Distributed channel assignment algorithms for 802.11n WLANs with heterogeneous clients

As the latest IEEE 802.11 standard, 802.11n applies several new technologies, such as multiple input multiple output (MIMO), channel bonding, and frame aggregation to greatly improve the rate, range and reliability of wireless local area networks (WLANs). In 802.11n WLANs, access points (APs) are often densely deployed to provide satisfactory coverage. Thus nearby APs should operate at non-overlapping channels to avoid mutual interference. It is challenging to assign channels in legacy 802.11a/b/g WLANs due to the limited number of channels. Channel assignment becomes more complex in 802.11n WLANs, as the channel bonding in 802.11n allows WLAN stations (APs and clients) to combine two adjacent, non-overlapping 20MHz channels together for transmission. On the other hand, IEEE 802.11n is backward compatible, such that 802.11n clients will coexist with legacy clients in 802.11n WLANs. Legacy clients may affect the performance of nearby 802.11n clients, and reduce the effectiveness of channel bonding. Based on these observations, in this paper, we study channel assignment in 802.11n WLANs with heterogeneous clients. We first present the network model, interference model, and throughput estimation model to estimate the throughput of each client. We then formulate the channel assignment problem into an optimization problem, with the objective of maximizing overall network throughput. Since the problem is NP-hard, we give a distributed channel assignment algorithm based on the throughput estimation model. We then present another channel assignment algorithm with lower complexity, and aim at minimizing interference experienced by high-rate, 802.11n clients. We have carried out extensive simulations to evaluate the proposed algorithms. Simulation results show that our algorithms can significantly improve the network throughput of 802.11n WLANs, compared with other channel assignment algorithms.     

An experimental study of inter-cell interference effects on system performance in unplanned wireless LAN deployments

In this paper, we report on our experimental study of the effects of inter-cell interference on IEEE 802.11 performance. Due to growing use of wireless LANs (WLANs) in residential areas and settings supporting flash crowds, chaotic unplanned deployments are becoming the norm rather than an exception. Environments in which these WLANs are deployed, have many nearby access points and stations on the same channel, either due to lack of coordination or insufficient available channels. Thus, inter-cell interference is common but not well-understood. According to conventional wisdom, the efficiency of an IEEE 802.11 network is determined by the number of active clients. However, we find that with a typical TCP-dominant workload, cumulative system throughput is characterized by the number of actively interfering access points rather than the number of clients. We verify that due to TCP flow control, the number of backlogged stations in such a network equals twice the number of active access points. Thus, a single access point network proves very robust even with over one hundred clients, while multiple interfering access points lead to a significant increase in collisions that reduces throughput and affects media traffic. Only two congested interfering cells prevent high quality VoIP calls. Based on these findings, we suggest a practical contention window adaptation technique using information on the number of nearby access points rather than clients. We also point out the need for collision-resilient rate adaptation in such a setting. Together these techniques can largely recover the 50% loss in cumulative throughput in a setting with four strongly interfering access points.     

异构网络下基于混合保护子帧的干扰协调方案

增强型小区间干扰协调（enhanced inter cell interference coordination,eICIC)引入几乎空白子帧(almost black subframes,ABS)来降低异构网络中小区间的干扰,然而过多的ABS会损失宏蜂窝用户性能。为了提高异构网络的性能,联合考虑ABS和低功率几乎空白子帧(low power-ABS,LP-ABS),提出了一种基于混合保护子帧(Hybrid Protected Subframes,HPS)的干扰协调方案。该方案综合考虑用户资源分配、HPS密度、HPS混合比例以及用户接入策略,以最大化系统比例公平效用为目标。仿真结果显示,所提方案在系统负载均衡、用户吞吐量以及用户公平性等指标上都优于传统增强型小区间干扰协调方案。     

Interference coordination based on random fractional spectrum reuse in femtocells toward Internet of Things

Femtocell is featured with a low-power and low-cost cellular access in indoor environments, and thus offers an effective yet flexible way to implement information exchange over Internet of Things. In femtocell networks, the dense deployment of home eNodeBs causes severe inter-cell interferences and imposes heavier load on the scarce frequency spectrum. In this paper, we propose an inter-femtocell interference coordination scheme to enable random and fractional reuse of frequency resources in a 3D in-building scenario. Specifically, we consider the regular femtocell deployment, where all the femtocells are divided into two groups and two neighboring femtocells will be classified into different group. Each group is initially allocated with a half of frequency resources. To more sufficiently utilize the spectrum, either group of femtocell is allowed to transmit over the frequency assigned to the other group of femtocell in a random way at the cost of introducing some interferences, i.e., reuse based on a specified probability. This probability is determined by maximizing the geometric mean of users’ average throughput, such that the fairness among users is guaranteed simultaneously. Moreover, an equivalent scheme generated from full frequency reuse between two femtocells groups is also given. Here, either group of femtocell will avoid transmitting over fractional frequency randomly with a certain probability and the interference to the adjacent femtocell can be reduced. The simulation results show that the proposed schemes could obtain the larger system average rate and edge user performance compared with the baseline schemes. Moreover, the geometrical average throughput per user achieved by our method is highest, and a more fair resources allocation can be realized .     

Energy-conservation in 802.11 WLANs via transmission-strategy-aware airtime allocation

In a typical 802.11 wireless local area network (WLAN), different wireless stations may communicate with the access point (AP) with different transmission rates, transmit-power levels, and data payload sizes. Such phenomenon is often referred to as transmission-strategy diversity. In this paper, we study the energy-conservation problem in 802.11 WLANs in the presence of transmission-strategy diversity. This problem is addressed from a unique angle – the system-level fairness which is quite different from most of current research that focuses on improving the performance of each individual wireless station. To emphasize fair energy consumption among contending stations, we introduce a new fairness notion, called energy-conservation fairness, which is in sharp contrast to the conventional throughput fairness and airtime fairness. Another contribution of this paper is an energy-efficient scheme that allocates airtime shares to contending stations so as to achieve combined airtime and energy-conservation fairness. Our simulation results show that, when the energy-conservation fairness is considered, both aggregate system throughput and overall system energy-efficiency can be improved significantly with all contending stations consuming a similar amount of energy.     

异构网载波聚合系统基于干扰对齐的联合算法研究*

为了满足异构网络热点区域覆盖,同时解决由于低功率基站在高功率基站覆盖区域随意分布而带来的小区间干扰及系统容量速率受限问题,提出了一种载波聚合系统的联合小区选择、载波选择和干扰对齐算法。该方法是在载波公平比例准则下,动态的选择成员载波。为了进一步降低小区间干扰,设计了新的基于干扰对齐的用户小区选择算法。理论分析表明,联合优化算法问题可以分解成三个子问题进行优化求解处理。仿真结果表明,与调度复用因子为1的参考算法相比,设计的方案由于联合了小区选择和载波选择使得用户选择低功率节点作为服务小区的机会增多,提高了低功率节点小区容量,使系统的吞吐量得到提高。     

一种公平的认知无线电系统下行频谱分配策略

目前关于认知无线电频谱分配的研究大多以最大化系统容量为目标,很少考虑认知用户的QoS需求,频谱分配方案设计缺乏公平性。针对主用户干扰限制和保障认知用户QoS需求,结合OFDM技术,研究了认知无线电场景中下行多用户分配算法。该算法构建不等式约束下的目标函数以最大化系统容量,通过拉格朗日(Lagrange)对偶优化法给出近似最优解。仿真结果表明,所提算法在牺牲系统和容量的前提下充分保证了次用户的QoS需求,提高了系统的公平性。     

中继蜂窝系统联合调度的公平性优化

针对中继蜂窝系统,提出一种联合调度的公平性优化模型.在分析中继网络小区用户通信方式的基础上,从边缘用户调度的公平性角度考虑充分发挥不同调度算法的优势,对基站采用最大载干比调度算法,中继器节点运用比例公平的联合调度算法对小区频率资源进行合理分配,提高边缘用户信号质量和小区的容量及覆盖率.仿真结果表明,联合调度算法的边缘用户性能优于传统调度算法,系统吞吐量提高20％.     

Efficient multicasting over large-scale WLANs through controlled association

Support for efficient multicasting in WLANs can enable new services such as streaming of TV channels, radio channels, and visitor’s information. With increasing deployments of large-scale WLANs, such services can be made available to a large number of users. However, any new multicast based services must minimally impact the existing unicast services which are currently the core services offered by most WLANs. In this paper, we leverage the flexibility of associating with different access-points (APs), which occurs often due to overlapping coverage of APs, to optimize the network’s objective. Motivated by different revenue functions and network scenarios, three different optimization objectives are considered which are: maximizing the number of admitted users (MNU), balancing the load among APs (BLA), and minimizing the load of APs (MLA). We show that these problems are NP-hard and present centralized approximation algorithms and distributed approaches to solve them. These algorithms compute which AP a user should be associated with. Using simulations we evaluate their performance and compare them to a naive approach in which users associate to the AP with the best RSSI (Received Signal Strength Indicator).     

Joint transmit power and physical carrier sensing adaptation based on loss differentiation for high density IEEE 802.11 WLAN

In high density (HD) IEEE 802.11 WLAN, packet loss can occur due to co-channel interference (asynchronous interference) or collisions (synchronous interference). In order to effectively mitigate the interference for spatial reuse, the causes of packet loss should be differentiated and corresponding network parameters (physical carrier sensing (PCS) threshold, transmit power (TXPW) and contention windows size) tuned accordingly. Such loss differentiation ability is not supported by current IEEE 802.11 networks; we devised a novel, zero over-the-air overhead, robust yet accurate method of estimating the probability of collision and interference, respectively. In this work, we investigate how to use differentiated packet error rate (PER) to mitigate asynchronous interference for increasing spatial reuse. Motivated by analysis, a joint transmit power and PCS threshold self-adaptation algorithm based on loss differentiation is proposed. Heuristics that address node starvation and fairness are also incorporated within the above (aggregate throughput maximization) framework to allow a flexible suite of approaches to network tuning. Elaborate simulations show that such joint adaptation algorithm can increase both total throughput and worst link throughput in HD WLAN greatly compared with PCS only adaptation without loss differentiation.     

Mitigating collisions through power-hopping to improve 802.11 performance

In this article, we introduce a power-hopping technique (PH-MAC) that, by alternating between different transmission power levels, aims to deliberately cause packet capture and thereby reduce the impact of collisions in 802.11 WLANs. We first devise an analytical model of the 802.11 protocol with heterogeneous capture probabilities, and show that, depending on the network load, the capture effect can enhance the throughput performance of all nodes. We base the design of PH-MAC on the findings following from this analysis and demonstrate that important performance improvements can be achieved by exploiting the interactions between the MAC and PHY layers to mitigate collisions. Finally, to understand the feasibility of this technique in practical deployments, we present a prototype implementation of PH-MAC which relies on commodity hardware and open-source drivers. We evaluate the performance of this implementation in an indoor testbed under different network conditions in terms of link qualities, network loads and traffic types. The experimental results obtained show that our scheme can provide significant gains over the default 802.11 mechanism in terms of throughput, fairness and delay.     

Wireless LAN load balancing with genetic algorithms

In recent years IEEE 802.11 wireless local area networks (WLANs) have become increasingly popular. Consequently, there has also been a surge in the number of end-users. The IEEE 802.11 standards do not provide any mechanism for load distribution and as a result user quality of service (QoS) degrades significantly in congested networks where large numbers of users tend to congregate in the same area. The objective of this paper is to provide load balancing techniques that optimise network throughput in areas of user congestion, thereby improving user QoS. Specifically, we develop micro-genetic and standard genetic algorithm approaches for the WLAN load balancing problem, and we analyse their strengths and weaknesses. We also compare the performance of these algorithms with schemes currently in use in IEEE 802.11 WLANs. The results demonstrate that the proposed genetic algorithms give a significant improvement in performance over current techniques. We also show that this improvement is achieved without penalising any class of user.     

IEEE 802.11ax密集WLAN的干扰协调策略

无线局域网(WLAN)中设备数量的指数级增长,导致激烈的信道争用及严重的同频干扰。当运行在同一频段上的两个WLAN在彼此感知范围内时,使用先监听后发送的分布式信道接入方式会引起资源浪费,降低网络吞吐率。提出一种密集WLAN场景下的干扰协调策略。根据IEEE 802.11ax中的基本服务集颜色对站点进行分组,提出协调交替目标唤醒时间策略(CAT),安排不同组内站点在不同的时间接收数据,从而避免信道争用,最小化干扰,同时通过优化下行数据包大小提高网络吞吐率。仿真结果表明,当两个WLAN距离很近时,CAT方案能够保证网络吞吐率。此外,在考虑误码率的情况下,吞吐率并非随着数据包的增大单调递增,而是存在一个阈值,超过该阈值后网络吞吐率即呈下降趋势。     

Joint spectrum allocation and scheduling for fair spectrum sharing in cognitive radio wireless networks

Cognitive radio and Dynamic Spectrum Access (DSA) enable wireless users to share a wide range of available spectrums. In this paper, we study joint spectrum allocation and scheduling problems in cognitive radio wireless networks with the objectives of achieving fair spectrum sharing. A novel Multi-Channel Contention Graph (MCCG) is proposed to characterize the impact of interference under the protocol model in such networks. Based on the MCCG, we present an optimal algorithm to compute maximum throughput solutions. As simply maximizing throughput may result in a severe bias on resource allocation, we take fairness into consideration by presenting optimal algorithms as well as fast heuristics to compute fair solutions based on a simplified max–min fairness model and the well-known proportional fairness model. Numerical results show that the performance given by our heuristic algorithms is very close to that of the optimal solution, and our proportional fair algorithms achieve a good tradeoff between throughput and fairness. In addition, we extend our research to the physical interference model, and propose effective heuristics for solving the corresponding problems.     

Joint transmission in cellular networks with CoMP—Stability and scheduling algorithms

Due to the current trend towards smaller cells, an increasing number of users of cellular networks reside at the edge between two cells; these users typically receive poor service as a result of the relatively weak signal and strong interference. Coordinated Multi-Point (CoMP) with Joint Transmission (JT) is a cellular networking technique allowing multiple Base Stations (BSs) to jointly transmit to a single user. This improves the users’ reception quality and facilitates better service to cell-edge users. We consider a CoMP-enabled network, comprised of multiple BSs interconnected via a backhaul network. We formulate the OFDMA Joint Scheduling (OJS) problem of determining a subframe schedule and deciding if and how to use JT in order to maximize some utility function. We show that the OJS problem is NP-hard. We develop optimal and approximation algorithms for specific and general topologies, respectively. We consider a time dimension and study a queueing model with packet arrivals in which the service rates for each subframe are obtained by solving the OJS problem. We prove that when the problem is formulated with a specific utility function and solved optimally in each subframe, the resulting scheduling policy is throughput-optimal. Via extensive simulations we show that the bulk of the gains from CoMP with JT can be achieved with low capacity backhaul. Moreover, our algorithms distribute the network resources evenly, increasing the inter-cell users’ throughput at only a slight cost to the intra-cell users. This is the first step towards a rigorous, network-level understanding of the impact of cross-layer scheduling algorithms on CoMP networks.     

Hybrid inter-cell interference management for ultra-dense heterogeneous network in 5G

The Ultra-dense Heterogeneous Network (HetNet), which consists of macro-cells and pico-cells, has been recognized as a key technique to improve network performance. However, the increasing number of pico-cells also causes severe interference including inter-cell interference and intra-cell interference. Therefore, interference management has become an important issue in ultra-dense HetNets, and the traditional enhanced inter-cell interference coordination (eICIC) scheme is no longer fit for the high density of small cells. In this paper, a hybrid interference management method based on dynamic eICIC and coordinated multi-point transmission (CoMP) is proposed. Firstly, a virtual cell is established based on the characteristics of ultra dense HetNets. Then, a novel joint dynamic eICIC scheme combined with multi-user beamforming is deployed to eliminate the inter-cell interference, and improve the throughput of virtual cell significantly without sharp decrease of throughput of macro-cell. Furthermore, a virtual cell based joint transmission scheme is deployed with a power control algorithm, which can obviously increase the spectrum efficiency of virtual cell edge. Simulation results verify that the proposed scheme can achieve better spectrum efficiency both at macro-cell and virtual cell edges, and the network throughput is also improved.     

Data traffic scheduling algorithm for multiuser OFDM system with adaptive modulation considering fairness among users

Orthogonal frequency division multiplexing (OFDM) is regarded as a very promising digital modulation technique for achieving high rate transmission. However, the increasing number of wireless data users and the deployment of broadband wireless networks have brought about issues of fairness among users and system throughput. In this paper, we propose an efficient scheduling algorithm to maximize system throughput while providing a level of fairness among users for non-real-time data traffic in the downlink of a multiuser OFDM system. We establish a practical scheduling procedure to implement our scheme considering fairness among users and also formulate the resource allocation problem for rate, power, and subcarrier allocation as an integer program that maximizes system throughput. Next, we present a computationally efficient heuristic algorithm for a problem based on the Lagrangian relaxation procedure. Through the computing simulation, we show that the proposed scheme performs better than other schemes in terms of both system throughput and fairness among users.     

一种新型的LTE系统干扰协调算法

为了解决LTE多小区系统在重度边缘负载情况下所承受的严重的小区间干扰问题,提出了一种基于小区边缘用户数的干扰协调调度算法ICPF。该算法在软频率复用干扰协调场景下提出了改进型资源分配以及二次调度思想,在初步分配资源的基础上进行频率资源二次调整,并有效地与调度算法结合起来。仿真结果表明,ICPF算法能在保证频谱利用率的前提下,提高小区边缘用户性能以及多用户分集的效果。     

Game-theoretic static load balancing for distributed systems

In this paper, we present a game theoretic approach to solve the static load balancing problem for single-class and multi-class (multi-user) jobs in a distributed system where the computers are connected by a communication network. The objective of our approach is to provide fairness to all the jobs (in a single-class system) and the users of the jobs (in a multi-user system). To provide fairness to all the jobs in the system, we use a cooperative game to model the load balancing problem. Our solution is based on the Nash Bargaining Solution (NBS) which provides a Pareto optimal solution for the distributed system and is also a fair solution. An algorithm for computing the NBS is derived for the proposed cooperative load balancing game. To provide fairness to all the users in the system, the load balancing problem is formulated as a non-cooperative game among the users who try to minimize the expected response time of their own jobs. We use the concept of Nash equilibrium as the solution of our non-cooperative game and derive a distributed algorithm for computing it. Our schemes are compared with other existing schemes using simulations with various system loads and configurations. We show that our schemes perform near the system optimal schemes and are superior to the other schemes in terms of fairness.     

基于用户分配和负载的频谱分配算法

提出了一种基于用户分配和负载的频谱分配算法.该算法包括两部分:用户分配子算法和频谱分配子算法.用户分配子算法首先基于聚类划分理论,使分配到相同访问点下的用户具有相近的信噪比,缓解了无线接入网络中普遍存在的远近效应问题.在该用户分配基础上,频谱分配子算法根据各访问点的负载及其关联用户信噪比的平均值计算最优频谱分配.该算法具有可实现性、多项式时间的计算复杂度以及比例公平性.真实数据驱动的仿真实验结果表明,该算法能够有效地提高系统吞吐量,同时大幅度减小访问点的报文缓冲区队长.