다이나믹 펨토셀 네트워크에서 커버리지와 데이터 부하 균형을 고려한 기지국의 파워 조절 분산 알고리즘

Dynamic sleeping of base stations under off-peak time is an efficient way to reduce the energy consumption of cellular networks. However, traffic in femtocell networks is always under fluctuation, which leads to the high complexity of the existing sleeping approaches. To overcome this problem, in this paper a traffic prediction based sleeping (TPBS) mechanism with low complexity is proposed in femtocell networks. Artificial neural network (ANN) model is used to predict future traffic in each base station. Then based on prediction results, we propose a dynamic base station switching algorithm with low complexity, where base station can be switched off/on dynamically according to the traffic in real time. We show that this approach can minimize the number of active base stations while providing a satisfying service with low blocking probability to all users and, at the same time, the algorithm complexity is low compared with the Markov Decision Process (MDP) based sleeping method. Simulation results are used to evaluate the performance of our schemes considering energy saving and algorithm complexity.

The deployment of femtocell is as a potential solution to improving the indoor coverage and capacity of a cellular network. However, providing quality of service (QoS) is one of the most significant challenges in wireless femtocell networks. Cellular users with different QoS requirements always look for a serving base station (BS) to achieve their desired QoS. Therefore, intelligent BS allocation plays a crucial role in guaranteeing the QoS. In this paper, we propose a game-theoretic BS allocation approach with a QoS guarantee for downlink femtocell networks. We model the BS allocation problem as an evolutionary game in which users with bounded rationality learn from the environment and make BS selection decisions with minimum exchange of information. In the propounded model, not only do we consider the users’ QoS, but we also take account of macro users’ activity as an interferer to reduce the cross-tier interference. Unlike the previous studies, we calculate the demand rejection probability for each user associated with a BS to evaluate statistical QoS guarantees. A distributed learning-based algorithm is developed to show the existence and fairness of the solution to our proposed model and to demonstrate the convergence to the evolutionary equilibrium as the solution of the game. Simulation results verify the effectiveness, performance improvement, and good convergence of the proposed approach.

In the last decade, drones became frequently used to provide eye-in-the-sky overview in the outdoor environment. Their main advantage compared to the other types of robots is that they can fly above obstacles and rough terrains and they can quickly cover large areas. These properties also open a new application; drones could provide a multi-hop, line of sight communication for groups of ground users. The aim of this thesis is to develop a drone team that will establish wireless ad-hoc network between users on the ground and distributively adapt links and spatial arrangement to the requirements and motion of the ground users. For this application, we use fixed wing drones. Such platforms can be easily and quickly deployed. Fixed wing drones have higher forward speed and higher battery life than hovering platforms. On the other hand, fixed wing drones have unicycle dynamics with constrained forward speed which makes them unable to hover or perform sharp turns. The first challenge consists in bridging unicycle dynamics of the fixed wing drones. Some control strategies have been proposed and validated in simulations using the average distance between the target and the drone as a performance metric. However, besides the distance metric, energy expenditure of the flight also plays an important role in assessing the overall performance of the flight. We propose a new methodology that introduces a new metric (energy expenditure), we compare existing methods on a large set of target motion patterns and present a comparison between the simulation and field experiments on proposed target motion patterns. The second challenge consists in developing a formation control algorithm that will allow fixed wing robots to provide a wide area coverage and to relay data in a wireless ad-hoc network. In such applications fixed wing drones have to be able to regulate an inter-drone distance. Their reduced maneuverability presents the main challenge to design a formation algorithm that will regulate an inter-drone distance. To address this challenge, we present a distributed control strategy that relies only on local information. Each drone has its own virtual agent, it follows the virtual agent by performing previously evaluated and selected target tracking strategy, and flocking interaction rules are implemented between virtual agents. It is shown in simulation and in field experiments with a team of fixed wing drones that using this distributed formation algorithm, drones can cover an area by creating an equilateral triangular lattice and regulate communication link quality between neighboring drones. The third challenge consists in allowing connectivity between independently moving ground users using fixed wing drone team. We design two distributed control algorithms that change drones' spatial arrangement and interaction topology to maintain the connectivity. We propose a potential field based strategy which adapts distance between drones to shrink and expand the fixed wing drones' formation. In second approach, market-based adaptation, drones distributively delete interaction links to expand the formation graph to a tree graph. In simulations and field experiments we show that our proposed strategies successfully maintain independently moving ground users connected. Overall, this thesis presents synthesis of distributed algorithms for fixed wing drones to establish and maintain wireless ad-hoc communication networks.

Stackelberg game for backhaul resource allocation in the two-tier LTE femtocell networks

Driven by the emerging demands of enhancing the indoor coverage, the network capacity and users’ service experience, small scaled femtocell networks will be implemented extensively in home, office and hotspots, which can provide substantial benefits for both operators and users, such as the capital expenditures (CAPEX) and the operational expenditures (OPEX) reduction, the easy plug-and-play (PnP) deployment. Due to users’ random-deployed manner indoors, femto base station (FBS) should have cognitive abilities, such as the position awareness, the automatic parameter tuning and the learning ability, in order to self-optimize its indoor coverage and minimize the unexpected interference outdoors. In contrast to the traditional static power allocation algorithm, the FBS has applied the dynamic power allocation scheme to minimize the interference to macro base station (MBS) and macro user equipment (MUE) by considering the path loss under different wall penetration conditions. Based on the position awareness ability, the optimal coverage radii for FBS indoors are proposed and proved by closed-form formulas at typical positions, which were not considered before. To further enable the intelligent coverage self-optimization for the random-deployed FBS indoors, a joint dynamic power allocation and antenna pattern selection scheme has been proposed based on the Artificial Neural Network (ANN) with training and self-tuning abilities. Numerous results prove both the effectiveness and the accuracy of the proposed coverage self-optimization scheme for the random-deployed femtocell networks.KeywordsCognitive Femtocell NetworkArtificial Neural NetworkCoverage Self-optimization

In a conventional cellular network, a terminal receives signals not only from the base station of that cell, but also from other cell base stations. This inter-cell interference has more impact on the cell-edge users, in multi cell environment. The inter-cell interference degrades the performance of wireless systems. Using Base Station Cooperation, the ability of a mobile station to receive signals from multiple base stations can be utilized as an opportunity to improve the spectral efficiency and to get higher data rates for cell edge users. In multi cell environment using base station cooperation overall interference can be minimized marginally, whereas the interference within the cooperation region is largely reduced. This leads to a question whether it is worth doing cooperation all the time. However increase in terms of throughput may not always be enough to increase the throughput of each of the user .Hence for such a scenario the distinct cooperation scheme is used. The distinct cooperation is a joint transmission scheme in which the selection criterion is based on user’s signal to interference plus noise ratio (SINR) is proposed and the capacity achieved through cooperation is shared equally among the cell-edge users. Here we will analyze the normal operation, full cooperation and distinct cooperation scheme in the downlink environment for cell edge users in cellular network and we will compare and see which method improves the user capacity and data rate.KeywordsCooperative transmissionfull cooperationDistinct cooperationsignal to interference plus noise ratio (SINR)

The cellular network systems are expected to evolve into Multi-hop Cellular Network (MCN). While a mobile terminal and the base station have a direct connection in a conventional cellular network, in MCN a mobile terminal may reach the base station via relays by using multi-hopping. The relay can be either mobile terminal referred to client relay or dedicated relay referred to infra relay that has capabilities like those of the base station. In this paper, we focus on routing mechanism in multi-hop cellular networks. In particular, we study routing performance metrics for multi-hop cellular networks which consider energy efficiency and the relay capabilities.

Femtocell architecture involves the use of two separate layers—the macrocell and femtocell layers. In this architecture, the former is the conventional cellular network, whereas the latter incorporates a range of shorter range cells. Femtocells are designed to coexist alongside macrocells, providing spatial frequency reuse, higher spectrum efficiency, and cover areas where macrocells cannot. Femtocells positioned in the macrocell considerably improve the indoor coverage and provide better user experience. However, interference between the two layers is imminent; therefore, ways to manage it must be employed to efficiently avoid problems such as coverage holes in the macrocells. Essential limits of capacity and attainable data rates also mainly depend on the interference faced by a femtocell network. Recently, cognitive radio (CR), which has the ability to sense its environment and accordingly alter its characteristics, e.g., transmission parameters, has been merged with femtocells to exploit the capabilities of the former in the latter. CR-enabled femtocells in a two-tier network can sense the environment and opportunistically allocate both licensed and unlicensed frequency bands to user equipments to avoid interference. This paper examines interference mitigation in femtocells using CR and provides comprehensive survey of different CR-enabled interference mitigation schemes. Presented schemes such as power control, spectrum access, antenna, and joint schemes are classified before they are compared for pros and cons. Finally, tradeoffs and cost of using CR in femtocells are highlighted with some insight into future research issues and challenges.

Multi-hop heterogeneous cellular networks (MHCNs) consist of conventional macro cellular networks overlaid with an irregular deployment of low-power base stations (BSs), where the communication between BSs and mobile users can be established through a single hop or multiple hops. By modeling different kinds of randomly located BSs as K tiers of independent homogeneous Poisson Point Processes, we first explore the capacity of downlink MHCNs and derive the expression of capacity under Rayleigh fading channels. Particularly, the capacity gain achieved by cell splitting and multi-hop relaying is quantified for the first time. We then study the effects of BS density, transmit power, and signal-to-interference-plus-noise-ratio (SINR) threshold on the capacity of MHCNs. More importantly, we obtain the spectral efficiency enhancement condition under which the increase of BS density and transmit power improve the spectral efficiency, thereby enhancing the capacity. One interesting observation is that at a given SINR threshold, the capacity increases with BS density when all the tiers have the same SINR threshold. Moreover, the capacity of some special networks (i.e., heterogeneous cellular networks, multi-hop cellular networks, and conventional cellular networks) are derived directly by specializing some system parameters in our results. Finally, numerical studies and simulations are conducted to validate our analysis.

This paper explores the fundamental downlink performance limits of multicell networks when cooperation is allowed between all the base station in the network. Toward this end, we infer the asymptotic sum rate of a capacity-achieving technique (known as dirty paper coding) for the broadcast channel in the limit of a large number of transmit antennas and single-antenna users. The users have unequal SNRs characterized by a doubly-regular gain matrix and we show that this condition can be satisfied in a finite cellular network of hexagonal cells where users are placed on corners of hexagons centered on the bases. Under this placement, we can compute the asymptotic rate per user when dirty paper coding is used across base stations in a coordinated network. We extend the analysis to an infinite coordinated network and show that its performance is lower-bounded by that of a single isolated cell. Performance comparisons are also made with conventional cellular networks where coordination among bases is not allowed.

To deal with challenges of enhanced user density, high data rate demand and coverage, conventional macro cellular network architecture is evolving to irregular and complex Heterogeneous Networks (HetNets) through dense deployment of low power Base Stations (BSs) such as pico and femto BSs. Various parameters and their effects are considered while analyzing the performance of HetNets. In this paper we investigate the impact of macro and pico BSs separation on the network performance. We consider picocell within the association region of a macrocell and investigate the association region of picocell, average rate, and Energy Efficiency (EE) of the network. The results show that network performance is improved with increase in macro and pico BSs separation within the association region of a macrocell.

In recent years, wireless industries have adopted femtocell networks for enhancing indoor coverage and quality of service. In the femtocell networks, it is an important issue to achieve much more revenue with the limited spectrum resource. The macrocell base station (MBS) owns all available resource, and femtocell base stations (FBSs) own no spectrum and want to rent spectrum from the MBS. This paper proposes an auction-based pricing scheme to investigate the spectrum leasing problem in the scenario with a central macrocell and multiple femtocells. We model the spectrum leasing procedure between MBS and FBSs as an auction that aims at motivating the MBS to lease its spectrum resource. All FBSs act as the bidders and the monopolist MBS acts as the auctioneer. In this auction, FBSs submit their bids to rent spectrum resources so that they can make profit by selling them to their subscribers, while the MBS determines the spectrum leasing amount and chooses the winner FBSs. In this paper, we focus on spectrum pricing scheme and revenue maximization of the MBS. Simulation results show that the proposed scheme provides effective motivation for the MBS to lease spectrum to FBSs and both the MBS and FBSs can benefit from spectrum leasing.

The exponential increase in high rate traffic driven by the new generation of wireless services is expected to overload cellular network capacity in the near future. Femtocell networks have recently been proposed as an efficient and cost-effective solution to enhance cellular network capacity and coverage. However, dense and unplanned deployment of new Base Stations (BSs) and their uncoordinated operation may increase the system power consumption and rise co-channel interference. Thus, efficient schemes are essential for managing femtocell activity and improving the system performance. Classical cell switch off and discontinuous transmission (DTX) algorithms aim at improving the network Energy Efficiency (EE) in lightly loaded scenarios. In this paper, we propose a novel multi-cell architecture for Open Access femtocell networks, which also enables energy saving at medium and high loads without compromising the end-user performance.

On distributed power control in full duplex wireless networks

With the rapid increase in data traffic and high data rate demands from cellular users, conventional cellular networks are becoming insufficient to fulfill these requirements. Femto cells are integrated in macro cellular network to increase the capacity, coverage, and to fulfill the increasing demands of the users. Time required for handoff process between the cells became more sensitive and complex with the introduction of femto cells in the network. Public internet which connect the femto base station with the mobile core network induces higher latency if conventional handoff procedures are also employed in macro-femto cell network. So, handoff process will become slower and network operation will become insufficient. Some standards, procedures, and protocols should be defined for macro-femto cell network rather than using existing protocols. This chapter presents a comprehensive survey of handoff process, types of handoff in macro-femto cell network, and proposed methods and schemes for frequent and unnecessary handoff reduction for efficient network operation.