Interference and Resource management strategy for handover in femtocells

Interference in femtocells due to neighboring femtocells and macrocells is a major issue of two-tier networks. Handover should be made to reduce interference, if and only if, when resources are available. Otherwise, it will further degrade network performance. Resource management should be made in an efficient manner that will not cause interference between macrocells and neighboring femtocells. Since distance between macro base station (MBS) and femto access point (FAP) is short, therefore, it is very hard to sustain low handover probability when macro user moves from MBS to FAP. We proposed handover algorithm for uplink co-channel interference mitigation that will make handover decision on the basis of time-to-stay and signal to interference plus noise ratio thresholds along with efficient resource management mechanism to reduce number of handovers and also resolve interference problem.

     

An efficient handoff algorithm based on received signal strength and wireless transmission loss in hierarchical cell networks

Compared with the macrocell systems, the femtocell systems allow users to obtain broadband service with high data rate by using lower costs of transmit power, operation and capital expenditure. Traditional handoff algorithms used in macrocells cannot well satisfy the mobility of users efficiently in hierarchical macro/femto cell networks. In this paper based on the received signal strength (RSS) and wireless transmission loss, a new handoff algorithm in hierarchical cell networks called RWTL-HO is proposed, which considers the discrepancy in transmit power between macrocell and femtocell base stations. The simulation results show that compared with the conventional algorithm, the proposed algorithm improves the utilization of femtocells by doubling the number of handoffs; and in comparison with the handoff algorithm based on combining the RSSs from both macro and femto cell base stations, reduces half the number of redundant handoffs.     

Interference coordination method based on graph theory in two-tier cellular networks

This paper studies an interference coordination method by means of spectrum allocation in Long-Term Evolution (LTE) multi-cell scenario that comprises of macrocells and femtocells. The purpose is to maximize the total throughput of femtocells while ensuring the Signal-to-Interference plus Noise Ratio (SINR) of the edge macro mobile stations (mMSs) and the edge femtocell Mobile Stations (fMSs). A new spectrum allocation algorithm based on graph theory is proposed to reduce the interference. Firstly, the ratio of Resource Blocks (RBs) that mMSs occupy is obtained by genetic algorithm. Then, after considering the impact of the macro Base Stations (mBSs) and small scale fading to the fMS on different RBs, multi-interference graphs are established and the spectrum is allocated dynamically. The simulation results show that the proposed algorithm can meet the Quality of Service (QoS) requirements of the mMSs. It can strike a balance between the edge fMSs’ throughput and the whole fMSs’ throughput.     

Dynamic resource allocation in mobile heterogeneous cellular networks

User mobility is a challenging issue in macro and femto cellular networks for the fifth-generation and newer mobile communications due to the time-varying interference and topology experienced. In this paper, we consider an OFDMA-based two-tier network with one macro cell and several femto cells, wherein each macro user and/or femto user can leave or enter its serving cell frequently, referred to as user mobility. A resource allocation problem with different rate requirements of mobile users is then formulated. Assuming well knowledge of the user locations and the channel state information, we propose a dynamic algorithm with static and dynamic parts for a better trade-of between computational complexity and system throughput. The static algorithm, named interference weighted cluster algorithm in this paper, is based on the graph theory to cluster the femtocells by minimizing the interference between clusters, while the dynamic algorithm is to deal with the user mobility by sharing the resource blocks under the constraints of rate requirements. Numerical results are demonstrated to show the effectiveness of the proposed dynamic resource allocation algorithm in terms of capacity, computational time, and outage probability.

     

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 Q Learning and Fuzzy Q Learning Approach for Optimization of Interference Constellations in Femto–Macro Cellular Architecture in Downlink

The reduction in the cost and enhancement in the network coverage and capacity are the main objectives in the establishment of mobile networks. These objectives were the key force behind the idea of femtocells deployment. But, there are many technical issues for the femtocells deployment with already existing macro network. Cross-tier interference is one of the main challenge that must have to be resolved for smooth operation of macro–femto network. This paper gives self-optimizing and self-healing technique that utilizes Q-learning and fuzzy Q-learning algorithm for the objectives of enhancement in the network capacity and spectral efficiency. In our proposed scheme, each macro base station acts as an agent which interacts with its local environment (all the femtocells and mobile stations under its coverage area), gathers the information and takes the suitable actions correspondingly. For the objective of controlling cross-tier interference, macrousers are rescheduled in such an intelligent way that performance of the femtousers, located on the overlapped spectral portion, is not degraded. The simulation results confirm our proposed approach to improve the network capacity and spectral efficiency as well as sharp convergence, which designates its capability to meet the self organizing network requirements set by 3GPP.     

Toward Distributed Robust Power Allocation of Wireless Backhaul Links in Vehicular Small Cells

The vehicular small cell (VSC) is a new paradigm that has been recently proposed to be a potential technology for 5G cellular systems. Briefly, VSC concept lies in using the small cell technology inside vehicles such as buses and private cars to provide better coverage and good internet experience while on the move where the wireless backhaul link is inevitable. However, in order to increase the spectral efficiency, co-channel deployment of VSCs on the wireless backhaul link is preferred. Thus, managing the variable interference on the wireless backhaul and its power allocation requirement seem to be serious challenges in implementing the VSCs. Motivated by the simplicity and practically of the power allocation based on pilot power and received signal strength index (RSSI) information, this paper proposes an evolutionary approach and robust to the interference fluctuations in which, taking the limited dynamic range of transmitted power using linear mapping into account, the signal to interference plus noise ratio (SINR) balancing of the vehicular small base stations in their home macro base station and maximum capacity on the backhaul link are achieved at the cost of exchanging some power level information among both macro and small base stations. Finally, simulation results prove aforementioned potential advantages attained from the presented schemes.     

Enhancement of Geometry and Throughput in LTE Femtocells Cognitive Radio Networks

The mutual electromagnetic interference among macro users and femto users is a challenge, when femtocells are deployed in LTE and LTE advanced systems. When the used femtocells have a closed access, the macro users, who are indoors or near to the femtocells, are prone to a severe interference from the femto access points especially, in the case of the universal frequency reuse deployment. A power control is an effective way to improve the macro users’ geometry at the expense of a drop in the femto users’ geometry and capacity. The concept of a cognitive radio is proposed, as a novel approach, to mitigate the interference and improve the macro and femto users’ geometry. The system is designed, mathematically analyzed, and simulated considering that the femto users are secondary users for the macro users. The macro users and the femto users’ throughputs of the proposed system are estimated. Comparisons among the universal frequency reuse, the power control, and the suggested approach are held. The simulation results validate the efficiency of the proposed system. The average of femto users’ throughput in the proposed system is better than the corresponding one employing the universal frequency reuse or the power control, even if only 20 % of the subcarriers are available to be accessed by the femto users. Moreover, the macro users’ throughput in the proposed system is better than the corresponding one applying the universal frequency reuse or the power control, even if only 40 % of the subcarriers are available to be accessed by the macro users.     

A distributed implementation of mobility load balancing with power control and cell reselection in 4G network

We consider a self‐organizing network (SON) capability of mobility load balancing in a 4G network, which determines the transmission power level for individual base stations and cell reselection for individual mobile stations such that the network‐wide load is minimized while satisfying the minimum signal‐to‐noise and interference ratio (SINR) requirement of individual users. Both centralized and distributed schemes are proposed. The centralized scheme is based on the greedy algorithm, serving as a performance bound to the distributed scheme. The distributed scheme is to solve the system‐wide optimization problem in the flat network model, i.e. no central control node. Furthermore, it requires relatively low inter‐cell exchange information among neighboring cells over an inter‐cell channel, e.g. X2 interface in the LTE network. The proposed design objective is to minimize the number of mobile users that do not satisfy the specified average throughput, while distributing the user traffic load as uniformly as possible among the neighboring cells. Our simulation results for a uniform user distribution demonstrate that the proposed scheme can achieve up to almost 80% of a load balancing gain that has been achieved by a greedy algorithm in the centralized optimization. Copyright © 2014 John Wiley & Sons, Ltd.     

Analytical framework for power saving evaluation in two-tier heterogeneous mobile networks

Reducing the power consumption of base stations in mobile networks is an important issue. We investigate the power saving evaluation in two-tier heterogeneous mobile networks which consist of femtocells overlaid by macrocells. In the heterogeneous mobile networks, base stations without traffic load are allowed to enter the sleep mode to save power. The power saving probability that a base station enters the sleep mode and the average total power consumption of this network are complex joint-effects of various factors. Successful modelling of these complex joint-effects is critical to mobile network operators when they pursue the design of green mobile networks. In this paper we propose an analytical framework to facilitate systematic analysis. Based on the proposed analytical framework, we investigate the power saving probabilities and the average total power consumption in terms of several parameters, including the new traffic arrival rate per user, the maximum transmission power of a femtocell, the number of femtocells within a macrocell, and the number of users in the network. Numerical results show that the proposed analytical framework provides a useful and efficient method to facilitate systematic analysis and design of green mobile networks. Simulation results validate the accuracy of the proposed analytical framework.     

Outage performance of downlink communications in cognitive-based two-tier networks: cooperative and non-cooperative femtocells

Femtocell deployment, which is a promising approach to the coverage and capacity improvement of indoor communications, suffers from cross-tier interference. Therefore to make the femtocell technology practical this issue needs to be addressed appropriately. One serious type of cross-tier interference occurs in downlink communication, in which a macrocell user is located far from its macro base station. In this setup, the communication of the adjacent femto access points with their users makes the macrocell user experience a low SINR. This paper considers this scenario and shows how cognitive-enabled femto access points can cope with cross-tier interference. More precisely, we compute the outage probability of macro users in a two-tier network when femto access points use the energy detection-based spectrum sensing technique to find the unoccupied frequency subband. To improve the outage probability of macro users, we also study the effectiveness of cooperation among neighbor femto access points. In all cases, the analytical expressions are validated by computer simulations which confirm the accuracy of the used approximations.

     

Energy Efficiency Improvements in Heterogeneous Network Through Traffic Load Balancing and Sleep Mode Mechanisms

Heterogeneous network (HetNet) is one of the most promising approaches of IMT Advanced, which not only offers higher capacity and data rate, but also network Energy Efficiency (EE). HetNet is an advanced network that promotes complex cooperation between multiple tiers or sizes of base stations, i.e. macro, micro, pico, and femto base stations towards the above benefits. In this paper, a theoretical model for evaluating the EE of HetNet is proposed. Then, a sleep mode mechanism on picocells is proposed to reduce the total energy consumption which subsequently improves the EE. Simulation results show that EE can be increased by balancing the traffic load between different types of base stations. In fact, the improvement very much depends on the percentage of traffic that is offloaded to picocells. At low to medium traffic load conditions, significant improvements in EE can be observed through the proposed sleep mechanism. It is observed that by combining the sleep mode feature of picocells and load balancing between the different types of base stations in HetNet, further EE improvements up to 68 % for low traffic load and up to 33 % for medium traffic load can be achieved.     

Optimal Microwave Wireless Backhaul Link Design Using a Massive MIMO for 5G HetNet-Practical Deployment Scenario

The massive multiple-input–multiple-output that enhances energy efficiency and spectral efficiency is the primary technology for fifth generation wireless networks. A move toward heterogeneous elements such as microcells, femtocells, picocells as well as remote radio heads, characterised by physical measurements, backhauls, transmission and propagation, is now underway to ensure an economical transition to the cellular network infrastructure, that is far from expensive high power mounted base stations. This adaptation presents many obstacles to network operations and co-existence. The proposed work therefore provides a design for a 28 GHz microwave wireless backhaul link for small cell base stations (SBSs) as well as the number of antennas required for the base station (BS) to achieve a target backhaul rate of 10 Gbit/s within a given transmit power of 40 dBm. In this work a distributed beamforming algorithm is formulated in a multi-cell scenario using methods from random matrix theory, under the assumption that the system dimensions are large. The design purpose is to minimize the total transmit power over all BSs according to the constraints of the signal-to-interference-and-noise ratio (SINR) as beamformers are integrated in a distributed manner. The BSs may only need to share the channel statistics in the suggested algorithm, instead of the instant channel state information. The simulation results show that the proposed algorithm strongly satisfies the target SINR constraints as the number of SBSs per cell grows high.

     

Throughput and cost‐efficient interference cancelation strategies for the downlink of spectrum‐sharing Long Term Evolution heterogeneous networks

In a heterogeneous network (HetNet), small cells such as femtocells considered in this work are deployed jointly with macrocells. This new cells' layer, when added to the network, generates interference, which could hamper neighboring macro‐user equipment (MUE) and femto‐user equipment (FUE) transmissions. In fact, this interference results in degradation of the network performance. In this paper, we propose a downlink interference cancelation (DL‐IC) strategy for spectrum‐sharing Long Term Evolution (LTE) HetNet. This DL‐IC strategy aims to reduce the interference impact on users by optimizing their received signal to interference plus noise ratio (SINR) using new utility functions for both FUEs and MUEs. These utility functions allow relaxation of the cancelation ratios in order to reduce implementation complexity while maximizing SINR, QoS, and throughput. We support by different system‐level simulations that both global network performance and user experience in terms of total throughput and received SNR or link‐level throughput, respectively, are significantly enhanced. Throughput gains achievable by the new DL‐IC strategy can reach as much as 200% against a homogeneous LTE network without IC along with an extra 48% per additional femtocell base station against a basic spectrum‐sharing LTE HetNet without IC. These performance figures are shown to surpass those achieved by interference avoidance techniques using either power or frequency resource allocation. Copyright © 2014 John Wiley & Sons, Ltd.     

A Virtual Topology Based Routing Protocol for Multihop Dynamic Wireless Networks

In this paper, a new hierarchical multihop routing algorithm and its performance evaluation is presented for fully dynamic wireless networks. The routing algorithm operates on a virtual topology obtained by partitioning the routing information for mobile terminals and mobile base stations into a hierarchical, distributed database. Based on the virtual topology, each mobile base station stores a fraction of the routing information to balance the complexity of the location-update and the path-finding operations. Mobility of the network entities changes the load distribution and causes processing and memory bottlenecks in some parts of the network. However, since the network routing elements are also mobile, their movement can be used to distribute the load. Thus, new load balancing schemes are intoduced to distribute the routing overhead uniformly among the mobile base stations. The performance of the hierarchical multihop routing algorithm is investigated through simulations. It is shown that the routing protocol can cope with high mobility and deliver packets to the destinations successfully.     

Distributed User Association with Resource Partitioning in Heterogeneous Cellular Networks

To fully utilize the resources of heterogeneous cellular networks (HCNs), an effective approach that offloads users to the underloaded small cells from overloaded macrocells is widely advocated. However, this operation often leads to a bad result that the offloaded users achieve lower signal-to-interference-plus-noise-ratio (SINR) than these users in macrocells. Thus, some appropriate interference avoidance techniques should be adopted to partially alleviate the SINR degradation. For this, we consider the resource (frequency) partitioning that turns off some fraction of such resources in a macrocell. Naturally, an optimal offloading strategy should be closely coupled with resource partitioning, and in turn the optimal partition decides the offloading performance. In this paper, we propose a distributed association strategy with joint offloading and resource partitioning for HCNs. We reveal that load balancing, by itself, is insufficient, and additional resource partitioning is required to improve system performance. Meanwhile, we also show that, compared with the best power association and range extension association, the proposed scheme provides better association performance.

     

异构无线网络中边缘用户小区选择算法

在异构网络中,部署多种小功率基站,会出现大量的“小区边缘区域”,边缘用户的性能会受到影响。为此,提出了一种边缘用户小区选择算法,通过发送端进行预编码抑制干扰,提高用户接收到的信干噪比。根据小区当前用户数,动态地调整给微小区边缘用户参考接收信号添加的偏置值,避免边缘用户接入用户数过多的拥堵小区。仿真结果表明,该算法与参考算法相比,能够有效降低宏小区负载,平衡不同微小区间负载,提高轻载微小区的网络吞吐量和资源利用率。     

Base station selection and resource allocation in macro–femtocell networks under noisy scenario

In this paper, we address the problem of optimizing resources for downlink transmission in a macro–femtocell network under non-dense femtocell deployment. In the literature, some approaches perform bandwidth or power optimization depending on the air interface technology and others optimize both types of resources, but only in femtocell network. However, the following limitations can be noticed: (1) Equal distribution of transmitted power among all subcarriers, even if they are not used, leads to resource underutilization, (2) femtocell data rates are reduced in order to minimize the interference from femto base stations to macro users, and (3) the impact of noise has not been evaluated. Moreover, there is lack of optimal selection of users that can be served by femtocells. To overcome these limitations, we propose a model that finds a tradeoff between bandwidth and power to reduce the bandwidth usage per user and to minimize the impact of noise. By means of Linear Programming, our solution maximizes user satisfaction and provides optimal: serving base station, power and bandwidth for each mobile user taking into account its location and demand. Furthermore, we present a performance analysis under changes of signal to noise ratio. Simulations were conducted and a comparison with a modified version of Weighted Water Filling algorithm is presented.     

QoS Guaranteed Resource Allocation Scheme for Cognitive Femtocells in LTE Heterogeneous Networks with Universal Frequency Reuse

In this paper, we propose a novel resource allocation scheme for co-channel interference avoidance in LTE heterogeneous networks with universal spectrum reuse where both macro users (MUs) and cognitive femto base stations (FBSs) within the same macrocell coverage can dynamically reuse whole spectrum. Specifically, resource blocks (RBs) are shared between cognitive FBSs in underlay mode while the resource sharing among FBSs and MUs is in overlay mode. The macrocell is divided into inner and outer regions with the inner region further divided into three sectors. The proposed scheme addresses co-channel interference (CCI) by employing fractional frequency reuse (FFR) for RB allocation in the outer region of the macrocell and increase the distance of users that reuse the same RB within the macrocell. Part of RBs are allocated to the outer region of the macrocell with a FFR factor of 1/3, while the remaining RBs are dynamically allocated to each sector in the inner region of macrocell based on MUs demand to efficiently utilize the available spectrum. A basic macro base station (MBS) assistance is required by the FBS in selection of suitable RB to avoid interference with MU in each sector. With the proposed solution, both macro and femto users can dynamically access the whole spectrum while having minimum bandwidth guarantee even under fully congested scenarios. Moreover, the proposed scheme practically eliminates the cross-tier interference and the CCI problem in heterogeneous network reduces to inter-femtocell interference. The throughput and outage performances of the proposed scheme are validated through extensive simulations under LTE network parameters. Simulation results show that the proposed scheme achieves a performance gain of more than 1.5 dB in terms of SINRs of both macro user and femto user compared to traditional cognitive and non-cognitive schemes without bandwidth guarantee for femtocells.     

Interference management with adaptive fractional frequency reuse for LTE-A femtocells networks

This paper presents a novel interference management strategy, to adaptively choose the best fractional frequency reuse (FFR) scheme for macro and femto networks. The strategy aims to maximize the system throughput taking into account a number of system constraints. Here, the system constrains consist of the outage constraints of two-tier users and macrocell spectral efficiency requirement. The detailed procedures of our proposed strategy are: 1) A reference signal received power (RSRP) based selection algorithm is presented to adaptively select the optional FFR schemes satisfying the outage constraints. 2) Considering the macrocell spectral efficiency, the optimal FFR scheme is selected from the optional FFR schemes at MeNB side, to achieve the maximum system throughput in two-tier femtocell networks. We study the efficacy of the proposed strategy using an long term evolution advanced (LTE-A) system level simulator. Simulation results show that our proposed interference management strategy can select the best FFR scheme to maximize the system throughput, and the FFR schemes derived by using RSRP-based selection algorithm can be the effective solutions to deploy femtocells in macrocells.