Abstract

The surging mobile traffic poses serious challenges for mobile operators and the advancement of information and communication technologies (ICT). The cost and energy consumption cannot support affordable mobile services and sustainable growth. As a new architecture, cloud-based radio access network (C-RAN) is proposed to confront these challenges. C-RAN is a deployment paradigm that seeks to isolate baseband unit (BBU) from its remote radio unit (RRU) in base station (BS), consolidating the BBUs into a common place (i.e. BBU pool). In the BBU pool, the computing resources provided by the BBUs can be dynamically assigned to RRUs on demand by the BBU controller. Thus, with the fluctuation of data traffic from RRUs, a part of BBUs can be dynamically turned on or off. As a result, the energy consumption of the BBU pool can be reduced correspondingly. In this paper, we design a Markov chain-based calculation model to formulate the energy-saving operation of the BBU pool with an active/sleep mode under dynamic RRU traffic load. On this basis, we propose two different BBU state transition strategies for the BBU pool, i.e., “Cautious ON, Bold OFF (CO-BF)” strategy and “Bold ON, Cautious OFF (BO-CF)” strategy. We formulate the key performance indicators in terms of the energy saving efficiency (ESE), the consequent packet queuing delay (PQD) and the normalized tradeoff cost as well. In extensive simulations, we investigate the effect of these key parameter indicators on the system performances of the BBU pool. Achieving the minimum normalized cost, an optimal operating strategy for the BBU pool can be determined by adjusting the parameter values of the ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> ). The simulation results show when RRU traffic load is light (e.g., <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda =0.1$ </tex-math></inline-formula> ), the proposed BO-CF strategy can lead to the minimum normalized cost, which corresponds to ESE of up to 75.4% and PQD of 0.0097ms. For heavier load (e.g., <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda =0.4$ </tex-math></inline-formula> ), the minimum normalized cost can be obtained along with ESE of up to 74.1% and PQD of 0.1241ms, when the CO-BF strategy is adopted. Hence, we observe that the BO-CF strategy is slightly better than the CO-BF for the light traffic load of the BBU pool, while the CO-BF strategy would be more suitable for the BBU pool with the heavier traffic load. It proves the efficacy of our proposed Markov chain-based calculation model to pursuit an optimal operating strategy for the delay-aware and energy-efficient BBU pool.

Highlights

  • With the rapid popularization of mobile devices and emerging applicationsThe associate editor coordinating the review of this manuscript and approving it for publication was Hao Shen .like high-definition video streaming, there is an increasing need for high-capacity mobile networks

  • We identify the main contributions as follows: (1) formulating the state transfer model based on the Markov chain for the baseband unit (BBU) pool with a sleep mode under dynamic remote radio unit (RRU) traffic load; (2) proposing two energysaving operation strategies for the BBU pool (i.e. ‘‘Cautious ON, Bold OFF (CO-BF)’’ strategy and ‘‘Bold ON, Cautious OFF (BO-CF)’’ strategy); (3) formulating the key performance indicators of the BBU pool in terms of energy saving efficiency, packet queuing delay caused by state transition and normalized tradeoff cost; (4) seeking and evaluating the optimal BBU pool operating strategy that achieves the minimum cost with the given reference goals of the energy saving efficiency and the packet queuing delay (Dg)

  • Based on the calculation model, two energy-saving operation strategies for the BBU pool are proposed by formulating a sleep mode adopted in the BBU pool

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Summary

INTRODUCTION

With the rapid popularization of mobile devices (e.g., smartphones and Internet of things, IoT) and emerging applications. It is urgently desired to develop delay-aware energy-saving operating strategies for the BBU pool to achieve dynamic self-optimization under the dynamic RRU traffic load. To develop such operating strategies, a BBU pool operation model needs to be built. We identify the main contributions as follows: (1) formulating the state transfer model based on the Markov chain for the BBU pool with a sleep mode under dynamic RRU traffic load; (2) proposing two energysaving operation strategies for the BBU pool

RELATED WORKS
STEADY STATE PROBABILITY OF STATE SPACE FOR BBU POOL
FORMULATION OF PERFORMANCE ANALYSIS FOR BBU POOL
FORMULATIONS OF THE PERFORMANCE INDEXES
TRADE-OFF FOR ABOVE PERFORMANCE INDEXES
PERFORMANCE EVALUATION
Findings
CONCLUSION
Full Text
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