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.     

Resource allocation in heterogeneous cooperative cognitive radio networks

In cognitive radio networks (CRNs), resources available for use are usually very limited. This is generally because of the tight constraints by which the CRN operate. Of all the constraints, the most critical one is the level of permissible interference to the primary users. Attempts to mitigate the limiting effects of this constraint, thus achieving higher productivity, are a current research focus, and in this work cooperative diversity is investigated as a promising solution. Cooperative diversity has the capability to achieve diversity gain for wireless networks. In the work, therefore, the possibility of and mechanism for achieving greater utility for the CRN when cooperative diversity is incorporated are studied. To accomplish this, a resource allocation model is developed and analyzed for the heterogeneous, cooperative CRN. In the model, during cooperation, a best relay is selected to assist the secondary users that have poor channel conditions. Overall, the cooperation makes it feasible for virtually all the secondary users to improve their transmission rates while still causing minimal harm to the primary users. The results show a marked improvement in the resource allocation performance of the CRN when cooperation is used in contrast to when the CRN operates only by direct communication.     

RETRACTED ARTICLE: Throughput maximization of multichannel allocation mechanism under interference constraint for hybrid overlay/underlay cognitive radio networks with energy harvesting

Wireless Networks - By harvesting energy from ambient radio frequency (RF) signals, significant progress has been achieved in wireless networks self-maintaining their life cycles. Motivated by this...     

A survey of overlay and underlay paradigms in cognitive radio networks

In the recent years, wireless applications and services have grown tremendously, resulting to a shortage of radio spectrum. On one hand, most of the available radio spectrum has already been allocated to different users and service providers. On another hand, research and statistics have revealed that the spectrum utilization usability is very limited. To address this dilemma, the concept of cognitive radio has emerged, which promotes the use of overlay and underlay transmission techniques to boost the utilization of radio spectrum resources. This paper provides a comprehensive survey of these 2 techniques and compares them qualitatively based on several network parameters. Next, this paper simulates overlay and underlay transmission techniques in OMNeT++ simulator on different network parameters, namely, Primary user arrival rate, throughput, sensing duration, and energy consumption. Our findings reveal that neither the overlay nor the underlay technique is sufficient itself to fulfill the demands for future wireless systems, and adopting a hybrid access technique consisting of a joint utilization of overlay and underlay approaches is desirable. Furthermore, the key challenges and open research issues in radio spectrum resources utilization are discussed.     

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.     

Optimal resource allocation solutions for heterogeneous cognitive radio networks

Cognitive radio networks (CRN) are currently gaining immense recognition as the most-likely next-generation wireless communication paradigm, because of their enticing promise of mitigating the spectrum scarcity and/or underutilisation challenge. Indisputably, for this promise to ever materialise, CRN must of necessity devise appropriate mechanisms to judiciously allocate their rather scarce or limited resources (spectrum and others) among their numerous users. ‘Resource allocation (RA) in CRN', which essentially describes mechanisms that can effectively and optimally carry out such allocation, so as to achieve the utmost for the network, has therefore recently become an important research focus. However, in most research works on RA in CRN, a highly significant factor that describes a more realistic and practical consideration of CRN has been ignored (or only partially explored), i.e., the aspect of the heterogeneity of CRN. To address this important aspect, in this paper, RA models that incorporate the most essential concepts of heterogeneity, as applicable to CRN, are developed and the imports of such inclusion in the overall networking are investigated. Furthermore, to fully explore the relevance and implications of the various heterogeneous classifications to the RA formulations, weights are attached to the different classes and their effects on the network performance are studied. In solving the developed complex RA problems for heterogeneous CRN, a solution approach that examines and exploits the structure of the problem in achieving a less-complex reformulation, is extensively employed. This approach, as the results presented show, makes it possible to obtain optimal solutions to the rather difficult RA problems of heterogeneous CRN.     

Joint overlay and underlay resource allocation with weighted fairness in OFDM‐based cognitive radio systems

In this paper, the problem of hybrid overlay and underlay spectrum access is investigated for OFDM‐based cognitive radio (CR) systems. Both the metrics for system (e.g. capacity) and users (e.g. fairness) are integrated into the unified framework of weighted‐capacity maximization with the interference constraint in CR systems. For easing the procedure of resource allocation, two criteria, respectively, for subcarrier assignment and power allocation are theoretically derived based on the Karush–Kuhn–Tucker conditions. Under the guidance of the two criteria, max‐capacity subcarrier assignment and optimal power allocation are proposed to flexibly distribute spectrum resources to secondary users. In order to reduce the computational complexity further, a suboptimal power allocation algorithm, referred to as cap‐limited waterfilling, is also presented by decomposing the interference constraint. Simulation results show that the capacity and fairness performance of the proposed algorithms is considerably better than the conventional ones in references. The proposed suboptimal algorithm with substantially lower complexity approaches to optimal power allocation in the vicinity of only 1% performance gap. Meanwhile, joint access model is greatly beneficial to spectrum efficiency enhancement in CR systems. Copyright © 2014 John Wiley & Sons, Ltd.     

On-demand ecology-inspired spectrum allocation mechanism for heterogeneous cognitive radio networks

As increasing number of cognitive radio network (CRN) standards are developed in TV White Spaces band with incompatible communication patterns, heterogeneous CRNs coexistence problem could not be avoided. However, most solutions on this problem have not considered CRNs’ actual data transmission demands and weighted fairness simultaneously. Therefore, we would like to introduce a novel On-demand ecological Species Competition based HEterogeneous networks coexistence MEchanism (O-SCHEME) in this paper. Inspired by ecology species competition model, O-SCHEME utilizes an ecology based spectrum allocation mechanism for guaranteeing heterogeneous CRNs’ spectrum shares weighted fairness. And by employing CRNs’ communication spectrum requirement constraints, actual data transmission needs could be satisfied without wasted communication resources. Through both theoretical and simulation analyses, we demonstrate that O-SCHEME can achieve stable and fair spectrum allocations among coexisting networks with high communication efficiency.     

Resource allocation for non-real-time services in OFDM-based cognitive radio systems

We study the resource allocation (RA) problem in a multiuser OFDM-based cognitive radio (CR) system for non-realtime (NRT) applications in which average user data rates are to be maintained proportionally. In contrast to existing algorithms designed for multiuser OFDM systems, which are unable to guarantee users proportional rates when applied in a CR system, the proposed optimal RA algorithm ensures that CR user rates are maintained in proportion to predefined target rates while at the same time providing an improved system throughput.     

Distributed opportunistic scheduling for MIMO underlay cognitive radio networks

Cognitive radio networks have emerged to improve the utilization of the scarce spectrum. In this paper, we propose a distributed resource allocation algorithm that allocates resources opportunistically to the secondary users in a multiple‐input multiple‐output environment. In order to reduce the complexity and cost, antenna selection schemes are employed to allow the secondary communication using a single radio frequency chain. The proposed algorithm is proved theoretically and using simulations, to give a performance very close to that of a centralized one with lower delay and overhead. Furthermore, we introduce two techniques for the proposed algorithm based on the allowable data rates referred to as limited and maximum rates. We derive closed‐form expression for the consumed power and tight upper bounds for the average throughput achieved by each technique. A comparison between the proposed techniques is also provided. Both simulations and analytical results show that the proposed algorithm achieves high throughput with low complexity. Moreover, the results show that the tightness of the bounds improves with the diversity order. Finally, the proposed techniques are compared with two suggested random schemes to investigate their effectiveness. Copyright © 2016 John Wiley & Sons, Ltd.     

Performance analysis of two-way relay cooperation underlay cognitive radio networks based on WIPT

The two-way relay cooperation for underlay cognitive radio networks based on WIPT was presented,where secondary system adopted the two-way relay cooperative transmission.First,the relay adopted a power splitting protocol to harvest energy and to decode information transmitted by secondary users,then the relay forwarded information to two secondary users by using the harvested energy.Subsequently the exact expression of the outage probability,the ergodic capacity and energy efficiency of the secondary user system were derived.Finally,numerical simulation discusses the impact on the system performance with regard to secondary transmission power.The results reveal that the two-way relay cooperation effectively reduces the outage probability of data transmission.The capacity and energy efficiency of the system reaches optimal level when the power allocation coefficient is 0.5.     

基于用户分簇的认知超密集网络资源分配

针对5G时代小基站的密集部署带来的复杂干扰问题,对下行的认知无线电超密集网络下的资源分配进行了研究。为减小网络干扰,提高次用户吞吐量,提出了一种改进的基于用户分簇的资源分配算法。基于基站的覆盖范围,选出用户的强干扰基站,以用户-基站干扰关系建立用户-用户干扰图,按用户受到的平均弱干扰划分优先级对用户分簇,再为簇集群预分配频段,为每个簇分配对应频段中效用最大的信道。该资源分配算法能准确反映用户间的干扰关系,保障资源分配公平性。仿真结果表明,当用户密度与基站密度均较大时,与相同场景的已有算法相比,该改进算法有较好的抗干扰能力,能有效提高次用户的吞吐量。     

Study on optimization strategy for hybrid underlay/overlay spectrum sharing based on queuing model

In order to improve the licensed spectrum utilization in cognitive radio networks,and provide higher experience quality to system users,the optimizing strategies of the hybrid underlay/overlay spectrum sharing mode was studied.For secondary users,a queuing model with service time following two phase order exponential distribution was constructed,and a method to obtain the steady state distribution was presented for the system model.Based on reward-cost structure,individual optimization strategy with observable case and the Nash equilibrium strategy with unobservable case were discussed.With purpose of optimal social benefit and maximal spectrum incomes,the pricing policies for secondary users to use licensed spectrum were formulated.Using the system experiment,the relations among the different optimal strategies were investigated,and the rationality of the price mechanism was verified.By contrasting the optimal social benefits gained by hybrid underlay/overlay spectrum sharing mode,overlay spectrum sharing mode and underlay spectrum sharing mode,it is further shown that the social optimization strategy of hybrid overlay/underlay sharing mode is more effective and stable to fully use the spectrum resource.     

认知双向中继网络的功率分配优化算法研究

相对于传统的认知单向中继系统,认知双向中继网络由于引入了网络编码技术,减少了传输时隙,能获得更高的频谱效率．对采用时分广播(Time Division Broadcast,TDBC)传输协议的译码转发(Decode-and-Forward,DF)认知双向中继网络的和速率进行了分析,提出了一种功率分配的优化算法,能在满足次用户(Secondary Users,SUs)总功率约束以及对主用户(Primary Users,PUs)最大干扰功率(Maximum Tolerable Interference Power,MTIP)约束的前提下,最大限度提高次用户网络的和速率．并推导了不同情况下,次用户网络功率分配的最优解．数值仿真结果验证了该理论分析的正确性,同时表明,次用户的总功率以及主用户的干扰功率限制,对次用户网络的和速率有较大影响．     

Channel allocation and reallocation for cognitive radio networks

In this paper, a new channel allocation and re‐location scheme is proposed for cognitive radio users to efficiently utilize available spectrums. We also present a multiple‐dimension Markov analytical chain to evaluate the performance of this scheme. Both analytical results and simulation results demonstrate that the new scheme can enhance the radio system performance significantly in terms of blocking probability, dropping probability, and throughput of second users. The proposed scheme can work as a non‐server‐based channel allocation, which has practical values in real engineering design. Copyright ©2011 John Wiley & Sons, Ltd.     

Power allocation algorithm for cognitive radio energy harvesting networks based on energy cooperation

An algorithm to optimize the power allocation by maximizing the system throughput in cognitive radio energy harvesting networks was proposed.The algorithm formulated the throughput optimization model subject to the causality constraints of the harvested energy within the two secondary users and the interference constraint of the primary user.In addition,by applying the variable-substitution method and problem equivalence transformation,the joint optimization problem of power and cooperative energy was decoupled into two problems:a power allocation problem and a cooperative energy one.The former problem could be solved by iterating the two decoupled problems.As shown in the simulation results,the energy cooperation can significantly improve the system throughput when the harvested energy difference between two nodes is rather large.     

基于改进遗传算法的认知无线传感网动态频谱分配方案

将认知无线电中的动态频谱分配技术应用在无线传感网中,针对工作在ISM(industrial,scientific and medical)频段的无线传感网面临的频谱资源紧缺问题,提出一种基于改进自适应遗传算法的动态频谱分配方案.该算法以图论着色模型为基础,以最大带宽收益和最小切换频率为目标函数,在交叉和变异过程中采用自适应交叉概率和变异概率代替固定的交叉概率和变异概率.仿真结果表明,与传统遗传算法和颜色敏感图论着色算法相比,该算法可以实现提高频谱利用率、降低能量消耗的预期目标.