Discrete polynary coding immune clonal selection‐based joint subcarrier and power allocation in uplink cognitive OFDM network

Cognitive radio has been considered to be one of the main technologies to solve the problem of low spectrum utilization, while the adaptive allocation of network resource is one of the key technologies. A discrete polynary coding immune clonal selection (DPICS)‐based joint subcarrier and power allocation algorithm is proposed to solve the resource allocation problem in uplink cognitive OFDM networks. The novelties of DPICS include the following: A unique coding method is adopted to deal with multi‐value discrete variables. Compared with the traditional methods, the proposed method can acquire the shortest code. Meanwhile, the constraints of the subcarrier allocation are avoided. A heuristic mutation scheme is used to direct the mutation. Subcarriers are reallocated randomly to the secondary users with larger homotactic noise, which has a large probability to produce the optimal solution and improves the searching process. Subcarriers and power are allocated simultaneously, which is different with the traditional biphasic resource allocation algorithms. The biphasic resource allocation algorithms cannot acquire the subcarrier allocation result and power allocation result simultaneously, which makes the final result imprecise. The proposed algorithm avoids this situation and improves the accuracy of the final result. Compared with state‐of‐the‐art algorithms, the proposed algorithm is shown as effective by simulation results. Copyright © 2014 John Wiley & Sons, Ltd.     

Dynamic subcarrier and power allocation based on cooperative game theory in symmetric cooperative OFDMA networks

In order to improve the efficiency and fairness of radio resource utilization,a scheme of dynamic cooperative subcarrier and power allocation based on Nash bargaining solution(NBS-DCSPA) is proposed in the uplink of a three-node symmetric cooperative orthogonal frequency division multiple access(OFDMA) system.In the proposed NBS-DCSPA scheme,resource allocation problem is formulated as a two-person subcarrier and power allocation bargaining game(SPABG) to maximize the system utility,under the constraints of each user’s maximal power and minimal rate,while considering the fairness between the two users.Firstly,the equivalent direct channel gain of the relay link is introduced to decide the transmission mode of each subcarrier.Then,all subcarriers can be dynamically allocated to the two users in terms of their selected transmission mode.After that,the adaptive power allocation scheme combined with dynamic subcarrier allocation is optimized according to NBS.Finally,computer simulation is conducted to show the efficiency and fairness performance of the proposed NBS-DCSPA scheme.     

Resource allocation in MIMO‐OFDM‐based cooperative cognitive radio networks: optimal and suboptimal low complexity approaches

The problem of resources allocation in multiple‐input multiple‐output‐orthogonal frequency division multiplexing based cooperative cognitive radio networks is considered, in this paper. The cooperation strategy between the secondary users is decode‐and‐forward (DF) strategy. In order to obtain an optimal subcarrier pairing, relay selection and power allocation in the system, the dual decomposition technique is recruited. The optimal resource allocation is realized under the individual power constraints in source and relays so that the sum rate is maximized while the interference induced to the primary system is kept below a pre‐specified interference temperature limit. Moreover, because of the high computational complexity of the optimal approach, a suboptimal algorithm is further proposed. The jointly allocation of the resources in suboptimal algorithm is carried out taking into account the channel qualities, the DF cooperation strategy, the interference induced to the primary system and the individual power budgets. The performance of the different approaches and the impact of the constraint values and deploying multiple antennas at users are discussed through the numerical simulation results. Copyright © 2014 John Wiley & Sons, Ltd.     

认知无线网络中一种基于匹配和干扰量化的LTE-A上行资源共享机制

认知无线网络中基于OFDMA的次系统(SS)与LTE-A主系统(PS)以重叠方式共享频谱的问题越来越受到学术界重视,该文关注上述场景中的资源分配和干扰避免问题。该问题的困难在于资源分配子问题中带耦合干扰的功率分配问题是NP-难的。为了满足研究场景提出的时延约束,该文将提出两阶段资源分配算法：子载波分配阶段的最大权匹配方法和功率分配阶段的干扰量化分配方法,简记为MQRA算法。理论分析和仿真结果表明,该文提出的MQRA算法能够很好地平衡性能和复杂性,并适用于LTE-A主系统下的频谱共享问题。     

Robust power and subcarrier allocation algorithm for cognitive network based on interference efficiency maximization

For the cognitive OFDMA uplink communication system,a robust power and subcarrier allocation algorithm based on maximum interference efficiency was proposed.Firstly,considering primary user interference constraint,secondary user transmit power constraint,subcarrier allocation constraint and secondary user minimum rate constraint,a robust resource optimization model based on outage probability was established.Then,by using Bernstein approximation and Dinkelbach’s method,the original non-convex problem based on outage probability was transformed into an equivalent convex optimization one,and the analytical solution was obtained by Lagrangian dual function method.Meanwhile,the computational complexity and robust sensitivity of the algorithm were analyzed.The simulation results show that the proposed algorithm has better interference efficiency and robustness.     

Adaptive subcarrier bandwidth and power in OFDM‐based cognitive radio systems for high mobility applications

OFDM‐based cognitive radio systems are spectrally flexible and efficient, but they are vulnerable to intercarrier interference (ICI), especially in high mobility environments. High mobility of the terminal causes large Doppler frequency spread resulting in serious ICI. Such ICI severely degrades the system performance, which is ignored in the existing resource allocation of OFDM‐based cognitive radio systems. In this paper, an adaptive subcarrier bandwidth along with power allocation problem in OFDM‐based cognitive radio systems for high mobility applications is investigated. This adaptive subcarrier bandwidth method should choose the suitable subcarrier bandwidth not only to balance the tradeoff between ICI and intersymbol interference but also to be large enough to tolerate an amount of Doppler frequency spread but less than the coherence bandwidth. The power budget and interference to primary users caused by cognitive radio users are imposed for primary users' protection. With these constraints, a joint optimization algorithm of subcarrier bandwidth and power allocation is proposed to maximize the bandwidth efficiency of OFDM‐based cognitive radio systems in such conditions. Numerical simulation results show that the proposed algorithm could maximize the system bandwidth efficiency and balance this tradeoff while satisfying the constraints. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive Resource Allocation for MC‐CDMA and OFDMA in Reconfigurable Radio Systems

This paper studies the uplink resource allocation for multiple radio access (MRA) in reconfigurable radio systems, where multiple‐input and multiple‐output (MIMO) multicarrier‐code division multiple access (MC‐CDMA) and MIMO orthogonal frequency‐division multiple access (OFDMA) networks coexist. By assuming multi‐radio user equipment with network‐guided operation, the optimal resource allocation for MRA is analyzed as a cross‐layer optimization framework with and without fairness consideration to maximize the uplink sum‐rate capacity. Numerical results reveal that parallel MRA, which uses MC‐CDMA and OFDMA networks concurrently, outperforms the performance of each MC‐CDMA and OFDMA network by exploiting the multiuser selection diversity.     

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.     

Proportional-fairness resource allocation for uplink OFDM-based cognitive radio systems

This paper has proposed a proportional-fairness resource allocation algorithm, including both subcarrier assignment algorithm and power allocation algorithm, for uplink orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems. First, to get a better performance in the proposed system model, the influence factor (a,b,c) was introduced to realize the assignment of the subcarriers. Second, the transmit power of the secondary users (SUs) was allocated to the corresponding subcarriers in order to maximize the uplink capacity of the SUs subject to both power and interference constraints. With the appropriate influence factor in the subcarrier assignment, the loss of transmitted data rate arising from the fairness was minimized. Simulation results showed that the proposed algorithm can achieve a perfect fairness among the SUs while maximizing the system capacity simultaneously, and is of a low computation complexity.     

Resource Allocation Algorithm for Multi‐cell Cognitive Radio Networks with Imperfect Spectrum Sensing and Proportional Fairness

This paper addresses the resource allocation (RA) problem in multi‐cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered—such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP‐hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub‐gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.     

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.     

Utility‐based resource allocation in uplink of OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum opportunistically on the basis of non‐interfering to licensed users. This paper addresses the problem of resource allocation for multiaccess channel (MAC) of OFDMA‐based cognitive radio networks. The objective is to maximize the system utility, which is used as an approach to balance the efficiency and fairness of wireless resource allocation. First, a theoretical framework is provided, where necessary and sufficient conditions for utility‐based optimal subcarrier assignment and power allocation are presented under certain constraints. Second, based on the theoretical framework, effective algorithms are devised for more practical conditions, including ellipsoid method for Lagrangian multipliers iteration and Frank–Wolfe method for marginal utilities iteration. Third, it is shown that the proposed scheme does not have to track the instantaneous channel state via an outage‐probability‐based solution. In the end, numerical results have confirmed that the utility‐based resource allocation can achieve the optimal system performance and guarantee fairness. Copyright © 2009 John Wiley & Sons, Ltd.     

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.     

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.     

LTE-A异构网络下的高效资源分配算法

分析了OFDMA上行系统中,由宏基站(macrocell)和家庭式基站(femtocell)组成的双层网络,并提出了高效的资源分配算法。为避免严重的跨层干扰导致双层网络中的资源分配不协调,提出了一个跨层干扰控制算法。在基于干扰控制算法的结果上,提出包括功率分配和频谱分配的资源分配算法,以满足UE的目标速率,并获得较好的吞吐量性能。通过仿真,结果显示所提的资源分配算法相比较传统的算法,尤其在UE QoS保证和吞吐量性能的体现上,能获得明显的性能增益。     

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.     

Joint resource allocation,routing and CAC for uplink OFDMA networks with cooperative relaying

In this paper, we propose a joint resource allocation, routing, and connection admission control (CAC) scheme for uplink transmission in orthogonal frequency division multiple access (OFDMA) relay networks with cooperative relaying. For cooperative relaying, relay station can relay uplink data from mobile station (MS) to base station with cooperation of the MS using transmit diversity. Transmit diversity can be achieved by virtual MISO via distributed space–time coding. The proposed scheme jointly allocates OFDMA resources and selects path for each user with CAC to maximize the upink throughput of cooperative OFDMA relay networks. The basic OFDMA resource unit is considered as a resource element which is one subcarrier over one OFDMA symbol. An efficient multi-choice multi-dimensional knapsack (MMKP) algorithm is presented for the proposed scheme. The proposed MMKP algorithm provides a unified framework which is applicable to OFDMA networks with and without cooperative relaying. We evaluate the performance of the proposed scheme with and without cooperative relaying in a hilly terrain with heavy tree density by using OPNET-based simulation. We show that the cooperative relaying improve the uplink system throughput compared with non-cooperative relaying, and the proposed scheme outperforms the conventional link quality-based scheme in both cooperative and non-cooperative relay networks.     

基于OFDM的协同认知网络跨层资源调度

协同通信与认知无线电是未来移动通信的重要技术。针对基于OFDM的无线协同认知网络中的资源分配问题,该文提出了一种有效的跨层资源调度方案。该调度方案在考虑对主用户所受干扰功率进行控制的前提下,以最大化认知用户超帧中总的传输速率为目标,在调度帧中对各传输帧两阶段的子载波进行最佳配对,并为配对子载波分配最优的发送功率。通过分步求解的方法,该调度方案形成的优化问题得到有效解决。仿真结果表明该资源调度方案使得认知用户传输速率有显著提升,方案的可行性与有效性得到了验证。     

A hybrid joint ML technique for CFO,timing offset,and channel estimations in an OFDMA uplink

In this paper, we propose a novel hybrid joint maximum‐likelihood estimator for carrier frequency offset (CFO), timing offset, and channel response of all users in the uplink of an orthogonal frequency division multiple access (OFDMA) system. The proposed estimation method significantly reduces complexity of this multiparameter, multidimensional optimization problem, using the concept of separation of the different user signals by means of newly defined projection operators. This projection technique is combined with the alternating projection method available in the literature to arrive at a new hybrid algorithm that offers significant performance advantages in terms of computational complexity and estimator performance. The joint estimation of the CFOs, timing offsets, and channel coefficients for all active users together at the base station of the OFDMA uplink is a rarely addressed task. The proposed method also offers the flexibility of application to any subcarrier assignment scheme used in OFDMA systems. Extensive simulation studies corroborate the advantages of the new hybrid method for all three estimation requirements in the multiuser OFDMA uplink. Copyright © 2012 John Wiley & Sons, Ltd.