COMPARATIVE ANALYSIS OF USER-CELL ASSOCIATION METHODS FOR MILIMETER WAVE MASSIVE MIMO BY DEVELOPING A SYSTEM LEVEL SIMULATOR FOR HETNETS

Massive multiple-input-multiple-output (MIMO) base station deployments and millimeter wave (mmWave) spectrum utilization have been identified as promising disruptive technologies, along with ultra-dense Heterogeneous Networks (UDHNs) to meet the exponential data requirement of the next generation cellular networks. With the proliferation of UDHNs, optimal user-cell association in cellular networks, which is a well-known open problem, will be exacerbated due to the power differential of macro and small cells. This study investigates the user-cell association problem for ultra-dense two-tier networks with massive MIMO deployment and small cells operating in mmWave spectrum. The association problem is modeled as a convex utility maximization problem, adapted from [11], and is a function of the user throughput. The problem is solved through a centralized subgradient algorithm. Additionally, a game theoretical user-centric distributed load balancing algorithm, inspired from [32], where each user chooses its serving base station to maximize its user throughput selfishly, is also evaluated. Moreover, these adapted algorithms are compared against smallest pathloss and maximum downlink data rate association methods and it is demonstrated via extensive simulations that both the centralized and user-centric approaches almost equally outperform the smallest pathloss and maximum downlink data rate association methodologies in terms of user throughput and cell load distribution. The results exhibit average throughput gains between 20% and 40% for the majority of users if massive MIMO UDHN deployments are operated in the mmWave spectrum as compared to existing sub-6 GHz bands under the optimal user-cell association schemes

Unified and Distributed QoS-Driven Cell Association Algorithms in Heterogeneous Networks

This paper addresses the cell association problem in the downlink of a multi-tier heterogeneous network (HetNet), where base stations (BSs) have finite number of resource blocks (RBs) available to distribute among their associated users. Two problems are defined and treated in this paper: sum utility of long term rate maximization with long term rate quality of service (QoS) constraints, and global outage probability minimization with outage QoS constraints. The first problem is well-suited for low mobility environments, while the second problem provides a framework to deal with environments with fast fading. The defined optimization problems in this paper are solved in two phases: cell association phase followed by the optional RB distribution phase. We show that the cell association phase of both problems have the same structure. Based on this similarity, we propose a unified distributed algorithm with low levels of message passing to for the cell association phase. This distributed algorithm is derived by relaxing the association constraints and using Lagrange dual decomposition method. In the RB distribution phase, the remaining RBs after the cell association phase are distributed among the users. Simulation results show the superiority of our distributed cell association scheme compared to schemes that are based on maximum signal to interference plus noise ratio (SINR)

Cell Selection in Wireless Two-Tier Networks: A Context-Aware Matching Game

The deployment of small cell networks is seen as a major feature of the next generation of wireless networks. In this paper, a novel approach for cell association in small cell networks is proposed. The proposed approach exploits new types of information extracted from the users' devices and environment to improve the way in which users are assigned to their serving base stations. Examples of such context information include the devices' screen size and the users' trajectory. The problem is formulated as a matching game with externalities and a new, distributed algorithm is proposed to solve this game. The proposed algorithm is shown to reach a stable matching whose properties are studied. Simulation results show that the proposed context-aware matching approach yields significant performance gains, in terms of the average utility per user, when compared with a classical max-SINR approach.Comment: 11 pages, 11 figures, Journal article in ICST Wireless Spectrum, 201

Matching Theory for Future Wireless Networks: Fundamentals and Applications

The emergence of novel wireless networking paradigms such as small cell and cognitive radio networks has forever transformed the way in which wireless systems are operated. In particular, the need for self-organizing solutions to manage the scarce spectral resources has become a prevalent theme in many emerging wireless systems. In this paper, the first comprehensive tutorial on the use of matching theory, a Nobelprize winning framework, for resource management in wireless networks is developed. To cater for the unique features of emerging wireless networks, a novel, wireless-oriented classification of matching theory is proposed. Then, the key solution concepts and algorithmic implementations of this framework are exposed. Then, the developed concepts are applied in three important wireless networking areas in order to demonstrate the usefulness of this analytical tool. Results show how matching theory can effectively improve the performance of resource allocation in all three applications discussed