Abstract

With the rapid proliferation of wireless traffic and the surge of various data-intensive applications, the energy consumption of wireless networks has tremendously increased in the last decade, which not only leads to more CO2 emission, but also results in higher operating expenditure. Consequently, energy efficiency (EE) has been regarded as an essential design criterion for future wireless networks. This paper investigates the problem of EE maximisation for a cooperative heterogeneous network (HetNet) powered by hybrid energy sources via joint base station (BS) switching (BS-Sw) and power allocation using combinatorial optimisation. The cooperation among the BSs is achieved through a coordinated multi-point (CoMP) technique. Next, to overcome the complexity of combinatorial optimisation, Lagrange dual decomposition is applied to solve the power allocation problem and a sub-optimal distance-based BS-Sw scheme is proposed. The main advantage of the distance-based BS-Sw is that the algorithm is tuning-free as it exploits two dynamic thresholds, which can automatically adapt to various user distributions and network deployment scenarios. The optimal binomial and random BS-Sw schemes are also studied to serve as benchmarks. Further, to solve the non-fractional programming component of the EE maximisation problem, a low-complexity and fast converging Dinkelbach’s method is proposed. Extensive simulations under various scenarios reveal that in terms of EE, the proposed joint distance-based BS-Sw and power allocation technique applied to the cooperative and harvesting BSs performs around 15–20% better than the non-cooperative and non-harvesting BSs and can achieve near-optimal performance compared to the optimal binomial method.

Highlights

  • Massive growth in the number of mobile users and mobile user equipment (UE) has sown the seeds of data hunger and severely high traffic congestion, especially in cellular networks

  • The proposed binomial base station (BS)-Sw method was simulated for three different scenarios, i.e., (1) coordinated multi-point (CoMP)-enabled harvesting; (2) CoMP-enabled non-harvesting; (3) non-CoMP harvesting scenarios (the legends of the graphs are abbreviated as follows: Binomial base station switching (BS-Sw) technique for CoMP-enabled harvesting system (Bin-CoMP-H), distance-based BS-Sw technique for CoMP-enabled harvesting system (Dist-CoMP-H), random BS-Sw technique for CoMP-enabled harvesting system (Rand-CoMP-H), Binomial BS-Sw technique for Non-CoMP harvesting system (Bin-Non-CoMP-H) and Binomial BS-Sw technique for CoMP-enabled non-harvesting system (Bin-CoMP-NoH))

  • For a CoMP-enabled system, the macrocell UEs are served solely by the macro BS (MBS) while small cell UEs are served by both MBS and their respective SBS

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Summary

Introduction

Massive growth in the number of mobile users and mobile user equipment (UE) has sown the seeds of data hunger and severely high traffic congestion, especially in cellular networks. To reduce wastage of radio resources and save energy, certain small-cell BSs with low spectrum utilisation in a HetNet can be switched off; it is noteworthy that it does not mean there are no mobile users at all during off-peak hours. This can be explained by comparing the available energy per BS and its user strength and /or distribution, which rarely compensates one another Several technologies, such as power lines and smart grids, are being studied for energy cooperation among the connected BSs. The research conducted in [13] discusses safe and reliable architectures and current implementations of the smart grid; it is clear that utilising this technology in this work has the potential for significant and reliable contribution.

Related Work and Contributions
System Model and Problem Formulation
Proposed Technique
Combinatorial Optimisation Algorithm
3: Set the b j status of each base station using one of the BS-Sw methods:
Dual Decomposition
Simulation Results and Analysis
Simulation Setting
Simulation Results and Discussions
Final Remarks
Full Text
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