Femtocell structures can offer better voice and data exchange in cellular networks. However, interference in such networks poses a major challenge in the practical development of cellular communication. To tackle this issue, an advanced interference mitigation scheme for Line-Of-Sight (LOS) femtocell networks in indoor environments is proposed in this paper. Using a femtocell management system (FMS) that controls all femtocells in a service area, the aggressor femtocells are identified and then the transmitted beam patterns are adjusted using the linear array antenna equipped in each femtocell to mitigate the interference contribution to the neighbouring femtocells. Prior to that, the affected users are switched to the femtocells that provide better throughput levels to avoid increasing the outage probability. This paper considers different femtocell deployment indexes to verify and justifies the feasibility of the findings in different density areas. Relative to fixed and adaptive power control schemes, the proposed scheme achieves approximately 5% spectral efficiency (SE) improvement, about 10% outage probability reduction, and about 7% Mbps average user throughput improvement.

Femtocell has been considered as a key promising technology to improve the capacity of a cellular system. However, the femtocells deployed inside a macrocell coverage are potentially suffered from excessive interference. This paper proposes a novel radio resource optimization in closed access femtocell networks based on bat algorithm. Bat algorithm is inspired by the behavior of bats in their echolocation process. While the original bat algorithm is designed to solve the complex optimization problem in continuous search space, the proposed modified bat algorithm extends the search optimization in a discrete search space which is suitable for radio resource allocation problem. The simulation results verify the convergence of the proposed optimization scheme to the global optimal solution and reveal that the proposed scheme based on modified bat algorithm facilitates the improvement of the femtocell network capacity.

The demand for wireless traffic is increasing rapidly, which has posed huge challenges to mobile network operators (MNOs). A heterogeneous network (HetNet) framework, composed of a marcocell and femtocells, has been proved to be an effective way to cope with the fast-growing traffic demand. In this paper, we assume that both the macrocell and femtocells are owned by the same MNO, with revenue optimization as its ultimate goal. We aim to propose a pricing strategy for macro-femto HetNets with a user centric vision, namely, mobile users would have their own interest to make rational decisions on selecting between the macrocell and femtocells to maximize their individual benefit. We formulate a Stackelberg game to analyze the interactions between the MNO and users, and obtain the equilibrium solution for the Stackelberg game. Via extensive simulations, we evaluate the proposed pricing strategy in terms of its efficiency with respect to the revenue optimization.

This paper proposes a proportional fair-based joint optimization method for user association and the bandwidth ratio of protected radio resources exclusively used by pico base stations (BSs) for inter-cell interference coordination (ICIC) in heterogeneous networks where low transmission-power pico BSs overlay a high transmission-power macro BS. The proposed method employs an iterative algorithm, in which the user association process for a given bandwidth ratio of protected radio resources and the bandwidth ratio control of protected radio resources for a given user association are applied alternately and repeatedly up to convergence. For user association, we use our previously reported decentralized iterative user association method based on the feedback information of each individual user assisted by a small amount of broadcast information from the respective BSs. Based on numerical results, we show that the proposed method adaptively achieves optimal user association and bandwidth ratio control of protected radio resources, which maximizes the geometric mean user throughput within the macrocell coverage area. The system throughput of the proposed method is compared to that for conventional approaches to show the performance gain.

In the conventional cellular macrocell implementation strategy, the main base station transmits the radio signals in the omnidirectional manner in order to provide a wide range of cellular transmission to the users. In reality, however, the users move from one place to another depending on their activities, hence, sometimes this creates areas where no user exists inside the macrocell. Nevertheless, the base station continues to transmit the radio signals to all the coverage areas due to its involuntary manner, thus causing waste of energy. In our previous work, an energy efficient LTE macrocell base station scheme based on hourly user location distribution, which utilized opportunistic beamforming, was proposed in order to provide the cellular transmission only to the area where the user density is high. The drawback of this scheme was that there were many users who cannot receive the cellular transmission because of the limitation of the beamforming shape. In this paper, to overcome this difficulty, a new energy efficient macrocell strategy will be proposed. Here, additional low power consumption femtocell access points are deployed inside the macrocell to support the energy efficient opportunistic beamforming based on the hourly user location distribution. Concretely, the femtocell access points are woken up only when the active calling users exist inside its range. The proposed new strategy will be evaluated in terms of the hourly successful calling user ratio, the total power consumption and the hourly average downlink throughput compared with the previously proposed beamforming transmission strategy and the conventional omnidirectional transmission. The results will show the effectiveness of the proposed strategy in providing an energy efficient cellular macrocell system with high quality cellular services.

This paper presents a downlink interference mitigation framework for two-tier heterogeneous networks, that consist of spectrum-sharing macrocells and femtocells*. This framework establishes cooperation between the two tiers through two algorithms, namely, the restricted waterfilling (RWF) algorithm and iterative reweighted least squares interference alignment (IRLS-IA) algorithm. The proposed framework models the macrocell-femtocell two-tier cellular system as an overlay cognitive radio system in which the macrocell system plays the role of the primary user (PU) while the femtocell networks play the role of the cognitive secondary users (SUs). Through the RWF algorithm, the macrocell basestation (MBS) cooperates with the femtocell basestations (FBSs) by releasing some of its eigenmodes to the FBSs to do their transmissions even if the traffic is heavy and the MBS's signal to noise power ratio (SNR) is high. Then, the FBSs are expected to achieve a near optimum sum rate through employing the IRLS-IA algorithm to mitigate both the co-tier and cross-tier interference at the femtocell users' (FUs) receivers. Simulation results show that the proposed IRLS-IA approach provides an improved sum rate for the femtocell users compared to the conventional IA techniques, such as the leakage minimization approach and the nuclear norm based rank constraint rank minimization approach. Additionally, the proposed framework involving both IRLS-IA and RWF algorithms provides an improved total system sum rate compared with the legacy approaches for the case of multiple femtocell networks.

In dense femtocell networks (DFNs), one of the main issues is interference management since interference between femtocell access points (FAPs) reduces the system performance significantly. Further, FAPs serve different numbers of femtocell user equipments (FUEs), i.e., some FAPs have more than one FUE while others have one or no FUEs. Therefore, for DFNs, an intelligent channel assignment scheme is necessary considering both the number of FUEs connected to the same FAPs and interference mitigation to improve system performance. This paper proposes a two-stage dynamic channel assignment (TS-DCA) scheme for downlink DFNs based on orthogonal frequency division multiple access/frequency division duplex (OFDMA/FDD). In stage 1, using graph coloring algorithm, a femtocell gateway (FGW) first groups FUEs based on an interference graph that considers different numbers of FUEs per FAP. Then, in stage 2, the FGW dynamically assigns subchannels to FUE clusters according to the order of maximum capacity of FAP clusters. In addition, FAPs adaptively assign remaining subchannels in FUE clusters to their FUEs in other FUE clusters. Through simulations, we first find optimum parameters of the FUE clustering to maximize the system capacity and then evaluate system performance in terms of the mean FUE capacity, unsatisfied FUE probability, and mean FAP transmission energy consumption according to the different numbers of FUEs and FAPs with a given FUE traffic load.

Open-access femtocell networks assure the cellular user of getting a better and stronger signal. However, due to the small range of femto base stations (FBSs), any motion of the user may trigger handover. In a dense environment, the possibility of such handover is very frequent. To avoid frequent communication disruptions due to phenomena such as the ping-pong effect, it is necessary to ensure the effectiveness of the cell selection method. Existing selection methods commonly uses a measured channel/cell quality metric such as the channel capacity (between the user and the target cell). However, the throughput experienced by the user is time-varying because of the channel condition, i.e., owing to the propagation effects or receiver location. In this context, the conventional approach does not reflect the future performance. To ensure the efficiency of cell selection, user's decision needs to depend not only on the current state of the network, but also on the future possible states (horizon). To this end, we implement a learning algorithm that can predict, based on the past experience, the best performing cell in the future. We present in this paper a reinforcement learning (RL) framework as a generic solution for the cell selection problem in a non-stationary femtocell network that selects, without prior knowledge about the environment, a target cell by exploring past cells' behavior and predicting their potential future states based on Q-learning algorithm. Then, we extend this proposal by referring to a fuzzy inference system (FIS) to tune Q-learning parameters during the learning process to adapt to environment changes. Our solution aims at minimizing the frequency of handovers without affecting the user experience in terms of channel capacity. Simulation results demonstrate that· our solution comes very close to the performance of the opportunistic method in terms of capacity, while fewer handovers are required on average.· the use of fuzzy rules achieves better performance in terms of received reward (capacity) and number of handovers than fixing the values of Q-learning parameters.

In this paper, a new technique is proposed to reduce the frequency of cell search by user equipment (UE) in the presence of femtocells. A new common signal (CS) and a separate set of primary synchronization signals (PSSs) are employed to facilitate efficient cell search in a next-geration LTE-based system. The velocity of the UE is also utilized to determine cell search mode. A slow UE recognizes the presence of femtocells using the CS, so that it can make separate searches for macrocells and femtocells. A fast UE will not search for femtocells since the coverage of femtocells is restricted to a small region. The fast UE detects the macrocell boundary using the PSSs transmitted from neighboring macrocells, so that it can search for macrocells only at the macrocell boundary. The effects of CS and UE velocity on the number of cell searches are analyzed. The performance of the proposed technique is evaluated by computer simulations.

This paper proposes a simple decentralized cell association method for heterogeneous networks, where low transmission-power pico or femto base stations (BSs) overlay onto a high transmission-power macro BS. The focus of this investigation is on the downlink and the purpose of cell association is to achieve better user fairness, in other words, to increase the minimum average user throughput (worst user throughput). In the proposed method, an appropriate cell association for all users within a cell is achieved in an iterative manner based on the feedback information of each individual user assisted by a small amount of broadcast information from the respective BSs. The proposed method does not require cooperation between BSs. Furthermore, the proposed method is applicable to cases of inter-cell interference coordination (ICIC) between macro and pico/femto BSs through the use of protected radio resources exclusively used by the pico/femto BSs. Based on numerical results, we show that the proposed method adaptively achieves better cell association for all users according to the user location distributions compared to the conventional cell range expansion (CRE) method. The advantage of the proposed method over CRE is further enhanced in an ICIC scenario.

Recently much attention is being devoted to a femtocell's potential for improving indoor cellular coverage with the provision of high data rate services in a wireless environment. Femtocells are usually deployed in homes and buildings and overlay existing macrocells, or microcells which cover wider service areas. In such an overlaid network structure, one of the important issues in network planning is the analysis of system capacity achievable by femtocells, which could be significantly affected by indoor radio propagation properties. This paper addresses a typical environmental scenario where a detailed indoor radio propagation model can be adopted. Moreover, a performance evaluation of embedded femteocell networks reflecting various environmental scenarios and factors is provided by the metrics of outage probability, dynamic range of spectral efficiency, and required separation distances for various wall structures, distance, and the number of walls between the home femtocell and the user. Our computer simulation and numerical analysis indicate an outage probability of 1%∼58%, dynamic range of spectral varies from around 2.2 to 7, while the required separation from the macrocell station is 25 m ∼ 327 m. This information could be useful for femtocell network planning.

Orthogonal Frequency Division Multiple Access (OFD-MA) is a leading air interface candidate for future generation cellular networks. However, if deployed in a multi-user multi-tier cellular system, it is important to fairly share radio resources such as transmission power and sub-carriers among co-tier and cross-tier users. This paper focuses on a mathematical formulation of cell inner-zone/outer-zone radio resource partitioning variables and considers the case of an FFR-based macrocell underlaid with femtocell. By applying an exhaustive search procedure on the developed formulation, we determine the optimal radio resource partitioning parameter values from the perspectives of macrocell user fairness and femtocell throughput maximization.

Since femtocells are deployed in a two tier cellular network, along with macrocells operating on the same channel, interference between them limits the overall performance of the network. Without any control of the femtocell operation, pre-deployed macrocells will experience severe interference, which is not consistent with the current femtocell deployment principle. In this paper, to resolve this problem, a mathematical framework that optimizes the downlink transmission power of femtocells is formulated. Based on the formulated framework, we derive the optimal value of the transmission power so that the transmission affects the pre-deployed macrocell's downlink performance at a minimum scale, while providing sufficient Quality of Service (QoS) to its served users. Furthermore, to reduce the complexity of the power control process, we propose an Interference Estimation scheme which approximates the interference levels between different pairs of macrocell and femtocell base stations. The feasibility of this estimation process is shown by deriving the lower and upper bound of the estimation error. Through simulations, compared to no power control, we show that our proposed method provides a 17.64% reduction in macro user's outage probability, 5.9 dB decrease of interference on cell-edge macrocell users, and a 1.41 times increase in average user throughput.

The impact of co-channel deployment of femtocells on existing macro-cellular systems is investigated considering the use of techniques to resolve the loud neighbor problem. There are several approaches to this aim, for example, femtocell power control, interference coordination, and opening access to femtocells. Of these, coordinated scheduling, including power control, and their impact will be the main focus of this work. In the context of 3GPP-LTE, we examine under various operational scenarios the performance in terms of the average and 5% worst user throughput, a useful measure of fairness among users, both for femto and macro cells. Although recent studies have shown that co-channel femtocell has a minor impact on the macrocell performance in average sense, a non-negligible percentage of users may lose their opportunity to get satisfactory data service and, hence, we focus more on the 5% worst users.

In this letter, we propose a novel resource allocation scheme to enhance downlink system performance for orthogonal frequency division multiple access (OFDMA) and time division duplex (TDD) based femtocell networks. In the proposed scheme, the macro base station (mBS) and femto base stations (fBSs) service macro user equipments (mUEs) and femto user equipments (fUEs) in inner and outer zones in different periods to reduce interference substantially. Simulations show the proposed scheme outperforms femtocell networks with fractional frequency reuse (FFR) systems in terms of the system capacity and outage probability for mUEs and fUEs.

Mobility Robustness Optimization (MRO) is one of the most important goals in LTE-Advanced Self-Organizing Networks (SON). Seamless handover in femtocell network is urgent and challenging, which has not been paid enough attention. Handover decision parameters, such as Time-To-Trigger (TTT), Hysteresis, Cell Individual Offset (CIO), have great effect on mobility performance, which may lead to Radio Link Failures (RLFs) and Unnecessary Handover. This letter proposes a handover parameters optimization approach based on Ant Colony Algorithm in the femtocell networks. The simulation result shows that the proposed scheme has a better performance than the fixed parameters method.

In this letter, we propose and analyze a cooperative transmission scheme (CTS) that uses transmission timing control for LTE enterprise femtocells. In our scheme, the user equipment (UE) can receive the desired signal from an adjacent fBS as well as its serving femtocell BS (fBS). Thus, UE achieves an improved signal to interference ratio (SIR) due to the synchronization of the two signals. Analysis and simulation results show that the proposed scheme can reduce the outage probability for enterprise femtocells compared to the conventional system. In particular, a significant performance improvement can be achieved for UEs located at cell edges.

In this letter, we introduce two different resource allocation and Tx power management schemes, called resource control and fixed power (RCFP) and fixed resource and power control (FRPC), in an LTE-Advanced femtocell network. We analyze and compare the two schemes in terms of the system throughput for downlink and energy consumption of home evolved NodeB (HeNB) Tx power according to the number of HeNBs and home user equipment (HUE)'s user traffic density (C). The simulation results show that the FRPC scheme has better performance in terms of system throughput for macro user equipments (MUEs) and energy consumption in low C.

This paper proposes new scheduling algorithms for best effort (BE) traffic classification in business femtocell networks. The purpose of traffic classification is to provide differentiated services to BE users depending on their traffic classes, and the concept of traffic classification is called Inter User Best Effort (IUBE) in CDMA2000 1x Evolution Data Optimized (EVDO) standard. Traffic differentiation is achieved by introducing Grade of Service (GoS) as a quality of service (QoS) parameter into the scheduler's decision metric (DM). New scheduling algorithms are called QoS Round Robin (QoS-RR), QoS Proportionally Fair (QoS-PF), QoS maximum data rate control (DRC) (QoS-maxDRC), QoS average DRC (QoS-aveDRC), QoS exponent DRC (QoS-expDRC), QoS maxDRC-PF (QoS-maxDRC-PF). Two different femtocell throughput experiments are performed using real femtocell devices in order to collect real DRC values. The first experiment examines 4, 8, 12 and 16 IUBE users, while second experiment examines 4 IUBE + 2 Voice over IP (VoIP), 8 IUBE + 2 VoIP, 12 IUBE + 2 VoIP, 16 IUBE + 2 (VoIP) users. Average sector throughput, IUBE traffic differentiation, VoIP delay bound error values are investigated to compare the performance of the proposed scheduling algorithms. In conclusion, QoS-maxDRC-PF scheduler is proposed for business femtocell environment.

Femtocell is considered a promising solution for indoor service enhancement in IEEE 802.16e cellular systems. However, the scanning scheme of IEEE 802.16e is not suitable for direct use in scanning femtocells in terms of efficiency and scan duration. In this paper, we propose an efficient scanning scheme for femtocells in IEEE 802.16e systems. The proposed scheme can achieve a lower scanning overhead by reducing the number of femtocells needed to be scanned. Numerical results show that the proposed scanning scheme can reduce the control message overhead and the scan duration.