Femtocell Capacity Research Articles

Q-Learning-Based Adaptive Power Control in Wireless RF Energy Harvesting Heterogeneous Networks

This article investigates adaptive power control in wireless radio frequency energy harvesting (EH) femtocell heterogeneous networks (HetNets), where some EH devices desire to harvest energy from the signals transmitted from both macro base stations (BSs), and femtocell BSs. An optimization problem is formulated to maximize the sum capacity of femtocells while satisfying the EH requirements of energy users, and information quality of service (QoS) requirements of macrocell users by adaptively controlling the transmit power of femtocell HetNets, where nonlinear EH model is adopted. Due to the discrete variables of transmit power, the formulated optimization problem is with combinatorial computational complexity, and cannot be solved with known solution methods. Thus, a Q-learning-based algorithm is presented, and a segmented reward function based on the distance factor, and the penalty parameter is designed. Simulation results show the effectiveness of the proposed Q-learning-based algorithm, and the presented segmented reward function. It is also demonstrated that by using the nonlinear EH model can effectively avoid the deviation brought by the traditional ideal linear EH model. Additionally, it shows that the convergence time of our proposed scheme grows linearly w.r.t. the number of femtocell BSs, and the number of selectable transmit power levels of femtocell BSs roughly.

Handover Algorithm Based on User’s Speed and Femtocell Capacity in LTE/LTE-A Networks

Femtocells as an integral part of LTE/LTE-A has been widely accepted as a good solution to coverage and bandwidth problems in mobile cellular networks. With femtocells, the coverage area of a macrocell base station can be extended and large amount of traffic can be offloaded. Densely deployed femtocells play a major role in meeting data demand in the present and future networks characterized by very high speed and various traffic types. An efficient handover algorithm is therefore required that can work well under such highly mobile and varying traffic scenarios to handle frequent and unnecessary handovers. In this work, a handover algorithm based on user speed and femtocell capacity in LTE/LTE-A has been proposed. The performance of this algorithm is compared with an existing algorithm without consideration for user’s speed and femtocell capacity, in terms of total number of handovers and the ratio of target femtocells in the system.

Resource Allocation Based on Channel Sensing and Spatial Spectrum Reuse for Cognitive Femtocells

A cognitive femtocell is a new small cell based on a smart home base station to solve the spectrum-scarcity problem. Recently, dedicated resource allocation for cognitive femtocell to mitigate co-channel interference is extensively researched. However, the cognitive femtocell may suffer from the lack of frequency resource for its users due to high data traffic load of the macrocell. We propose a novel resource allocation and power control mechanism using spatial frequency reuse and spectrum sensing, which enables femto users in the cognitive femtocell to obtain more feasible resource. We analyze and evaluate the performance gain of the proposed scheme. Although data traffic load of the macrocell increases, the capacity of the cognitive femtocell can be maintained appropriately by the proposed resource allocation and power control scheme and it is shown that the performance is improved compared to that of the conventional scheme.

Semi-Clustering of Victim-Cells Approach for Interference Management in Ultra-Dense Femtocell Networks

Network densification is seen as a necessary trend in the evolution toward 5G networks to cope with future high-traffic demands. In particular, the use of femtocells seems to be the most feasible solution for hotspot areas where high traffic is concentrated. However, femtocell densification will face a number of technical challenges. Among others, the co-tier interference arises as an old acquaintance with a new significance. In point of fact, the interference characteristics and the role of aggressor and victim depend on a large extent on the density scenario, especially when femtocells share the same channel and operate in a Closed Subscriber Group (CSG) mode. In this regard, identification of victim and aggressor femtocells is a prerequisite to design an effective interference management scheme for ultra-dense femtocell networks (UDFNs). This paper implements a new approach for radio resource utilization and management for victim femtocells in an ultra-dense network environment. The proposed semi-clustering of victim-cell (SCVC) approach focuses mainly on users’ status whether critical or non-critical to categorize victim femtocells and their aggressors. After identifying the victim femtocells, the SCVC scheme semi-cluster each victim femtocell based on the status of each user. Then, it smartly allocates the appropriate radio resources in a dynamic manner, which allows ranging from shared use of resources for critical users to the frequency reuse one for non-critical users, thereby ensuring minimum co-tier interference and enhancement of spectrum efficiency. Simulation results show that our approach outperforms one of the prominent related schemes, namely, femtocell cluster based resource allocation (FCRA), in terms of the mean throughput of critical users, the average capacity of victim femtocells, and the percentage of resource utilization by an approximate average gain of 185%, 64%, and 31%, respectively.

Incentive Mechanism for Hybrid Access in Cognitive Femtocell Networks

In this paper, we propose a new incentive mechanism for hybrid access in cognitive femtocell networks. The purpose of the proposed incentive mechanism is to guarantee the QoS of macro user equipments (MUEs) and to increase femtocell capacity. MUEs channel condition report triggers bidding procedure by neighbor femtocell base stations (FBS). Macro base station (MBS) can offer some subchannels as rewards to encourage FBSs to reliably support its MUEs. Simulation results validate the effectiveness of our proposed scheme.

Power management in adjacent cognitive femtocells with distance-dependent interference in full coverage area

In cognitive heterogeneous networks, when multiple adjacent femtocells are deployed, uncontrolled transmission power can lead to severe mutual interference. In order to reduce interference while satisfying capacity requirements, we propose a power management scheme for an adjacent femtocell network. Firstly, we build an interference model for adjacent femtocells, in which distance-dependent interference to terminals within the whole femtocell coverage area is considered. Then, we calculate the total capacity of adjacent femtocells based on the mutual interference and formulate a non-convex optimization problem to maximize the capacity under the transmission power constraints. To solve the non-convex problem, we divide it into two convex subproblems and solve them with the Lagrange dual theory and linear programming method. Finally, we derive the closed-form expression of the optimal power configuration to maximize capacity while minimizing energy consumption simultaneously. The simulation results indicate that the proposed power scheme demonstrates obvious improvement in terms of capacity and power economization, compared with the maximal power configuration method.

Delay Analysis of an Improved Wimax Macro-Femto Handover Technique and Cell Selection Algorithm

Femtocells (FC) have been introduced in WiMAX networks due to the high data rate broadband access provided by Wimax networks. The key features like increased cell coverage, high throughput indoors and system capacity of FC are widely being accepted. However, issues regarding macro/femto handover decision are still being considered. This paper evaluates a technique for a macro/femto handover. The analyzed procedure offers communication with the mobile station having reduced delay. Moreover, it minimizes the number of FC(s) to be scanned during cell selection on the basis of cell ratio thus saving handover decision time.

Analysis of Uplink Intercarrier Interference in OFDMA Femtocell Networks

The femtocell has been considered to be a promising and cost-effective technology to enhance cellular coverage and capacity. However, in the uplink of orthogonal frequency-division multiple access (OFDMA)-based femtocell systems, the signals from macrocell users (MUs) generally arrive at the femtocell base station (FBS) asynchronously because their transmissions are scheduled to be synchronized at the macrocell base station (MBS). When the timing misalignment caused by the asynchronous reception at the FBS is greater than the cyclic prefix length, intercarrier interference (ICI) will arise in demodulation. In this paper, a performance analysis of uplink OFDMA femtocell network is presented. First, the cumulative distribution function (CDF) of MU arrival time is derived. Evaluation shows that the derived CDF is accurate and agrees with simulation results. With the CDF, a closed-form expression of probability mass functions (PMFs) of relative delay of MU signal and probability of ICI occurrence for two synchronization schemes are developed. Based on the PMF of relative delay, ICI power averaged over MU locations for the macrocell using fractional power control is derived for the two synchronization schemes. This new theoretical result helps analyze the signal-to-interference-plus-noise ratio (SINR) of the femtocell, femtocell capacity, and symbol error rate (SER). The theoretical analysis provides a solid evaluation of the effects of ICI for different FBS locations on system performance. It is shown that the performance analysis is quite agreeable with computer simulation. Theory and simulation results show that the system performance of the femtocell using first MU arrival time for synchronization is close to that of no ICI and better than that of using the earliest permissible arrival time.

Distributed joint resource and power allocation in self-organized femtocell networks: A potential game approach

Femtocells, which are widely deployed within a macrocell, are considered to be a novel technology that leads to the escalation of indoor coverage and capacity. However, due to lack of coordination between the femtocell and the macrocell, designing a distributive resource and power allocation is a challenging task. In this study, a potential game (PG)-theoretic approach is proposed for joint resource and power allocation (JRPA), which is demonstrated to exhibit unique Nash Equilibrium. Specifically, femto-base stations, which are considered as the players of the PG, learn the strategies in terms of resource and power allocation by taking into account the interest of other entities. To this end, the utility function of players is designed such that it minimizes the impact interference and the satisfaction for improving the femtocell capacity, without jeopardizing the macrocell performance. Precisely, the utility function incorporates all the sources of interference such as co-tier and cross-tier, and also the reward of each player in terms of capacity. The proposed PG-based JRPA is solved by employing the better response dynamics, which selects the resources and the power levels by utilizing a particle swarm optimization-constriction factor model. The performance of PG-based JRPA is analyzed in regard to average femtocell capacity and system capacity. Additionally, two different traffic cases are considered: high load traffic and low load traffic. For the sake of comparison, random allocation is employed. Simulation results are carried out in terms of the performance metrics, which includes convergence, min-max capacity, varying resource blocks, femtocell density and fairness. The results illustrate the superior performance of the proposed PG in terms of the aforementioned performance metrics.

Non-Ideal Backhaul Based Spectrum Splitting and Power Allocation for Downlink <roman>CoMP</roman> in Cognitive Macro/Femtocell Networks

This letter propose a novel scheme for cognitive macro/femtocell downlink coordinated multipoint (CoMP) transmission to improve the capacity of femtocell without affecting the normal communications of macrocell users (MUs). In specific, the femtocell access point (FAP) assists the macrocell base station (MBS) by jointly transmiting to the MU in the vicinity of the femtocell. A portion of the spectrum originally assigned to the MU is reserved for CoMP. In return, the rest can be freely utilized by the femtocell. Moreover, the impact of non-ideal backhaul (NIB) is considered, which makes the joint spectrum splitting and power allocation non-convex. A universal dual bisection algorithm is proposed to achieve the globally optimal solution. Simulation results indicate that the capacity of femtocell is enhanced up to 200% relative to the traditional methods. Meanwhile, the data communications of MUs are well protected compared with the scheme that ignores the impact of NIB.

Clustering Based Adaptive Power Control for Interference Mitigation in Two-Tier Femtocell Networks

Two-tier femtocell networks, consisting of a conventional cellular network underlaid with femtocell hotspots, play an important role in the indoor coverage and capacity of cellular networks. However, the cross- and co-tier interference will cause an unacceptable quality of service (QoS) for users with universal frequency reuse. In this paper, we propose a novel downlink interference mitigation strategy for spectrum-shared two-tier femtocell networks. The proposed solution is composed of three parts. The first is femtocells clustering, which maximizes the distance between femtocells using the same slot resource to mitigate co-tier interference. The second is to assign macrocell users (MUEs) to clusters by max-min criterion, by which each MUE can avoid using the same resource as the nearest femtocell. The third is a novel adaptive power control scheme with femtocells downlink transmit power adjusted adaptively based on the signal to interference plus noise ratio (SINR) level of neighboring users. Simulation results show that the proposed scheme can effectively increase the successful transmission ratio and ergodic capacity of femtocells, while guaranteeing QoS of the macrocell.

Cooperative Q‐learning techniques for distributed online power allocation in femtocell networks

AbstractIn this paper, we address the problem of distributed interference management of femtocells that share the same frequency band with macrocells using distributed multi‐agent Q‐learning. We formulate and solve two problems representing two different Q‐learning algorithms, namely, femto‐based distributed and sub‐carrier‐based distributed power controls using Q‐learning (FBDPC‐Q and SBDPC‐Q). FBDPC‐Q is a multi‐agent algorithm that works on a global basis, for example, deals with the aggregate macrocell and femtocell capacities. Its complexity increases exponentially with the number of sub‐carriers in the system. Also, it does not take into consideration the sub‐carrier macrocell capacity as a constraint. To overcome these problems, SBDPC‐Q is proposed, which is a multi‐agent algorithm that works on a sub‐carrier basis, for example, sub‐carrier macrocell and femtocell capacities. Each of FBDPC‐Q and SBDPC‐Q works in three different learning paradigms: independent (IL), cooperative (CL), and weighted cooperative (WCL). IL is considered the simplest form for applying Q‐learning in multi‐agent scenarios, where all the femtocells learn independently. CL and WCL are the proposed schemes in which femtocells share partial information during the learning process in order to strike a balance between practical relevance and performance. We prove the convergence of the CL paradigm when used in the FBDPC‐Q algorithm. We show via simulations that the CL paradigm outperforms the IL paradigm in terms of the aggregate femtocell capacity, especially in networks with large number of femtocells and large number of power levels. In addition, we propose WCL to address the CL limitations. Finally, we evaluate the robustness and scalability of both FBDPC‐Q and SBDPC‐Q, against several typical dynamics of plausible wireless scenarios (fading, path loss, random activity of femtocells, etc.). We show that the CL paradigm is the most scalable to large number of femtocells and robust to the network dynamics compared with the IL and WCL paradigms. Copyright © 2014 John Wiley & Sons, Ltd.

A docitive Q‐learning approach towards joint resource allocation and power control in self‐organised femtocell networks

AbstractFemtocell is a technology that contributes towards the escalation of coverage as well as throughput. By virtue of uncertain deployment of femtocells, self‐organisation is a viable solution for resource allocation. In this study, we are projecting a docitive Q‐learning (DQL) paradigm for joint resource allocation and power control (JRAPC). Moreover, the proposed learning paradigm is compared with independent Q‐learning for the same JRAPC problem. In the proposed DQL paradigm, femto base stations, which are agents, learn the strategies by exploiting Q‐learning and share their learned strategies with their neighbours. Concerning the shared channel environment, the problem function is formulated as the maximisation of femtocell capacity while maintaining the quality of service requirement of the macrousers. The impact of the proposed DQL paradigm is investigated on system capacity and femtocell capacity. Furthermore, comparison is carried out with the considered independent learning paradigm in terms of convergence, min‐max capacity and the effect of femtocell density. Also, the fairness index is computed to have further insight. The results illustrate that DQL‐based JRAPC outperforms its counterpart. Copyright © 2014 John Wiley & Sons, Ltd.

Frequency Collision Elimination Method Based on Negotiation and Non-Cooperative Game in Femtocell Networks

In the user deployed femtocell networks, the frequency collision dramatically decreases the throughput of femtocell networks. In this paper, we propose a frequency collision elimination method based on negotiation and non- cooperative game to avoid frequency collisions between neighboring femtocells. The frequency collisions inside a cluster are figured out by using the negotiation mechanism. The game theoretical mechanism deals with the inter-cluster frequency collisions. The femtocell network gets an equilibrium point rapidly by using the proposed methods in the context of stable femtocell network topology. Furthermore, the method is achievable in realistic communication system. Simulation results show that the proposed scheme significantly reduces the interference and considerably increases the average capacity of femtocells. Index Terms—Femtocell network, fractional frequency reuse, frequency collision, game theory

Resource Allocation Method Using Channel Sensing andResource Reuse for Cognitive Femtocells

A cognitive femtocell is a new small cell based on a smart home base station to solve the spectrum-scarcity problem. Recently, dedicated resource allocation for cognitive femtocells is extensively researched to mitigate the co-channel interference. However, the cognitive femtocell may suffer from the lack of frequency resource for its users due to high data traffic load of the macrocell. In this paper, we propose a novel resource allocation scheme based on the channel sensing and the spatial radio resource reuse mechanism, which enables femto users in the cognitive femtocell to obtain more feasible radio resource. The simulation results show that the capacity of the cognitive femtocell can be improved under high data traffic load of the macrocell compared to that of the conventional scheme.

Distributed Q-Learning for Interference Mitigation in Self-Organised Femtocell Networks: Synchronous or Asynchronous?

Femtocells promise to improve the quality of indoor wireless communications substantially. However, a serious interference problem arises with universal frequency reuse. In this paper, an asynchronous dynamic power allocation among femtocells based on Q-learning is proposed to mitigate the interference in the network. Simulation results show that in the high femtocells density deployment, asynchronous decision-making process has better performance than the synchronous one in terms of both performance degradation of the macrocell and average capacity of femtocells. In addition, it is shown that our method has superiority to smart power control algorithm proposed by 3GPP when femtocell occupation ratio is over 53 %.

UMTS Multi-Service Uplink Capacity and Interference Statistics of Femtocells

In this work, the multiservice uplink capacity of single and multiple femtocells is given. The COST231 multiwall and multifloor indoor propagation model has been used to calculate the indoor propagation loss. Results show that the uplink capacity of a deployed femtocell will reduce by 2 % if two extra femtocells are deployed in the same building higher and lower of it. Results also show that the uplink capacity is slightly affected if there are several femtocells deployed in the buildings around the one at which the femtocell under study is already exists. It is demonstrated that uplink capacity is interference limited if the femtocell is deployed to serve the users in three floors. Results show that the uplink capacity will be interference and noise limited if the femtocell is deployed to serve the users in five floors. Finally, it is found that the effect of the interference due to the uniformly distributed users within the macrocell around the femtocell is insignificant.

Resource allocation with interference mitigation in OFDMA femtocells for co-channel deploymenta

Femtocells have been considered as a promising technology to provide better indoor coverage and spatial reuse gains. However, the co-channel deployment of macrocells and femtocells is still facing challenges arising from potentially severe inter-cell interference. In this article, we investigate the uplink resource allocation problem of femtocells in co-channel deployment with macrocells. We first model the uplink power and subchannel allocation in femtocells as a non-cooperative game, where inter-cell interference is taken into account in maximizing the femtocell capacity and uplink femto-to-macro interference is alleviated by charging each femto user a price proportional to the interference that it causes to the macrocell. Based on the non-cooperative game, we then devise a semi-distributed algorithm for each femtocell to first assign subchannels to femto users and then allocate power to subchannels. Simulation results show that the proposed interference-aware femtocell uplink resource allocation algorithm is able to provide improved capacities for not only femtocells, but also the macrocell, as well as comparable or even better tiered fairness in the two-tier network, as compared with existing unpriced subchannel assignment algorithm and modified iterative water filling-based power allocation algorithm.

셀룰러 펨토 시스템에서 부하 분산을 통한 분산적 부채널 ON/OFF 스케쥴링 기법

셀룰러 펨토 시스템에서 펨토 기지국(f-BS: femto base station)은 좁은 영역에 중복 설치 및 과밀 설치될 수 있다. 이러한 불필요한 설치는 채널을 공유하는 인접 f-BS간 간섭문제를 야기하여서 시스템의 용량과 커버리지에 영향을 미칠 수 있다. 본 논문은 셀룰러 펨토 시스템에서 발생할 수 있는 이러한 성능하락 문제를 해결하기 위하여 강제 핸드오버를 이용한 부하분산과 확률적 자원 이용방법을 제시한다. 제안하는 기법은 중앙 컨트롤러의 조정이 아닌 이웃 f-BS간의 통신을 통한 분산적인 방법이며, f-BS가 주변 정보를 수집하여 스스로 과밀지역에 분포하였음을 인식하고 부하 및 자원 이용의 조절하는 방법을 포함한다. 평균 셀 수율, 사용자당 평균 수율을 바탕으로 제안하는 기법의 성능 향상을 모의실험을 통해 검증하였다. In cellular femto systems, femto Base stations(f-BSs) can be installed unnecessarily and overcrowded in small areas. This will cause an interference problem and it can impact on the capacity, blocking probability, and coverage of femtocells in the shared channel systems. In this paper, we propose a load distribution scheme by using forced handover and probabilistic subchannel scheduling policy to resolve the problem. The proposed scheme operates in distributed manner though communication with neighboring f-BSs, and includes self-detection of overcrowded area and radio resource management based on measurements. We evaluate the performance of the proposed scheme in terms of average cell throughput and average throughput per users.

Resource Allocation with Partitioning Criterion for Macro-Femto Overlay Cellular Networks with Fractional Frequency Reuse

The interference mitigation technique based on fractional frequency reuse (FFR) provides improved cell-edge performance with similar overall cell capacity as that of systems with the frequency reuse factor of one. Furthermore, frequency sub-band allocation by FFR has the benefit of allowing flexibility for the deployment of femto-cells through frequency partitioning. Determination of a proper frequency partitioning criterion between the cell-center and the cell-edge, and between the cells with femto-cells is an important issue. In addition, time resource partitioning introduces another degree of freedom to the design of time-frequency resource allocation. In this paper, we propose a novel time-frequency resource allocation mechanism using FFR for a macro-femto overlay cellular network. Feasible frequency sub-band and time resource is allocated to the cell-center and the cell-edge region in a cell by the proposed partitioning criterion and the time partitioning ratio. We provide a guideline for how to determine the partitioning criterion for the regions and how to design the amount of time resource. We derive the average capacity of macro-cells and femto-cells, and introduce a new harmonic mean metric to maximize the average capacity of the regions while achieving the fairness among users in a cell.