JOURNAL ARTICLE

Supermodular game based energy efficient power allocation in heterogeneous small cell networks

Abstract

Heterogeneous small cell network is a promising technique in the next generation mobile communications. Many works have been studied in small cells, including resource allocation and interference mitigation, but most studies didn't consider the quality-of-service (QoS) and power consumption. This paper focuses on the power allocation based on non-cooperative scheme to mitigate the interference and increase the energy efficiency in small cells. The delay constraint is introduced in small cells to guarantee the QoS. We reconsider the capacity according to Shannon' capacity formula and bring in the concept of effective capacity. We take the total power consumption of the small cells into account and employ energy efficiency metric to formulate the problem of power allocation. The power allocation problem is modeled as non-cooperative supermodular game, and it is shown to converge to Nash equilibrium, and then it is transformed into a convex optimization problem, which is solved by the multi-agent Q-learning algorithm based on conjecture. The effectiveness of the proposed supermodular game based power allocation is verified by the simulations.

Keywords:
Computer science Mathematical optimization Quality of service Resource allocation Efficient energy use Nash equilibrium Small cell Energy consumption Optimization problem Game theory Power (physics) Resource management (computing) Convex optimization Constraint (computer-aided design) Cellular network Computer network Regular polygon Mathematics Mathematical economics Engineering

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4
Cited By
0.53
FWCI (Field Weighted Citation Impact)
19
Refs
0.70
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Cooperative Communication and Network Coding
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced Wireless Network Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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