AORS: adaptive mobile data offloading based on attractor selection in heterogeneous wireless networks

The unforeseen mobile data explosion poses a major challenge to the performance of today’s cellular networks, and is in urgent need of novel solutions to handle such voluminous mobile data. Obviously, data offloading through third-party WiFi access points (APs) can effectively alleviate the data load in the cellular networks with a low operational and capital expenditure. In this paper, we propose and analyze an attractor-aware offloading ratio selection (AORS) algorithm, which can adaptive select an optimum offloading ratio based on attractor selection for the current networks environment. In the proposed algorithm, the throughput of AP and the cellular load corresponding to the coverage area of the AP, are mapped into the cell activity, which is the reflector of the current network environment. When the current attractor activity is low, the network is dominated by the noise. Then, the noise triggers the controller to select adaptive attractor for each users, the optimal offloading ratio \(\phi \), to adapt to the dynamic network environment. Hence, according to the offloading ratio \(\phi \), the part of the cellular traffic will be transmitted via WiFi networks. Through simulation, we show that the proposed AORS algorithm outperforms the existing ones with 42 % higher heterogeneous network throughput in a dense traffic environment.     

System design of cdma2000 femtocells - [femtocell wireless communications]

Femtocells extend the cellular network coverage and provide high speed data service inside homes and enterprises for mobiles supporting existing cellular radio communication techniques. They also provide additional system capacity by offloading macro network traffic. This article reviews the characteristics of cdma2000-based femtocell systems. It discusses design and deployment aspects such as carrier allocation, access control, efficient support for femtocell discovery by idle mobiles, and active call hand-in from macrocell to femtocell. The evolution of the cdma2000 standard for optimizing performance and enriching user experience with femtocells is also discussed.     

基于NOMA的全双工多层异构网下行链路覆盖分析

针对异构网（Heterogeneous Network,HetNet）无线回程,现有研究主要集中于提升网络吞吐量,而对回程覆盖性能研究较少.由此,本文构造了一种在小小区基站（Small cell Base Station,SBS）上结合全双工（Full-Duplex,FD）和非正交多址接入（Non-Orthogonal Multiple Access,NOMA）技术的大规模多输入多输出（Multiple Input Multiple Output,MIMO）辅助多层HetNet模型.利用信干比（Signal-to-Interference Ratio,SIR）来模拟有源SBS的分布,得出不同类型接收端的干扰;然后推导了移动用户（Mobile User,MU）下行链路覆盖概率闭合表达式.仿真和数值结果表明,SBS下行链路覆盖概率会随着小小区下行链路功率共享系数的增加而减小;此外,通过对比NOMA和正交多址接入（Orthogonal Multiple Access,OMA）以及FD和半双工（Half-Duplex,HD）对下行链路覆盖性能的影响,本文提出的方案能显著提升网络性能.     

Offloading in Software Defined Network at Edge with Information Asymmetry: A Contract Theoretical Approach

The proliferation of highly capable mobile devices such as smartphones and tablets has significantly increased the demand for wireless access. Software defined network (SDN) at edge is viewed as one promising technology to simplify the traffic offloading process for current wireless networks. In this paper, we investigate the incentive problem in SDN-at-edge of how to motivate a third party access points (APs) such as WiFi and smallcells to offload traffic for the central base stations (BSs). The APs will only admit the traffic from the BS under the precondition that their own traffic demand is satisfied. Under the information asymmetry that the APs know more about own traffic demands, the BS needs to distribute the payment in accordance with the APs’ idle capacity to maintain a compatible incentive. First, we apply a contract-theoretic approach to model and analyze the service trading between the BS and APs. Furthermore, other two incentive mechanisms: optimal discrimination contract and linear pricing contract are introduced to serve as the comparisons of the anti adverse selection contract. Finally, the simulation results show that the contract can effectively incentivize APs’ participation and offload the cellular network traffic. Furthermore, the anti adverse selection contract achieves the optimal outcome under the information asymmetry scenario.     

Cluster based resource allocation in two‐tier HetNets with hierarchical throughput constraints

Two‐tier heterogeneous networks (HetNets), formed by deploying small cell base stations (SBSs) over existing macrocells, can enhance the network performance in future fifth generation network. However, the cross‐/co‐tier interference in HetNets also will severely influence the user throughput of both tiers. In this paper, we investigate the resource allocation and interference mitigation problem in cluster based orthogonal frequency division multiple access (OFDMA) two‐tier HetNets. In a typical cluster, one SBS is selected as the cluster head to allocate resources among all small cells to guarantee their throughput requirements. Hybrid access policy enables small cells to suppress the cross‐tier interference and earn additional revenue from macrocells, but it also leads to decrease of available resources for small cell users (SUs). To compensate hybrid access SBSs for their resources loss, we impose hierarchical SU throughput constraints on the optimization problem, which guarantee these small cells more resources than closed access ones. Besides, the cross‐tier interference constraint is also considered to protect the transmissions of macrocell users. Accordingly, a subgradient iteration based resource allocation algorithm is proposed. Numerical results show that the proposed algorithm can satisfy SU throughput constraints of all small cells with different access policies and guarantee quality of service requirements of all accessed macrocell users in hybrid access small cells.     

Toward green 5G heterogeneous small-cell networks: power optimization using load balancing technique

The overwhelming demand for data by an ever-increasing number of users is a great challenge wireless cellular networks are faced with. One potential solution to this issue is deploying a massive number of small cells (SCs) in the existing macro network. As SC overlay has a big role in the future wireless networks that can overcome the data traffic upsurge at little power cost, heterogeneous network (HetNet) has been viewed as a promising technology for 5G networks that extends cell coverage, improves network capacity and offloads the network traffic from the macro cell (MC) to the SCs. However, the hyper-dense SCs and their uncorrelated operation raise an important question about the joint power consumption of the macro base station (MBS) and the small base stations (SBSs) in the HetNet since the aggregate power consumption of the dense SBSs cannot be ignored. Recently, the SC sleeping technique has become a hot topic for saving energy in HetNets. To minimize power consumption in HetNets, we propose three algorithms to dynamically adapt the operation of the SBSs to active/sleep (on/off) for non-uniform user distribution in the HetNet. We investigate the general optimal power minimization problem for HetNet that requires relatively high computational complexity. Taking into account the additional increase of the traffic load brought to the MBS, a key design principle of the proposed algorithms is to switch off the SBSs gradually based on their locations, user densities in their coverage areas or the highest power that can be saved by switching some of them off, respectively. Then, we enhance the mathematical framework to make the analysis more realistic by considering the offloading between the SCs and the MBS that occurs when the traffic load exceeds SCs’ capacity. In this paper, based on the fact that user densities of SCs and MC change with time, we model the traffic on the European traffic profile and portray the power consumption of the HetNet throughout the day. Simulation results show that by applying SC sleeping and our proposed algorithms, the HetNet can save about 20% power daily. The performances of our proposed algorithms are close to that of the optimal algorithm and their computational complexities are remarkably lower.     

利用用户移动提高WiFi业务分担能力的用户激励机制研究

WiFi网络可以分担蜂窝网络的通信业务压力,缓解其拥塞状况。然而,WiFi网络的业务分担只能在其覆盖范围内进行。由于用户具有移动性,如果通过提供一些奖励引导WiFi网络覆盖范围之外的用户延迟其在蜂窝网络中的业务、直至其进入WiFi覆盖区再接受服务,WiFi网络的业务分担能力将得到显著提升。该文探讨了运营商通过激励机制鼓励用户延迟其蜂窝网络业务转而接入WiFi网络的过程,并将其建模为两阶段斯塔克博格(Stackelberg)博弈。在该博弈中,运营商期望采取最优的奖励方案,能够兼顾蜂窝网络拥塞和付出的用户奖励。该文推导出了运营商的最优奖励方案。数值结果表明,所提激励机制可以有效降低包括蜂窝网络拥塞代价和奖励用户代价在内的运营商总代价。     

SDN assisted Stackelberg Game model for LTE-WiFi offloading in 5G networks

The data traffic that is accumulated at the Macro Base Station (MBS) keeps on increasing as almost all the people start using mobile phones. The MBS cannot accommodate all user’s demands, and attempts to offload some users to the nearby small cells so that the user could get the expected service. For the MBS to offload data traffic to an Access Point (AP), it should offer an optimal economic incentive in a way its utility is maximized. Similarly, the APs should choose an optimal traffic to admit load for the price that it gets from MBS. To balance this tradeoff between the economic incentive and the admittance load to achieve optimal offloading, Software Defined Networking (SDN) assisted Stackelberg Game (SaSG) model is proposed. In this model, the MBS selects the users carefully to aggregate the service with AP, so that the user experiencing least service gets aggregated first. The MBS uses the Received Signal Strength Indicator (RSSI) value of the users as the main parameter for aggregating a particular user for a contract period with LTE and WiFi. Each player involved in the game tries to maximize their payoff utilities, and thus, while incorporating those utilities in real-time scenario, we obtain maximum throughput per user which experiences best data service without any lack in Quality of Experience (QoE). Thus, the proposed SaSG model proves better when compared with other game theory models, and hence an optimal data offloading is achieved.     

Pricing framework for almost blank subframe scheme in two‐tier heterogeneous networks

As a part of enhanced inter‐cell interference coordination (eICIC), almost blank subframe (ABS) is an efficient technique to mitigate the cross‐tier interference of two‐tier heterogeneous networks (HetNets) and enhance overall network performance. However, in small cells with closed subscriber group (CSG) mode, how to motivate small cell base stations (SBSs) to adopt ABS schemes is still one of technical challenges due to the selfish nature of SBSs. In this paper, we propose a pricing framework with ABS scheme that benefit both the macrocell and small cell tier. Within the proposed framework, each SBS with closed access policy performs ABS scheme by muting a portion of the whole frame in time domain, and then dedicating this interference‐free subframe to macrocell users (MUs) for exclusive use. In return, the macrocell base station (MBS) announces the price for these ABSs and offers a certain amount of revenue to each SBS according to the length of its ABS. Furthermore, we extend the small cell performance analysis to the scenario of hybrid access policy, which allow neighboring MUs to access small cells. To investigate the interaction between two tiers, we formulate the proposed framework as a one‐leader multiple‐follower Stackelberg game, which regards the MBS and SBSs as leader and followers, respectively. On the basis of the theoretical analysis, we prove that a unique Stackelberg equilibrium (SE) exists and obtain the optimal strategies for both tiers. Numerical results evaluate the utility performance of both tiers when SE is achieved and verify the validity of the proposed framework.     

Efficient coverage management of pico cells in HetNets via spectrum slicing,cell biasing,and transmit power spreading

Cell biasing is an effective solution for mobile user offloading in Heterogeneous Cellular Network (HetNet). Cell biasing modifies the user association criteria by incorporating Range Expansion Bias (REB) in traditional reference signal based user association technique. For sparse user distribution, REB for picocells does not offload users located outside RSRP Threshold Coverage Area. This is because the actual Reference Signal Received Power (RSRP) value for such users is lesser than the threshold RSRP value for successful communication. On the other hand, using a negative REB value for dense user distribution around picocells is not desirable because it leads to higher interference at users and high energy consumption at macrocells. In this paper, we suggest a unified framework for coverage optimization using spectrum slicing and transmit power spreading. Our proposed framework considers a combination of subchannel transmit power and REB which is based on the user distribution around picocells. Additionally, in order to protect the signal quality of macrocell users located close to picocells, we suggest location aware subchannel allocation technique. This technique maximizes the number of Interference Free subchannels for macrocell users. Obtained results show that our proposed framework can significantly improve the coverage and system blocking for HetNet.     

基于贝叶斯博弈的WLAN节能机制研究

针对无线局域网（Wireless Local Area Networks,WLAN）中密集部署无线接入点（Access Point,AP）导致的能耗和同频干扰问题,提出了一种基于贝叶斯博弈的节能机制（BaYesian Game based Energy Saving scheme,BYG-ES）.首先,对通用AP设备的能耗进行测量与分析,构建AP发射功率-负载-能耗的关系模型;然后,基于该关系模型及软件定义网络控制器实时收集的网络状态信息,设计基于贝叶斯博弈的能耗优化模型;最后,利用社会选择函数求解能耗优化模型,获得干扰限制下最优的休眠AP集合和发射功率配置规则,完成用户流量卸载和AP发射功率的调整,同时保证AP参与博弈的诚实性.实验结果表明,BYG-ES节能机制能在减小系统能耗的同时提高网络性能.     

Energy-efficient placement and sleep control of relay nodes in heterogeneous small cell networks

Small cell (SC) provides low-power radio access with a relatively smaller coverage range than a macrocell. It has been regarded as a key solution for offloading traffic in the future 5G system. Previous works on energy-efficient placement of base stations (BSs) in cellular networks introduced placement and sleep control of low-power relay stations (RSs) to reduce the total power consumption for downlink transmission from BSs to users. As compared with legacy RSs, SC can serve as an RS with a larger coverage range though consuming a bit more circuit power. Hence, this work additionally considers to deploy small cells (SCs) in a one-dimensional highway cellular network with BSs and legacy RSs, and further models the power consumption minimization problem for placement and sleep control of legacy RSs and SCs in this network. Since the problem is hard to be solved analytically, a genetic algorithm with dynamic operator-selection mechanism is further proposed to resolve this problem. Performance of the proposed algorithm is evaluated via simulation with a practical experimental parameter setting.     

面向接入回传一体化的毫米波空地网络建模与分析

无人机(UAV)作为空中基站有望成为传统地面网络的有力补充,以提供灵活覆盖和容量增强的解决方案.然而,大多现有研究忽略空中基站的无线回传这一实际因素对网络性能和用户体验的影响.为此,考虑接入回传一体化的空地毫米波蜂窝网络场景,其中无人机提供热点流量传输服务,地面基站(TBS)提供无人机回传链路并且服务非热点区域用户,以...     

Comparison of WiFi positioning on two mobile devices

Metropolitan WiFi positioning is widely used to complement GPS on mobile devices. WiFi positioning typically has very fast time-to-first-fix and can provide reliable location information when GPS signals are too weak for a position fix. Several commercial WiFi positioning systems have been developed in recent years and most newer model smart phones have the technology embedded. This study empirically determined the performance of WiFi positioning system on two different mobile devices. Skyhook's system, running on an iPhone and a laptop, was selected for this study. Field work was carried out in three cities at a total of 90 sites. The positional accuracy of WiFi positioning was found to be very similar on the two devices with no statistically significant difference between the two error distributions. This suggests that the replicability of WiFi positioning on different devices is high based on aggregate performance metrics. Median values for positional accuracy in the three study areas ranged from 43 to 92?m. These results are similar to earlier independent evaluations of Skyhook's system. The number of access points (APs) observed on the iPhone was consistently lower than that on the laptop. This lower number of APs, however, was not found to reduce positional accuracy. In general, no relationship was found between the number of APs and positional accuracy for either device, counter to earlier findings. The results indicate, however, that WiFi positioning can be achieved with a small number of APs (5–10), but that increased numbers of APs do not contribute to improved positional accuracy. Despite the agreement in aggregate performance metrics between the two devices, the replicability of WiFi positioning using Skyhook's system in terms of getting the same location by using two different devices at approximately the same place and time was relatively poor. Implications for location-based services on mobile devices are discussed.     

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.     

Performance analysis of an advanced heterogeneous mobile network architecture with multiple small cell layers

The integration of small cell technologies into the current mobile network operators is a necessity for providing capacity and coverage improvement in the future mobile networks (5G). This integration paves the way for heterogeneous networking. In this paper, a novel heterogeneous architecture for the efficient integration of small cell technology into the current mobile networks is developed, namely advanced heterogeneous mobile network (AHMN). AHMN architecture consists of a stack of multiple cell layers wherein the upper layer is the macrocell layer while under this layer, a number of lower small cell layers are formed. Focusing on femtocells and metrocells, as the most typical paradigms of small cells, a femtocell layer which serves the indoor traffic activity of femtocell users is considered, while the metrocell serves the outdoor traffic activities as well as the overflow traffic from femtocells. The overall heterogeneous network (HetNet) is completed with the macrocell overlay layer, which serves only the macrocell users and the overflowed traffic from the underlay metrocell layer. In the proposed AHMN architecture, the metrocell layer is deployed as a complementary layer between the macrocell and femtocell layers and facilitates the handover traffic interaction between the edge layers. Meanwhile, the mobility management in this architecture is critical and hence, the interaction between successive network layers, due to the handover (HO) traffic, is analyzed. Furthermore, for each network layer, a guard channel scheme is proposed in order to minimize the HO dropping rate of the mobile users. We show both analytically and by simulation the capability of AHMN in offloading traffic and reducing the blocking/dropping probability compared with the traditional macrocellular network.     

When to offload in two-tier smallcell networks: a Stackelberg game approach with pre-offloading-decision

In this paper, we consider the problem of traffic offloading in a two-tier downlink smallcell network with hybrid access. We formulate a Stackelberg game with pre-offloading decision, which includes two steps, to study the problem. The utility of the MBS is designed as a piecewise function, corresponding to the two possible decisions of the MBS. We design a bonus-based incentive mechanism to motivate smallcell base stations (SBSs) serve the MUEs. We prove the existence and uniqueness of the Stackelberg equilibrium. We also consider the incomplete information game, where the SBSs have private information. A Bayesian Stackelberg game with pre-offloading decision is formulated and the existence of Bayesian Stackelberg equilibrium is proved. Our proposed approach achieves much higher utilities than the existing approach does under some circumstances in both cases, which proves the necessity and superiority of our proposed game structure.     

BiLSTM Based Reinforcement Learning for Resource Allocation and User Association in LTE-U Networks

LTE-unlicensed (LTE-U) technology is a promising innovation to extend the capacity of cellular networks. The primary challenge for LTE-U is the fair coexistence between LTE systems and the incumbent WiFi systems. In this paper, we aim to maximize the long-term average per-user LTE throughput with long-term fairness guarantee by jointly considering resource allocation and user association on the unlicensed spectrum within a prediction window. We first formulate the problem as an NP-hard combinatorial optimization problem, then reformulate it as a non-cooperative game by applying the penalty function method. To solve the game, a novel reinforcement learning approach based on Bi-directional LSTM neural network is proposed, which enables small base stations (SBSs) to predict a sequence of future actions over the next prediction window based on the historical network information. It is shown that the proposed approach can converge to a mixed-strategy Nash equilibrium of the studied game and ensure the long-term fair coexistence between different access technologies. Finally, the effectiveness of the proposed algorithm is demonstrated by numerical simulation.

     

Distributed self-optimizing interference management in ultra-dense networks with non-orthogonal multiple access

Both non-orthogonal multiple access (NOMA) and ultra-dense network (UDN) are promising technologies in future wireless networks. However, considering the overlapped coverage of small base stations (SBSs) and the spectrum sharing with NOMA, interference management (IM) becomes a more complex and fundamental problem. Moreover, considering the massive SBSs and dynamic network conditions in UDN, more efficient mechanisms need to be designed to deal with the IM issue. Thus, we propose a distributed self-optimizing interference management approach to address both the intra-cell interference caused by NOMA and the inter-cell interference among dense deployed SBSs. Aiming to minimize the interference and guarantee the users’ requirements, we mathematically formulate the joint resource allocation and user selection problem with consideration of the diverse user requirements, complicated interference topology, and limited resources. Furthermore, we consider the imperfections of successive interference cancellation at receivers for separating and decoding superimposed signals and analyze the impacts of residual interference and outage probability in NOMA-based UDNs. For tractability purpose, we introduce interference graph and satisfaction game theory and propose distributed algorithms to solve the problem. Simulation results show that interference can be reduced significantly in UDNs with NOMA compared with the traditional IM approaches.

     

Optimal joint load balancing and EDCA configuration of IEEE 802.11 wireless hotspots

Wireless hotspots, ie, infrastructures composed of several IEEE 802.11 access points (APs), are today the most common solution in providing Internet access to a wide and rapidly changing population of users. According to common device implementation, stations establish associations with APs based on the measured strongest Received Signal Strength Indicator level. This usually leads to an uneven distribution of users to APs, increasing the chances of local network congestion. Load balancing (LB) solutions aim at mitigating this problem controlling the distribution of users. The LB algorithms enforce stations to associate with APs that manage a low number of users and/or that have a low traffic load. Usually, LB solutions do not consider traffic priorities or they assume some a priori quality of service (QoS) configuration for users. In this study, we propose a QoS‐LB solution based on the cell breathing technique with the goal of balancing the load in IEEE 802.11e Enhanced Distributed Channel Access (EDCA) Hotspots. The proposed algorithm explores the space of possible power/EDCA configurations by using a branch and bound approach that reduces the number of analyzed configurations and, hence, the time required to find the global optimal solution. The algorithm has been analytically defined and its performance evaluated through simulations and tests in a real test bed. The results prove that the proposed solution is effective in solving the optimal QoS‐LB configuration problem in WiFi hotspots of average size.