基于先进小区干扰协调技术的异构网络联合资源分配

高发射功率的宏基站与低发射功率的小基站之间的资源分配策略直接影响着异构蜂窝网络的性能。这是一个联合资源优化问题,即用户的基站接入选择、宏基站预留给小基站的资源数量和基站的调度策略。针对这一问题,利用块并列下降方法,提出了一组新颖的资源优化算法。所提出的解决方案能分布式实现,并兼容先进长期演进技术( LTE-A )协议中的先进小区间干扰协调技术( eICIC)。大量的动态系统级仿真结果表明系统性能和用户间公平性都得到了显著提升。     

异构网络中小区间联合干扰协调算法研究

研究了如何在LTE-Advanced系统异构网络中通过有效的增强型小区间干扰协调提高系统总吞吐量问题。通过分析网络中存在的干扰,建立数学模型,提出了一种基于减少发射功率几乎空白子帧的小区间联合干扰协调算法,利用优化方法研究系统总吞吐量和减少发射功率几乎空白子帧之间的关系,实现了最大化系统吞吐量,同时解决宏基站分配多少资源给微微小区,以及用户的接入选择问题。仿真结果表明,所提方法和对比方法相比,系统总吞吐量有19.8%提升,可以达到算法上限的97.4%,适用于对系统总吞吐量要求较高,而边缘用户性能要求较低的场景。     

Semi‐distributed dynamic inter‐cell interference coordination scheme for interference avoidance in heterogeneous networks

Inter‐cell interference (ICI) is a major problem in heterogeneous networks, such as two‐tier femtocell (FC) networks, because it leads to poor cell‐edge throughput and system capacity. Dynamic ICI coordination (ICIC) schemes, which do not require prior frequency planning, must be employed for interference avoidance in such networks. In contrast to existing dynamic ICIC schemes that focus on homogeneous network scenarios, we propose a novel semi‐distributed dynamic ICIC scheme to mitigate interference in heterogeneous network scenarios. With the goal of maximizing the utility of individual users, two separate algorithms, namely the FC base station (FBS)‐level algorithm and FC management system (FMS)‐level algorithm, are employed to restrict resource usage by dominant interference‐creating cells. The distributed functionality of the FBS‐level algorithm and low computational complexity of the FMS‐level algorithm are the main advantages of the proposed scheme. Simulation results demonstrate improvement in cell‐edge performance with no impact on system capacity or user fairness, which confirms the effectiveness of the proposed scheme compared to static and semi‐static ICIC schemes.     

End-to-end utility-based resource allocation for multi-RAT nodes in heterogeneous cognitive wireless networks

This paper studies the problem of effective resource allocation for multi-radio access technologies (Multi-RAT) nodes in heterogeneous cognitive wireless networks (HCWNs). End-to-end utility, which is defined as the delay of end-to-end communication, is taken into account in this paper. In the scenario of HCWNs, it is assumed that the cognitive radio nodes have the ability of Multi-RAT and can communicate with each other through different paths simultaneously by splitting the arrival packets. In this paper, the problem is formulated as the optimization of split ratio and power allocation of the source cognitive radio node to minimize the delay of end-to-end communication, and a low complexity step-by-step iterative algorithm is proposed. Numerical results show good performance of the proposed algorithm over two other conventional algorithms.     

Dynamic spectrum allocation in heterogeneous wireless networks under interference constraints across the cell coverage

In order to improve spectrum utilization, dynamic spectrum allocation (DSA) schemes with interference management have been widely investigated, and a special interest is in the current heterogeneous wireless network (HWN) environment. In the previous work, the approach that guarantees quality of service for the cell‐boundary user is extensively used in the DSA scheme. However, such approach gives a pessimistic result. In this paper, we design a DSA scheme for the HWN system, which adopts relatively accurate interference constraints. First, considering that users may randomly locate over the cell, we propose interference constraints across the cell coverage, in which the interference experienced at a point is controlled below the level suffered when using fixed spectrum allocation in only a single network, and the proportion of the cell area where interference is controlled reaches the required area coverage probability. Then under the interference constraints, we formulate the downlink DSA scheme as a combinatorial optimization problem. As the problem is NP‐hard, to reduce the computational complexity, we propose two greedy heuristic algorithms for its solution. Simulation results show that the DSA scheme could improve the total spectrum utility for operators and increase the satisfaction rate of spectrum demands for base stations. Copyright © 2013 John Wiley & Sons, Ltd.     

Joint resource allocation with QoS provisioning in K-tier heterogeneous cellular networks

In this paper, the joint resource allocation （RA） problem with quality of service （QoS） provisioning in downlink heterogeneous cellular networks （HCN） is studied. To fully exploit the network capacity, the HCN is modeled as a K-tier cellular network where each tier＇s base stations （BSs） have different properties. However, deploying numbers of low power nodes （LPNs） which share the same frequency band with macrocell generates severe inter-cell interference. Enhancement of system capacity is restricted for inter-cell interference. Therefore, a feasible RA scheme has to be developed to fully exploit the resource efficiency. Under the constraint of inter-cell interference, we formulate the RA problem as a mixed integer programming problem. To solve the optimization problem we develop a two-stage solution. An integer subchannel assignment algorithm and Lagrangian-based power allocation algorithm are designed. In addition, the biasing factor is also considered and the caused influence on system capacity is evaluated. Simulation results show that the proposed algorithms achieve a good tradeoff between network capacity and interference. Moreover, the average network efficiency is highly improved and the outage probability is also decreased.     

双层无线异构网络下行干扰抑制方法研究

针对引入家庭基站技术的双层无线异构网络中存在严重的跨层和同层干扰的问题,提出了一种基于伪随机子信道选择的干扰抑制方案。该方案首先通过干扰随机化抑制跨层干扰,然后利用干扰图计算最大可选择伪随机序列个数抑制同层干扰。通过对比传统干扰抑制方案,验证了该方案能更有效地抑制系统干扰,提高系统吞吐量。     

基于用户中断概率的D2D通信干扰协调与资源分配

在LTE系统中引入设备直传(D2D)通信技术,会因为D2D用户复用蜂窝用户资源进行通信而产生同频干扰.在现有的干扰协调与资源分配研究中,都需要基站获取各个通信链路的信道状态信息(CSI),但这样无疑会增加基站的信令负担.为减小干扰与基站的信令负担,提出了一种基于用户中断概率的干扰协调与资源分配算法,首先在保证蜂窝用户正常通信的情况下,通过限制D2D用户到基站间的距离来降低干扰;其次通过遍历所有蜂窝用户的频谱资源,选择能使D2D用户的总中断概率最低的频谱资源进行复用.仿真结果表明,所提算法能够在保证蜂窝用户正常通信的情况下,明显降低D2D用户的平均中断概率,同时还能够降低基站信令负担.     

Stackelberg game for backhaul resource allocation in the two-tier LTE femtocell networks

As one promising technology for indoor coverage and service offloading from the conventional cellular networks, femtocells have attracted considerable attention in recent years. However, most of previous work are focused on resource allocation during the access period, and the backhaul involved resource allocation is seriously ignored. The authors studied the backhaul resource allocation in the wireless backhaul based two-tier heterogeneous networks （HetNets）, in which cross-tier interference control during access period is jointly considered. Assuming that the macrocell base station （MBS） protects itself from interference by pricing the backhaul spectrum allocated to femtocells, a Stackelberg game is formulated to work on the joint utility maximization of the macrocell and femtocells subject to a maximum interference tolerance at the MBS. The closed-form expressions of the optimal strategies are obtained to characterize the Stackelberg equilibriums for the proposed games, and a backhaul spectrum payment selection algorithm with guaranteed convergence is proposed to implement the backhaul resource allocation for femtocell base stations （FBSs）. Simulations are presented to demonstrate the Stackelberg equilibrium （SE） is obtained by the proposed algorithm and the proposed scheme is effective in backhaul resource allocation and macrocell protection in the spectrum-sharing HetNets.     

Radio resource allocation for interference management in mobile broadband OFDMA based networks

This paper focuses on the inter‐cell interference (ICI) management problem in the downlink channel for mobile broadband wireless OFDMA‐based systems. This subject is addressed from the standpoint of different interrelated resource allocation mechanisms operating in multi‐cell scenarios in order to exploit frequency and multi‐user diversity: ICI coordination/avoidance and adaptive subcarrier and power allocation. Even though these methods can be applied in a stand‐alone way, a significant performance improvement is achieved if they are jointly designed and operate in a combined basis. Several alternatives for mixed frequency and power ICI coordination schemes are proposed in this paper. Connected with a proper power mask‐based design, the potential gain of a flexible frequency sectorization solution, halfway between fractional/soft frequency reuse and pure frequency sectorization, is explored. The main objective is to outperform fractional/soft frequency reuse offering an attractive trade‐off between cell‐edge user data rates and average cell throughput. Proposals concerning ICI coordination/avoidance have been evaluated in combination with several heuristic adaptive subcarrier and power allocation algorithms. Copyright © 2009 John Wiley & Sons, Ltd.     

Optimal resource allocation for heterogeneous traffic in multipath networks

Multipath networks allow each source to send packets from it to its destination over multiple paths, which increases the available bandwidth and throughput for source‐destination pairs. Recently, a variety of flow control schemes have been presented for multipath networks to achieve optimal resource allocation. Unfortunately, much of the investigation focused on elastic traffic with controllable packet injection rates. Networks have witnessed an increase in real‐time traffic (voice and video), which are inelastic. We consider resource allocation for heterogeneous traffic in multipath networks and formulate an optimization problem, which is intrinsically difficult nonconvex. In order to address the aforementioned issue and obtain the optimum, we approximate an equivalent problem of the original optimization problem to a strictly convex problem and present a primal‐dual resource allocation algorithm for the approximation problem, which converges to an optimal solution satisfying the Karush‐Kuhn‐Tucker conditions of the original problem. We evaluate its convergence performance through theoretical analysis and illustrate it with numerical examples. Copyright © 2014 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.     

基于深度学习的异构资源分配算法研究

资源分配是目前云计算领域中一个重要的研究方向。在异构云计算体系结构下的复杂应用问题研究中,为了满足异构资源分配的需求,提升资源利用效率,文中提出了一种基于深度学习的面向应用的资源分配算法。该算法将数据特征进行量化,更加精确地刻画了不同服务器资源之间的性能差异,在分配算法中加入了一个工作负载预测模型,使给出的资源分配方案与需求更加匹配,同时提高了资源利用率。     

协作D2D异构网络的联合资源分配和功率控制

针对下行协作D2D(Device-to-Device)异构网络中复用蜂窝用户的联合资源分配和功率控制问题,提出了一种量子珊瑚礁优化算法(Quantum Coral Reef Optimization Algorithm,QCROA).首先,构建异构网络模型并推导得到整个网络总吞吐量的数学表达式;其次,基于QCROA算法...     

Radio resource allocation using genetic algorithm in heterogeneous networks

Radio resource management to enable user association and resource block (RB) allocation is crucial for enhancing the performance of heterogeneous networks (HetNets), which are required for fifth generation (5G) mobile networks. This paper proposed a resource allocation technique based on a genetic algorithm (GA) for use in HetNets. We aimed to optimize user association and RB allocation simultaneously to fulfill multiple objectives, such as throughput and fairness measure. In addition to the four primary phases used in GA process, namely initialization, crossover, mutation, and selection, a further operator was provided for managing illegal offspring generated during a GA process. We performed a simulation to compare the proposed GA‐based approach with best channel quality indicator (CQI) algorithm and integer linear programming (ILP) approach in terms of total throughput and fairness measure. The simulation results revealed that the total throughput obtained using the proposed approach is 32.7% and 37.6% better than that obtained using the ILP and best CQI approaches, respectively. Moreover, the fairness measure obtained using the proposed GA‐based approach was 31.8% and 33.2% higher than that obtained using ILP and best CQI approaches, respectively.     

认知小蜂窝网络中基于能效的下行资源分配算法

在认知小蜂窝网络框架下,对基于OFDMA技术的下行联合频谱资源块和功率分配问题进行了研究。小蜂窝基站在分布式结构下采用开放式接入方式共享空闲频谱资源以最大化其能量效率,基站间的竞争关系使系统资源的动态分配过程可建模为非合作博弈模型。由于最大化具有多个限制条件的分数形势的能量效用函数属于非凸最优问题,可通过将其转化为等价的减数形势,并从串行和并行迭代的角度进行求解。在给定资源块分配策略后,原有博弈模型可被重新建模为便于独立求解发射功率的等价子博弈模型。仿真结果表明,所提算法在干扰受限的通信环境下能收敛到纳什均衡,并有效提高了系统资源利用率和能量效率。     

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.     

Robust resource allocation for NOMA-assisted heterogeneous networks

As a promising technology to improve spectrum efficiency and transmission coverage, Heterogeneous Network (HetNet) has attracted the attention of many scholars in recent years. Additionally, with the introduction of the Non-Orthogonal Multiple Access (NOMA) technology, the NOMA-assisted HetNet cannot only improve the system capacity but also allow more users to utilize the same frequency band resource, which makes the NOMA-assisted HetNet a hot topic. However, traditional resource allocation schemes assume that base stations can exactly estimate direct link gains and cross-tier link gains, which is impractical for practical HetNets due to the impact of channel delays and random perturbation. To further improve energy utilization and system robustness, in this paper, we investigate a robust resource allocation problem to maximize the total Energy Efficiency (EE) of Small-Cell Users (SCUs) in NOMA-assisted HetNets under imperfect channel state information. By considering bounded channel uncertainties, the robust resource optimization problem is formulated as a mixed-integer and nonlinear programming problem under the constraints of the cross-tier interference power of macrocell users, the maximum transmit power of small base station, the Resource Block (RB) assignment, and the quality of service requirement of each SCU. The original problem is converted into an equivalent convex optimization problem by using Dinkelbach's method and the successive convex approximation method. A robust Dinkelbach-based iteration algorithm is designed by jointly optimizing the transmit power and the RB allocation. Simulation results verify that the proposed algorithm has better EE and robustness than the existing algorithms.     

A self‐organized resource allocation scheme for heterogeneous macro‐femto networks

This paper investigates the radio resource management (RRM) issues in a heterogeneous macro‐femto network. The objective of femto deployment is to improve coverage, capacity, and experienced quality of service of indoor users. The location and density of user‐deployed femtos is not known a‐priori. This makes interference management crucial. In particular, with co‐channel allocation (to improve resource utilization efficiency), RRM becomes involved because of both cross‐layer and co‐layer interference. In this paper, we review the resource allocation strategies available in the literature for heterogeneous macro‐femto network. Then, we propose a self‐organized resource allocation (SO‐RA) scheme for an orthogonal frequency division multiple access based macro‐femto network to mitigate co‐layer interference in the downlink transmission. We compare its performance with the existing schemes like Reuse‐1, adaptive frequency reuse (AFR), and AFR with power control (one of our proposed modification to AFR approach) in terms of 10 percentile user throughput and fairness to femto users. The performance of AFR with power control scheme matches closely with Reuse‐1, while the SO‐RA scheme achieves improved throughput and fairness performance. SO‐RA scheme ensures minimum throughput guarantee to all femto users and exhibits better performance than the existing state‐of‐the‐art resource allocation schemes.Copyright © 2014 John Wiley & Sons, Ltd.     

Joint interference coordination approach in femtocell networks for QoS performance optimization

Future heterogeneous networks with dense cell deployment may cause high intercell interference. A number of interference coordination (IC) approaches have been proposed to reduce intercell interference. For dense small‐cell deployment with high intercell interference between cells, traditional forward link IC approaches intended to improve edge user throughput for best effort traffic (ie, file transfer protocol download), may not necessarily improve quality of service performance for delay‐sensitive traffic such as voice over long‐term evolution traffic. This study proposes a dynamic, centralized joint IC approach to improve forward link performance for delay‐sensitive traffic on densely deployed enterprise‐wide long‐term evolution femtocell networks. This approach uses a 2‐level scheme: central and femtocell. At the central level, the algorithm aims to maximize network utility (the utility‐based approach) and minimize network outage (the graphic‐based approach) by partitioning the network into clusters and conducting an exhaustive search for optimized resource allocation solutions among femtocells (femto access points) within each cluster. At the femtocell level, in contrast, the algorithm uses existing static approaches, such as conventional frequency reuse (ReUse3) or soft frequency reuse (SFR) to further improve user equipment quality of service performance. This combined approach uses utility‐ and graphic‐based SFR and ReUse3 (USFR/GSFR and UReUse3/GReUse3, respectively). The cell and edge user throughput of best effort traffic and the packet loss rate of voice over long‐term evolution traffic have been characterized and compared using both the proposed and traditional IC approaches.