Optimal power allocation for multi-user OFDM and distributed antenna cognitive radio with RoF

In cognitive radio (CR), power allocation plays an important role in protecting primary user from disturbance of secondary user. Some existing studies about power allocation in CR utilize 'interference temperature' to achieve this protection, which might not be suitable for the OFDM-based CR. Thus in this paper, power allocation problem in multi-user orthogonal frequency division multiplexing (OFDM) and distributed antenna cognitive radio with radio over fiber (RoF) is firstly modeled as an optimization problem, where the limitation on secondary user is not 'interference temperature', but that total throughput of primary user in all the resource units (RUs) must be beyond the given threshold. Moreover, based on the theorem about maximizing the total throughput of secondary user, equal power allocation algorithm is introduced. Furthermore, as the optimization problem for power allocation is not convex, it is transformed to be a convex one with geometric programming, where the solution can be obtained using duality and Karush-Kuhn-Tucker (KKT) conditions to form the optimal power allocation algorithm. Finally, extensive simulation results illustrate the significant performance improvement of the optimal algorithm compared to the existing algorithm and equal power allocation algorithm.     

一种新的认知无线电功率分配算法（英文）

Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable signal to interference plus noise ratio(SINR) loss constraint in cognitive transmission to protect primary users.Considering power allocation problem for cognitive users over flat fading channels,in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user,we propose a new power allocation algorithm.The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.     

全双工中继协作下的认知MIMO系统吞吐量最大化研究

本文研究了全双工中继协作下的认知MIMO系统的平均吞吐量最大化问题。与传统的中继协作认知无线电系统不同的是,该系统模型中的双工中继节点既能协助认知用户源节点进行多天线频谱感知以提高频谱检测性能,也能解码转发认知用户源节点的发送信号以获得更大的系统吞吐量。为使系统平均吞吐量最大,首先,本文以认知用户能获得的最大平均频谱空洞被发现的概率为目标,对系统的帧结构进行优化以获得最佳的感知时间,接着对多个发送天线进行优化以选择出最佳的发送天线,并推导出了在总的发送功率和对主用户干扰受限条件下的认知用户源节点和双工中继节点的最佳功率分配方案。最后的仿真结果表明本文提出的系统模型和优化方案相比传统的双工等功率分配方案以及单工功率分配方案能够获得更大的系统平均吞吐量。      

Resource allocation in orthogonal frequency division multiple access‐based cognitive radio systems with minimum rate constraints

In this paper, resource allocation problem in orthogonal frequency division multiple access‐based cognitive radio (CR) systems to maintain minimum transmission rate constraints of CR users (CRUs) with the specified interference thresholds is investigated. Firstly, a single primary user (PU) CR system is considered, and a suboptimal resource allocation algorithm to maximize the sum transmission rate of all CRUs is proposed. Secondly, the single‐PU scenario is extended to multiple‐PU case, and an asymptotically optimal resource allocation algorithm is proposed using dual methods subject to constraints on both interference thresholds of PUs and total transmit power of all CRUs. Analysis and numerical results show that, in contrast to classical resource allocation algorithms, the proposed algorithm can achieve higher transmission rate and guarantee each CRU's minimum transmission rate in both scenarios. Copyright © 2012 John Wiley & Sons, Ltd.     

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

Energy‐Efficient Power Allocation for Cognitive Radio Networks with Joint Overlay and Underlay Spectrum Access Mechanism

Traditional designs of cognitive radio (CR) focus on maximizing system throughput. In this paper, we study the joint overlay and underlay power allocation problem for orthogonal frequency‐division multiple access–based CR. Instead of maximizing system throughput, we aim to maximize system energy efficiency (EE), measured by a “bit per Joule” metric, while maintaining the minimal rate requirement of a given CR system, under the total power constraint of a secondary user and interference constraints of primary users. The formulated energy‐efficient power allocation (EEPA) problem is nonconvex; to make it solvable, we first transform the original problem into a convex optimization problem via fractional programming, and then the Lagrange dual decomposition method is used to solve the equivalent convex optimization problem. Finally, an optimal EEPA allocation scheme is proposed. Numerical results show that the proposed method can achieve better EE performance.     

Optimization algorithm of periodical cooperative spectrum sensing in cognitive radio

To decrease the interference to the primary user (PU) and improve the detected performance of cognitive radio (CR), a single‐band sensing scheme wherein the CR periodically senses the PU by cooperative spectrum sensing is proposed in this paper. In this scheme, CR first senses and then transmits during each period, and after the presence of the PU is detected, CR has to vacate to search another idle channel. The joint optimization algorithm based on the double optimization is proposed to optimize the periodical cooperative spectrum sensing scheme. The maximal throughput and minimal search time can be respectively obtained through the joint optimization of the local sensing time and the number of the cooperative CRs. We also extend this scheme to the periodical wideband cooperative spectrum sensing, and the joint optimization algorithm of the numbers of the sensing time slots and cooperative CRs is also proposed to obtain the maximal throughput of CR. The simulation shows that the proposed algorithm has lower computational quantity, and compared with the previous algorithms, when SNR = 5 dB, the throughput and search time of the proposed algorithm can respectively improve 0.3 kB and decrease 0.4 s. The simulation also indicates that the wideband cooperative spectrum sensing can achieve higher throughput than the single‐band cooperative spectrum sensing. Copyright © 2012 John Wiley & Sons, Ltd.     

基于OFDM的认知无线电系统功率分配研究

分析了基于OFDM的认知无线电系统中认知用户和授权用户之间的相互干扰,以及下行链路对认知用户进行功率分配的优化目标,并给出了速率最大化优化目标下的最优功率分配方案。授权用户能够承受的干扰功率成为认知无线电系统功率分配问题的主要限制因素,其限制了认知用户的发射功率和传输速率,认知用户传输产生的干扰必须满足授权用户能够承受的干扰功率限制。     

A joint subcarrier selection and power allocation scheme using variational inequality in OFDM‐based cognitive relay networks

Introducing orthogonal frequency division multiplexing (OFDM) into cognitive radio (CR) can potentially increase the spectrum efficiency, but it also leads to further challenges for the resource allocation of CR networks. In OFDM‐based cognitive relay networks, two of the most significant research issues are subcarrier selection and power allocation. In this paper, a non‐cooperative game model is proposed to maximize the system throughput by jointly optimizing subcarrier selection and power allocation. First, taking the direct and relay links into consideration, an equivalent channel gain is presented to simplify the cooperative relay model into a non‐relay model. Then, a variational inequality method is utilized to prove the existence and uniqueness of the Nash equilibrium solution of the proposed non‐cooperative game. Moreover, to compute the solution of the game, a suboptimal algorithm based on the Lagrange function and distributed iterative water‐filling algorithm is proposed. The proposed algorithm can jointly optimize the process of subcarrier selection and power allocation. Finally, simulation results are shown to demonstrate the effectiveness of the proposed joint subcarrier selection and power allocation scheme. Copyright © 2015 John Wiley & Sons, Ltd.     

H-CRAN网络下联合拥塞控制和资源分配的网络切片动态资源调度策略

针对异构云无线接入网络(H-CRAN)网络下基于网络切片的在线无线资源动态优化问题,该文通过综合考虑业务接入控制、拥塞控制、资源分配和复用,建立一个以最大化网络平均和吞吐量为目标,受限于基站(BS)发射功率、系统稳定性、不同切片的服务质量(QoS)需求和资源分配等约束的随机优化模型,并进而提出了一种联合拥塞控制和资源分配的网络切片动态资源调度算法。该算法会在每个资源调度时隙内动态地为性能需求各异的网络切片中的用户分配资源。仿真结果表明,该文算法能在满足各切片用户QoS需求和维持网络稳定的基础上,提升网络整体吞吐量,并且还可通过调整控制参量的取值实现时延和吞吐量间的动态平衡。     

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.     

协作多组多播认知无线网络的资源优化配置

考虑到无线电频谱资源日益紧缺,提出了一种基于组间组内协作传输的多播组新机制,涉及多个多播组并使用同一频谱资源以协作方式传输信息。基于认知无线网络中该机制,研究了系统的资源优化配置,理论分析得出了功率分配方案,进而讨论了系统加权总传输速率的优化,同时考虑了主用户和认知用户之间信号干扰及功率限制对传输速率的影响,最优化用户性能。仿真结果表明,优化方案下多播组传输速率随用户人数的增加而上升,达到最优化用户服务质量;当功率限制时,通过设置加权因子,能够保证主用户拥有良好的通信性能。     

Power Allocation with Max–Min and Min–Max Fairness for Cognitive Radio Networks with Imperfect CSI

This paper consider the power allocation strategies in the cognitive radio (CR) system in the presence of channel estimation errors. As the user has different channel condition in CR systems, different amount of power resource is required to meets the QoS request. In order to guarantee the fairness of each CR user, ensure the interference from the primary user and other CR users meet the QoS requirement of the CR user and limit the interference that is caused by CR users on primary user within the range into the level that primary user can tolerate, we proposed some new power allocation schemes. The targets are to minimize the maximum power allocated to CR users, to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all CR users and to minimize the maximum outage probability over all CR users. The first power allocation scheme can be formulated using Geometric Programming (GP). Since GP problem is equivalent to the convex optimization problem, we can obtain the optimal solutions for the first scheme. The latter two power allocation schemes are not GP problems. We propose iterative algorithms to solve them. Simulation results show that proposed schemes can efficiently guarantee the fairness of CR users under the QoS constraint of the primary user and CR users.     

Novel scheme for interference avoidance in cognitive radio based cellular networks

The cognitive radio (CR) technology is believed to improve the spectrum efficiency.However,the interference problem has become a critical issue due to the coexistence of primary systems and CR systems....     

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.     

A Fast Subcarrier, Bit, and Power Allocation Algorithm for Multiuser OFDM-Based Systems

In this paper, we propose a real-time subcarrier, bit, and power allocation algorithm for orthogonal frequency-division multiplexing-based multiuser communication systems in downlink transmission. Assuming that base stations know the channel gains of all subcarriers of all users, the proposed loading algorithm tries to minimize the required transmit power while satisfying the rate requirement and data error rate constraint of each user. The novel algorithm simultaneously determines subcarrier, bit, and power allocation by enhancing the suboptimal algorithm by Wong while having the same computational complexity. The proposed scheme offers better performance in terms of transmit power than that of Wong , as demonstrated in the simulation results, whereas the performance of the scheme in Wong was close to that of the optimal solution.     

Joint power and spectrum allocation in multi-hop cognitive radio networks

Various cognitive network technologies are developed rapidly. In the article, the power and spectrum allocation in multi-hop cognitive radio network （CRN） with linear topology is investigated. The overall goal is to minimize outage probability and promote spectrum utility, including total reward and fairness, while meeting the limits of total transmit power and interference threshold to primary user simultaneously. The problem is solved with convex optimization and artificial bee colony （ABC） algorithm jointly. Simulation shows that the proposed scheme not only minimizes outage probability, but also realizes a better use of spectrum.     

Power allocation in OFDM cognitive radio relay networks with outdated channel state information

In this paper, we study power allocation in OFDM cognitive radio (CR) relay networks. The objective of power allocation is to maximize the instantaneous capacity of the CR network. It is assumed that the available channel state information between the secondary and primary users is an outdated but correlated version of the actual instantaneous channel state information. Optimal power allocation schemes are developed for both decode‐and‐forward and amplify‐and‐forward relay assisted CR transmission, assuming that the primary users are subject to average interference constraints and the CR transmitters are subject to maximum transmit power constraint. In addition, suboptimal power allocation schemes with reduced complexity are also proposed. Performance of the proposed schemes is compared with uniform power allocation and numerical results confirm that the proposed power allocation schemes achieve significant capacity improvement in comparison to uniform power loading. Furthermore, the proposed suboptimal power allocation schemes can be used as less complex alternatives for optimal power allocation with some capacity degradation. Copyright © 2014 John Wiley & Sons, Ltd.     

Joint Optimization of User Set Selection and Transmit Power Allocation for Orthogonal Random Beamforming in Multiuser MIMO Systems

When the number of users is finite, the performance improvement of the orthogonal random beamforming (ORBF) scheme is limited in high signal‐to‐noise ratio regions. In this paper, to improve the performance of the ORBF scheme, the user set and transmit power allocation are jointly determined to maximize sum rate under the total transmit power constraint. First, the transmit power allocation problem is expressed as a function of a given user set. Based on this expression, the optimal user set with the maximum sum rate is determined. The suboptimal procedure is also presented to reduce the computational complexity, which separates the user set selection procedure and transmit power allocation procedure.     

QoS保证的多信道混合接入CRN频谱共享策略设计

根据既不对主用户(Primary Radio user,PR)产生干扰,又对认知无线电用户(Cognitive Radio user,CR)提供QoS保证的原则,将认知无线电网络(Cognitive Radio Network,CRN)中多信道接入频谱共享问题建模为混合整数非线性规划。采用多级功率限制保证PR不被干扰,以CR物理层能够提供的速率作为信道和功率分配的依据,提出将能够为CR提供最大传输速率的信道分配给该CR的分配策略,将混合整数非线性规划转化为整数线性规划,并给出集中式启发算法和基于功率速率比(Power Rate Ratio,PRR)最小的分布式启发算法求解该整数线性规划。仿真结果表明,文中给出的算法能够提供较高的CRN吞吐量和较好的CR用户QoS保证。