Cell Selection in Wireless Two-Tier Networks: A Context-Aware Matching Game (original) (raw)
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Matching with Externalities for Context-Aware Cell Association in Wireless Small Cell Networks
In this paper, we propose a novel user-cell association approach for wireless small cell networks that exploits previously unexplored context information extracted from users' devices, i.e., user equipments (UEs). Beyond characterizing precise quality of service (QoS) requirements that accurately reflect the UEs' application usage, our proposed cell association approach accounts for the devices' hardware type (e.g., smartphone, tablet, laptop). This approach has the practical benefit of enabling the small cells to make better informed cell association decisions that handle practical device-specific QoS characteristics. We formulate the problem as a matching game between small cell base stations (SBSs) and UEs. In this game, the SBSs and UEs rank one another based on well-designed utility functions that capture composite QoS requirements, extracted from the context features (i.e., application in use, hardware type). We show that the preferences used by the nodes to rank one another are interdependent and influenced by the existing network-wide matching. Due to this unique feature of the preferences, we show that the proposed game can be classified as a many-to-one matching game with externalities. To solve this game, we propose a distributed algorithm that enables the players (i.e., UEs and SBSs) to self-organize into a stable matching that guarantees the required applications' QoS. Simulation results show that the proposed context-aware cell association scheme yields significant gains, reaching up to 52% improvement compared to baseline context-unaware approaches.
Matching with externalities for context-aware user-cell association in small cell networks
In this paper, we propose a novel user-cell association approach for wireless small cell networks that exploits previously unexplored context information extracted from users' devices, i.e., user equipments (UEs). Beyond characterizing precise quality of service (QoS) requirements that accurately reflect the UEs' application usage, our proposed cell association approach accounts for the devices' hardware type (e.g., smartphone, tablet, laptop). This approach has the practical benefit of enabling the small cells to make better informed cell association decisions that handle practical device-specific QoS characteristics. We formulate the problem as a matching game between small cell base stations (SBSs) and UEs. In this game, the SBSs and UEs rank one another based on well-designed utility functions that capture composite QoS requirements, extracted from the context features (i.e., application in use, hardware type). We show that the preferences used by the nodes to rank one another are interdependent and influenced by the existing network-wide matching. Due to this unique feature of the preferences, we show that the proposed game can be classified as a many-to-one matching game with externalities. To solve this game, we propose a distributed algorithm that enables the players (i.e., UEs and SBSs) to self-organize into a stable matching that guarantees the required applications' QoS. Simulation results show that the proposed context-aware cell association scheme yields significant gains, reaching up to 52% improvement compared to baseline context-unaware approaches.
Device-Aware Cell Association in Heterogeneous Cellular Networks: A Matching Game Approach
IEEE Transactions on Green Communications and Networking, 2018
Heterogeneous cellular networks (HCNs) provide a promising paradigm for supporting different types of devices that have diverse quality of service (QoS) requirements such as Internet of things devices (IoTDs) and human-to-human devices (H2HDs). In this paper, a distributed cell association algorithm is developed to consider the dissimilar association requirements for IoTDs and H2HDs coexisting in HCNs. The device association process is formulated as a multi-objective optimization problem to minimize the uplink (UL) transmit power for IoTDs and maximize the downlink (DL) data rate for H2HDs while considering the various devices' QoS requirements. To solve this problem, an approach dependent on matching theory is proposed to model the interactions between devices and base stations (BSs) in the network. Using this approach, a distributed algorithm is developed to provide the device association solution. The proposed algorithm is then proved to converge to a stable matching. Simulation results validate the effectiveness of the proposed algorithm in improving the UL power performance for IoTDs as well as DL rate performance for H2HDs compared to other association algorithms.
Matching theory for priority-based cell association in the downlink of wireless small cell networks
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014
The deployment of small cells, overlaid on existing cellular infrastructure, is seen as a key feature in next-generation cellular systems. In this paper, the problem of user association in the downlink of small cell networks (SCNs) is considered. The problem is formulated as a many-to-one matching game in which the users and SCBSs rank one another based on utility functions that account for both the achievable performance, in terms of rate and fairness to cell edge users, as captured by newly proposed priorities. To solve this game, a novel distributed algorithm that can reach a stable matching is proposed. Simulation results show that the proposed approach yields an average utility gain of up to 65% compared to a common association algorithm that is based on received signal strength. Compared to the classical deferred acceptance algorithm, the results also show a 40% utility gain and a more fair utility distribution among the users.
Dynamic Clustering and User Association in Wireless Small Cell Networks with Social Considerations
2016
In this paper, a novel social network-aware user association in wireless small cell networks with underlaid device-to-device (D2D) communication is investigated. The proposed approach exploits social strategic relationships between user equipments (UEs) and their physical proximity to optimize the overall network performance. This problem is formulated as a matching game between UEs and their serving nodes (SNs) in which, an SN can be a small cell base station (SCBS) or an important UE with D2D capabilities. The problem is cast as a many-to-one matching game in which UEs and SNs rank one another using preference relations that capture both the wireless aspects (i.e., received signal strength, traffic load, etc.) and users' social ties (e.g., UE proximity and social distance). Due to the combinatorial nature of the network-wide UE-SN matching, the problem is decomposed into a dynamic clustering problem in which SCBSs are grouped into disjoint clusters based on mutual interference...
Base Station Association Game in Multi-cell Wireless Networks
We consider a multi-cell wireless network with a large number of users. Each user selfishly chooses the Base Station (BS) that gives it the best throughput (utility), and each BS allocates its resource by some simple scheduling policy. First we consider two cases: (1) BS allocates the same time to its users; (2) BS allocates the same throughput to its users. It turns out that, combined with users' selfish behavior, case (1) results in a single Nash Equilibrium (NE), which achieves system-wide Proportional Fairness. On the other hand, case (2) results in many possible Nash Equilibria, some of which are very inefficient. Next, we extend (1) to the case where the users have general concave utility functions. It is shown that the if each BS performs intracell optimization, the total utility of all users is maximized at NE. This suggests that under our model, the task of joining the "correct" BS can be left to individual users, leading to a distributed solution.
Context-Aware Small Cell Networks: How Social Metrics Improve Wireless Resource Allocation
In this paper, a novel approach for optimizing and managing resource allocation in wireless small cell networks (SCNs) with device-to-device (D2D) communication is proposed. The proposed approach allows to jointly exploit both the wireless and social context of wireless users for optimizing the overall allocation of resources and improving traffic offload in SCNs. This context-aware resource allocation problem is formulated as a matching game in which user equipments (UEs) and resource blocks (RBs) rank one another, based on utility functions that capture both wireless and social metrics. Due to social interrelations, this game is shown to belong to a class of matching games with peer effects. To solve this game, a novel, selforganizing algorithm is proposed, using which UEs and RBs can interact to decide on their desired allocation. The proposed algorithm is then proven to converge to a two-sided stable matching between UEs and RBs. The properties of the resulting stable outcome ar...
Base Station Association Game in Multi-Cell Wireless Networks (Special Paper
2008
We consider a multi-cell wireless network with a large number of users. Each user selfishly chooses the Base Station (BS) that gives it the best throughput (utility), and each BS allocates its resource by some simple scheduling policy. First we consider two cases: (1) BS allocates the same time to its users; (2) BS allocates the same throughput to its users. It turns out that, combined with users' selfish behavior, case (1) results in a single Nash Equilibrium (NE), which achieves system-wide Proportional Fairness. On the other hand, case (2) results in many possible Nash Equilibria, some of which are very inefficient. Next, we extend (1) to the case where the users have general concave utility functions. It is shown that the if each BS performs intracell optimization, the total utility of all users is maximized at NE. This suggests that under our model, the task of joining the "correct" BS can be left to individual users, leading to a distributed solution.
2014 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2014
In this paper, we propose a novel social network aware approach for user association in wireless small cell networks. The proposed approach exploits social relationships between user equipments (UEs) and their physical proximity to optimize the network throughput. We formulate the problem as a matching game between UEs and their serving nodes (SNs). In our proposed game, the serving node can be a small cell base station (SCBS) or an important node with device-todevice capabilities. In this game, the SCBSs and UEs maximize their respective utility functions capturing both the spatial and social structures of the network. We show that the proposed game belongs to the class of matching games with externalities. Subsequently, we propose a distributed algorithm using which the SCBSs and UEs interact and reach a stable matching. We show the convergence of the proposed algorithm and study the properties of the resulting matching. Simulation results show that the proposed socially-aware user association approach can efficiently offload traffic while yielding a significant gain reaching up to 63% in terms of data rates as compared to the classical (social-unaware) approach.
Context-aware wireless small cell networks: How to exploit user information for resource allocation
2015 IEEE International Conference on Communications (ICC), 2015
In this paper, a novel context-aware approach for resource allocation in two-tier wireless small cell networks (SCNs) is proposed. In particular, the SCN's users are divided into two types: frequent users, who are regular users of certain small cells, and occasional users, who are one-time or infrequent users of a particular small cell. Given such context information, each small cell base station (SCBS) aims to maximize the overall performance provided to its frequent users, while ensuring that occasional users are also well serviced. We formulate the problem as a noncooperative game in which the SCBSs are the players. The strategy of each SCBS is to choose a proper power allocation so as to optimize a utility function that captures the tradeoff between the users' quality-of-service gains and the costs in terms of resource expenditures. We provide a sufficient condition for the existence and uniqueness of a pure strategy Nash equilibrium for the game, and we show that this condition is independent of the number of users in the network. Simulation results show that the proposed context-aware resource allocation game yields significant performance gains, in terms of the average utility per SCBS, compared to conventional techniques such as proportional fair allocation and sum-rate maximization.