607 research outputs found
Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication
Device-to-device (D2D) communication underlaying cellular networks allows
mobile devices such as smartphones and tablets to use the licensed spectrum
allocated to cellular services for direct peer-to-peer transmission. D2D
communication can use either one-hop transmission (i.e., in D2D direct
communication) or multi-hop cluster-based transmission (i.e., in D2D local area
networks). The D2D devices can compete or cooperate with each other to reuse
the radio resources in D2D networks. Therefore, resource allocation and access
for D2D communication can be treated as games. The theories behind these games
provide a variety of mathematical tools to effectively model and analyze the
individual or group behaviors of D2D users. In addition, game models can
provide distributed solutions to the resource allocation problems for D2D
communication. The aim of this article is to demonstrate the applications of
game-theoretic models to study the radio resource allocation issues in D2D
communication. The article also outlines several key open research directions.Comment: Accepted. IEEE Wireless Comms Mag. 201
Coalitional Games with Overlapping Coalitions for Interference Management in Small Cell Networks
In this paper, we study the problem of cooperative interference management in
an OFDMA two-tier small cell network. In particular, we propose a novel
approach for allowing the small cells to cooperate, so as to optimize their
sum-rate, while cooperatively satisfying their maximum transmit power
constraints. Unlike existing work which assumes that only disjoint groups of
cooperative small cells can emerge, we formulate the small cells' cooperation
problem as a coalition formation game with overlapping coalitions. In this
game, each small cell base station can choose to participate in one or more
cooperative groups (or coalitions) simultaneously, so as to optimize the
tradeoff between the benefits and costs associated with cooperation. We study
the properties of the proposed overlapping coalition formation game and we show
that it exhibits negative externalities due to interference. Then, we propose a
novel decentralized algorithm that allows the small cell base stations to
interact and self-organize into a stable overlapping coalitional structure.
Simulation results show that the proposed algorithm results in a notable
performance advantage in terms of the total system sum-rate, relative to the
noncooperative case and the classical algorithms for coalitional games with
non-overlapping coalitions
Sequentially Distributed Coalition Formation Game for Throughput Maximization in C-RANs
Cloud radio access network (C-RAN) has been proposed as a solution to reducing the huge cost of network upgrade while providing the spectral and energy efficiency needed for the new generation cellular networks. In order to reduce the interference that occur in C-RAN and maximize throughput, this paper proposes a sequentially distributed coalition formation (SDCF) game in which players, in this case the remote radio heads (RRHs), can sequentially join multiple coalitions to maximize their throughput. Contrary to overlapping coalition formation (OCF) game where players contribute fractions of their limited resources to different coalitions, the SDCF game offers better stability by allowing sequential coalition formation depending on the availability of resources and therefore providing a balance between efficient spectrum use and interference management. An algorithm for the proposed model is developed based on the merge-only method. The performance of the proposed algorithm in terms of stability, complexity and convergence to final coalition structure is also investigated. Simulation results show that the proposed SDCF game did not only maximize the throughput in the C-RAN, but it also shows better performances and larger capabilities to manage interference with increasing number of RRHs compared to existing methods
Game Theoretic Approaches to Massive Data Processing in Wireless Networks
Wireless communication networks are becoming highly virtualized with
two-layer hierarchies, in which controllers at the upper layer with tasks to
achieve can ask a large number of agents at the lower layer to help realize
computation, storage, and transmission functions. Through offloading data
processing to the agents, the controllers can accomplish otherwise prohibitive
big data processing. Incentive mechanisms are needed for the agents to perform
the controllers' tasks in order to satisfy the corresponding objectives of
controllers and agents. In this article, a hierarchical game framework with
fast convergence and scalability is proposed to meet the demand for real-time
processing for such situations. Possible future research directions in this
emerging area are also discussed
Sub-channel Assignment, Power Allocation and User Scheduling for Non-Orthogonal Multiple Access Networks
In this paper, we study the resource allocation and user scheduling problem
for a downlink nonorthogonal multiple access network where the base station
allocates spectrum and power resources to a set of users. We aim to jointly
optimize the sub-channel assignment and power allocation to maximize the
weighted total sum-rate while taking into account user fairness. We formulate
the sub-channel allocation problem as equivalent to a many-to-many two-sided
user-subchannel matching game in which the set of users and sub-channels are
considered as two sets of players pursuing their own interests. We then propose
a matching algorithm which converges to a two-side exchange stable matching
after a limited number of iterations. A joint solution is thus provided to
solve the sub-channel assignment and power allocation problems iteratively.
Simulation results show that the proposed algorithm greatly outperforms the
orthogonal multiple access scheme and a previous non-orthogonal multiple access
scheme.Comment: Accepted as a regular paper by IEEE Transactions on Wireless
Communication
A cooperative-based model for smart-sensing tasks in fog computing
OAPA Fog Computing is currently receiving a great deal of focused attention. Fog Computing can be viewed as an extension of cloud computing that services the edges of networks. A cooperative relationship among applications to collect data in a city is a fundamental research topic in Fog Computing (FC). When considering the Green Cloud (GC), people or vehicles with smart-sensor devices can be viewed as users in FC and can forward sensing data to the data center (DC). In a traditional sensing process, rewards are paid according to the distances between the users and the platform, which can be seen as the existing solution. Because users with smart-sensing devices tend to participate in tasks with high rewards, the number of users in suburban regions is smaller, and data collection is sparse and cannot satisfy the demands of the tasks. However, there are many users in urban regions, which makes data collection costly and of low quality. In this paper, a cooperative-based model for smartphone tasks, named a Cooperative-based Model for Smart-Sensing Tasks (CMST), is proposed to promote the quality of data collection in FC networks. In the CMST scheme, we develop an allocation method focused on improving the rewards in suburban regions. The rewards to each user with a smart sensor are distributed according to the region density. Moreover, for each task there is a cooperative relationship among the users; they cooperate with one another to reach the volume of data that the platform requires. Extensive experiments show that our scheme improves the overall data-coverage factor by 14.997% to 31.46%, and the platform cost can be reduced by 35.882
Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory
Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization
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