Coalition‐based sleep mode and power allocation for energy efficiency in dense small cell networks

Ultra-dense small cell (SC) deployment in future 5G network makes the architecture of the network as heterogeneous networks (HetNets). This is a good solution to boost the capacity of the network and extend its coverage. However, the dense SCs deployment has brought new challenges to the network including interference, frequent unnecessary handovers and handover failures. Therefore, user equipment (UE) will suffer from a degraded quality of service (QoS). In this paper, we propose a Grey Rational Analysis based handover method (GRA-HO) in dense SCs HetNet. The proposed method combines the Analytical Hierarchy Process (AHP) technique to obtain the weight of the handover metrics and the GRA method to rank the available cells for the best handover target. The performance of the proposed method is evaluated and compared with the traditional Multiple Attribute Decision Making (MADM) method including Simple Additive Weighting (SAW) and VIKOR methods. Results show that the GRA-HO method has outperformed the existing methods in terms of reducing the number of frequent handovers and link failures, in addition to enhancing the energy efficiency.

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“…where A 2 is the current location of the UE. Finally, we substitute (16) and (17) in (13) to get the time of stay as…”

Section: Predicted Tos Criterionmentioning

confidence: 99%

GRA‐based handover for dense small cells heterogeneous networks

2019

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“…The resource allocation problem is formulated as an optimization problem whose solution results in several advantageous features such as interference avoidance and quality of service (QoS) demand satisfaction. In the work of Wu et al, 6 the authors proposed a power allocation scheme energy efficiency of small dense cell networks. The problem is formulated as a coalitional game; the solution is shown to result in energy efficiency performance gains.…”

Section: Related Workmentioning

confidence: 99%

“…[4][5][6][7][8] Cognitive radio (CR) 9 is a key technology that allows opportunistic access to the limited spectrum. Therefore, achieving efficient spectrum utilization is one of the most important tasks in designing wireless systems.…”

Section: Introductionmentioning

confidence: 99%

“…Due it its importance, extensive research work has been dedicated to devise efficient resource allocation schemes. [4][5][6][7][8] Cognitive radio (CR) 9 is a key technology that allows opportunistic access to the limited spectrum. Unlicensed users (referred to as secondary users (SUs)) perform spectrum sensing to discover transmission opportunities over frequency bands assigned to licensed users (primary users (PUs)) who are currently inactive.…”

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confidence: 99%

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A rate‐maximizing spectrum sharing algorithm for cognitive radio networks with generic resource constraints

Halloush

Almalkawi

et al. 2019

Trans Emerging Tel Tech

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Algorithms for spectrum sharing over resource‐limited cognitive radio networks are often designed to solve specific problems. This means that a certain algorithm deals specifically with a certain limited resource, and is not suitable for other resources. This limitation violates the software‐defined networking philosophy, where a scheme has to be reprogrammable to cope with different limited resources that can dynamically arise depending on network conditions. In this work, we investigate the problem of spectrum sharing in resource‐limited cognitive radio networks. Specifically, we introduce a novel spectrum sharing algorithm that is compatible with software‐defined networks, in the sense that it can be reprogrammed to support multiple constraints on resources of different types. A main feature of the proposed scheme is that computations could be distributed across multiple processing units to reduce computational complexity on each unit. In addition, the proposed algorithm is equipped with a fairness scheme. Simulation results demonstrate the efficacy of the proposed scheme.

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“…Hence, following to the traffic condition, the authors [11] designed the bandwidth division among wireless backhaul and radio access links and proved two-tier MIMO heterogeneous network is more efficient when compared to single tier system in terms of energy. To enhance EE in dense small cell networks, CSMPA method is proposed [12] to control the system performance and support the target rates of users. Hence, the number of outage users is very less and satisfied the requirements of the user.…”

Section: Improving Energy Efficiency and Minimizing Backhaul Traffic mentioning

confidence: 99%

Improving Energy Efficiency and Minimizing Backhaul Traffic in LTE-A Network with Cooperation and DTX Mechanism

2019

IJRTE

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The promising approach to enhance energy efficiency (EE) in LTE-A network is to switch underutilized evolved node B (eNB) to sleep mode, but it increases the transmission power to guarantee the coverage under the remaining active eNBs. The increase in transmission power can be reduced by coordinated multi-point (CoMP) technique through eNB cooperation, but this technique consumes extra power due to backhaul traffic and signal processing. This problem can be solved by the proposed energy efficient acceleration factor failure rate (EEAFR) algorithm. The algorithm jointly considers the eNB cooperation and DTX mechanism to minimize the backhaul traffic with less failure rate. Also, to enhance energy efficiency, the proposed algorithm efficiently utilizes the cooperation in all traffic load scenarios based on the decision criteria and DTX mechanism. The results are compared with the existing AFEE and Green CoMP with Backhaul Traffic algorithm. In all the traffic loads EEAFR save 59.8% energy and reduces the network outage which depends on the failure rate of the eNB components

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Coalition‐based sleep mode and power allocation for energy efficiency in dense small cell networks

Cited by 16 publications

References 26 publications

GRA‐based handover for dense small cells heterogeneous networks

GRA‐based handover for dense small cells heterogeneous networks

A rate‐maximizing spectrum sharing algorithm for cognitive radio networks with generic resource constraints

Improving Energy Efficiency and Minimizing Backhaul Traffic in LTE-A Network with Cooperation and DTX Mechanism

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