178 research outputs found
A Comprehensive Survey of Potential Game Approaches to Wireless Networks
Potential games form a class of non-cooperative games where unilateral
improvement dynamics are guaranteed to converge in many practical cases. The
potential game approach has been applied to a wide range of wireless network
problems, particularly to a variety of channel assignment problems. In this
paper, the properties of potential games are introduced, and games in wireless
networks that have been proven to be potential games are comprehensively
discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on
Communications, vol. E98-B, no. 9, Sept. 201
Spectrum Leasing as an Incentive towards Uplink Macrocell and Femtocell Cooperation
The concept of femtocell access points underlaying existing communication
infrastructure has recently emerged as a key technology that can significantly
improve the coverage and performance of next-generation wireless networks. In
this paper, we propose a framework for macrocell-femtocell cooperation under a
closed access policy, in which a femtocell user may act as a relay for
macrocell users. In return, each cooperative macrocell user grants the
femtocell user a fraction of its superframe. We formulate a coalitional game
with macrocell and femtocell users being the players, which can take individual
and distributed decisions on whether to cooperate or not, while maximizing a
utility function that captures the cooperative gains, in terms of throughput
and delay.We show that the network can selforganize into a partition composed
of disjoint coalitions which constitutes the recursive core of the game
representing a key solution concept for coalition formation games in partition
form. Simulation results show that the proposed coalition formation algorithm
yields significant gains in terms of average rate per macrocell user, reaching
up to 239%, relative to the non-cooperative case. Moreover, the proposed
approach shows an improvement in terms of femtocell users' rate of up to 21%
when compared to the traditional closed access policy.Comment: 29 pages, 11 figures, accepted at the IEEE JSAC on Femtocell Network
Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining
The deployment of underlay small base stations (SBSs) is expected to
significantly boost the spectrum efficiency and the coverage of next-generation
cellular networks. However, the coexistence of SBSs underlaid to an existing
macro-cellular network faces important challenges, notably in terms of spectrum
sharing and interference management. In this paper, we propose a novel
game-theoretic model that enables the SBSs to optimize their transmission rates
by making decisions on the resource occupation jointly in the frequency and
spatial domains. This procedure, known as interference draining, is performed
among cooperative SBSs and allows to drastically reduce the interference
experienced by both macro- and small cell users. At the macrocell side, we
consider a modified water-filling policy for the power allocation that allows
each macrocell user (MUE) to focus the transmissions on the degrees of freedom
over which the MUE experiences the best channel and interference conditions.
This approach not only represents an effective way to decrease the received
interference at the MUEs but also grants the SBSs tier additional transmission
opportunities and allows for a more agile interference management. Simulation
results show that the proposed approach yields significant gains at both
macrocell and small cell tiers, in terms of average achievable rate per user,
reaching up to 37%, relative to the non-cooperative case, for a network with
150 MUEs and 200 SBSs
Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach
This paper investigates the price-based resource allocation strategies for
the uplink transmission of a spectrum-sharing femtocell network, in which a
central macrocell is underlaid with distributed femtocells, all operating over
the same frequency band as the macrocell. Assuming that the macrocell base
station (MBS) protects itself by pricing the interference from the femtocell
users, a Stackelberg game is formulated to study the joint utility maximization
of the macrocell and the femtocells subject to a maximum tolerable interference
power constraint at the MBS. Especially, two practical femtocell channel
models: sparsely deployed scenario for rural areas and densely deployed
scenario for urban areas, are investigated. For each scenario, two pricing
schemes: uniform pricing and non-uniform pricing, are proposed. Then, the
Stackelberg equilibriums for these proposed games are studied, and an effective
distributed interference price bargaining algorithm with guaranteed convergence
is proposed for the uniform-pricing case. Finally, numerical examples are
presented to verify the proposed studies. It is shown that the proposed
algorithms are effective in resource allocation and macrocell protection
requiring minimal network overhead for spectrum-sharing-based two-tier
femtocell networks.Comment: 27 pages, 7 figures, Submitted to JSA
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
Distributed resource allocation for inter cell interference mitigation in irregular geometry multicell networks
Extensive increase in mobile broadband applications and proliferation of smart phones and gadgets require higher data rates of wireless cellular networks. However, limited frequency spectrum has led to aggressive frequency reuse to improve network capacity at the expense of increased Inter Cell Interference (ICI). Fractional Frequency Reuse (FFR) has been acknowledged as an effective ICI mitigation scheme but in irregular geometric multicellular network, ICI mitigation poses a very challenging issue. The thesis developed a decentralized ICI mitigation scheme to improve both spectral and energy efficiency in irregular geometric multicellular networks. ICI mitigation was realized through Distributed Resource Allocation (DRA) deployed at the cell level and region level of an irregular geometric cell. The irregular geometric cell consists of a minimum of four regions comprising three sectors and a central region. DRA at the cell level is defined as Multi Sector DRA (MSDRA), and at the region level is defined as Distributed Channel Selection and Power Allocation (DCSPA). MSDRA allocates discrete power to every region in a cell based on Game Theory and Regret Learning Process with correlated equilibrium as the optimum decision level. The DCSPA allocates power to every channel in a region based on non-coalesce liquid droplet phenomena by selecting optimum channels in a region and reserving appropriate power for the selected channels. The performance was evaluated through simulation in terms of data rate, spectral efficiency and energy efficiency. The results showed that MSDRA significantly improved cell data rate by 58.64% and 37.92% in comparision to Generalized FFR and Fractional Frequency Reuse-3 (FFR-3) schemes, respectively. The performance of MSDRA at the cell level showed that its spectral and energy efficiency improved 32% and 22%, respectively in comparison to FFR-3. When the number of sectors increased from three to four, data rate was improved by 30.26% and for three to six sectors, it was improved by 56.32%. The DCSPA further improved data rate by 41.07% when compared with Geometric Water Filling, and 86.46% in comparison to Asynchronous Iterative Water Filling. The DCSPA enhanced data rate achieved in MSDRA by 15.6%. Overall, DRA has shown to have significant improvement in data rate by 53.6%, and spectral efficiency by 38.10% as compared to FFR-3. As a conclusion, the DRA scheme is a potential candidate for Long Term Evaluation – Advanced, Fifth Generation networks and can be deployed in future heterogeneous irregular geometric multicellular Orthogonal Frequency Division Multiple Access networks
Hierarchical Resource Allocation Framework for Hyper-Dense Small Cell Networks
This paper considers joint power control and subchannel allocation for co-tier interference
mitigation in extremely dense small cell networks, which is formulated as a combinatorial optimization problem. Since it is intractable to obtain the globally optimum assignment policy for existing techniques due to the huge computation and communication overheads in ultra-dense scenario, in this paper, we propose a hierarchical resource allocation framework to achieve a desirable solution. Speci cally, the solution is obtained by dividing the original optimization problem into four stages in partially distributed manner. First, we propose a divide-and-conquer strategy by invoking clustering technique to decompose
the dense network into smaller disjoint clusters. Then, within each cluster, one of the small cell access points is elected as a cluster head to carry out intra-cluster subchannel allocation with a low-complexity algorithm. To tackle the issue of inter-cluster interference, we further develop a distributed learning-base coordination mechanism. Moreover, a local power adjustment scheme is also presented to improve the system performance. Numerical results verify the ef ciency of the proposed hierarchical scheme, and demonstrate that our solution outperforms the state-of-the-art methods, especially for hyper-dense networks
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