A docitive Q‐learning approach towards joint resource allocation and power control in self‐organised femtocell networks

Shahid, Adnan; Aslam, Saleem; Kim, Hyung Seok; Lee, Kyung-Geun

doi:10.1002/ett.2800

Cited by 25 publications

(7 citation statements)

References 25 publications

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“…The related work is divided into three parts: different approaches for the self-organized resource management [6][7][8][9][10], the game-theoretic approaches for resource management [11][12][13], and the energy-efficient resource management for two-tier femtocell networks [14,15]. The authors in [6] propose a joint resource and power allocation in self-organized femtocell networks by exploiting a potential game.…”

Section: Related Workmentioning

confidence: 99%

“…However, the assumption of their study is that the information is thoroughly exchanged among the SBSs for performance improvement which is not practical in the real environment. The authors in [9] employ a novel docitive Q-learning for self-organized resource allocation in femtocell networks. However, it takes time to learn the learning mechanism for the optimal strategies, which makes it unsuitable for the real cases.…”

Section: Related Workmentioning

confidence: 99%

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Energy-efficient downlink resource management in self-organized OFDMA-based two-tier femtocell networks

Shahid

Aslam

Kim

et al. 2015

EURASIP J. Adv. Signal Process.

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Femtocell is a novel technology that is used for escalating indoor coverage as well as the capacity of traditional cellular networks. However, interference is the limiting factor for performance improvement due to co-channel deployment between macrocells and femtocells. The traditional network planning is not feasible because of the random deployment of femtocells. Therefore, self-organization approaches are the key to having successful deployment of femtocells. This study presents the joint resource block (RB) and power allocation task for the two-tier femtocell network in a self-organizing manner, with the concern to minimizing the impact of interference and maximizing the energy efficiency.In this study, we analyze the performance of the system in terms of the energy efficiency, which is composed of both the transmission and circuit power. Most of the previous studies investigate the performance regarding the throughput requirement of the two-tier femtocell network while the energy efficiency aspect is largely ignored. Here, the joint allocation task is modeled as a non-cooperative game which is demonstrated to exhibit pure and unique Nash equilibrium. In order to reduce the complexity of the proposed non-cooperative game, the joint RB and power allocation task is divided into two subproblems: an RB allocation and a particle swarm optimization-based power allocation. The analysis of the proposed game is carried out in terms of not only energy efficiency but also throughput. With practical 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) parameters, the simulation results illustrate the superior performance of the proposed game as compared to the traditional methods. Also, the comparison is carried out with the joint allocation scheme which only considers the throughput as the objective function. The results illustrate that significant performance improvement is achieved in terms of energy efficiency with slight loss in the throughput. The analysis in regard to energy efficiency and throughput of the two-tier femtocell network is carried out in terms of the performance metrics, which include convergence, impact of varying RBs, impact of femtocell density, and the fairness index.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Energy-efficient downlink resource management in self-organized OFDMA-based two-tier femtocell networks

Shahid

Aslam

Kim

et al. 2015

EURASIP J. Adv. Signal Process.

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“…Various resource allocation methods have been proposed in the literature that can mitigate inter-cell and intra-cell interference and, consequently, can improve the system performance [17][18][19][20][21][22][23]. The authors in [17] propose a conjunction of dual polarization and time domain resource allocation technique.…”

Section: Related Workmentioning

confidence: 99%

“…The authors in [21] propose a heuristic approach for resource management in femtocell networks. A docitive learning mechanism for resource allocation and power control is presented in [22], where the femtocell environment is considered. However, the concept of CA is not taken into account which is the state of the art technology for escalating the system performance.…”

Section: Related Workmentioning

confidence: 99%

A self-organized metaheuristic approach towards inter-cell interference management for LTE-Advanced

Shahid

Aslam

Sohaib

et al. 2014

J Wireless Com Network

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In order to meet the high throughput demand set by international mobile telecommunication union, carrier aggregation is exploited for expanding the bandwidth of up to 100 MHz in Long Term Evolution-Advanced (LTE-A). For achieving the aforementioned bandwidth, a maximum of five component carriers (CCs) can be aggregated as per Release 10 LTE-A. Improper CC selection and scheduling will result in hazardous throughput, fairness, and interference problems. Therefore, a proper CC selection and scheduling algorithm is most important for the overall performance of the network. On the other hand, due to an increased information exchange, centralized network planning is not a suitable choice here. In this study, we are employing a self-organized particle swarm optimization (PSO)-based joint component carrier selection and scheduling (JCCS) algorithm for the downlink. More precisely, the concern of the proposed algorithm is the autonomous distribution of resource blocks (RBs) from the pool of CCs by the base station, with the concern of minimizing the impact of inter-cell interference. Our proposed PSO-based JCCS algorithm results in the maximization of the min-max throughput by managing the inter-cell interference in an appropriate manner. Moreover, the proposed algorithm is compared with the traditional CC selection and scheduling algorithms, i.e., random, round robin, and proportional fair. The comparison is carried out in terms of throughput and fairness, and the calculated percentage gain in the end elaborates the performance improvement by exploiting PSO-based JCCS.

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“…However, in the previous literature, the spectrum allocation and power control are not jointly considered in a distributed fashion. In [4, 5], the authors adopt a novel Q‐learning and potential game for the SCBSs, respectively, to jointly consider the power control and channel allocation spectrum. However, the motivation for the MBS to share the wireless resource is weak.…”

Section: Introductionmentioning

confidence: 99%

Interference pricing in 5G ultra‐dense small cell networks: a Stackelberg game approach

Wang

et al. 2016

IET Communications

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A docitive Q‐learning approach towards joint resource allocation and power control in self‐organised femtocell networks

Cited by 25 publications

References 25 publications

Energy-efficient downlink resource management in self-organized OFDMA-based two-tier femtocell networks

Energy-efficient downlink resource management in self-organized OFDMA-based two-tier femtocell networks

A self-organized metaheuristic approach towards inter-cell interference management for LTE-Advanced

Interference pricing in 5G ultra‐dense small cell networks: a Stackelberg game approach

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