The use of flying platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, is rapidly growing. In particular, with their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. On the one hand, UAVs can be used as aerial base stations to enhance coverage, capacity, reliability, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. In this paper, a comprehensive tutorial on the potential benefits and applications of UAVs in wireless communications is presented. Moreover, the important challenges and the fundamental tradeoffs in UAV-enabled wireless networks are thoroughly investigated. In particular, the key UAV challenges such as 3D deployment, performance analysis, channel modeling, and energy efficiency are explored along with representative results. Then, open problems and potential research directions pertaining to UAV communications are introduced. Finally, various analytical frameworks and mathematical tools, such as optimization theory, machine learning, stochastic geometry, transport theory, and game theory are described. The use of such tools for addressing unique UAV problems is also presented. In a nutshell, this tutorial provides key guidelines on how to analyze, optimize, and design UAV-based wireless communication systems.

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A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems

The use of flying platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, is rapidly growing. In particular, with their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. On the one hand, UAVs can be used as aerial base stations to enhance coverage, capacity, reliability, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. In this paper, a comprehensive tutorial on the potential benefits and applications of UAVs in wireless communications is presented. Moreover, the important challenges and the fundamental tradeoffs in UAV-enabled wireless networks are thoroughly investigated. In particular, the key UAV challenges such as three-dimensional deployment, performance analysis, channel modeling, and energy efficiency are explored along with representative results. Then, open problems and potential research directions pertaining to UAV communications are introduced. Finally, various analytical frameworks and mathematical tools such as optimization theory, machine learning, stochastic geometry, transport theory, and game theory are described. The use of such tools for addressing unique UAV problems is also presented. In a nutshell, this tutorial provides key guidelines on how to analyze, optimize, and design UAV-based wireless communication systems.

Cognitive small cell networks have been envisioned as a promising technique for meeting the exponentially increasing mobile traffic demand. Recently, many technological issues pertaining to cognitive small cell networks have been studied, including resource allocation and interference mitigation, but most studies assume non-cooperative schemes or perfect channel state information (CSI). Different from the existing works, we investigate the joint uplink subchannel and power allocation problem in cognitive small cells using cooperative Nash bargaining game theory, where the cross-tier interference mitigation, minimum outage probability requirement, imperfect CSI and fairness in terms of minimum rate requirement are considered. A unified analytical framework is proposed for the optimization problem, where the near optimal cooperative bargaining resource allocation strategy is derived based on Lagrangian dual decomposition by introducing time-sharing variables and recalling the Lambert-W function. The existence, uniqueness, and fairness of the solution to this game model are proved. A cooperative Nash bargaining resource allocation algorithm is developed, and is shown to converge to a Pareto-optimal equilibrium for the cooperative game. Simulation results are provided to verify the effectiveness of the proposed cooperative game algorithm for efficient and fair resource allocation in cognitive small cell networks.

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Resource Allocation for Cognitive Small Cell Networks: A Cooperative Bargaining Game Theoretic Approach

Summary form only given. The layered architecture is one of the key reasons behind the explosive and continuing growth of the Internet. There are, however, special networks in which cross-layer design is appropriate and may even be necessary. Two such cases are small wireless LAN and large-scale sensor networks. We consider first the design of medium access control (MAC) for a small wireless LAN based on a multiuser physical layer. We present a complete characterization of the throughput region and present conditions under which ALOHA is optimal. Next we consider the estimation of signal field using data collected from a large scale sensor network. The impact of medium access control on estimation is examined. We show that there exists a threshold on sensor outage probability above which a distributed random access protocol (such as ALOHA) outperforms the centralized deterministic schedulers.

On cross-layer design of wireless networks

Support of femtocells is an integral part of the Long Term Evolution - Advanced (LTE-A) system and a key enabler for its wide adoption in a broad scale. Femtocells are short-range, low-power and low-cost cellular stations which are installed by the consumers in an unplanned manner. Even though current literature includes various studies towards understanding the main challenges of interference management in the presence of femtocells, little light has been shed on the open issues of mobility management (MM) in the two-tier macrocell-femtocell network. In this paper, we provide a comprehensive discussion on the key aspects and research challenges of MM support in the presence of femtocells, with the emphasis given on the phases of a) cell identification, b) access control, c) cell search, d) cell selection/reselection, e) handover (HO) decision, and f) HO execution. A detailed overview of the respective MM procedures in the LTE-A system is also provided to better comprehend the solutions and open issues posed in real-life systems. Based on the discussion for the HO decision phase, we subsequently survey and classify existing HO decision algorithms for the two-tier macrocell-femtocell network, depending on the primary HO decision criterion used. For each class, we overview up to three representative algorithms and provide detailed flowcharts to describe their fundamental operation. A comparative summary of the main decision parameters and key features of selected HO decision algorithms concludes this work, providing insights for future algorithmic design and standardization activities.

Mobility Management for Femtocells in LTE-Advanced: Key Aspects and Survey of Handover Decision Algorithms

Femtocell is a small access point using the wire broadband connections or wireless technologies to access the mobile operator's network for the user equipment(UE), which can provide better indoor coverage and satisfy the upcoming demand of high data rate for wireless communication system.Femtocell related handover cost reduction is one of the important targets in LTE-Advanced SON (Self-Organising Networks). In this paper, a handover optimization algorithm based on the UE's mobility state is proposed. An analytical model was presented for the handover signalling cost analysis. Numerical results are provided to compare the signalling cost of different handover management schemes. The comparison between the proposed algorithm and the traditional handover control algorithm shows that the algorithms proposed in this paper have a signiﬁcant reduction in the signalling overhead.

Signalling Cost Evaluation of Handover Management Schemes in LTE-Advanced Femtocell

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

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

Video applications such as video-on-demand and videoconferencing over wireless networks require system resources to be allocated dynamically and optimally in accordance with the time-varying environment and video contents. User-perceived quality is tending to be a crucial factor in evaluating the success of video applications. The aim of this paper is to propose a cross-layer design scheme for optimizing resource allocation of video applications over Long Term Evolution (LTE) networks based on Quality of Experience (QoE) evaluation. We propose a novel mapping model between Peak Signal-to-Noise Ratio (PSNR) and Mean Opinion Score (MOS) based on a hyperbolic tangent function, which can reflect the relation between objective system parameters and subjective perceived quality simply and precisely. The cross-layer architecture presented in this paper jointly optimizes the Application (APP) layer, the Media Access Control (MAC) layer and the Physical (PHY) layer of the wireless protocol stack. On the basis of this architecture, we present a QoE prediction function and utilize the Particle Swarm Optimization (PSO) method to solve the resource allocation problem. Simulation results show that the proposed scheme significantly outperforms the traditional scheduling scheme in terms of maximizing user-perceived quality as well as maintaining fairness among users.

QoE-based cross-layer design for video applications over LTE

Femtocells, combined with orthogonal frequency division multiple access (OFDMA), can improve cellular coverage and offload traffics from existing macrocells. However, the co-channel deployment of femtocells is still facing challenges arising from potentially severe co-channel interference in dense femtocells. In this paper, we investigate the uplink power allocation problem in dense deployed femtocells. We first model the uplink power allocation in femtocells as a non-cooperative game, where co-channel interference is taken into account in maximizing the femtocell capacity and uplink femto-to-femto interference is alleviated by charging each femto user a price proportional to the signal to interference and noise ratio (SINR). Based on the non-cooperative game, we then devise a distributed power allocation algorithm with differentiated pricing update. Simulation results show that the proposed power allocation algorithm is not only able to provide improved capacities for femtocells, but also can improve users' fairness, as compared with existing unpriced water filling power allocation algorithm.

Differentiated-pricing based power allocation in dense femtocell networks

The invention relates to a novel radio network architecture, called G-RAN (green-radio access network) which realizes energy conservation and consumption reduction by re-designing the traditional network architecture in the further mobile communication network. Aiming at reducing the number of machine rooms of a base station, reducing energy consumption and improving spectrum efficiency, on the basis of the key technologies such as centralized base-band processing, virtual base station, base station coordination, dynamic network architecture and the like, and combining with resource sharing and network dynamic scheduling, the G-RAN is proposed to realize low-cost, high-bandwidth and high-flexibility operation. The radio network architecture introduces a series of new technologies and processes such as distributed base station, base station virtualization, centralized processing and the like, and promotes the improvement of energy utilization efficiency of the industry.

Wenmin Ma

Papers

Signalling Cost Evaluation of Handover Management Schemes in LTE-Advanced Femtocell

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

QoE-based cross-layer design for video applications over LTE

Differentiated-pricing based power allocation in dense femtocell networks

Novel radio access network method and system based on G-RAN (green-radio access network)