Capacity Analysis of LTE-Advanced HetNets with Reduced Power Subframes and Range Expansion

The time domain inter-cell interference coordination techniques specified in LTE Rel. 10 standard improves the throughput of picocell-edge users by protecting them from macrocell interference. On the other hand, it also degrades the aggregate capacity in macrocell because the macro base station (MBS) does not transmit data during certain subframes known as almost blank subframes. The MBS data transmission using reduced power subframes was standardized in LTE Rel. 11, which can improve the capacity in macrocell while not causing high interference to the nearby picocells. In order to get maximum benefit from the reduced power subframes, setting the key system parameters, such as the amount of power reduction, carries critical importance. Using stochastic geometry, this paper lays down a theoretical foundation for the performance evaluation of heterogeneous networks with reduced power subframes and range expansion bias. The analytic expressions for average capacity and 5th percentile throughput are derived as a function of transmit powers, node densities, and interference coordination parameters in a heterogeneous network scenario, and are validated through Monte Carlo simulations. Joint optimization of range expansion bias, power reduction factor, scheduling thresholds, and duty cycle of reduced power subframes are performed to study the trade-offs between aggregate capacity of a cell and fairness among the users. To validate our analysis, we also compare the stochastic geometry based theoretical results with the real MBS deployment (in the city of London) and the hexagonal-grid model. Our analysis shows that with optimum parameter settings, the LTE Rel. 11 with reduced power subframes can provide substantially better performance than the LTE Rel. 10 with almost blank subframes, in terms of both aggregate capacity and fairness.Comment: Submitted to EURASIP Journal on Wireless Communications and Networking (JWCN

Enhancements in spectrum management techniques for heterogeneous 5G future networks

Mención Internacional en el título de doctorIn the last decade, cellular networks are undergoing with a radical change in their basic design foundations. The huge increase in traffic demand requires a novel design of future cellular networks. Driven by this increase, a network densification phenomena is occurring thereby, which in turns requires to devise efficient and reliable mechanisms to deal with the interference problems resulting from such densification. The architecture and mechanisms resulting from such drastic re-design of the network are commonly referred under the term ’5G network’. In this context, this work unveils that current networking solutions are no longer sufficient to (i) provide the required network spectral efficiency, and (ii) guarantee the desired level of quality of experience from the user side. In order to address this problem, in this thesis we propose a novel SDN-like framework that incorporates the needed mechanisms to improve spectral efficiency while delivering the desired quality of experience to users. In particular, our architecture includes the following two approaches: Our first approach addresses the intercell interference issues resulting from high network densification. To this end, we propose novel mechanisms to mitigate the inter-cell interference problem. We address the design of such schemes from two angles: (i) a controller-aided mechanism, which gathers all the information of the network at a centralized point and, based on this information, optimally schedules the transmission from different users, and (ii) a semi-distributed mechanism, which limits the signaling overhead involved in sending the information to a centralized point while providing close to optimal performance. One of the key novelties of our scheduling algorithms is that they are based on the Almost Blank SubFrame (ABSF) scheme; indeed, this scheme has been standardized only recently and very little work has addressed the design of algorithm to use it. Our second approach addresses spectral efficiency from a complementary angle: cellular traffic offloading for content update applications. This approach leverages high user mobility to offload the cellular downlink traffic through a device-to-device communication. In this context, we propose an adaptive algorithm to decide how to optimally transmit content to base stations in order to maximize traffic offload. By relying on control theory techniques, our approach delivers near optimally performance. A third key contribution of this thesis is the design of a solution that combines the above two approaches. In particular, our solution takes into account that traffic offload is taking place in the network and addresses the design of an optimal scheduling algorithm that leverages on the Almost Blank SubFrame (ABSF) scheme. Indeed, the combination of these kind of approaches has received little attention from the literature. The feasibility and performance of the approaches described above are thoroughly evaluated and compared against state-of-the-art solutions through an exhaustive simulation campaign. Our results show that the proposed approaches outperform conventional eICIC techniques as well as standard offloading mechanisms, respectively, and confirm their feasibility in terms of overhead and computational complexity. To the best of our knowledge, this thesis is the first attempt to design an unified framework which is able to optimally perform offloading for content-update distribution applications while boosting the network performance in terms of spectral efficiency.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Pablo Serrano Yáñez-Mingot.- Secretario: Juan José Alacaraz Espín.- Vocal: Matteo Cesan

Spectrum Sharing, Latency, and Security in 5G Networks with Application to IoT and Smart Grid

The surge of mobile devices, such as smartphones, and tables, demands additional capacity. On the other hand, Internet-of-Things (IoT) and smart grid, which connects numerous sensors, devices, and machines require ubiquitous connectivity and data security. Additionally, some use cases, such as automated manufacturing process, automated transportation, and smart grid, require latency as low as 1 ms, and reliability as high as 99.99\%. To enhance throughput and support massive connectivity, sharing of the unlicensed spectrum (3.5 GHz, 5GHz, and mmWave) is a potential solution. On the other hand, to address the latency, drastic changes in the network architecture is required. The fifth generation (5G) cellular networks will embrace the spectrum sharing and network architecture modifications to address the throughput enhancement, massive connectivity, and low latency. To utilize the unlicensed spectrum, we propose a fixed duty cycle based coexistence of LTE and WiFi, in which the duty cycle of LTE transmission can be adjusted based on the amount of data. In the second approach, a multi-arm bandit learning based coexistence of LTE and WiFi has been developed. The duty cycle of transmission and downlink power are adapted through the exploration and exploitation. This approach improves the aggregated capacity by 33\%, along with cell edge and energy efficiency enhancement. We also investigate the performance of LTE and ZigBee coexistence using smart grid as a scenario. In case of low latency, we summarize the existing works into three domains in the context of 5G networks: core, radio and caching networks. Along with this, fundamental constraints for achieving low latency are identified followed by a general overview of exemplary 5G networks. Besides that, a loop-free, low latency and local-decision based routing protocol is derived in the context of smart grid. This approach ensures low latency and reliable data communication for stationary devices. To address data security in wireless communication, we introduce a geo-location based data encryption, along with node authentication by k-nearest neighbor algorithm. In the second approach, node authentication by the support vector machine, along with public-private key management, is proposed. Both approaches ensure data security without increasing the packet overhead compared to the existing approaches

실제 전파 환경을 반영한 이동통신 시스템의 최적화 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 8. 김성철.The 4th generation cellular systems, such as LTE (Long-Term Evolution) or LTEAdvanced, significantly improve the speed and the quality of data service as compared to the previous generation systems. In this situation, many applications generating a huge amount of mobile traffic (e.g., high definition (HD) video streaming or cloudbased storage services) have been widely spread. For this reason, the amount of mobile data traffic keeps increasing and sometimes even exceeds the capacity of the system. In order to accommodate explosively increasing mobile data traffic, service providers try to enhance the spatial reuse of wireless resources by deploying more base stations (BSs). Furthermore, small-sized BSs, such as pico and femto BSs, draw much attention as an economical and easy to deploy solution for relieving the load of macro BSs. In this dissertation, I investigate several strategies for optimizing the utilization of cellular systems. Especially, load balancing algorithms, which forcibly redirect users associated with a congested BS thereby experiencing low service quality to nearby BSs, are proposed. As a first step, I propose methods for predicting the service quality (or equivalently the long-term average throughput) of each individual user when multiple users share the same BS. During developing these algorithms, the time-varying characteristic of wireless channel due to multi-path propagation environment is considered to reflect real propagation environments. To this end, the fluctuation phenomenon of the received signal strength is expressed by a random variable, and then, two types of user throughput estimation schemes are developed. The proposed algorithms can be easily implemented in a practical system, and prediction errors are less than 10% for almost every case. Based on the proposed throughput estimation methods, I deal with a user association problem in multi-cell environments. At first, a centralized user association algorithm is developed, where a central node collects all the channel information between every BS and every user and then assigns an optimal base station to each individual user. However, transferring a lot of information to the central node requires excessive uplink feedback and backhaul usage. In addition, such overheads are increased with the density of BSs. For this reason, I propose a decentralized version of user association algorithm, where users themselves choose an optimal BS by considering not only their service quality but also network-wide utilization. The proposed decentralized algorithm especially can be compatible with heterogeneous cellular networks, where there are abundant BSs in the vicinity of each user. Finally, I study an inter-tier interference management problem between macro and small cell BSs in heterogeneous cellular networks. As the name indicates, small cell BSs are designed to consume much less power as compared to conventional macro BSs. For this reason, users associated with small cell BSs experience severe interference from macro BSs. To mitigate inter-tier interference, the eICIC (enhanced Inter Cell Interference Coordination) method was proposed. In this scheme, macro BSs periodically mute data transmission in order to guarantee the signal quality of users at the small cell BSs. In this dissertation, I try to optimize both user association and inter-tier interference management problems. As a result, users change their association and the system alters data transmission strategies in order to optimize network-wide utilization.Chapter 1 INTRODUCTION 1 Chapter 2 USER THROUGHPUT ESTIMATION FOR THE PF SCHEDULING ALGORITHM 5 2.1 Motivation 5 2.2 System Model 6 2.3 Throughput Estimation for a Single Antenna Scenario under the Rayleigh Fading Environment 9 2.4 Throughput Estimation for General Cases 13 2.4.1 Single User MIMO Scheduling Scenario 13 2.4.2 Multiuser MIMO Scheduling Scenario 14 2.5 Implementation Issues 15 2.6 Performance Evaluation and Discussion 16 2.6.1 Simulation Setup 16 2.6.2 Single Antenna Scenario 17 2.6.3 Multiple Antenna Scenario 20 Chapter 3 DYNAMIC USER ASSOCIATION IN MULTI-CELL CELLULAR NETWORKS 24 3.1 Motivation 24 3.2 System Model 25 3.3 Problem Formulation 27 3.3.1 Objective and Optimal Algorithm 27 3.3.2 User Association Problem 29 3.4 Centralized Dynamic User Association Algorithm 31 3.5 Performance Evaluation and Discussion 34 3.5.1 Simulation Setup 34 3.5.2 Throughput Estimation Error in Multi-cell Environments 36 3.5.3 Load Balancing Effect 37 Chapter 4 DECENTRALIZED USER ASSOCIATION METHOD IN HETEROGENEOUS CELLULAR NETWORKS 40 4.1 Motivation 40 4.2 System Model 41 4.3 Problem Formulation 43 4.4 Decentralized User Association Algorithm 44 4.4.1 Overview 44 4.4.2 User Scheduling and Throughput Estimation 46 4.4.3 Broadcast Signal Design 46 4.5 Fully Decentralized Algorithm 52 4.6 Performance Evaluation and Discussion 53 4.6.1 Simulation Setup 53 4.6.2 Unbalanced Traffic Intensity 54 4.6.3 Equal Traffic Intensity 59 4.6.4 Dynamic Scenarios 64 Chapter 5 JOINT OPTIMIZATION OF USER ASSOCIATION & INTER-TIER INTERFERENCE MANAGEMENT IN HETEROGENEOUS CELLULAR NETWORKS 68 5.1 Motivation 68 5.2 System Model 69 5.3 Problem Formulation 70 5.4 Joint Optimization Algorithm 72 5.5 Performance Evaluation and Discussion 74 5.5.1 Simulation Setup 74 5.5.2 Simulation Results 74 Chapter 6 CONCLUSION 80 Appendix 82 Appendix A Proof of Proposition 5.1 82 Appendix B Proof of Proposition 5.3 83 Abstract (In Korean) 93Docto