正交多址接入系统(CNOMA)相比,CNOMA-SWIPT系统的能量效率得到了较大的提高,在基站最大发射功率为30 dBm时相比NOMA系统能达到60.8%的增益,相比CNOMA系统能达到比CNOMA系统高出约11.5%的增益,更符合绿色通信的发展理念。     

Introducing Fairness-Efficiency Trade-off for Energy Savings in Wireless Cooperative Networks

The focus of this paper is on a wireless cooperative network architecture, where a group of users exploits short-range wireless links to share the costs of a cellular download. To maximize the efficiency of the communication system, an optimization of parameters such as download time, monetary cost, and energy consumption can be implemented. Following this approach different portions of data shall be assigned for download to the involved users, which will then cooperatively exchange the contents on the short-range link. However, the policy of task assignment to the user terminals has a direct influence on the payoff of the single users, raising fairness issues in real implementation scenarios. Focusing on the energy savings introduced by the wireless cooperative network, in this paper we address the fairness issue by relying on game theoretic bargaining solutions. These solutions, have intrinsic properties to nicely model the duality between fairness and efficiency in the performances. An optimal trade-off algorithm between efficiency and fairness is then introduced, allowing the service coordinator to select the most appropriate bargaining solution and energy savings allocation under different constraints on fairness.     

Throughput analysis of partial channel information proportional fairness scheduling

Wireless multi-carrier communication systems that use packet schedulers based on channel knowledge have been proved their performance. Proportional fairness scheduling (PFS), if used in these systems, promises an attractive trade-off between fairness among users and system throughput. In this paper, an analytical solution is presented for the PFS throughput. Then, a simple scheme is presented to reduce the feedback signaling of the PFS without a significant loss in performance. This reduced complexity PFS attempts to meet a trade-off between multi-user diversity gain, fairness among users and low rate feedback signaling. As shown by simulations, for a large number of users compared to the number of sub-channels, this scheme kept fairness among users while minimizing the feedback signaling.     

Radio Resource Allocation Algorithms for the Downlink of Multiuser OFDM Communication Systems

This article surveys different resource allocation algorithms developed for the downlink of multiuser OFDM wireless communication systems. Dynamic resource allocation algorithms are categorized into two major classes: margin adaptive (MA) and rate adaptive (RA). The objective of the first class is to minimize the total transmit power with the constraint on users? data rates whereas in the second class, the objective is to maximize the total throughput with the constraints on the total transmit power as well as users? data rates. The overall performance of the algorithms are evaluated in terms of spectral efficiency and fairness. Considering the trade-off between these two features of the system, some algorithms attempt to reach the highest possible spectral efficiency while maintaining acceptable fairness in the system. Furthermore, a large number of RA algorithms considers rate proportionality among the users and hence, are categorized as RA with constrained-fairness. Following the problem formulation in each category, the discussed algorithms are described along with their simplifying assumptions that attempt to keep the performance close to optimum but significantly reduce the complexity of the problem. It is noted that no matter which optimization method is used, in both classes, the overall performance is improved with the increase in the number of users, due to multiuser diversity. Some on-going research areas are briefly discussed throughout the article.     

Cooperative bargaining solution for efficient and fair spectrum management in cognitive wireless networks

This paper studies the fairness among the primary users (PUs) and the secondary users (SUs) for resource allocation in cognitive radio systems. We propose a novel co‐opetition strategy based on the Kalai–Smorodinsky bargaining solution to balance the system efficiency and the fairness among users. The strategy formulates the spectrum sharing problem as a nonlinear and integral sum utility maximization subject to a set of constraints describing the co‐opetition among the PUs and the SUs. Then, we solve the maximization problem by proposing a heuristical method that consists of four steps: multi‐PU competition, PU's subcarrier contribution, multi‐SU competition, and SU's subcarrier contribution. Extensive simulation results are presented by comparing the co‐opetition strategy with several conventional ones, including the Kalai–Smorodinsky bargaining solution, sum rate maximization as well as the Max–Min. Results indicate that the co‐opetition strategy can jointly balance the system efficiency and fairness in multiuser resource allocation, as it is able to support more satisfied users and in the meanwhile improve the utility of those unsatisfied. Moreover, the co‐opetition can help enable the coexistence of the PUs and the SUs in cognitive radio systems. Copyright © 2013 John Wiley & Sons, Ltd.     

OFDMA毫微微小区网络中基于效用公平的功率控制策略

毫微微小区(Femtocell)网络能够增强室内覆盖,提高系统容量,但是在频谱共享正交频分多址(OFDMA) Femtocell网络中,同频干扰严重限制了网络的性能。针对频谱共享Femtocell网络中的上行链路,基于网络效率和毫微微小区用户间的公平性,该文提出合作纳什议价功率控制博弈模型,该博弈模型不仅考虑了对宏基站的干扰,而且考虑了毫微微小区用户最小信干噪比(SINR)需求。根据该博弈模型,进一步分析了具有帕累托(Pareto)最优的Kalai-Smorodingsky(KS)议价解。仿真结果表明,该策略既能保证用户公平性、最小SINR需求,又能够有效提高网络频谱利用率。     

OFDMA系统跨层资源分配算法

OFDM具有高频谱利用率和抗多径衰落的优点,已被公认为第三代移动通信系统长期演进标准以及第四代移动通信系统的核心技术。OFDMA是基于OFDM的一种多用户接入技术,在OFDMA系统中,各用户在不同的子载波上同时传输数据。主要研究了OFDMA系统中的跨层资源分配算法。详细分析了保证速率比例公平的非实时业务跨层资源分配算法,仿真结果说明该算法能够较好地保证用户之间的公平性,并能够获得较大的系统吞吐量和较小的业务延时。     

Fair Multiuser Channel Allocation for OFDMA Networks Using Nash Bargaining Solutions and Coalitions

In this paper, a fair scheme to allocate subcarrier, rate, and power for multiuser orthogonal frequency-division multiple-access systems is proposed. The problem is to maximize the overall system rate, under each user's maximal power and minimal rate constraints, while considering the fairness among users. The approach considers a new fairness criterion, which is a generalized proportional fairness based on Nash bargaining solutions and coalitions. First, a two-user algorithm is developed to bargain subcarrier usage between two users. Then a multiuser bargaining algorithm is developed based on optimal coalition pairs among users. The simulation results show that the proposed algorithms not only provide fair resource allocation among users, but also have a comparable overall system rate with the scheme maximizing the total rate without considering fairness. They also have much higher rates than that of the scheme with max-min fairness. Moreover, the proposed iterative fast implementation has the complexity for each iteration of only$O(K^2Nlog_2 N+K^4)$, where$N$is the number of subcarriers and$K$is the number of users.     

基于认知的协作系统中继分配算法

随着无线移动通信系统的飞速发展,无线通信网络能耗急剧增加,基于中继协作技术的绿色无线通信研究受到众多研究者的关注.针对基于认知的中继协作系统,提出了一种以最大主系统能效为目标的中继分配算法.该算法在不影响主系统性能基础上,对主系统请求次系统用户作为中继转发数据,且共享主用户频谱进行了简要介绍.算法中次系统通过最大权重匹配方法为主系统分配中继（次用户）,在满足主系统能效最大化的同时,实现了次系统与主系统的频谱共享.对算法进行仿真验证,提出的算法能获得较高的主系统能效,同时提高了整个系统的频谱利用率.     

Asymptotic RZF cooperative beamforming algorithm based on energy efficiency

A low complexity asymptotic regularized zero forcing cooperative beamforming algorithm based on energy efficiency in heterogeneous massive MIMO system was proposed,aiming at the problem that the current multi-flow regularization zero forcing beamforming algorithm sets the power constraint of each antenna in the regularization term as a fixed value and ignores the influences of factors such as the number of antennas,the number of users and QoS.The algorithm selects the optimal antenna power constraint set through the optimization method,and the optimal beamforming was asymptotically ob-tained to balance the interference among users to achieve the optimal energy efficiency,considering the impact of the number of antennas and users with the constraints of the antenna power and QoS.In view of the importance of backhaul in massive MIMO system,a backhaul power consumption model and the impact of backhaul power consumption on system performance was analyzed.Analysis and simulation results show that the proposed algorithm has great improvement of the performance,especially when the number of antennas is large.The algorithm is close to optimal performance,especially suitable for massive MIMO system of next generation communication.