分层异构网络中基于斯坦克尔伯格博弈的资源分配算法

分层异构网络中家庭基站与宏基站之间往往存在干扰,如何分配资源以获得高谱率和高容量、保证用户性能一直是研究的重点。为了解决这个问题,本文提出了一种异构蜂窝网络中基于斯坦克尔伯格博弈的家庭基站与宏基站联合资源分配算法,算法首先基于图论的分簇算法对家庭基站和宏用户进行分簇和信道分配,以减少家庭基站之间的同层干扰和家庭基站层与宏蜂窝网络的跨层干扰;然后建立了联合家庭基站发射功率以及宏用户接入选择的斯坦克尔伯格博弈,推导出达到纳什均衡时的家庭基站发射功率的表达式,并据此为宏用户选择合适的接入策略。仿真结果表明,该算法能够有效地提高宏用户的信干噪比（SINR）,家庭用户的性能也得到改善。      

A preset threshold based cross-tier handover algorithm for uplink co-channel interference mitigation in two-tier femtocell networks

This paper considers the co-channel interference mitigation problem and proposes a preset threshold based cross-tier handover algorithm for uplink co-channel interference mitigation in two-tier femtocell networks. The proposed cross-tier handover algorithm introduces a preset threshold cross-tier handover policy, which takes into account both the time-to-stay (TTS) of a macrocell user equipment (MUE)/femtocell user equipment (FUE) in a femtocell/the macrocell, and the received signal to interference plus noise ratio (SINR) at a femtocell access point (FAP)/the macrocell base station (MBS) in making a cross-tier handover decision for an MUE/FUE. A cross-tier handover decision is made by comparing the TTS of an MUE/FUE in a femtocells/the macrocell and the SINR at a FAP/the MBS with a preset TTS threshold and different SINR thresholds. The objective of the preset threshold based cross-tier handover algorithm is to increase the received SINR at the MBS/FAPs and thus improve the network performance. The performance of the proposed cross-tier handover algorithm with the minimum power transmission and the optimal power transmission is analyzed, respectively. Numerical results show that the proposed preset threshold based cross-tier handover algorithm can significantly improve the network performance in terms of the outage probability, user sum rate, and network capacity.     

Clustering-based interference management in densely deployed femtocell networks

Deploying femtocells underlaying macrocells is a promising way to improve the capacity and enhance the coverage of a cellular system. However, densely deployed femtocells in urban area also give rise to intra-tier interference and cross-tier issue that should be addressed properly in order to acquire the expected performance gain. In this paper, we propose an interference management scheme based on joint clustering and resource allocation for two-tier Orthogonal Frequency Division Multiplexing (OFDM)-based femtocell networks. We formulate an optimization task with the objective of maximizing the sum throughput of the femtocell users (FUs) under the consideration of intra-tier interference mitigation, while controlling the interference to the macrocell user (MU) under its bearable threshold. The formulation problem is addressed by a two-stage procedure: femtocells clustering and resource allocation. First, disjoint femtocell clusters with dynamic sizes and numbers are generated to minimize intra-tier interference. Then each cluster is taken as a resource allocation unit to share all subchannels, followed by a fast algorithm to distribute power among these subchannels. Simulation results show that our proposed schemes can improve the throughput of the FUs with acceptable complexity.     

认知型飞蜂窝网络中的子信道分配与功率控制

为了解决宏蜂窝与飞蜂窝构成的两层异构网络上行干扰与资源分配问题,提出了一种在认知型飞蜂窝的双层异构网中结合子信道分配和功率控制进行资源分配的框架。通过对异构网中跨层干扰问题进行分析与建模,将求解最优子信道分配矩阵和用户发射功率矩阵作为干扰管理问题的解决方法。模型中认知型飞蜂窝网络子信道和飞蜂窝网络用户构成非合作博弈,双方利用效用函数最优值进行匹配,构成初始信道分配矩阵;再由接入控制器根据接入条件从初始信道分配矩阵中筛选用户,并优化接入用户的发射功率矩阵,得到最优子信道分配矩阵和功率矩阵。仿真结果表明,优化框架提高了双层异构网络中飞蜂窝网络用户的吞吐量和接入率,降低了异构网中跨层干扰。     

Interference Management and Six-Sector Macrocells for Performance Improvement in Femto–Macro Cellular Networks

Femtocells are considered as a solution for indoor high data rate demands. Interference mitigation is a fundamental challenge in two-tier femto–macrocell networks. In this paper, we consider six-sector macrocell layout for reducing the co-tier interference in the macrocell network and cross-tier interferences from macrocell to femtocell network. As interference reduces, the whole of available spectrum can be used in each macrocell which increases the spectrum efficiency. We also consider interference-level algorithm to allocate resource for femtocell in which macrocell uses the whole of spectrum. In the coverage area of each sector, femtocell uses a portion of the spectrum that is not used by the macrocell users. This approach ignores the high co-channel interference from the macrocell network to the femtocell network and vice versa in each sector. Simulation results show that the proposed layout and interference management scheme reduce the downlink interference and increase the efficiency of the orthogonal frequency division multiple access (OFDMA)-based femtocell and macrocell. Consequently, system throughput and outage probability are improved significantly.     

Fairness Guaranteed Cooperative Resource Allocation in Femtocell Networks

User-deployed low-power femtocell access points (FAPs) can provide better indoor coverage and higher data rates than conventional cellular networks. However, a major problem in this uncoordinated frequency reuse scenario is the inter-cell interference. In this paper, we propose a graph based distributed algorithm called fairness guaranteed cooperative resource allocation (FGCRA) to manage interference among femtocells. Since the optimal resource allocation is a NP-hard problem, which is difficult to get global optimization in femtocell networks, our proposed FGCRA algorithm provides sub-optimal resource allocation via cooperation among interfering neighbors. First, we propose a specific fairness factor obtained from two-hop interference relations, to determine the lower bound amount of subchannels that each FAP can use and guarantee the fairness among femtocells. Second, we propose scalable rules for distributed resource allocation and the solution to avoid the conflicts among interfering neighbors. Simulation results show that our proposed FGCRA significantly enhances both average user throughput and cell edge user throughput, and provides better fairness.     

Managing Femto to Macro Interference without X2 Interface Support through POMDP

We present a self-organized downlink power control for interference management when Home eNodeBs (HeNBs) work in co-channel operation with the macrocell system. The main novelty with regards to previous works is that we provide a completely autonomous framework, considering 3GPP release?11 hypothesis of non availability of X2 interface between evolved NodeBs (eNBs) and HeNBs. In this situation, the HeNB has to make autonomous decisions without receiving any feedback from the macro network. We model the HeNBs as a multiagent system where each node is an independent agent able to learn through Reinforcement Learning (RL) techniques a downlink power allocation policy for different interference situations. To deal with the lack of information in the scenario, we rely on the theory of Partially Observable Markov Decision Process (POMDP). POMDP works on the basis of a set of beliefs that the HeNB builds considering the impact it causes to the macrocell system. To gather this system performance information, we propose that HeNBs use spatial interpolation techniques, such as ordinary Kriging. Results show that the proposed approach allows HeNBs to autonomously learn a power allocation policy to coexist with the macro network, in a 3GPP compliant fashion, and without introducing overhead signaling in the system.     

Distributed Resource Allocation in Two‐Hierarchy Networks

In this paper, a new distributed resource allocation algorithm is proposed to alleviate the cross‐tier interference for orthogonal frequency division multiplexing access macrocell and femtocell overlay. Specifically, the resource allocation problem is modeled as a non‐cooperative game. Based on game theory, we propose an iterative algorithm between subchannel and power allocation called distributed resource allocation which requires no coordination among the two‐hierarchy networks. Finally, a macrocell link quality protection process is proposed to guarantee the macrocell UE's quality of service to avoid severe cross‐tier interference from femtocells. Simulation results show that the proposed algorithm can achieve remarkable performance gains as compared to the pure waterfilling algorithm.     

OFDMA毫微微小区双层网络中基于分组的资源分配

毫微微小区(Femtocell)网络能够增强室内覆盖,提高系统容量,但是在频谱共享的正交频分多址(OFDMA)毫微微小区网络中,毫微微小区之间的同层干扰以及毫微微小区与宏小区(Macrocell)之间的跨层干扰严重限制了系统的性能。针对这两种干扰,该文提出一种基于分组的资源分配算法。该算法包括两部分：一部分是宏基站先利用改进的匈牙利算法为宏小区用户分配信道,再用注水算法分配功率,保证宏小区用户的正常传输;另一部分是在避免干扰宏小区用户的基础上,先采用模拟退火算法对毫微微小区进行分组,再进行信道和功率分配,满足毫微微小区用户的数据速率需求,最大化频谱效率。仿真结果表明,该算法有效地抑制了这两种干扰,既能保证用户的数据速率需求,又能有效提升网络频谱效率。     

一种femto-macro异构网络多业务资源公平管理算法

摘要：针对毫微微蜂窝（femtocell）网络中多种业务（固定速率业务和可变速率业务）环境下如何公平分配毫微微蜂窝基站（femtocell base station, FBS）资源的问题,提出了一种基于比例公平算法的femto-macro异构网络资源分配算法。该算法以基于比例公平法则的可变速率用户的吞吐量为优化目标,并以每个用户的服务质量（quality of service, QoS）、FBS的下行传输总功率和宏蜂窝（macrocell）用户的跨层同频干扰门限值为约束组成优化问题。在上述资源分配最优化问题为凸优化问题的基础上,采用对偶分解算法进行求解。仿真结果表明,提出的算法在保证不同用户 QoS 的同时,不仅能够有效地公平分配资源给可变速率用户,而且降低了macrocell用户受到来自FBS的跨层同频干扰。     

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.     

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.     

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.     

Terminal density dependent resource management in cognitive heterogeneous networks

In cognitive heterogeneous network, when multitudes of femtocells coexist, effective resource management become important to enhance network performance. Based on the base station location and terminal distribution density, we propose spectrum management and power configuration scheme for femtocells deployment network. In the beginning, we consider two femtocells adjacent network and propose the resource management scheme. The scheme allocates time frequency resource by adopting complete reusing and private usage in non-overlapping and overlapping areas respectively. Subsequently the scheme optimizes base station power under the constraints of cross-tier interference and maximal transmission power to maximize network capacity. According to the analysis of the power variation effect to femtocell coverage, a near-optimal solution of the transmission power is derived, and the corresponding power configuration scheme is proposed. After then we extend the spectrum and power management to multiple femtocells coexisting networks, and propose the management scheme applied for multiple femtocells deployment networks. The simulation results indicate that in capacity performance, the proposed power solution is close to the optimal solution, and the proposed resource management outperforms the existing schemes.     

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。     

同频异构femtocell联合子信道和功率分配算法

摘要：针对macro-femto同频融合网络中基于资源分配的干扰抑制问题,提出一种联合子信道和功率分配算法来抑制同频干扰。该算法通过对MU进行功率控制并采用跨层切换消除同频跨层干扰,对FU进行联合信道和功率分配消除同频层内干扰;跨层切换问题是在每一层网络目标中断概率约束下通过优化网络吞吐量实现,而基于联合信道和功率分配的同频干扰抑制问题是在切换MU的目标数据速率和其他MU以及FU干扰门限约束下,通过优化FU的和速率实现。理论分析和仿真结果表明,该算法能够提高FU的和速率,增大femtocell的网络容量,并可增加femtocell的部署数目。     

Power Control Based on Maximum Power Adaptation in Two-Tier Femtocell Networks

In recent years, femtocells are receiving considerable attention in mobile communication as a cost-effective means of improving indoor coverage and capacity. A significant technical challenge in the deployment of a large number of femtocells is the management of interference from the underlay of femtocells onto the overlay of macrocell. In this paper, a reasonable and effective interference suppression scheme based on the adaptive adjustment of femtocell users’ maximum transmission power is proposed. The highlight of the scheme is the joint design of macrocell users’ uplink communication protection and femtocell users’ optimal power allocation. The scheme restricts the cross-tier interference at macrocell base station below a given threshold and ensures the optimization of femtocell users’ power allocation at each adjustment phase. Last, admission control is also considered, aiming to exploit the network resources more effectively. Simulation results show the superiority of the proposed scheme over the scheme based on the Signal-to-Interference-Plus-Noise Ratio adaptation. We also give some reference on utility function selection by setting different coefficients in the utility function, and show the effectiveness of admission control in both fixed and random network topologies.     

Handling interference in self-organizing femtocell networks through frequency-polarization diversity

The next generation heterogeneous networks are expected to offer higher data-rate and better QoS to the customers by leveraging smaller cells like femtocells and making use of orthogonal frequency division multiple access. However, uncoordinated dense deployment of femtocells in macrocell network pose unique challenges involving cross-tier interference and resource management which results in significant degradation of the system performance. As part of addressing these challenges for the successful integration of both technologies, this paper proposes the deployment of a self-organizing femtocell network that employs an opportunistic smart frequency reuse technique –cross polarized complementary frequency allocation (CPCFA). It exploits the frequency and polarization diversity to mitigate interference in two-tier femto-macro networks. In this work, a strategy combining the adoption of reverse frequency allocation and orthogonal polarized transmission is analyzed as a potential solution for maximizing spectral efficiency and minimizing interference in the existing heterogeneous networks. Focus of the current work is on downlink transmission where the traffic is high and the deployment of femtocell is more beneficial. The results of analytic and simulation studies prove that CPCFA increases the scope for an easily implementable, remarkable opportunity in the context of two-tier femto-macro network that can substantially increase the system capacity as well as cell coverage without additional network complexities.     

Interference Mitigation Using Uplink Power Control for Two-Tier Femtocell Networks

This paper proposes two interference mitigation strategies that adjust the maximum transmit power of femtocell users to suppress the cross-tier interference at a macrocell base station (BS). The open-loop and the closed-loop control suppress the cross-tier interference less than a fixed threshold and an adaptive threshold based on the noise and interference (NI) level at the macrocell BS, respectively. Simulation results show that both schemes effectively compensate the uplink throughput degradation of the macrocell BS due to the cross-tier interference and that the closed-loop control provides better femtocell throughput than the open-loop control at a minimal cost of macrocell throughput.     

Dense femtocell networks power self‐optimization: an exact potential game approach

Femtocell is regarded as a promising technology to enhance indoor coverage and improve network capacity. However, highly dense and self‐organized femtocells in urban environment will result in serious inter‐femtocell interference. To solve this problem, this paper proposes a distributed power self‐optimization scheme for the downlink operation of dense femtocell networks. First, a novel convex pricing mechanism is presented to price the transmit power of femtocells and construct the utility function of femtocells. Then, a noncooperative game framework for power self‐optimization of femtocells in dense femtocell networks is established on the basis of the exact potential game theory, which is demonstrated to converge to a pure and unique Nash equilibrium. Finally, combined with firefly algorithm, an effective power self‐optimization algorithm with guaranteed convergence is proposed to achieve the Nash equilibrium of the proposed game. With practical LTE parameters and a 3GPP dual‐strip femtocell model, simulation results show that the proposed game with convex pricing mechanism increases the femtocell network throughput by 7% and reduces the average transmit power of femtocells by 50% in dense femtocell networks, with respect to the compared schemes. Copyright © 2014 John Wiley & Sons, Ltd.