A survey of component carrier selection algorithms for carrier aggregation in long term evolution-advanced

Given that the demand for real-time multimedia contents that require significantly high data rate are getting of high popularity, a new mobile cellular technology known as Long term Evolution-Advanced (LTE-A) was standardized. The LTE-A is envisaged to support high peak data rate by aggregating more than one contiguous or non-contiguous Component Carriers (CCs) of the same or different frequency bandwidths. This paper provides a survey on the case where the LTE-A is working in backward compatible mode as well as when the system contains only LTE-A users. Note that the backward compatible mode indicates that the LTE-A contains a mixture of the legacy Long Term Evolution Release 8 (LTE) users that support packets (re)transmission on a single CC and the LTE-A users that are capable of utilizes more than one CCs for packets (re)transmission. It can be concluded from the study that the CC selection algorithms for newly-arrived LTE users can benefit from the channel diversity and the load status whereas the carrier aggregation that does not allocate all of the available CCs to the newly arrived LTE-A users shown to be more efficient

Joint spectrum sensing and access for stable dynamic spectrum aggregation

International audienc

Packet Scheduling Algorithms in LTE/LTE-A cellular Networks: Multi-agent Q-learning Approach

Spectrum utilization is vital for mobile operators. It ensures an efficient use of spectrum bands, especially when obtaining their license is highly expensive. Long Term Evolution (LTE), and LTE-Advanced (LTE-A) spectrum bands license were auctioned by the Federal Communication Commission (FCC) to mobile operators with hundreds of millions of dollars. In the first part of this dissertation, we study, analyze, and compare the QoS performance of QoS-aware/Channel-aware packet scheduling algorithms while using CA over LTE, and LTE-A heterogeneous cellular networks. This included a detailed study of the LTE/LTE-A cellular network and its features, and the modification of an open source LTE simulator in order to perform these QoS performance tests. In the second part of this dissertation, we aim to solve spectrum underutilization by proposing, implementing, and testing two novel multi-agent Q-learning-based packet scheduling algorithms for LTE cellular network. The Collaborative Competitive scheduling algorithm, and the Competitive Competitive scheduling algorithm. These algorithms schedule licensed users over the available radio resources and un-licensed users over spectrum holes. In conclusion, our results show that the spectrum band could be utilized by deploying efficient packet scheduling algorithms for licensed users, and can be further utilized by allowing unlicensed users to be scheduled on spectrum holes whenever they occur

New Methods of Efficient Base Station Control for Green Wireless Communications

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 이병기.This dissertation reports a study on developing new methods of efficient base station (BS) control for green wireless communications. The BS control schemes may be classified into three different types depending on the time scale — hours based, minutes based, and milli-seconds based. Specifically, hours basis pertains to determining which BSs to switch on or offminutes basis pertains to user equipment (UE) associationand milli-seconds basis pertains to UE scheduling and radio resource allocation. For system model, the dissertation considers two different models — heterogeneous networks composed of cellular networks and wireless local area networks (WLANs), and cellular networks adopting orthogonal frequency division multiple access (OFDMA) with carrier aggregation (CA). By combining each system model with a pertinent BS control scheme, the dissertation presents three new methods for green wireless communications: 1) BS switching on/off and UE association in heterogeneous networks, 2) optimal radio resource allocation in heterogeneous networks, and 3) energy efficient UE scheduling for CA in OFDMA based cellular networks. The first part of the dissertation presents an algorithm that performs BS switchingon/off and UE association jointly in heterogeneous networks composed of cellular networks and WLANs. It first formulates a general problem which minimizes the total cost function which is designed to balance the energy consumption of overall network and the revenue of cellular networks. Given that the time scale for determining the set of active BSs is much larger than that for UE association, the problem may be decomposed into a UE association algorithm and a BS switching on/off algorithm, and then an optimal UE association policy may be devised for the UE association problem. Since BS switching-on/off problem is a challenging combinatorial problem, two heuristic algorithms are proposed based on the total cost function and the density of access points of WLANs within the coverage of each BS, respectively. According to simulations, the two heuristic algorithms turn out to considerably reduce energy consumption when compared with the case where all the BSs are always turned on. The second part of the dissertation presents an energy-per-bit minimized radioresource allocation scheme in heterogeneous networks equipped with multi-homing capability which connects to different wireless interfaces simultaneously. Specifically, an optimization problem is formulated for the objective of minimizing the energy-per-bit which takes a form of nonlinear fractional programming. Then, a parametric optimization problem is derived out of that fractional programming and the original problem is solved by using a double-loop iteration method. In each iteration, the optimal resource allocation policy is derived by applying Lagrangian duality and an efficient dual update method. In addition, suboptimal resource allocation algorithms are developed by using the properties of the optimal resource allocation policy. Simulation results reveal that the optimal allocation algorithm improves energy efficiency significantly over the existing resource allocation algorithms designed for homogeneous networks and its performance is superior to suboptimal algorithms in reducing energy consumption as well as in enhancing network energy efficiency. The third part of the dissertation presents an energy efficient scheduling algorithm for CA in OFDMA based wireless networks. In support of this, the energy efficiency is newly defined as the ratio of the time-averaged downlink data rate and the time-averaged power consumption of the UE, which is important especially for battery-constrained UEs. Then, a component carrier and resource block allocation problem is formulated such that the proportional fairness of the energy efficiency is guaranteed. Since it is very complicated to determine the optimal solution, a low complexity energy-efficient scheduling algorithm is developed, which approaches the optimal algorithm. Simulation results demonstrate that the proposed scheduling scheme performs close to the optimal scheme and outperforms the existing scheduling schemes for CA.Abstract i List of Figures viii List of Tables x 1 Introduction 1 2 A Joint Algorithm for Base Station Operation and User Association in Heterogeneous Networks 7 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.4 UE Association Algorithm . . . . . . . . . . . . . . . . . . . . . . 14 2.5 BS Switching-on/off Algorithm . . . . . . . . . . . . . . . . . . . . 17 2.5.1 Cost Function Based (CFB) Algorithm . . . . . . . . . . . 19 2.5.2 AP Density Based (ADB) Algorithm . . . . . . . . . . . . 19 2.6 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . 20 2.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3 Energy-per-Bit Minimized Radio Resource Allocation in Heterogeneous Networks 27 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.2 System Model and Problem Formulation . . . . . . . . . . . . . . . 30 3.3 Parametric Approach to Fractional Programming . . . . . . . . . . 36 3.3.1 Parametric Approach . . . . . . . . . . . . . . . . . . . . . 37 3.3.2 Double-Loop Iteration to Determine Optimal θ . . . . . . . 38 3.4 Optimal Resource Allocation Algorithm . . . . . . . . . . . . . . . 39 3.4.1 Optimal Allocation of Subcarrier and Power . . . . . . . . . 41 3.4.2 Optimal Allocation of Time Fraction . . . . . . . . . . . . . 44 3.4.3 Lagrangian Multipliers Update Algorithm . . . . . . . . . . 48 3.5 Design of Suboptimal Algorithms . . . . . . . . . . . . . . . . . . 51 3.5.1 Time-Fraction Allocation First (TAF) Algorithm . . . . . . 51 3.5.2 Normalized Time-Fraction Allocation (NTA) Algorithm . . 53 3.6 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . 54 3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 4 Energy Efficient Scheduling for Carrier Aggregation in OFDMA Based Wireless Networks 68 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.3 Energy Efficiency Proportional Fairness (EEPF) Scheduling . . . . 74 4.4 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . 78 4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 5 Conclusion 87 5.1 Research Contributions . . . . . . . . . . . . . . . . . . . . . . . . 87 5.2 Future Research Directions . . . . . . . . . . . . . . . . . . . . . . 91 References 93Docto