Bee colony optimization aided adaptive resource allocation in OFDMA systems with proportional rate constraints

Orthogonal frequency division multiple access (OFDMA) is a promising technique, which can provide high downlink capacity for the emerging wireless systems. The total capacity of OFDMA can be maximized by adaptively assigning subcarriers to the users with the best gains for those subcarriers, with power subsequently distributed by water-filling. In this paper, we propose the use of artificial bee colony (ABC) algorithm combined with Deb’s selection mechanism to handle the constraints. In this scheme, a probabilistic selection scheme assigns probability values to feasible solutions based on their fitness values and to infeasible individuals based on their violations, to allocate the resources to the users in downlink OFDMA system. Specifically we propose two approaches for resource allocation in downlink OFDMA systems using ABC algorithm. In the first approach, ABC algorithm is used for subcarrier allocation only, while in second approach the ABC algorithm is used for joint subcarrier and power allocation. It is shown that both these approaches obtain higher sum capacities as compared to that obtained by previous works, with comparable computational complexity. It is also shown that the joint subcarrier and power allocation approach provides near optimal results at the cost of slightly higher computational cost.     

基于改进图着色的D2D资源分配和功率控制

针对蜂窝网络中D2D（Device-to-Device）用户复用蜂窝信道带来的同频干扰问题,提出了一种基于改进图着色的资源分配和功率控制算法。首先通过构建干扰图和候选集进行用户之间干扰关系建模,并定义指数型累积因子改进图着色算法,为D2D用户分配蜂窝信道;再采用基于信干噪比的闭环功率控制算法动态调整D2D用户发射功率,减小由于信道复用产生的干扰。仿真结果表明,与现有算法相比,所提算法能够有效提升系统吞吐量和D2D用户接入率,实现信道资源的合理分配。     

Power allocation in multibeam satellites based on particle swarm optimization

In this paper, a power allocation in multibeam satellite (MBS) communication based on heuristic particle swarm optimization (PSO) is proposed. The PSO algorithm is evocated to solve the problem of power allocation in the multiple narrow spotbeams aiming to provide the minimum signal-to-noise plus interference ratio (SNIR) required by Earth station users to establish reliable communication. In the developed model it is considered the multibeam interference and the different channel conditions of each beam by rain attenuation. The numerical results have been generated taking into account different sky situations, including clear and rainy scenarios; such results have revealed the viability and accuracy of the PSO algorithm deployment in solving the power allocation problem. In addition, with the proposed scheme it is observed the decrement of transmitted power for non-rainy beams with guarantee of the minimum SNIR at the Earth receivers input, while increase the power availability to the rainy beams; as a consequence, the overall energy efficiency of the MBS system has been improved substantially. Moreover, the convergence of the proposed heuristic PSO-based algorithm is discussed while such heuristic approach comes with computational complexity reduction when compared with others efficient power allocation schemes.     

认知无线网络中功率和信道接入的联合优化

在认知无线网络中,针对系统中所有用户能否接入同一信道进行通信的问题,提出了适用于不同情形的联合优化方案.在系统不可行的情形下,提出了联合优化功率和接入控制的方案.由于接入控制是NP问题,于是利用所提LP-PSO算法来实现优化控制,并分析和证明了所提算法的收敛性.在系统可行的情形下,提出了联合优化功率和传输速率分配的方案,通过改进拉格朗日对偶(Lagrange duality)算法来实现优化控制.数值结果分析表明,相比其他接入控制算法,虽然所提算法的时间复杂度有所增加但能够快速收敛,在有效地提高接入量的同时还能降低功率消耗,并能使传输速率得到更公平的分配.     

Energy efficient joint radio resource management in D2D assisted cellular communication

Device-to-device (D2D) is one of the promising technology that can be used in association with cellular networks for the provision of high data rates, which is the foremost demand of today’s cellular users. The climatic changes due to combustion are posing another big challenge that needs to be addressed by today’s technologists to strive for existence of humanity. Thus developing energy efficient schemes for the deployment of such joint venture is a challenging task due to increased system complexity. This paper addresses the mode selection, user admission control and the resource allocation issues related to optimizing the overall Energy Efficiency (EE) of the cellular systems. The contributions that have been made in this paper are (1) Development of a pooled D2D and cellular network optimization model for efficient resource allocation (2) Development of an algorithm for maximization of EE for the proposed joint D2D cellular network . The problem formulated is a Mixed Integer Nonlinear Problem, whereas such problems belong to a class of optimization problems whose computational complexity is quite high that is NP-hard. In such hard problems the computational complexity increases with increasing the number of users that make these problems more challenging. Finding the optimal solution of such hard problems by the brute force and searching the feasible space is also challenging since the complexity increases exponentially by increasing the admitted users. A Mesh Adaptive Direct Search algorithm has been proposed to find the EE resource allocation for this user admission controlled D2D based cellular network. Based on analysis of our simulation results, it can be clearly designated that our proposed solution for increasing the EE for this joint cellular and D2D venture is very much close to optimal solution provided by Exhaustive Search Algorithm.     

改进粒子群算法在频谱功率分配中的应用

在认知无线电中,由于次用户干扰门限要求的存在,传统频谱功率分配方式获得的次用户有效信道容量较低。针对这一问题,提出了一种基于粒子群算法的频谱功率分配算法。首先建立基于干扰距离的认知网络干扰模型,将频谱功率分配问题转化为函数优化问题,并借助混合随机变异思想的粒子群算法进行求解;针对寻优过程中的约束问题,提出了一种基于投入产出比的外点法,保证粒子群在可行域中寻优,最终获得频谱功率分配。仿真结果表明,与传统算法相比,所提算法能够获得较高的次用户有效信道容量。     

Robust resource allocation algorithm for heterogeneous wireless networkwith SWIPT

To improve energy efficiency and robustness of heterogeneous wireless networks with wireless information and power transfer,the robust joint transmit power and power splitting resource allocation problem was studied.Based on mini-max probability machine and Dinkelbach method,the original NP-hard problem was transformed into a solvable convex optimization form,meanwhile a distributed dual resource allocation algorithm was proposed.Additionally,both computational complexity and robust sensitivity were analyzed.Simulation results show that the proposed algorithm can guarantee the quality of service requirements of macro cellular users and femtocell users under channel uncertainties.     

Dynamic resource allocation algorithm in multi-user cooperative OFDMA systems: considering QoS and fairness constraints

Wireless transmission systems are constrained by several parameters such as the available spectrum bandwidth, mobile battery energy, transmission channel impairments and users’ minimum quality-of-service. In this paper, a new strategy is investigated that aims at improving the allocation of resources in a dual hop OFDMA cooperative network consisting in multi source–destination pairs and multiple decode-and-forward relays. First, the joint optimization of three types of resources: power, sub-channel and relay nodes, is formulated as a problem of subchannel-relay assignment and power allocation, with the objective of minimizing overall transmission power under the bit-error-rate and data rate constraints. However, the optimal solution to the optimization problem is computationally complex to obtain and may be unfair. Assuming knowledge of the instantaneous channel gains for all links in the entire network, an iterative three-step resource allocation algorithm with low complexity is proposed. In order to guarantee the fairness of users, several fairness criteria are also proposed to provide attractive trade-offs between network performance (i.e. overall transmission power, average network lifetime and average outage probability) and fairness to all users. Numerical studies are conducted to evaluate the performance of the proposed algorithm in two practical scenarios. Simulation results show that the proposed allocation algorithm achieves an efficient trade-off between network performance and fairness among users.     

Resource allocation for multiuser two-way OFDMA relay networks with user rate constraints

This paper studies the resource allocation for a multi-user two-way amplify-and-forward (AF) relay network over orthogonal frequency-division multiplexing (OFDM) technology,where all users communicate with their pre-assigned partners.Using convex optimization techniques,an optimal solution tominimize the total transmit power while satisfy each user-pair’s data rate requirements is proposed.We divide the resource allocation problem into two subproblems:(1) power optimization within user-pair and relay in each subcarrier.(2) optimal subcarrier allocation and sum power assignment among N parallel OFDM subcarriers.Closed-form expressions of the power among user-pair and relay can be obtained in subproblem (1),and so the proposed algorithm decreases the variable dimensionality of the objective function to reduce the complexity of this optimization problem.To solve it,a three-step suboptimal approach is proposed to assign the resources to user-pairs:Firstly,decompose each user-pair into two sub user-pairs which have one-way and two-way relaying transmission modes.Secondly,allocate the subcarriers to the new mode user-pairs and assign the transmit power to each carrier.Thirdly,distribute the assigned power to three nodes allocated in the subcarrier.Simulation results demonstrate the significant power is saved with the proposed solutions,as compared to a fixed subcarrier allocation.     

Adaptive subcarrier and bit allocation in OFDMA systems supporting heterogeneous services

Orthogonal Frequency Division Multiple Access (OFDMA) is an efficient multiple access method for the future wireless systems. This paper studies the adaptive subcarrier and bit allocation problem in OFDMA systems to support heterogeneous services. The goal of the considered resource optimization technique is to maximize the total system throughput under the overall transmit power constraint while guaranteeing the QoS requirement of realtime users and supporting proportional fairness among non-realtime users. First, we introduce a Rate Adaptive (RA) resource allocation algorithm for non-realtime users and a Margin Adaptive (MA) algorithm for realtime users. Then, based on the previous algorithms, a novel algorithm is proposed to allocate the resource to both classes of users, which makes an efficient tradeoff between the resource usage of realtime users and non-realtime users. The algorithm is locally optimal solution provided that the MA and RA algorithms are utilized. Also, to reduce the computational complexity, a suboptimal method based on the balancing of the average power per subcarrier is also introduced. Monte Carlo simulation results show that all the proposed algorithms outperform the existing counterparts. The results also show that the suboptimal method for heterogeneous services can efficiently reduce the computational complexity at the cost of very little performance degradation. This work was supported by the National Natural Science Foundation of China (Nos. 60472079, 60572115), and by the Natural Science Foundation of Zhejiang Province (No. Z104252), China.     

Coalition-based downlink resource allocation for LTE system with divide-and-conquer approach

To take advantage of the multiuser diversity resulted from the variation in channel conditions among the users,it has become an interesting and challenging problem to efficiently allocate the resources such as subcarriers,bits,and power.Most of current research concentrates on solving the resource-allocation problem for all users together in a centralized way,which brings about high computational complexity and makes it impractical for real system.Therefore,a coalitional game framework for downlink multi-user resource allocation in long term evolution(LTE) system is proposed,based on the divide-and-conquer idea.The goal is to maximize the overall system data rate under the constraints of each user’s minimal rate requirement and maximal transmit power of base station while considering the fairness among users.In this framework,a coalitional formation algorithm is proposed to achieve optimal coalition formation and a two-user bargaining algorithm is designed to bargain channel assignment between two users.The total computational complexity is greatly reduced in comparison with conventional methods.The simulation results show that the proposed algorithms acquire a good tradeoff between the overall system throughout and fairness,compared to maximal rate and max-min schemes.     

异构无线网络干扰效率最大顽健资源分配算法

针对能效提升、宏用户干扰减小的问题,该文研究了基于干扰效率最大的异构无线网络顽健资源分配算法.首先,考虑宏用户干扰约束、微蜂窝用户速率需求约束和最大发射功率约束,将资源优化问题建模为多变量非线性规划问题.其次,考虑有界信道不确定性模型,利用Dinkelbach辅助变量方法和连续凸近似方法结合对数变换方法,将原分式规划顽健资源分配问题转换为等价的确定性凸优化问题,并利用拉格朗日对偶算法获得解析解.理论分析了计算复杂度和参数不确定性对性能的影响.仿真结果表明该算法具有较好的干扰效率和鲁棒性.     

Discrete bit loading and power allocation for OFDMA downlink with minimum rate guarantee for users

Performance optimization of the communication networks with quality of service (QoS) considerations for all active users is of great practical importance in highly delay-sensitive applications like multipoint videoconferences and interactive video games. Using minimum data rate as the primary criterion for the QoS and the BER as a second one, in this paper, we provide the optimum discrete bit loading for an OFDMA downlink in which the QoS of all users are satisfied. We formulate the problem and solve the dual problem efficiently and without any suboptimality. Albeit the problem is non-convex, it has been shown that the duality gap tends zero in practical scenarios. We propose a novel approach to solve the dual problem by decomposing dual function and finding discrete rate allocation solution for practical applications. Also, we present a novel fast converging iterative algorithm to find the solution with much less complexity compared to that of well-known ellipsoid optimization algorithm. We analyze the complexity of these solutions, and using simulation results, show the superiority of our novel approach.     

Joint Spectrum Allocation and Relay Selection in Cellular Cognitive Radio Networks

Cognitive Radio Network (CRN) has been proposed in recent years to solve the spectrum scarcity problem by exploiting the existence of spectrum holes. One of the important issues in the cellular CRNs is how to efficiently allocate primary user (PU) spectrum inside a CRN cell without causing harmful interference to PUs. In this paper, we present a cross-layer framework which jointly considers spectrum allocation and relay selection with the objective of maximizing the minimum traffic demand of secondary users (SUs) in a CRN cell. Specifically, we consider (1) CRN tries to utilize PU spectrum even when the CRN cell is not completely outside the protection region of the PU cell, and (2) cooperative relay is used in cellular CRNs to improve the utilization of PU spectrum. We formulate this cross-layer design problem as a Mixed Integer Linear Programming (MILP) and propose a low complexity heuristic algorithm to solve it. Compared to a simple channel allocation scheme, the numerical results show a significant improvement by using our proposed method and the performance is close to the optimal solution. We further consider the spectrum allocation among several CRN cells with the objective of maximizing the overall minimum throughput of all cells while ensuring each individual cell’s minimum throughput requirement. A low complexity algorithm is proposed to achieve the objective with satisfactory performance.     

多无人机辅助通信中用户匹配与频谱资源联合优化方法

针对多无人机作为空中基站为地面设备提供临时服务的动态频谱分配问题，主要考虑无人机与地面用户匹配、子信道分配和功率分配三个方面。为了保证用户通信的公平性，在考虑频谱复用和共信道干扰的情况下，以最大化地面用户最小传输速率为目标，提出了一种用户匹配与频谱资源联合优化算法来解决上述混合整数非线性优化问题，通过聚类算法优化无人机与地面用户的最佳匹配，通过块坐标下降法迭代优化子信道分配和功率分配。仿真实验分析表明，提出的求解方法可以有效提升用户的传输速率，保证用户通信公平性。     

认知无线电网络中基于协作中继的资源分配算法

在认知无线电网络的协作中继机制下,中继节点利用其和源节点以及目的节点的不同公共信道为二者的通信转发数据,可以有效解决次用户的通信需求和可用带宽之间的矛盾,提高频谱利用率和系统吞吐量。基于协作中继的认知无线电网络中,不同通信链路上可能存在公共可用信道,使信道和中继的分配问题变得复杂。本文研究了公共信道存在的情况下系统的资源分配问题,基于网络最大流理论提出了两种算法:并行算法和贪婪算法,并分析了算法复杂度。仿真结果表明,两种算法都能够更有效地分配资源,提高频谱利用率,改善网络吞吐量。并行算法可以得到最优解,但其复杂度随信道公用程度的上升增长迅速,受节点并行处理能力的限制,只适用于信道公用程度较低的情况。贪婪算法不一定能得到最优解,但其复杂度较低,并且信道公用程度高时接近最优解,因此超出节点的并行处理能力后,可以选择贪婪算法。      

Downlink user selection and resource allocation for semi-elastic flows in an OFDM cell

We are concerned with user selection and resource allocation in wireless networks for semi-elastic applications such as video conferencing. While many packet scheduling algorithms have been proposed for elastic applications, and many user selection algorithms have been proposed for inelastic applications, little is known about optimal user selection and resource allocation for semi-elastic applications in wireless networks. We consider user selection and allocation of downlink transmission power and subcarriers in an orthogonal frequency division multiplexing cellular system. We pose a utility maximization problem, but find that direct solution is computationally intractable. We first propose a method that makes joint decisions about user selection and resource allocation by transforming the utility function into a concave function so that convex optimization techniques can be used, resulting in a complexity polynomial in the number of users with a bounded duality gap. This method can be implemented if the network communicates a shadow price for power to power allocation modules, which in turn communicate shadow prices for rate to individual users. We then propose a method that makes separate decisions about user selection and resource allocation, resulting in a complexity linear in the number of users.     

NOMA增强型D2D通信的资源分配算法

传统蜂窝网络中,多址接入技术起着尤为关键的作用,与正交多址（Orthogonal Multiple Access,OMA）技术相比,非正交多址（Non-Orthogonal Multiple Access,NOMA）能够支持的用户数量远远超过可用正交资源的数量,可以达到更高的频谱效率和用户公平性。因此,为提高异构蜂窝网络的整体容量,本文研究了NOMA增强型设备到设备（Device to Device,D2D）的资源分配问题,并将其分解为两个独立的子问题:信道分配和功率控制。一方面,基于Coalition博弈为D2D组分配合适的信道;另一方面,对D2D发送功率和功率分配因子依据可行解域进行联合优化,以最大化整个网络中D2D可实现速率。仿真结果表明所提算法在保证系统性能的同时,还可以有效降低计算复杂度。      

改进的多用户OFDM系统子载波和比特分配算法

针对多用户正交频分复用（OFDM）系统资源分配问题,提出了一种改进的基于边缘自适应（MA）准则的子载波和比特分配算法。在采用比例公平准则为每个用户分配子载波集合基础上,以用户速率最大者-最小者（Max-Min）子载波交换为原则进行子载波调整,使用户功率递减同时兼顾用户的公平性;通过对信道状态信息进行判断,利用贪婪算法将用户子载波分配的比特取整,以实现系统功率最小化。实验结果表明,本文提出的改进次优算法的计算复杂度较传统分步算法稍高,但仍远低于最优算法,其系统性能得以提升,且接近最优算法。     

Resource allocation with proportional rate fairness in orthogonal frequency division multiple access relay networks

We address the problem of subchannel and transmission power allocation in orthogonal frequency division multiple access relay networks with an aim to maximize the sum rate and maintain proportional rate fairness among users. Because the formulated problem is a mixed‐integer nonlinear optimization problem with an extremely high computational complexity, we propose a low‐complexity suboptimal algorithm, which is a two‐step separated subchannel and power allocation algorithm. In the first step, subchannels are allocated to each user, whereas in the second step, the optimal power allocation is carried out on the basis of the given subchannel allocation and the nonlinear interval Gauss–Seidel method. Simulation results have demonstrated that the proposed algorithm can achieve a good trade‐off between the efficiency and the fairness compared with two other existing relevant algorithms. In particular, the proposed algorithm can always achieve 100% fairness under various conditions. Copyright © 2012 John Wiley & Sons, Ltd.