Managing interference in a network of macrocells underlaid with femtocells presents an important, yet challenging problem. A majority of spatial (frequency time) reuse based approaches partition the users based on coloring the interference graph, which is shown to be suboptimal. Some spatial time reuse based approaches schedule the maximal independent sets (MISs) in a cyclic, (weighted) round-robin fashion, which is inefficient for delay-sensitive applications. Our proposed policies schedule the MISs in a non-cyclic fashion, which aim to optimize any given network performance criterion for delay-sensitive applications while fulfilling minimum throughput requirements of the users. Importantly, we do not take the interference graph as given as in existing works; we propose an optimal construction of the interference graph. We prove that under certain conditions, the proposed policy achieves the optimal network performance. For large networks, we propose a low-complexity algorithm for computing the proposed policy. We show that the policy computed achieves a constant competitive ratio (with respect to the optimal network performance), which is independent of the network size, under wide range of deployment scenarios. The policy can be implemented in a decentralized manner by the users. Compared to the existing policies, our proposed policies can achieve improvement of up to 130 in large-scale deployments.
Besides the above two categories, there are several other related works. For instance in @cite_34 @cite_14 , the authors propose reinforcement learning and evolutionary learning techniques for the femtocells to learn efficient interference management policies. In @cite_34 , the femtocells learn the fixed transmit power levels, while in @cite_14 , the femtocells learn to randomize over different transmit power levels. However, the interference management policies in @cite_34 and @cite_14 cannot provide minimum throughput guarantees for the UEs. In constrast, we provide rigorous minimum throughput guarantees for the UEs. In both @cite_34 @cite_14 the femtocell UEs need to limit their transmission powers in every time slot such that the SINR of the macrocell UE is sufficiently high. If there is strong interference between some femtocells and the macrocell, the femtocell UEs will always transmit at lower power levels, leading to a low sum throughput for them.
@cite_14 @cite_34
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This paper proposes two interference mitigation strategies that adjust the maximum transmit power of femtocell users to suppress the cross-tier interference at a macrocell base station (BS). The open-loop and the closed-loop control suppress the cross-tier interference less than a fixed threshold and an adaptive threshold based on the noise and interference (NI) level at the macrocell BS, respectively. Simulation results show that both schemes effectively compensate the uplink throughput degradation of the macrocell BS due to the cross-tier interference and that the closed-loop control provides better femtocell throughput than the open-loop control at a minimal cost of macrocell throughput. In two-tier networks comprising a conventional cellular network overlaid with shorter range hotspots (e.g. femtocells, distributed antennas, or wired relays) with universal frequency reuse, the near-far effect from cross-tier interference creates dead spots where reliable coverage cannot be guaranteed to users in either tier. Equipping the macrocell and femtocells with multiple antennas enhances robustness against the near-far problem. This work derives the maximum number of simultaneously transmitting multiple antenna femtocells meeting a per-tier outage probability constraint. Coverage dead zones are presented wherein cross-tier interference bottlenecks cellular and femtocell coverage. Two operating regimes are shown namely 1) a cellular-limited regime in which femtocell users experience unacceptable cross-tier interference and 2) a hotspot-limited regime wherein both femtocell users and cellular users are limited by hotspot interference. Our analysis accounts for the per-tier transmit powers, the number of transmit antennas (single antenna transmission being a special case) and terrestrial propagation such as the Rayleigh fading and the path loss exponents. Single-user (SU) multiple antenna transmission at each tier is shown to provide significantly superior coverage and spatial reuse relative to multiuser (MU) transmission. We propose a decentralized carrier-sensing approach to regulate femtocell transmission powers based on their location. Considering a worst-case cell-edge location, simulations using typical path loss scenarios show that our interference management strategy provides reliable cellular coverage with about 60 femtocells per cell-site. This paper proposes a decentralized interference control scheme for an OFDMA (Orthogonal Frequency Division Multiple Access) cellular scenario where multiple macrocells and femtocells are deployed. In particular, we model the distributed resource allocation problem by means of a potential game, which is demonstrated to converge to a unique and pure Nash equilibrum. In this game, the femto base stations are the players, their actions are the resource blocks and the corresponding power levels to be allocated for downlink transmission, and the utility is designed to guarantee coexistence with the macro system, guaranteeing a fair tradeoff between femto and macro systems' performances. To do that, the utility function does not only consider the capacity of the femtocells, but also the different sources of inter-system interference: macrocell to femtocell, femtocell to femtocell, and femtocell to macrocell. The game is solved by applying a better response dynamic, which first selects the best resource blocks allocation policy for the femtousers, and then selects the most appropriate power levels for each resource block, through the solution of the corresponding convex optimization problem. Simulation results show that the introduction of femtocells in the scenario increases the total system capacity, and that the considered utility function provides an improvement in macro system performance of up to 40 , while reducing the femto capacity only up to 7 , with respect to the well known iterative waterfilling game. In a two tier cellular network - comprised of a central macrocell underlaid with shorter range femtocell hotspots - cross-tier interference limits overall capacity with universal frequency reuse. To quantify near-far effects with universal frequency reuse, this paper derives a fundamental relation providing the largest feasible cellular Signal-to-Interference-Plus-Noise Ratio (SINR), given any set of feasible femtocell SINRs. We provide a link budget analysis which enables simple and accurate performance insights in a two-tier network. A distributed utility- based SINR adaptation at femtocells is proposed in order to alleviate cross-tier interference at the macrocell from cochannel femtocells. The Foschini-Miljanic (FM) algorithm is a special case of the adaptation. Each femtocell maximizes their individual utility consisting of a SINR based reward less an incurred cost (interference to the macrocell). Numerical results show greater than 30 improvement in mean femtocell SINRs relative to FM. In the event that cross-tier interference prevents a cellular user from obtaining its SINR target, an algorithm is proposed that reduces transmission powers of the strongest femtocell interferers. The algorithm ensures that a cellular user achieves its SINR target even with 100 femtocells cell-site (with typical cellular parameters) and requires a worst case SINR reduction of only 16 at femtocells. These results motivate design of power control schemes requiring minimal network overhead in two-tier networks with shared spectrum. We address interference avoidance by resource partitioning in densely deployed femtocell networks. The main objective is to protect user equipments (UEs) that are located near the cell boundary of two or more femtocells from detrimental downlink interference. The available frequency bands are divided into subbands that are distributed among femtocells in a way that directly adjacent cells do not occupy the same subbands. For this purpose, a novel centrally controlled resource partitioning method is developed based on graph coloring that assigns subbands in terms of resource efficiency. The proposed algorithm strikes a balance between interference protection and spatial frequency reuse of subbands, and is well suited for randomly deployed wireless networks. System-level simulations reveal that cell edge capacities are significantly boosted without causing a degradation in average system throughput. In OFDMA systems adopting fractional frequency reuse, we can allocate orthogonal bandwidth to femtocells, which mitigates throughput degradation of macrocell users. In this paper, we discuss the optimal power allocation for femtocells with different orthogonal subbands, based on analysis of macrocell interferences. Recently, Long Term Evolution (LTE) has developed a femtocell for indoor coverage extension. However, interference problem between the femtocell and the macrocell should be solved in advance. In this paper, we propose an interference management scheme in the LTE femtocell systems using Fractional Frequency Reuse (FFR). Under the macrocell allocating frequency band by the FFR, the femtocell chooses sub-bands which are not used in the macrocell sub-area to avoid interference. Simulation results show that proposed scheme enhances total edge throughputs and reduces the outage probability in overall network, especially for the cell edge users. One of the effective techniques of improving the coverage and enhancing the capacity and data rate in cellular wireless networks is to reduce the cell size (i.e., cell splitting) and transmission distances. Therefore, the concept of deploying femtocells over macrocell has recently attracted growing interests in academia, industry, and standardization forums. Various technical challenges towards mass deployment of femtocells have been addressed in recent literature. Interference mitigation between neighboring femtocells and between the femtocell and macrocell is considered to be one of the major challenges in femtocell networks because femtocells share the same licensed frequency spectrum with macrocell. Further, the conventional radio resource management techniques for hierarchical cellular system is not suitable for femtocell networks since the positions of the femtocells are random depending on the users' service requirement. In this article, we provide a survey of the different state-of-the-art approaches for interference and resource management in orthogonal frequency-division multiple access (OFDMA)-based femtocell networks. A qualitative comparison among the different approaches is provided. To this end, open challenges in designing interference management schemes for OFDMA femtocell networks are discussed. The deployment of femtocells in a macrocell network is an economical and effective way to increase network capacity and coverage. Nevertheless, such deployment is challenging due to the presence of inter-tier and intra-tier interference, and the ad hoc operation of femtocells. Motivated by the flexible subchannel allocation capability of OFDMA, we investigate the effect of spectrum allocation in two-tier networks, where the macrocells employ closed access policy and the femtocells can operate in either open or closed access. By introducing a tractable model, we derive the success probability for each tier under different spectrum allocation and femtocell access policies. In particular, we consider joint subchannel allocation, in which the whole spectrum is shared by both tiers, as well as disjoint subchannel allocation, whereby disjoint sets of subchannels are assigned to both tiers. We formulate the throughput maximization problem subject to quality of service constraints in terms of success probabilities and per-tier minimum rates, and provide insights into the optimal spectrum allocation. Our results indicate that with closed access femtocells, the optimized joint and disjoint subchannel allocations provide the highest throughput among all schemes in sparse and dense femtocell networks, respectively. With open access femtocells, the optimized joint subchannel allocation provides the highest possible throughput for all femtocell densities. We introduce two mechanisms for interference mitigation, inspired by evolutionary game theory and machine learning to support the coexistence of a macrocell network underlaid with self-organized femtocell networks. In the first approach, stand-alone femtocells choose their strategies, observe the behavior of other players, and make the best decision based on their instantaneous payoff, as well as the average payoff of all other femtocells. We formulate the interactions among selfish femtocells using evolutionary games and demonstrate how the system converges to an equilibrium. In contrast, in the Reinforcement-Learning (RL) approach, information exchange among femtocells is no longer possible and hence each femtocell adapts its strategy and gradually learns by interacting with its environment (i.e., neighboring interferers) through trials-and-errors. Our investigations reveal that through learning, femtocells are able to self-organize by relying only on local information, while mitigating the interference towards the macrocell network. Besides, a trade-off exists where faster convergence is obtained in the evolutionary case as compared to the RL approach, at the expense of more side information. Finally, it is shown that femtocells face an interesting tradeoff of exploration versus exploitation in their learning processes. This paper investigates price-based resource allocation strategies for two-tier femtocell networks, in which a central macrocell is underlaid with distributed femtocells, all operating over the same frequency band. Assuming that the macrocell base station (MBS) protects itself by pricing the interference from femtocell users, a Stackelberg game is formulated to study the joint utility maximization of the macrocell and femtocells subject to a maximum tolerable interference power constraint at the MBS. Two practical femtocell network models are investigated: sparsely deployed scenario for rural areas and densely deployed scenario for urban areas. For each scenario, two pricing schemes: uniform pricing and non-uniform pricing, are proposed. The Stackelberg equilibriums for the proposed games are characterized, and an effective distributed interference price bargaining algorithm with guaranteed convergence is proposed for the uniform-pricing case. Numerical examples are presented to verify the proposed studies. It is shown that the proposed schemes are effective in resource allocation and macrocell protection for both the uplink and downlink transmissions in spectrum-sharing femtocell networks. Two-tier networks, comprising a conventional cellular network overlaid with shorter range hotspots (e.g. femtocells, distributed antennas, or wired relays), offer an economically viable way to improve cellular system capacity. The capacity-limiting factor in such networks is interference. The cross-tier interference between macrocells and femtocells can suffocate the capacity due to the near-far problem, so in practice hotspots should use a different frequency channel than the potentially nearby high-power macrocell users. Centralized or coordinated frequency planning, which is difficult and inefficient even in conventional cellular networks, is all but impossible in a two-tier network. This paper proposes and analyzes an optimum decentralized spectrum allocation policy for two-tier networks that employ frequency division multiple access (including OFDMA). The proposed allocation is optimal in terms of area spectral efficiency (ASE), and is subjected to a sensible quality of service (QoS) requirement, which guarantees that both macrocell and femtocell users attain at least a prescribed data rate. Results show the dependence of this allocation on the QoS requirement, hotspot density and the co-channel interference from the macrocell and femtocells. Design interpretations are provided. To successfully deploy femtocells overlaying the Macrocell as a two-tier that had been shown greatly benefiting communications quality in various manners, it requires to mitigate cross-tier interference between the Macrocell and femtocells, and intra-tier interference among femtocells, as well as to provide Quality-of-Service (QoS) guarantees. Existing solutions therefore assign orthogonal radio resources in frequency and spatial domains to each network, however, infeasible for dense femtocells deployments. It is also difficult to apply centralized resource managements facing challenges of scalability to the two-tier. Considering the infeasibility of imposing any modification on existing infrastructures, we leverage the cognitive radio technology to propose the cognitive radio resource management scheme for femtocells to mitigate cross-tier interference. Under such cognitive framework, a strategic game is further developed for the intra-tier interference mitigation. Through the concept of effective capacity, proposed radio resource management schemes are appropriately controlled to achieve required statistical delay guarantees while yielding an efficient radio resources utilization in femtocells. Performance evaluation results show that a considerable performance improvement can be generally achieved by our solution, as compared with that of state-of-the-art techniques, to facilitate the deployment of femtocells. With the exponential increase in high rate traffic given by a new generation of wireless devices, data is expected to overwhelm cellular network capacity in the near future. Femtocell networks have been recently proposed as an efficient and cost-effective approach to provide unprecedented levels of network capacity and coverage. However, the dense and random deployment of femtocells and their uncoordinated operation raise important questions concerning interference pollution and spectrum allocation. Motivated by the flexible subchannel allocation capabilities of cognitive radio, we propose a cognitive hybrid division duplex (CHDD) that is suitable for heterogeneous networks in future mobile communication systems. Specifically, our CHDD scheme has a pair of frequency bands to perform frequency division duplex (FDD) on the macrocell, while time division duplex (TDD) is simultaneously operated in these bands by underlaid cognitive femtocells. By doing so, the proposed CHDD scheme exploits the advantages of both FDD and TDD schemes: operating in FDD at the macrocell tier controls inter-tier interference, whereas operating in TDD at the femtocell tier provides to femtocells the flexibility of adjusting uplink and downlink rates together with opportunistic access benefits. Using tools from stochastic geometry, we provide a methodology on how to design efficient switching mechanisms for cognitive TDD operation of femtocells. In particular, we derive closed-form expressions for the success probability and the area spectral efficiency of the proposed CHDD scheme when the macro tier is in downlink and uplink mode. Furthermore, we propose an open access policy as a means to improve the performance of macrocell transmissions. Our analysis and numerical results show the effectiveness of introducing cognition in femtocells so as to improve the system performance of two-tier femtocell networks. In this paper, we propose a joint subchannel and power allocation algorithm for the downlink of an orthogonal frequency-division multiple access (OFDMA) mixed femtocell macrocell network deployment. Specifically, the total throughput of all femtocell user equipments (FUEs) is maximized while the network capacity of an existing macrocell is always protected. Towards this end, we employ an iterative approach in which OFDM subchannels and transmit powers of base stations (BS) are alternatively assigned and optimized at every step. For a fixed power allocation, we prove that the optimal policy in each cell is to give each subchannel to the user with the highest signal-to-interference-plus-noise ratio (SINR) on that subchannel. For a given subchannel assignment, we adopt the successive convex approximation (SCA) approach and transform the highly nonconvex power allocation problem into a sequence of convex subproblems. In the arithmetic-geometric mean (AGM) approximation, we apply geometric programming to find optimal solutions after condensing a posynomial into a monomial. On the other hand, logarithmic and d ifference-of-two- c oncave-functions (D.C.) approximations lead us to solving a series of convex relaxation programs. With the three proposed SCA-based power optimization solutions, we show that the overall joint subchannel and power allocation algorithm converges to some local maximum of the original design problem. While a central processing unit is required to implement the AGM approximation-based solution, each BS locally computes the optimal subchannel and power allocation for its own servicing cell in the logarithmic and D.C. approximation-based solutions. Numerical examples confirm the merits of the proposed algorithm. Two-tier femtocell networks- comprising a conventional cellular network plus embedded femtocell hotspots- offer an economically viable solution to achieving high cellular user capacity and improved coverage. With universal frequency reuse and DS-CDMA transmission however, the ensuing cross-tier interference causes unacceptable outage probability. This paper develops an uplink capacity analysis and interference avoidance strategy in such a two-tier CDMA network. We evaluate a network-wide area spectral efficiency metric called the operating contour (OC) defined as the feasible combinations of the average number of active macrocell users and femtocell base stations (BS) per cell-site that satisfy a target outage constraint. The capacity analysis provides an accurate characterization of the uplink outage probability, accounting for power control, path loss and shadowing effects. Considering worst case interference at a corner femtocell, results reveal that interference avoidance through a time-hopped CDMA physical layer and sectorized antennas allows about a 7x higher femtocell density, relative to a split spectrum two-tier network with omnidirectional femtocell antennas. A femtocell exclusion region and a tier selection based handoff policy offers modest improvements in the OCs. These results provide guidelines for the design of robust shared spectrum two-tier networks. In this paper, a novel framework is proposed to jointly optimize user association and resource allocation in the uplink cognitive femtocell network (CFN). In the considered CFN, femtocell base stations (FBSs) are deployed to serve a set of femtocell user equipments (FUEs) by reusing subchannels used in a macrocell base station (MBS). The problem of joint user association, subchannel assignment, and power allocation is formulated as an optimization problem, in which the goal is to maximize the overall uplink throughput while guaranteeing FBSs overloading avoidance, data rate requirements of the served FUEs, and MBS protection. To solve this problem, a distributed framework based on the matching game is proposed to model and analyze the interactions between the FUEs and FBSs. Using this framework, distributed algorithms are developed to enable the CFN to make decisions about user association, subchannel allocation, and transmit power. The algorithms are then shown to converge to a stable matching and exhibit a low computational complexity. Simulation results show that the proposed approach yields a performance improvement in terms of the overall network throughput and outage probability, with a small number of iterations to converge. Femtocells can effectively resolve the poor connectivity issue of indoor cellular users. This paper investigates the economic incentive for a cellular operator to add femtocell service on top of its existing macrocell service. We model the interactions between a cellular operator and users as a Stackelberg game: The operator first determines spectrum allocations and pricings of femtocell and macrocell services, and then heterogeneous users choose between the two services and the amount of resource to request. In the ideal case where the femtocell service has the same full spatial coverage as the macrocell service, we show that the operator will choose to provide femtocell service only, as this leads to a better user quality of service and a higher operator profit. However, if we impose the constraint that no users' payoffs decrease after introducing the femtocell service, then the operator will always continue providing the macrocell service (with or without the femtocell service). Furthermore, we study the impact of operational cost, limited coverage, and spatial reuse on femtocell service provision. As the operational cost increases, fewer users are served by femtocell service and the operator's profit decreases. When the femtocell service has limited spatial coverage, the operator always provides the macrocell service beside the femtocell service. However, when the coverage is high or the total resource is low, the operator will set the prices such that all users who can access femtocell will choose to use the femtocell service only. Finally, spatial reuse of spectrum will increase the efficiency of femtocell services and gives the operator more incentives to allocate spectrum to femtocells. OFDMA femtocells have been pointed out by the industry as a good solution not only to overcome the indoor coverage problem but also to deal with the growth of traffic within macrocells. However, the deployment of a new femtocell layer may have an undesired impact on the performance of the macrocell layer. The allocation of spectrum resources and the avoidance of electromagnetic interference are some of the more urgent challenges that operators face before femtocells become widely deployed. In this article a coverage and interference analysis based on a realistic OFDMA macro femtocell scenario is provided, as well as some guidelines on how the spectrum allocation and interference mitigation problems can be approached in these networks. Special attention is paid to the use of self-configuration and self-optimization techniques for the avoidance of interference. In this paper, the feasibility of user deployed femtocells in the same frequency band as an existing macrocell network is investigated. Key requirements for co-channel operation of femtocells such as auto-configuration and public access are discussed. A method for power control for pilot and data that ensures a constant femtocell radius in the downlink and a low pre-definable uplink performance impact to the macrocells is proposed, and the theoretical performance of randomly deployed femtocells in such a hierarchical cell structure is analysed for one example of a cellular UMTS network using system level simulations. The resulting impact on the existing macrocellular network is also investigated.