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Stochastic Asymmetric Blotto Game Approach for Wireless Resource Allocation Strategies

Research output: Contribution to journalJournal article

Published

Standard

Stochastic Asymmetric Blotto Game Approach for Wireless Resource Allocation Strategies. / Chien, S. F.; Zarakovitis, C. C.; Ni, Q.; Xiao, Pei.

In: IEEE Transactions on Wireless Communications, Vol. 18, No. 12, 01.12.2019, p. 5511 - 5528.

Research output: Contribution to journalJournal article

Harvard

Chien, SF, Zarakovitis, CC, Ni, Q & Xiao, P 2019, 'Stochastic Asymmetric Blotto Game Approach for Wireless Resource Allocation Strategies', IEEE Transactions on Wireless Communications, vol. 18, no. 12, pp. 5511 - 5528. https://doi.org/10.1109/TWC.2019.2936853

APA

Vancouver

Author

Chien, S. F. ; Zarakovitis, C. C. ; Ni, Q. ; Xiao, Pei. / Stochastic Asymmetric Blotto Game Approach for Wireless Resource Allocation Strategies. In: IEEE Transactions on Wireless Communications. 2019 ; Vol. 18, No. 12. pp. 5511 - 5528.

Bibtex

@article{c6fa70d267844f659524d1bad8bd7663,
title = "Stochastic Asymmetric Blotto Game Approach for Wireless Resource Allocation Strategies",
abstract = "The development of modellings and analytical tools to structurise and study the allocation of resources through noble user competitions become essential, especially considering the increased degree of heterogeneity in application and service demands that will be cornerstone in future communication systems. Stochastic asymmetric Blotto games appear promising to modelling such problems, and devising their Nash equilibrium (NE) strategies by anticipating the potential outcomes of user competitions. In this regard, this paper approaches the generic energy efficiency problem with a new stochastic asymmetric Blotto game paradigm to enable the derivation of joint optimal bandwidth and transmit power allocations by setting multiple users to compete in multiple auction-like contests for their individual resource demands. The proposed modelling innovates by abstracting the notion of fairness from centrally-imposed to distributed-competitive, where each user{\textquoteright}s pay-off probability is expressed as quantitative bidding metric, so as, all users{\textquoteright} actions can be interdependent, i.e., each user attains its utility given the allocations of other users, which eliminates the chance of low-valued carriers not being claimed by any user, and, in principle, enables the full utilisation of wireless resources. We also contribute by resolving the allocation problem with low complexity using new mathematical techniques based on Charnes-Cooper transformation, which eliminate the additional coefficients and multipliers that typically appear during optimisation analysis, and derive the joint optimal strategy as a set of linear single-variable functions for each user. We prove that our strategy converges towards a unique, monotonous and scalable NE, and examine its optimality, positivity and feasibility properties in detail. Simulation comparisons with relevant studies confirm the superiority of our approach in terms of higher energy efficiency performance, fairness index and quality-of-service provision.",
keywords = "Charnes-Cooper transformation, competitive game, energy efficiency, green communications, Nash equilibrium, radio resource scheduling, stochastic asymmetric Blotto games",
author = "Chien, {S. F.} and Zarakovitis, {C. C.} and Q. Ni and Pei Xiao",
note = "{\textcopyright}2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.",
year = "2019",
month = dec
day = "1",
doi = "10.1109/TWC.2019.2936853",
language = "English",
volume = "18",
pages = "5511 -- 5528",
journal = "IEEE Transactions on Wireless Communications",
issn = "1536-1276",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "12",

}

RIS

TY - JOUR

T1 - Stochastic Asymmetric Blotto Game Approach for Wireless Resource Allocation Strategies

AU - Chien, S. F.

AU - Zarakovitis, C. C.

AU - Ni, Q.

AU - Xiao, Pei

N1 - ©2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2019/12/1

Y1 - 2019/12/1

N2 - The development of modellings and analytical tools to structurise and study the allocation of resources through noble user competitions become essential, especially considering the increased degree of heterogeneity in application and service demands that will be cornerstone in future communication systems. Stochastic asymmetric Blotto games appear promising to modelling such problems, and devising their Nash equilibrium (NE) strategies by anticipating the potential outcomes of user competitions. In this regard, this paper approaches the generic energy efficiency problem with a new stochastic asymmetric Blotto game paradigm to enable the derivation of joint optimal bandwidth and transmit power allocations by setting multiple users to compete in multiple auction-like contests for their individual resource demands. The proposed modelling innovates by abstracting the notion of fairness from centrally-imposed to distributed-competitive, where each user’s pay-off probability is expressed as quantitative bidding metric, so as, all users’ actions can be interdependent, i.e., each user attains its utility given the allocations of other users, which eliminates the chance of low-valued carriers not being claimed by any user, and, in principle, enables the full utilisation of wireless resources. We also contribute by resolving the allocation problem with low complexity using new mathematical techniques based on Charnes-Cooper transformation, which eliminate the additional coefficients and multipliers that typically appear during optimisation analysis, and derive the joint optimal strategy as a set of linear single-variable functions for each user. We prove that our strategy converges towards a unique, monotonous and scalable NE, and examine its optimality, positivity and feasibility properties in detail. Simulation comparisons with relevant studies confirm the superiority of our approach in terms of higher energy efficiency performance, fairness index and quality-of-service provision.

AB - The development of modellings and analytical tools to structurise and study the allocation of resources through noble user competitions become essential, especially considering the increased degree of heterogeneity in application and service demands that will be cornerstone in future communication systems. Stochastic asymmetric Blotto games appear promising to modelling such problems, and devising their Nash equilibrium (NE) strategies by anticipating the potential outcomes of user competitions. In this regard, this paper approaches the generic energy efficiency problem with a new stochastic asymmetric Blotto game paradigm to enable the derivation of joint optimal bandwidth and transmit power allocations by setting multiple users to compete in multiple auction-like contests for their individual resource demands. The proposed modelling innovates by abstracting the notion of fairness from centrally-imposed to distributed-competitive, where each user’s pay-off probability is expressed as quantitative bidding metric, so as, all users’ actions can be interdependent, i.e., each user attains its utility given the allocations of other users, which eliminates the chance of low-valued carriers not being claimed by any user, and, in principle, enables the full utilisation of wireless resources. We also contribute by resolving the allocation problem with low complexity using new mathematical techniques based on Charnes-Cooper transformation, which eliminate the additional coefficients and multipliers that typically appear during optimisation analysis, and derive the joint optimal strategy as a set of linear single-variable functions for each user. We prove that our strategy converges towards a unique, monotonous and scalable NE, and examine its optimality, positivity and feasibility properties in detail. Simulation comparisons with relevant studies confirm the superiority of our approach in terms of higher energy efficiency performance, fairness index and quality-of-service provision.

KW - Charnes-Cooper transformation

KW - competitive game

KW - energy efficiency

KW - green communications

KW - Nash equilibrium

KW - radio resource scheduling

KW - stochastic asymmetric Blotto games

U2 - 10.1109/TWC.2019.2936853

DO - 10.1109/TWC.2019.2936853

M3 - Journal article

VL - 18

SP - 5511

EP - 5528

JO - IEEE Transactions on Wireless Communications

JF - IEEE Transactions on Wireless Communications

SN - 1536-1276

IS - 12

ER -