基于子载波权衡的多用户OFDMA资源分配算法

在多用户OFDMA资源分配中提出一种基于子载波权衡的资源分配算法.资源分配过程中,在对公平性最差的用户进行子载波分配时,进行子载波权衡.根据权衡后子载波信道增益的变化情况,进行子载波分配.通过子载波权衡,将待分配的子载波分配给权衡用户;同时对于公平性最差的用户,从已分配给权衡用户的子载波中获得一个权衡子载波;使得权衡后分配的子载波较权衡之前获得更高的信道增益.仿真结果表明,算法在保证用户公平性的同时,提升了系统的频谱利用率.     

基于效用函数的IEEE 802.16 OFDMA系统资源分配算法

针对IEEE 802.16系统中复杂的服务质量(quality of service,Qos)机制,设计了一种统一的效用函数作为资源分配的目标函数以平衡资源分配中的效率和公平性,使资源分配问题转化为基于系统效用最大化的系统优化问题.考虑到对算法的实时性要求和适用于IEEE802.16正交频分复用多址(OFDMA)系统的要求,提出了一种基于效用函数的资源分配(URA)的算法.仿真结果表明,所提出的URA算法在性能上非常接近于最优算法,而计算复杂度却大幅度降低;同时,URA算法能够在频谱效率和公平性之间取得良好的折衷,以满足IEEE 802.16系统中各业务类型不同的QoS要求.     

下行多用户多业务OFDM系统动态资源分配方法

针对未来无线通信系统必须能够同时支持多种业务类型的用户的问题,按照各用户服务质量(QoS)需求的不同将用户分为具有不同优先级的类,并基于子载波与功率分配联合优化的思想,提出了一种下行多用户OFDM系统动态资源分配方法.仿真结果表明,与现有方法相比,该方法在首先满足具有较高优先级用户的QoS需求的情况下,将更多的资源分配给优先级相对较低的用户,从而提高了资源利用率,进一步增加了系统的整体速率.     

适合于HC-MAC协议的感知信道动态预留算法

针对基于HC-MAC协议的认知无线电系统提出了一种感知信道动态预留算法,以解决系统用户较多时可用频谱不能被充分利用的问题.该算法通过在感知开始前为认知用户预留一些信道,使得认知用户可以同时感知信道,从而减少了认知用户等待感知可用信道的时间,提高了频谱利用率.为了使该算法更具实用性,根据实时类业务和尽力服务类业务两类常见...     

基于改进粒子群算法的分布式天线系统跨层功率分配方案

结合数据链路层的队列状态信息和物理层的信道状态信息定义了系统的吞吐量系数和公平性系数,建立了分布式天线系统跨层功率分配的离散速率集优化模型。对粒子群优化算法的初始群体产生、粒子更新等步骤进行了改进,形成了改进粒子群算法(IMPSO)。利用IMPSO进行了动态功率分配和跨层优化。数值仿真结果表明,IMPSO能够取得很好的队列时延性能,选取不同的权重可对系统吞吐量性能和公平性性能产生重要影响,IMPSO获得的系统吞吐量性能和公平性性能较之功率固定分配算法(AP)均有较大幅度的提高。     

互补随机子梯度分布式认知无线电功率分配

频谱作为一种有限资源,随着无线通信服务和器件的日益增多,频段越来越稀缺,认知无线电是有效提高频谱利用率的解决方法之一.认知用户利用授权系统的固有反馈信息,合理设置认知用户的发射功率,两个通信系统能够同时工作,提高了频谱效率,并控制对授权用户造成的干扰.在不需要主动合作的前提下,该文提出了适合认知无线网络的互补随机子梯度分布式功率控制算法(CSDPC),分析了该分布算法的收敛特性,采用互补式的搜索方式,获得了提高收敛速度的有效途径.仿真结果表明,该算法和相关文献比较,收敛时间不到类似算法运算时间的1/10,增强了系统的灵活性,提高了通信容量.     

无线中继网络系统容量最大化中继选择机制

分析了基于用户频谱效率的中继选择算法的不足,基于最大流最小割定理,给出了系统容量最优化问题模型,分析了两跳中继网络接入链路和中继链路对系统容量的不同影响.基于链路权重因子,提出一种基于系统容量最大化的中继选择算法.对不同中继选择算法下的系统容量差异的理论与仿真分析结果表明,提出的系统容量最大化中继选择算法可以获得更优的系统容量性能,并对网络拓扑和节点个数具有良好的鲁棒性.     

雾计算辅助车联网中面向视频直播业务的资源分配研究

提出一种车辆雾计算网络中视频直播业务的资源分配方法,通过联合优化比特率选择、用户调度和频谱资源分配,以实现在最大化视频质量的同时降低时延和视频抖动.为了降低时延和视频抖动,在效用函数的设计中将时延和比特率切换作为惩罚因子.由于网络的动态变化特性和可用的频谱资源,将上述优化问题建模为马尔可夫决策过程,采用Soft Actor-Critic深度强化学习算法获得最优资源分配策略.仿真结果证明,所提方法比现有强化学习算法具有更好的探索能力和收敛性能.     

基于主用户行为的多天线频谱共享

本文考虑认知无线电系统中主用户的行为的变化,提出基于主用户行为的多天线频谱共享方案,并针对频谱共享的覆盖和平铺两种不同的接入方式,分别提出系统频谱共享优化算法。通过仿真,结果表明新的频谱共享优化算法在保护主用户的前提下提高了认知无线电系统性能。     

OFDM水声通信下行非正交多址接入功率分配方法研究

针对基于功率域非正交多址接入（Power Domain Non-orthogonal Multiple Accesses,PD-NOMA）的正交频分复用（Orthogonal Frequency Division Multiplexing,OFDM）水声下行通信系统的功率分配问题,提出了一种基于中断概率的功率分配方法。用户节点在系统初始化阶段根据源节点广播的组网数据包获取水声信道的统计特征,源节点根据水下用户反馈的信道特征参数建立水下用户的中断概率模型,以最小化两用户的中断概率和为目标建立目标函数,在中断概率区域边界上遍历搜索最优的功率分配系数。仿真结果表明,该方法在保证公平性的条件下,有效降低了用户节点的中断概率,提高了系统的频谱利用率和误码性能。     

Sum Rate Maximization-based Fair Power Allocation in Downlink NOMA Networks

Non-orthogonal multiple access (NOMA) has been seen as a promising technology for 5G communication. The performance optimization of NOMA systems depends on both power allocation (PA) and user pairing (UP). Most existing researches provide sub-optimal solutions with high computational complexity for PA problem and mainly focuses on maximizing the sum rate (capacity) without considering the fairness performance. Also, the joint optimization of PA and UP needs an exhaustive search. The main contribution of this paper is the proposing of a novel capacity maximization-based fair power allocation (CMFPA) with low-complexity in downlink NOMA. Extensive investigation and analysis of the joint impact of signal to noise ratio (SNR) per subcarrier and the channel gains of the paired users on the performance of NOMA in terms of the capacity and the user fairness is presented. Next, a closed-form equation for the power allocation coefficient of CMFPA as a function of SNR, and the channel gains of the paired users is provided. In addition, to jointly optimize UP and PA in NOMA systems an efficient low-complexity UP (ELCUP) method is proposed to be incorporated with the proposed CMFPA to compromise the proposed joint resource allocation (JRA). Simulation results demonstrate that the proposed CMFPA can improve the capacity and fairness performance of existing UP methods, such as conventional UP, and random UP methods. Furthermore, the simulation results show that the proposed JRA significantly outperforms the existing schemes and gives a near-optimal performance.     

Outage-constrained capacity of spectrum-sharing channels in fading environments

Cognitive radio technology has been recently proposed for sharing and utilising the spectrum in order to satisfy the increasing demands for spectrum access. In this radio technology, secondary users may be granted access to the spectrum bands occupied by a primary user as long as the interference power, inflicted on the primary receiver as an effect of the transmission of the secondary user, is deemed unharmful. In this paper the authors assume that the successful operation of the primary user requires a minimum rate to be guaranteed by its channel for a certain percentage of time and obtain the interference-power constraint that is required to be fulfilled by the secondary user. Considering the input transmit-power constraint, on average or peak power, for the secondary user, the authors investigate the capacity gains offered by this spectrum-sharing approach when only partial channel information of the link between the secondary's transmitter and primary's receiver is available to the former. In particular, the lower bounds on the capacity of a Rayleigh flat-fading channel with two different transmission techniques, namely channel inversion and optimum rate allocation with constant power transmission, are derived. Closed-form expressions for these capacity metrics are provided, and numerical simulations are conducted to corroborate the theoretical results.     

Proportional Fairness-Based Power Allocation Algorithm for Downlink NOMA 5G Wireless Networks

Non-orthogonal multiple access (NOMA) is one of the key 5G technology which can improve spectrum efficiency and increase the number of user connections by utilizing the resources in a non-orthogonal manner. NOMA allows multiple terminals to share the same resource unit at the same time. The receiver usually needs to configure successive interference cancellation (SIC). The receiver eliminates co-channel interference (CCI) between users and it can significantly improve the system throughput. In order to meet the demands of users and improve fairness among them, this paper proposes a new power allocation scheme. The objective is to maximize user fairness by deploying the least fairness in multiplexed users. However, the objective function obtained is non-convex which is converted into convex form by utilizing the optimal Karush-Kuhn-Tucker (KKT) constraints. Simulation results show that the proposed power allocation scheme gives better performance than the existing schemes which indicates the effectiveness of the proposed scheme.     

Interference-limited resource allocation for cognitive radio in orthogonal frequency-division multiplexing networks

Efficient and fair resource allocation strategies are being extensively studied in current research in order to address the requirements of future wireless applications. A novel resource allocation scheme is developed for orthogonal frequency-division multiplexing (OFDM) networks designed to maximise performance while limiting the received interference at each user. This received interference is in essence used as a fairness metric; moreover, by defining different interference tolerances for different sets of users, the proposed allocation scheme can be exploited in various cognitive radio scenarios. As applied to the scheme, the authors investigate a scenario where two cellular OFDM-based networks operate as primary and secondary systems in the same band, and the secondary system benefits by accessing the unused resources of the primary system if additional capacity is required. The primary system benefits either by charging the secondary system for the use of its resources or by some form of reciprocal arrangement allowing it to use the secondary system's licenced bands in a similar manner, when needed. Numerical results show our interference-limited scheduling approach to achieve excellent levels of efficiency and fairness by allocating resources more intelligently than proportional fair scheduling. A further important contribution is the application of sequential quadratic programming to solve the non-convex optimisation problems which arise in such scenarios.     

An Adaptive Power Allocation Scheme for Performance Improvement of Cooperative SWIPT NOMA Wireless Networks

Future wireless networks demand high spectral efficiency, energy efficiency and reliability. Cooperative non-orthogonal multiple access (NOMA) with simultaneous wireless information and power transfer (SWIPT) is considered as one of the novel techniques to meet this demand. In this work, an adaptive power allocation scheme called SWIPT based adaptive power allocation (SWIPT-APA-NOMA) is proposed for a power domain NOMA network. The proposed scheme considers the receiver sensitivity of the end users while calculating the power allocation coefficients in order to prevent wastage of power allocated to user in outage and by offering priority to any one of the users to use maximum harvested power. A detailed analysis on the bit error rate (BER) performance of the proposed scheme is done and closed form expression is obtained. Simulations have been carried out with various parameters that influence the receiver sensitivity and the results show that the network achieves better outage and BER performance using the proposed scheme. It is found that the proposed scheme leads to a ten-fold decrease in transmit power for the same error performance of a fixed power allocation scheme. Further, it offers 96.06% improvement in the capacity for a cumulative noise figure and fading margin of 10 dB.     

Optimal power and subcarriers allocation in downlink OFDMA system with imperfect channel knowledge

Most of existing work on resource allocation in TDMA and OFDMA systems assumes the availability of perfect channel state information (CSI) at the transmitter, which is rarely possible due to feedback delay and channel estimation error. In this paper, we study the effect of feedback delay and channel estimation error on margin adaptive resource allocation in a downlink OFDMA system. By using convex optimization framework, we find an optimal solution to the problem. First, we study the individual effect of feedback delay and channel estimation error on resource allocation by considering them exclusively. Then, we consider the simultaneous presence of feedback delay and channel estimation error and study their combined effect on resource allocation. We derive an explicit close form expression for the users’ transmit power and propose an algorithm for power and subcarriers allocation for each of these three scenarios. The algorithms have polynomial complexities and solve the problem with zero optimality gaps. Simulation results show that the system performance is very sensitive to feedback delay and is affected significantly by imperfect channel estimation. Our proposed algorithms highly improve the system performance in the availability of only imperfect CSI at the transmitter.     

Energy Efficient Resource Allocation Approach for Renewable Energy Powered Heterogeneous Cellular Networks

In this paper, maximizing energy efficiency (EE) through radio resource allocation for renewable energy powered heterogeneous cellular networks (HetNet) with energy sharing, is investigated. Our goal is to maximize the network EE, conquer the instability of renewable energy sources and guarantee the fairness of users during allocating resources. We define the objective function as a sum weighted EE of all links in the HetNet. We formulate the resource allocation problem in terms of subcarrier assignment, power allocation and energy sharing, as a mixed combinatorial and non-convex optimization problem. We propose an energy efficient resource allocation scheme, including a centralized resource allocation algorithm for iterative subcarrier allocation and power allocation in which the power allocation problem is solved by analytically solving the Karush-Kuhn-Tucker (KKT) conditions of the problem and a water-filling problem thereafter and a low-complexity distributed resource allocation algorithm based on reinforcement learning (RL). Our numerical results show that both centralized and distributed algorithms converge with a few times of iterations. The numerical results also show that our proposed centralized and distributed resource allocation algorithms outperform the existing reference algorithms in terms of the network EE.     

一种新颖的多用户OFDM资源分配算法

在多用户正交频分复用(OFDM)系统中设计一种新颖的子载波-功率分配方法来最大化用户数据传输速率.这个方案分成两部分,子载波分配和功率分配.其中,子载波分配方法是在信道容量矩阵中将信道容量最好的子载波首先进行分配,功率分配采用注水方法.研究和模拟结果表明,该算法在只改变各个子载波增益系数的基础上,基本保持了较低的复杂度,并且极大地提高了用户数据传输速率.     

A Capacity Improving Scheme in Multi-RSUs Deployed V2I

The communication reliability and system capacity are two of the key performance indicators for Internet of Vehicles (IoV). Existing studies have proposed a variety of technologies to improve reliability and other performance, such as channel selection and power allocation in Vehicle-to-Infrastructure (V2I). However, these researches are mostly applied in a single roadside unit (RSU) scenario without considering inter-cell interference (ICI) of multi-RSUs. In this paper, considering the distribution characteristics of multi-RSUs deployment and corresponding ICI, we propose a reliable uplink transmission scheme to maximize the total capacity and decrease the interference of multi-RSUs (mRSU-DI) in condition of the uplink interruption performance. In the proposed mRSU-DI scheme, ICI is depressed by dynamic channel and power allocation algorithm. A heuristic algorithm based on penalty function is proposed to obtain the optimal power allocation solution of the model. In addition, we realize the scheme in both given conditions of channel state information (CSI) and channel state distribution, respectively. The results show that the proposed scheme can both improve the system capacity and guarantee the reliable transmission in both premises.