基于比例速率保证的信道误差OFDMA中继系统资源分配

针对存在有信道估计误差的正交频分多址( OFDMA)中继系统,在考虑用户传输中断概率的同时,提出了满足不同用户最小服务质量( QoS)需求和比例公平性约束条件下的中继选择、子载波分配和功率分配的联合优化问题,建立了以最大化系统总容量为目标的优化模型。在此基础上以速率最大化为目标进行最佳中继选择,并通过动态子载波分配来满足用户的最小QoS需求和比例公平性,最后采用拉格朗日乘子法来得到最优功率分配方案。仿真结果表明,此算法在降低用户中断概率的同时,提高了系统吞吐量并保证了用户速率的比例公平性。     

多用户多中继系统下协作NOMA的中断性能

在基于非正交多址接入技术(NOMA)的多用户多中继协作中继网络中,为优先满足混叠信号中的时延敏感信息的服务质量(QoS)需求,对功率因子进行了简单分析,进而找到了关于信道增益的解码限制条件。在给定中继的情况下,根据解码限制条件建立用户集合,进而找到可以使高QoS信号速率最大化的用户中继对作为最佳“用户-中继”来传递信号。并且对该“用户-中继”选择方案下的系统中断概率的表达式进行推导并求出了其渐进式。仿真结果验证了推导结果的正确性,系统的中断概率随着节点数目的增多而降低,而当信噪比趋于无穷时,系统的分集增益取决于用户数目和中继数目。且与已有文献进行对比,本文提出的用户中继匹配方案的中断性能相对较好。     

窃听环境下AF中继选择与功率分配的研究

传统的最佳中继选择方案仅参考了合法用户的信道状态信息,在实际的通信系统中由于存在窃听用户而无法保证信息的可靠传输。现有的最佳中继选择方案将窃听用户的信道状态信息纳入考虑后,系统的安全性能得到了一定改善,但是依然采用的是等功率分配。针对放大转发协议,本文在现有最佳中继选择方案的基础上,以降低系统安全中断概率为目标,在系统总功率受限的前提下,根据源节点和中继节点以及中继节点和目的节点间的信道参数引出功率分配因子,对源节点和中继节点间的功率进行适当分配。通过仿真对比,可以发现功率分配能够降低系统的安全中断概率,从而改善系统的安全性能。      

OFDMA协同通信系统子载波和功率联合分配算法

针对OFDMA协同通信系统资源分配仅考虑平均功率下的子载波分配,中继存在未用功率情况,研究子载波分配后中继剩余功率分配问题。提出一种既满足业务QoS需求又兼顾用户间公平性的子载波和功率联合分配算法,并设计一种基于二分法的功率注水分配方案。测试表明,该算法能在满足业务QoS需求及用户公平性的同时,提升系统容量。     

协作NOMA系统中的一种新型节能功率分配方案

在传统的协作非正交多址（CNOMA, Cooperative Non Orthogonal Multiple Access)系统中,通常需要向弱用户分配更多的功率,分配给强用户的功率不超过总功率的一半。同时,强用户还需在协作阶段承担中继通信的任务。上述功率分配方式必将给强用户带来一定的负担。为了在满足弱用户服务质量的情况下,进一步提高强用户的中断性能,本文提出一种基于中继和无线携能通信（SWIPT, Simultaneous Wireless Information and Power Transfer）的新型功率分配方案。该方案使用能量收集设备收集能量,通过最大化系统和速率寻求无线携能通信的最优功率分割因子,从而获得系统中断概率的闭式表达。考虑到优化问题的性质,本文提出了一种在功率分配固定的情况下,通过单调优化求解无线携能通信功率分割因子的算法。仿真结果表明,与CNOMA系统的传统功率分配方案相比,本文所提方案能够在不损失弱用户中断性能的前提下,有效提升强用户的中断概率,系统和速率总体提高了近 20%。      

OFDMA系统下行链路自适应带宽与子载波分配方案

该文分析了OFDMA系统下行链路自适应资源分配问题,在系统总功率约束下提出了最小化系统中断概率的次最佳两步子载波分配算法。首先分析用户带宽分配与子载波功率分配特点,在此基础上提出了根据系统可用资源、用户QoS要求及信道状态为用户分配带宽和子载波的两步分配算法。仿真结果表明,该文提出的算法能在极小化系统中断概率的同时满足总功率约束。     

放大转发认知中继协作系统中继增益分配方案和性能分析

由于在传统的放大转发认知中继协作方案中,中继增益因子的分配只考虑了部分主、从系统参数,使得系统的能量效率较低、系统资源未被充分利用。为此,基于主系统传输速率约束和从系统终端接收信号平均误符号率最小准则,文章提出了一个新颖的中继增益最优化分配方案,获得了中继增益最优化精确解以及相应的上、下限封闭解析解;并基于获得的最优化中继增益,分析了系统的平均误符号率。结果表明,文章所获得的中继增益因子分配方案由于不仅考虑了从信源功率和从信源-中继链路增益,而且还综合考虑了中继-从信宿链路和主系统参数,可以实现系统资源的最优化配置,系统性能得到改善。      

Underlay协同频谱共享系统中基于SDF-DZFB的物理层安全传输

协同中继传输不仅能改善认知用户的传输可靠性,而且也能增强认知用户物理层安全性。针对Underlay模式下多中继协同频谱共享认知无线网络,本文设计了基于选择译码转发和分布式迫零波束成形（SDF-DZFB）的物理层安全传输方案,其中,假设存在单个被动窃听节点窃听中继节点的发送信号,在认知用户发送端同时考虑峰值干扰温度约束和最大发射功率约束,中继和认知用户目的端都受到主用户干扰。在此情况下,分析了认知用户发送端分别到目的端（称为主链路）和到窃听节点（称为窃听链路）的等效信干噪比的统计特性,进而推导出系统安全中断概率性能的闭式表达式。为了揭示所提物理层安全传输方案的安全分集度性能,本文进一步分析了高信噪比条件下安全中断概率的渐近表达式。计算机仿真验证了本文的理论分析结果。      

两级中继选择的协作CR-NOMA网络性能分析

本文研究了中继选择方案对协作下认知非正交多址（CR-NOMA）网络中断性能的影响,提出了一种两级中继选择方案。第一时隙在保证主用户服务质量的基础上,次级网络源节点向认知中继集群广播叠加信号。第二时隙认知中继提供解码转发服务,协助源节点传输信息。基于上述假设,推导了次级用户中断概率的闭合表达式并给出了分析结果。证明相比于部分中继选择策略,两级中继选择策略可以达到更好的中断性能和更大的分集增益。同时本文的分析结果验证了备选中继节点数目和功率分配因子对系统中断性能的影响,蒙特卡罗仿真验证了理论结果。      

非理想干扰删除下全双工中继NOMA系统的物理层安全性能研究

全双工协作中继转发信号时存在的自干扰现象会降低系统性能.本文考虑存在窃听者的下行非理想自干扰全双工协作中继非正交多址接入（NFCR-E-NOMA,Non-ideal Full Duplex Cooperative Relay in Non-Orthogonal Multiple Access system with Eavesdropper）系统,分别从系统中断概率和系统截获概率的角度分析了全双工协作中继的自干扰因素对于NFCR-E-NOMA系统安全中断性能的影响;推导了系统中断概率和截获概率的闭合表达式.仿真结果表明,全双工中继转发的自干扰因素对系统性能的影响较大,在NFCR-E-NOMA系统中,存在优化的中继转发功率,且在不同的基站发射功率和中继转发功率条件下,功率分配比对系统性能的影响也不同,在实际主链路信道条件允许的情况下,可通过设置较高的数据传输速率来抑制窃听者的截获概率.     

Cooperative transmissions for secondary spectrum access in cognitive radios

In cognitive radio networks (CRNs), the primary users (PUs) and secondary users (SUs) will interfere with each other, which may severely degrade the performances of both primary and secondary transmissions. In this paper, we propose a two‐phase cognitive transmission (TCT) protocol for secondary spectrum access in CRNs, aiming at improving the secondary transmission performance while guaranteeing the quality‐of‐service (QoS) of primary transmissions. In TCT protocol, SUs gain the opportunities to access the licensed spectrum through assisting primary transmissions using superposition coding (SC), where SUs limit their transmit power to satisfy a given primary QoS requirement and also employ interference cancelation technique to mitigate the interference from PUs. Under the constraint of satisfying a required primary outage probability, we derive the closed‐form expressions of secondary outage probabilities over Rayleigh fading channels for proposed TCT protocol. Numerical and simulation results reveal that, with a guaranteed primary outage probability, TCT achieves better secondary transmission performance than traditional case. Copyright © 2013 John Wiley & Sons, Ltd.     

Multiuser two‐way relay processing and power control methods for cognitive radio networks

We consider a cognitive radio system where a secondary network shares the spectrum band with a primary network. Aiming at improving the frequency efficiency of the secondary network, we set a multiantenna relay station in the secondary network to perform two‐way relaying. Three linear processing schemes at the relay station based on zero forcing, zero forcing‐maximum ratio transmission, and minimum mean square error criteria are derived to guarantee the quality of service of primary users and to suppress the intrapair and interpair interference among secondary users (SUs). In addition, the transmit power of SUs is optimized to maximize the sum rate of SUs and to limit the interference brought to PUs. Numerical results show that the proposed multiuser two‐way relay processing schemes and the optimal power control policies can efficiently limit the interference caused by the secondary network to primary users, and the sum rate of SUs can also be greatly improved. Copyright © 2011 John Wiley & Sons, Ltd.     

Cooperative spectrum sharing of multiple primary users and multiple secondary users

This paper proposes a multiple-input multiple-output (MIMO) based cooperative dynamic spectrum access (DSA) framework that enables multiple primary users (PUs) and multiple secondary users (SUs) to cooperate in spectrum sharing. By exploiting MIMO in cooperative DSA, SUs can relay the primary traffic and send their own data at the same time, which greatly improves the performance of both PUs and SUs when compared to the non-MIMO time-division spectrum sharing schemes. Especially, we focus on the relay selection optimization problem among multiple PUs and multiple SUs. The network-wide cooperation and competition are formulated as a bargaining game, and an algorithm is developed to derive the optimal PU-SU relay assignment and resource allocation. Evaluation results show that both primary and secondary users achieve significant utility gains with the proposed framework, which gives all of them incentive for cooperation.     

Optimal Resource Allocation for Spectrum Sensing Based Cognitive Radio Networks with Statistical QoS Guarantees

Resource allocation under spectrum sensing based dynamic spectrum sharing strategy is a critically important issue for cognitive radio networks (CRNs), because they need to not only satisfy the interference constraint caused to the primary users (PUs), but also meet the quality-of-service (QoS) requirements for the secondary users (SUs). In this paper, we develop the optimal spectrum sensing based resource allocation scheme for the delay QoS constrained CRNs. Specifically, we aim at maximizing the maximum constant arrival rate of the SU that can be supported by the time-varying service process subject to the given statistical delay QoS constraint. In our derived power allocation scheme, not only the average transmit and interference power constraints are considered, but also the impact of the PUs?? transmission to the CRNs and the PUs?? spectrum-occupancy probability are taken into consideration. Moreover, the spectrum sensing errors are also taken into consideration. Simulation results show that, (1) the effective capacity of the secondary link decreases when the statistical delay QoS constraint becomes stringent; (2) given the QoS constraint, the effective capacity of the secondary link varies with the interference power constraint and the SNR of the primary link.     

Joint Beamforming and Power Allocation for Multiple Access Channels in Cognitive Radio Networks

A cognitive radio (CR) network refers to a secondary network operating in a frequency band originally licensed/allocated to a primary network consisting of one or multiple primary users (PUs). A fundamental challenge for realizing such a system is to ensure the quality of service (QoS) of the PUs as well as to maximize the throughput or ensure the QoS, such as signal-to-interference-plus-noise ratios (SINRs), of the secondary users (SUs). In this paper, we study single-input multiple output multiple access channels (SIMO-MAC) for the CR network. Subject to interference constraints for the PUs as well as peak power constraints for the SUs, two optimization problems involving a joint beamforming and power allocation for the CR network are considered: the sum-rate maximization problem and the SINR balancing problem. For the sum-rate maximization problem, zero-forcing based decision feedback equalizers are used to decouple the SIMO-MAC, and a capped multi-level (CML) water-filling algorithm is proposed to maximize the achievable sum-rate of the SUs for the single PU case. When multiple PUs exist, a recursive decoupled power allocation algorithm is proposed to derive the optimal power allocation solution. For the SINR balancing problem, it is shown that, using linear minimum mean-square-error receivers, each of the interference constraints and peak power constraints can be completely decoupled, and thus the multi-constraint optimization problem can be solved through multiple single-constraint sub-problems. Theoretical analysis for the proposed algorithms is presented, together with numerical simulations which compare the performances of different power allocation schemes.     

Reinforcement Learning Enhanced Iterative Power Allocation in Stochastic Cognitive Wireless Mesh Networks

As the scarce spectrum resource is becoming over-crowded, cognitive wireless mesh networks have great flexibility to improve the spectrum utilization by opportunistically accessing the licensed frequency bands. One of the critical challenges for realizing such network is how to adaptively allocate transmit powers and frequency resources among secondary users (SUs) of the licensed frequency bands while maintaining the quality-of-service (QoS) requirement of the primary users (PUs). In this paper, we consider the power control problem in the context of cognitive wireless mesh networks formed by a number of clusters under the total transmit power constraint by each SU as well as the mean-squared error (MSE) constraint by PUs. The problem is modeled as a non-cooperative game. A distributed iterative power allocation algorithm is designed to reach the Nash equilibrium (NE) between the coexisting interfered links. It offers an opportunity for SUs to negotiate the best use of power and frequency with each other. Furthermore, how to adaptively negotiate the transmission power level and spectrum usage among the SUs according to the changing networking environment is discussed. We present an intelligent policy based on reinforcement learning to acquire the stochastic behavior of PUs. Based on the learning approach, the SUs can adapt to the dynamics of the interference environment state and reach new NEs quickly through partially cooperative information sharing via a common control channel. Theoretical analysis and numerical results both show effectiveness of the intelligent policy.     

Reliability-Intercept Gap Analysis of Underlay Cognitive Networks Under Artificial Noise and Primary Interference

Wireless Personal Communications - Underlay mode of cognitive radio networks (CRNs) permits secondary users (SUs) to simultaneously operate with primary users (PUs), inducing mutual interference...     

Resource allocation for heterogeneous services in multiuser cognitive radio networks

This paper considers a downlink cognitive radio network consisting of one cognitive base station and multiple secondary users (SUs) that shares spectrum with a primary network. Unlike most of previous studies that focus on the SUs that carry only one type of service, in this paper, the SUs that carry heterogeneous services are considered. Specifically, the SUs are classified by service types, that is, the SUs that carry nonreal‐time services and the SUs that carry real‐time services. The QoS of the nonreal‐time SUs is guaranteed by the minimum mean rate constraint, whereas the QoS of the real‐time SUs is guaranteed by the minimum instantaneous rate constraint. Under this setup, a joint subchannel, rate, and power allocation scheme based on dual optimization method is proposed to minimize the mean transmit power consumption of the cognitive base station. The complexity of the proposed scheme is linear in the number of subchannels and the number of SUs. Extensive simulation results are provided to validate the proposed resource allocation scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

A low‐complexity resource allocation algorithm in OFDMA‐based cooperative cognitive radio networks

In this paper, we propose a low‐complexity resource allocation algorithm for the orthogonal frequency division multiplexing cooperative cognitive radio networks, where multiple primary users (PUs) and multiple secondary users (SUs) coexist. Firstly, we introduce a new concept of ‘efficiency capacity’ to represent the channel conditions of SUs by considering both of the interference caused by the PUs and the channel gains of the SUs with the assist of the relays. Secondly, we allocate the relay, subcarrier and transmission power jointly under the constraint of limiting interference caused to the PUs. Simulation results show that the proposed algorithm can achieve a high data rate with a relative low power level. Copyright © 2014 John Wiley & Sons, Ltd.     

Joint power allocation and beamforming with users selection for cognitive radio networks via discrete stochastic optimization

Cognitive radio is a promising technique to dynamic utilize the spectrum resource and improve spectrum efficiency. In this paper, we study the problem of mutual interference cancellation among secondary users (SUs) and interference control to primary users (PUs) in spectrum sharing underlay cognitive radio networks. Multiple antennas are used at the secondary base station to form multiple beams towards individual SUs, and a set of SUs are selected to adapt to the beams. For the interference control to PUs, we study power allocation among SUs to guarantee the interference to PUs below a tolerable level while maximizing SUs?? QoS. Based on these conditions, the problem of joint power allocation and beamforming with SUs selection is studied. Specifically, we emphasize on the condition of imperfect channel sensing due to hardware limitation, short sensing time and network connectivity issues, which means that only the noisy estimate of channel information for SUs can be obtained. We formulate the optimization problem to maximize the sum rate as a discrete stochastic optimization problem, then an efficient algorithm based on a discrete stochastic optimization method is proposed to solve the joint power allocation and beamforming with SUs selection problem. We verify that the proposed algorithm has fast convergence rate, low computation complexity and good tracking capability in time-varying radio environment. Finally, extensive simulation results are presented to demonstrate the performance of the proposed scheme.