Rights statement: This is the peer reviewed version of the following article: Mudassir, A, Hassan, SA, Pervaiz, H, Akhtar, S, Kamel, H, Tafazolli, R. Game theoretic efficient radio resource allocation in 5G resilient networks: A data driven approach. Trans Emerging Tel Tech. 2019;e3582. https://doi.org/10.1002/ett.3582 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1002/ett.3582 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Game Theoretic Efficient Radio Resource Allocation in 5G Resilient Networks
T2 - A Data Driven Approach
AU - Mudassir, Ahmad
AU - Hassan, Syed Ali
AU - Pervaiz, Haris
AU - Akhtar, Saleem
AU - Kamel, Hesham
AU - Tafazolli, Rahim
N1 - This is the peer reviewed version of the following article: Mudassir, A, Hassan, SA, Pervaiz, H, Akhtar, S, Kamel, H, Tafazolli, R. Game theoretic efficient radio resource allocation in 5G resilient networks: A data driven approach. Trans Emerging Tel Tech. 2019;e3582. https://doi.org/10.1002/ett.3582 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1002/ett.3582 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - In recent years, 5G resilient networks have gained significant attention in the wireless industry. The prime concern of commercial networks is to maximize network capacity to increase their revenue. However, in disaster situations during outages when cell sites are down, instead of capacity, coverage becomes predominant. In this paper, we propose a game theory–based optimal resource allocation scheme, while aiming to maximize the sum rate and coverage probability for the uplink transmissions in disaster situations. The proposed hierarchical game theoretical framework optimizes the uplink performance in multitier heterogeneous network with pico base stations and femto access points overlaid under a macro base station. The test simulations are based on a real‐time data set obtained for a predefined amount of time. The data statistics are then manipulated to create practical disaster situations. The solution for the noncooperative game has been obtained by using pure strategy Nash equilibrium. We perform simulations with different failure rates and the results show that the proposed scheme improves the sum rate and outage probability by significant margin with or without disaster scenario.
AB - In recent years, 5G resilient networks have gained significant attention in the wireless industry. The prime concern of commercial networks is to maximize network capacity to increase their revenue. However, in disaster situations during outages when cell sites are down, instead of capacity, coverage becomes predominant. In this paper, we propose a game theory–based optimal resource allocation scheme, while aiming to maximize the sum rate and coverage probability for the uplink transmissions in disaster situations. The proposed hierarchical game theoretical framework optimizes the uplink performance in multitier heterogeneous network with pico base stations and femto access points overlaid under a macro base station. The test simulations are based on a real‐time data set obtained for a predefined amount of time. The data statistics are then manipulated to create practical disaster situations. The solution for the noncooperative game has been obtained by using pure strategy Nash equilibrium. We perform simulations with different failure rates and the results show that the proposed scheme improves the sum rate and outage probability by significant margin with or without disaster scenario.
U2 - 10.1002/ett.3582
DO - 10.1002/ett.3582
M3 - Journal article
VL - 30
JO - Transactions on Emerging Telecommunications Technologies
JF - Transactions on Emerging Telecommunications Technologies
SN - 2161-3915
IS - 8
M1 - e3582
ER -