两层异构网络中Femtocell研究进展与展望

对femtocell研究进展进行了细致分析和探讨,着重讨论两层异构网络中频率资源分配、干扰管理和接入控制3个主要议题,同时也分析回程链路、用户移动性和公平性等其他相关问题。最后论述femtocell应用前景和归纳未来研究方向。     

Pseudo-handover based subchannel and power adaptation scheme for interference mitigation in OFDMA two-tier femtocell networks

In the two-tier femtocell network,a central macrocell is underlaid with a large number of shorter range femtocell hotspots,which is preferably in the universal frequency reuse mode.This kind of new network architecture brings about urgent challenges to the schemes of interference management and the radio resource allocation.Motivated by these challenges,three contributions are made in this paper:1) A novel joint subchannel and power allocation problem for orthogonal frequency division multiple access (OFDMA) downlink based femtocells is formulated on the premise ofminimizing radiated interference of every Femto base station.2) The pseudo-handover based scheduling information exchange method is proposed to exchange the co-tier and cross-tier information,and thus avoid the collision interference.3) An iterative scheme of power control and subchannel is proposed to solve the formulated problem in contribution 1),which is an NP-complete problem.Through simulations and comparisons with four other schemes,better performance in reducing interference and improving the spectrum efficiency is achieved by the proposed scheme.     

Stackelberg game based interference management for two-tier femtocell networks

Femtocell is viewed as a promising option for mobile operators to improve coverage and provide high-data-rate services in a cost-effective manner. This paper considers the uplink interference management problem in a spectrum-sharing femtocell network. Assuming that the macrocell base station (MBS) is rewarded for sharing the spectrum with femtocells by setting a reasonable interference cap (IC) for femtocell users’ (FUEs’) transmissions. Within IC, the FUEs allocate their transmission powers competitively while not introducing much interference to both the macrocell users (MUEs) and other FUEs. A Stackelberg game is formulated to jointly maximize the utility of MBS and the individual utility of FUEs. Specifically, the maximum tolerable interference at the MBS is used as the resource that the leader (MBS) and the followers (FUEs) compete for. Then, the backward induction method is applied to achieve the Stackelberg equilibrium and a distributed power update rule is developed for FUEs. In addition, the implementation protocol is presented, some issues related to the implementations and some future extensions regarding the MUEs’ uplink protection are discussed. Lastly, numerical results demonstrate the performance of our proposed power allocation in detail, and show the effects of varying the number of FBSs and changing other system parameters on the system’s performance.     

Stackelberg game theoretic pricing algorithm for bandwidth allocation in cooperative access

Cooperative access among user devices by sharing wireless access bandwidth opens a new paradigm in heterogeneous networks.However,how to stimulate cooperative relay nodes forwarding service data for others and allocating corresponding bandwidth to support it are two key issues in the cooperative access.This paper proposes a Stackelberg game based framework which is benefit participants including relay nodes and client nodes.This framework generalizes the pricing based bandwidth allocation algorithm by the Stackelberg game model,which optimizes the profit of the cooperative relay nodes while guaranteeing the bandwidth requirements of client nodes.We transform the profit maximization problem into a convex problem and solve it using the convex optimization method.The simulation results demonstrate that the proposed framework and corresponding algorithms outperform the bidding weight proportional fairness and fixed value bandwidth allocation ones significantly.     

Caching resource management of mobile edge network based on Stackelberg game

Mobile edge caching technology is gaining more and more attention because it can effectively improve the Quality of Experience (QoE) of users and reduce backhaul burden. This paper aims to improve the utility of mobile edge caching technology from the perspectie of caching resource management by examining a network composed of one operator, multiple users and Content Providers (CPs). The caching resource management model is constructed on the premise of fully considering the QoE of users and the servicing capability of the Base Station (BS). In order to create the best caching resource allocation scheme, the original problem is transformed into a multi-leader multi-follower Stackelberg game model through the analysis of the system model. The strategy combinations and the utility functions of players are analyzed. The existence and uniqueness of the Nash Equilibrium (NE) solution are also analyzed and proved. The optimal strategy combinations and the best responses are deduced in detail. Simulation results and analysis show that the proposed model and algorithm can achieve the optimal allocation of caching resource and improve the QoE of users.     

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.     

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.     

A Stackelberg game for resource allocation in multiuser cooperative transmission networks

In this paper, we consider the problem of stimulating cooperation and resource allocation in cooperative transmission networks. We formulate this problem as a sellers' market competition where a relay is willing to share its resource with multiple users. We use a Stackelberg game to jointly consider the benefits of the relay and the users. Firstly, the relay determines the price of relaying according to the user demand. Secondly, the users purchase the optimal amount of resources to maximize their utilities. Although the Nash equilibrium, i.e., the solution of the game, can be obtained in a centralized manner, we develop a distributed algorithm to search the Nash equilibrium, which is more applicable in practical systems. Also, the convergence conditions of the algorithm are analyzed. Simulation results show, by using the distributed algorithm, the relay and the users could determine what price should ask for and how much bandwidth should buy, respectively. Copyright © 2010 John Wiley & Sons, Ltd.     

Price‐based interference management in dense femtocell systems

Femtocell technology has been drawing considerable attention as a cost‐effective means of improving cellular coverage and capacity. However, under co‐channel deployment, femtocell system in dense environment may incur high uplink interference to existing macrocells and experiences strong inter‐cell interference at the same time. To manage the uplink interference to macrocell, as well as the inter‐cell interference, this paper proposes a price‐based uplink interference management scheme for dense femtocell systems. Specifically, on the one hand, to guarantee the macrocell users' quality of service, the macrocell base station prices the interference from femtocell users (FUEs) subject to a maximum tolerable interference power constraint. On the other hand, the inter‐cell interference is also taken into consideration. Moreover, a Stackelberg game model is adopted to jointly study the utility maximization of the macrocell base station and FUEs. Then, in order to reduce the amount of information exchange, we design a distributed power allocation algorithm for FUEs. In addition, admission control is adopted to protect the active FUEs' performance. Numerical results show that the price‐based interference management scheme is effective. Meanwhile, it is shown that the distributed power allocation combined with admission control is capable of robustly protecting the performance of all the active FUEs. Copyright © 2013 John Wiley & Sons, Ltd.     

Interference management in femtocell networks

Recently, smaller cells such as femtocells have been proposed to address the cellular coverage problem and provide a ‘greener’ solution to future high‐speed wireless access. On the other hand, interference is a serious problem that could impact the wide deployment of femtocells. The contributions of this paper are threefold. First, we focus on the trade‐off between energy efficiency and system performance. With realistic long‐term evolution system parameters, we have shown that femtocells can indeed improve energy efficiency of the network. However, this comes with a price—performance degradation due to interference, which is especially severe in densely deployed scenarios. Second, we propose a proactive approach to handover and access management in femtocell systems, focusing especially on the interference issue of closed subscriber group femtocells. Third, we propose an efficient data offloading mechanism for interference mitigation and mobility management, with the aim to avoid potential interference and save radio resources and signalling load in the network. Simulation results have been presented to demonstrate the benefits of the proposed schemes. Copyright © 2011 John Wiley & Sons, Ltd.     

Co‐tier downlink interference management in dense femtocell networks

With the adoption of long‐term evolution standard for 4G mobile communications, the deployment of femtocell base stations (FBSs) to cope with the surging traffic in mobile wireless communication is becoming increasingly popular. However, with the random installation of FBSs, the problem of interference among FBSs is still a challenge. In this paper, assuming the presence of a femtocell management system that can control and coordinate the densely deployed FBSs, a novel power backoff scheme is proposed that determines the appropriate transmit power of each FBS so that the interference is reduced. Simulation results for randomly deployed FBSs in an environment with shadowing using MATLAB are provided, showing that our proposed methods can effectively mitigate the co‐tier downlink interference while improving the system capacity in a densely deployed femtocell network with shared spectrum use. Quantitatively, the average interference is reduced by roughly 90% to 100% of dBm, and the average capacity is increased by more than 80%. These results attest to the effectiveness of the proposed scheme.     

Joint backhaul bandwidth and power allocation in heterogeneous cellular networks: A two‐level approach

We investigate the problem of joint downlink wireless backhaul bandwidth (WBB) and power allocation in heterogeneous cellular networks (HCNs). A WBB partitioning scheme is considered, which allocates the whole bandwidth between the macrocell and small cells for data transmission and backhauling. We formulate an optimization problem to maximize the weighted sum logarithmic utility function by jointly optimizing WBB portion and fronthaul power allocation of each base station with consideration of the backhaul capacity limitation on each small cell. In order to solve this joint optimization problem, we propose a hierarchical two‐level approach and decompose the original problem into two independent subproblems: the WBB allocation at the macrocell base station (MBS) and the power allocation at both the MBS and small cell base stations (SBSs). Accordingly, the optimal WBB portion and power allocation solutions are obtained, respectively. Furthermore, we develop a distributed algorithm to implement the joint WBB and power allocation. Numerical results verify the effectiveness of the proposed approach and analyze the impact of the weighted coefficient and backhaul capacity limitation on the network performance. In addition, significant performance gains can be achieved by the proposed approach over the benchmark.     

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.     

Distributed optimization of enhanced intercell interference coordination and resource allocation in heterogeneous networks

In two‐tier heterogeneous networks (HetNets), the cross‐tier interference caused by spectrum sharing between macrocell and small cells poses obstacle to ideal overall network performance. Both enhanced intercell interference coordination (eICIC) at the macrocell base station (MBS) and resource allocation (RA) at small cell base station (SBS) have been considered as efficient approaches to mitigate the cross‐tier interference. In this paper, we propose a distributed optimization framework to jointly optimize the eICIC and RA schemes at different tiers. In specific, an enhanced almost blank subframe (ABS) scheme is performed by the MBS to encourage SBSs to adopt hybrid access policy and admit the offloaded macrocell users (MUs) so as to guarantee their QoS requirements. To model the intricate interaction between two tiers, we formulate the joint optimization problem as a one‐leader multiple‐follower Stackelberg game. We prove the existence of Stackelberg equilibrium (SE) and obtain the optimal strategies for both tiers. Numerical results are presented to show that the proposed framework with hybrid access policy converges to a unique SE and utilities for both tiers is maximized, which creates a win‐win situation.     

A multi‐cell adaptive resource allocation scheme based on potential game for ICIC in LTE‐A

Intercell interference coordination in Third Generation Partnership Project long‐term evolution‐advanced system has received much attention both from the academia and the standardization communities. Moreover, the network architecture of long‐term evolution‐advanced system is modified to take into account coordinated transmission. In this article, we study the dynamic resource allocation problem and potential game theory and propose a multicell adaptive distributed resource allocation algorithm based on potential game. The allocation process is divided into two steps; subchannel is allocated first, and then, transmitted power is optimized dynamically according to a novel pricing factor. Besides, existence and uniqueness of Nash equilibrium of the proposed game model are assured. As a result, intercell interference is well coordinated. Simulation results show that transmitted power is saved efficiently and system fairness is improved to a large extent, accompanied with good performance gain of total and cell‐edge throughputs. Copyright © 2013 John Wiley & Sons, Ltd.     

无线数据网络中基于斯塔克尔博格博弈的功率控制

功率控制是无线数据网络中资源管理的关键技术。为使无线数据网络中非合作博弈功率控制算法得到帕累托改进,将斯塔克尔博格博弈引入到无线数据网络功率控制算法中,使所有系统终端都工作在最佳的等信干比下,提出一个基于斯塔克尔博格博弈的分布式功率控制算法,并进行了数值仿真。仿真结果表明,该算法明显提高了系统的性能,使系统终端具有相对较高的效用和较低的发射功率,并使得无线网络资源的使用更加合理和公平,同时算法拥有较好的收敛性。     

Optimal resource allocation scheme for cognitive radio networks with relay selection based on game theory

In this paper,we present a non-transferable utility coalition graph game(NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing(OFDMA) based cognitive radio networks to maximize both system throughput and system fairness.In this algorithm,with the assistance of others SUs,SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs.So this scheme can effectively exploit both space and frequency diversity of the system.Performance results show that,NTU-CGG significantly improves system fairness level while not reducing the throughput comparing with other existing algorithms.     

基于合作博弈的CPS通信资源分配算法

为了提高信息物理融合系统的通信速率,同时保证各用户的QoS需求,提出了一种基于合作博弈的CPS通信资源分配算法。将CPS中OFDMA网络下行链路的资源分配过程建模为多用户间的合作博弈,通过求解纳什议价解,实现用户间的Pareto最优性。仿真结果表明,该算法在系统速率最大化和用户公平性上获得了很好的折中,与最大化系统速率算法相比更具有公平性,与最大化最小公平性算法相比速率提高了34%,在一定程度上提高了CPS通信网络的性能。     

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。     

Clustering‐based low‐complexity resource allocation in two‐tier femtocell networks with QoS provisioning

In this paper, we study the resource allocation problem of the uplink transmission with delay quality‐of‐service constraints in two‐tier femtocell networks. Particularly, to provide statistical delay guarantees, the effective capacity is employed as the network performance measure instead of the conventional Shannon capacity. To make the problem computationally efficient and numerically tractable, we decompose the problem into three subproblems, namely, cluster configuration subproblem, intra‐cluster subchannel allocation subproblem and inter‐cluster power control subproblem. Firstly, we develop a low‐complexity heuristic semi‐dynamic clustering scheme, where the delay of the channel state information feedback via backhaul is considered. We model such system in the framework of networked partial observation Markov decision process and derive a strategy to reduce the search range for the best cluster configuration. Then, for a given cluster configuration, the cluster heads deal with subchannel allocation and power control within each cluster. We propose a subchannel allocation scheme with proportional fairness. Thereafter, the inter‐cluster power control subproblem is modeled as a set of exact potential games, and a channel quality related pricing mechanism is presented to mitigate inter‐cluster interference. The existence and uniqueness of Nash equilibriums for the proposed game are investigated, and an effective decentralized algorithm with guaranteed convergence is designed. Simulation results demonstrate that the proposed algorithms not only have much lower computational complexity but also perform close to the exhaustive search solutions and other existing schemes. Copyright © 2015 John Wiley & Sons, Ltd.