Optimal User Association in Multi-user MIMO Small Cell Networks

International audience—Dense Networks and large MIMO are two key enablers to achieve high data rates towards next generation 5G networks. In this context, we study user association in an interference limited Multiuser MIMO Small Cell Network. Extending on our previous findings, we derive explicit expressions for the optimal ratio of the number of antennas at the base station to the number of users that can associate to a base station in such a Network. This expressions are used to compute the actual number of users that can associate for a given interference level and other system parameters. Simulation results and numerical examples are provided to support our theoretical findings

Harmonized Cellular and Distributed Massive MIMO: Load Balancing and Scheduling

Multi-tier networks with large-array base stations (BSs) that are able to operate in the "massive MIMO" regime are envisioned to play a key role in meeting the exploding wireless traffic demands. Operated over small cells with reciprocity-based training, massive MIMO promises large spectral efficiencies per unit area with low overheads. Also, near-optimal user-BS association and resource allocation are possible in cellular massive MIMO HetNets using simple admission control mechanisms and rudimentary BS schedulers, since scheduled user rates can be predicted a priori with massive MIMO. Reciprocity-based training naturally enables coordinated multi-point transmission (CoMP), as each uplink pilot inherently trains antenna arrays at all nearby BSs. In this paper we consider a distributed-MIMO form of CoMP, which improves cell-edge performance without requiring channel state information exchanges among cooperating BSs. We present methods for harmonized operation of distributed and cellular massive MIMO in the downlink that optimize resource allocation at a coarser time scale across the network. We also present scheduling policies at the resource block level which target approaching the optimal allocations. Simulations reveal that the proposed methods can significantly outperform the network-optimized cellular-only massive MIMO operation (i.e., operation without CoMP), especially at the cell edge

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

Joint Power Allocation and User Association Optimization for Massive MIMO Systems

This paper investigates the joint power allocation and user association problem in multi-cell Massive MIMO (multiple-input multiple-output) downlink (DL) systems. The target is to minimize the total transmit power consumption when each user is served by an optimized subset of the base stations (BSs), using non-coherent joint transmission. We first derive a lower bound on the ergodic spectral efficiency (SE), which is applicable for any channel distribution and precoding scheme. Closed-form expressions are obtained for Rayleigh fading channels with either maximum ratio transmission (MRT) or zero forcing (ZF) precoding. From these bounds, we further formulate the DL power minimization problems with fixed SE constraints for the users. These problems are proved to be solvable as linear programs, giving the optimal power allocation and BS-user association with low complexity. Furthermore, we formulate a max-min fairness problem which maximizes the worst SE among the users, and we show that it can be solved as a quasi-linear program. Simulations manifest that the proposed methods provide good SE for the users using less transmit power than in small-scale systems and the optimal user association can effectively balance the load between BSs when needed. Even though our framework allows the joint transmission from multiple BSs, there is an overwhelming probability that only one BS is associated with each user at the optimal solution.Comment: 16 pages, 12 figures, Accepted by IEEE Trans. Wireless Commu