QoS-Driven Power Allocation Under Peak and Average Interference Constraints in Cognitive Radio Networks

Efficient radio spectrum utilization can be improved using cognitive radio technology. In this work, we consider a spectrum underlay cognitive radio system operating in a fading environment. We propose an efficient power control scheme that maximizes the effective capacity of the secondary user, provisioning quality of service while on the same time the communication of the primary user is guaranteed through interference constraints. The specific power allocation scheme uses a policy in which the outage events of the primary user are exploited leading to a significant increase of the secondary user’s effective capacity. Moreover, the interference of the primary link to the secondary is taken into account so as to study a more realistic scenario. In order to safeguard primary user’s communication, two types of restrictions are considered: the traditional interference power constraint and the proposed inverse signal to interference plus noise ratio constraint. Different scenarios depending on the nature of the constraints (peak/average) are studied and their impact on the performance of the primary and secondary users is investigated. The superiority of the proposed schemes is demonstrated through their comparison with two reference power control schemes. Finally, numerical calculations, validated with simulation results, confirm the theoretical analysis and evaluate the performance of the proposed scheme for all the different scenarios.     

Optimal Resource Allocation in Heterogeneous MIMO Cognitive Radio Networks

The optimal resource allocation in MIMO cognitive radio networks with heterogeneous secondary users, centralized and distributed users, is investigated in this work. The core aim of this work is to study the joint problems of transmission time and power allocation in a MIMO cognitive radio scenario. The optimization objective is to maximize the total capacity of the secondary users (SUs) with the constraint of fairness. At first, the joint problems of transmission time and power allocation for centralized SUs in uplink is optimized. Afterwards, for the heterogeneous case with both the centralized and distributed secondary users, the resource allocation problem is formulated and an iterative power water-filling scheme is proposed to achieve the optimal resource allocation for both kinds of SUs. A dynamic optimal joint transmission time and power allocation scheme for heterogeneous cognitive radio networks is proposed. The simulation results illustrate the performance of the proposed scheme and its superiority over other power control schemes.     

Opportunistic power allocation strategies and fair subcarrier allocation in OFDM-based cognitive radio networks

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user’s QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user’s tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.     

认知无线电网络中基于功率有效性的最优功率分配

在资源受限的认知无线电网络中,如何提高次用户网络的功率利用率是一个值得考虑的问题。针对这个问题,本文首先提出了认知无线电网络中基于功率有效性的次用户最优功率分配算法,该算法不仅考虑主用户网络中断概率对次用户发射功率的限制,而且兼顾次用户网络本身的中断概率要求。其次,为了进一步降低节点的计算复杂度,本文通过降维处理将目标最优化问题转化为两个子问题进行求解,从而提出一种次优的低复杂度功率分配算法。仿真结果表明,次优算法相比最优算法仅带来有限的性能损失,但是却有效地节省了计算时间和存储空间;此外,当中继节点靠近源节点时更有利于系统功率效率的提高,源节点到目的节点链路相比中继链路对系统的性能影响更大。      

Improving Water-Filling Algorithm to Power Control Cognitive Radio System Based Upon Traffic Parameters and QoS

Cognitive radio scenario is based upon the ability to determine the radio transmission parameters from its surrounding environment. Power allocation in cognitive radio systems improves secondary network capacity subject to primary receiver interference level threshold. In this paper, statistical property of the injected interference power in primary user channel is used to establish the container bottom for each subcarrier employing water filling algorithm. In other words, the container bottom level of each subcarrier depends on the injected interference in primary user (PU) (most probably from the overloaded neighbor subcarriers). Traffic statistical parameters are also employed to formulate power allocation problem. Within this context, quality of service constraint is considered also to improve performance of power allocation algorithm. Simulation Results show that the injected interference in PU is decreased while the secondary user capacity improves. Indeed, the proposed algorithm is more compatible than a waterfilling algorithm with cognitive radio system constraints.     

认知中继协同无线通信系统功率分配和混合频谱接入方案

文章首先对Underlay 认知-中继协作（cognitive radio relay cooperation, CR-RC）系统信源和中继的功率分配问题进行了研究,获得了Underlay CR-RC系统信源、中继独立功率分配(independent power allocation, IPA）和联合功率分配（joint power allocation, JPA）方案,并给出了基于IPA和JPA的CR-RC系统的中断概率和各态历经容量的封闭解析解;其次通过对Underlay CR-RC系统中断性能的比较分析,提出了高频谱效率、高能量效率的混合Interweave-Underlay CR-RC方案。在该方案中,定义了主、从用户中断概率约束,充分考虑了主、从系统的服务质量(quality of service, QoS),当即使从用户的发射功率为零,主系统的QoS仍不能满足时,从用户以最大功率发送信号,无需考虑其对主用户的影响;当由于很强的主用户干扰,使得从用户的QoS不能得到满足时,从用户不再发射信号,发信功率为零;当主、从系统的QoS能够同时满足时,以Underlay模式工作。      

Joint power and rate allocation for spectrum sharing cognitive radio multicast networks under service outage constraint

This letter considers a downlink spectrum sharing cognitive radio (CR) multicast network coexisting with a primary network. The problem of joint power and rate allocation to maximize the average sum rate is studied. In this regard, a joint power and rate allocation scheme is proposed, where the allocated rate can be higher than the lowest rate of all the secondary users (SUs) within the same group, which is different from the conventional multicast transmission scheme. To guarantee the quality of service (QoS) of the SU, the service outage probability defined as the probability that the maximum achievable rate of the SU is lower than the rate of the group, is constrained to be under a certain threshold, which is termed as the service outage constraint. The numerical results show that the proposed scheme provides significant improvement over the conventional scheme in terms of average sum rate.     

基于稳定匹配的认知无线网络协作物理层安全机制

在Underlay认知无线网络中,次用户被允许在主用户进行数据发送时接入主用户的频谱.此时,主用户将对次用户和窃听者造成干扰.利用协作干扰技术,主用户产生的干扰可以被用来改善次用户的物理层安全.基于此,本文针对包含多个主次用户的Underlay认知无线网络,提出了一种新的协作物理层安全机制.为了在保证主用户通信质量的前提下,最大化网络中次用户的总的安全容量,该机制将对次用户进行合理的频谱接入选择和功率控制.另外,考虑到个体理性和自私性对于频谱接入稳定性的影响,该机制利用稳定匹配理论将频谱接入选择问题建模为一对一的双边匹配问题,通过构建主次用户之间的稳定匹配来保证频谱接入的稳定性.仿真结果表明,使用本文所提安全机制,可以在保证主用户通信质量的前提下,稳定而又有效地改善网络中次用户获得的总的安全容量.     

Optimal power allocation for cognitive radio under interference outage constraint

Cognitive radio is able to share the spectrum with primary licensed user, which greatly improves the spectrum efficiency. We study the optimal power allocation for cognitive radio to maximize its ergodic capacity under interference outage constraint. An optimal power allocation scheme for the secondary user with complete channel state information is proposed and its approximation is presented in closed form in Rayleigh fading channels. When the complete channel state information is not available, a more practical transmitter-side joint access ratio and transmit power constraint is proposed. The new constraint guarantees the same impact on interference outage probability at primary user receiver. Both the optimal power allocation and transmit rate under the new constraint are presented in closed form. Simulation results evaluate the performance of proposed power allocation schemes and verify our analysis.     

OFDMA认知无线电网络中面向需求的频谱共享

从满足次网络通信需求的角度,设计一个两阶段模型,求解OFDMA 认知无线电网络中频谱租赁与分配问题。模型第1阶段,次基站收集次网络通信需求,向多个主基站租用频谱资源。运用Bertrand博弈对主、次基站的交易行为进行建模,并将纳什均衡作为最终定价方案。第2阶段,基于纳什议价方案,将次基站子载波和功率分配问题定义成非线性规划问题,并通过拉格朗日乘数法进行求解。仿真实验表明,相对于其他频谱共享方案,所提方案高效地满足每个次用户的通信需求。     

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.     

PLC-RF无线传输网络中的能效最优设计方法

针对电力线通信（PLC）和射频（RF）无线通信混合传输的室内通信场景,提出了一种基于角度信息的信道状态信息（AI-CSI）的能效优先传输方案。首先,Wi-Fi无线网络和PLC网络分别作为主网络和次级网络,并且采用认知无线电技术来提高频谱效率的情况下,建立次级网络总能效最大化为目标函数的优化问题。其次,为了求解该问题,通过基于AI-CSI的迫零波束成形方法,获得波束成形权矢量,并进一步提出Dinkelbach与拉格朗日乘子法相结合的优化方法,进行最优的功率分配。最后,计算机仿真结果不仅验证了所提方案的有效性和优越性,而且分析了中继天线数和用户个数等典型参数对系统能效带来的影响,从而为实际系统设计提供了参考和依据。     

基于强化学习的合作频谱分配算法

为了解决认知无线电网络中的频谱分配问题,提出了一种基于用户体验质量的合作强化学习频谱分配算法,将认知网络中的次用户模拟为强化学习中的智能体,并在次用户间引入合作机制,新加入用户可以吸收借鉴其他用户的强化学习经验,能够以更快的速度获得最佳的频谱分配方案;并且在频谱分配过程中引入了主用户和次用户之间的价格博弈因素,允许主用...     

认知无线Ad hoc网络的功率控制

当FCC提出传统电视系统和认知无线电网络频谱共享,以增加频谱的利用率时,主要涉及到的问题之_是来自认知无线电网络的干扰不得影响主用户的QoS。在本文中,考虑由低功耗个人／便携设备组成的认知无线电网络与传统电视系统同时运作的情况。本文在保证主用户和认知用户的QoS的情况下,推导出问题的可行性条件,并提出集中式和分布式两种解决方案,最大限度地提高认知用户的能源效率。并且通过仿真表明该方案的有效性。     

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.     

一种基于干扰温度限制的信道与功率联合分配新算法

随着无线通信业务的不断增长,频谱资源越来越紧缺,然而另一方面大量授权的无线频谱却被闲置或者利用率极低,于是认知无线电技术应运而生,已成为无线通信领域的研究热点。认知无线电的基本思想是次用户（认知用户）利用主用户（授权用户）未占用的空闲频谱进行通信,其可用无线资源是根据授权用户的频谱使用情况而动态变化的。因此,能否实现对系统可用无线资源的合理有效管理,对整个认知无线电系统性能的优劣起着决定性作用。本文提出了一种在干扰温度限制下基于公平的功率与信道联合分配算法,该算法在主用户干扰温度及次用户发射功率的双重限制下,以最大化系统容量为基本目标,实现信道与功率的联合分配,并且引入贫困线来保证各个用户信道分配的公平性。论文建立了该问题的非线性规划数学模型,给出了模型的求解方法,并进一步设计了具体分配算法及其步骤。论文对干扰门限分别为-90dBm、-95dBm、-100dBm、-105dBm、-110dBm时的系统归一化容量累积分布函数进行了仿真比较,发现当干扰门限越低时,本文算法的优势越明显。这是因为在干扰门限较低时,干扰温度限制是功率分配的主要制约因素,而本文的算法正是基于干扰门限进行分配的。因此基于干扰温度限制的公平的功率与信道联合分配算法具有良好的性能,在保证了系统的公平性效益的同时,提高了系统的归一化容量。      

A matching game framework for users clustering and resource allocation with wireless power transfer in a CR-NOMA network

This paper investigates the resource allocation in a massively deployed user cognitive radio enabled non-orthogonal multiple access (CR-NOMA) network considering the downlink scenario. The system performance deteriorates with the number of users who are experiencing similar channel characteristics from the base station (BS) in NOMA. To address this challenge, we propose a framework for maximizing the system throughput that is based on one-to-one matching game theory integrated with the machine learning technique. The proposed approach is decomposed to solve users clustering and power allocation subproblems. The selection of optimal cluster heads (CHs) and their associated cluster members is based on Gale-Shapley matching game theoretical model with the application of Hungarian method. The CHs can harvest energy from the BS and transfer their surplus power to the primary user (PU) through wireless power transfer. In return, they are allowed to access the licensed band for secondary transmission. The power allocation to the users intended for power conservation at CHs is formulated as a probabilistic constraint, which is then solved by employing the support vector machine (SVM) algorithm. The simulation results demonstrate the efficacy of our proposed schemes that enable the CHs to transfer the residual power while ensuring maximum system throughput. The effects of different parameters on the performance are also studied.     

Resource allocation in underlay cognitive radio networks with full‐duplex cognitive base station

This paper considers an underlay cognitive radio network with a full‐duplex cognitive base station and sets of half‐duplex downlink and uplink secondary users, sharing multiple channels with the primary user. The resource allocation problem to maximize the sum rate of all the secondary users is investigated subject to the transmit power constraints and the interference power constraint. The optimization problem is highly nonconvex, and we jointly use the dual optimization method and the successive convex approximation method to derive resource allocation algorithms to solve the problem. Extensive simulations are shown to verify the performance of the resource allocation algorithms. It is shown that the proposed algorithms achieve much higher sum rate than that of the optimal half‐duplex algorithms and the reference full‐duplex algorithms.     

基于能效的NOMA蜂窝车联网动态资源分配算法

在支持车与车直接通信(V2V)的非正交多址接入(NOMA)蜂窝网络场景下,针对V2V用户与蜂窝用户的干扰以及NOMA准则下的功率分配问题,该文提出一种基于能效的动态资源分配算法。该算法首先为了保证V2V用户的时延及可靠性同时满足蜂窝用户的速率需求,联合考虑子信道调度、功率分配和拥塞控制,建立了最大化系统能效的随机优化模型。其次,利用李雅普诺夫随机优化方法,通过控制可接入数据量保证队列稳定性以避免网络拥塞,并根据实时网络负载状态动态地进行资源调度,设计一种次优化子信道匹配算法获得用户调度方案,进一步,利用凸优化理论和拉格朗日对偶分解方法得到功率分配策略。最后,仿真结果表明,该文算法可以满足不同用户的服务质量(QoS)需求,并在保证网络稳定性前提下提高系统能效。     

Performance analysis of an opportunistic multi‐user cognitive network with multiple primary users

Consider a multi‐user underlay cognitive network where multiple cognitive users concurrently share the spectrum with a primary network with multiple users. The channel between the secondary network is assumed to have independent but not identical Nakagami‐m fading. The interference channel between the secondary users (SUs) and the primary users is assumed to have Rayleigh fading. A power allocation based on the instantaneous channel state information is derived when a peak interference power constraint is imposed on the secondary network in addition to the limited peak transmit power of each SU. The uplink scenario is considered where a single SU is selected for transmission. This opportunistic selection depends on the transmission channel power gain and the interference channel power gain as well as the power allocation policy adopted at the users. Exact closed form expressions for the moment‐generating function, outage performance, symbol error rate performance, and the ergodic capacity are derived. Numerical results corroborate the derived analytical results. The performance is also studied in the asymptotic regimes, and the generalized diversity gain of this scheduling scheme is derived. It is shown that when the interference channel is deeply faded and the peak transmit power constraint is relaxed, the scheduling scheme achieves full diversity and that increasing the number of primary users does not impact the diversity order. Copyright © 2014 John Wiley & Sons, Ltd.