Distributed Interference-Aware Energy-Efficient Resource Allocation for Device-to-Device Communications Underlaying Cellular Networks

The introduction of device-to-device (D2D) into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of user equipments (UEs). In this paper, we propose a distributed interference-aware energy-efficient resource allocation algorithm to maximize each UE's energy efficiency (EE) subject to its specific quality of service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. The formulated EE maximization problem is a non-convex problem and is transformed into a convex optimization problem by exploiting the properties of the nonlinear fractional programming. An iterative optimization algorithm is proposed and verified through computer simulations.Comment: 6 pages, 3 figures, IEEE GLOBECOM 201

Energy Efficiency and Spectral Efficiency Tradeoff in Device-to-Device (D2D) Communications

In this letter, we investigate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in device-to-device (D2D) communications underlaying cellular networks with uplink channel reuse. The resource allocation problem is modeled as a noncooperative game, in which each user equipment (UE) is self-interested and wants to maximize its own EE. Given the SE requirement and maximum transmission power constraints, a distributed energy-efficient resource allocation algorithm is proposed by exploiting the properties of the nonlinear fractional programming. The relationships between the EE and SE tradeoff of the proposed algorithm and system parameters are analyzed and verified through computer simulations.Comment: 8 pages, 6 figures, long version paper of IEEE Wireless Communications Letters, accepted for publication. arXiv admin note: text overlap with arXiv:1405.196

A Game-Theoretic Approach to Energy-Efficient Resource Allocation in Device-to-Device Underlay Communications

Despite the numerous benefits brought by Device-to-Device (D2D) communications, the introduction of D2D into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of User Equipments (UEs). Most of the previous studies mainly focus on how to maximize the Spectral Efficiency (SE) and ignore the energy consumption of UEs. In this paper, we study how to maximize each UE's Energy Efficiency (EE) in an interference-limited environment subject to its specific Quality of Service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. A distributed interference-aware energy-efficient resource allocation algorithm is proposed by exploiting the properties of the nonlinear fractional programming. We prove that the optimum solution obtained by the proposed algorithm is the Nash equilibrium of the noncooperative game. We also analyze the tradeoff between EE and SE and derive closed-form expressions for EE and SE gaps.Comment: submitted to IET Communications. arXiv admin note: substantial text overlap with arXiv:1405.1963, arXiv:1407.155

Energy Efficient Power Allocation for Distributed Antenna System over Shadowed Nakagami Fading Channel

In this paper, the energy efficiency (EE) of downlink distributed antenna system (DAS) with multiple receive antennas is investigated over composite fading channel that takes the path loss, shadow fading and Nakagami-m fading into account. Our aim is to maximize EE which is defined as the ratio of the transmission rate to the total consumed power under the constraints of maximum transmit power of each remote antenna. According to the definition of EE and using the upper bound of average EE, the optimized objective function is provided. Based on this, utilizing Karush-Kuhn-Tucker (KKT) conditions and mathematical derivation, a suboptimal energy efficient power allocation (PA) scheme is developed, and closed-form PA coefficients are obtained. The developed scheme has the EE performance close to the existing optimal scheme. Moreover, it has relatively lower complexity than the existing scheme because only the statistic channel information and less iteration are required. Besides, it includes the scheme in composite Rayleigh channel as a special case. Simulation results show the effectiveness of the developed scheme

Distributed energy efficient channel allocation in underlay multicast D2D communications

In this paper, we address the optimization of the energy efficiency of underlay multicast device-to-device (D2MD) communications on cellular networks. In particular, we maximize the energy efficiency of both the global network and the individual users considering various fairness factors such as maximum power and minimum rate constraints. For this, we employ a canonical mixed-integer non-linear formulation of the joint power control and resource allocation problem. To cope with its NP-hard nature, we propose a two-stage semi-distributed solution. In the first stage, we find a stable, yet sub-optimal, channel allocation for D2MD groups using a cooperative coalitional game framework that allows co-channel transmission over a set of shared resource blocks and/or transmission over several different channels per D2MD group. In the second stage, a central entity determines the optimal transmission power for each user in the system via fractional programming. We performed extensive simulations to analyze the resulting energy efficiency and attainable transmission rates. The results show that the performance of our semi-distributed approach is very close to that obtained with a pure optimal centralized one.Ministerio de Ciencia, Innovación y Universidades | Ref. GO2EDGERED2018-102563-TAgencia Estatal de Investigación | Ref. TEC2017-85587-RAgencia Estatal de Investigación | Ref. RED2018-102563-

Resource Allocation for Next Generation Radio Access Networks

Driven by data hungry applications, the architecture of mobile networks is moving towards that of densely deployed cells where each cell may use a different access technology as well as a different frequency band. Next generation networks (NGNs) are essentially identified by their dramatically increased data rates and their sustainable deployment. Motivated by these requirements, in this thesis we focus on (i) capacity maximisation, (ii) energy efficient configuration of different classes of radio access networks (RANs). To fairly allocate the available resources, we consider proportional fair rate allocations. We first consider capacity maximisation in co-channel 4G (LTE) networks, then we proceed to capacity maximisation in mixed LTE (including licensed LTE small cells) and 802.11 (WiFi) networks. And finally we study energy efficient capacity maximisation of dense 3G/4G co-channel small cell networks. In each chapter we provide a network model and a scalable resource allocation approach which may be implemented in a centralised or distributed manner depending on the objective and network constraints